scholarly journals Comparative Study on the Developmental Stages of Global CCS Technology Based on the S-Curve Model

2021 ◽  
Author(s):  
Yaya Li ◽  
Shuai Qin
Keyword(s):  
Comparative Study ◽  
Developmental Stages ◽  
Curve Model ◽  
S Curve

scholarly journals Comparative study on five kinds of cytokines in the tissues of Chinese giant salamander (Andrias davidianus) of different developmental stages

2021 ◽  
Vol 869 (1) ◽  
pp. 012067
Author(s):  
J Qian ◽  
X Y Zhai ◽  
L Guo ◽  
W G Chen ◽  
J J Fu ◽  
...  
Keyword(s):  
Comparative Study ◽  
Blood Serum ◽  
Developmental Stages ◽  
Distribution Area ◽  
Andrias Davidianus ◽  
Tnf Α ◽  
Sandwich Method ◽  
Different Ages ◽  
Chinese Giant Salamander ◽  
Different Tissues

Abstract By using of the double antibody sandwich method of ELISA, the activities of five cytokines including IL-2, IL-4, IFN-α, IFN-β and TNF-α from the blood serum, liver, intestine and spleen at two developmental stages of Chinese giant salamander (Andrias davidianus) were determined to analyze the distribution of the cytokines. The result indicated that five cytokines were found in these four tissues, while their activities were different in different tissues and different ages. The highest activity of IL-2 and IL-4 was all present in blood serum of two different ages. The activity of IFN-α was the highest in blood serum of 1-year-old and in spleen of 2-year-old, respectively. The activity of IFN-β was also highest in blood serum of two different ages. The activity of TNF-α was highest in liver of two different ages. Thus, this study provides convincing reference for blood serum and liver as the most important distribution area of Chinese giant salamander.

S-curve Model of Relationship Between Energy Consumption and Economic Development

2014 ◽  
Vol 24 (1) ◽  
pp. 53-64 ◽  
Author(s):  
Anjian Wang ◽  
Gaoshang Wang ◽  
Qishen Chen ◽  
Wenjia Yu ◽  
Kun Yan ◽  
...  
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Curve Model ◽  
S Curve

Uncertain Technology Evolution and Decision Making in Design

2012 ◽  
Vol 134 (10) ◽  
Author(s):  
Jonathan L. Arendt ◽  
Daniel A. McAdams ◽  
Richard J. Malak
Keyword(s):  
Research And Development ◽  
Pareto Frontier ◽  
Evolutionary Process ◽  
Evolutionary Model ◽  
Development Effort ◽  
Technology Evolution ◽  
Curve Model ◽  
S Curve ◽  
Over Time

The potential for engineering technology to evolve over time can be a critical consideration in design decisions that involve long-term commitments. Investments in manufacturing equipment, contractual relationships, and other factors can make it difficult for engineering firms to backtrack once they have chosen one technology over others. Although engineering technologies tend to improve in performance over time, competing technologies can evolve at different rates and details about how a technology might evolve are generally uncertain. In this article we present a general framework for modeling and making decisions about evolving technologies under uncertainty. In this research, the evolution of technology performance is modeled as an S-curve; the performance evolves slowly at first, quickly during heavy research and development effort, and slowly again as the performance approaches its limits. We extend the existing single-attribute S-curve model to the case of technologies with multiple performance attributes. By combining an S-curve evolutionary model for each attribute with a Pareto frontier representation of the optimal implementations of a technology at a particular point in time, we can project how the Pareto frontier will move over time as a technology evolves. Designer uncertainty about the precise shape of the S-curve model is considered through a Monte Carlo simulation of the evolutionary process. To demonstrate how designers can apply the framework, we consider the scenario of a green power generation company deciding between competing wind turbine technologies. Wind turbines, like many other technologies, are currently evolving as research and development efforts improve performance. The engineering example demonstrates how the multi-attribute technology evolution modeling technique provides designers with greater insight into critical uncertainties present in long-term decision problems.

An Updated Trend Analysis Representing the Outbreak of Novel Coronavirus (2019-nCoV) in 16 Cities of Hubei Province, China Using Logistic S-Curve Model

2020 ◽  
Author(s):  
Muhammad Fawad ◽  
Sumaira Mubarik ◽  
Saima Shakil Malik ◽  
Yangyang Hao ◽  
Chuanhua Yu ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Hubei Province ◽  
Curve Model ◽  
S Curve ◽  
Novel Coronavirus

Midgut bacterial communities in the giant Asian honeybee (Apis dorsata) across 4 developmental stages: A comparative study

2016 ◽  
Vol 24 (1) ◽  
pp. 81-92 ◽  
Author(s):  
Prakaimuk Saraithong ◽  
Yihong Li ◽  
Kanokporn Saenphet ◽  
Zhou Chen ◽  
Panuwan Chantawannakul
Keyword(s):  
Comparative Study ◽  
Bacterial Communities ◽  
Developmental Stages ◽  
Apis Dorsata ◽  
Asian Honeybee
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