Randomly selected order statistics in ranked set sampling: A less expensive comparable alternative to simple random sampling

Rank-based sampling designs are powerful alternatives to simple random sampling (SRS) and often provide large improvements in the precision of estimators. In many environmental, ecological, agricultural, industrial and/or medical applications the interest lies in sampling designs that are cheaper than SRS and provide comparable estimates. In this paper, we propose a new variation of ranked set sampling (RSS) for estimating the population mean based on the random selection technique to measure a smaller number of observations than RSS design. We study the properties of the population mean estimator using the proposed design and provide conditions under which the mean estimator performs better than SRS and some existing rank-based sampling designs. Theoretical results are augmented with some numerical studies and a real-life example, where we also study the performance of our proposed design under perfect and imperfect ranking situations.     

Pathogenicity of Aeromonas hydrophila isolated from the Malaysian Sea against coral (Turbinaria sp.) and sea bass (Lates calcarifer)

Environmental Science and Pollution Research - A study was carried out to determine the pathogenicity (hemolytic activity) on corals (Turbinaria sp.) and sea bass (Lates calcarifer) of Aeromonas...     

Drivers of local people’s participation in sustainable natural resource management: a case study in central Iran

The driving forces behind natural resource management (NRM) vary among countries. Most NRM programmes focus on biophysical drivers such as soil, water and vegetation, with little attention directed towards the nuanced sociocultural and religious drivers of sustainable natural resource management (SNRM) practices. This paper explores those understudied drivers that influence local people’s participation (LPP) in SNRM in Isfahan, Iran. Using a multi-stage stratified sampling method, we selected 200 natural resource experts and natural resource users to complete a questionnaire about their perceptions of SNRM. Results reveal that sociocultural and religious beliefs are the major drivers of SNRM. The results also indicate that subsidiary drivers include: a sense of responsibility towards SNRM; the conviction that natural resources belong to God and should therefore be preserved; participation to preserve natural resources because of training courses and media influence; a long-established custom of preserving natural resources; and the specific impact of environmental television programmes. Demographic analysis finds a significant relationship between educational level and LPP in SNRM. This study’s results therefore suggest that natural resource managers would benefit from a deeper understanding of the local sociocultural and religious contexts that motivate people to participate in SNRM.     

Monitoring of trace amounts of heavy metals in different food and water samples by flame atomic absorption spectrophotometer after preconcentration by amine-functionalized graphene nanosheet

We are introducing graphene oxide modified with amine groups as a new solid phase for extraction of heavy metal ions including cadmium(II), copper(II), nickel(II), zinc(II), and lead(II). Effects of pH value, flow rates, type, concentration, and volume of the eluent, breakthrough volume, and the effect of potentially interfering ions were studied. Under optimized conditions, the extraction efficiency is >97 %, the limit of detections are 0.03, 0.05, 0.2, 0.1, and 1 μg L^?1 for the ions of cadmium, copper, nickel, zinc, and lead, respectively, and the adsorption capacities for these ions are 178, 142, 110, 125, and 210 mg g^?1. The amino-functionalized graphene oxide was characterized by thermogravimetric analysis, transmission electron microscopy, scanning electron microscopy, and Fourier transform infrared spectrometry. The proposed method was successfully applied in the analysis of environmental water and food samples. Good spiked recoveries over the range of 95.8–100.0 % were obtained. This work not only proposes a useful method for sample preconcentration but also reveals the great potential of modified graphene as an excellent sorbent material in analytical processes.     

Oasis land-use change and its effects on the eco-environment in Yanqi Basin, Xinjiang, China

Satellite data and the published coefficients about the world's and China's ecosystem were used to analyze the effects of land-use changes on the ecosystem service in the Yanqi Basin. Both economic developments and arid, fragile ecosystems have strongly affected the land use. A sensitivity analysis determined the effect of manipulating the coefficients on the estimated values. Results indicated that (1) the total value of ecosystem services in the Yanqi Basin were 9,374.66, 10,450.52, 9,964.20, and 9,8707.77 million Yuan in 1990, 2000, 2005, and 2011, respectively. The net increase in ecosystem service values were about 496.11 million Yuan within 1990–2011; (2) The aggregated ecosystem service values of water body, wetlands, grasslands, and croplands were about 99.25 % of the total value; (3) Waste treatment and soil formation were the top two ecological functions with high service values and contributing about 61.70 % of the total service values; and (4) Ecosystem service values estimated in this study were inelastic with respect to the value coefficients; therefore, the estimation was robust in spite of uncertainties on the value coefficients. A reasonable land-use plan should be based on rigorous environmental impact analyses for maintaining stability and sustainable development of the Yanqi Basin.     

Water and waste load allocation in rivers with emphasis on agricultural return flows: application of fractional factorial analysis

In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.