Search Results (5,929)

Accurate measurement of material mechanics parameters is crucial for evaluating process quality and product reliability and is a major challenge in the development of 3D heterogeneous integration technology. Aiming to perform high-accuracy measurements of the elastoplastic nonlinear constitutive parameters of microelectronic materials using the nanoindentation testing technique, we take advantage of a neural network to construct a forward characterization model to characterize these response characteristic parameters for different materials, design an improved algorithm for obtaining a reverse iterative solution of the forward characterization model, and develop a material mechanics parameter measurement method to solve overdetermined equations using the least-squares method. This method was further improved by addressing the issues of algorithm stability and solution uniqueness, achieving high-precision and fast reverse solutions for elastoplastic constitutive parameters. The relative error of the material parameters is less than 3% (95% confidence interval), the maximum error is less than 8%, and the inversion convergence error of the key indentation response characteristic parameters is less than 0.1%. The difference between the measured material parameters and the theoretical model in the influence on the process stress of TCV (through ceramic via) products is verified through finite element simulation. Full article

The operational reliability of Insulated Gate Bipolar Transistor (IGBT) modules in demanding transportation applications, such as traction systems, is critically challenged by solder layer and bond wire failures under cyclic thermal stress. To address this, this paper proposes a novel health monitoring framework that innovatively synergizes micro-scale spatial thermal analysis with microsecond electrical dynamics inversion. The method requires only non-invasive temperature measurements on the module baseplate and utilizes standard electrical signals (load current, duty cycle, switching frequency, DC-link voltage) readily available from the converter’s controller, enabling simultaneous diagnosis without dedicated voltage or high-bandwidth current sensors. First, a non-invasive assessment of solder layer fatigue is achieved by correlating the normalized thermal gradient ($\nabla T_{\mathrm{P}}$) on the baseplate with the underlying thermal impedance ($Z_{\mathrm{JC}}$). Second, for bond wire aging, a cost-effective inversion algorithm estimates the on-state voltage ($V_{\mathrm{ce},\mathrm{on}}$) by calculating the total power loss from temperature, isolating the conduction loss ($P_{\mathrm{cond}}$) with the aid of a Foster-model-based junction temperature ($T_{\mathrm{J}}$) estimate, and finally computing $V_{\mathrm{ce},\mathrm{on}}$ at a unique current inflection point ($I_{\mathrm{C},\inf }$) to nullify $T_{\mathrm{J}}$ dependency. Third, the health states from both failure modes are fused for comprehensive condition evaluation. Experimental validation confirms the method’s accuracy in tracking both degradation modes. This work provides a practical and economical solution for online IGBT condition monitoring, enhancing the predictive maintenance and operational safety of transportation electrification systems. Full article

Saudi Arabia’s ambition to improve quality of life is paving its way, and this study aligns with that vision, adopting an experimental approach to explore urban solutions to enhance outdoor thermal comfort for pedestrians in neighborhoods within Riyadh City, Saudi Arabia. Given the city’s hot and arid climate, outdoor spaces are often subject to extreme thermal conditions that reduce the quality of life for residents. To address this issue, the study utilizes Ladybug in Grasshopper, a tool designed for modeling the microclimate and assessing the impact of urban design strategies on outdoor thermal comfort. A base model representing the current urban fabric of selected neighborhoods is developed, and then multiple alternatives of urban morphology (sidewalk, setbacks, fence, and vegetation) are evaluated for their effectiveness in mitigating heat stress and improving outdoor thermal conditions. The findings from this study provide valuable insights into how urban planning and design interventions can be tailored to the unique climatic challenges of Riyadh, with potential applications for enhancing the sustainability, livability, and overall quality of life of the city’s neighborhoods. Full article

