Explore the vast range of titles available.

مؤلف هذا الكتاب صارح المسلمين بحقائق قل أن جرؤ غيره على التصريح بها : إنه درس دقيق لحال المسلمين اليوم من الناحية الثقافية والروحية. وهو يدعو المسلمين إلى العودة إلى حقيقة دينهم، لأن الدين الذي استطاع أن يجمع العرب منذ أربعة عشر قرنا، ويجعل منهم قوة عظيمة في السياسة والعلم والاجتماع يستطيع أن يقدم لهم اليوم ما قدم بالأمس : دستورا للحياة لا يجدون مثله في النظم التي تعرضت منذ فجر التاريخ حتى اليوم لتهذيب البشر.

The paper shows the effect of the probe on the performance of a transonic axial speed compressor. The unobstructed flow case with the experimental data was validated and used as a guide for all subsequent study cases. The aerodynamic performance for different probe parameters were calculated numerically using ANSYS-CFX. This covered the results on compressor output from changing probe axial positions, the radial immersion depths, the size of the probe, and the total number of probes. The findings were evaluated in relation to the total pressure ratio, performance, margin of deflation and stability. The velocity part distributions further showed that the probe block and raises the flow Mach value, which is the explanation why the compressor rotor’s total pressure ratio is lost. In fact, the parameters of the sample will significantly influence the calculation outcomes and affect the standard margin. The range of stability was also affected, which changes the performance trend from the choke to the stall. Consequently, the collection of correct probe parameters with fewer impact on compressor output is addressed.

The emergence of the covid-19 health crisis, in this advanced technological era where connections between markets, nations, and economies have grown stronger than ever before, the shock of the COVID-19 pandemic quickly had an impact on both physical and digital financial assets. The Chinese financial market experienced the first consequences of the covid-19 pandemic, then spilled over to other financial markets, including those for cryptocurrencies and the precious metals. This study examines the impact of the covid-19 pandemic on the volatilities of the dynamics of bitcoin and gold. Both assets share some characteristics, such as online trading platforms, however, gold is a tangible financial asset unlike bitcoin, which is digitally generated without any physical form. This study argues that the similarities and differences between bitcoin and gold play major roles in how the covid-19 crisis affected their respective dynamics. Using daily data ranging from 9/22/2014 to 1/31/2023 and employing ARMA as the mean equation for GARCH model, the impact of the health crisis (covid-19) is examined on the volatilities of the prices and volumes of bitcoin and gold. Empirical evidence points out that, the pandemic has a symmetric impact on the volatilities of bitcoin and gold price returns, causing them to be more volatile. The impact of the covid-19 observed on the volume returns of the assets, however, is asymmetrical. The empirical results give evidence to the role that the vital differences existing between these assets played during the covid-19 pandemic.

This study examines the association between food insecurity and mental health of women during the COVID-19 pandemic in a resource poor setting. Data were collected at two time-points (wave 1 and 2) from 2402 women, one per household, participating in a larger study during extended COVID-19 lockdown in the rural areas of the southwest region of Bangladesh. The primary outcome of the analyses is the association between food insecurity, measured using the Food Insecurity Experience Scale (FIES), and stress level, measured using the Perceived Stress Scale (PSS), for women during the lockdown. General awareness about COVID-19 and attitude towards prescribed preventive measures were also measured since COVID-19 health concerns could exacerbate food insecurity. An individual-level evaluation of the effect of wave 2 FIES score on PSS score showed that worsening of the food security status increasing the stress level of the participants (95% CI: 1.61; 2.13; p-value: <0.001). Additionally, a significant negative association was observed between the PSS score and change in food security status between the two waves (Coefficient: -1.15, 95% CI: -1.30; -0.99, p-value: <0.001), indicating that deterioration in food security status over the pandemic period increasing the stress level. At the village level, the results showed a similar pattern. General awareness around ways coronavirus spreads was high, yet there were misperceptions at a higher level. Maintaining hand hygiene, wearing face masks outside the home, and going outside only when necessary were widely practised. Fewer respondents could maintain a 1.5-metre distance from others in the outside and maintained cough and sneeze etiquette. The results indicate a higher stress level, a potential contributor to poor mental health, as food insecurity deteriorated. Policy initiatives in ameliorating immediate food insecurity during crises, improving long-term wellbeing, and expanding the reach of mental health support are warranted.

