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Open Access
Article
Publication date: 15 March 2024

Anis Jarboui, Emna Mnif, Nahed Zghidi and Zied Akrout

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance…

Abstract

Purpose

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

Design/methodology/approach

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Findings

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Originality/value

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

Details

Arab Gulf Journal of Scientific Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1985-9899

Keywords

Article
Publication date: 12 January 2024

Kai Xu, Ying Xiao and Xudong Cheng

The purpose of this study is to investigate the effects of nanoadditive lubricants on the vibration and noise characteristics of helical gears compared with conventional…

Abstract

Purpose

The purpose of this study is to investigate the effects of nanoadditive lubricants on the vibration and noise characteristics of helical gears compared with conventional lubricants. The experiment aims to analyze whether nanoadditive lubricants can effectively reduce gear vibration and noise under different speeds and loads. It also analyzes the sensitivity of the vibration reduction to load and speed changes. In addition, it compares the axial and radial vibration reduction effects. The goal is to explore the application of nanolubricants for vibration damping and noise reduction in gear transmissions. The results provide a basis for further research on nanolubricant effects under high-speed conditions.

Design/methodology/approach

Helical gears of 20CrMnTi were lubricated with conventional oil and nanoadditive oils. An open helical gearbox with spray lubrication was tested under different speeds (200–500 rpm) and loads (20–100 N·m). Gear noise was measured by a sound level meter. Axial and radial vibrations were detected using an M+P VibRunner system and fast Fourier transform analysis. Vibration spectrums under conventional and nanolubrication were compared. Gear tooth surfaces were observed after testing. The experiment aimed to analyze the noise and vibration reduction effects of nanoadditive lubricants on helical gears and the sensitivity to load and speed.

Findings

The key findings are that nanoadditive lubricants significantly reduce the axial and radial vibrations of helical gears under low-speed conditions compared with conventional lubricants, with a more pronounced effect on axial vibrations. The vibration reduction is more sensitive to rotational speed than load. At the same load and speed, nanolubrication reduces noise by 2%–5% versus conventional lubrication. Nanoparticles change the friction from sliding to rolling and compensate for meshing errors, leading to smoother vibrations. The nanolubricants alter the gear tooth surfaces and optimize the microtopography. The results provide a basis for exploring nanolubricant effects under high speeds.

Originality/value

The originality and value of this work is the experimental analysis of the effects of nanoadditive lubricants on the vibration and noise characteristics of hard tooth surface helical gears, which has rarely been studied before. The comparative results under different speeds and loads provide new insights into the vibration damping capabilities of nanolubricants in gear transmissions. The findings reveal the higher sensitivity to rotational speed versus load and the differences in axial and radial vibration reduction. The exploration of nanolubricant effects on gear tribological performance and surface interactions provides a valuable reference for further research, especially under higher speed conditions closer to real applications.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0220/

Details

Industrial Lubrication and Tribology, vol. 76 no. 2
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 12 March 2024

Shuowen Yan, Pu Xue, Long Liu and M.S. Zahran

This study aims to investigate the design and optimization of landing gear buffers to improve the landing-phase comfort of civil aircraft.

Abstract

Purpose

This study aims to investigate the design and optimization of landing gear buffers to improve the landing-phase comfort of civil aircraft.

Design/methodology/approach

The vibration comfort during the landing and taxiing phases is calculated and evaluated based on the flight-testing data for a type of civil aircraft. The calculation and evaluation are under the guidance of the vibration comfort standard of GB/T13441.1-2007 and related files. The authors establish here a rigid-flexible coupled multibody dynamics finite element model of one full-size aircraft. Furthermore, the authors also implement a dynamic simulation for the landing and taxiing processes. Also, an analysis of how the main parameters of the buffers affect the vibration comfort is presented. Finally, the optimization of the single-chamber and double-chamber buffers in the landing gear is performed considering vibration comfort.

Findings

The double-chamber buffer with optimized parameters in landing gear can improve the vibration comfort of the aircraft during the landing and taxiing phases. Moreover, the comfort index can be increased by 25.6% more than that of a single-chamber type.

