A nonlinear energy harvesting system is proposed, consisting of a tip-loaded slender vertical cantilever beam with a strain gauge attached. The beam is oriented with its free end pointing upward and its fixed end at the bottom, and is subjected to vertical base excitations. Under such excitation, the slender beam experiences a compressive force resulting from both the base motion and the tip mass. The theory of buckling is explored, and it is shown that beyond a critical value of the crippling force, the beam undergoes buckling. To understand the system’s stability, the potential energy equation is analyzed, revealing conditions for monostability, biostability, and stochastic responses. Free vibration tests and corresponding simulations show good agreement in the natural frequencies of the proposed beam. Experimental results under frequency-swept vertical excitation demonstrate that the combined inertial forces from the tip mass and base motion can transform the system’s behavior from monostable to bistable. This resulted in non-linear large amplitude horizontal vibrations of the harvester. The strain gauge measurements confirm the feasibility of using this vertical cantilever beam for the efficient vibration energy harvesting.

Chemical graph theory is the application of discrete mathematics to chemistry applied to model, physical and biological properties of chemical compounds. In this paper we establish Atom-Bond Connectivity Index ABC(G), Geometric Arithmetic Index GA(G), First and Second Zagreb Indices M1(G) and M2(G), Randic Index R(G), Sum Connectivity Index SCI(G), Harmonic Index H(G), Augmented Zagreb Index AZI(G), Forgotten Index F(G), Inverse Sum Indeg Index ISI(G), Hyper-Zagreb Index HM(G) for Phthalocyanine Tetrasulfonic Acid, Phthalocyanine Octacarboxylic Acid, Anthraquinone Cyanines, Phthalocyanine Porphyrin and zinc bis(1,4-didecylbenzo) bis(3,4-pyridoporphyrazine).

Over the past several decades, education has made great progress due to advancements in information and communication technology (ICT). Artificial intelligence (AI) is a potential technology for revolutionizing education and learning. However, incorporation of AI in education should prioritize emotional management, not only academic achievements, as it is vital in the educational process (González et al., 2023). This study examines how emotions and artificial intelligence impact learning and interpersonal interactions in educational environments. Automated grading, plagiarism detection, virtual assistants, and adaptive learning systems can alter higher education teaching and research. Many faculty members reject AI adoption because they see it as a threat to their positions. Eliminating such resistance may need emotional intelligence (EI). Higher EI faculty can better handle stress, emotions, and technology. This may improve their teaching, research, and institutional contributions. This study examines how Emotional Intelligence (EI) affects teacher opposition to AI adoption and job performance in Rajasthan, India, higher education institutions. Based on theories of emotional regulation and technology resistance, the study suggests that teachers with greater EI can better manage stress, adjust to technological disruptions, and adopt AI-enabled practices, lowering resistance and improving performance. Chi Square and Annova analyzes data from a quantitative, cross-sectional survey using verified EI, technology resistance, and work performance measures. The findings aim to extend theoretical understanding by integrating emotional and technological dimensions of faculty performance. Additionally, they provide practical insights for policymakers and administrators to develop EI-based interventions and training programs that facilitate smoother AI integration in higher education.

Solar energy is rendered useful among renewable energy in India. The government has launched a National Solar Mission to meet future demands for electricity. The favorable condition in throughout the country provides enormous scope for research and development. This work is aimed to fine-tune design parameters like band-gap, doping concentration and thickness of CIGS absorber to enhance the energy conversion per unit cell. For this a laboratory reference model was considered. A precise and correlated simulation model is designed using SCAPS-1D. Effects of optimization of its parameters are studied where band gap of CIGS is varied in the range 1.040eV to 1.411eV, doping consideration from 1015 (/cm3) to 1017 (/cm3) and thickness of CIGS layer from 0.5µm to 2µm. Number of iterations of simulations are performed to precise the open circuited voltage and short-circuited current density. Another objective of this work was to replace toxic Cd by a suitable compound. A well extracted ZnS of are incorporated with different compositions to propose an optimized CIGD/ZnS/ZnO structured solar cell. The 26.82% efficiency (best performance) achieved at band-gap 1.268eV, acceptor concentration 1015(1/cm3), and thickness 1.5µm with buffer Zn1-yS:Cuy at y=0.06 which is 28.55% higher than that of reference cell.

El-Bayadh region, situated in southwestern Algeria, is marked by a semi-arid climate with scarce and irregular precipitation, making groundwater the primary source to satisfy growing water demands. Rapid economic development and population growth have further intensified the pressure on these limited resources, creating a significant deficit. This study seeks to evaluate the current status of water resources in the region, project future requirements, and anticipate the main challenges for sustainable water management. To achieve this, Geographic Information Systems (GIS) were employed to develop thematic and spatial databases, facilitating the assessment of both surface and groundwater resources. Furthermore, the hydrochemical properties of key aquifers—namely the Albian, Infra-Cretaceous, Bajo-Bathonian, and Continental Intercalary systems—were examined through Piper diagram analyses. The findings underscore the urgent necessity of adopting integrated water resource management strategies that combine conservation measures with the mobilization of non-conventional resources to secure water availability in El Bayadh.