In this study, we examine multiple perspectives on soliton solutions to the (3+1)-dimensional Boussinesq model by applying the unified Riccati equation expansion (UREE) approach. The Boussinesq model examines wave propagation in shallow water, which is derived from the fluid dynamics of a dynamical system. The UREE approach allows us to derive a range of distinct solutions, such as single, periodic, dark, and rational wave solutions. Furthermore, we present the bifurcation, chaotic, and sensitivity analysis of the proposed model. We use planar dynamical system theory to analyze the structure and characteristics of the system’s phase portraits. The current study depends on a dynamic structure that has novel and unexplored results for this model. In addition, we display the behaviors of associated physical models in 3-dimensional, density, and 2-dimensional graphical structures. Our findings demonstrate that the UREE technique is a valuable mathematical tool in engineering and applied mathematics for studying wave propagation in nonlinear evolution equations.

The Coronavirus Disease 2019 (COVID-19) pandemic and associated mitigation policies created a global economic and health crisis of unprecedented depth and scale, raising the estimated prevalence of depression by more than a quarter in high-income countries. Low- and middle-income countries (LMICs) suffered the negative effects on living standards the most severely. However, the consequences of the pandemic for mental health in LMICs have received less attention. Therefore, this study assesses the association between the COVID-19 crisis and mental health in 8 LMICs. We conducted a prospective cohort study to examine the correlation between the COVID-19 pandemic and mental health in 10 populations from 8 LMICs in Asia, Africa, and South America. The analysis included 21,162 individuals (mean age 38.01 years, 64% female) who were interviewed at least once pre- as well as post-pandemic. The total number of survey waves ranged from 2 to 17 (mean 7.1). Our individual-level primary outcome measure was based on validated screening tools for depression and a weighted index of depression questions, dependent on the sample. Sample-specific estimates and 95% confidence intervals (CIs) for the association between COVID-19 periods and mental health were estimated using linear regressions with individual fixed effects, controlling for independent time trends and seasonal variation in mental health where possible. In addition, a regression discontinuity design was used for the samples with multiple surveys conducted just before and after the onset of the pandemic. We aggregated sample-specific coefficients using a random-effects model, distinguishing between estimates for the short (0 to 4 months) and longer term (4+ months). The random-effects aggregation showed that depression symptoms are associated with a increase by 0.29 standard deviations (SDs) (95% CI [−.47, −.11], p -value = 0.002) in the 4 months following the onset of the pandemic. This change was equivalent to moving from the 50th to the 63rd percentile in our median sample. Although aggregate depression is correlated with a decline to 0.21 SD (95% CI [−0.07, −.34], p -value = 0.003) in the period thereafter, the average recovery of 0.07 SD (95% CI [−0.09, .22], p -value = 0.41) was not statistically significant. The observed trends were consistent across countries and robust to alternative specifications. Two limitations of our study are that not all samples are representative of the national population, and the mental health measures differ across samples. Controlling for seasonality, we documented a large, significant, negative association of the pandemic on mental health, especially during the early months of lockdown. The magnitude is comparable (but opposite) to the effects of cash transfers and multifaceted antipoverty programs on mental health in LMICs. Absent policy interventions, the pandemic could be associated with a lasting legacy of depression, particularly in settings with limited mental health support services, such as in many LMICs. We also demonstrated that mental health fluctuates with agricultural crop cycles, deteriorating during “lean”, pre-harvest periods and recovering thereafter. Ignoring such seasonal variations in mental health may lead to unreliable inferences about the association between the pandemic and mental health.

