Search Results (9,827)

In alignment with global educational trends, Australia has adopted a pluralistic approach to initial teacher education (ITE), encompassing traditional university-based programs, employment-integrated models and vocational training routes. This diversification of pathways has emerged as a strategic response to persistent workforce challenges, including chronic shortages, uneven distribution of qualified educators, and limited demographic diversity within the profession. Rather than supplanting conventional ITE models, these alternative pathways serve as complementary options, broadening access and enhancing system responsiveness to evolving societal and educational needs. The rise in non-traditional routes represents a deliberate response to the well-documented global teacher shortage, frequently examined in comparative educational research. Central to their design is a restructuring of traditional program elements, particularly duration and delivery methods, to facilitate more flexible and context-sensitive forms of teacher preparation. Such approaches often create opportunities for individuals who may be excluded from conventional pathways due to socioeconomic constraints, geographic isolation, or non-linear career trajectories. Significantly, the diversity introduced by alternative entry candidates has the potential to enrich school learning environments. These educators often bring a wide range of prior experiences, disciplinary knowledge, and cultural perspectives, contributing to more inclusive and representative teaching practices. The implications for student learning are substantial, particularly in disadvantaged communities where culturally and professionally diverse teachers may enhance engagement and academic outcomes. From a policy perspective, the development of flexible, multifaceted teacher education pathways constitutes a critical component of a sustainable workforce strategy. As demand for qualified teachers intensifies, especially in STEM disciplines and in rural, regional and remote areas, the role of alternative pathways is likely to become increasingly pivotal in achieving broader goals of equity, quality and innovation in teacher preparation. Full article

Achieving state-of-the-art performance (82.5% IoU, 85.6% F1), this paper proposes an enhanced DeepLabV3+ model for robust underwater crack detection through three integrated innovations: a physics-based light propagation correction model for illumination distortion, multi-scale feature extraction for variable crack dimensions, and curvature flow-guided loss for boundary precision. Our approach significantly outperforms DeepLabV3+, SCTNet, and LarvSeg by 10.6–13.4% IoU, demonstrating particular strength in detecting small cracks (78.1% IoU) under challenging low-light/high-turbidity conditions. The solution provides a practical framework for automated underwater infrastructure inspection. Full article

Coronary artery bypass grafting (CABG) has evolved into a cornerstone treatment for coronary artery disease, with graft selection playing a critical role in long-term outcomes. Multiple arterial grafting (MAG) represents a significant advancement over single arterial grafting, utilizing conduits such as the internal thoracic artery and radial artery to enhance graft durability and patient survival. This review examines the outcomes, challenges, and controversies associated with MAG, highlighting its superior patency rates and reduced need for repeat revascularization procedures. While the technique provides long-term survival benefits, concerns such as the complexity of surgical techniques, increased operative time, and higher resource utilization underscore the importance of surgeon expertise and institutional infrastructure. Patient selection remains critical, as factors like age, comorbidities, and gender influence outcomes and highlight disparities in access to MAG. Emerging evidence addresses debates regarding optimal graft choice and balancing long-term benefits against short-term risks. Future directions focus on ongoing clinical trials, innovations in minimally invasive and robotic-assisted CABG, and technological advancements aimed at improving graft patency. Professional guidelines and best practices underscore the need for personalized approaches to optimize MAG’s potential. This article underscores the promise of MAG in redefining CABG care, paving the way for enhanced patient outcomes and broadened applicability. This article highlights the promise of MAG in transforming CABG care, leading to improved patient outcomes and expanded applicability. Full article

