Diffusion of cations in salt solutions between ice walls

It is important for food, medical and energy engineering to control ice growth during cooling processes. Adding salts and antifreeze protein to water is a promising method for doing this. However, the effects of ions in solution on ice–water interface in narrow spaces have not yet been clarified. Therefore, we carried out molecular dynamics simulations of sodium chloride, potassium chloride and calcium chloride in water between ice walls. It was found that the peaks of the radial distribution function for calcium ions are highest among the cations. In addition, the diffusion coefficient of calcium ions was lower than those of the other ions. A further finding was that one water molecule on the interface and two water molecules adjacent to the interface in liquid phase were positioned in the first or second hydration shell for the calcium ion, which was located at the closest point to the interface. Such hydration shells caused the reductions in motion and diffusion coefficient of the specific calcium ion.     

Bagging GLM: Improved generalized linear model for the analysis of zero-inflated data

Species-occurrence data sets tend to contain a large proportion of zero values, i.e., absence values (zero-inflated). Statistical inference using such data sets is likely to be inefficient or lead to incorrect conclusions unless the data are treated carefully. In this study, we propose a new modeling method to overcome the problems caused by zero-inflated data sets that involves a regression model and a machine-learning technique. We combined a generalized liner model (GLM), which is widely used in ecology, and bootstrap aggregation (bagging), a machine-learning technique. We established distribution models of Vincetoxicum pycnostelma (a vascular plant) and Ninox scutulata (an owl), both of which are endangered and have zero-inflated distribution patterns, using our new method and traditional GLM and compared model performances. At the same time we modeled four theoretical data sets that contained different ratios of presence/absence values using new and traditional methods and also compared model performances. For distribution models, our new method showed good performance compared to traditional GLMs. After bagging, area under the curve (AUC) values were almost the same as with traditional methods, but sensitivity values were higher. Additionally, our new method showed high sensitivity values compared to the traditional GLM when modeling a theoretical data set containing a large proportion of zero values. These results indicate that our new method has high predictive ability with presence data when analyzing zero-inflated data sets. Generally, predicting presence data is more difficult than predicting absence data. Our new modeling method has potential for advancing species distribution modeling.     

An overview of the effects of urbanization on the quantity and quality of groundwater in South Asian megacities

One of the challenges facing megacities in South Asian developing countries in their attempts to realize so-called urban rejuvenation is groundwater conditioned by canal seepage and immense sewage loads. To understand the connection between groundwater pollutants and urbanization, numerous studies were reviewed, and data obtained from a variety of national and international organizations were analyzed. In Delhi and Dhaka, urbanization has lowered the groundwater level as a result of severe overextraction, and its dense population makes Delhi particularly vulnerable to groundwater pollution. In the coastal areas of Karachi and Mumbai, such pollution is magnified by the proximity of seawater as well as the increasing populations of these areas. Among the groundwater pollutants associated with urbanization, chlorides and nitrates are the chief anthropogenic toxins; thus, they are examined in this study. This paper concludes with policy recommendations for minimizing the impact of urbanization on groundwater.