Search Results (1,595)

This paper examines the artistic project Border Ghosts (2018–2025) as a practice of material translation through which migrant presences—excluded from institutional records along the Mexico–United States border—become perceptible in artistic form. Situated within necropolitical regimes that produce structural vulnerability, the study draws on the work of Achille Mbembe, Ariadna Estévez, and Avery Gordon to consider how spectrality operates not as metaphor, but as a mediated mode of presence. Through brief interviews and three-dimensional recordings of bodies, objects, and temporary dwellings using 3D scanning and printing, the project transforms fragmentary traces into sculptural configurations that make precarious lives perceptible within exhibition space. The case studies show that even minimal testimonies, often absent from formal archives, can persist as material traces within aesthetic circulation. Rather than proposing a solution to structural violence, Border Ghosts approaches artistic practice as a way of engaging absence, mediation, and incompletion. In doing so, the project reflects on the limits of institutional recognition and on the conditions under which marginal lives may be encountered. Full article

This study evaluates stakeholders’ perceptions of the complexity of ecotourism opportunities and their support for ecotourism development, and then identifies the correlation between perception and support. This study adopts a mixed-method approach combining qualitative and quantitative techniques. In the first phase, in-depth interviews were conducted to explore the complexity of ecotourism opportunity development. In the second phase, a questionnaire survey was used to examine stakeholders’ perceptions and their support for ecotourism development. The results reveal moderate overall perception and support for ecotourism opportunity development among stakeholders. However, a strong positive relationship was identified between stakeholders’ perception of ecotourism complexity and their support for ecotourism initiatives. Regression analysis further indicated that stakeholders’ perception is positively associated with their level of support for ecotourism development. These findings provide practical insights for integrating stakeholder perspectives into conservation strategies and sustainable ecotourism development. This study contributes to conservation-oriented planning by linking stakeholder perception to ecotourism development. Full article

Background: Medication adherence is essential for treatment effectiveness and safety, but pharmacy students may find it difficult to assess adherence comprehensively during medication reviews (MRs). This study examined how pharmacy students assess medication adherence in real-world MRs and explored whether complementary adherence frameworks could support broader evaluation. Methods: This observational exploratory study was conducted in the integrated MSc (Master of Science) Pharmacy program at the University of Tartu, Estonia. During the internship, 21 pharmacy students performed a Brown Bag MR with patients aged 65 years or older who used at least 5 prescription medications. Data included patient interviews, e-prescription records, and a validated MR documentation form. An expert panel applied the World Health Organization Medication Adherence Model (WHO-MAM) and the Perceptions and Practicalities Approach (PAPA) to identify adherence determinants not captured by the student-used MR tool. Descriptive statistics and qualitative content analysis were used. Results: Students mainly documented therapy- and patient-related issues, such as incorrect dosing, side effects, and interactions, while socioeconomic and healthcare system factors were rarely identified. Students identified potential adherence-related issues in 19% of cases, whereas experts identified such issues in 57% of cases. Additional gaps included limited recognition of financial barriers, access difficulties, and social support factors. Conclusions: In this exploratory study, pharmacy students identified medication-use-related problems during MRs, but broader adherence-related determinants were less consistently documented. These preliminary findings suggest that structured frameworks such as WHO-MAM and PAPA may be useful for broadening adherence assessment in experiential pharmacy education. Full article

EigenPlaces is a state-of-the-art visual place recognition (VPR) method that constructs training classes via SVD-based focal points, where a fixed focal distance D controls how far the focal point is placed from each cell center. However, this globally fixed D cannot adapt to the diverse scene geometries encountered across different urban environments. In this work, we systematically analyze the sensitivity of D across multiple benchmark datasets and reveal that the optimal D value is highly dataset-dependent, with performance gaps of up to 4.4 percentage points between the best and worst D choices. We then propose a depth-aware adaptive D strategy that leverages monocular depth estimation to compute per-cell focal distances, combined with quantile mapping to ensure sufficient variance in the assigned D values. By establishing a principled connection between visual sensor data and geometric training supervision, our method enhances the environmental perception reliability of intelligent sensing platforms. Experiments on three benchmarks (Pitts30k, AmsterTime, SF-XL) validate the dataset-dependent nature of D and confirm that our depth-aware approach achieves the best same-distribution performance among all tested configurations. We further conduct a multi-strategy ablation comparing depth raw, depth quantile, and SVD eigenvalue ratio approaches, providing practical guidance for adaptive focal distance selection in VPR training pipelines. Full article