Background/Objectives: Aging is often accompanied by physical and cognitive decline, affecting older adults’ mobility. Virtual reality (VR) offers innovative opportunities to safely practice everyday tasks, such as street crossing. This study was designed as a feasibility and pilot study to explore acceptance, usability, and preliminary effects of a VR-based road-crossing intervention for older adults. It investigates the use of virtual reality (VR) as an innovative training tool to support senior citizens in safely navigating everyday challenges such as crossing roads. By providing an immersive environment with realistic traffic scenarios, VR enables participants to practice in a safe and controlled setting, minimizing the risks associated with real-world road traffic. Methods: A VR training application called “Wegfest” was developed to facilitate targeted road-crossing practice. The application simulates various scenarios commonly encountered by older adults, such as crossing busy streets or waiting at traffic lights. The study applied a single-group pre-post design. Outcomes included the Timed Up and Go test (TUG), Falls Efficacy Scale-International (FES-I), and Montreal Cognitive Assessment (MoCA). Results: The development process of “Wegfest” demonstrates how a highly realistic street environment can be created for VR-based road-crossing training. Significant improvements were found in the Timed Up and Go test (p = 0.002, d = 0.784) and fall-related self-efficacy (FES-I, p = 0.005). No change was observed in cognitive function (MoCA, p = 0.56). Participants reported increased subjective safety (p < 0.001). Discussion: The development of the VR training application “Wegfest” highlights the feasibility of creating realistic virtual environments for skill development. By leveraging immersive technology, both physical and cognitive skills required for road-crossing can be effectively trained. The findings suggest that “Wegfest” has the potential to enhance the mobility and safety of older adults in road traffic through immersive experiences and targeted training interventions. Conclusions: As an innovative training tool, the VR application not only provides an engaging and enjoyable learning environment but also fosters self-confidence and independence among older adults in traffic settings. Regular training within the virtual world enables senior citizens to continuously refine their skills, ultimately improving their quality of life. Full article

The demand for land monitoring information continues to increase, but the range and diversity of the available products to date have made their integrated use challenging and, at times, counterproductive. There has therefore been a growing need to enhance and harmonise the practice of land monitoring on a pan-European level with the formulation of a more consistent and standardised set of modelling criteria. The outcome has been a paradigm shift away from a “paper map”-based world where features are given a single, fixed label to one where features have a rich characterisation which is more informative, flexible and powerful. The approach allows the characteristics to be dynamic so that, over time, a feature may only change part of its description (i.e., a forest can be felled, but it may remain as forestry if replanted) or it can have multiple descriptors (i.e., a forest may be used for both timber production and recreation). The concept proposed by the authors has evolved since 2008 from first drafts to a comprehensive and powerful tool adopted by the European Union’s Copernicus programme. It provides for the semantic decomposition of existing nomenclatures, as well as supports a descriptive approach to the mapping of all landscape features in a flexible and object-oriented manner. In this way, the key move away from classification towards the characterisation of the Earth’s surface represents a novel and innovate approach to handling complex land surface information more suited to the age of distributed databases, cloud computing and object-oriented data modelling. In this paper, the motivation for and technical approach of the EAGLE concept with its matrix and UML model implementation are explained. This is followed by an update of the latest developments and the presentation of a number of experimental and operational use cases at national and European levels, and it then concludes with thoughts on the future outlook. Full article

This study investigates the mechanisms by which green finance mitigates non-point source pollution. Based on provincial panel data from China spanning 2005 to 2023, this study conducts an empirical analysis that yields several key findings: (1) The development of green finance significantly reduces the intensity of agricultural non-point source pollution. (2) Green finance indirectly contributes to pollution reduction by incentivizing farmers to adopt environmentally sustainable production practices. (3) The pollution control effects of green finance are amplified in regions with advanced digital infrastructure. (4) The impact of green finance on agricultural pollution demonstrates a threshold effect associated with regional innovation capacity—only when innovation capability exceeds a certain threshold does the emission reduction effect of green finance become evident. Theoretically, this study broadens the research dimensions of green finance by integrating farmer behavioral factors and revealing boundary conditions related to technology and innovation. Policy implications include the need to tailor green financial products for agriculture, accelerate the development of rural digital infrastructure, and implement innovation-driven differentiated policies to enhance precision. Full article

