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Over the past decade, plant extracts are ultimate green candidatures to substitute the expensive and noxious synthetic corrosion inhibitors. In this regard, this study aims to focus on evaluating anti-corrosion properties of green inhibitor Cyperus rotundus (C. rotundus), a perennial herb found throughout India.

The biocompatible components present in C. rotundus extract was analyzed by gas chromatography–mass spectroscopy analysis. The corrosion inhibitory effect of C. rotundus was assessed by impedance, polarization and surface morphometric study [atomic force microscopy (AFM)]. Density functional theory (DFT) study was carried using DFT/B3LYP, and basis set used for calculations was 6-31G (d, p) using Gaussian 03 program package.

Predominant components such as octadecanoicacid, ethylester, n-hexadecanoic acid, pentanoicacid-4-oxoethyl ester, cyclotrisiloxane, hexamethyl, cyclotetrasiloxane and octamethyl were identified from the extract of C. rotundus. Impedance study demonstrated that the addition of inhibitor reduces the double-layer capacitance and increases the charge transfer resistance. Furthermore, polarization studies indicated that the extract of C. rotundus acted as a mixed-type inhibitor with decrease in corrosion current density with increase in concentration. AFM study evinced the formation of inhibitor film on mild steel surface. The donor–acceptor interactions of active sites of predominant phytoconstituents were substantiated by computational analysis (DFT).

This paper deals with the inhibition effect of extract of C. rotundus on mild steel in 0.5M H₂SO₄. C. rotundus has a capability to adsorb on the metal surface, thus hindering corrosion.

The emerging markets are facing a lot of risks and disruptions across their supply chains (SCs) due to the deadly coronavirus disease 2019 (COVID-19) pandemic. To mitigate the significant post-COVID-19 consequences, organizations should modify their existing strategies and focus more on the key flexible sustainable SC (SSC) strategies. Still now, a limited number of studies have highlighted about the flexible strategies what firms should adopt to reduce the rampant effects in the context of emerging markets.

This study presents an integrated approach including Delphi method, Bayesian, and the Best-Worst-Method (BWM) to identify, assess and evaluate the importance of the key flexible SSC strategies for the footwear industry in the emerging market context.

The results found the manufacturing flexibility through automation integration as the most important flexible SSC strategy to improve the flexibility and sustainability of modern SCs. Also, developing omni-channel distribution and retailing strategies and increasing the level of preparedness by using artificial intelligent are crucial strategies for overcoming the post-COVID-19 impacts.

The novelty of this research is that the research connects a link among flexible strategies, SCs sustainability, and the impacts of the COVID-19 pandemic. Moreover, the research proposes a novel and intelligent framework based on Delphi and Bayesian-BWM to identify and analyze the key flexible SSC strategies to build up sustainable and robust SCs which can withstand in the post-COVID-19 world.

The aim of this paper was to investigate the corrosion inhibition potential of two synthesized benzothiazines, namely, 3,4-dihydro-2-methoxycarbonylmethyl-3-oxo-2H-1,4-benzothiazine (1) and ethyl 3-oxo-3,4-dihydro-2H-1,4-benzothiazine-2-carboxylate (2) on mild steel corrosion in 1M H₂SO₄.

Corrosion inhibition efficiency (IE%) was studied by weight loss measurements, potentiodyanmic polarization method, alternating current (AC) impedance spectroscopy, fourier transform infrared (FT-IR) spectroscopy and scanning electron microscopy. Quantum chemical approach was used to complement the experimental results.

The results obtained show that the IE% increased with inhibitor concentration and follow the order 2 > 1, obeying Langmuir adsorption isotherm. The calculated quantum chemical indices were consistent with experimental results.

This paper provides information on the inhibitive properties of new set of benzothiazines on mild steel corrosion in 1M H₂SO₄.

The study aims to find new anticorrosive components from a plant source, namely, Pachysandra terminalis Sieb. et Zucc. (P. terminalis), a traditional medicinal shrub predominantly used by Tujia people.

Because phenolic components from plants are known for its numerous values in several fields, the corrosion inhibitive ability of P. terminalis extract was analyzed by electrochemical studies (polarization, electrochemical impedance spectroscopy) and surface examination (by scanning electron microscopy [SEM], energy-dispersive X-ray spectroscopy [EDX] and atomic force microscopy [AFM]).