The purpose of this article is to introduce the concept of elliptic-valued suprametric spaces and to establish some common fixed point theorems within this newly proposed framework. The development of elliptic-valued suprametric spaces, along with the main results presented here, is illustrated through non-trivial examples. As applications, we employ our fixed point results to study the nonlinear Volterra integral equation of the second kind, demonstrating the existence and uniqueness of solutions under suitable conditions. In particular, we highlight the role of such equations in age-structured population models, where they serve as powerful tools for describing hereditary effects, density-dependent interactions, and delayed responses in population dynamics. This connection bridges the abstract theory with applied contexts in mathematical biology, ecology, and epidemiology, emphasizing the relevance of elliptic-valued suprametric structures in both theoretical analysis and real-world applications. Furthermore, we derive corresponding fixed point results in elliptic-valued suprametric spaces, complex-valued suprametric spaces, elliptic-valued metric spaces, and complex-valued metric spaces as corollaries of our main findings. Full article

Advances in sensing technologies are increasingly transforming cutting operations by enabling data-driven condition monitoring, predictive maintenance, and process optimization. This review surveys recent developments in sensing modalities for cutting systems, including vibration sensors, acoustic emission sensors, optical and vision-based systems, eddy-current sensors, force sensors, and emerging hybrid/multi-modal sensing frameworks. Each sensing approach offers unique advantages in capturing mechanical, acoustic, geometric, or electromagnetic signatures related to tool wear, process instability, and fault development, while also showing modality-specific limitations such as noise sensitivity, environmental robustness, and integration complexity. Recent trends show a growing shift toward hybrid and multi-modal sensor fusion, where data from multiple sensors are combined using advanced data analytics and machine learning to improve diagnostic accuracy and reliability under changing cutting conditions. The review also discusses how artificial intelligence, Internet of Things connectivity, and edge computing enable scalable, real-time monitoring solutions, along with the challenges related to data needs, computational costs, and system integration. Future directions highlight the importance of robust fusion architectures, physics-informed and explainable models, digital twin integration, and cost-effective sensor deployment to accelerate adoption across various manufacturing environments. Overall, these advancements position advanced sensing and hybrid monitoring strategies as key drivers of intelligent, Industry 4.0-oriented cutting processes. Full article

As a natural refrigerant, CO₂ shows significant potential in sustainable thermal engineering due to its environmental safety and economic viability. While the transcritical CO₂ cycle demonstrates strong performance in heating, low-temperature applications, and integration with renewable energy sources, its widespread adoption is hindered by key challenges at the application level. These include: high sensitivity of system efficiency to operating conditions, which creates an “efficiency hump” and narrows the optimal operating window; increased component costs and technical challenges for key devices such as multi-channel valves due to high-pressure requirements; and complex system control with limited intelligent solutions currently integrated. Despite these challenges, the transcritical CO₂ cycle holds unique value in enabling synergistic energy conversion. Its ability to efficiently match and cascade different energy grades makes it particularly suitable for data center cooling, industrial combined cooling and heating, and solar–thermal hybrid systems, positioning it as an indispensable technology in future low-carbon energy systems. To fully realize its potential, development efforts must focus on high-value applications and key technological breakthroughs. Priority should be given to demonstrating its use in fields where it holds a distinct advantage, such as low-temperature refrigeration and high-temperature industrial heat pumps, to establish commercially viable models. Concurrently, core technologies—including adaptive intelligent control algorithms, high-efficiency expanders, and cost-effective pressure-resistant components—must be advanced. Supportive policies, encompassing energy efficiency standards, safety regulations, and fiscal incentives, will be essential to facilitate the transition from demonstration projects to widespread industrial adoption. Full article

Background: Health care work contributes significantly to greenhouse gas emissions. Primary health care is community-based and focused on wellness and disease prevention. Within primary health care, pharmacists are most frequently the stewards of medicines, supplies, and other tangible products that contribute to carbon footprints. Pharmacists are in a unique position to help adapt to and mitigate climate change-related issues. Objective: To examine pharmacists’ perspectives on climate adaptation and mitigation strategies in primary health care delivery in interprofessional settings. Methods: Semi-structured qualitative interviews with primary care pharmacists were undertaken. Constant-comparative data analysis was used to code and categorize findings. The COREQ system was applied to ensure rigor and quality of research. Results: A total of 21 primary care pharmacists participated in this research. Several core themes emerged as follows: (a) universal agreement that climate change is real and primary health care needs to evolve rapidly to address it; (b) recognition that primary health care is time-pressured and resource constrained so successful solutions need to be pragmatic and work within realities of practice; (c) identification of actionable priorities with high potential for mitigation impact; and (d) mobilization of a coalition to develop system-wide initiatives that could be implemented in primary health care. Conclusions: Collaborative approaches and those that focus on the implementation of regulatory requirements were identified as being most productive in this setting. Full article