In order to cope with the multimodal changes led by the digital era, enterprises urgently need to promote the construction of new-quality productive forces (NQPFs) through digital transformation. NQPFs take digital technology empowerment as the core driving force and emphasize the dynamic matching and synergy between the new-quality elements (digital infrastructure, digital talents, data resources, and diversified ecology) and the new-quality capabilities (digital dynamic capabilities) so as to unleash the innovation potentials of different production modes. Based on resource orchestration theory, this study constructs a “resource-capability-value creation” framework for digital empowerment (D-RCV) and employs fuzzy set qualitative comparative analysis (fsQCA) to examine 205 enterprise samples. Results reveal that enhanced innovation performance stems from digital empowerment at both resource and capability levels, generating three configurational paths: collaborative symbiosis, resource optimization, and data-driven approaches. These paths emerge through the interaction of resources and capabilities under different conditions. This study contributes by proposing a digital empowerment framework and exploring multiple pathway choices for new-quality productivity development. The findings provide theoretical insights for enterprise innovation research and practical guidance for innovation management strategies. Full article

During the last few years, the requirements for highly efficient, sustainable, and versatile materials in modern biomedicine, aircraft and aerospace industries, automotive production, and electronic and electrical engineering applications have increased. This has led to the development of new and innovative methods for material modification and optimization. This can be achieved in many different ways, but one such approach is the application of surface thin films. They can be conductive (metallic), semi-conductive (metal-ceramic), or isolating (polymeric). Special emphasis is placed on applying semi-conductive thin films due to their unique properties, be it electrical, chemical, mechanical, or other. The particular thin films of interest are composite ones of the type of transition metal oxide (TMO) and transition metal nitride (TMN), due to their widespread configurations and applications. Regardless of the countless number of studies regarding the application of such films in the aforementioned industrial fields, some further possible investigations are necessary to find optimal solutions for modern problems in this topic. One such problem is the possibility of characterization of the applied thin films, not via textbook approaches, but through a simple, modern solution using their electrical properties. This can be achieved on the basis of measuring the films’ electrical impedance, since all different semi-conductive materials have different impedance values. However, this is a huge practical work that necessitates the collection of a large pool of data and needs to be based on well-established methods for both characterization and formation of the films. A thorough review on the topic of applying thin films using physical vapor deposition techniques (PVD) in the field of different modern applications, and the current results of such investigations are presented. Furthermore, current research regarding the possible methods for applying such films, and the specifics behind them, need to be summarized. Due to this, in the present work, the specifics of applying thin films using PVD methods and their expected structure and properties were evaluated. Special emphasis was paid to the electrical impedance spectroscopy (EIS) method, which is typically used for the investigation and characterization of electrical systems. This method has increased in popularity over the last few years, and its applicability in the characterization of electrical systems that include thin films formed using PVD methods was proven many times over. However, a still lingering question is the applicability of this method for backwards engineering of thin films. Currently, the EIS method is used in combination with traditional techniques such as X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), energy-dispersive X-ray spectroscopy (EDX), and others. There is, however, a potential to predict the structure and properties of thin films using purely a combination of EIS measurements and complex theoretical models. The current progress in the development of the EIS measurement method was described in the present work, and the trend is such that new theoretical models and new practical testing knowledge was obtained that help implement the method in the field of thin films characterization. Regardless of this progress, much more future work was found to be necessary, in particular, practical measurements (real data) of a large variety of films, in order to build the composition–structure–properties relationship. Full article

This paper provides research that shows that the scale and quantification of the degree of fracturing in a rock mass should and can be considered when estimating geological strength index (GSI) ratings for rock mass strength and deformability estimates. In support of this notion, a brief review is provided to demonstrate why it is imperative that scale is considered when using GSI in engineering design. The impact of scale and scale effects on the engineering response of a rock mass typically requires a definition of fracture intensity relative to the volume or size of rock mass under consideration and the relative scale of the project being built. In this research three volume scales are considered: the volume of a structural domain, a representative elemental REV, and unit volume. A theoretical framework is established that links these three volume scales together, how they are estimated, and how they relate to parameters used to estimate engineering behaviour. Analysis of data from several examples and case histories for real rock masses is presented that compares and validates the use of a new and innovative but practical method (a sphere of unit volume) to estimate fracture intensity parameters VFC or P30 (fractures/m³) and P32 (fracture area—m²/m³) that is included on the vertical axis of the volumetric V-GSI chart. The research demonstrates that the unit volume approach to calculating VFC and P32 used in the V-GSI system compares well with other methods of estimating these two parameters (e.g., discrete fracture network (DFN) modelling). The research also demonstrates the reliability of the VFC-correlated rating scale included on the vertical axis of the V-GSI chart for use in estimating first-order strength and deformability estimates for rock masses. This quantification does not negate or detract from geological logic implicit in the original graphical GSI chart. Full article

