Use of 2–methoxyethyl ether and nitromethane as oxygenated additives for performance improvement and emission reduction of CI engine: experimental investigation and numerical simulation

Environmental Science and Pollution Research - Diesel engines are playing a vital responsibility in the field of automobile, agriculture, construction, and power generation. In the present world,...     

Coping with the ‘Indian summer’: unique nesting cycle and nest architecture of the paper wasp,Polistes wattii

The Science of Nature - Leaf-cutting ants are highly successful herbivores in the Neotropics. They forage large amounts of fresh plant material to nourish a symbiotic fungus that sustains the...     

Removal of textile dyes from aqueous solution using PEG based aqueous biphasic system

Aqueous biphasic systems (ABSs) composed of polyethylene glycol (PEG) and salt have been examined for the removal of textile dyes from textile effluent. The partitioning of four dyes namely Cibacron Scarlet LS 2G, Rhodamine B, Brown ERN and Astacryl Red 3B was investigated. All the dyes studied were found to partition into the upper PEG rich layer. Sodium carbonate was found to be the most efficient salt for extraction of dyes. Sodium sulphate was found to be marginally less efficient. Sodium chloride did not cause partitioning at all. Partitioning occurred at all pH and was almost pH independent. The partitioning of these dyes in larger volume (100?mL) ABS was also demonstrated. Studies using dye bath effluent were also conducted. In all cases very high efficiencies consistently above 98% were obtained.     

Use of fuzzy logic models for prediction of taste and odor compounds in algal bloom-affected inland water bodies

Mechanistic modeling of how algal species produce metabolites (e.g., taste and odor compounds geosmin and 2-methyl isoborneol (2-MIB)) as a biological response is currently not well understood. However, water managers and water utilities using these reservoirs often need methods for predicting metabolite production, so that appropriate water treatment procedures can be implemented. In this research, a heuristic approach using Adaptive Network-based Fuzzy Inference System (ANFIS) was developed to determine the underlying nonlinear and uncertain quantitative relationship between observed cyanobacterial metabolites (2-MIB and geosmin), various algal species, and physical and chemical variables. The model is proposed to be used in conjunction with numerical water quality models that can predict spatial–temporal distribution of flows, velocities, water quality parameters, and algal functional groups. The coupling of the proposed metabolite model with the numerical water quality models would assist various utilities which use mechanistic water quality models to also be able to predict distribution of taste and odor metabolites, especially when monitoring of metabolites is limited. The proposed metabolite model was developed and tested for the Eagle Creek Reservoir in Indiana (USA) using observations over a 3-year period (2008–2010). Results show that the developed models performed well for geosmin (R ²?=?0.83 for all training data and R ²?=?0.78 for validation of all 10 data points in the validation dataset) and reasonably well for the 2-MIB (R ²?=?0.82 for all training data and R ²?=?0.70 for 7 out of 10 data points in the validation dataset).     

Changes in the dry tropical forests in Central India with human use

Understanding changes in forest composition and structure is important to help formulate effective policies that promote future ability of forests to provide local livelihood needs, habitat and ecosystem services. This is particularly important in dry tropical forests that are ecologically different from other forests and are heavily used by local, forest-dependent residents. In this study, we identify biophysical, demographic and use factors associated with differences in species diversity, vegetation structure (abundance at different size classes), biomass and relative abundance of species across the Kanha–Pench landscape in Central India. We sampled vegetation in twenty transects across different human and livestock population densities and frequencies of use. We found that biomass, species diversity and vegetation (abundance at different size classes) are negatively associated with increasing population density, and species composition at different size classes is significantly different at higher frequencies of use at low population densities. Lack of difference in species composition at high population densities may be due to colonization and growth of individuals at some of these sites due to creation of new ecological niches and gaps at high human use. Relative abundance of species at different size classes also varies with frequency of use and population density. Results suggest that human use is altering relative abundance of species, which may change long-term forest composition and thus alter biomass and vegetation structure of the forest. We conclude that human use is an agent in altering long-term composition that can alter availability of tree species for local use and other ecosystem services.     