This research work investigates the existence, uniqueness, and stability of solution for a time-fractional fourth-order partial differential equation, subject to two initial conditions and four nonlocal integral boundary conditions. The equation incorporates several key components: the Caputo fractional derivative operator, the Laplace operator, the biharmonic operator, as well as terms representing frictional and viscoelastic damping. The presence of these elements, particularly the nonlocal boundary constraints, introduces new mathematical challenges that require the development of advanced analytical methods. To address these challenges, we construct a functional analytic framework based on Sobolev spaces and employ energy estimates to rigorously prove the well-posedness of the problem. Full article

This study addresses the stability and quasi-synchronization of fractional-order neural networks that incorporate mixed delays, system uncertainties, and external disturbances. Accordingly, a more realistic neural network model is constructed. For fractional-order neural networks incorporating mixed delays and uncertainties (FONNMDU), this study establishes a criterion for uniform asymptotic stability and proves the existence and uniqueness of the equilibrium solution. Furthermore, it investigates the global uniform stability and stability regions of fractional-order neural networks with mixed delays, uncertainties, and external disturbances (FONNMDUED). Then, to address the quasi-synchronization problem, a controller is designed and some novel sufficient conditions for achieving quasi-synchronization are established. The results show that tuning the control parameters can adjust the error bound. These findings not only enrich the theoretical foundation of fractional-order neural networks but also offer practical insights for applications in complex systems. Full article

The development of large-scale cascade hydropower complexes has improved the navigation conditions of mountainous rivers but creates unique “continuous dam zones,” presenting complex challenges for port site selection due to hydrological variability and geological risks. To address the lack of specialized evaluation tools for this specific context, this paper constructs a comprehensive evaluation indicator system tailored for mountainous reservoir areas. The proposed system explicitly integrates critical engineering and physical constraints—specifically fluctuating backwater zones, geological hazards, and dam-bypass mileage—alongside ecological and social requirements. The Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) are integrated using a Game Theory model to determine combined weights, and the Evaluation based on Distance from Average Solution (EDAS) model is applied to rank the alternatives. An empirical analysis of the Xiluodu Reservoir area on the Jinsha River demonstrates that operational efficiency, geological safety, and environmental feasibility constitute the critical decision-making factors. The results indicate that Option C (Majiaheba site) offers the optimal solution (ASi = 0.9695), effectively balancing engineering utility with environmental protection. Sensitivity analysis further validates the consistency and stability of this ranking under different decision-making scenarios. The findings provide quantitative decision support for project implementation and offer a replicable reference for infrastructure planning in similar complex mountainous river basins. Full article

Adlay (Coix lacryma-jobi L.) stands out as a vital health-promoting cereal due to its dual nutritional and medicinal properties; however, it remains significantly underdeveloped compared to major crops. The lack of mechanistic understanding of its caryopsis development and trait formation severely constrains targeted genetic improvement. While transformative technologies, specifically micro-computed tomography (micro-CT) imaging combined with AI-assisted analysis (e.g., Segment Anything Model (SAM)) and multi-omics approaches, have been successfully applied to unravel the structural and physiological complexities of model cereals, their systematic adoption in adlay research remains fragmented. Going beyond a traditional synthesis of these methodologies, this article proposes a novel, multidimensional framework specifically designed for adlay. This forward-looking strategy integrates high-resolution 3D phenotyping with spatial multi-omics data to bridge the gap between macroscopic caryopsis architecture and microscopic metabolic accumulation. By offering a precise digital solution to elucidate adlay’s unique developmental mechanisms, the proposed framework aims to accelerate precision breeding and advance the scientific modernization of this promising underutilized crop. Full article

