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After reading this case study, students will be able to understand the impact of cyber threats on businesses; explore the intersection of innovation and ethical considerations; understand the proactive role of entrepreneurs in identifying gaps in traditional industries, such as insurance, and innovating solutions that align with local dynamics; and learn to formulate strategies addressing cultural factors, market gaps and challenges.

The case study follows Hasnain, a prosperous entrepreneur in Pakistan, who was surprised by the news of a cyberattack on Bank Islami. This event, coupled with a personal data breach in his family’s business, triggered Hasnain’s willingness and interest to address the growing threat of cyber risks and attacks. As the progenitor of a digital solutions startup, he identified a gap in the insurance industry’s replication to cyber threats and envisioned the desideratum for a Sharia-compliant cyber-insurance product withal called cyber risk takaful. The case study explores Hasnain’s journey as he contemplated the challenges of introducing cyber risk takaful – a Sharia-compliant insurance solution for businesses and individuals. Apperceiving the low vigilance and perceived costs associated with cyber insurance, Hasnain faced the dilemma of surmounting these barriers in a country where the penetration of insurance, in general, is already minimal. The story raises critical questions: How can Hasnain efficaciously introduce cyber risk takaful to a market reluctant to embrace cyber insurance? What business strategies should he use to engender vigilance and acceptance of this innovative insurance solution? Will businesses and individuals embrace the concept of cyber risk takaful and recognize its paramount in forfending their digital assets?

This case study is designed to meet the educational needs of both undergraduate and postgraduate students, particularly those enrolled in business administration programs. This case study is tailored for students in the final year of BBA and the first year of MBA programs. It is also well-suited for executive education programs that focus on strategic decision-making in the context of emerging market challenges, such as entrepreneurship and corporate strategy. The case study is particularly relevant for courses centered on entrepreneurship, business strategy, strategic management and corporate strategy.

Teaching notes are available for educators only.

CSS11: Entrepreneurship.

The boundary layer flow of immiscible fluids plays a crucial role across various industries, influencing advancements in industrial processes, environmental systems, healthcare and more. This study explores the thermally radiative boundary layer flow of a shear-driven Ree–Eyring fluid over a nanofluid. The investigation offers valuable insights into the intricate dynamics and heat transfer behavior that arise when a nanofluid, affected by thermal radiation, interacts with a non-Newtonian Ree–Eyring fluid. This analysis contributes to a deeper understanding of the complex interactions governing such systems, which is essential for enhancing efficiency and innovation in multiple applications.

The simulation investigates the convergence of boundary layers under varying shear strengths. A comparative analysis is conducted using γAl2O3 and Al₂O₃ nanoparticles, with water as the base fluid. The model’s numerical outcomes are derived using the bvp4c method through the application of appropriate similarity transformations. The resulting numerical data are then used to produce graphical representations, offering valuable insights into the influence of key parameters on flow behavior and patterns.

The temperature of the Al₂O₃ nanoparticles is always higher than the γAl2O3 nanoparticles, and hence, Al₂O₃ nanoparticles become more significant in the cooling process then γAl2O3 nanoparticles. It is also observed that the fluid velocity for both regions is enhanced by increasing values of the Ree–Eyring fluid parameter.

The results stated are original and new with the thermal radiative boundary layer flow of two immiscible Ree–Eyring fluid and Al₂O₃/γAl2O3 nanofluid.

Emissions have significant environmental impacts. Hence, minimizing emissions is essential. This study aims to use a hybrid neural network model to predict carbon monoxide (CO) and nitrogen oxide (NOx) emissions from gas turbines (GTs) to enhance emission prediction for GTs in predictive emissions monitoring systems (PEMS).

The hybrid model architecture combines convolutional neural networks (CNN) and bidirectional long-short-term memory (Bi-LSTM) networks called CNN-BiLSTM with modified extrinsic attention regression. Over five years, data from a GT power plant was uploaded to Google Colab, split into training and testing sets (80:20), and evaluated using test matrices. The model’s performance was benchmarked against state-of-the-art emissions prediction methodologies.

The model showed promising results for GT CO and NOx emissions. CO predictions had a slight underestimation bias of −0.01, with root mean-squared error (RMSE) of 0.064, mean absolute error (MAE) of 0.04 and R² of 0.82. NOx predictions had an RMSE of 0.051, MAE of 0.036, R² of 0.887 and a slight overestimation bias of +0.01.

While the model demonstrates relative accuracy in CO emission predictions, there is potential for further improvement in future research.

Implementing the model in real-time PEMS and establishing a continuous feedback loop will ensure accuracy in real-world applications, enhance GT functioning and reduce emissions, fuel consumption and running costs.

Accurate GT emissions predictions support stricter emission standards, promote sustainable development goals and ensure a healthier societal environment.

This paper presents a novel approach that integrates CNN and Bi-LSTM networks. It considers both spatial and temporal data to mitigate previous prediction shortcomings.

The use of polysaccharides increases solubility and consistency and causes functions such as viscosity? Moisture and food emulsifier stabilizer. This study aims to enrich the formulation of low-fat mozzarella cheese using microcoated vitamin D3 (VD3).

This study investigates the addition of hydrocolloids to low-fat mozzarella cheese to enhance its properties and nutritional value. Tests were conducted on cheese samples with 0.05% and 0.25% hydrocolloid concentrations at various stages: before production and at three and six months’ postproduction. The samples were evaluated for elasticity, pH and solubility to select the best one, which was then fortified with VD3. The vitamin was microencapsulated using alginate and whey protein to shield it from light and oxygen, optimizing the formula using the response surface method. The fortified cheese was tested for VD3 content over its shelf life.

Results indicated that all hydrocolloids tested improved moisture and meltability of the cheese while higher protein levels increased stretchability two to threefold. Rice starch hydrocolloid at 0.05% concentration was chosen due to superior sensory scores and minimal oil separation. This study concluded that VD3 levels remained stable during the cheese’s shelf life, suggesting that this approach could enhance the nutritional value of low-fat cheese without compromising its quality. Therefore, after examining the obtained results and comparing the regression models, the results indicated that the Quadratic model was chosen to investigate the effect of independent variables on the response rate, which had a statistically significant difference with other models (p = 0.0019). Also the results of the area under the curve and using the encapsulation efficiency equation, the percentage of microencapsulated vitamin was obtained, and according to the simulation results, the encapsulation efficiency was reported as 89.02%.

Developing innovative functional dairy products fortified with VD3 could improve the vitamin D status in deficient populations. Therefore, these designs can be applied at industrial scales for functional cheese production.