Urban sprawl has been the subject of extensive scholarly investigation, as it is widely regarded as an unfavourable phenomenon with profound socio-economic consequences. Its fundamental forms have been delineated through specific Spatial Form Metrics (SFMs). In southern Poland, there exists a region whose dispersed development pattern is particularly distinctive. Owing to its considerable size—exceeding 5500 km²—it was deemed appropriate to analyse this area using the metrics and categories conventionally applied in urban sprawl research. The findings reveal a settlement pattern often described in the literature as resembling a ‘leopard skin’. Key urban parameters—such as density, intensity, dispersion, and clustering—were most effectively characterised by Shannon entropy levels calculated for these categories. In all instances, the entropy values proved to be very high, indicating minimal variation in development form across the study area. This outcome reflects the prevalence of numerous small, closely spaced building clusters, without the emergence of major concentrations capable of serving as nuclei for service centres with a developed public realm. As a result, structures that would ordinarily provide higher-order services and foster social integration fail to materialise. The implications for the open landscape are pronounced and predominantly negative: both agricultural landscapes and the still-existing, though limited, semi-natural landscapes are severely fragmented by scattered, unstructured building clusters. This fragmentation undermines rational agricultural management and impedes the conservation of self-regenerating areas that approximate the natural landscape. Against this backdrop, the present study examines the built-up structure of Area X in order to delineate pathways for a transition from environmentally detrimental settlement patterns towards forms of development that not only ensure the sustenance of urban life but also align with the broader principles of sustainable urban development, thereby safeguarding the continuity of urban life as a fundamental condition for long-term urban resilience.

Friction stir welding (FSW) is an environmentally friendly, solid-state welding technique. In this research work, we analyze the microstructure of a new type of FSW weld applying a two- stage framework based on image processing algorithms containing a segmentation step and microstructure analysis of objects occurring in different layers. A dual-speed tool as used to prepare the tested weld. In this paper, we present the segmentation method for recognizing areas containing particles forming bands in the microstructure of a dissimilar weld of aluminum alloys made by FSW technology. A digital analysis was performed on the images obtained using an Olympus GX51 light microscope. The image analysis process consisted of basic segmentation methods in conjunction with domain knowledge and object detection located in different layers of a weld using morphological operations and point transformations. These methods proved to be effective in the analysis of the microstructure images corrupted by noise. The segmentation parts as well as single objects were separated enough to analyze the distribution on different layers of the specimen and the variability of shape and size of the underlying microstructures, which was not possible without computer vision support.

Pediatric craniofacial fractures represent a significant diagnostic challenge due to age-dependent anatomical variability, subtle fracture lines, and the limited availability of specialists during emergency care. Computed tomography (CT) remains the gold standard for fracture assessment; however, small or non-displaced fractures may be easily overlooked. Advances in artificial intelligence offer opportunities for automated support in injury detection. In this study, we developed a 2.5D deep learning model that uses multiplanar CT reconstructions (axial, coronal, sagittal) as a three-channel input to a ResNet-18 network with transfer learning. A total of 63 high-quality CT examinations were included and split into a training set (n = 44) and a validation set (n = 19). The preprocessing pipeline included isotropic resampling, bone-window normalization, and the generation of 384 × 384 images. Model performance was evaluated using ${\mathrm{AUC}}_{ROC}$, ${\mathrm{AUC}}_{PR}$, sensitivity, specificity, precision, F1-score, and threshold optimization using Youden’s index. The proposed model achieved ${\mathrm{AUC}}_{ROC}$ = 0.822 and ${\mathrm{AUC}}_{PR}$ = 0.855. At the optimal decision threshold (t = 0.54), sensitivity reached 0.556, specificity 1.000, and F1-score 0.714. Grad-CAM visualizations correctly highlighted fracture-related structures, which was confirmed in an independent clinical assessment. The results demonstrate the potential of the proposed model as a decision-support tool for pediatric craniofacial trauma, providing a foundation for future extensions toward radiomics and hybrid deep-radiomic pipelines.

Symbiosis and synergy among urban uses are key determinants of spatial quality, liveability, and resilience. While symbiosis denotes the coexistence of users and functions within specific places, synergy refers to the collective benefits emerging from their interaction. These dynamics are especially relevant in city centres and main streets, which serve as structural and social backbones of urban life. This article applies the SyM_SyN Method to Zwycięstwa Street in Gliwice, Poland, to assess the intensity and distribution of symbiotic and synergistic relations. The analysis identified significant spatial deficiencies that weaken the coherence and attractiveness of the street. The results demonstrate how a systematic, data-driven evaluation can expose hidden weaknesses in urban structures. Importantly, from the perspective of the smart city paradigm, liveability and responsiveness of urban spaces cannot be reduced to technology-driven systems of sensors and devices. They must also be understood in terms of human-scale interactions and the ability of urban form to support them. Beyond its methodological contribution, the study emphasises the practical implications for urban renewal: reinforcing positive interactions between adjacent uses enhances street vitality, improves social inclusiveness, and supports more sustainable development strategies. The SyM_SyN Method thus provides both an analytical framework and a decision-support tool for designing user-oriented, high-quality urban spaces within the broader smart and sustainable city paradigm.