scholarly journals Stable-isotope Labeled Metabolic Analysis in Drosophila melanogaster: from Experimental Setup to Data Analysis

BIO-PROTOCOL ◽  
2018 ◽  
Vol 8 (18) ◽  
Author(s):  
Yuping Cai ◽  
Nan Liu ◽  
Zheng-Jiang Zhu
Keyword(s):  
Drosophila Melanogaster ◽  
Data Analysis ◽  
Stable Isotope ◽  
Experimental Setup ◽  
Metabolic Analysis

Settling Characteristics of Polymeric Additives in Dodecane

2018 ◽  
Author(s):  
Gurjap Singh ◽  
Stephen Pitts ◽  
Elio Lopes ◽  
Albert Ratner
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Experimental Setup ◽  
Objective Data ◽  
Polymeric Additives ◽  
Burning Rates ◽  
Settling Behavior ◽  
Settling Characteristics

Recent studies have shown that adding polymeric additives to hydrocarbon-based fuels can lead to suppression of their splashing behavior, as well as enhance their burning rates. However, there is a lack of objective data on polymeric additives settling times in these fuels. Choosing Dodecane as a representative of diesel-based fuels, present research experimentally investigates the settling behavior of polymeric additives (graphene) when mixed in with Dodecane, and the effects of various surfactants on such behavior. Methodology for experimental setup, data collection and data analysis is presented. Various concentrations of additives and surfactants are analyzed, and trends for settling times are shown.

Use of high coverage reference libraries of Drosophila melanogaster for relational data analysis

1991 ◽  
Vol 220 (4) ◽  
pp. 903-914 ◽  
Author(s):  
Jörg D. Hoheisel ◽  
Gregory G. Lennon ◽  
Günther Zehetner ◽  
Hans Lehrach
Keyword(s):  
Drosophila Melanogaster ◽  
Data Analysis ◽  
Relational Data ◽  
High Coverage

scholarly journals Metabolic Analysis of Drosophila melanogaster Larval and Adult Brains

10.3791/58007 ◽  
2018 ◽  
Author(s):  
Kathryn E. Neville ◽  
Timothy L. Bosse ◽  
Mia Klekos ◽  
John F. Mills ◽  
Marla Tipping
Keyword(s):  
Drosophila Melanogaster ◽  
Metabolic Analysis

Data-driven thinking for measuring the human experience in the built environment

2021 ◽  
pp. 147807712110251
Author(s):  
Bige Tunçer ◽  
Francisco Benita
Keyword(s):  
Data Analysis ◽  
Built Environment ◽  
Urban Design ◽  
Learning Experience ◽  
Landscape Design ◽  
Data Driven ◽  
Sensor Data ◽  
Experimental Setup ◽  
Collection Data

This article introduces a methodology to implement Data-driven Thinking in the context of urban design. We present the results of a case study based on a 7-day workshop with 10 participants with landscape design and architecture background. The goal of the workshop was to expose participants to Data-driven Thinking through experimental design, multi-sensor data collection, data analysis, visualization, and insight generation. We evaluate their learning experience in designing an experimental setup, collecting real-time immediate environmental and physiological body reactions data. Our results from the workshop show that participants increased their knowledge about measuring, visualizing and understanding data of the surrounding built environment.

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