Order restricted randomized designs and two sample inference

This paper develops a new design that relies on subjective judgment ranking to compare subsets of experimental units. This judgment ranking is used along with restricted randomization to improve statistical inference for the contrast between two levels of a treatment. The new design assigns the judgment ranked units in a subset to different treatments. Such an assignment translates the positive dependence among units within each subset into negative dependence for the estimators of treatment means, and hence leads to a reduction in variance for the contrast. For the proposed design, a test for the difference in means of two treatment levels is developed along with an associated confidence interval. It is shown that the null distribution of the proposed test is approximated reasonably well with the Student’s t-distribution for sample sizes as small as 6. A simulation study indicates that the proposed design is advantageous compared to its competitors in the literature for both high and low quality rankings. The new design’s advantage increases with the quality of rankings.     

Statistical inference using stratified judgment post-stratified samples from finite populations

This paper develops statistical inference for population mean and total using stratified judgment post-stratified (SJPS) samples. The SJPS design selects a judgment post-stratified sample from each stratum. Hence, in addition to stratum structure, it induces additional ranking structure within stratum samples. SJPS is constructed from a finite population using either a with or without replacement sampling design. Inference is constructed under both randomization theory and a super population model. In both approaches, the paper shows that the estimators of population mean and total are unbiased. The paper also constructs unbiased estimators for the variance (mean square prediction error) of the sample mean (predictor of population mean), and develops confidence and prediction intervals for the population mean. The empirical evidence shows that the proposed estimators perform better than their competitors in the literature.     

The financial development-environmental degradation nexus in the United Arab Emirates: the importance of growth,globalization and structural breaks

Environmental Science and Pollution Research - This article revisits the nexus between financial development and environmental degradation by incorporating economic growth, electricity consumption...     

The impact of age structure on carbon emission in the Middle East: the panel autoregressive distributed lag approach

Environmental Science and Pollution Research - Rapid evolution in the population age structure of the Middle East countries has major economic, social, and environmental outcomes. Therefore, to...     

Atmospheric deposition of organochlorine pesticides by precipitation in a coastal area

Wet deposition fluxes of organochlorine pesticides (OCPs) were determined for rain samples collected in a coastal area of Turkey. Seventeen precipitation samples were collected over a 1-year period from 2008 to 2009. Rainwater was accumulated at the beginning of rain events using real time monitoring. Atmospheric concentrations were also measured in parallel with deposition samples. Both atmospheric concentrations and deposition fluxes were determined as particle and gas phases. The particle phase and dissolved phase deposition fluxes were 794.26?±?756.70 ngm^?2 day^?1 and 800.77?±?672.63 ngm^?2 day^?1, respectively. The washout ratios for OCP compounds were calculated separately for the particle and dissolved phases using the atmospheric concentrations and rain concentrations. The minimum washout ratio for the particle phase was 2339.47 for Endrin aldehyde, whereas the maximum washout ratio was 497593.34 for Methoxychlor. The maximum washout ratio for the dissolved phase was 247523.89 for Endosulfan beta, whereas the minimum washout ratio was 10169.69 for p,p′-DDT. The dry deposition velocities ranged from 0.01 to 1.67 cms^?1. The partitioning of wet deposition between the particle and dissolved phases was 50 % in terms of total OCP deposition.     

Assessing the long- and short-run asymmetrical effects of climate change on rice production: empirical evidence from India

Environmental Science and Pollution Research - In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist’s attention across the globe due to its...     

Consumers’ intention-based influence factors of renewable energy adoption in Pakistan: a structural equation modeling approach

As the adoption of renewable energy (RE) is a complex and intricate procedure affected by a wide range of factors, it prompts traction among researchers to examine these influence factors. The aim of this study is to scrutinize the factors affecting consumers’ intention to adopt RE for household use in Pakistan. The current research has contributed through expanding the structural framework of the theory of planned behavior by incorporating three novel factors (perception of self-effectiveness, perception of neighbor’s participation, and belief about RE benefits) to have a deep insight into the factors that motivate or inhibit consumers to adopt RE. Outcomes are based on the primary data compiled from 353 households in the five main cities of Pakistan accompanying an inclusive survey. The state-of-the-art structural equation modeling was utilized to test and analyze the proposed hypotheses. The results signify that the influencing factors such as perception of self-effectiveness, awareness of RE, and perception of neighbor’s participation impart a positive effect on consumers’ intention to adopt RE, whereas cost of RE generation has an opposite effect. Interestingly, environmental concern and belief about RE benefits found to have neutral effects. Research results emphasize the need to enhance public awareness, reform policy structure, transform social norms, and highlight the benefits that RE provides, all through an integrative and coherent way.

     

Nitrogen-efficient rice cultivars can reduce nitrate pollution

Introduction  

Environmental pollution by un-utilized nitrogenous fertilizer at the agricultural field is one of the key issues of the day. Rice-based cropping system, the mainstay of Indian agriculture, is one of the main sources of unused N-fertilizer since rice utilizes only 30–40% of total applied N, and the rest goes to waste and creates environmental as well as economic loss.     

Effects of azadirachtin on Beet soilborne pomovirus and soil biological properties on sugar beet

Beet soilborne pomovirus (BSBV) is an important soilborne virus disease in growing areas of sugar beet. BSBV was transmitted by Polymyxa betae Keskin. Effects of azadirachtin on BSBV and soil biological properties were studied under a greenhouse. The presence of BSBV was tested in soil samples using bait plant test and triple antibody sandwich-enzyme-linked immunosorbent assay (TAS-ELISA). The concentration of BSBV in sugar beet roots was significantly reduced by the application of azadirachtin to the soils. TAS-ELISA absorption values in 1.52, 3.04, and 7.60 ppm were lower than that 0.38 and 0.76 ppm of azadirachtin. Furthermore, in this study, it was determined the 0.38, 0.76, and 1.52 ppm doses of azadirachtin in soils had high amounts of soil biological properties (Cmic, BSR, DHA), while the 3.04 and 7.60 ppm doses had no statistical significance compared to the control treatments.