This paper evaluates the performance of eight tests with null hypothesis of cointegration on basis of probabilities of type I and II errors using Monte Carlo simulations. This study uses a variety of 132 different data generations covering three cases of deterministic part and four sample sizes. The three cases of deterministic part considered are: absence of both intercept and linear time trend, presence of only the intercept and presence of both the intercept and linear time trend. It is found that all of tests have either larger or smaller probabilities of type I error and concluded that tests face either problems of over rejection or under rejection, when asymptotic critical values are used. It is also concluded that use of simulated critical values leads to controlled probability of type I error. So, the use of asymptotic critical values may be avoided, and the use of simulated critical values is highly recommended. It is found and concluded that the simple LM test based on KPSS statistic performs better than rest for all specifications of deterministic part and sample sizes.

This paper investigates the triple impact of innovation, financial inclusion, and renewable energy consumption on the quality of the environment. The study employed data between 2007 and 2019 from selected emerging economies. Using the fixed effect, two-step GMM econometric method. The result found that financial inclusion and innovation have a positive relationship with carbon emissions, hence contributing to the reduction in the quality of the environment. Renewable energy consumption was found to reduce carbon emissions. Similarly, the interactive terms TPT*FIN, FIN*REN, and TPT*REN were all negatively related to carbon emissions. The study recommends that governments should increase financial instruments to support innovation that will enhance environmental quality. Additionally, governments should strengthen their environmental policies. Financial institutions should encourage firms to access green finance solutions. The value and originality of this study is the introduction of the interactive term, which throws more light on variables that affect the environment and through which channels. Moreso, there are few works with these interactive terms relative to emerging economies. Third, there are no previous studies that employed the fixed effect two-step GMM to analyze the impact of financial inclusion, technological innovation, and renewable energy consumption on environmental quality.

Non-uniform inlet flows frequently occur in aircrafts and result in chronological distortions of total temperature and total pressure at the engine inlet. Distorted inlet flow operation of the axial compressor deteriorates aerodynamic performance, which reduces the stall margin and increases blade stress levels, which in turn causes compressor failure. Deep learning is an efficient approach to predict catastrophic compressor failure, and its stability for better performance at minimum computational cost and time. The current research focuses on the development of a transonic compressor instability prediction tool for the comprehensive modeling of axial compressor dynamics. A novel predictive approach founded by an extensive CFD-based dataset for supervised learning has been implemented to predict compressor performance and behavior at different ambient temperatures and flow conditions. Artificial Neural Network-based results accurately predict compressor performance parameters by minimizing the Root Mean Square Error (RMSE) loss function. Computational results show that, as compared to the tip radial pressure distortion, hub radial pressure distortion has improved the stability range of the compressor. Furthermore, the combined effect of pressure distortion with the bulk flow has a qualitative and deteriorator effect on the compressor.

Targeted transfer programs have gained significant attention as effective tools for poverty alleviation. While the targeting mechanisms in social transfer programs have been successful in identifying individuals in need, their implementation often encounters challenges and failures. This study seeks to examine the differences in risk perception among poor households regarding their participation in social transfer programs. A theoretical model was developed to explore the relationship between risk aversion and financial transfers, and the analysis was further supported by statistical and econometric methods using the Income and Living Conditions Survey of Türkiye. The findings indicate that, under varying levels of risk aversion, while the impact of economy-wide risks on the uptake of social transfers remains consistent, idiosyncratic shocks and changes in utility have differential effects on participation. Specifically, households with higher levels of risk aversion tend to participate more actively in social transfer programs. These results underscore the importance of households’ risk perceptions in shaping policies related to social transfers and poverty reduction. Programs should incorporate behavioral factors alongside economic indicators to improve efficiency and fairness. This study's validity is limited by the assumption of a constant risk aversion coefficient for all households, as individual risk preferences were not measurable.