This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. By modeling directional variability in thermal conductivity using both uniform and Von Mises distributions, the study highlights the superiority of the Von Mises distribution in providing consistent and efficient thermal performance. The Von Mises distribution, known for its concentration around a mean direction, demonstrates a significant advantage over the uniform distribution, resulting in higher mean efficiency and lower variability. The findings underscore the importance of considering both stochastic effects and directional consistency in thermal systems, paving the way for more robust and reliable design strategies.

In this study, we consider the extended Brinkman's-Darcy model for a triple diffusive convection system which consists of some parameters such as Taylor number (Ta), Solutal Rayleigh numbers (RC1 , RC2 ), and Prandtl number (Pr). To investigate the range of these parameters, a dynamical system of the Ginzburg-Landau equation is developed. The parametric analysis and comparative study of the model for the three Rayleigh numbers which leads to the clear fluid layer, sparsely packed porous layer, and densely packed porous layer is done with the help of bifurcation maps and the Lyapunov exponents. It is found that for a certain range of parameters, the system exhibits a chaotic behaviour.

The current state of the Moroccan mountains in general, and the Beni Iznassen Mountains in particular, is the result of a dynamic process that has accelerated in recent years due to rapid demographic growth and the associated pressure on mountain natural resources. This has led to significant degradation, varying in severity across different areas within the Beni Iznassen Mountain range. In the context of these imbalances between natural mountain resources and the daily needs of the local population, there has been an emergence of various challenges, such as poverty and marginalization, affecting the lives of the region’s residents and a noticeable decline in socioeconomic indicators. This situation has consequently driven migration towards regions that better meet the population’s needs. Therefore, it has become essential to pay attention to this natural area by restoring its residents’ livelihoods, breaking their isolation, and rationalizing the use of its land-based natural resources. This has made the region a focus of territorial development efforts by both the state and local stakeholders.

Immeasurable basic and applied information has been evolved on all important floricultural crops through large-scale worldwide research on interdisciplinary aspects. The quantum and quality of work done on Chrysanthemum, among all other ornamentals, are par excellence. Conscientious attempt has been made to collect the whole multidisciplinary experimental results achieved world over. Despite remarkable achievements in knowledge and technology, a major part of present experimental research on chrysanthemum is largely a routine repeat of work. Assessment of past and present work is now significant for preparing target-oriented future research resolutions. This will help to secure the favored results within a justifiable period.

The fast-growing field of nanotheranostics is revolutionizing cancer treatment by allowing for precise diagnosis and targeted therapy at the cellular and molecular levels. These nanoscale platforms provide considerable benefits in oncology, including improved disease and therapy specificity, lower systemic toxicity, and real-time monitoring of therapeutic outcomes. However, nanoparticles' complicated interactions with biological systems, notably the immune system, present significant obstacles for clinical translation. While certain nanoparticles can elicit favorable anti-tumor immune responses, others cause immunotoxicity, including complement activation-related pseudoallergy (CARPA), cytokine storms, chronic inflammation, and organ damage. Traditional toxicity evaluation approaches are frequently time-consuming, expensive, and insufficient to capture these intricate nanoparticle-biological interactions. Artificial intelligence (AI) and machine learning (ML) have emerged as transformational solutions to these problems. This paper summarizes current achievements in nanotheranostics for cancer, delves into the causes of nanoparticle-induced immunotoxicity, and demonstrates how AI/ML may help anticipate and create safer nanoparticles. Integrating AI/ML with modern computational approaches allows for the detection of potentially dangerous nanoparticle qualities, guides the optimization of physicochemical features, and speeds up the development of immune-compatible nanotheranostics suited to individual patients. The combination of nanotechnology with AI/ML has the potential to completely realize the therapeutic promise of nanotheranostics while assuring patient safety in the age of precision medicine.