This study analyzes the closure, decommissioning, and abandonment (CDA) of a fuel storage and distribution facility in southern Quito, Ecuador, conceptualizing the process as a socio-technical urban transition embedded within territorial governance dynamics. While infrastructure decommissioning is commonly addressed from a predominantly technical perspective, limited research integrates reverse logistics design, stakeholder influence structures, and territorial development into a unified analytical framework, particularly in Latin American metropolitan contexts. Using a mixed-methods case study approach, the research combines documentary analysis, operational data, and 34 semi-structured interviews with public authorities, engineers, fuel marketers, business owners, and community representatives. A thematic analysis was applied to reconstruct the decommissioning logistics chain and to develop a stakeholder mapping and influence matrix assessing actor positions, economic interdependencies, and legitimacy claims. The findings show that decommissioning operates as a structured reverse logistics system embedded within asymmetric governance configurations, where economic dependency, risk perception, and urban redevelopment expectations generate competing territorial imaginaries. Technical feasibility alone proves insufficient to guide decision-making; instead, legitimacy emerges through the alignment of engineering planning, institutional coordination, and community-level expectations. The study advances an integrated socio-technical framework that articulates Engineering Management, Social Management, and Territorial Development, positioning decommissioning as a governance-driven transition rather than a purely technical operation. The results contribute to sustainability and infrastructure transition scholarship while offering practical guidance for managing urban hydrocarbon infrastructure closure in socially vulnerable territories. Full article

Simulation is increasingly recognised as a strategic approach in nursing education for developing clinical competencies within safe learning environments. However, there is limited understanding of how virtual patient simulation supports the early development of clinical reasoning from the perspective of nursing students. Aim: To explore the perceptions of first-year undergraduate nursing students regarding the development of clinical reasoning and collaborative decision-making through virtual patient simulation. Methods: A qualitative, descriptive, and exploratory design was adopted. Semi-structured focus groups were conducted with 73 first-year undergraduate nursing students. Data were analysed using thematic content analysis following Bardin’s approach. Results: Students perceived virtual patient simulation as a meaningful and high-impact learning strategy. Realism, interactivity, and group collaboration emerged as key strengths. Engagement with dynamic clinical scenarios supported the integration of theoretical knowledge into practice, enhanced prioritisation skills, and promoted structured clinical reasoning. Collaborative learning facilitated shared reflection and collective problem-solving, while immediate feedback enabled learning through error within a psychologically safe environment. Participants also reported increased confidence and autonomy in decision-making. At the same time, students identified limitations related to software constraints and the alignment between automated assessment and their reasoning processes. Conclusions: Group-based virtual simulation appears to support the early structuring of clinical reasoning, extending beyond technical skill acquisition to foster reflective and collaborative practice. Its educational value, however, depends on intentional curricular integration and strong pedagogical alignment including structured facilitation, alignment between assessment and learning objectives, and opportunities for guided reflection. These findings contribute to a process-oriented understanding of how novice learners make sense of clinical reasoning in simulated contexts. Full article

