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This study aims to investigate magnetohydrodynamic (MHD) conjugate pure mixed convection considering interior heat production and resistive heating inside a square closed/open cavity featuring a rotating cylinder for aiding (clockwise) and opposing (counterclockwise) flow configurations. Moreover, the impacts of altering cylinder size and conductivity on the system’s overall performance to determine optimum conditions are examined in this investigation.

The closed chamber is differentially heated by keeping high and low temperatures at the vertical boundaries. In contrast, the open cavity has a heated left wall and an open right boundary. The Galerkin finite element method is used to solve the Navier–Stokes and the thermal energy equations, which construct the present study’s mathematical framework. Numerical simulations are conducted for the specified ranges of several controlling parameters: Reynolds (31.62 ≤ Re ≤ 1000), Grashof (10³ ≤ Gr ≤ 10⁶) and Hartmann numbers (0 ≤ Ha ≤ 31.62), and volumetric heat generation coefficient (Δ = 0, 3).

When Gr, Re and Ha simultaneously increase, the average Nusselt number along the warmed boundary rises accordingly. Conversely, interior heat production lowers heat transmission within the computational domain, which is also monitored regarding mean fluid temperature, overall entropy production and thermal performance criterion. Finally, the open cavity confirms better thermal performance than the closed cavity.

Comprehending the impacts of the magnetic field, Joule heating, internal heat generation and enclosed or open boundary on pure MHD combined free-forced convective flow offers valuable understandings of temperature fluctuations, velocity propagations, heat transport and irretrievable energy loss in numerous engineering applications.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

This study aims to investigate the relationship between stock liquidity, future investment, future investment efficiency and the moderating effect of financial constraints.

To serve the purpose of the study, the data of 178 companies listed on the Tehran Stock Exchange in 2012–2017 were examined. In this research, two Amihud liquidity and stock trading turnover measures were taken for the liquidity. Due to variance heterogeneity, the FGLS test was used. Moreover, a modified multiple regression analysis was used to investigate the moderating role of financial constraints.

The results showed a significant positive relationship between the firm stock liquidity in the current year and the next year investment; the firm stock liquidity (based on the stock trading turnover) in the current year and the next two years’ investment; the firm stock liquidity (based on the trading turnover index) in the current year and the next year investment efficiency; and the firm stock liquidity (based on the stock trading turnover) in the current year and the next two years’ investment efficiency. Moreover, financial constraints negatively moderated the relationship of firm stock liquidity (based on trading turnover index) in the current year and investment in the next year; investment in the next two years; investment efficiency in the next year; and investment efficiency in the next two years.

Given the importance of investment and investment efficiency in emerging markets especially in Asian emerging markets, and because the predicted impacts through financing constraints are usually unclear, this paper attempted to fill the existing gap and be innovative in this regard.

This study addresses a critical aspect of tourism in Arunachal Pradesh, India, by investigating how tour quality impacts on tourist satisfaction of domestic tourists. As one of the least explored regions of the country, Arunachal Pradesh holds immense tourism potential. Understanding the factors that contribute to tourist satisfaction, particularly the role of tour quality, is of paramount importance for enhancing the region's appeal as a sought-after travel destination.

The study was operationalized using survey questionnaires from domestic tourists (n = 200) visiting Ziro Valley, Arunachal Pradesh, India. A convenient sampling method was adopted for the study. Ordinary least square structural equation modeling (OLS-SEM) was used to measure the relationships.

The findings show that tourist expectations and tourist motivation influence tour quality and consequently impact the overall satisfaction of tourists.

This study extended the existing literature on tourist satisfaction in the domain of travel and tour by demonstrating the significance of tourist expectations and motivations on tour quality and tourist satisfaction. The findings offer insights for stakeholders seeking to enhance destinations' image, tour quality and overall tourist satisfaction.

This paper provides original contributions to the field of tourism by examining the effect of tour quality on tourist satisfaction. It integrates the factors, namely tourist expectations and motivations, into the analysis, offering insights into delivering customized tour experiences that meet tourists' needs.

Environmental pollution has been a great concern for the government of Bangladesh. Bangladesh was the least developed country, with a lot of financial challenges. The industrial process in Bangladesh has not been able to maintain the directives of the SDGs. The lack of proper industrial policy, technological backwardness and lacunae in implementing environmental governance have affected the environment of the country. The unorganised and informal manufacturing units are often accused of emitting greenhouse gases. Like other South Asian countries, the informal manufacturing sector in Bangladesh has been established without proper planning and environmental guidelines. In Bangladesh, the informal sector includes brick kilns, food processing factories, leather tanning, etc., which are responsible for environmental pollution, health hazards and violations of SDG goals. The issue of environmental pollution by the informal manufacturing sectors of Bangladesh needs to be investigated in the context of the socioeconomic profile of the country and the performance of the government in monitoring the issue. Due to the lack of environmental governance, a high level of pollution has been occurring in the country. What kinds of economic tools and industrial policies are needed to be implemented to avoid environmental hazards? The content analysis method will be applied in this chapter.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

Pabna is suffering from waterlogging problems from ancient times. The previous Drainage Master Plan was failed due to the lack of reflection of the general people of Pabna Municipality. As a result, this study focuses on identifying the causes of waterlogging in people's eyes. This paper will help the local authority and planners eradicate the waterlogging problem and build a planned and resilient community.

