Search Results (1,241)

Coastal urbanization is increasingly constrained by legacy land-use patterns and escalating climate risks, yet long-term morphological trajectories remain poorly quantified due to the absence of multispectral data in pre-satellite archives. This study introduces a scalable deep learning pipeline that bridges a century-scale domain gap through an attention-enhanced Pix2Pix colorization stage and a few-shot U-Net++ segmentation stage, enabling automated reconstruction of urban expansion from panchromatic historical aerial imagery (1920–1971) and digital aerial photographs (1997) to contemporary very-high-resolution satellite data (2024) in Les Sables-d’Olonne, France. The novelty of the approach lies in coupling generative colorization with epoch-specific fine-tuning to overcome radiometric and annotation bottlenecks that have historically prevented quantitative urban reconstruction from pre-satellite archives. The colorization stage achieved high spectral fidelity (PSNR 35.21 dB, SSIM 0.9762), and segmentation performed strongly on modern imagery (mIoU 0.9789). While the segmentation model performed strongly on modern imagery, direct transfer to historical data exhibited substantial domain shift due to radiometric discrepancies. Few-shot adaptation on year-specific calibration sets recovered reliable building footprints (mIoU 0.53–0.65) across the full timeline. Multi-scalar analysis of the reconstructed footprints revealed constrained anisotropic expansion: early saturation of the coastal historic core, followed by rapid inland peri-urbanization post-1971 driven by geographic barriers. This spatiotemporal shift has entrenched spatial lock-in, placing recent development in retro-littoral zones that are vulnerable to submersion and characterized by severe vegetation loss. The framework unlocks previously inaccessible historical archives for quantitative urban monitoring, providing critical insights into legacy effects of unconstrained growth and informing resilient coastal planning under climate change. Full article

Background/Objectives: Visuospatial impairments are among the earliest cognitive symptoms in Alzheimer’s disease (AD) and related dementias (ADRD), yet standard assessments often lack ecological validity and focus on isolated domains. This study examines whether integrating linguistic, behavioral, and eye-tracking measures provides a more comprehensive characterization of cognitive deficits within a multimodal, exploratory framework. Methods: Twenty older adults (10 with mild to moderate dementia, including AD/ADRD, and 10 age-matched controls) completed three tasks: (1) oral narrative production, (2) visuospatial behavioral tasks (manipulation, recognition, reproduction), and (3) free-viewing eye-tracking. Linguistic, behavioral (time, errors), and fixation-based measures were analyzed using non-parametric statistics, with emphasis on effect sizes and cross-domain patterns. Results: The clinical group differed consistently from controls across domains. Linguistic measures showed increased output but reduced quality, including lower syntactic complexity, more grammatical errors, greater pragmatic deviations, and reduced gist comprehension. Behavioral tasks revealed slower performance and more frequent failures. Eye-tracking differences were less pronounced, showing a tendency toward longer fixations and less efficient visual exploration. A composite multimodal index showed clear separation between groups, indicating a consistent pattern of impairment across measures. Conclusions: Cognitive differences in dementia are expressed across multiple domains, with the strongest effects in linguistic and behavioral measures. These findings highlight the value of multimodal profiles for capturing multidimensional impairment. Results should be interpreted as exploratory and require confirmation in larger, confirmatory studies. Full article

In the renewal of rural self-built houses, dispersed construction patterns, insufficient design guidance, and resource constraints often lead to tensions between individual building needs and the overall settlement landscape. Grounded in the theory of spatial self-organization, this study proposes a roof interface renewal framework of “Clustering–Collaboration–self-organization,” and takes Dianju Village in Anning City, Yunnan Province, as a case study to explore how limited architectural interventions can address the fragmentation of roof landscapes in rural settlements. This research adopts a mixed-method approach combining ethnographic fieldwork, resident design observation, and post-occupancy evaluation (POE). The POE was conducted with 16 participating households, focusing on residents’ perceptions of roof usability, visual order, material acceptance, opportunities for neighborhood interaction, and maintenance issues. The findings indicate that residents generally perceive that continuous roof treatment, the application of bamboo–timber materials, and adjustable structural units have improved the usability of roof spaces, while enhancing their recognition of the overall village image and the expression of local materials. At the same time, residents’ feedback suggests that the long-term performance of bamboo–timber materials still depends on continuous maintenance and appropriate structural protection. The contribution of this study lies in translating spatial self-organization theory into a participatory and locally adaptive process of rural landscape renewal. Rather than providing a directly replicable roof typology, this case offers exploratory insights into key interface identification, resident negotiation, and localized construction strategies for the renewal of rural self-built houses in developing and transitional contexts. Full article

