scholarly journals A New Model of Vegetable Waste Resource Treatment Combining Rapid Volume Reduction and Biochemical Technology

Author(s):  
Weiwei Song ◽  
Wanfeng Jiang ◽  
Meng Zhang
2018 ◽  
Vol 7 (3.12) ◽  
pp. 784
Author(s):  
Senthilkumar Palaniappan ◽  
Murugappan Alagappan

The low optimum level of vermi pile depth (10 cm-15 cm) warrants encroachment of large land area and consume more time in the vermicomposting process.  In engineered vermicomposting, the acceleration of digestion of high volume of waste was done by eliminating the pre-composting and introducing pre-processing the waste.  This process involves chopping, pulverizing, stocking, and drying the waste followed by injecting the engineered microorganisms (EM) at various depths in vermi bin during the vermicomposting process. Pre-processing and injection of EM enabled to increase the substrate depth by two-to-three-fold (30 cm).  Experimentation was conducted in five vermi bins with same quantity of worms (100 gms of E. fetida in each bin), with different stock loads of EM  (0.3ml, 0.4ml, 0.5ml, 0.6ml and 0.7ml) named as Bin 1, Bin 2, Bin 3, Bin 4 and Bin 5 respectively.  In parallel, a control (Bin C1) and conventional (Bin C2) vermi bin were also set up to compare the differences observed.  The outcome of the study clearly showed that the bin loaded with 0.7ml EM (Bin 5) stock achieved high volume reduction (70%). Moreover, the trail unit loaded with 0.5ml of EM stock (Bin 3) exhibited high biomass growth rate than its counter trail units.   


2019 ◽  
Vol 19 (1) ◽  
pp. 109-122 ◽  
Author(s):  
P. Rivas-García ◽  
◽  
J.E. Botello-Álvarez ◽  
L.R. Miramontes-Martínez ◽  
J.J. Cano-Gómez ◽  
...  

Author(s):  
H. Akabori ◽  
K. Nishiwaki ◽  
K. Yoneta

By improving the predecessor Model HS- 7 electron microscope for the purpose of easier operation, we have recently completed new Model HS-8 electron microscope featuring higher performance and ease of operation.


2005 ◽  
Vol 173 (4S) ◽  
pp. 140-141
Author(s):  
Mariana Lima ◽  
Celso D. Ramos ◽  
Sérgio Q. Brunetto ◽  
Marcelo Lopes de Lima ◽  
Carla R.M. Sansana ◽  
...  

Author(s):  
Thorsten Meiser

Stochastic dependence among cognitive processes can be modeled in different ways, and the family of multinomial processing tree models provides a flexible framework for analyzing stochastic dependence among discrete cognitive states. This article presents a multinomial model of multidimensional source recognition that specifies stochastic dependence by a parameter for the joint retrieval of multiple source attributes together with parameters for stochastically independent retrieval. The new model is equivalent to a previous multinomial model of multidimensional source memory for a subset of the parameter space. An empirical application illustrates the advantages of the new multinomial model of joint source recognition. The new model allows for a direct comparison of joint source retrieval across conditions, it avoids statistical problems due to inflated confidence intervals and does not imply a conceptual imbalance between source dimensions. Model selection criteria that take model complexity into account corroborate the new model of joint source recognition.


1986 ◽  
Vol 31 (2) ◽  
pp. 108-109
Author(s):  
Alexandra G. Kaplan
Keyword(s):  

PsycCRITIQUES ◽  
2004 ◽  
Vol 49 (Supplement 13) ◽  
Author(s):  
Paul E. Priester
Keyword(s):  

1993 ◽  
Vol 38 (4) ◽  
pp. 406-407
Author(s):  
Donald B. Yarbrough ◽  
Monika Schaffner

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