Search Results (1,850)

As semiconductor process nodes shrink to 3 nm and beyond, traditional optical proximity correction (OPC) and resolution enhancement technologies (RETs) can no longer meet the high patterning precision needs of advanced chip manufacturing due to the sub-wavelength lithography limits. Inverse lithography technology (ILT), a key part of computational lithography, has become a critical solution for these issues. From an EDA industry perspective, this review provides an original and systematic summary of ILT’s development and applications, which helps integrate the scattered research into a clear framework for both academic and industrial use. Compared with traditional OPC, the latest ILT has three main advantages: (1) better patterning accuracy, as a result of the precise optical models that fix complex optical issues (like diffraction and interference) in advanced lithography systems; (2) a wider process window, as it optimizes mask designs by working backwards from the target wafer patterns, making lithography more stable against process changes; and (3) stronger adaptability to new lithography scenarios, such as High-NA EUV and extended DUV nodes. This review first explains ILT’s working principles (the basic concepts, mathematical formulae, and main methods like level-set and pixelated approaches) and its development history, highlighting key events that boosted its progress. It then analyzes ILT’s current application status in the industry (such as hotspot fixing, full-chip trials, and EUV-era use) and its main bottlenecks: a high computational complexity leading to long runtime, difficulties in mask manufacturing, challenges in model calibration, and a conservative market that slows large-scale adoption. Finally, it discusses promising future directions, including hybrid ILT-OPC-SMO strategies, improving model accuracy, AI/ML-driven design, GPU acceleration, multi-beam mask writer improvements, and open-source data to solve data shortage problems. By combining the latest research and industry practices, this review fills the gap of comprehensive ILT summaries that cover the principles, progress, applications, and prospects. It helps readers fully understand ILT’s technical landscape and offers practical insights for solving the key challenges, thus promoting ILT’s industrial use in advanced chip manufacturing. Full article

A well construction plan includes a drilling program, drilling fluids, casing-setting-depth selection, casing-grade-combination design, bit selection, cementing, and a wellhead design. Casing-setting-depth selection techniques are an integral part of the construction of oil and gas wells, where setting-depth selection methods rely on both safety and economics. In this study, a new casing-setting-depth selection method is developed. This new method is based on the estimation of the fracturing pressure using the Mohr–Coulomb failure criterion. To validate this new casing-setting-depth selection method, ten core samples, representing ten underground formations in the Saudi lithological column, were tested for uniaxial compressive and tensile strengths. The results were utilized to establish rock failure criteria and estimate casing setting depth using a newly proposed casing-setting-depth selection method based on the Mohr–Coulomb failure criterion and compared to other traditional casing-setting-depth estimation methods. The results demonstrated that the Hubbert & Willis method provided a very narrow safe mud window compared to the other methods, while the leak-off, Eaton, Mathews & Kelly, and other methods provided more economical results. On the other hand, the Mohr–Coulomb method provided the widest and most economical safe mud window compared to all other traditional methods. One of the main requirements of the Mohr–Coulomb casing-setting-depth selection method is that it either requires appreciable core samples from various depths to be tested in the laboratory for their mechanical properties and failure criteria, or that core-calibrated well logs be used. Additionally, relying on Mohr–Coulomb casing-setting-depth selection methods requires the use of filtration loss control materials to seal any microcracks that may form. Economical comparisons in terms of casing string number and length yielded that Eaton, leak-off, and Mathews and Kelly methods reduced casing cost by 31% compared to Hubbert and Willis methods. On the other hand, the new casing-setting-depth selection method based on the Mohr–Coulomb method reduced casing costs by 41% compared with the Hubbert and Willis methods and by 10% compared with the leak-off and Mathews and Kelly methods. Therefore, this study provides a new proof of concept for developing an efficient method for selecting the casing setting depth for oil and gas wells. Full article