High-voltage direct current (HVDC) transmission systems are increasingly used for long-distance power transmission and the integration of renewable energy sources. In such systems, outdoor insulators are exposed to combined electrical stresses, including steady DC voltage, transient overvoltages, and environmental contamination, which can significantly influence leakage current behaviour and insulation performance. This work presents an experimental and numerical investigation of leakage currents on artificially contaminated polymer insulators under two application-relevant HVDC operating scenarios. The first scenario considers superimposed HVDC voltage with switching impulses and very slow front overvoltages, which may occur during fault conditions in converter-based HVDC systems. The second scenario investigates electromagnetic coupling effects in a hybrid HVDC/HVAC transmission line configuration, where AC and DC conductors are installed on the same tower. Artificial contamination layers with different morphologies and conductivities are applied to the insulator surface to reproduce realistic pollution conditions. Leakage currents are measured using a high-resolution acquisition system, and the results are supported with numerical simulations based on finite-element modelling. The results show that transient overvoltages significantly increase leakage current amplitude and duration, leading to increased electrical stress on contaminated insulators. In the hybrid transmission configuration, electromagnetic coupling between AC and DC paths induces additional current components in the DC leakage current. The presented results contribute to a better understanding of leakage current behaviour under realistic HVDC operating conditions and provide useful information for insulation assessment and condition monitoring of outdoor insulators in modern HVDC transmission systems. Full article

Knowledge about the condition of electrical equipment in energy networks is of great importance to network operators. Partial discharges are a key parameter for evaluating the health of the insulation. While a quantifiable PD measurement for offline tests is state of the art, it is costly and labour-intensive. It, therefore, makes sense to carry out permanent monitoring during operation. At the medium-voltage level in the European interconnected grid, comprehensive monitoring of PD is not implemented. This study presents a novel sensor concept that is used to detect PD in medium-voltage switchgear and cables: the so-called Magnetic Flux Concentrator Sensor (MFCS). It is an inductive sensor concept with high sensitivity in the frequency range of a few MHz, like well-established High-Frequency Current Transformers (HFCTs) but with better magnetic saturation properties in specific use cases. The highly permeable ferrite core of the MFCS is unconventionally shaped, resulting in a higher-saturation field strength. Therefore, this sensor is not driven into saturation by the operating currents of typical MV power cables. Using the MFCS and conventional HFCT in a suitable combination enables direction-selective PD detection. This work presents the sensor concept and the method for directional detection of the PD location, as analysed and evaluated theoretically and practically with laboratory experiments. Full article

Pulse-width-modulated (PWM) automotive headlights enhance nighttime event-based camera detection, yet systematic parameter optimization for vulnerable road user detection remains unexplored. This study evaluates PWM frequency, duty cycle, light distribution, ego-vehicle speed, and ambient lighting under European New Car Assessment Programme-inspired crossing scenarios for cyclist and pedestrian detection. Results establish performance ranging from substantial improvements to severe degradation relative to continuous illumination. Cyclist detection achieves robust performance with high-frequency modulation across light distributions, while low-frequency operation with low beam produces severe degradation through background noise accumulation. Pedestrian detection requires high beam with street lighting enabled; low beam universally fails regardless of modulation parameters. Limited parameter combinations achieve simultaneous improvements for both targets. Detection performs optimally on retroreflective surfaces, while low-reflectivity clothing limits capability, requiring target-specific optimization. Full article

Background/Objectives: Fever is a common concern among parents, often leading to heightened anxiety and misconceptions about its management. While fever phobia has been extensively studied in Western countries, data from the Middle East—particularly Iran—remain limited. Understanding parental knowledge and anxiety in this cultural context is essential for developing targeted educational interventions. This study aims to assess parental knowledge, behavior, and anxiety regarding fever in children and to identify factors associated with higher levels of anxiety among Iranian parents, thereby contributing culturally specific evidence to the international literature on pediatric fever management. Methods: A cross-sectional study was conducted involving 552 parents from Tehran, Iran, recruited through convenience sampling. Data were collected using self-administered questionnaires assessing demographic characteristics, knowledge about fever, treatment practices, and anxiety levels using a 10-point Likert scale. Principal component analysis (PCA) was performed to examine the underlying factors influencing parents’ decisions to reduce fever. Univariate and multivariate linear regression analyses on standardized z-values were conducted to determine the predictors of fever-related anxiety. Results: Results showed that 67.4% of parents experienced anxiety when managing their child’s fever, with 65.6% perceiving fever as harmful. Fear of febrile seizures (77.4%) and brain damage were significant concerns motivating parents to reduce fever. Female parental sex (β = 0.336, p = 0.004) and the perception of fever as harmful (β = 0.058, p < 0.001) were the strongest predictors of fever-related anxiety. The PCA identified two key factors influencing fever management behavior: well-being protection and medical risk prevention. Parents commonly treated fever using combinations with either Paracetamol or Ibuprofen (47.6%). Conclusions: Parental anxiety about fever in Iran is largely driven by misconceptions, especially regarding febrile seizures and brain damage. Culturally tailored education and clear communication from healthcare providers are essential to reduce these fears, improve fever management, and decrease unnecessary antipyretic use. Full article