Both primary and secondary data were used for the study. Present drainage pattern, topology climatic elements were collected from the journals, websites and Municipal Ingratiated Development Plan (MIDP), Pabna-2008. The sample size was 246, and this respondent was surveyed. By the survey, the people's perception of waterlogging was collected. For that, five independent variables and one dependent variable were determined. These variables were determined by previous studies, reconnaissance survey of the study area. It used multiple linear regression and the correlation method; the causes of waterlogging were determined.

The study found solid waste disposal into the drainage, absence of operation and maintenance system, small discharge capacity with blocked in the current drains, nonappearance of combined drainage network of roadside drains and unplanned drainage system as the leading causes of waterlogging from the perception of the people. Also found that the absence of operation and maintenance system, solid waste disposal into the drainage and unplanned drainage system as the influencing causes on small discharge capacity with blocked in the current drains.

This study has focused on people's perceptions rather than secondary data. That is why this study will significantly impact eradicating the waterlogging problem from the Pabna Municipality and will carry out the core problems without any bias. This will lead to a sustainable, planned and resilient community.

The purpose of this study was to assess the repercussions of eucalyptus bark and tea leaf extract as natural dyes and antibacterial agents for jute–cotton union fabric.

The dye was collected from the eucalyptus tree’s bark and tea leaves by the aqueous extraction method. The fabric was dyed with potassium alum mordant, using pre-mordanting, post-mordanting and meta-mordanting methods. Examine the color performance analyzed the K/S, L*, a*, b*; fastness to washing using standard test method ISO 105 C06 A2S, rubbing fastness was performed by Crock meter using AATCC 115. The dyed fabrics were characterized by Fourier transform infrared radiation for the existence of various functional groups. Also, antimicrobial activity testing was done by the agar diffusion method (AATCC method SN 195 920) where Escherichia coli and Staphylococcus aureus were used.

The extracted dye tea leaves meta-mordant dyed samples were determined to have the strongest relative color. Fabrics pre-mordanted and post-mordanted with extracted eucalyptus and extracted tea dye produced the same outcome, which was excellent for wash fastness to staining and very good for wash fastness to fading. For both eucalyptus bark and tea, rubbing fastness on the pre-mordanted fabric produced very positive results. In mordanted colored fabric, significant antibacterial activity was discovered against S. aureus and E. coli.

This study demonstrates that the eucalyptus bark and tea leaves extract encompasses a solid antimicrobial action with amazing coloring execution for jute–cotton union fabric.

This study aims to test the role of the state of occupation, represented in Israel, as one of the most significant challenges, which faces the Jordanian water security. Where Israel expands in its policy and ideology everyday its hydro-hegemony over the Jordanian waters. Hence, its acts result in negative consequences on the Jordanian water and food security, which in turn affects the Jordanian national security as a whole.

This study relied on the following two approached to tackle its problem: first: descriptive approach: the descriptive approach depends on defining the apparent features and describing their nature and the type of the relationship between its variables. It aims to achieving a better and deeper understanding on the situation of its future policies and measures. And research uses the system analysis approach to handle the subject matter. Given the influence of water on the development, Jordan, as an organic or a political and social state, takes into account the reasons and causes of development. Jordan turns into an active political state, with water as an influencing factor on it. This premise represents the core of the system analysis approach.

The research concluded that the Israeli theft of the Jordanian waters is the main factor in the Jordanian water crisis. If Jordan had received its usurped water rights by Israel, it could have been able to solve its water issue represented in the increasing deficit in its water balance. Therefore, the Israeli hydro-hegemony on the Jordanian water resources caused the imbalance in its water security and, in turn, caused the development process to falter in general.

The value of the research lies in the fact that it addresses the most important reasons behind the water crisis in Jordan, represented in the Israeli control over the Jordanian water resources and the research shows that the amount of water stolen by Israel is enough to solve the water crisis in Jordan.

The study aims to enhance the detection and classification of conjunctival eye diseases' severity through the development of ConjunctiveNet, an innovative deep learning framework. This model incorporates advanced preprocessing techniques and utilizes a modified Otsu’s method for improved image segmentation, aiming to improve diagnostic accuracy and efficiency in healthcare settings.

ConjunctiveNet employs a convolutional neural network (CNN) enhanced through transfer learning. The methodology integrates rescaling, normalization, Gaussian blur filtering and contrast-limited adaptive histogram equalization (CLAHE) for preprocessing. The segmentation employs a novel modified Otsu’s method. The framework’s effectiveness is compared against five pretrained CNN architectures including AlexNet, ResNet-50, ResNet-152, VGG-19 and DenseNet-201.

The study finds that ConjunctiveNet significantly outperforms existing models in accuracy for detecting various severity stages of conjunctival eye conditions. The model demonstrated superior performance in classifying four distinct severity stages – initial, moderate, high, severe and a healthy stage – offering a reliable tool for enhancing screening and diagnosis processes in ophthalmology.

ConjunctiveNet represents a significant advancement in the automated diagnosis of eye diseases, particularly conjunctivitis. Its originality lies in the integration of modified Otsu’s method for segmentation and its comprehensive preprocessing approach, which collectively enhance its diagnostic capabilities. This framework offers substantial value to the field by improving the accuracy and efficiency of conjunctival disease severity classification, thus aiding in better healthcare delivery.