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The primary goals of this work are to determine the genetic variability of virus populations for advancing our understanding of virus spread, and to study interactions between viruses, insect vectors, and plant hosts with the aims of developing robust detection methodologies and implementing innovative approaches for disease management.
Primary goals are to determine the genetic variability of virus populations for advancing our understanding of virus spread, and to study interactions between viruses, vectors, and plant hosts with the aims of developing robust detection methodologies, and implementing innovative approaches for crop improvement.
For this reason, it is necessary to reduce the amount of sludge generation by improving the efficiency of the treatment methodologies and implementing new technologies able to use sludge as raw material for compost, generate biomolecules and energy.
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To date, a variety of methodologies and implemented systems have been proposed that all seek to make sketching the primary interaction method for 3D geometric modeling.
To address potential response bias issues, we will use standard statistical methodologies and implement propensity-based and imputation methods with imputation of smoking status or treatment utilization at follow-up.
In this paper, we propose a practical methodology and implement an environment by employing model-based robustness testing for embedded software systems.
This model has recently been modified to include a graphical user interface based on an object-oriented methodology, and implemented using the Visual Basic programming language.
This paper describes an automated modular fixture design system developed using a CAD-based methodology and implemented on a 3-D CAD/CAM software package.
The chip has been designed with the standard cell based design methodology, and implemented in the central semiconductor manufacturing corporation (CSMC) 0.5 μm complementary metal-oxide-semiconductor (CMOS) process technology.
The aim of this paper is to fill this gap with developing an adaptable, geographical information system-based methodology and implement it in a study area where the previously mentioned conditions are highly observable.
The paper describes two MOOCs on distinct topics using this methodology and implemented on the same platform.
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