Quality of life (QoL) is a multidimensional concept involving physical, psychological, social, and environmental dimensions. Therefore, it reflects not only individual well-being but also the overall well-being and sustainability of societies. Current approaches to QoL have expanded from purely economic or health-based indicators to incorporate a range of multidimensional analyses at urban, regional, and national levels, with more recent emphasis on interlinkages between socio-economic and spatial factors. This research investigates how geoinformation methodologies, including remote sensing, spatial analysis, and machine learning, can be applied to assess QoL across multiple spatial scales. Through a systematic review and comparative evaluation, the study aims to identify which indicators, data sources, and analytical tools are used at each spatial level—from neighborhood and urban scale to regional and national levels. Emphasis was placed on understanding how methodological approaches vary across scales and how spatial resolution, data availability, and urban context influence the design and implementation of QoL assessment frameworks. The main objective was to establish a common analytical framework for evaluating QoL across different spatial scales. The review revealed that combining data, machine learning algorithms, and spatial analysis approaches in a common framework will enhance comparative and predictive capabilities beyond the state of the art, although it will face significant data heterogeneity challenges. Future research aims to develop consistent, multidimensional models supportive of policies fostering sustainability and spatial equity in urban and regional contexts. Full article

Background/Objectives: Mathematical modelling provides a quantitative way to describe the fate and action of drugs in the oral cavity, where transport processes are shaped by salivary flow, pellicle formation, biofilm structure and the wash-out effect of gingival crevicular fluid (GCF). Local pharmacokinetics in the mouth differ substantially from systemic models, and therefore a dedicated framework is required. The aim of this work was to present a structured, physiologically based concept that links in vitro release testing with local pharmacokinetics and pharmacodynamics. Methods: A narrative review with elements of systematic search was conducted in PubMed, Scopus and Web of Science (1980–2025) for publications describing drug release, local PBPK, and PK/PD modelling in the oral cavity. Mathematical formulations were grouped into release kinetics, mini-PBPK transport and local PK/PD relations. Classical models (Higuchi, Korsmeyer–Peppas, Peppas–Sahlin) were integrated with a mini-PBPK structure describing saliva–mucosa–biofilm–pocket interactions. Results: The combined model captures adsorption to pellicle, diffusion within biofilm and wash-out by GCF. It allows simulation of variable clinical conditions, such as inflammation-related changes in Q_GCF, and links local exposure to pharmacodynamic outcomes. Case studies with PerioChip^®, Arestin^®, and Atridox^® demonstrate how mechanistic models explain observed therapeutic duration and low-systemic exposure. Conclusions: The proposed mini-PBPK framework bridges empirical release data and physiological transport in the oral cavity. It supports rational formulation design, optimisation of local dosage, and personalised prediction of drug retention in gingival pockets. This modelling approach can become a practical tool for the development of dental biomaterials and subgingival therapies. Full article

This paper provides a comprehensive overview of mobile network softwarization, emphasizing the technological foundations and its transformative impact on the energy efficiency of modern and future mobile networks. In the paper, a detailed analysis of communication concepts known as software-defined networking (SDN) and network function virtualization (NFV) is presented, with a description of their architectural principles, operational mechanisms, and the associated interfaces and management frameworks that enable programmability, virtualization, and centralized control in modern mobile networks. The study further explores the role of cloud computing, virtualization platforms, distributed SDN controllers, and resource orchestration systems, outlining how they collectively support mobile network scalability, automation, and service agility. To assess the maturity and evolution of mobile network softwarization, the paper reviews contemporary research directions, including SDN security, machine-learning-assisted traffic management, dynamic service function chaining, virtual network function (VNF) placement and migration, blockchain-based trust mechanisms, and artificial intelligence (AI)-enabled self-optimization. The analysis also evaluates the relationship between mobile network softwarization and energy consumption, presenting the main SDN- and NFV-based techniques that contribute to reducing mobile network power usage, such as traffic-aware control, rule placement optimization, end-host-aware strategies, VNF consolidation, and dynamic resource scaling. Findings indicate that although fifth-generation (5G) mobile network standalone deployments capable of fully exploiting softwarization remain limited, softwarized SDN/NFV-based architectures provide measurable benefits in reducing network operational costs and improving energy efficiency, especially when combined with AI-driven automation. The paper concludes that mobile network softwarization represents an essential enabler for sustainable 5G and future beyond-5G systems, while highlighting the need for continued research into scalable automation, interoperable architectures, and energy-efficient softwarized network designs. Full article

