European Journal of Theoretical and Applied Sciences
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Leadership Models in VUCA Environments: Self-Similarity and Decentralization
Get PDFIn the contemporary business landscape, characterized by heightened Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), leadership is increasingly pivotal in navigating organizations toward sustained success. This paper examines two leadership paradigms—self-similarity and decentralization—by analyzing their respective efficacies within stable and VUCA environments. The self-similarity model, predicated on the principles of consistency and uniformity, is traditionally effective in stable contexts where operational predictability and efficiency are essential. However, this model's inherent rigidity may render it inadequate in VUCA environments, where adaptability and responsiveness are paramount. Conversely, decentralization, which empowers decision-making at multiple levels within the organization, offers enhanced agility and responsiveness, indispensable traits in navigating the complexities. However, this model's emphasis on flexibility and localized autonomy can also introduce risks related to coherence and strategic alignment, particularly in environments that demand uniformity and centralized control. It is important for leaders to be aware of these potential pitfalls when considering the implementation of decentralization. Through a comparative analysis, this paper proposes a strategic framework that enables leaders to discern when and how to transition between these leadership approaches. Doing so underscores the importance of dynamic leadership in fostering organizational resilience and adaptability. Leaders capable of balancing self-similarity with decentralization are better equipped to steer their organizations through challenges of stable and volatile environments, thereby securing long-term organizational viability. 
Heat Transfer in Unsteady Flow of Third-Grade Fluid Over a Flat Rigid Plate with Porous Medium
Get PDFThis study investigates the heat transfer characteristics of an unsteady flow of a third-grade fluid over a flat rigid plate embedded in a porous medium. The governing equations, including the momentum and energy equations, are derived based on the assumptions of incompressible fluid and negligible body forces. Analytical methods are employed to solve the coupled non-linear equations. The effects of various parameters, such as the porosity of the medium, thermal conductivity, and the non-Newtonian fluid properties, on the velocity, temperature profiles, and skin friction are discussed extensively. The results provide insights into optimizing heat transfer processes in engineering applications, including polymer processing and geothermal systems. 
The Role of Industrial Energy Efficiency in Emission Reduction: Insights from China
Get PDFIndustrial energy efficiency is a pivotal strategy for mitigating greenhouse gas (GHG) emissions, particularly in industrialized nations like China, where the industrial sector accounts for over 70% of total emissions. This study analyzes China's progress in reducing emissions through technological upgrades, energy management systems, and policy interventions. Employing a comprehensive review of industrial energy data and policy frameworks from 2005 to 2024, the findings reveal a 40% reduction in industrial energy intensity and a 32% decrease in CO₂ emissions per unit of output.
Key measures, including combined heat and power systems, renewable energy integration, and ISO 50001-certified systems, have been instrumental, supported by targeted programs for energy-intensive enterprises and financial incentives. However, challenges such as coal dependency, regional disparities, and limited digitalization persist.
China’s efforts present a valuable model for achieving carbon neutrality by 2060 and offer insights for other nations seeking to balance industrial growth with sustainability. The findings underscore the critical role of energy efficiency in combating climate change while highlighting areas for future research and policy development. 
Unplanned Use of Schools as Emergency Temporary Camps for Displaced Disaster Victims: Implications for Teaching and Learning Outcomes in Nigeria
Get PDFWhen schools are inundated and submerged by floods, overwhelmed with extreme drought and heatwaves, lockdown by persistent conflicts crises and banditry, or sudden epidemics like the case of COVID-19 and Ebola, etc, academic activities are disrupted, causing a significant impact on students' learning. Classrooms and educational materials may be damaged or destroyed, leading to school closure and suspension of formal teaching and learning. This paper therefore evaluates the Unplanned Use of Schools as Emergency Temporary Camps for Displaced Disaster Victims and its Implications for Teaching and Learning Outcomes in Nigeria. Its specific objectives were to assess the rationale for designating school facilities as emergency temporary camps during and after a disaster; the effect of unplanned school closure on the children, teachers or staff, parents or family, as well as the school academic calendar; and the key considerations and checklist for preparing schools as temporary camps for displaced disaster victims. The paper noted the absence of adequate preparedness plans, a lack of resilient school infrastructure, a low level of deployment of digital teaching and learning platforms, as well as other adaptive and contingency measures as some of the limitations in the use of schools as temporary camps for disaster evacuees and victims prepared and planned well ahead before a disaster strike. It recommends deploying a new paradigm shift of having adequate contingency planning and preparedness in place before a disaster strikes,in a bid to mitigate the impact of the disruption of already planned school academic calendar and activities, thereby ensuring that formal teaching and learning are minimally disrupted most especially in the Secondary and Primary Schools which are the ones that are regularly used as as temporary camps for disaster displaced victims in Nigeria. 
About the Modeling, Optimization and Simulation of a Stationary Infinite Horizon Problem from the Financial Field
Get PDFThis article is an application of the paper (Belhenniche et al., 2024). We will solve a new optimization problem from the financial and economic field, for the maximization of the utility of households, with infinite-horizon iterative techniques and a numerical simulation in C++. We developed a procedure to solve the stationary infinite-horizon optimization problems and for regression analysis between functions and paramaters. In the article (Belhenniche et al., 2024) we showed the convergence in norm with probability for an iterative procedure defined for our problem under the stated assumptions. For regression analysis we used the SPSS program. The conclusions are we can use C++ and an operator in a Banach space, for fast and numerical simulations, for study the optimal cost function of an infinite horizon problem. 