To enhance the measuring capabilities of modern Non-Destructive Evaluation (NDE) devices, it has become essential to integrate standardized digitization services and industry-compliant functionalities. This perspective paper examines approaches for improving NDE systems by incorporating key Industry 4.0 technologies, specifically digital representations such as the Asset Administration Shell (AAS) and OPC UA (Open Platform Communications Unified Architecture). We discuss requirements for interoperable, semantically rich descriptions of NDE systems, outline how OPC UA information models and AAS submodels can be combined with MQTT-based transport, and illustrate these concepts through representative prototype implementations, including predictive maintenance and chatbot assistant use cases. By leveraging these technologies, NDE devices can be transformed into interoperable, data-rich, and intelligent components within smart industrial ecosystems. Compared with previous studies, this Perspective is the first to systematically bring together the requirements, architectural patterns, and evaluation criteria for digital representations designed specifically for NDE systems. It also provides, in a practical and accessible way, NDE-focused OPC UA and AAS-based architectures that support both predictive maintenance and LLM-assisted operator guidance. The presented implementations are at an early stage and serve as illustrative examples, while systematic quantitative validation is ongoing and is outlined as future work. Full article

Background: This study aimed to assess the prevalence of PD-L1 protein expression in dermatofibrosarcoma protuberans (DFSP) to provide insights into the potential use of immune checkpoint inhibitors. Methods: We retrospectively analyzed formalin-fixed, paraffin-embedded primary DFSP specimens (n = 17). Diagnoses were confirmed by two senior dermatopathologists according to guideline criteria, including diffuse CD34 positivity and storiform spindle cell morphology. All cases represented conventional DFSP without fibrosarcomatous transformation. PD-L1 immunohistochemistry was carried out using a rabbit monoclonal antibody (ab205921, clone 28-8; Abcam). Only membranous staining in viable tumor cells was scored as a tumor proportion score (TPS), where >1% was considered positive. Any cytoplasmic staining without convincing membranous accentuation was not scored. PD-L1 staining in tumor-infiltrating immune cells was recorded separately. Five pleomorphic dermal sarcomas served as positive controls. Results: The median age was 62 years (IQR 55–74); 12 patients were men and 5 were women. The primary sites were trunk (59%), upper extremity (35%), and lower extremity (6%); immunosuppression was present in 18%. By FNCLCC, 82% of tumors were G1 and 18% were G2; no G3 tumors were identified. All DFSPs were PD-L1-negative in DFSP cells (TPS ≤ 1%) and in tumor-infiltrating lymphocytess. Among controls, 3/5 pleomorphic dermal sarcomas were PD-L1-positive with the expected membranous pattern and variable intensity. Conclusions: PD-L1 expression was absent in this cohort of conventional, predominantly low-grade DFSP, suggesting that classic DFSP is generally not an ideal candidate for PD-1/PD-L1-directed checkpoint blockade. These conclusions should not be extrapolated to fibrosarcomatous DFSP or metastatic disease, where PD-L1 expression has been reported. Selective PD-L1 testing may still be warranted in clinically aggressive scenarios (e.g., fibrosarcomatous transformation, unresectable recurrence, or metastasis). Full article

Background: Modern supply chains (SC) are increasingly difficult to manage as they become more complex and interconnected. This encourages companies to rely more on real-time data analysis and analytical tools on operational processes. This study aims to develop and evaluate a Supply Chain Wave Report for a non-food retail that represents goods movement across logistics stages as a continuous analytical flow. Methods: Proposed framework integrates multiple operational phases—Booked Orders, Main Transit, On-Carriage, Warehouse Operations, Store Delivery, and Sales—into a unified monitoring structure. This model can combine operational data with advanced analytics, including Artificial Intelligence-, cloud computing-, and Internet of Things-based technologies. Through cloud-based data infrastructures, System enables data integration and near real-time visibility across organizational functions, allowing continuous monitoring through key performance indicators and predictive simulations. Results: This framework enables dynamic performance of supply chain management and generates real-time signals as goods move across logistics network. This enables managers to detect irregularities earlier and respond before operational deviations propagate further along the chain. Wave-based monitoring approach highlights interdependence between SC stages and illustrates how small disruptions may propagate over time, potentially contributing to effects like bullwhip effect. Conclusions: Findings suggest that a cloud-enabled wave analytics framework can enhance coordination, reduce information gaps, and support informed decision-making in retail. Full article

