Search Results (13,583)

Ion beam figuring (IBF) is an ultra-high-precision surface finishing technology characterized by a distinct trade-off between the spot size of the removal function and its corresponding figuring capabilities. A larger spot size for the removal function leads to higher processing efficiency but lower figuring ability. Conversely, a smaller spot size results in higher figuring ability but lower efficiency. Adjusting the spot size of the removal function using tools with an aperture is a possible approach. However, existing variable-aperture tools have certain limitations in IBF processing. To leverage the advantages of both large and small spot sizes for the removal function during IBF processing, an in situ dynamic beam variable-aperture device has been designed. This device optimizes the parameters of diaphragm sheets and employs FOC for dynamic aperture adjustment. Simulations show that 12 numbers of 0.1 mm-thick sheets minimize removal function distortion, with the thermal strain-induced area variation being <5%. FOC enables rapid (≤0.45 s full range) and precise aperture control. Experiments confirm adjustable spot sizes (FWHM 0.7–17.2 mm) with Gaussian distribution (correlation >96.7%), operational parameter stability (relative change rate ≤5%), and high repeatable positioning precision (relative change rate ≤3.2% in repeated adjustments). The design enhances IBF efficiency, flexibility, and accuracy by enabling in situ spot size optimization, overcoming conventional limitations. Full article

Acoustic tweezers, as advanced micro/nano manipulation tools, play a pivotal role in biomedical engineering, microfluidics, and precision manufacturing. However, piezoelectric-based acoustic tweezers face performance limitations due to multi-physical coupling effects during microfabrication. This study proposes a novel approach using injection molding with embedded electronics (IMEs) technology to fabricate piezoelectric micro-ultrasonic transducers with micron-scale precision, addressing the critical issue of acoustic node displacement caused by thermal–mechanical coupling in injection molding—a problem that impairs wave transmission efficiency and operational stability. To optimize the IME process parameters, a hybrid multi-objective optimization framework integrating NSGA-II and MOPSO is developed, aiming to simultaneously minimize acoustic node displacement, volumetric shrinkage, and residual stress distribution. Key process variables—packing pressure (80–120 MPa), melt temperature (230–280 °C), and packing time (15–30 s)—are analyzed via finite element modeling (FEM) and validated through in situ tie bar elongation measurements. The results show a 27.3% reduction in node displacement amplitude and a 19.6% improvement in wave transmission uniformity compared to conventional methods. This methodology enhances acoustic tweezers’ operational stability and provides a generalizable framework for multi-physics optimization in MEMS manufacturing, laying a foundation for next-generation applications in single-cell manipulation, lab-on-a-chip systems, and nanomaterial assembly. Full article

This study examines the complex process of Islam’s localization in Sudan, focusing on how hospitality, Sufi dhikr, and Mawlid celebrations integrate with Islamic practices. Drawing on three years of qualitative fieldwork, it demonstrates how Sudan’s geography, ethnic diversity, and historical heritage enable the blending of core religious principles with local customs. Sufi brotherhoods—particularly Qādiriyya, Tījāniyya, Shādhiliyya, and Khatmiyya—play a pivotal role in local culture by incorporating traditional musical, choreographic, and narrative art forms into their rituals, resulting in highly dynamic worship and social interaction. In Sudan, hospitality emerges as a near-sovereign social norm, reflecting the Islamic ethics of charity and mutual assistance while remaining deeply intertwined with local traditions. Islam’s adaptability toward local customs is further illustrated by the vibrant drumming, chanting, and dancing that enhance large-scale Mawlid al-Nabi celebrations, uniting Muslims under a religious identity that goes beyond dogmatic definitions. Beyond their spiritual meanings, these Sufi practices and networks also serve as tools for social cohesion, often functioning as support systems in regions with minimal state presence. They help prevent disputes and foster unity, demonstrating the positive impact of a flexible Islam—one that draws on both scripture and local traditions—on peacebuilding in Sudan. While highlighting the country’s social realities, this study offers insights into how Islam can function as a transformative force within society. Full article

Mycelium-bonded composites (MBCs), or myco-composites, represent a novel engineered material that combines natural lignocellulosic substrates with a fungal matrix. As a sustainable alternative to plastics, MBCs are gaining increasing interest; however, their large-scale industrial adoption remains limited, partly due to low social acceptance resulting from their unattractive appearance. Laser engraving provides a promising method for fabricating intricate patterns and functional surfaces on MBCs, minimizing tool wear, material loss, and environmental impact, while enhancing esthetic and engineering properties. This study investigates the influence of CO₂ laser parameters on the material removal rate during the engraving of myco-composites, focusing on the effects of variable laser power, beam defocus, and head feed rate on engraving outcomes. The results demonstrate that laser power and beam focus significantly impact material removal in mycelium-bonded composites. Specifically, increasing the laser power results in greater material removal, which is more pronounced when the beam is focused due to higher energy density. In contrast, a beam defocused by 1 mm produces less intense material removal. These findings highlight the critical role of beam focus—surpassing the influence of power alone—in determining engraving quality, particularly on irregular or uneven surfaces. Moreover, reducing the laser head feed rate at a constant power level increases the material removal rate linearly; however, it also results in excessive charring and localized overheating, revealing the low thermal tolerance of myco-composites. These insights are essential for optimizing laser processing techniques to fully realize the potential of mycelium-bonded composites as sustainable engineering materials, simultaneously maintaining their appearance and functional properties. Full article