The examination of total phenolic content (TPC), total flavonoids content (TFC) and individual phenols (UHPLC) showed the presence of 85.21 mg/g (TPC), 25.38 mg/g (TFC), protocatechuic acid (62.10 µg/g), gentisic acid (60.21µg/g), rutin (50.12 µg/g), kaempferol (46.58 µg/g) and p-Coumaric acid (42.35µg/g) . The polarization study shows that the maximum shift is (16 mV), imposing a mixed mode of inhibition, dominantly anodic. The surface morphology studies by SEM, EDX and AFM confirmed the adsorption of phytochemical components on the low carbon steel surface blocking the active sites.

The study unveils the inhibitive nature of P. terminalis, preventing aggressive attack by 0.5 M HCl on low carbon steel. This also exhibits few phenols present in methanolic leaf extract which may be the role player of corrosion inhibition.

The purpose of this paper is to investigate the relationships between personality, motivating factors and herding behaviour of individual investors. Investors’ personality has been classified consonant to the personality traits (compliant, aggressive and detached) encapsulated in Horney’s tripartite model.

To carry out this study, the author surveyed 363 individual investors of the Indian stock market using a structured questionnaire. Structural equation modelling is used to empirically test the relationships between personality, three motivating factors (cognitive capability, emotional factors and social factors) and herding behaviour.

The result reveals that, expect compliant personality, none shows proclivity towards herding behaviour. Investors possessing compliant personality are more influenced by social motivating factors; however, cognitive factor motivates aggressive personality, inhibiting herding behaviour. Furthermore, investors having detached personality are not influenced by any motivating factors of herding.

The limitation is the difficulty in generalizing the results to overall country populations as the Indian stock market has a huge turnover every day, and the author’s survey consisted of only small sample of individual investors.

The outcomes of this study could possibly unveil a new insight to discern the behaviour of individual investors in the Indian stock market.

The influences of personality on investment choices have been investigated before, but the influence of personality specifically on herding behaviour has not being adequately investigated in an emerging economy like India, as very scanty literature is available on the influence of personality on herding behaviour. The study addresses this gap and further explores the association of personality with different motivating factors that cause herding bias.

In the recent dynamic market, supply chain disruptions are rapidly increasing with varied customer demand, technological changes, uncertain pandemic events etc. To overcome the unexpected disruptions, supply chain of each business should be resilient and pharmaceutical supply chain (PSC) is no exception. Motivated by the challenges and unexpected pandemic disruptions, this paper aims to examine the performance indicators (PIs) of the resilient PSC and to predict the resilience level for a certain time period in the context of Bangladesh.

The aim of this paper presents a structured framework based on the Delphi method, fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and system dynamics (SD). The proposed methodology was validated using expert's inputs from the relevant field in Bangladesh. This study reveals the influential relationships of indicators and resilience level using fuzzy DEMATEL and SD to improve the resiliency.

Findings revealed that “Supply chain risk orientation”, “Visibility”, “Flexibility”, “Agility in supply chain” and “Collaboration” are the top five influential performance indicators for resilient PSC. The cause and effect relationship found that “IT capability”, “Flexibility”, “Supply chain network design”, “Resource availability”, “Supply chain risk orientation” and “Velocity” were in cause category which play a vital role for establishing resilient supply chain. SD approach has developed a model for predicting the resilience level of the supply chain.

This work is one of the initial contributions in the literature that has targeted on the identification and analysis of the significant PIs and predicting the resilience level of the PSC.

The recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic has severely disrupted the operations of global supply chains (SCs) providing an opportunity for decision-makers to rethink and tune their existing strategies. To tackle the impacts caused by such a pandemic, this study aims to examine the contextual relations among the factors influencing supply chain viability (SCV) for achieving long-term Sustainable Development Goals (SDGs).

A decision-aid approach by integrating Pareto analysis, grey theory and total interpretive structural modeling (TISM) has been propounded. The proposed approach examines contextual relations among the factors for SCV for small and medium-sized enterprises (SMEs) in an emerging economy. This study contributes to theory, methodology and practice by exploring a new research problem in the context of the SCV and COVID-19 pandemic and by developing a new decision-aid approach.