A recent umbrella review evaluated evidence-based interventions for children with developmental central hypotonia, including those with Down syndrome. Motor, sensorimotor, orthotics, positioning, mobility, and infant massage interventions are supported by positive but low- or very-low-quality evidence. Using a retrospective case report format, these interventions are described, and their proposed mechanism of action is examined through the F-words lens tool and from the perspective of the parent. Tummy time, compression garments, early supported sitting for grasp and reach, ON-Time use of a supported stepping device, and orthotics are all used in the context of coaching in natural environments and family-centered care. Full article

The increasing impact of climate change and resource scarcity demands energy-efficient and resource-conserving manufacturing strategies. Metal forming offers substantial potential for lightweight construction and material efficiency. Forming-induced ductile damage, particularly void nucleation and growth, is often neglected in component design. Industrial practice still relies mainly on macroscopic mechanical properties and safety factors, while microstructural damage evolution and its influence on fatigue performance are largely disregarded. This study investigates load-path-dependent fatigue behavior and damage mechanisms using axial and combined axial–torsional fatigue tests. Particular attention is given to the phase shift d between axial and torsional loading, which strongly affects fatigue life. The results indicate that axial loading dominates damage evolution, while load path interactions significantly change fatigue performance. A phase shift of d = 90° resulted in a significant increase in the number of cycles to failure, N_f, for different total strain amplitudes with the same rotational angle amplitude of θ = 10°. These findings highlight the importance of considering load-path-sensitive stress states in fatigue assessment of formed components. Fractographic analyses, AI-assisted 3D reconstruction, and confocal laser scanning microscopy support the experimental results. Full article

In today’s world, characterised by rapid technological advances, particularly in AI, companies are compelled to acquire knowledge through employee training. This article seeks to empirically validate four hypotheses derived from a theoretical model identifying key factors firms should consider when investing in training. The hypotheses concern the most suitable type of knowledge for companies to invest in, according to their production processes, as well as the mechanisms for preventing opportunistic behaviour by trained employees. Cross-frequency tables are analysed using data obtained from a sample of 105 Mexican companies operating in both manufacturing and services sectors, representing an appropriate approach given the nature of the data. The results partially support the model. Manufacturing firms tend to train employees in specific skills and use simultaneous training to prevent opportunistic behaviour, whereas companies with heterogeneous production processes predominantly invest in general knowledge. However, firms providing professional services invest more in general knowledge than predicted by the model, contrasting with evidence from Spanish companies in the same industry. These findings suggest that the model should be refined to account for the possible complementarity between specific and general knowledge in training and for differences in institutional, cultural, and economic environments. Full article

An increasing number of municipalities are adopting urban digital twins (UDTs) to improve urban management. Although the models differ widely, municipalities face similar challenges in their implementation. Therefore, sharing insights on UDTs provides an opportunity for collective growth. To facilitate this growth, the present exploratory study maps the characteristics, challenges, and potentials of 99 UDTs in Europe, North America, and Asia. We first estimate the UDT readiness based on established features, along with contextual and local authority involvement indicators. Next, we conduct semi-structured interviews with key individuals from eight selected cities to contextualize the review findings. The mapping results indicate that most UDTs in our sample operate at the municipal level, and that over half (57%) are not in series operation. The reviewed UDTs are mid-level in maturity, and local authority involvement is a key driver of scalability. We infer that UDT progress depends as much on common frameworks, organizational readiness, governance capacity, and relevant data as on technology. Collaborations with private companies and researchers can play a central role in the long-term sustainment and growth of UDT infrastructures. Full article

This study investigates the properties of concrete incorporating recycled aggregates (RAs) for rigid pavement applications. A 15-point three-level experimental design was used to vary three composition factors: Portland cement substitution with fly ash (FA), and dosages of a superplasticizer (SP) and polypropylene fibers (PFs). A set of experimental–statistical models (ES models) was developed to predict the concrete strength, abrasion and frost resistance (FR), water absorption (WA), and global warming potential (GWP). This study aimed to develop a material that achieves both adequate mechanical performance for pavement applications and enhanced environmental sustainability by incorporating RAs and FA. The results demonstrate that replacing up to 13% of cement with FA does not compromise the splitting tensile strength or FR. For non-fibrous concrete, this substitution increases FR by approximately 50 freeze–thaw cycles. Application of PFs (2.4–3 kg/m³) enhances splitting tensile strength by 14–16% and improves FR by about 50 cycles. Using response surface methodology (RSM), optimal concrete compositions were identified that meet all target criteria: compressive strength ≥ 40 MPa, flexural strength ≥ 5 MPa, FR ≥ F200 (cycles), and abrasion resistance (AR) ≤ 0.5 g/cm², while simultaneously minimizing GWP. An additional optimum composition was determined by imposing a constraint on splitting tensile strength of ≥4.5 MPa. This graphical optimization approach, utilizing two-factor interaction diagrams, provides an effective and visual methodology for practical concrete mixture design. The novelty of the method lies in the discretization of the factor space, which enables efficient identification of optimal concrete mixture compositions. Full article