Originality/value

To the best of the authors’ knowledge, this study first investigates the evaluation methods and evaluation indexes on the aircraft vibration comfort, then further conducts the optimization of the parameters of landing gear buffer with different structures, so as to improve the comfort of aircraft passengers during landing process. Most of the current studies on aircraft landing gear have focused on the strength and safety of the landing gear, with very limited research on cabin vibration comfort during landing and subsequent taxiing because of the coupling of runway surface unevenness and airframe vibration.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 6 March 2023

Gaytri Malhotra, Miklesh Prasad Yadav, Priyanka Tandon and Neena Sinha

This study unravels an attempt to investigate the dynamic connectedness of agri-commodity (wheat) of Russia with 10 financial markets of wheat importing counties during the…

Abstract

Purpose

This study unravels an attempt to investigate the dynamic connectedness of agri-commodity (wheat) of Russia with 10 financial markets of wheat importing counties during the Russia–Ukraine invasion.

Design/methodology/approach

This study took the daily prices of Wheat FOB Black Sea Index (Russia) along with stock indices of 10 major wheat-importing nations of Russia and Ukraine. The time frame for this study ranges from February 24, 2022 to July 31, 2022. This time frame was selected since it fully examines all of the effects of the crisis. The conditional correlations and volatility spillovers of these indices are predicted using the DCC-GARCH model, Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) models.

Findings

It is found that there is dynamic linkage of agri-commodity of with stock markets of Iraq, Pakistan and Tanzania in short run while stock markets of Egypt, Turkey, Bangladesh, Pakistan, Brazil and Iraq are spilled by agri-commodity in long run. In addition, it documents that there is large spillover in short run than medium and long run comparatively. This signifies that investors have more diversification opportunity in short run then long run contemplating to invest in these markets.

Originality/value

To the best of the authors’ understanding this is the first study to undertake the dynamic linkage of agri-commodity (wheat) of Russia with financial market of select importing counties during the Russia–Ukraine invasion.

Details

Benchmarking: An International Journal, vol. 31 no. 2
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 5 May 2022

Dat Van Truong, Song Thanh Quynh Le and Huong Mai Bui

Kapok was well-known for its oleophilic properties, but its mechanical properties and morphology impeded it from forming suitable absorbent materials. This study aims to…

Abstract

Purpose

Kapok was well-known for its oleophilic properties, but its mechanical properties and morphology impeded it from forming suitable absorbent materials. This study aims to demonstrate the process of creating an oil-absorbent web from a blend of treated kapok and polypropylene fibers.

Design/methodology/approach

Kapok fibers were separated from dried fruits, then the wax was removed with an HCl solution at different concentrations. The morphological and structural changes of these fibers were investigated using scanning electron microscopy images. The blending ratios of kapok and polypropylene fibers were 60/40, 70/30 and 80/20, respectively. The fiber blends were fed to a laboratory carding machine to form a web and then consolidated using the heat press technique. The absorption behavior of the formed web was evaluated regarding oil absorption capacity and oil retention capacity according to ASTM 726.

Findings

The results showed that the HCl concentration of 1.0% (wt%) gave the highest wax removal efficiency without damaging the kapok fibers. This study found that oil absorbency is influenced by the fiber blending ratio, web tensile strength and elongation, porosity, oil type and environmental conditions. The oil-absorbency of the web can be re-used for at least 20 cycles.

Research limitations/implications

This study only looked at three types of oils: diesel, kerosene and vegetable oils.

Practical implications

When the problem of oil spills in rivers and seas is growing and causing serious environmental and economic consequences, using physical methods to recover oil spills is the most effective solution.

Originality/value

This research adds to the possibility of using kapok fiber in the form of a web of non-woven fabric for practical purposes.

Details

Research Journal of Textile and Apparel, vol. 28 no. 1
Type: Research Article
ISSN: 1560-6074

Keywords

Open Access
Article
Publication date: 31 March 2023

Nguyen Hong Yen and Le Thanh Ha

This paper aims to study the interlinkages between cryptocurrency and the stock market by characterizing their connectedness and the effects of the COVID-19 crisis on their…

1022

Abstract

Purpose

This paper aims to study the interlinkages between cryptocurrency and the stock market by characterizing their connectedness and the effects of the COVID-19 crisis on their relations.