The shift towards the integration of and transition to renewable energy has led to an increase in renewable energy communities (RECs) and smart grids (SGs). The significance of these RECs is mainly energy self-sufficiency, energy independence, and energy autonomy. Despite this, in low- and middle-income countries and regions like Pakistan and the Middle East, SGs and RECs are still in their initial stage. However, they have potential for green energy solutions rooted in their unique geographic and climatic conditions. SGs offer energy monitoring, communication infrastructure, and automation features to help these communities build flexible and efficient energy systems. This work provides an overview of Pakistani and Middle Eastern energy policies, goals, and initiatives while aligning with European comparisons. This work also highlights technical, regulatory, and economic challenges in those regions. The main objectives of the research are to ensure that residential service sizes are optimized to maximize the economic and environmental benefits of green energy. Furthermore, in line with SDG 7, affordable and clean energy, the focus in this study is on the development and transformation of energy systems for sustainability and creating synergies with other SDGs. The paper presents insights on the European Directive, including the amended Renewable Energy Directive (RED II and III), to recommend policy enhancements and regulatory changes that could strengthen the growth of RECs in Asian countries, Pakistan, and the Middle East, paving the way for a more inclusive and sustainable energy future. Additionally, it addresses the main causes that hinder the expansion of RECs and SGs, and offers strategic recommendations to support their development in order to reduce dependency on national electric grids. To perform this, a perspective study of Pakistan’s indicative generation capacity by 2031, along with comparisons of energy capacity in the EU, the Middle East, and Asia, is presented. Pakistan’s solar, wind, and hydro potential is also explored in detail. This study is a baseline and informative resource for policy makers, researchers, industry stakeholders, and energy communities’ promoters, who are committed to the task of promoting sustainable renewable energy solutions. Full article

We consider the Poisson stable solutions and their exponential attractiveness for the linear difference equation $z(n+1)=Az\left(n\right)+g\left(n\right)$ and semi-linear difference equation $z(n+1)=Az\left(n\right)+G(n,z(n\left)\right).$ Via Shcherbakov’s comparability principle, we show that if the forcing g (respectively, G) has some Poisson stable property, there is precisely one bounded solution that shares the same recurrence character as $g(\mathrm{respectively}, G)$ under appropriate assumptions. Moreover, the unique Poisson stable solution exponentially attracts every other solution. Full article

Fast large-scale network scanning is an important way to understand internet service configurations and security in real time, among which stateless scan technology is representative. Existing stateless scanners can perform single-packet scans for internet-wide network measurements but are limited to host discovery or port scanning. To obtain further information over TCP, slower stateful scanners must be used in conjunction, which spend more time and memory because of connection state maintenance. Through the simplification of the TCP finite state machine (FSM), this paper proposes a novel stateless scanning model, which can establish TCP connections and obtain further responses in a completely stateless manner. Based on this model, we implement ZBanner, an improved modular stateless scanner that utilizes user-defined probes for identifying services and versions, fingerprinting TLS servers, etc. We present the unique design of ZBanner and experimentally characterize its feasibility and performance. Experiments show that ZBanner performs better than current state-of-the-art solutions in terms of scan rate and memory usage. ZBanner achieves a scan rate that is at least three times faster than current tools for generic ports and over 90 times faster for open ports while keeping a minimum and stable memory usage. Full article

This study explores how school principals evacuated from their schools in the wake of the 7 October 2023 war perceived their unique challenges, the strategies they adopted, and the ways in which their agency was shaped during the extreme crisis. Using semi-structured, in-depth interviews with 33 displaced principals from elementary, middle, secondary, and special education schools, we identified four interconnected dimensions of the principals’ agency during wartime. Intrapersonal agency reflected the principal’s inner identity as a foundation for action. Critical agency emerged from frustration with systemic failures and bureaucratic obstacles, motivating the pursuit of meaningful change. Collaborative agency was expressed in building and maintaining trust-based networks and partnerships that enabled effective solutions. Finally, proactive agency was driven by an internal desire for growth and influence, promoting innovative strategies and renewal processes at organizational, emotional, and community levels. This leadership framework for understanding principalship in wartime highlights agency as a holistic framework that enables principals not only to ensure the survival of their schools, but also to respond to chaotic realities. Practically, the findings inform the design of models for ensuring educational continuity in emergencies, and tailored support mechanisms for displaced educational communities. Full article