Image stitching is a computational technique designed to align and seamlessly fuse multiple overlapping images into a single panoramic image with an extended field of view. It plays a critical role in diverse domains, including mobile photography, autonomous navigation, and visual perception systems. However, most conventional image stitching pipelines implicitly assume that the input images have been pre-corrected for geometric distortions, particularly radial distortion inherent to wide-angle and fisheye lenses. This assumption often fails in practice, as many consumer-grade cameras lack built-in correction or calibration support. Consequently, applying standard image stitching methods to the uncorrected imagery frequently degrades feature correspondence reliability and introduces visible geometric misalignments and seam discontinuities in the final panorama. To overcome these limitations, this paper introduces a task-driven joint iterative optimization framework for image stitching that unifies unsupervised radial distortion correction, distortion-aware feature registration, and seam-aware blending within a single cohesive optimization objective. Specifically, lens distortion parameters are explicitly modeled as learnable variables and embedded into both the geometric registration and seam optimization sub-problems. An efficient closed-loop optimization strategy is then employed to jointly refine distortion parameters, homography estimates, and optimal seam paths in an alternating, mutually reinforcing manner. Implementation-wise, we first propose a calibration-free initial radial distortion estimation method which leverages intrinsic image gradients and epipolar consistency to provide physically plausible initialization for subsequent optimization. During iteration, distortion parameters are progressively refined by integrating robust geometric constraints derived from current feature matches (via RANSAC-based consensus filtering) with photometric consistency cues. Extensive experiments on multiple public benchmarks featuring pronounced radial distortion demonstrate that our method achieves superior stitching fidelity using metrics including PSNR and SSIM. It also confirms enhanced feature matching stability, which outperforms both distortion-agnostic approaches and two-stage pipelines that decouple distortion correction from registration. Furthermore, comprehensive ablation studies quantitatively and qualitatively validate the functional necessity and synergistic contribution of each core module, confirming the design rationale and effectiveness of the proposed joint optimization architecture. Full article

The widespread disposal of waste has led to severe environmental challenges, making the reuse of materials critical for sustainable development. Recycled products, which transform waste into valuable items, are gaining increasing attention from consumers. This research examines how perceived resource scarcity shapes consumer preferences for recycled products and the psychological mechanisms underlying this effect. Across four studies, we induced perceptions of scarcity using two distinct approaches and found that consumers experiencing resource scarcity exhibit higher purchase intentions for recycled products compared with those who do not. This effect is mediated by holistic thinking, which allows consumers to integrate information about a product’s past and present identities, enhancing appreciation for transformation and reuse. Moreover, perceived product contamination moderates this relationship. When contamination concerns are low, scarcity strengthens preference for recycled products, whereas high contamination perceptions weaken or eliminate this effect. These findings extend understanding of how resource scarcity influences sustainable consumption, highlight the cognitive processes driving recycled product demand, and provide practical guidance for policymakers and businesses promoting environmentally responsible consumption. Full article

The employment and labor market landscape has undergone significant transformations globally, including the three Central European countries examined in this study. Over the past decades, organizations in this region have transitioned from a state of full employment to labor shortages, raising the question: What factors have driven these changes? Our study aims to present a theoretical framework highlighting key macro-level factors, such as demographic trends, economic development, labor market dynamics, the impact of the COVID-19 pandemic, and the role of robotization and artificial intelligence. Based on two empirical studies conducted in 2019 and 2022 among Czech, Hungarian, and Slovak organizations, we analyzed the extent and causes of labor shortages, as well as the labor market effects of robotization. Using descriptive and non-parametric statistical methods, including frequency analysis and Mann–Whitney U tests, the study examined key trends and compared the two periods to identify significant shifts. The analytical approach of this study primarily aims to compare perceptions across occupational groups and between the two survey waves (2019 and 2022). Because most variables were measured on ordinal Likert-type scales and the datasets represent independent cross-sectional samples rather than a panel dataset, non-parametric methods were considered the most appropriate. More advanced causal modeling techniques, such as regression or factor analysis, were not applied because the objective of the research was exploratory and comparative rather than to establish causal relationships between variables. The findings reveal significant shifts in the perceived causes of labor shortages across occupational groups in the surveyed Central European organizations. In particular, increasing labor shortages were observed in specific job categories, alongside changes in the relative importance of the underlying drivers of labor shortages. While adopting robotization and artificial intelligence has been positively received, demographic decline and emigration remain critical challenges. The study provides practical insights for policymakers and corporate leaders regarding labor market challenges, workforce planning, and the potential role of robotization and artificial intelligence in addressing labor shortages. Although the research is based on a non-representative sample, it offers valuable insights into the Central European region’s employment and labor market trends. Future research could examine whether, in hard-to-fill positions, robotization and AI primarily provide indirect support by augmenting and reallocating human work, or whether they may serve as direct substitutes. Full article

