scholarly journals Using causality and correlation analysis to decipher microbial interactions in activated sludge

2021 ◽  
Author(s):  
Weiwei Cai ◽  
Xiangyu Han ◽  
Hong Yao
Keyword(s):  
Time Series ◽  
Activated Sludge ◽  
Network Theory ◽  
Time Series Data ◽  
Microbial Interactions ◽  
Series Data ◽  
Natural Environments ◽  
Cell Aggregate ◽  
Causality Analysis ◽  
Mutualistic Relationship

Network theory is widely used to understand microbial interactions in activated sludge and numerous other artificial and natural environments. However, when using correlation-based methods, it is not possible to identify the directionality of interactions within microbiota. Based on the classic Granger test of sequencing-based time-series data, a new Microbial Causal Correlation Network (MCCN) was constructed with distributed ecological interaction on the directed, associated links. As a result of applying MCCN to a time series of activated sludge data, we found that the hub species OTU56, classified as belonging the genus Nitrospira, was responsible for completing nitrification in activated sludge, and mainly interacted with Proteobacteria and Bacteroidetes in the form of amensal and commensal relationships, respectively. Phylogenetic tree suggested a mutualistic relationship between Nitrospira and denitrifiers. Zoogloea displayed the highest ncf value within the classified OTUs of the MCCN, indicating that it could be a foundation for activated sludge through forming the characteristic cell aggregate matrices into which other organisms embed during floc formation. Overall, the introduction of causality analysis greatly expands the ability of a network to shed a light on understanding the interactions between members of a microbial community.

Examining the Long Run Effects of Export, Import and FDI Inflows on the FDI Outflows from India: A Causality Analysis

2009 ◽  
Vol 10 (1) ◽  
pp. 65-88
Author(s):  
Nandita Dasgupta
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Driving Force ◽  
Time Series Data ◽  
Series Data ◽  
Causality Analysis ◽  
Fdi Inflows ◽  
Long Run ◽  
Time Series Data Analysis ◽  
Trade And Investment

The objective of this paper is to examine the effects of international trade and investment related macro economic variables, namely, exports, imports and FDI inflows on the outflows of FDI from India over 1970 through 2005. Using time series data analysis, the empirical part of the paper finds unidirectional Granger Causality from export and import to FDI outflows but no such causality exists from FDI inflows to the corresponding outflows from India. Results confirm the assumption that lagged imports and exports are a driving force of ing front.

HUBUNGAN KAUSALITAS HARGA JUAL DAN HARGA SEWA APARTEMEN DI JABODETABEK

2021 ◽  
Vol 1 (1) ◽  
pp. 93-105
Author(s):  
Zainal Zawir Simon ◽  
Effendy Zain ◽  
Zulihar Zulihar
Keyword(s):  
Time Series ◽  
Granger Causality ◽  
Time Series Data ◽  
Investment Analysis ◽  
Series Data ◽  
Analysis Tool ◽  
Selling Price ◽  
Causality Analysis ◽  
Granger Causality Analysis ◽  
Causality Relationship

Abstrak Penelitian ini bertujuan untuk mengetahui hubungan kausalitas antara harga jual apartemen dan harga sewa apartemen di wilayah Jabodetabek. Data yang dipergunakan adalah data  time series dalam bentuk kuartalan untuk periode 2007:1-2018:3 dan alat analisis yang dipergunakan adalah analisa kausalitas Granger. Hasil penelitian menunjukkan bahwa tidak terdapat hubungan kausalitas antara harga jual apartemen dan harga sewa apartemen di wilayah Jabodetabek. Dengan kata lain perubahan harga jual  tidak mempengaruhi harga sewa. Sebaliknya harga sewa juga tidak mempengaruhi harga jual apartemen. Dengan demikian Investor diharapkan dalam melakukan analisis investasinya memasukkan faktor-faktor lain yang dapat mempengaruhi harga jual dan harga sewa untuk apartemen, agar terlepas dari pandangan bahwa harga jual mempengaruhi harga sewa dan sebaliknya.Kata Kunci : Harga Jual apartemen, Harga Sewa Apartemen, Data Runtut Waktu, Analisa Kausalitas GrangerABSTRACTThis study aims to determine the causality relationship between the selling price of apartments and apartment rental prices in the Greater Jakarta area. The data used are time series data in quarterly form for the period 2007: 1-2018: 3 and the analysis tool used is the Granger causality analysis. The results showed that there was no causality relationship between apartment selling prices and apartment rental prices in the Greater Jakarta area. In other words, changes in selling prices do not affect rental prices. Conversely the rental price also does not affect the selling price of the apartment. Thus Investors are expected to carry out investment analysis to include other factors that can affect the selling price and rental price for an apartment, so that regardless of the view that the selling price affects the rental price and vice versa.Keywords : Selling Price of apartments, rental prices apartments, time series data, Granger Causality Analysis

Predicting microbial interactions from time series data with network information

2017 ◽  
Vol 17 (2) ◽  
pp. 97
Author(s):  
Yan Wang ◽  
Mingzhi Mao ◽  
Fang Li ◽  
Wenping Deng ◽  
Shaowu Shen ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Microbial Interactions ◽  
Series Data ◽  
Network Information

Development and Terrorism in Nigeria: Co-Integration and Causality Analysis of Macroeconomic Factors

2018 ◽  
Vol 2 (1) ◽  
pp. 1-33
Author(s):  
Emmanuel O. Okon
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Trade Openness ◽  
Private Investment ◽  
Series Data ◽  
Causality Analysis ◽  
Macroeconomic Policies ◽  
Macroeconomic Factors ◽  
The Government ◽  
Adf Test

This paper is a cointegration and causality analysis of macroeconomic factors and terrorism in Nigeria using time series data spanning between 1970 and 2016. The stochastic characteristics of each time series was examined using Augmented Dickey Fuller (ADF) test. The result reveals that LOG(GOVX), LOG(INTR), POLX, DLOG(GDPC) and DLOG(OPEN) were in line with the apriori expectation. With this development, some recommendations were made amongst which are that trade openness rate should be all time kept at peak benchmark by adopting tight trade openness while strategic macroeconomic policies should be instituted in order to encourage domestic private investment to enhance the growth of the economy. Nigerian political system has to be stabilized and the government should step up its intelligence gathering capacity as well as training security agents to forcefully combat terrorist group.

Predicting microbial interactions from time series data with network information

2017 ◽  
Vol 17 (2) ◽  
pp. 97
Author(s):  
Fang Li ◽  
Shaowu Shen ◽  
Xingpeng Jiang ◽  
Yan Wang ◽  
Mingzhi Mao ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Microbial Interactions ◽  
Series Data ◽  
Network Information
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