On the use of multivariate statistical methods for combining in-stream monitoring data and spatial analysis to characterize water quality conditions in the White River Basin,Indiana, USA

Mechanistic hydrologic and water quality models provide useful alternatives for estimating water quality in unmonitored streams. However, developing these elaborate models for large watersheds can be time-consuming and expensive, in addition to challenges that arise during calibration when there is limited spatial and/or temporal monitored in-stream water quality data. The main objective of this research was to investigate different approaches for developing multivariate analysis models as alternative methods for rapidly assessing relationships between spatio-temporal physical attributes of the watershed and water quality conditions in monitored streams, and then using the developed relationships for estimating water quality conditions in unmonitored streams. The study compares the use of various statistical estimates (mean, geometric mean, trimmed mean, and median) of monitored water quality variables to represent annual and seasonal water quality conditions. The relationship between these estimates and the spatial data is then modeled via linear and non-linear multivariate methods. Overall, the non-linear techniques for classification outperformed the linear techniques with an average cross-validation accuracy of 79.7%. Additionally, the geometric mean based models outperformed models based on other statistical indicators with an average cross-validation accuracy of 80.2%. Dividing the data into annual and quarterly datasets also offered important insights into the behavior of certain water quality variables impacted by seasonal variations. The research provides useful guidance on the use and interpretation of the various statistical estimates and statistical models for multivariate water quality analyses.     

Untangling outcomes of de jure and de facto community‐based management of natural resources

We systematically reviewed the literature on the tragedy of the commons and common‐property resources. We segregated studies by legal management regimes (de jure regimes) and management that develops in practice (de facto regimes) to understand how the structure of regime formation affects the outcome of community management on sustainability of resource use. De facto regimes, developed within the community, are more likely to have positive impacts on the resource. However, de facto regimes are fragile and not resilient in the face of increased population pressure and unregulated markets, and de facto management regimes are less successful where physical exclusion of external agents from resources is more difficult. Yet, formalization or imposition of de jure management regimes can have complicated impacts on sustainability. The imposition of de jure regimes usually has a negative outcome when existing de facto regimes operate at larger scales than the imposed de jure regime. In contrast, de jure regimes have largely positive impacts when the de facto regimes operate at scales smaller than the overlying de jure regimes. Formalization may also be counterproductive because of elite capture and the resulting de facto privatization (that allows elites to effectively exclude others) or de facto open access (where the disenfranchised may resort to theft and elites cannot effectively exclude them). This underscores that although the global movement to formalize community‐management regimes may address some forms of inequity and may produce better outcomes, it does not ensure resource sustainability and may lead to greater marginalization of users. Comparison of governance systems that differentiate between initiatives that legitimize existing de facto regimes and systems that create new de facto regimes, investigations of new top‐down de jure regimes, and studies that further examine different approaches to changing de jure regimes to de facto regimes are avenues for further inquiry.     

Life after the layoff: getting a job worth keeping

The competitive environment of business today makes corporate layoffs an organizational reality, and losing one's job can be a highly stressful experience. We propose and test a model that places objective underemployment and subjective underemployment in a causal sequence between organizational actions and employees' restoration of equilibrium by obtaining jobs worth keeping. We longitudinally examine relationships between layoff fairness, workers' stress symptoms and appraisal, and subsequent employment outcomes among 149 laid‐off technical employees over the course of one year. Structural equation model results support seven of nine hypothesized paths, and demonstrate discriminant validity between and mediational properties of objective and subjective underemployment. Findings also reveal the important role that employees' perceptions and subjective assessments play in successfully returning to pre‐job loss equilibrium following displacement. Copyright © 2008 John Wiley & Sons, Ltd.     

Effect of experimental parameters on photocatalytic degradation efficiency of TiO2 nanoparticles synthesized by electrochemical method towards Rhodamine B dye solution under natural sunlight

Environmental Science and Pollution Research - In this study,?~?40 nm anatase TiO2 nanoparticles were successfully prepared by a simple electrochemical method by using succinic...