De Vita and Trachanas's (hereafter DV-T, 2016) paper published in (Energy Economics, Volume 56, May 2016, pages, 150-160) criticizes Bal and Rath's paper (Energy Economics, Volume 51, September 2015, pages, 149-156) (hereafter, BR, 2015) by undertaking a â€˜pure replication' and a â€˜reanalysis' using (BR, 2015) data set. The aim of this paper is to reassess (BR, 2015) by providing comments and additional evidence. We revisit (BR, 2015) with the aim of applying additional unit root, cointegration and nonlinear causality tests. The results derived from these supplementary tests clearly reveal that the oil price series is non-stationary at level. The bivariate noisy Mackey-Glass model proposed by Kyrtsou and Terraza (2003) reveals bi-directional non-linear causality exists between real oil price and exchange rate in case of China, whereas for India, only unidirectional nonlinear causality running from oil price to exchange rate.

Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India - A Reassessment

Solid oxide fuel cell (SOFC) performance evaluation, fault diagnosis and health control: A review

Hydrochar derived from municipal sludge through hydrothermal processing: A critical review on its formation, characterization, and valorization.

An Emerged Challenge of Air Pollution and Ever-Increasing Particulate Matter in Pakistan; A Critical Review.

Deep reinforcement learning control of electric vehicle charging in the presence of photovoltaic generation

Geopolitical factors are considered a crucial factor that makes a difference in crude oil prices. Over the last three decades, many political events occurred frequently, causing short-term fluctuations in crude oil prices. This paper aims to examine the dynamic correlation and causal link between geopolitical factors and crude oil prices based on data from June 1987 to February 2020. By using a time-varying copula approach, it is shown that the correlation between geopolitical factors and crude oil prices is strong during periods of political tensions. The GPA (geopolitical acts) index, as the real factor, drives the rise in prices of crude oil. Moreover, the dynamic correlation between geopolitical factors and crude oil prices shows strong volatility over time during periods of political tensions. We also found unidirectional causality running from geopolitical factors to crude oil prices by using the Granger causality test.

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Do Tense Geopolitical Factors Drive Crude Oil Prices

Three-dimensional stability assessments of a non-circular tunnel face reinforced by bolts under seepage flow conditions

Transition metal phosphides/phosphates (TMPs) are considered appealing electrode materials in energy-related fields, especially in supercapacitors. However, the dilemma of inadequate electrode kinetics and dimensional unreliability evoked by a huge volume variation during cycling significantly plagues their progress. To mitigate this issue, in this work, a 3D cross-network in situ assembled via self-derived N-doped carbon hybrid Ni-Co-P/POx 2D sheets is fabricated. Particularly, high-Fermi-level N-doped carbon well confines Ni-Co-P/POx nanoparticles at the molecular level, and N-doping leads to redistribution of spin/electron density in the carbon skeleton, effectively regulating the electron environment of nearby Ni-Co-based moieties, resulting in a relatively lower surface work function, as known via experimental and Kelvin probe force microscopy (KPFM) results, which favors electron flee from the electrode surface and facilitates electron transport toward a rapid supercapacitor response. Moreover, the well-defined 3D cross-network architectures featured with in-plane pores and interconnected with each other can provide more ion/electron transfer pathways and 2D sheets with excellent surface chemistry available for sustainable ion/electron mobility, synergistically affording the favorable electrode kinetics. Accordingly, the resultant Ni-Co-P/POx@NC electrode shows admirable specific capacitance, excellent rate survivability, and long-term cyclability. The as-assembled asymmetric device exhibits remarkable energy and power outputs (48.5 Wh kg-1 and 7500 W kg-1), superior to many reported devices. Furthermore, our devices possess the prominent ability to power a commercial electronic thermometer for 1560 s at least, showcasing superb application prospects.

Towards High-Performance Supercapacitor Electrodes via Achieving 3D Cross-Network and Favorable Surface Chemistry.

Abstract We use the state space model to describe the financial cycles of China and G7 countries since 1990, and the DY spillover index to quantify the spillover effects of China's financial cycles on G7 countries. We find that China plays the role of a net recipient most of the time. China's financial cycle net spillover index fluctuates widely and is vulnerable to economic events such as the financial crisis. This implies that international capital flows have brought volatility and shocks to the Chinese financial market, such as the Asian financial crisis and the 2008 international financial crisis. In addition, during 2004-2005 and 2014-2015, the G7 countries also suffered from financial cycle spillover from China. The US received most of the financial cycle spillover from China, followed by Canada, Germany, and Italy.

https://www.tandfonline.com/doi/pdf/10.1080/1331677X.2021.2025123?needAccess=true

Does China transmit financial cycle spillover effects to the G7 countries?

This study aims to address debate in previous studies on whether AI has a positive or negative effect on carbon emission reduction. We used quantile regression and PSTR models to study the diverse impacts of AI on carbon emissions in 66 countries from 1993–2019. There were three main findings in this paper. First, the impact of AI on carbon emissions varies across countries, and its effect on carbon reduction is mainly found in high-carbon emission and high-income countries. Second, the industrial structure environment of different countries affects the role of AI in carbon reduction, with its marginal effect in limiting emissions decreasing with the rise of secondary industrial structures. Third, the impact of AI varies in countries based on their different demographic structures. The marginal effect of AI on carbon emission reduction increases in places with older populations. This study offers unique insight into the heterogeneous impact of AI on CO2 emissions. Our analysis confirms the importance of industrial and demographic structures in promoting carbon emission reduction. We provide effective policy recommendations for economic development and environmental governance. 

Junhao Zhong

Papers

Do Tense Geopolitical Factors Drive Crude Oil Prices

Three-dimensional stability assessments of a non-circular tunnel face reinforced by bolts under seepage flow conditions

Towards High-Performance Supercapacitor Electrodes via Achieving 3D Cross-Network and Favorable Surface Chemistry.

Does China transmit financial cycle spillover effects to the G7 countries?

The impact of AI on carbon emissions: evidence from 66 countries