1,157 research outputs found
Composition, productivity and impact of grazing on the biodiversity of a grazing land in Almora District
Biodiversity of Almora district is heavily affected in the areas with heavy grazing pressure, although moderate grazing enhanced the biodiversity of the area. In the present study site a total of 45 herbaceous species were present and therophytes were dominant among them. Live shoot biomass of plants varied from 175.0±3.5 to 1862.0±5.75 kg/ha and 87.0±3.25 to 1303.0±7.50 kg/ha in ungrazed and grazed plots respectively. Aboveground primary productivity was significantly higher on control plot (3082.2 kg/ha) over grazed plot (2644.0 kg/ha). The average bite frequency per hour was recorded maximum for goats (1106.5 bite/hr) and least for buffalos (920 bites/hr). The monthly dry matter consumption per animal was amounted to 157.15, 154.51, 68.66 and 61.34 kg for cow, buffalo, sheep and goat respectively under nomadic open grazing. The percent herbage exploitation was observed maximum by sheep (9.82%) and minimum by buffalo (8.75%)
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Preface
Sixteen months ago in a comment during office hours, we raised the idea for a journal at Columbia Law School dedicated to tax law and policy. Within a few weeks, student interest grew in support of the idea and sparked active discussion. Over the course of last year, the proposal that developed brought together the perspectives of the faculty, administration, library, alumni and colleagues outside of academia, and students pursuing tax as their field of focus. It is our pleasure to introduce the Inaugural Issue of the Columbia Journal of Tax Law, the culmination of over a year and a half’s preparation.
The field of tax has the attribute of attracting a diverse collection of backgrounds and perspective among the individuals who participate in its lively debates. It is a great asset of this field, and one of our principal sources of inspiration as we crafted the vision for this Journal. The readers and authors of the scholarship in our pages draw from at least three distinct groups within the field of tax. They include the policymakers in federal, state, and foreign governments, practitioners in the private sector, and professors in academia
Non-Equilibrium Surface Tension of the Vapour-Liquid Interface of Active Lennard-Jones Particles
We study a three-dimensional system of self-propelled Brownian particles
interacting via the Lennard-Jones potential. Using Brownian Dynamics
simulations in an elongated simulation box, we investigate the steady states of
vapour-liquid phase coexistence of active Lennard-Jones particles with planar
interfaces. We measure the normal and tangential components of the pressure
tensor along the direction perpendicular to the interface and verify mechanical
equilibrium of the two coexisting phases. In addition, we determine the
non-equilibrium interfacial tension by integrating the difference of the normal
and tangential component of the pressure tensor, and show that the surface
tension as a function of strength of particle attractions is well-fitted by
simple power laws. Finally, we measure the interfacial stiffness using
capillary wave theory and the equipartition theorem, and find a simple linear
relation between surface tension and interfacial stiffness with a
proportionality constant characterized by an effective temperature.Comment: 12 pages, 5 figures (Corrected typos and References
Interpreting Financial Results
The article discusses three accounting changes issued by the Financial Accounting Standards Board (FSAB). The Statement of Financial Accounting Standards (SFAS) No. 158 Employers\u27 Accounting for Defined Benefit Pension and Other Retirement Plans and the SFAS No. 160 Noncontrolling Interests in Consolidated Financial Statements are mentioned. Financial Interpretation 48 Accounting for Uncertainty in Income Taxes, an Interpretation of FSAB Statement No. 109 is mentioned.
The takeaway? Financial analysts, investors, and creditors need to carefully interpret ratios and measures, including debt to equity, liabilities to equity, and return on equity. Financial ratios used in loan covenants should be clearly designed and defined, and, in some cases, equity may be more meaningfully defined as adjusted for certain changes in other comprehensive income
Improving protein fold recognition using the amalgamation of evolutionary-based and structural-based information
Deciphering three dimensional structure of a protein sequence is a challenging task in biological science. Protein
fold recognition and protein secondary structure prediction are transitional steps in identifying the three
dimensional structure of a protein. For protein fold recognition, evolutionary-based information of amino acid
sequences from the position specific scoring matrix (PSSM) has been recently applied with improved results. On
the other hand, the SPINE-X predictor has been developed and applied for protein secondary structure prediction.
Several reported methods for protein fold recognition have only limited accuracy. In this paper, we have
developed a strategy of combining evolutionary-based information (from PSSM) and predicted secondary structure
using SPINE-X to improve protein fold recognition. The strategy is based on finding the probabilities of amino acid
pairs (AAP). The proposed method has been tested on several protein benchmark datasets and an improvement of
8.9% recognition accuracy has been achieved. We have achieved, for the first time over 90% and 75% prediction
accuracies for sequence similarity values below 40% and 25%, respectively. We also obtain 90.6% and 77.0%
prediction accuracies, respectively, for the Extended Ding and Dubchak and Taguchi and Gromiha benchmark
protein fold recognition datasets widely used for in the literature
A mixture of physicochemical and evolutionary–based feature extraction approaches for protein fold recognition
Griffith Sciences, Griffith School of EngineeringFull Tex
A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem
Better understanding of structural class of a given protein reveals important information about its overall folding type and its domain. It can also be directly used to provide critical information on general tertiary structure of a protein which has a profound impact on protein function determination and drug design. Despite tremendous enhancements made by pattern recognition-based approaches
to solve this problem, it still remains as an unsolved issue for bioinformatics which demands more attention and exploration. In this study, we propose a novel feature extraction model which incorporates physicochemical and evolutionary-based information simultaneously. We also propose overlapped segmented distribution and autocorrelation based feature extraction methods to provide more local and global discriminatory information. The proposed feature extraction methods are explored for 15 most promising attributes that are selected from a wide range of physicochemical-based attributes. Finally, by applying an ensemble of different classifiers namely, Adaboost.M1, LogitBoost, Naive Bayes, Multi-Layer Perceptron (MLP), and Support Vector Machine (SVM) we show enhancement of the protein structural class prediction accuracy for four popular benchmarks
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