Supercapacitors are widely used energy storage systems in the modern world due to their excellent electrochemical performance, fast charging capability, easy handling, and high power density. In the ...present work, pure MoS2 and MoS2/Bi2S3 nanocomposites with different compositions of bismuth were synthesized by the hydrothermal method. The structural properties of the electrode materials were studied using the XRD technique, which confirmed the formation of MoS2 and the secondary phase of Bi2S3 while increasing Bi substitution. The morphological studies of the synthesized electrode materials were performed using SEM, TEM, and HRTEM techniques, which indicated the 3D layered hierarchical structure of MoS2 nanospheres and the nanosheet-like structure of Bi2S3. The electrochemical properties of pristine MoS2 and MoS2/Bi2S3 nanocomposites were analysed by CV, CP, and EIS techniques using a 2 M KOH electrolyte in a three-electrode system. The CV curves show evidence of significant improvement in the electrochemical performance of MoS2/Bi2S3 composites compared to that of pure MoS2. The calculated specific capacitances of MoS2/Bi2S3 nanocomposites were relatively higher than those of pristine MoS2. The 20 mol% Bi added sample showed a maximum specific capacitance of 371 F g−1, compared to pristine MoS2 and other samples at a current density of 1 A g−1. The kinetics of the electrochemical process was studied. The Nyquist plots indicated that the Bi-added nanocomposites had lower Resr and RCT values, which resulted in high electrochemical performance. The experimental results revealed that Bi-substitution can further enhance the electrochemical energy storage performance of MoS2 for supercapacitor applications.
PurposeThis paper verifies whether popular Internet information from Internet forum and search engine exhibit useful content for forecasting the volatility in Chinese stock ...market.Design/methodology/approachFirst, the authors’ study commences with several HAR-RV-type models, then the study amplifies them respectively with the posting volume and search frequency to construct HAR-IF-type and HAR-BD-type models. Second, from in-sample and out-of-sample analysis, the authors empirically investigate the interpretive ability, forecasting performance (statistic and economic). Third, various robustness checks are utilized to reconfirm the authors’ findings, including alternative forecast window, alternative evaluation method and alternative stock market. Finally, the authors further discuss the forecasting performance in different forecast horizons (h = 5, 10 and 20) and asymmetric effect of information from Internet forum.FindingsFrom in-sample perspective, the authors discover that posting volume exhibits better analytical ability for Chinese stock volatility than search frequency. Out-of-sample results indicate that forecasting models with posting volume could achieve a superior forecasting performance and increased economic value than competing models.Practical implicationsThese findings can help investors and decision-makers obtain higher forecasting accuracy and economic gains.Originality/valueThis study enriches the existing research findings about the volatility forecasting of stock market from two dimensions. First, the authors thoroughly investigate whether the Internet information could enhance the efficiency and accuracy of the volatility forecasting concerning with the Chinese stock market. Second, the authors find a novel evidence that the information from Internet forum is more superior to search frequency in volatility forecasting of stock market. Third, they find that this study not only compares the predictability of the posting volume and search frequency simply, but it also divides the posting volume into “good” and “bad” segments to clarify its asymmetric effect respectively.HighlightsThis study aims to verify whether posting volume and search frequency contain predictive content for estimating the volatility in Chinese stock market.The forecasting model with posting volume can achieve a superior forecasting performance and increases economic value than competing models.The results are robust in alternative forecast window, alternative evaluation method and alternative market index.The posting volume still can help to forecast future volatility for mid- and long-term forecast horizons. Additionally, the role of posting volume in forecasting Chinese stock volatility is asymmetric.
Tubular structures are common in vehicles in the form of crash energy absorbers. Inevitably, these tubes contain holes for assembling fasteners and heating sources. Though the introduction of holes ...in the surface of the tube minimizes the initial peak crushing force (IPF), their structural stability also gets affected, which leads to a reduction in energy absorption capacity (EA). Therefore, the shape, dimension, and patterns of the holes in the tubular structure are to be scrutinized to minimize its unstable response during the crash event. This paper addresses the hole's position, shape, and dimensional effects on the performance characteristics of aluminum square tubes subjected to axial quasi-static compression experimentally. Numerical models were initially created using ABAQUS/CAE® code for simulating the quasi-static structural response of square tubes (without holes) and validated against experiments. Further, numerical analysis was explored to investigate the hole's position, shape, and dimensional effects on IPF and EA. The performance characteristics of all the examined specimens were quantified based on the best performance with the help of the TOPSIS method. Finally, Response Surface Methodology (RSM) was carried out to determine the best optimal square tube with holes. It was observed that, with an increase in the hole size, the IPF gets minimized. Among all the specimens, the diamond-shaped hole exhibits the best performance characteristics. The study also reveals that the EA varied greatly with the arrangement of holes (patterns). The research findings can provide ample guidance when designing crash tubes in the automotive protective system.