The findings reveal that the creation of SC digital twin and transformation of SCs to supply networks would help the policymakers to deal with the “new normal.” Also, SC crowdfunding and policy development for health protocols are critical driving factors influencing SCV.

This research work is perhaps one of few initial attempts to advance the theoretical and practical understanding of SCV and to achieve SDGs in industries following a pandemic risk.

A new control method is proposed for grid integration of improved hybrid three quasi z source converter (IHTQZSC). The proposed controller provides a constant switching frequency with an improved dynamic response with fewer computations. The proposed constant switching frequency predictive controller (CSF-PC) does not need weighting factors and reduces the complexity of the control circuit.

A single PI controller is intended to control voltage across dc-link by generating the necessary shoot-through duty ratio. The predictive controller produces the modulating signals required to inject the desired grid current. The performance of the proposed controller is validated with MATLAB/Simulink software.

The discrete-time instantaneous model on the grid side in the proposed controller influences the inductor current with minimum ripples. Dynamic response and computational complexity of the converter with the PI controller, finite set model predictive controller (FS-MPC) and the proposed controller are discussed.

The converter belongs to impedance source converters (ISC) family, delivers higher voltage gain in a single-stage power conversion process, extract the energy from the intermittent nature of renewable energy conversion systems. Implementing CSF-PC for ISC is simple, as it has a single PI controller.

Grid integration of high voltage gain IHTQZSC is accomplished with PI, FS-MPC and CSF-PC. Though the FS-MPC exhibits superior dynamic response under input voltage disturbance and grid current variation, total harmonic distortion (THD) in the grid current is high. CSF-PC provides better THD with a good dynamic response with reduced inductor current ripples.

The purpose of this paper is to present the Switched Inductor Z-Source Inverter (SLZSI) topology for three-phase on-line uninterruptible power supply (UPS) by employing third harmonic injected maximum constant boost pulse width modulation (PWM) control. Conventional UPS consists of step-up transformer or boost chopper along with voltage source inverter (VSI) which reduces the efficiency and increases energy conversion cost. The proposed three-phase UPS by using SLZSI has the voltage boost capability through shoot through zero state which is not available in traditional VSI and current source inverter.

Performance of three-phase on-line UPS based on ZLZSI by using third harmonic injected maximum constant boost PWM control is analyzed and evaluated in MATLAB/Simulink software and the results are compared with Z-source inverter (ZSI) fed UPS. Experimental results are presented for the validation of the simulation and theoretical analysis.

The output voltages, currents, THD values, voltage stress and efficiencies for different loading condition are determined and compared with the theoretical values and UPS with ZSI. The experimental results validate the theoretical and simulation results.

Compared with the traditional ZSI, the SLZSI provides high-voltage boost inversion ability with a very short shoot through zero state. This proposed UPS by using SLZSI increases the efficiency with less number of components, reduces the harmonics, increases the voltage gain and reduces the voltage stress.

The purpose of this paper is to examine the impact of carbon permit allocation rules (grandfathering mechanism and benchmarking mechanism) on incentive contracts provided by the retailer to encourage the manufacturer to invest more in reducing carbon emissions.

The authors consider a two-echelon supply chain in which the retailer offers three contracts (wholesale price contract, cost-sharing contract and revenue-sharing contract) to the manufacturer. Based on the two carbon permit allocation rules, i.e. grandfathering mechanism and benchmarking mechanism, six scenarios are examined. The optimal price and carbon emission reduction decisions and members’ equilibrium profits under six scenarios are analyzed and compared.

The results suggest that the revenue-sharing contract can more effectively stimulate the manufacturer to reduce carbon emissions compared to the cost-sharing contract. The cost-sharing contract can help to achieve the highest environmental performance, whereas the implementation of revenue-sharing contract can attain the highest social welfare. The benchmarking mechanism is more effective for the government to prompt the manufacturer to produce low-carbon products than the grandfathering mechanism. Although a loose carbon policy can expand the total emissions, it can improve the social welfare.

These results can provide operational insights for the retailer in how to use incentive contract to encourage the manufacturer to curb carbon emissions and offer managerial insights for the government to make policy decisions on carbon permit allocation rules.

This paper contributes to the literature regarding to firm’s carbon emissions reduction decisions under cap-and-trade policy and highlights the importance of carbon permit allocation methods in curbing carbon emissions.