Rockfalls, among the most common natural disasters, pose risks such as traffic congestion, casualties, and substantial property damage. Guizhou Province, with China’s fourth-longest highway network, features mountainous terrain prone to frequent rockfall incidents annually. Consequently, assessing highway rockfall risks in Guizhou Province is crucial for safeguarding the lives and travel of residents. This study evaluates highway rockfall risk through three key components: susceptibility, hazard, and vulnerability. Susceptibility was assessed using information content and logistic regression methods, considering factors such as elevation, slope, normalized difference vegetation index (NDVI), aspect, distance from fault, relief amplitude, lithology, and rock weathering index (RWI). Hazard assessment utilized a fuzzy analytic hierarchy process (AHP), focusing on average annual rainfall and daily maximum rainfall. Socioeconomic factors, including GDP, population density, and land use type, were incorporated to gauge vulnerability. Integration of these assessments via a risk matrix yielded comprehensive highway rockfall risk profiles. Results indicate a predominantly high risk across Guizhou Province, with high-risk zones covering 41.19% of the area. Spatially, the western regions exhibit higher risk levels compared to eastern areas. Notably, the Bijie region features over 70% of its highway mileage categorized as high risk or above. Logistic regression identified distance from fault lines as the most negatively correlated factor affecting highway rockfall susceptibility, whereas elevation gradient demonstrated a minimal influence. This research provides valuable insights for decision-makers in formulating highway rockfall prevention and control strategies. Full article

The current research trends of production engineering are based on optimizing the machining process concerning human and environmental factors. High-performance materials, such as hardened steels, nickel-based alloys, fiber-reinforced polymer (FRP) composites, and titanium alloys, are classified as hard-to-cut due to their ability to maintain strength at high operating temperatures. Due to these characteristics, such materials are employed in applications such as aerospace, marine, energy generation, and structural. The purpose of this article is to investigate the machinability of these alloys under various cutting conditions. The purpose of this article is to compare cryogenic cooling and cryogenic processing from the perspective of machinability and sustainability in the manufacturing process. Compared to conventional machining, hybrid techniques, which mix cryogenic and minimal quantity lubricant, led to significantly reduced cutting forces of 40–50%, cutting temperatures and surface finishes by approximately 20–30% and more than 40%, respectively. A carbon footprint is determined by several factors including power consumption, energy requirements, and carbon dioxide emissions. As a result of the cryogenic technology, the energy consumption, power consumption, and CO₂ emissions were reduced by 40%, 28%, and 35%. Full article

Electrostatic separation is a promising technology for the recovery of valuable metals from electronic waste, particularly from printed circuit boards (PCBs). This study explores the application of electrostatic separation for the selective recovery of metallic and non-metallic fractions from crushed PCBs (PCBs). The process exploits the differences in electrical properties between conductive metals and non-conductive polymers and ceramics, facilitating their separation through applied electric fields. The raw materials were pre-treated via mechanical comminution using shredders and hammer mills to achieve an optimal particle size distribution (<3 mm), which enhances separation efficiency. Ferrous materials were removed prior to electrostatic separation to improve process selectivity. Key operational parameters, including particle size, charge accumulation, environmental conditions, and separation efficiency, were systematically analysed. The results demonstrate that electrostatic separation effectively recovers high-value metals such as copper and gold while minimizing material losses. Additionally, the process contributes to the sustainability of e-waste recycling by enabling the recovery of non-metallic fractions for potential secondary applications. This work underscores the significance of electrostatic separation as a viable technique for e-waste management and highlights optimization strategies for enhancing its performance in large-scale recycling operations. Full article