The United Nations’ 2030 Agenda for Sustainable DeveTablelopment centers on the 17 Sustainable Development Goals (SDGs). Among these goals, two address climate change education: Goal 13, Climate Action, and Goal 4, Quality Education. In order to build a more sustainable future, climate change education is critical. In 2022, New Jersey became the first state in the US to integrate climate change into learning standards across subjects and grade levels K-12. In an effort to better understand the way in which teachers began to include climate change in their instruction, 50 teachers were observed implementing a lesson of their choosing that included climate change throughout the 2023–2024 academic year. Though most of the observed lessons featured science, many subject areas were included in the dataset, such as art, technology, history, and physical education. Teachers engaging in climate change instruction tended to use a variety of instructional practices. In nearly all cases, a multitude of methodologies were used in each lesson. However, small group instruction was featured in nearly all observed lessons. Quantitative descriptions of the findings are followed by three vignettes of exemplar instruction to provide a clearer understanding of the context of this work. These findings provide a scope for how climate change can be integrated in instructional settings at scale and suggestions for leveraging the experiences of early adopters of this innovation to support widespread implementation. Full article

The growing demand for functional and sustainable foods has driven food innovation, enhancing its nutritional value. This study aimed to develop a nutritious bread using local rye from the Trás-os-Montes region of Portugal and incorporating whey, a by-product of the dairy industry, as a replacement for water. Three bread formulations were tested: a traditional recipe with 37.5% rye flour and water (Control—CTR); the same recipe using whey instead of water (Rye Whey—RW); and a formulation with 100% local rye and whey replacing water (Full Rye Whey—FRW). Nutritional composition was assessed, including moisture, ash, protein, dietary fiber, sodium, potassium, lipids, and carbohydrates. Sensory analysis included both quantitative descriptive analysis and consumer acceptance testing. Microbiological quality was also evaluated. Whey-containing samples showed lower moisture and increased levels of ash, lipids, carbohydrates, and potassium. RW had the highest protein content (6.54 ± 0.28 g/100 g, p < 0.05), while FRW exhibited the highest dietary fiber (6.96 ± 0.15 g/100 g, p < 0.05). RW demonstrated a balanced nutritional and sensory profile, with high consumer acceptance. Overall, the combination of local rye and whey presents a promising strategy for producing nutritious bread while valorizing local agricultural resources and dairy by-products. These findings support sustainable food production practices and contribute to circular economy approaches. Full article

Medical education is the paradigm of 21st century education and the current changes involve the adoption of integrative and comprehensive patient-centered teaching and learning approaches. Thus, curricular developers from George Emil Palade University of Medicine, Pharmacy, Sciences, and Technology of Targu Mures (G.E. Palade UMPhST of Targu Mures) have recently designed and implemented an innovative medical curriculum, as well as two valuable assessment tools for both theoretical knowledge and practical skills. Thus, during the first three preclinical years, the students will benefit from an organ- and system-centered block teaching approach, while the clinical years will focus on enabling students to achieve the most important practical skills in clinical practice, based on a patient bedside teaching system. In terms of theoretical knowledge assessment, the UNiX center at G.E. Palade UMPhST of Targu Mures, a recently designed center endowed with the latest next-generation technology, enables individualized, secured multiple-choice question-based assessments of the student’s learning outcomes. Moreover, an intelligent assessment tool for practical skills was also recently implemented in our branch in Hamburg, the Objective Structured Clinical Examination (O.S.C.E). This system uses direct observations for testing the student’s practical skills regarding anamnesis, clinical exams, procedures/maneuvers, the interpretation of laboratory tests and paraclinical investigations, differential diagnosis, management plans, communication, and medical counselling. The integrative, comprehensive, patient-centered curriculum and the intelligent assessment system, implemented in G.E Palade UMPhST of Targu Mures, help define innovation in education and enable the students to benefit from a high-quality medical education. Full article