Fall-compliant flooring represents a passive fall preventative approach that has emerged as an effective intervention for reducing fall-related injuries, yet its adoption remains limited due to insufficient understanding among end-users and key stakeholders. To address this knowledge gap, this perspective article provides a proof-of-concept for an interactive pedagogical tool designed to use gamification principles to improve understanding of the mechanical behavior of fall-compliant flooring. This two-part perspective article first establishes the scientific foundation through controlled ball drop experiments comparing energy dissipation between fall-compliant and standard flooring. Through video-based tracking analysis, the experiments quantified kinetic energy and force dissipation across spatial and temporal dimensions. Results revealed that fall-compliant flooring exhibits significantly superior spatiotemporal energy dissipation capabilities compared to standard flooring across both force and kinetic energy metrics. Building on these findings, the second part proposes a conceptual framework for a pedagogical tool that translates these experimental insights into an interactive learning experience that could, in future implementations, allow users to conduct hands-on ball drop activities supported by real-time scientific explanations. This approach transforms complex biomechanical concepts into accessible, engaging learning experiences. By combining experiential learning with gamified elements, this tool, termed “Fallville”, has the potential to increase fall-injury prevention awareness, deepen understanding of fall-compliant flooring mechanisms, and ultimately accelerate adoption of this proven safety intervention in healthcare and residential settings. Full article

In third-generation centralized heating systems, qualitative regulation of the heat transfer medium parameters is mainly performed at heat sources, while quantitative regulation is implemented at central and individual heating points, with buildings remaining passive heat consumers. Unlike fourth-generation systems, such systems generally do not employ renewable energy sources, thermal energy storage, or low-temperature operating regimes. Third-generation centralized heating systems operate based on design high-temperature schedules and centralized control, without considering the actual thermal loads of consumers. Under conditions of physical deterioration of heating networks, hydraulic imbalance, and operational constraints, the actual parameters of the heat transfer medium supplied to buildings often deviate from design values, resulting in deviations of thermal conditions at the level of end consumers and disruptions of thermal comfort. This study proposes the concept of an intelligent active individual heating point (IAIHP), designed to provide adaptive qualitative–quantitative regulation of heat transfer medium parameters at the level of individual buildings. Unlike approaches focused on demand-side management, the use of thermal energy storage, or the integration of renewable energy sources, the proposed solution is based on the application of a local thermal energy source. The IAIHP compensates for deviations in heat transfer medium parameters and acts as a local thermal energy source within the building heat supply system (BHSS). Control of the IAIHP operation is performed by a developed automation system that provides combined qualitative and quantitative regulation of the heat transfer medium supplied to the BHSS. The study assesses the potential scale of IAIHP implementation in third-generation centralized heating systems, develops a methodology for selecting the capacity of a local heat source, and presents the operating algorithm of the automatic control system of the IAIHP. At present, the reconstruction of an individual heating point of a kindergarten connected via a dependent scheme is being carried out based on the developed project documentation. Modeling and calculations show that the application of the IAIHP makes it possible to ensure indoor thermal comfort by reducing the risk of temperature deviations, which are otherwise typically compensated for by electric heaters. The proposed concept provides a methodological basis for a gradual transition from third-generation to fourth-generation centralized heating systems, while equipping the IAIHP with an intelligent control system opens opportunities for improving the energy efficiency of urban heating networks. The proposed integrated solution and the developed automatic control algorithms exhibit scientific novelty and practical relevance for Russia and other countries operating third-generation centralized heating systems, including Northern and Eastern European states, where large-scale infrastructure modernization and the implementation of fourth-generation technologies are technically or economically constrained. Full article

