A weight-adjusted Peto’s test when cause of death is not assigned

A new statistical testing approach using a weighted logrank statistic is developed for rodent tumorigenicity assays that have a single terminal sacrifice but not cause-of-death data. Instead of using cause-of-death assignment by pathologists, the number of fatal tumors is estimated by a constrained nonparametric maximum likelihood estimation method. For data lacking cause-of-death information, the Peto test is modified with estimated numbers of fatal tumors and a Fleming–Harrington-type weight, which is based on an estimated tumor survival function. A bootstrap resampling method is used to estimate the weight function. The proposed testing method with the weight adjustment appears to improve the performance in various situations of single-sacrifice animal experiments. A Monte Carlo simulation study for the proposed test is conducted to assess size and power of the test. This testing approach is illustrated using a real data set.     

Selective adsorption of phenanthrene dissolved in surfactant solution using activated carbon

Selective adsorption of a hazardous hydrophobic organic compound (HOC) by activated carbon as a means of recovering surfactants after a soil washing process was investigated. As a model system, phenanthrene was selected as a representative HOC and Triton X-100 as a nonionic surfactant. Three activated carbons that differed in size (Darco 20–40 (D20), 12–20 (D12) and 4–12 (D4) mesh sizes) were used in adsorption experiments. Adsorption of surfactant onto activated carbon showed a constant maximum above the critical micelle concentration, which were 0.30, 0.23, 0.15 g g⁻¹ for D20, D12, and D4, respectively. Selectivity for phenanthrene to Triton X-100 was much higher than 1 over a wide range of activated carbon doses (0–6 g l⁻¹) and initial phenanthrene concentrations (10–110 mg l⁻¹). Selectivity generally increased with decreasing particle size, increasing activated carbon dose, and decreasing initial concentration of phenanthrene. The highest selectivity was 74.9, 57.3, and 38.3 for D20, D12, and D4, respectively, at the initial conditions of 10 mg l⁻¹ phenanthrene, 5 g l⁻¹ Triton X-100 and 1 g l⁻¹ activated carbon. In the case of D20 at the same conditions, 86.5% of the initial phenanthrene was removed by sorption and 93.6% of the initial Triton X-100 remained in the solution following the selective adsorption process. The results suggest that the selective adsorption by activated carbon is a good alternative for surfactant recovery in a soil washing process.     

Bio-reduction of N-nitrosodimethylamine (NDMA) using a hydrogen-based membrane biofilm reactor

N-Nitrosodimethylamine (NDMA) is a disinfection by-product shown to be carcinogenic, mutagenic, and teratogenic. A feasible detoxification pathway for NDMA is a three-step bio-reduction that leads to ammonia and dimethylamine. This study examines the bio-reduction of NDMA in a H2-based membrane biofilm reactor (MBfR) that also is active in nitrate and sulfate reductions. In particular, the study investigates the effects of H2 availability and the relative loadings of NDMA, nitrate, and sulfate, which potentially are competing electron acceptors. The results demonstrate that NDMA was bio-reduced to a major extent (i.e., at least 96%) in a H2-based MBfR in which the electron-equivalent fluxes from H2 oxidation were dominated by nitrate and sulfate reductions. NDMA reduction kinetics responded to NDMA concentration, H2 pressure, and the presence of competing acceptors. The most important factor controlling NDMA-reduction kinetics was the H2 availability, controlled primarily by the H2 pressure, and secondarily by competition from nitrate reduction.     

Formation of dimethyldithioarsinic acid in a simulated landfill leachate in relation to hydrosulfide concentration

Dimethyldithioarsinic acid (DMDTA^V), present in such intense sources as municipal landfill leachate, has drawn a great deal of attention due to its abundant occurrence and different aspect of toxicity. The hydrosulfide (HS⁻) concentration in leachate was studied as a major variable affecting the formation of DMDTA^V. To this end, the HPLC–ICPMS system equipped with the reversed-phase C18 column was used to determine DMDTA^V. Simulated landfill leachates (SLLs) were prepared to cover a mature landfill condition with the addition of sodium sulfate and sulfide at varying concentrations in the presence of dimethylarsinic acid (DMA^V). The concentration of sodium sulfide added in the SLLs generally exhibited a strong positive correlation with the concentration of DMDTA^V. As such, the formation of DMDTA^V in the SLLs is demonstrated to be controlled by the interactive relationship between DMA^V and the HS⁻.

