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Crops are increasingly affected by drought; hence, the current study explored the potential role of three desert endophytic fungi, Aspergillus fumigatus, Aspergillus terreus and Talaromyces variabilis, in conferring drought tolerance in tomato plants.

Preserved endophytic fungi from a Rhazya stricta desert plant were adopted to obtain the required fungal treatment; tomatoes received fungal treatments directly in plastic trays and subsequently in pots. Drought was applied using 15% of PEG-6000 at two stages: flowering and fruiting. The following parameters were measured: pollen sterility, growth characteristics, morphological analysis and biochemical analysis, including proline, gibberellic acid (GA3) and chlorophyll measurements; thus, the data were analyzed statistically using SPSS software.

All applied endophytes significantly promoted pollen viability and tomato yield under stressed and nonstressed conditions. Interestingly, these endophytes significantly enhanced the number of trichomes under drought stress and promoted tomato fruit quality. The colonized tomato plants accumulated a high proline level under drought stress but lower than un-inoculated stressed plants. Also, a significant rise in growth characteristics was observed by A. fumigatus and A. terreus under normal conditions. Moreover, both raised GA3 levels under drought-stressed and nonstressed conditions. Also these two endophytes enhanced chlorophyll and carotenoid contents under drought stress. Fruit characteristics were enhanced by nonstressed T. variabilis and stressed A. fumigatus.

The present endophytic fungi provide impressive benefits to their host in normal and drought-stressed conditions. Consequently, they represent valuable sources as sustainable and environmentally friendly alternatives to mitigate drought stress.

This study aims to evaluate the efficiency of various techniques for enhancing indoor air quality (IAQ) in construction. It analyzed the alterations in the concentration of indoor air pollutants over time for each product employed in controlling pollution sources and removing it, which included eco-friendly substances and adsorbents. The study will provide more precise and dependable data on the effectiveness of these control methods, ultimately supporting the creation of more efficient and sustainable approaches for managing indoor air pollution in buildings.

The research investigates the impact of eco-friendly materials and adsorbents on improving indoor air quality (IAQ) in Dubai's tall apartment buildings. Field experiments were conducted in six units of The Gate Tower, comparing the IAQ of three units built with “excellent” grade eco-friendly materials with three built with “good” grade materials. Another experiment evaluated two adsorbent products (H and Z) in the Majestic Tower over six months. Results indicate that “excellent” grade materials significantly reduced toluene emissions. Adsorbent product Z showed promising results in pollutant reduction, but there is concern about the long-term behavior of adsorbed chemicals. The study emphasizes further research on household pollutant management.

The research studied the effects of eco-friendly materials and adsorbents on indoor air quality in Dubai's new apartments. It found that apartments using “excellent” eco-friendly materials had significantly better air quality, particularly reduced toluene concentrations, compared to those using “good” materials. However, high formaldehyde (HCHO) emissions were observed from wood products. While certain construction materials led to increased ethylbenzene and xylene levels, adsorbent product Z showed promise in reducing pollutants. Yet, there is a potential concern about the long-term rerelease of these trapped chemicals. The study emphasizes the need for ongoing research in indoor pollutant management.

The research, while extensive, faced limitations in assessing the long-term behavior of adsorbed chemicals, particularly the potential for rereleasing trapped pollutants over time. Despite the study spanning a considerable period, indoor air pollutant concentrations in target households did not stabilize, making it challenging to determine definitive improvement effects and reduction rates among products. Comparisons were primarily relative between target units, and the rapid rise in pollutants during furniture introduction warrants further examination. Consequently, while the research provides essential insights, it underscores the need for more prolonged and comprehensive evaluations to fully understand the materials' and adsorbents' impacts on indoor air quality.

The research underscores the importance of choosing eco-friendly materials in new apartment constructions for better IAQ. Specifically, using “excellent” graded materials can significantly reduce harmful pollutants like toluene. However, the study also highlights that certain construction activities, such as introducing furniture, can rapidly elevate pollutant levels. Moreover, while adsorbents like product Z showed promise in reducing pollutants, there is potential for adsorbed chemicals to be rereleased over time. For practical implementation, prioritizing higher-grade eco-friendly materials and further investigation into furniture emissions and long-term behavior of adsorbents can lead to healthier indoor environments in newly built apartments.

The research offers a unique empirical assessment of eco-friendly materials' impact on indoor air quality within Dubai's rapidly constructed apartment buildings. Through field experiments, it directly compares different material grades, providing concrete data on pollutant levels in newly built environments. Additionally, it explores the efficacy of specific adsorbents, which is of high value to the construction and public health sectors. The findings shed light on how construction choices can influence indoor air pollution, offering valuable insights to builders, policymakers and residents aiming to promote public health and safety in urban living spaces.

The purpose of this paper is to show a comparative study of different direction-of-arrival (DOA) estimation techniques, namely, multiple signal classification (MUSIC) algorithm, delay-and-sum (DAS) beamforming, support vector regression (SVR), multivariate linear regression (MLR) and multivariate curvilinear regression (MCR).

The relative delay between the microphone signals is the key attribute for the implementation of any of these techniques. The machine-learning models SVR, MLR and MCR have been trained using correlation coefficient as the feature set. However, MUSIC uses noise subspace of the covariance-matrix of the signals recorded with the microphone, whereas DAS uses the constructive and destructive interference of the microphone signals.