Background/Objectives: This study aimed to investigate school-based speech–language pathologists’ (SLPs) perceptions of their ability and needs to identify and remediate students with dyslexia. Methods: A qualitative approach was employed, utilizing semi-structured interviews with school-based SLPs. The findings were thematically analyzed by following six steps; (a) familiarization with the data; (b) initial code generation; (c) theme identification; (d) theme review; (e) defining and naming themes; and (f) report writing. Results: The findings revealed that participants had a very limited knowledge of dyslexia, and most did not consider reading difficulties within their scope of practice. Professional development opportunities, collaboration with teachers, and administrative support were identified as crucial factors to enhance SLPs’ practice supporting dyslexic cases in school settings. Conclusions: The study showed that school-based SLPs lack the necessary knowledge to work with students with dyslexia, which aligns with results observed in other countries. This finding highlights the importance of empowering their abilities to effectively support students with dyslexia. Full article

Accurate camera–LiDAR calibration is a fundamental prerequisite for reliable perception in autonomous systems. However, traditional methods typically rely on manual intervention or specific calibration targets, which restrict their flexibility and scalability in dynamic, real-world environments. To address the challenge of targetless calibration, we propose EdgeDenseCalib, a novel approach driven by enhanced edge feature densification. A key innovation lies in a two-stage process designed to densify the inherently sparse edge features in LiDAR data, thereby making them highly comparable to the fine-grained edges present in images. Consequently, this facilitates more reliable feature matching between the two cross-modal data sources. An optimization algorithm is subsequently employed to refine the alignment and minimize the reprojection error. Experiments on the KITTI dataset show our method achieves accurate calibration results of 0.105° in mean rotation error and 0.903 cm in mean translation error. Compared to state-of-the-art edge-based methods, our approach significantly improves the rotation accuracy by 33.1% to 89.9%. This work provides a practical and automatic calibration solution, contributing to the development of more robust perception systems for autonomous applications. Full article

This contribution explores the role of reflective practice and performative methodologies in the professional development of support teachers, framing reflectivity as a complex and articulated form of thinking that goes beyond intuitive reflection. Drawing on theories of transformative learning and practice-based research, the paper argues that performative approaches—grounded in embodied, emotional, and narrative experience—can effectively foster teachers’ critical awareness, professional identity construction, and capacity for inclusive educational action. The study presents a teacher training experience implemented within the Specialization Course for Support Teaching Activities at Link Campus University, involving a 20-h workshop attended by 200 lower secondary school teachers. Centered on performance art practices, the workshop aimed to promote reflective processes related to themes of exclusion and inclusion through bodily engagement, collective meaning-making, and non-verbal communication. Participants were actively involved in designing and performing activities, thus positioning themselves as protagonists of their own learning trajectories. Data collected through pre- and post-intervention questionnaires highlight participants’ positive perceptions of the experience and its transferability to school contexts. Findings suggest that performative methodologies support emotional sharing, enhance group cohesion, and contribute to the creation of a supportive classroom climate, while also strengthening teachers’ reflective and transformative capacities. The paper concludes by emphasizing the pedagogical value of performative practices as tools for fostering inclusive, reflective, and experience-based teacher education. Full article

