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This study aims to provide an efficient nanocomposite that might be used to protect deteriorated archaeological stucco.

The current experimental study evaluates the effectiveness of the hydroxyapatite nanoparticles (HA NPs) added to graphite carbon nitride (g-C₃N₄) and mixed with Paraloid (B-72) (B-44) in acetone in consolidating samples. The physicochemical properties of the as-prepared nanopowders have been investigated using Fourier transform infrared (FT-IR). This study involves monitoring the transmission electron microscope (TEM), X-ray diffraction (XRD) and Fourier transform changes in consolidated samples after exposure to various conditions by using the digital microscope and scanning electron microscopy to identify the appearance of the consolidated stucco samples after applying the selected nanocomposites and after their artificial aging procedures. Color change is measured using a colorimeter, and comparisons are made between samples before and after aging. Physical and mechanical properties are determined, and the contact angle is measured to measure hydrophobicity rate.

The obtained results indicate that HA/g-C₃N₄ hybrid nanocomposites with a composition of HA 0.5%/g-C₃N₄ 1%/B-72 3% and HA 0.5%/g-C3N4 1%/B-44 3% achieved the best consolidating results among the proposed mixtures for stucco samples, where the percentage of weight loss was 0.77 with B-72, 0.53 with B-44. Surface identification and characterization of hydroxyapatite HA NPs/g-C₃N₄ hybrid nanocomposites embedded in B72/B44matrix were carried out using Scanning Electron Microscopy coupled with energy-dispersive x-ray spectroscopy (SEM–EDX).

This study provides important findings from the analytical procedures used to evaluate the consolidation materials used in this study. The findings are beneficial for the preservation of archaeological stucco. The investigation findings revealed that the most favorable outcomes were obtained from HA/g-C₃N₄ hybrid nanocomposites containing HA 0.5%, g-C₃N₄ 1% and B-72 3%, as well as HA 0.5%, g-C₃N₄ 1% and B-44 3%. Consequently, it is advised to use this nanocomposite to consolidate archaeological stucco, thus establishing a promising initial stride toward conserving archaeological stucco for future research endeavors. This study introduces a new nanocomposite material (HA NPs/G-C₃N₄) that can be used to protect and improve archaeological plaster. This is very important for preserving cultural heritage. The incorporation of nanotechnology improves the material’s physical and mechanical qualities. The research uses various characterization techniques (including TEM, XRD and FT-IR) to meticulously analyze the physicochemical properties of the nanocomposite material and assess its efficacy in practical applications through artificial aging experiments, offering novel insights and methodologies for future cultural relic preservation studies.

The purpose of this study is to investigate the interaction between magnetotactic bacteria and Fe₃O₄–water nanofluid (NF) in a wavy enclosure in the presence of 2D natural convection flow.

Uniform magnetic field (MF), Brownian and thermophoresis effects are also contemplated. The dimensionless, time-dependent equations are governed by stream function, vorticity, energy, nanoparticle concentration and number of bacteria. Radial basis function-based finite difference method for the space derivatives and the second-order backward differentiation formula for the time derivatives are performed. Numerical outputs in view of isolines as well as average Nusselt number, average Sherwood number and flux density of microorganisms are presented.

Convective mass transfer rises if any of Lewis number, Peclet number, Rayleigh number, bioconvection Rayleigh number and Brownian motion parameter increases, and the flux density of microorganisms is an increasing function of Rayleigh number, bioconvection Rayleigh number, Peclet number, Brownian and thermophoresis parameters. The rise in buoyancy ratio parameter between 0.1 and 1 and the rise in Hartmann number between 0 and 50 reduce all outputs average Nusselt, average Sherwood numbers and flux density of microorganisms.

This study implies the importance of the presence of magnetotactic bacteria and magnetite nanoparticles inside a host fluid in view of heat transfer and fluid flow. The limitation is to check the efficiency on numerical aspect. Experimental observations would be more effective.

In practical point of view, in a heat transfer and fluid flow system involving magnetite nanoparticles, the inclusion of magnetotactic bacteria and MF effect provide control over fluid flow and heat transfer.

This is a scientific study. However, this idea may be extended to sustainable energy or biofuel studies, too. This means that a better world may create better social environment between people.

The presence of magnetotactic bacteria inside a Fe₃O₄–water NF under the effect of a MF is a good controller on fluid flow and heat transfer. Since the magnetotactic bacteria is fed by nanoparticles Fe₃O₄ which has strong magnetic property, varying nanoparticle concentration and Brownian and thermophoresis effects are first considered.

This paper aims to numerically examine the impact of gyrotactic microorganisms and radiation on heat transport features of magnetic nanoliquid within a closed cavity. Thermophoresis, chemical reaction and Brownian motion are also considered in flow geometry for the moment of nanoparticles.

Finite element method (FEM) was depleted to numerically approximate the temperature, momentum, concentration and microorganisms concentration of the nanoliquid. The present simulation was unsteady state, and the resulting transformed equations are simulated by FEM-based Mathematica algorithm.

It has been found that isotherm patterns get larger with increasing values of the magnetic field parameter. Additionally, numerical codes for rate of heat transport impedance inside the cavity with an increasing Brownian motion parameter values.