Design/methodology/approach

The author employs a quantile vector autoregression (QVAR) to identify the connectedness of nine indicators from January 1, 2018, to December 31, 2021, in an effort to examine the relationships between cryptocurrency and stock markets.

Findings

The results demonstrate that the pandemic shocks appear to have influences on the system-wide dynamic connectedness. Dynamic net total directional connectedness implies that Bitcoin (BTC) is a net short-duration shock transmitter during the sample. BTC is a long-duration net receiver of shocks during the 2018–2020 period and turns into a long-duration net transmitter of shocks in late 2021. Ethereum is a net shock transmitter in both durations. Binance turns into a net short-duration shock transmitter during the COVID-19 outbreak before receiving net shocks in 2021. The stock market in different areas plays various roles in the short run and long run. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the most severe impact at the beginning of 2020.

Practical implications

Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets.

Originality/value

The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages between these two markets.

研究目的

本學術論文擬透過找出加密貨幣與股票市場兩者相互關聯之特徵,來探討這個聯繫;文章亦擬探究2019冠狀病毒病全球大流行對這相互關聯的影響。

研究設計/方法/理念

作者以分量向量自我迴歸法、來找出2018年1月1日至2021年12月31日期間九個指標的關聯,藉此探討加密貨幣與股票市場之間的關係。

研究結果

研究結果顯示,全球大流行的驚愕,似對全系統動態關聯產生了影響。動態總淨值定向關聯暗示了就我們的樣本而言,比特幣是一個純短期衝擊發送器。比特幣在2018年至 2020年期間是一個衝擊的長期純接收器,並進而於2021年年底成為一個衝擊的長期純發送器。以太坊則為短期以及長期之純衝擊發送器。幣安在2019冠狀病毒病爆發期間,在2021年接收純衝擊前、成為一個純短期衝擊發送器。位於不同地區的股票市場,無論在短期抑或長期而言均扮演各種不同的角色。在2019冠狀病毒病全球大流行的驚愕期間,成對的關聯顯示了加密貨幣可以以2020年年初最嚴重的影響去解釋和說明股票市場的波動。

實務方面的啟示

研究結果使我們能深入認識有關的市場之間不同情緒和看法的蔓延所帶來的影響的主要先例,這些知識、亦能幫助決策者制定適當的政策,以減少有關的市場的弱點,並把這些市場間的風險和不確定性的散播減到最低。

研究的原創性/價值

作者是首位研究加密貨幣與股票市場之間的相互關聯的學者,亦是首位學者、去評估像2019冠狀病毒病健康危機的不確定事件,會如何影響有關的兩個市場之間的動態相互關聯。

Details

European Journal of Management and Business Economics, vol. 33 no. 1
Type: Research Article
ISSN: 2444-8451

Keywords

Article
Publication date: 21 February 2024

Shuifeng Hong, Yimin Luo, Mengya Li and Duoping Yang

This paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk…

Abstract

Purpose

This paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.

Design/methodology/approach

With daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.

Findings

The empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.

Originality/value

The MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.

Details

The Journal of Risk Finance, vol. 25 no. 2
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 20 March 2024

Malav R. Sanghvi, Karan W. Chugh and S.T. Mhaske

This study aims to synthesize Prussian blue {FeIII4[FeII(CN)6]3} pigment by reacting ferric chloride with different ferrocyanides through the same procedure. The influence of the…

Abstract

Purpose

This study aims to synthesize Prussian blue {FeIII4[FeII(CN)6]3} pigment by reacting ferric chloride with different ferrocyanides through the same procedure. The influence of the ferrocyanide used on resulting pigment properties is studied.

Design/methodology/approach

Prussian blue is commonly synthesized by direct or indirect methods, through iron salt and ferrocyanide/ferricyanide reactions. In this study, the direct, single-step process was pursued by dropwise addition of the ferrocyanide into ferric chloride (both as aqueous solutions). Two batches – (K-PB) and (Na-PB) – were prepared by using potassium ferrocyanide and sodium ferrocyanide, respectively. The development of pigment was confirmed by an identification test and characterized by spectroscopic techniques. Pigment properties were determined, and light fastness was observed for acrylic emulsion films incorporating dispersed pigment.