Existing studies have demonstrated that insufficient horizontal deformation capacity of columns under high axial compression ratios constitutes a key factor leading to seismic damage in ordinary concrete frame structures. This paper proposes a novel framed structure incorporating composite columns by combining ultra-high performance concrete (UHPC), which exhibits excellent mechanical properties, with normal concrete (NC). The design concept maintains the overall mechanical performance of the composite column frame structure while significantly reducing the lateral stiffness when the composite columns are configured in a “split-column form.” For instance, the lateral stiffness of ZH-5 in the “split-column form” is only one-tenth of that of ZT-1 in its initial state, leading to a substantial enhancement in horizontal deformation capacity. This design approach maintains the overall mechanical performance of the composite column frame structure while significantly enhancing its horizontal deformation capacity by reducing lateral stiffness through the “split-column” configuration. Using the ABAQUS finite element software 2021, a finite element model of a multi-story frame column structure was developed. Research findings indicate that the frame structure utilizing UHPC-NC composite columns exhibits reduced tensile damage, lower peak and plastic displacements, and a relatively smaller inter-story drift angle. Specifically, the plastic drift angle of the UHPC-NC composite column frame structure from the first to the fourth story is 5% to 31% smaller than that of the conventional reinforced concrete column frame structure. The novel UHPC-NC composite column frame structure demonstrates superior seismic performance. Full article

While drug-eluting cardiovascular devices, including drug-eluting stents and drug-coated balloons, have significantly reduced restenosis rates, they remain limited by delayed vascular healing, chronic inflammation, and late adverse events. These limitations reflect a fundamental mismatch between current device pharmacology, which relies on nonselective antiproliferative drugs, and the highly coordinated, cell-specific programs that orchestrate vascular repair. Extracellular vesicles (EVs), nanometer-scale membrane-bound particles secreted by virtually all cell types, provide a biologically evolved platform for intercellular communication and cargo delivery. In the cardiovascular system, EVs regulate endothelial regeneration, smooth muscle cell phenotype, extracellular matrix remodeling, and macrophage polarization through precisely orchestrated combinations of miRNA, proteins, and lipids. Here, we synthesize mechanistic insights into EV biogenesis, cargo selection, recruitment, and functional effects in vascular healing and inflammation and translate these into a formal framework for EV-inspired device engineering. We discuss how EV-based or EV-mimetic coatings can be designed to sense the local microenvironment, deliver encoded biological “instruction sets,” and function within ECM-mimetic scaffolds to couple local stent healing with systemic tissue repair. Finally, we outline the manufacturing, regulatory, and clinical trial issues that must be addressed for EV-inspired cardiovascular devices to transition from proof of concept to clinical reality. By shifting the focus from pharmacological suppression to biological regulation of healing, EV-based strategies offer a path to resolve the long-standing tradeoff between restenosis prevention and durable vascular healing. Full article

Background: Dementia poses a significant health concern among Australia’s First Nations peoples, who experience higher prevalence and earlier onset compared to non-First Nations populations. Despite growing research attention, the overall scope and characteristics of existing literature on dementia in these communities remain unclear. Objective: This scoping review aimed to map and synthesise existing evidence on the burden of dementia among First Nations peoples, focusing on associated risk factors and culturally responsive approaches to prevention, intervention, and care. Methods: Following the PRISMA Extension for Scoping Reviews guidelines, a comprehensive search was conducted across Scopus, EMBASE, PubMed, PsycINFO, CINAHL, the Indigenous Studies Portal, and Google Scholar for English-language studies published between 2004 and 2025. Search terms combined dementia and cognitive impairment with First Nations, Indigenous peoples, and related concepts, alongside terms for risk factors, intervention, prevention, care strategies, and health disparities. Two reviewers independently screened studies and extracted data using a standardised template. Of the 620 records identified, 324 were screened, 130 were assessed in full, and 75 met the inclusion criteria. Data were narratively synthesised to identify key themes and evidence gaps. Results: The review revealed a disproportionate burden of dementia among First Nations peoples, characterised by earlier onset and higher prevalence than in non-First Nations populations. Major modifiable risk factors included social determinants of health, lifestyle behaviours, and inequitable access to healthcare. Studies emphasised the importance of culturally safe, community-led, and multidisciplinary approaches; however, many interventions remain poorly adapted to the diverse cultural contexts of First Nations communities. The review also identified gaps in diagnostic tools, culturally appropriate care pathways, and the integration of traditional knowledge and digital innovations in dementia management. Conclusions: Addressing dementia inequities among First Nations Australians demands transformative, community-driven action that extends beyond descriptive research. Future work should prioritise co-designed, culturally grounded interventions that embed First Nations knowledge systems, strengthen healthcare capacity, and foster long-term community empowerment. Embedding cultural safety within policy and clinical frameworks, and shifting toward preventive, strengths-based approaches, will advance equity in dementia care and provide valuable insights for First Nations health systems globally. Full article