Variations in root mean square angular error (RMSAE) values are plotted using different DOA estimation techniques at different signal-to-noise-ratio (SNR) values as 10, 14, 18, 22 and 26dB. The RMSAE curve for DAS seems to be smooth as compared to PR1, PR2 and RR but it shows a relatively higher RMSAE at higher SNR. As compared to (DAS, PR1, PR2 and RR), SVR has the lowest RMSAE such that the graph is more suppressed towards the bottom.

DAS has a smooth curve but has higher RMSAE at higher SNR values. All the techniques show a higher RMSAE at the end-fire, i.e. angles near 90°, but comparatively, MUSIC has the lowest RMSAE near the end-fire, supporting the claim that MUSIC outperforms all other algorithms considered.

This paper uses test panel data for the biggest companies listed on the boards of directors of the Palestine Stock Exchange from 2016 to 2022 and will focus on the relationship between the corporate governance index, accounting conservatism, and the comprehensive index of corporate governance.

The relationship between corporate governance and accounting conservatism is experimentally investigated for its impact on the likelihood of stock price breakdown and decline among companies listed on the Palestine Stock Exchange between 2016 and 2022, using a mixed utilities approach.

The findings demonstrated the adverse correlation between corporate governance, accounting conservatism, and stock prices. Higher levels of corporate governance can effectively reduce the likelihood of future stock price increases, while conservative accounting policies can effectively prevent stock price collapses in these listed companies. Higher levels of corporate governance can greatly lessen the detrimental effect of accounting conservatism on the likelihood of future stock price breakdowns and declines. Both accounting conservatism and corporate governance have substitution effects in decreasing the danger of stock price collapse.

The limitations of the current research are that higher levels of corporate governance can significantly reduce the harmful effect of accounting conservatism on the probability of stock price breakdown and decline in the future on the study sample used, and these results cannot be generalized to all company stocks that were excluded in this study. The last research limitation is that the sample size of this study is somewhat small, and therefore the effects of the results cannot be used on all unlisted companies, and they cannot be generalized to all of these companies except only to companies listed on the Palestine Stock Exchange.

Our findings have interesting managerial and policy implications. Listed firms should first strengthen external audit oversight, improve the method of disclosing accounting information, and improve the system architecture to raise the level of accounting conservatism. Moreover, it is imperative to enhance and improve the ownership structure of publicly traded firms, construct a robust mechanism for replacing shareholders, fortify the duties of the board of directors, proficiently fulfil the role of independent directors, and develop and refine the internal and external framework for corporate governance.

This study provides insights about reducing the probability of a stock market breakdown and collapse from two sides: enhancing corporate governance, improving accounting conservatism, enhancing the reliability and integrity of disclosure, and growing the number of sustainable disclosures. These suggestions can also be used as a template for Palestine's capital market's gradual and sustainable expansion.

This empirical paper aims to examine the impact of interest rate (IR) and political instability (POLINS) on Palestine's domestic private investment.

A set of econometric techniques of time series data are adopted to meet the study objectives. They include regression analysis, unit root tests, cointegration test, ARDL & Bound tests, VAR test and Granger causality test.

The study's primary results complement the neoclassical approach, which states that the IR is negatively associated with domestic private investment. The empirical results reveal that there is no long-run relationship. Also, there is no causality between domestic investment and lending rates. Accordingly, these findings alert policymakers to draw a series of steps to minimize the IR at a minimum to stimulate investment for improved economic growth and development.

There is still no national currency in Palestine. The Palestinian Monetary Authority (PMA) is advised to set an appropriate ratio of the IR for the currencies-in-circulation in Palestine for boosting investment and economic development.

This paper provides new background information to both policymakers and researchers on the main determinants of investment in Palestine using econometric analysis. Accordingly, this critical issue is required to be examined in Palestine for stimulating investment.

Since the beginning of 2020, economies faced many changes as a result of coronavirus disease 2019 (COVID-19) pandemic. The effect of COVID-19 on the Egyptian Exchange (EGX) is investigated in this research.

To explore the impact of COVID-19, three periods were considered: (1) 17 months before the spread of COVID-19 and the start of the lockdown, (2) 17 months after the spread of COVID-19 and the during the lockdown and (3) 34 months comprehending the whole period (before and during COVID-19). Due to the large number of variables that could be considered, dimensionality reduction method, such as the principal component analysis (PCA) is followed. This method helps in determining the most individual stocks contributing to the main EGX index (EGX 30). The PCA, also, addresses the multicollinearity between the variables under investigation. Additionally, a principal component regression (PCR) model is developed to predict the future behavior of the EGX 30.

The results demonstrate that the first three principal components (PCs) could be considered to explain 89%, 85%, and 88% of data variability at (1) before COVID-19, (2) during COVID-19 and (3) the whole period, respectively. Furthermore, sectors of food and beverage, basic resources and real estate have not been affected by the COVID-19. The resulted Principal Component Regression (PCR) model performs very well. This could be concluded by comparing the observed values of EGX 30 with the predicted ones (R-squared estimated as 0.99).

To the best of our knowledge, no research has been conducted to investigate the effect of the COVID-19 on the EGX following an unsupervised machine learning method.