An Intrusion detection system is an essential security tool for protecting services and infrastructures of wireless sensor networks from unseen and unpredictable attacks. Few works of machine ...learning have been proposed for intrusion detection in wireless sensor networks and that have achieved reasonable results. However, these works still need to be more accurate and efficient against imbalanced data problems in network traffic. In this paper, we proposed a new model to detect intrusion attacks based on a genetic algorithm and an extreme gradient boosting (XGBoot) classifier, called GXGBoost model. The latter is a gradient boosting model designed for improving the performance of traditional models to detect minority classes of attacks in the highly imbalanced data traffic of wireless sensor networks. A set of experiments were conducted on wireless sensor network-detection system (WSN-DS) dataset using holdout and 10 fold cross validation techniques. The results of 10 fold cross validation tests revealed that the proposed approach outperformed the state-of-the-art approaches and other ensemble learning classifiers with high detection rates of 98.2%, 92.9%, 98.9%, and 99.5% for flooding, scheduling, grayhole, and blackhole attacks, respectively, in addition to 99.9% for normal traffic.
•A chemically modified cellulose adsorbent bearing hydrazino-imidazoline groups was synthesized.•The adsorbent shows high selectivity and extraction performance towards precious metal ...ions.•Adsorption kinetics, isotherms, and thermodynamic parameters were investigated.•The adsorption process is achieved through chemical coordination mechanism.•The adsorbent selectively extract precious metal ions from geological samples.
A new hydrazono-imidazoline modified cellulose (HIMC) was synthesized for selective recovery of Pt(IV), Pd(II) and Au(III) from geological samples. Cellulose was oxidized by periodate and was further functionalized with hydrazono-imidazoline moieties to afford N-donor chelating fibers. Scanning electron microscopy (SEM), Fourier transform-infrared spectroscopy (FT-IR), X-ray diffraction (XRD), N2 physisorption, elemental analysis, and energy-dispersive X-ray spectroscopy (EDX) were used for characterization. Introducing the hydrazono-imidazoline groups at the surface of cellulose fibers did not alert their ordered structure and crystallinity, as indicated by XRD and SEM results. Factors affecting the adsorption were systematically investigated. Under the optimized conditions, the HIMC sorbent exhibited high adsorption capacities of 105, 88 and 75 mg g−1 for Pt(IV), Pd(II) and Au(III), respectively. Besides, the metal ion adsorption process fitted by pseudo-second-order kinetic model and Langmuir adsorption isotherm. These results highlight the applicability of this carbohydrate-based sorbent for the selective recovery of precious metals from various matrices.
This paper investigates the effect of state‐society relations (SSR) in the industrial sector on the sustainable economic growth of post‐Revolution Tunisia. The empirical part of the paper depends ...mainly on qualitative data collected from fieldwork interviews with the most important actors and publications of civil society organizations. The paper suggests the presence of state capture as the defining characteristic of SSR in post‐Revolution Tunisia. The combination of having powerful tycoons, weaker state, and ineffectively organized social actors produced conditions that harmed sustainability. These settings allowed tycoons to violate environmental regulations and prevented Green innovation through the adoption of Green technologies. Yet, factors such as low value‐added creation, increased labor‐intensity, and low environmental awareness or prioritization all interact with state capture to lower sustainability. In those sectors where tycoons are active and dominant, competing social actors are incapable of effectively exploiting the presence of a freer political system, ultimately failing to successfully organize resisting coalitions, as evident in the textile sector. While higher resistance is witnessed where tycoons are not dominant as was the case in the phosphate sector, tycoons could still use the situation to their advantage.
•Using SF and MK in concrete industry reduce clinker production and consumption.•The use of SF and MK also reduce the ECO2.•Strength and durability are improved even with low replacement level of ...5–10%.•Overall, SF pozzolana seems to perform better than MK.
The use of various pozzolanic and cementitious materials not only has an environmental and economic impact, by the reduction of Portland cement clinker production, but also could significantly improve the strength and durability performances of concrete. Silica fume (SF) is a well-known and largely used pozzolanic material due to numerous improvements that could provide to concrete while metakaolin (MK) even with quite similar performance is still less popular in concrete industry. The present study investigates and compares the key mechanical properties and durability performances of binary concrete mixes designed with different replacement levels of SF and MK varying from 5% to 25% of Portland cement (PC).