This research integrates stochastic optimization techniques with robust modeling and probabilistic modeling approaches to enhance photovoltaic cell manufacturing processes and product reliability. The study employed an adapted genetic algorithm to tackle uncertainties in the manufacturing process, resulting in improved operational efficiency. It consistently achieved optimal fitness, with values remaining at 1.0 over 100 generations. The model displayed a dynamic convergence rate, demonstrating its ability to adjust performance in response to process fluctuations. The system preserved resource efficiency by utilizing approximately 2600 units per generation, while minimizing machine downtime to 0.03%. Product reliability reached an average level of 0.98, with a maximum value of 1.02, indicating enhanced consistency. The manufacturing process achieved better optimization through a significant reduction in defect rates, which fell to 0.04. The objective function value fluctuated between 0.86 and 0.96, illustrating how the model effectively managed conflicting variables. Sensitivity analysis revealed that changes in sigma material and lambda failure had a minimal effect on average reliability, which stayed above 0.99, while average defect rates remained below 0.05. This research exemplifies how stochastic, robust, and probabilistic optimization methods can collaborate to enhance manufacturing system quality assurance and product reliability under uncertain conditions. Full article

The modern road industry requires a more effective solution according to efficiency and minimizing environmental burden. This article discusses the use of recycled materials to modify bitumen binders within the concept of the circular economy. The main aim of this article was to create a new composite based on waste materials, including polymer waste and rubber crumb. The important element is the usage of locally available waste that has not been investigated previously as a material for asphalt modification. The prepared composition was preliminarily assessed according to chemical composition. Next, research dedicated to road application was conducted, including the following: determination of the resistance to hardening, aging under the influence of high temperature and air, as well as oxidation processes, assessment of penetration, and evaluation of the softening point. The conducted studies showed that the new composites with the addition of polymer waste and rubber crumb improve the thermal stability, elasticity, and resistance of bitumen to aging. Optimum concentrations of modifiers were determined that provide an increase in the performance characteristics of bitumen, including a decrease in the brittleness temperature and an increase in the softening temperature. The obtained results demonstrate the potential for the introduction of new composites based on recycled materials in road construction, contributing to increased environmental sustainability and economic efficiency. Full article

In this paper, the problem of pitching attitude finite-horizon optimization for aircraft is posed with system uncertainties, external disturbances, and input constraints. First, a neural network (NN) and a nonlinear disturbance observer (NDO) are employed to estimate the value of system uncertainties and external disturbances. Taking input constraints into account, an auxiliary system is designed to compensate for the constrained input. Subsequently, the backstepping control containing NN and NDO is used to ensure the stability of systems and suppress the adverse effects caused by the system uncertainties and external disturbances. In order to avoid the derivation operation in the process of backstepping, a dynamic surface control (DSC) technique is utilized. Simultaneously, the estimations of the NN and NDO are applied to derive the backstepping control law. For the purpose of achieving finite-horizon optimization for pitching attitude control, an adaptive method termed adaptive dynamic programming (ADP) with a single NN-termed critic is applied to obtain the optimal control. Time-varying feature functions are applied to construct the critic NN in order to approximate the value function in the Hamilton–Jacobi–Bellman (HJB) equation. Furthermore, a supplementary term is added to the weight update law to minimize the terminal constraint. Lyapunov stability theory is used to prove that the signals in the control system are uniformly ultimately bounded (UUB). Finally, simulation results illustrate the effectiveness of the proposed finite-horizon optimal attitude control method. Full article

The internal combustion process in a boiler in power plants has a direct impact on boiler efficiency and NOx generation. The objective of this study is to propose an intelligent deep learning modeling and multi-objective optimization approach that considers NOx emission concentration and boiler thermal efficiency simultaneously for boiler combustion in power plants. Firstly, a hybrid deep learning model, namely, convolutional neural network–bidirectional gated recurrent unit (CNN-BiGRU), is employed to predict the concentration of NOx emissions and the boiler thermal efficiency. Then, based on the hybrid deep prediction model, variables such as primary and secondary airflow rates are considered as controllable variables. A single-objective optimization model based on an improved flow direction algorithm (IFDA) and a multi-objective optimization model based on NSGA-II are developed. For multi-objective optimization using NSGA-II, the average NOx emission concentration is reduced by 5.01%, and the average thermal efficiency is increased by 0.32%. The objective functions are to minimize the boiler thermal efficiency and the concentration of NOx emissions. Comparative analysis of the experiments shows that the NSGA-II algorithm can provide a Pareto optimal front based on the requirements, resulting in better results than single-objective optimization. The effectiveness of the NSGA-II algorithm is demonstrated, and the obtained results provide reference values for the low-carbon and environmentally friendly operation of coal-fired boilers in power plants. Full article