Amphibious light sport aircraft (LSA) combine the versatility of land and water operations but suffer aerodynamic penalties from their inherent design requirements, limiting cruise performance. This study investigates two drag reduction features for a proposed high-performance amphibious LSA developed by Altavia Aerospace. The concept targets a cruise speed of 140 KTAS, using retractable wingtip pontoons and a novel retractable hull step fairing. A 1/5-scale flying model was built and flight tested to assess the aerodynamic benefits of these features and evaluate sub-scale flight testing as a tool for drag measurement. Estimated propulsive power and GPS-based speed data corrected for wind were used to compute an estimated 17% reduction in drag coefficient by retracting the pontoons. The hull step fairing showed no measurable gains, likely due to inconsistent battery voltage, despite literature indicating potential 5% drag savings. Drag measurement precision of 7–9% was achieved using the power-based method, with potential precision better than 3% achievable if the designed thrust data system were fully validated and an autopilot integrated. A performance estimation for Altavia Aerospace’s concept predicts a cruise speed of 134 KTAS at 10,000 ft. Achieving the target of 140 KTAS may require further aerodynamic refinement, with investigation of a tandem seating configuration to reduce frontal area recommended. The study provides an initial drag assessment of retractable wingtip pontoons and demonstrates the potential of sub-scale flight testing for comparative drag analysis—two novel contributions to the field. Full article

Background/Objectives: Antimicrobial resistance (AMR) is a major global health threat that reduces antibiotic effectiveness and increases healthcare burdens. Countries in the Asia–Pacific region face a particularly high AMR burden, necessitating international collaboration, education, and practical training to combat this growing crisis. This study describes the design, implementation, and educational outcomes of the Infection Diagnosis Workshop, a short-term international program primarily targeting undergraduate medical sciences students that integrates AMR-focused hands-on clinical microbiology training and lectures, alongside cross-cultural collaboration and scientific English communication. Methods: The Infection Diagnosis Workshop was implemented as a four-day program combining lectures with hands-on laboratory activities. Training emphasizes the detection and analysis of antibiotic-resistant bacteria through environmental sampling, bacterial culturing, phenotypic and genotypic resistance detection, and species identification, core components that have remained consistent since the workshop’s establishment. Students also attended lectures on AMR science, global impact, and management strategies. Group discussions and collaborative tasks encouraged interdisciplinary learning. A thematic analysis of student feedback essays from previous workshop cohorts was conducted to identify key concepts, learning outcomes, and shared experiences. All participants provided informed consent for the use of their written feedback. Results: Thematic analysis revealed key learning outcomes categorized into three themes: (1) Knowledge, Awareness, and Technical Skills; (2) Cultural Understanding and Cross-Cultural Collaboration; and (3) English Language and Communication Skills. Students reported increased AMR knowledge, improved laboratory proficiency, enhanced cultural adaptability, and greater confidence in English communication. They also expressed a deeper appreciation for interdisciplinary and international approaches to AMR. Conclusions: The Infection Diagnosis Workshop effectively integrated practical laboratory training with international and cross-cultural engagement. The program strengthened student competencies and contributed to building global partnerships essential for combating AMR. Full article