To the best of the authors’ knowledge, the research work carried out in this paper is new, and no part is copied from others’ works.

This article identifies hybrid nanofluids and industrial thermal engineering devices as significant sources of solar energy. In this study, various nanoparticles suspended in base fluids such as water (H2O) and carboxymethyl cellulose (CMC), along with nanoparticles like graphene oxide (GO) and molybdenum disulfide (MoS2), are examined. The model also incorporates permeability and the effects of angled magnetic fields to provide a comprehensive analysis.

We have utilized the fractal fractional operator definition, the quickest and most advanced fractional approach, to address the problems with the hybrid nanofluid suspension. The integral transform scheme, i.e. the Laplace transform, converts the governing equations into a fractional form before various numerical methods are applied to solve the problem. Further, some numerical schemes to address the Laplace inverse are also utilized.

The fractional effects on flow rate and heat transfer are evident at varying time intervals. Consequently, we conclude that as the fractal constraints increase, the momentum and heat profiles decelerate. Furthermore, all necessary conditions are satisfied, resulting in the momentum and temperature fields decreasing near the plate and increasing over time. Additionally, the water-based (H2O + Go + MoS2) solution exhibits a more pronounced impact compared to the CMC-based (CMC + Go + MoS2) hybrid suspension.

The findings could be very useful in enhancing the efficiency of thermal systems. These findings align more accurately with conventional solutions and can be used to build and optimize various heat management strategies.

The primary goals of this research are to examine the thermal and flow properties of hybrid nanofluids for manufacturing purposes of thermal engineering equipment utilizing fractal fractional definition. Further, to improve thermal system productivity by applying sophisticated fractional techniques to better and maximize heat and momentum transmission in these hybrid nanofluid solutions

This study aims to assess the effect of water variation on bioethanol production from cassava peels (CP) using Saccharomyces cerevisiae yeast as the ethanologenic agent.

The milled CP was divided into three treatment groups in a small-scale flask experiment where each 20 g CP was subjected to two-stage hydrolysis. Different amount of water was added to the fermentation process of CP. The fermented samples were collected every 24 h for various analyses.

The results of the fermentation revealed that the highest ethanol productivity and fermentation efficiency was obtained at 17.38 ± 0.30% and 0.139 ± 0.003 gL⁻¹ h⁻¹. The study affirmed that ethanol production was increased for the addition of water up to 35% for the CP hydrolysate process.

The finding of this study demonstrates that S. cerevisiae is the key player in industrial ethanol production among a variety of yeasts that produce ethanol through sugar fermentation. In order to design truly sustainable processes, it should be expanded to include a thorough analysis and the gradual scaling-up of this process to an industrial level.

This paper is an original research work dealing with bioethanol production from CP using S. cerevisiae microbe.

1. Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

2. Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

3. Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

4. Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

This paper aims to examine the relationship between corporate COVID-19 disclosure (COVID_DISC) and stock price volatility (SPV) in Egypt.

The authors used the manual content analysis method to measure corporate COVID-19 disclosure in the narrative sections of annual reports. The authors use ordinary least squares (OLS) regression to examine the impact of corporate COVID-19 disclosure on stock price volatility using unique data from Egyptian-listed firms during COVID-19 pandemic over the period of 2020 to 2022. Propensity score matching method was adopted to mitigate the potential endogeneity issue.

This study reveals that corporate COVID-19 disclosure has a significant negative impact on stock price volatility, suggesting COVID-19 disclosure reduces stock price volatility. In addition, the results confirm that COVID-19 disclosure offers value relevant information to investors, which is consistent with the Egyptian Financial Supervisory Authority’s (EFSA) motivation in calling for more information on COVID-19 pandemic.

The findings of this study can help corporate managers and EFSA in enhancing corporate disclosure and transparency during future financial crises. Moreover, the findings offer valuable insights to investors, helping them gain a better understanding of the business environment during COVID-19 crisis.

To the best of the authors’ knowledge, this is the first Egyptian empirical evidence that examines the relationship between corporate COVID-19 disclosure and stock price volatility.

This study examines whether a firm’s management earnings forecasts affect its technical innovation activities. Our study also examines whether the cost of debt plays a mediating role between the management earnings forecasts and the innovation nexus.

We obtained data from 1,032 Chinese non-financial firms listed on the Shanghai and Shenzhen stock markets from 2005 to 2022 (i.e. 18,576 firm-year observations). We used various econometrics techniques, such as Heckman’s (1979) two-stage selection method and two-stage least square, to examine the relationship between management earnings forecasts and the firm’s technical innovation activities.

We find a positive relationship between management earnings forecasts and the firms' technical innovation. We also find that the cost of debt mediates the relationship between management earnings forecast and technical innovation. Further analysis indicates that frequent earnings forecasts provide incremental information regarding a firm’s future value and cash flows, thus reducing the volatility and uncertainty in cash flow calculations. Our findings are robust to several tests.

Our study has implications for policymakers, practitioners and high-level management of Chinese firms, enabling them to understand the relationship between management earnings forecasts and firms' innovation activities.