AI-Powered Autonomous Farming: The Future of Sustainable Agriculture
Get PDFThe integration of Artificial Intelligence (AI) in agriculture represents a transformative shift in traditional farming practices, enhancing productivity, efficiency, and sustainability. This paper explores key applications of AI across smart farming, vertical and urban farming, and fully autonomous farms, highlighting the significant role of AI in optimizing resource management, improving crop health monitoring, and automating agricultural operations. The synergy between AI and the Internet of Things (IoT) facilitates real-time data analysis, leading to precision agriculture and proactive decision-making. In urban and vertical farming, AI technology supports resource optimization and continuous crop monitoring, addressing challenges related to food security in densely populated areas. Fully autonomous farms further exemplify the advancement of agricultural technology by minimizing labor costs and maximizing operational efficiency.
However, the widespread adoption of AI in agriculture faces several challenges, including high initial investment costs, technological complexity, data privacy concerns, regulatory hurdles, and ethical implications related to employment. As the agricultural landscape evolves, addressing these challenges is vital for the successful implementation of AI technologies. Future prospects indicate that ongoing advancements in AI and robotics will enhance food production systems, contributing to sustainability and resilience in agriculture.
This exploration underscores the importance of continued collaboration among technology providers, policymakers, and the farming community to harness the potential of AI while mitigating associated risks, ensuring that modern agricultural practices meet the demands of a growing global population in an environmentally responsible manner. 
The Effect of Ground Application with Optimus Plus and Foliar Spraying with Amino Acids on Apple Seedlings, Sharabi Variety
Get PDFThe research was conducted in the plant canopy of the Department of Horticulture and Landscape Engineering - College of Agriculture - University of Karbala for the period from the beginning of April until October 2023 with the aim of studying the effect of foliar spraying with amino acids and ground addition of Optimus plus in improving some vegetative growth characteristics of apple seedlings, Sharabi variety. A factorial experiment was carried out according to a randomized block design (R.C.B.D). The first factor was amino acids at three concentrations (0-1.5-3 g/L), and the addition intervals were every 14 days. The second factor Optimus plus was at three concentrations (0-1.5-3 ml/L). It is sprayed every 14 days with three replicates, with each replicate including 18 seedlings, so the total number of seedlings is 54 seedlings, homogeneous in growth. The results were analyzed statistically using the Anova Table K, and the means were compared using the least significant difference (L.S.D) under the probability level of 0.05. 
About Fractional Programming Problems and SIR Models
Get PDFFractional programming problems have attracted the attention of many specialists due to their applications in many fields as Economics and Finance, Engineering, Biology, Epidemiology, Medicine, etc. In this article, we present examples of the problems of the fractional programming, and we discussed a parallel between the SIR models built using classical differential equations and using fractional differential equations. Epidemiological models (i.e. SIR model and it’ s generalizations) or pollution models, can provide particular cases of numerators and denominators for objective functions in fractional programming problems. For the SIR epidemiological model, the article discusses the existence of the solution for its generalization and brings a novelty regarding its approach as a model with partial derivatives. In the classical models, the rate of change is more abrupt, which suggests a more deterministic and predictable behavior in the spread of the disease. The fractional derivative brings a memory effect, which makes the spread and recovery slower and more extended over time. Simulations of many optimization problems were also realized in GeoGebra, Maple and MATLAB software. A case study related to optimizing vaccination rates between two regions, applied the Frank-Wolfe method for a fractional programming problem and an implementation in Maple. In the case study, in a context of a city divided into two regions, we supposed that the authorities aim to optimize the vaccination rate to minimize the combined infection rate. The aim was to maximize the ratio between vaccination effectiveness and total costs. A principal conclusion is that the use of simulations, for example, in GeoGebra, Maple or MATLAB software, can increase the quality of the teaching-learning process for students, in subjects such as Operational Research or Optimization Techniques. 
Possible Extensions on Quantum Field Theory, Loop Quantum Gravity and Statistics
No full textBased on the extensive quantum theory, the extensive quantum field theory first is discussed. Second, we propose the extensive loop quantum gravity and nineteen possible ways. Third, we research the extensive quantum statistics and relations with various interactions, in which FD and BE statistics correspond to repulsion and attraction interactions, respectively. Fourth, we study these theoretical applications in biolog
Evaluation of Hormonal and Histological Changes in the Reproductive System of Mice in Females and Males after Meperidine Administration
No full textBackground: Meperidine is one of the synthetic opioid analgesics regularly given as a prescription after surgery. Objective: This study aims to investigate the differential effects of meperidine on the reproductive systems of female and male mice. Methods: The study sample was 40 mice. After 14 days, the animals were left for mating. The experiment was divided into two groups: T1, the control animals (n = 20, male and female) were injected (1 ml/day) with distilled water intramuscularly, and T2, the meperidine treatment (n = 20, male and female) was administered (25 mg/kg/day). After 11 weeks, the blood samples were collected for laboratory tests. To perform histological examination, all animals were slaughtered. Result: The results showed a significant decrease in the FSH, LH, estrogen and progesterone in the females treated. The testosterone, LH, and FSH levels significantly decreased, whereas prolactin levels were highly significant in the males of the treated group compared to the control group. Histopathological findings of the ovary revealed congested tissues and hyperplasia in the endometrium with inflammatory cell infiltration and germ cell degeneration in testicular tissues. Conclusion: In conclusion, this research proved the direct effect of meperidine on the levels of gonadotropins (LH and FSH) and sex hormones (testosterone in males and estrogen in females). Meperidine has an important role on fertility in female mice, in contrast to male mice and body weight.