We propose a hybrid Convolutional Graph Neural Network (C-GNN) for direction-of-arrival (DOA) estimation in sparse sensor arrays under low-snapshot conditions. The C-GNN architecture combines 1D convolutional layers for local spatial feature extraction with graph convolutional layers for global structural learning, effectively capturing both fine-grained and long-range array dependencies. Leveraging the difference coarray technique, the sparse array is transformed into a virtual uniform linear array (VULA) to enrich the spatial sampling; real-valued covariance matrices derived from the array measurements are used as the network’s input features. A final multi-layer perceptron (MLP) regression module then maps the learned representations to continuous DOA angle estimates. This approach capitalizes on the increased degrees of freedom offered by the virtual array while inherently incorporating the array’s geometric relationships via graph-based learning. The proposed C-GNN demonstrates robust performance in noisy, low-data scenarios, reliably estimating source angles even with very limited snapshots. By focusing on methodological innovation rather than bespoke architectural tuning, the framework shows promise for data-efficient DOA estimation in challenging practical conditions. Full article

Energy-intensive industries (EIIs) face mounting pressure to reduce greenhouse gas emissions while maintaining international competitiveness—a balance that is central to achieving the EU’s 2030 and 2050 climate objectives. In this context, energy management (EM) emerges as a strategic instrument to decouple industrial growth from fossil energy consumption. This study proposes a redefinition of EM to support carbon-neutral supply chains within the European Union’s EIIs, addressing critical limitations of conventional EM frameworks under increasingly stringent carbon regulations. Using a modified systematic literature review based on PRISMA methodology, complemented by expert insights from EU Member States, this research identifies structural gaps in current EM practices and highlights opportunities for integrating sustainable innovations across the whole industrial value chain. The proposed EM concept is validated through an analysis of 24 EM definitions, over 170 scientific publications, and over 80 EU legal and strategic documents. The framework incorporates advanced digital technologies—including artificial intelligence (AI), the Internet of Things (IoT), and big data analytics—to enable real-time optimisation, predictive control, and greater system adaptability. Going beyond traditional energy efficiency, the redefined EM encompasses the entire energy lifecycle, including use, transformation, storage, and generation. It also incorporates social dimensions, such as corporate social responsibility (CSR) and stakeholder engagement, to cultivate a culture of environmental stewardship within EIIs. This holistic approach provides a strategic management tool for optimising energy use, reducing emissions, and strengthening resilience to regulatory, environmental, and market pressures, thereby promoting more sustainable, inclusive, and transparent supply chain operations. Full article

Healthcare supply chain management operates amid fluctuating patient demand, rapidly advancing biotechnologies, and unpredictable supply disruptions pose high risks and create an imperative for sustainable resource optimization. This study investigates the underlying mechanisms through which digital intelligence drives strategic decision optimization in healthcare supply chains. Drawing on the Resource-Based View and Dynamic Capabilities Theory, we develop a chain-mediated model, defined as the multistage indirect path whereby digital intelligence first bolsters innovation capability, which then activates supply chain resilience (absorptive, response, and restorative capability), to improve decision optimization. Data were collected from 360 managerial-level respondents working in healthcare supply chain organizations in China, and the proposed model was tested using structural equation modeling. The results indicate that digital intelligence enhances innovation capability, which in turn activates all three dimensions of resilience, producing a synergistic effect that promotes sustained decision optimization. However, the direct effect of digital intelligence on decision optimization was not statistically significant, suggesting that its impact is primarily mediated through organizational capabilities, particularly supply chain resilience. Practically, the findings suggest that in the process of deploying digital intelligence systems and platforms, healthcare organizations should embed technological advantages into organizational processes, emergency response mechanisms, and collaborative operations, so that digitalization moves beyond the technical system level and is truly internalized as organizational innovation capability and resilience, thereby leading to sustained improvement in decision-making performance. Full article