School leadership practices may influence teachers’ motivation and professional engagement, which, in turn, may affect overall school performance. This study explores how secondary school teachers and deputy head teachers perceive head teachers’ leadership practices and how these practices are understood to influence teacher motivation and professional engagement. Drawing on a qualitative design, data were collected through semi-structured interviews with 12 teachers and six deputy head teachers from six government secondary schools in Kabwe District, Zambia. A qualitative approach enabled an in-depth exploration of leadership perceptions across participants from multiple school contexts. Data were analysed using thematic analysis to identify patterns in leadership practices described by participants. The findings indicate that participants frequently described leadership practices aligned with delegation, mentorship, and open communication, shaped by contextual and organisational factors. However, these practices were not consistently experienced across all school contexts. Participants also described the presence of democratic and autocratic leadership practices. Participants perceived participatory and supportive leadership practices as contributing to their motivation and professional engagement. However, participants from several schools reported that autocratic leadership practices continued to shape decision-making, largely due to contextual, institutional, and workload-related constraints. The study highlights the importance of understanding leadership as contextually negotiated and relationally enacted. It contributes to African educational leadership research by demonstrating how leadership practices are experienced and interpreted within specific school contexts and emphasising the value of examining leadership beyond a single theoretical model. The implications of these findings for school leadership practice, policy development, and international educational leadership research are discussed. Full article

Winter pruning is a key management practice in viticulture that directly affects vine architecture, yield balance, and grape quality. At the same time, it is a highly labor-intensive operation, and the selective identification of appropriate cutting locations remains one of the main challenges limiting the automation of pruning in vineyards. Advances in machine vision provide new opportunities to support the development of robotic pruning systems. The objective of this study was to develop and evaluate a vision-based method for estimating grapevine pruning points and cutting lines using instance segmentation outputs generated by YOLO models. A dataset of 1500 RGB images of dormant grapevines was collected under field conditions in the Nobilis vineyard located in southeastern Poland. Two annotation strategies were implemented to define pruning regions. YOLO-based instance segmentation models were trained and evaluated for detecting cutting-related structures. Based on the predicted segmentation masks, a geometry-based method termed PCAcutSeg-V was developed to estimate class-dependent cutting points and cutting lines using principal component analysis applied to object contours. The results indicate that YOLOv8 and YOLO11 architectures achieved the highest segmentation performance among the evaluated models. The simplified annotation strategy provided more stable geometric inputs for the PCAcutSeg-V method, enabling more reliable estimation of cutting points and cutting lines compared with the extended annotation approach. When combined with the PCAcutSeg-V method, the proposed perception–geometry pipeline achieved high effectiveness in pruning decision estimation. The method was further implemented in a real-time processing pipeline using an RGB camera and an edge computing platform, where it maintained performance consistent with the results obtained from offline image analysis. These findings demonstrate that combining deep learning-based instance segmentation with deterministic geometric reasoning enables accurate and interpretable estimation of grapevine pruning locations and provides a promising foundation for future autonomous pruning systems. Full article

This study examines workplace bullying within the middle-management tier of a large Gauteng-based retail organisation in South Africa, with a focus on structural organisational pressures and perceptual differences among managers. While traditional research often emphasises individual personality traits or victim demographics, this study explores how organisational conditions—particularly the “middle management squeeze” and performance-driven Key Performance Indicators (KPIs)—are reflected in workplace behaviours. Grounded in a positivist paradigm, a quantitative cross-sectional survey was conducted among a probability-based sample of 253 retail managers. Data were collected using the Negative Acts Questionnaire (NAQ-22) and analysed using Exploratory Factor Analysis (EFA) and nonparametric inferential tests. The findings indicate that task-related negative acts, such as micromanagement (M = 2.00) and persistent monitoring (M = 1.87), are frequently experienced. EFA identified two dimensions—General Harassment and Managerial Control—accounting for 62% of the total variance. Inferential results show that perceptions of General Harassment differ significantly across educational groups (p = 0.0268), whereas perceptions of Managerial Control remain consistent (p = 0.3378). These findings indicate that social forms of incivility are interpreted differently across educational cohorts, while task-related managerial practices are widely normalised. The study highlights the importance of understanding workplace bullying as both a structural and perceptual phenomenon and underscores the need for organisational interventions that address systemic pressures rather than relying solely on individual-level approaches. Full article