The results indicate that using both SF and MK in a partial substitution of PC could significantly improve strengths and durability performances of blended cement concrete mixes in comparison with the control PC-concrete. Meanwhile, SF-concrete seems to perform better than MK-concrete with regards to strength development and resistance to freezing-thawing while MK-concrete has exhibited a better performance with regard to carbonation and chloride ions ingress. Furthermore, although economical assessment showed an increase in the cost of concrete made with SF/MK due to the fact that SF/MK are more expensive than PC, environmental assessment revealed that significant reduction of the embodied CO2 (ECO2) is generated when using MK, and especially SF as a partial substitution of PC. Designing a binary SF and MK concretes may help towards producing clean and environmentally friendly concrete material.
Not all pit viper species are present in every state of Malaysia and their distribution varies according to altitude. There is limited information on pit viper bite incidence and its geographical ...distribution. This was a cross-sectional study of confirmed pit viper bite cases referred to Remote Envenomation Consultancy Services (RECS) from January 2017 to December 2020. Data was collected following the approval of institutional research ethics committee. Universal sampling methods were used. Confirmed pit viper bite cases in each state, geographical location and the antivenom used were reported. A total of 523 confirmed pit viper bite injuries occurred over the 4-year study period. The majority were Malaysians, male and young adults. Most were non-occupational related (83.9%) and involved the upper limbs (46.8%). The commonest pit viper species involved was Trimeresurus purpureomaculatus (23.7%). Green pit viper antivenom (GPAV) was the most frequent antivenom used (n = 51) with the majority of patients requiring only one dose (3 vials). This study provides a better appreciation of indigenous pit viper species distribution for each state and reflects the requirement of appropriate antivenom to be stocked in each state or district hospital.
In the last few decades, photovoltaics have contributed deeply to electric power networks due to their economic and technical benefits. Typically, photovoltaic systems are widely used and implemented ...in many fields like electric vehicles, homes, and satellites. One of the biggest problems that face the relatability and stability of the electrical power system is the loss of one of the photovoltaic modules. In other words, fault detection methods designed for photovoltaic systems are required to not only diagnose but also clear such undesirable faults to improve the reliability and efficiency of solar farms. Accordingly, the loss of any module leads to a decrease in the efficiency of the overall system. To avoid this issue, this paper proposes an optimum solution for fault finding, tracking, and clearing in an effective manner. Specifically, this proposed approach is done by developing one of the most promising techniques of artificial intelligence called the adaptive neuro-fuzzy inference system. The proposed fault detection approach is based on associating the actual measured values of current and voltage with respect to the trained historical values for this parameter while considering the ambient changes in conditions including irradiation and temperature. Two adaptive neuro-fuzzy inference system-based controllers are proposed: (1) the first one is utilized to detect the faulted string and (2) the other one is utilized for detecting the exact faulted group in the photovoltaic array. The utilized model was installed using a configuration of 4 × 4 photovoltaic arrays that are connected through several switches, besides four ammeters and four voltmeters. This study is implemented using MATLAB/Simulink and the simulation results are presented to show the validity of the proposed technique. The simulation results demonstrate the innovation of this study while proving the effective and high performance of the proposed adaptive neuro-fuzzy inference system-based approach in fault tracking, detection, clearing, and rearrangement for practical photovoltaic systems.
This work investigates the effects of blending waste cooking oil (WCO) biodiesel with gasoline and kerosene on diesel engine performance, combustion characteristics and emissions compared to fossil ...diesel. The properties of WCO biodiesel derived through transesterification process, are consistent with the standard limits. Kerosene and gasoline additives are added to biodiesel at ratios of 5 and 10 % by volume. Tests are carried out on a diesel engine running at 1500 rpm with various loads. The decreases in peak cylinder pressures for kerosene blends are 2 and 1.5 % for K5 and K10, respectively but for gasoline blends are 3.5 and 3% for G5 and G10, respectively about diesel oil. The thermal efficiency at full load for diesel fuel had a value of 18.5 % and reduced by 9.0, 7.0, 3.5, and 2.0 % for G5, G10, K5, and K10, respectively. The CO emissions values were reduced by 24, 31, 35, 40, and 20 % for G5, G10, K5, K10, and WCO biodiesel, respectively. HC emissions were declined by 26, 33, 38, 43, and 21 % for G5, G10, K5, K10, and WCO biodiesel, respectively. NOx emissions were increased by 31, 25, 13 and 7.5 % when using G5, G10, K5, and K10, respectively about diesel oil. The smoke emissions decreases were 30, 34, 41, and 44 % when using G5, G10, K5, and K10, respectively. WCO biodiesel blended with gasoline or kerosene can be considered good alternatives for fuels in diesel engines due to their improvements in performance parameters, combustion chracteristics as well as emissions reduction.
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