In an increasingly interconnected world, opportunities for global collaboration have become critical in advancing research, business relations, and career development. This paper explores the potential benefits of gathering global participants in an event that facilitates the exchange of ideas and experiences. Such gatherings enable participants from diverse regions to engage in meaningful discussions, share innovative ideas, and establish connections that could lead to future collaborations. The paper discusses how in-person interactions foster networking, strengthen professional relationships, and encourage the formation of cross-border partnerships, ultimately contributing to the success and growth of individual careers, research endeavours, and business ventures. Through this research, we argue that fostering international linkages plays a crucial role in building a global community that is not only knowledgeable but also collaborative in nature, enabling advancements in various fields of study and industry.

This paper examines the transformative convergence of digital archives and oral narratives in contemporary historical research. Traditional archives, though foundational, have long privileged elite voices while excluding subaltern experiences. Digital archives expand access, preserve fragile sources, and generate new forms of evidence, yet they also raise critical concerns regarding authenticity, bias, and the reproduction of existing hierarchies. Oral narratives, once dismissed as unreliable, have emerged as essential tools for recovering silenced voices and reconstructing lived experience, though they too present methodological and ethical challenges rooted in memory, subjectivity, and power relations. By analyzing the strengths and limitations of both approaches, the paper argues that their integration offers the most promising path forward. Digital technologies enhance the preservation and dissemination of oral testimonies, while oral traditions complicate and enrich the archival record. Together, they democratize historical practice, broaden participation, and produce more inclusive narratives. The study concludes that a critical and ethical synthesis of these methods can redefine historical inquiry, creating histories that are both rigorous and profoundly humane.

Artificial Intelligence (AI) in AI – induced neuro – inspired leadership refers to the integration of Artificial Intelligence technologies to enhance AI – induced neuro – inspired leadership practices, decision-making, and organizational performance. AI tools automate routine tasks, analyze data for insights, and improve strategic planning, ultimately allowing leaders to focus on more strategic and human-centric aspects of AI – induced neuro – inspired leadership. However, ethical considerations and potential biases in AI systems also need to be addressed. AI algorithms can analyze large datasets to provide leaders with valuable insights and predictions, enabling more informed and data-driven decisions. AI assists in identifying trends, forecasting outcomes, and optimizing resource allocation, leading to more effective strategic planning. AI-powered tools can automate routine tasks, streamline workflows, and optimize processes, freeing up leaders’ time for more strategic initiatives. Leaders need to be aware of potential biases in AI algorithms and develop ethical frameworks to ensure fairness and accountability in the use of AI. AI can be used to identify and develop future leaders, personalize AI – induced neuro – inspired leadership training, and ensure smooth succession planning. AI-powered analytics tools can provide insights into employee performance, customer behavior, and market trends. Chat bots and virtual assistants can handle routine inquiries, freeing up human staff for more complex tasks. AI-driven talent management systems can help organizations identify and develop future leaders. AI-powered tools for automation can streamline workflows and improve efficiency across various departments. Protecting sensitive data used in AI systems is crucial. Ensure that AI algorithms are free from bias and promote fairness in decision-making is essential. Some employees may be resistant to the integration of AI, requiring effective change management strategies. Leaders need to consider the ethical implications of using AI and develop appropriate guidelines. In conclusion, AI is transforming AI – induced neuro – inspired leadership by providing powerful tools for decision-making, strategic planning, and operational efficiency. However, it is crucial for leaders to understand the ethical implications and potential challenges associated with AI integration and to develop strategies for responsible and effective implementation.

Modern Communication systems require network security in order to provide safe data transfer, efficient routing and fault tolerance measures. Total Prime Graceful labeling facilitates the identification of security threats within the network infrastructure. Total Prime Graceful labeling is an intriguing concept in graph theory that has applications in many different domains because of its special qualities and possible uses. The practical uses of total prime graceful labeling in diverse domains of network security contexts are examined in this study.

This study evaluates the role of energy consumption in predicting CO2 emissions and economic growth using advanced machine learning models. By analyzing data from 220 countries spanning 1990 to 2022, the research integrates Decision Tree, Random Forest, XGBoost, LightGBM, and CatBoost algorithms to uncover key predictors and their impacts. The findings indicate that electricity and fossil fuel consumption are critical predictors of CO2 emissions, while renewable energy use significantly influences economic growth. Gradient boosting models, particularly LightGBM and CatBoost, demonstrated superior predictive performance, capturing complex relationships between energy use and economic outcomes. The study concludes that balancing fossil fuel use with renewable energy adoption is essential for sustainable economic development and environmental protection. Recommendations for investors include prioritizing renewable energy projects and supporting energy efficiency initiatives. Managers are encouraged to adopt sustainable practices and invest in innovation, while government agencies should promote renewable energy policies and enforce energy efficiency standards. These insights aim to inform policy and strategic decision-making to achieve sustainable development goals.