Findings

The two pigments differed mainly in elemental detection owing to the dissimilar ferrocyanide being used; IR spectroscopy where only (Na-PB) showed peaks indicating water molecules; and bleeding tendency where (K-PB) was water soluble whereas (Na-PB) was not. The pigment exhibited remarkable blue colour and good bleeding resistance in several solvents and showed no fading in 24 h of light exposure though oil absorption values were high.

Originality/value

This article is a comparative study of Prussian blue pigment properties obtained using different ferrocyanides. The dissimilarity in the extent of water solubility will influence potential applications as a colourant in paints and inks. K-PB would be advantageous in aqueous formulations to confer a blue colour without any dispersing aid but unfavourable in systems where other coats are water-based due to their bleeding tendency.

Details

Pigment & Resin Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 19 October 2022

Fatimah A.M. Al-Zahrani

This paper aims to prepare a new donor–π–acceptor (D–π–A) and acceptor–π– D–π–A (A–π–D–π–A) phenothiazine (PTZ) in conjugation with vinyl isophorone (PTZ-1 and PTZ-2) were…

Abstract

Purpose

This paper aims to prepare a new donor–π–acceptor (D–π–A) and acceptor–π– D–π–A (A–π–D–π–A) phenothiazine (PTZ) in conjugation with vinyl isophorone (PTZ-1 and PTZ-2) were designed and their molecular shape, electrical structures and characteristics have been explored using the density functional theory (DFT). The results satisfactorily explain that the higher conjugative effect resulted in a smaller high occupied molecular orbital–lowest unoccupied molecular orbital gap (Eg). Both compounds show intramolecular charge transfer (ICT) transitions in the ultraviolet (UV)–visible range, with a bathochromic shift and higher absorption oscillator strength, as determined by DFT calculations.

Design/methodology/approach

The produced PTZ-1 and PTZ-2 sensors were characterized using various spectroscopic methods, including Fourier-transform infrared spectroscopy and nuclear magnetic resonance spectroscopy (1H/13CNMR). UV–visible absorbance spectra of the generated D–π–A PTZ-1 and A–π–D–π–A PTZ-2 dyes were explored in different solvents of changeable polarities to illustrate positive solvatochromism correlated to intramolecular charge transfer.

Findings

The emission spectra of PTZ-1 and PTZ-2 showed strong solvent-dependent band intensity and wavelength. Stokes shifts were monitored to increase with the increase of the solvent polarity up to 4122 cm−1 for the most polar solvent. Linear energy-solvation relationship was applied to inspect solvent-dependent Stokes shifting. Quantum yield (ф) of PTZ-1 and PTZ-2 was also explored. The maximum UV–visible absorbance wavelengths were detected at 417 and 419 nm, whereas the fluorescence intensity was monitored at 586 and 588 nm.

Originality/value

The PTZ-1 and PTZ-2 dyes leading to colorimetric and emission spectral changes together with a color shift from yellow to red.

Details

Pigment & Resin Technology, vol. 53 no. 3
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 12 April 2022

Monica Puri Sikka, Alok Sarkar and Samridhi Garg

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been…

1184

Abstract

Purpose

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been discussed in this review. Scientists have linked the underlying structural or chemical science of textile materials and discovered several strategies for completing some of the most time-consuming tasks with ease and precision. Since the 1980s, computer algorithms and machine learning have been used to aid the majority of the textile testing process. With the rise in demand for automation, deep learning, and neural networks, these two now handle the majority of testing and quality control operations in the form of image processing.

Design/methodology/approach

The state-of-the-art of artificial intelligence (AI) applications in the textile sector is reviewed in this paper. Based on several research problems and AI-based methods, the current literature is evaluated. The research issues are categorized into three categories based on the operation processes of the textile industry, including yarn manufacturing, fabric manufacture and coloration.

Findings

AI-assisted automation has improved not only machine efficiency but also overall industry operations. AI's fundamental concepts have been examined for real-world challenges. Several scientists conducted the majority of the case studies, and they confirmed that image analysis, backpropagation and neural networking may be specifically used as testing techniques in textile material testing. AI can be used to automate processes in various circumstances.

Originality/value

This research conducts a thorough analysis of artificial neural network applications in the textile sector.

Details

Research Journal of Textile and Apparel, vol. 28 no. 1
Type: Research Article
ISSN: 1560-6074

Keywords

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