Ammonia-Nitrogen Recovery from Synthetic Solution using Agricultural Waste Fibers

In this study, modification of Empty Fruit Bunch (EFB) fibers as a means to recover ammonianitrogen from a synthetic solution was investigated. Methods: The EFB fiber was modified using sodium hydroxide.Adsorption-desorption studies of ammonia nitrogen into the modified EFB fiber were investigated Findings: Theincrease in adsorption capacity was found to be proportional with the increase of pH up to 7, temperature and ammoniaconcentration. The maximum adsorption capacity is 0.53-10.89 mg/g. The attachment of ammonia nitrogen involves ionexchange-chemisorption. The maximum desorption capacity of 0.0999 mg/g. Applications: This study can be used as abaseline for designing a low cost adsorbent system for ammonia nitrogen recovery drainage and industrial wastewater aswell as EFBs-palm oil mill effluent composting

A maximum likelihood method for latent class regression involving a censored dependent variable

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45751/1/11336_2005_Article_BF02294647.pd

Scaling reducibility of metal oxides

International audienceThe reducibility of bulk metal oxides in which the cation is in its highest oxidation state (MgO, Sc2O3, Y2O3, TiO2, m-ZrO2, m-HfO2, CeO2, V2O5, Nb2O5, Ta2O5, WO3, CrO3, Al2O3, β-Ga2O3, SiO2, SnO2 and ZnO) has been studied by standard periodic density functional theory. We have defined and calculated descriptors able to describe and quantify semi-quantitatively the extent of reduction: electronic band gap, oxygen vacancy formation energy and electronic localization. We find that there is no single criterion for characterizing the reducibility. We discuss the advantages and limitations of each method, and we apply them to classify the materials with the PBE+U and B3LYP functionals. Typical irreducible oxides such as MgO show a large band gap, high oxygen vacancy formation energy and electronic localization of the reduction electrons forming and F-center, with a diamagnetic singlet electronic state. Reducible oxides such as TiO2 present small band gaps, small oxygen vacancy formation energy and electron localization of the reduction electrons in the cations, decreasing their oxidation state and presenting open-shell electronic states. Intermediate or ambivalent behavior is found for ZrO2, HfO2, β-Ga2O3, ZnO and SnO2

Influence of the anionic ligands on properties and reactivity of Hoveyda-Grubbs catalysts

Ruthenium based catalysts remain among the more successful complexes used in the catalysis of metathesis processes for the synthesis of new carbon-carbon bonds. The investigation of the influence of the different system moieties on its catalytic performance has led to important improvements in the field. To this extent, density functional theory (DFT) calculations have contributed significantly providing fundamental understandings to develop new catalysts. With this aim, we presented here a detailed computational study of how the nature of the anion ligand binding to the metal affects the global properties and reactivity of the catalyst. Geometric, energetic and electronic analysis have been performed to reach the key insights necessary to build structure-performance correlations

Identifying Sources of Heterogeneity for Empirically Deriving Strategic Types: A Constrained Finite-Mixture Structural-Equation Methodology

The resource-based view (RBV) of the firm suggests that strategic deployment of capabilities allows strategic business units (SBUs) to exploit distinctive competencies and create sustainable competitive advantage. Following the RBV, we propose a new predictive methodology for deriving typologies of SBUs that accommodates heterogeneity among SBUs with respect to their strategic capabilities, how effectively they are employed, and performance. Statistically, we devise a constrained finite-mixture structural-equation procedure that simultaneously accounts for firm capabilities, performance outcomes, and the relationships between them. The procedure allows for a comprehensive modeling and grouping of entities, and simultaneously provides a diagnosis of the sources of heterogeneity via the flexibility of estimating a series of nested models. Managerially, our proposed methodology is grounded in the strategic type and RBV literature and can capture the effects of environmental and industry-specific factors. Using data obtained from 216 SBUs in the United States for illustration, the results show that our derived four mixed-type solution dominates the four-group, Prospectors-Analyzers-Defenders-Reactors classification as well as a number of other nested model solutions in terms of objective statistical fit criteria for this data set, suggesting a more contingency-driven strategic stance adopted by these SBUs. We conclude with a discussion of the theoretical and managerial benefits of an improved methodology for empirically deriving strategic typologies.competitive strategy, strategic types, effectiveness performance, structural-equation models, finite mixtures, latent class models