     

Geochemical occurrences of arsenic and fluoride in bedrock groundwater: a case study in Geumsan County, Korea

Bedrock groundwaters in Geumsan County, Korea, were surveyed to investigate the distribution and geochemical behaviors of arsenic and fluoride, mobilized through geogenic processes. The concentrations were enriched up to 113 μg/L for arsenic and 7.54 mg/L for fluoride, and 16% of 150 samples exceeded World Health Organization drinking water guidelines for each element. Simple Ca-HCO(3) groundwater types and positive correlations with pH, Ca, SO(4), and HCO(3) were characteristics of high (>10 μg/L) As groundwaters. The oxidation reaction of sulfide minerals in metasedimentary rocks and locally mineralized zones seems to be ultimately responsible for the existence of arsenic in groundwater. Desorption process under high pH conditions may also control the arsenic mobility in the study area. High (>1.5 mg/L) F groundwaters were found in the Na-HCO(3) type and with greater depth. Fluoride seemed to be enriched by deep groundwater interaction with granitic rocks, and continuous supply to shallow Ca-HCO(3)-type groundwater kept the concentration high. In the study area, drinking water management should include periodic As and F monitoring in groundwater.     

Whole blood is the sample matrix of choice for monitoring systemic triclocarban levels

The antibacterial triclocarban (TCC) concentrates in the cellular fraction of blood. Consequently, plasma levels are at least two-fold lower than the TCC amount present in blood. Utilizing whole blood sampling, a low but significant absorption of TCC from soap during showering is demonstrated for a small group of human subjects.     

Thermoeconomic installation limit of PV/WT hybrid energy systems for Off-grid islands

An ideal off-grid island can become 100% energy-sufficient if one installs renewable energy systems such as solar photovoltaic (PV) and wind turbine (WT) systems. However, the intermittent and uncertain nature of the power supply from renewable energy systems hinders a 100% autonomy level (AL) without an infinite energy storage capacity. The thermoeconomic installation limit (TEIL) of a PV/WT hybrid energy system was studied using hourly weather data and the energy demand profile for off-grid islands. An appropriate battery size for the TEIL was also determined. Given the current installation cost of the hybrid energy system and the battery unit, the AL for a PV/WT hybrid energy system at the TEIL is calculated to be approximately 70%. Above the limit, the size of the energy storage unit and, correspondingly, the total annual cost of the PV/WT hybrid energy system increase sharply.     

Improving land use inference by factorizing mobile phone call activity matrix

Land use is shaped by human activities. Traditional methods of measuring land uses (e.g. surveys and remote sensing techniques) often have difficulties in capturing human activities. The near-ubiquitous coverage of mobile phones opens up a new way to investigate land use through human activities. We propose to analyze land use by characterizing human activity patterns based on the aggregated call volume, and apply non-negative matrix factorization to identify fundamental behavioral classes. Using tower-based call data from Dakar, Senegal, we discover two fundamental land use patterns: commercial/business/industrial (C/B/I) and residential. Then, the land use of the reception area of each cell tower can be inferred based on the weights obtained for each basis vector. To evaluate the proposed approach, the results are compared with two points-of-interest (POI) data sets obtained from OpenStreetMap and Facebook’s Graph API. We have found that a majority of POIs like embassies, offices, and hotels are located in the predicted C/B/I areas; specifically, there is a strong positive correlation between estimated land use weights and the number of related POIs. Furthermore, we have shown analyzing 24-h call pattern matrix can track daily land use changes.     

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.