Wind power generation ships (WPG ships), which combine rigid sails for propulsion and underwater turbines for onboard power generation, have attracted increasing attention as a promising concept for utilizing renewable energy at sea. This study presents an integrated assessment of a WPG ship by combining towing-tank experiments, CFD simulations using ANSYS Fluent, and theoretical analysis to evaluate the coupled performance of sails, hull, and underwater turbines. First, sail thrust and bare-hull resistance were quantified to identify the effective operating-speed range under Beaufort 6–8 wind conditions, and the optimal number of rigid sails was determined. Based on a thrust–resistance balance at a representative rated operating point, two turbine configurations (two and four turbines) were preliminarily sized. The results show that ten rigid sails can provide near-maximum thrust without excessive aerodynamic interference, and the installation of turbines significantly reduces the feasible operating range compared to the bare-hull case. For the two-turbine configuration, a common effective ship-speed range of 6.58–8.0 m/s is obtained, whereas the four-turbine configuration is restricted to 6.58–7.44 m/s due to wake losses, additional appendage drag, and near-free-surface effects. The four-turbine configuration exhibits approximately 30% lower total power output than the two-turbine configuration. These findings demonstrate that an integrated, system-level evaluation is essential for WPG ship design and indicate that the two-turbine configuration offers a more favorable balance between power generation capability and operational flexibility. Full article

Material tracking and localization are key applications of Industry 4.0 in manufacturing process control. Traditional approaches—such as barcode or QR code identification and RTLS-based localization using RF/UWB, 5G or GPS–require a large and complex infrastructure. As an alternative, this paper proposes an IoT-based solution that combines short-range Bluetooth Low Energy (BLE) communication with LPWAN LoRaWAN networks. Hybrid solutions using LoRaWAN and BLE technologies already exist, but pure localization based on BLE tags can lead to ambiguous asset identification in geometrically dense scenarios. Our paper aims to solve this problem with an alternative concept called Associated LoRaWAN Sensors (ALSs). An ALS enables logical grouping and integration of heterogeneous LoRaWAN sensors, providing their own data or directly scanning BLE tags. Sensor data can be combined and supplemented with new information, data, and events, supported by application logic (use case). Although ALS represents a general concept that could be applicable to various use cases (such as warehouse monitoring, object tracking), our paper will focus mainly on material tracking and validation in manufacturing. For this purpose, we designed a specific ALS model that integrates a classic LoRaWAN BLE sensor with an additional LoRaWAN magnetic contact sensor. The magnetic contact switch can provide validation of exact position, in addition to localization by BLE tag. Experimental validation using BLE tags (Trax 10229) and LoRaWAN sensors (IoTracker3, Milesight WS301) demonstrates the usability of the ALS model in typical industrial scenarios. We also measured RSSI and evaluated the accuracy of tag localization (3 × 25 = 75 tests) for the worst-case scenario: material validation on a machine with a BLE tag distance of ~0.5 m. While the traditional approach showed up to a 20% failure rate, our ALS model avoided the issue of incorrect accuracy. An additional magnetic switch in ALS confirmed that the correct carrier with the associated tag is attached to the machine and eliminated incorrect localization. The results confirm that a hybrid model based on BLE and LoRaWAN scanning can reliably support material localization and validation without the need for dense RTLS infrastructures. Full article

Glucagon is a peptide hormone secreted by pancreatic alpha cells which elevates blood glucose and plays a critical role in diabetes onset and homeostasis. The accurate assessment of glucagon concentration is challenging due to its structural similarity with other hormones, causing cross-reactivity in antibody-based methods. Rapid and specific glucagon detection is essential, particularly during hypoglycemia. This study aimed to develop glucagon-specific probes combining high specificity, rapid detection, and ease of operation. We designed novel peptide-based probes by screening glucagon-binding peptides from the glucagon receptor sequence using a peptide array method. This strategy, based on receptor amino acid sequences, can be applied to the identification of binding peptides for other hormones, expanding its potential utility. The screened peptides were conjugated with fluorescent dyes to create probes enabling detection within 30 min. The developed probes demonstrated superior specificity for glucagon relative to similar sequence analogs compared with conventional antibody-based methods, with detection limits in the nanomolar range. This study represents a proof-of-concept approach for rapid and highly specific glucagon detection. However, further optimization of probe sensitivity and validation under physiological conditions will be required before clinical or diagnostic application. These improvements in the probe’s properties will enable the reliable blood glucagon detection and accurate diagnostic assessment of diabetes-related diseases. Full article