This study aims to understand the dynamics of Australian boards by focusing on the influence of board gender diversity on firms' cash holdings, within the distinctive Australian “if not, why not” regulatory framework.

The study uses ordinary least squares (OLS), fixed effects, generalized method of moments (GMM) and quasi-experimental methods such as difference-in-differences and propensity score matching to analyze the data.

There is a significantly negative relationship between board gender diversity and corporate cash holdings. This relationship is more pronounced when two or more female directors are on the board, supporting the critical mass theory. The results also reveal that the observed pattern can be attributed to the heightened monitoring intensity of female independent directors. Our quasi-experimental methods and pre-post analysis reveal that the observed effects are genuinely attributable to the increase in board gender diversity following regulatory reforms in Australia.

The findings provide practical insights for companies and policymakers, emphasizing the tangible effects of gender diversity on a company's financial strategy and corporate cash holdings. This information is crucial for organizations aiming to make informed decisions regarding board compositions and governance structures.

This research offers fresh insights into an important relationship between gender diversity on boards and corporate financial strategies in the Australian context, enriching the global conversation on the significance of gender diversity in corporate leadership.

This study aims to address the critical issue of machine breakdowns in industrial settings, which jeopardize operation economy, worker safety, productivity and environmental compliance. It explores the efficacy of a predictive maintenance program in mitigating these risks by proactively identifying and minimizing failures, thereby optimizing maintenance activities for higher efficiency.

The article implements Logical Analysis of Data (LAD) as a predictive maintenance approach on an industrial machine maintenance dataset. The aim is to (1) detect failure presence and (2) determine specific failure modes. Data resampling is applied to address asymmetrical class distribution.

LAD demonstrates its interpretability by extracting patterns facilitating the failure diagnosis. Results indicate that, in the first case study, LAD exhibits a high recall value for failure records within a balanced dataset. In the second case study involving smaller-scale datasets, enhancement across all evaluation metrics is observed when data is balanced and remains robust in the presence of imbalance, albeit with nuanced differences in between.

This research highlights the importance of transparency in predictive maintenance programs. The research shows the effectiveness of LAD in detecting failures and identifying specific failure modes from diagnostic sensor data. This maintenance strategy exhibits its distinction by offering explainable failure patterns for maintenance teams. The patterns facilitate the failure cause-effect analysis and serve as the core for failure prediction. Hence, this program has the potential to enhance machine reliability, availability and maintainability in industrial environments.

Due to herbs and plants’ therapeutic properties and simplicity of availability in nature, humans have used them to treat a variety of maladies and diseases since ancient times. Later, as technology advanced, these plants and herbs gained significant relevance in some industries due to their suitable chemical composition, abundant availability and ease of access. Aegle marmelos is a species of plant that may be found in nature. Yet, little or very little literature was located on the coloration behavior of this plant’s leaves. This study aims to focus on the effect of different parameters on the extraction of colorant from Aegle marmelos leaves.

Some factors that affected on the extraction processes were examined and found to have significant impacts on the textile dyeing such as the initial dye concentration, extracted temperature, extracted bath pH and extracted time were all changed to see how they affected color extraction. The authors report a direct comparison between three heating methods, namely, microwave irradiation (MWI), ultrasonic waves (USW) and conventional heating (CH). The two kinetic models have been designed (pseudo-first and pseudo-second orders) in the context of these experiments to investigate the mechanism of the dyeing processes for fabrics under study. Also, the experimental data were analyzed according to the Langmuir and Freundlich isotherms.

From the result, it was discovered these characteristics were found to have a substantial effect on extraction efficiency. Temperature 90°C and 80°C when using CH and USW, respectively, while at 90% watt when using MWI, period 120 min when using CH as well as USW waves, while 40 min when using MWI, and pH 4, 5 and 10 for polyamide, wool and cotton, respectively, were the optimal extraction conditions. Also, the authors can say that wool gives a higher absorption than the other fabric. Additionally, MWI provided the best color strength (K/S) value, and homogeneity, at low temperatures reducing the energy and time consumed. The coloring follows the order: MWI > USW > CH. The adsorption isotherm of wool could be well fitted by Freundlich isotherm when applying CH and USW as a heating source, while it is well fitted by the Langmuir equation in the case of MWI. In the study, it was observed that the pseudo-first-order kinetic model fits better the experimental results of CH with a constant rate K₁ = −0.000171417 mg/g.min, while the pseudo-second-order kinetic model fits better the experimental results of absorption of both MWI (K2 = 38.14022572 mg/g.min) and USW (K₂ = 12.45343554 mg/g.min).

There is no research limitation for this work. Dye was extracted from Aegle marmelos leaves by applying three different heating sources (MWI, ultrasonic waves [USWW] and CH).

This work has practical applications for the textile industry. It is concluded that using Aegle marmelose leaves can be a possible alternative to extract dye from natural resource by applying new technology to save energy and time and can make the process greener.

Socially, it has a good impact on the ecosystem and global community because the extracted dye does not contain any carcinogenic materials.

The work is original and contains value-added products for the textile industry and other confederate fields.