The evaluation of open-ended questions is typically performed by human instructors using predefined criteria to uphold academic standards. However, manual grading presents challenges, including high costs, rater fatigue, and potential bias, prompting interest in automated essay scoring systems. While automated essay scoring tools can assess content, coherence, and grammar, discrepancies between human and automated scoring have raised concerns about their reliability as standalone evaluators. Large language models like ChatGPT offer new possibilities, but their consistency and fairness in feedback remain underexplored. This study investigates whether ChatGPT can provide stable and fair essay scoring—specifically, whether identical student responses receive consistent evaluations across multiple AI interactions using the same criteria. The study was conducted in two marketing courses at an engineering school in Chile, involving 40 students. Results showed that ChatGPT, when unprompted or using minimal guidance, produced volatile grades and shifting criteria. Incorporating the instructor’s rubric reduced this variability but did not eliminate it. Only after providing an example-rich rubric, a standardized output format, low temperature settings, and a normalization process based on decision tables did ChatGPT-4o demonstrate consistent and fair grading. Based on these findings, we developed a scalable algorithm that automatically generates effective grading rubrics and decision tables with minimal human input. The added value of this work lies in the development of a scalable algorithm capable of automatically generating normalized rubrics and decision tables for new questions, thereby extending the accessibility and reliability of automated assessment. Full article

Background: Tobacco use is disproportionately high in rural areas, contributing to elevated cancer mortality, yet it often goes untreated due to limited access to care, high poverty and uninsured rates, and co-occurring substance use disorders (SUDs). This study explored the utility of using rapid qualitative analysis (RQA) to guide the adaptation of a tobacco-free workplace program (TFWP) in Texas healthcare centers serving adults with SUDs in medically underserved areas. Methods: From September–December 2023 and May–July 2024, we conducted 11 pre-implementation, virtual semi-structured group interviews focused on adapting the TFWP to local contexts (N = 69); 7 with providers (n = 34) and managers (n = 12) and 4 with patients (n = 23) in 6 healthcare centers. Two qualified analysts independently summarized transcripts, using RQA templates of key domains drawn from interview guides to summarize and organize data in matrices, enabling systematic comparison. Results: The main themes identified were minimal organizational tobacco cessation support and practices, and attitudinal barriers, as follows: (1) the need for program materials tailored to local populations; (2) limited tobacco cessation practices and partial policies—staff requested guidance on enhancing tobacco screenings and cessation delivery, and integrating new interventions; (3) contradictory views on treating tobacco use that can inhibit implementation (e.g., wanting to quit yet anxious that quitting would cause SUD relapse); and (4) inadequate environmental supports—staff requested treating tobacco-use training, patients group cessation counseling; both requested nicotine replacement therapy. Conclusions: RQA identified key areas requiring capacity development through participants’ willingness to adopt the following adaptations: program content (e.g., trainings and tailored educational materials), delivery methods/systems (e.g., adopting additional tobacco care interventions) and implementation strategies (e.g., integrating tobacco cessation practices into routine care) critical to optimizing TFWP fit and implementation. The study findings can inform timely formative evaluation processes to design and tailor similar intervention efforts by addressing site-specific needs and implementation barriers to enhance program uptake. Full article

The increasing demand for high-speed, energy-efficient computing has propelled the development of integrated photonic logic gates, which utilize the speed of light to surpass the limitations of traditional electronic circuits. These gates enable ultrafast, parallel data processing with minimal power consumption, making them ideal for next-generation computing, telecommunications, and quantum applications. Recent advancements in nanofabrication, nonlinear optics, and phase-change materials have facilitated the seamless integration of all-optical logic gates onto compact photonic chips, significantly enhancing performance and scalability. This paper explores the latest breakthroughs in photonic logic gate design, key material innovations, and their transformative applications. While challenges such as fabrication precision and electronic–photonic integration remain, integrated photonic logic gates hold immense promise for revolutionizing optical computing, artificial intelligence, and secure communication. Full article

Oyster shells, though rich in calcium, are mostly discarded and contribute to environmental issues. Developing calcium-based materials with antimicrobial functionality offers a promising solution. However, their low bioavailability limits their direct use, requiring processing to enhance their applicability. Therefore, this study aims to evaluate the physicochemical properties and antimicrobial activity of thermally processed pulverized oyster shells (TPOS) and citric acid-treated TPOS (TPOSc) compared with those of fibrous calcium carbonate (FCC) and coral-derived calcium product (CCP), which are used as reference materials. The solubility values were 0.7 mg/g for FCC, 0.5 mg/g for TPOS, 0.4 mg/g for TPOSc, and 0.05 mg/g for CCP. The average particle sizes were 476 (FCC), 1000 (TPOS and TPOSc), and 1981 nm (CCP). Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) analyses revealed calcium ion release and structural changes in TPOS and TPOSc. Antibacterial testing further confirmed that these samples exhibited significant antimicrobial activity. Furthermore, to assess their practical applicability, TPOS and TPOSc samples with antimicrobial properties were incorporated into rice cakes. All samples retained antimicrobial activity at 0.3 wt%, while higher concentrations led to deterioration in their textural properties. These findings support the potential of thermally processed oyster shell powders for food applications that require microbial control with minimal impact on product quality. Full article