Search Results (596)

This entry explores the multifaceted intersections of gender and digital technologies, offering a comprehensive analysis of how structural inequalities are reproduced, contested, and transformed in digital contexts. It is structured into six interrelated sections that collectively address key dimensions of gendered digital contexts. It begins by addressing the gender digital divide, particularly in the Global South, emphasizing disparities in access, literacy, and sociocultural constraints. The second section examines gendered labor in the tech industry, highlighting persistent inequalities in Science, Technology, Engineering, and Mathematics (STEM) education, employment, and platform-based work. The third part focuses on gender representation in digital spaces, revealing how algorithmic and platform design perpetuate biases. The fourth section discusses gender bias in AI and disinformation, underscoring the systemic nature of digital inequalities. This is followed by an analysis of online gender-based violence, particularly its impact on marginalized communities and participation in digital life. The final section considers the potentials and limitations of digital activism in advancing gender justice. These sections collectively argue for an intersectional, inclusive, and justice-oriented approach to technology policy and design, calling for coordinated global efforts to create equitable digital futures. Full article

Introduction: Obstructive sleep apnea syndrome (OSAS) is caused by anatomical and non-anatomical factors which lead to upper airway (UA) obstruction during sleep. Intrinsic UA collapse is the most frequent determinant of OSA. In the era of personalized medicine, adopting a tailored diagnostic approach is essential to rule out secondary causes of UA collapse, particularly those stemming from extrinsic anatomical factors. Although being rarely considered in the differential diagnosis, space-occupying lesions of deep cervical spaces such as the parapharyngeal space (PPS) may be responsible for airway obstruction and lead to OSAS. Objective: This study aimed to present an atypical case of OSAS caused by extrinsic PPS compression, outlining the relevance of modern personalized medicine in the diagnostic and therapeutic protocols, and to enhance understanding through a comprehensive literature review. Methods: A 60-year-old female presented with sleep-disordered complaints and was diagnosed with severe OSAS after polysomnography. At physical examination, a swelling of the right posterior oropharyngeal mucosa was noticed. Imaging confirmed the suspicion of a PPS tumor, and transcervical resection was planned. Case presentation was adherent to the CARE checklist. A comprehensive literature review was conducted using the most reliable scientific databases. Results: Surgery was uneventful, and the patient made a full recovery. The histopathology report was consistent with the diagnosis of pleomorphic adenoma. Postoperative outcomes showed marked improvement in polysomnographic parameters and symptom burden. Conclusions: Parapharyngeal space tumors are a rare, often overlooked cause of OSA. This case highlights the role of a personalized head and neck assessment in OSA patients, particularly in identifying structural causes and offering definitive surgical management when indicated. Full article

Real-time positioning is a technological field with a multitude of applications, which expand across many scopes: from positioning within a large area to localization within smaller spaces; from locating people to locating equipment; from large-scale industrial or military applications to commercially available solutions. There are at least as many implementations of real-time positioning as there are applications and challenges. Within the domain of Radio Frequency (RF) systems, positioning has been approached from multiple angles. Some of the more common solutions involve using Time of Flight (ToF) and time difference of arrival (TDoA) technologies. Within TDoA-based systems, one common limitation stems from the computational power necessary to run the multi-lateration algorithms at a high enough speed to provide high-frequency refresh rates on the tag positions. The system presented in this study implements a complete hardware and software TDoA-based real-time positioning system, using wireless Ultra-Wideband (UWB) technology. This system demonstrates improvements in the state of the art by addressing the above limitations through the use of a hybrid Machine Learning solution combined with algorithmic fine tuning in order to reduce computational power while achieving the desired positioning accuracy. This study presents the design, implementation, verification and validation of the aforementioned system, as well as an overview of similar solutions. Full article

Blasting is one of the most widely used and cost-effective techniques for rock excavation and fragmentation in open-pit mining, particularly for large-scale operations. However, repeated or poorly controlled blasting can generate excessive ground vibrations that threaten slope stability by causing structural damage, fracturing of the rock mass, and potential failure. Evaluating the effects of blast-induced vibrations is essential to ensure safe and sustainable mining operations. This study investigates the impact of blasting-induced vibrations on slope stability at the Saindak Copper-Gold Open-Pit Mine in Pakistan. A comprehensive dataset was compiled, including field-monitored ground vibration measurements—specifically peak particle velocity (PPV) and key blast design parameters such as spacing (S), burden (B), stemming length (SL), maximum charge per delay (MCPD), and distance from the blast point (D). Geomechanical properties of slope-forming rock units were validated through laboratory testing. Slope stability was analyzed using pseudo-static limit equilibrium methods (LEMs) based on the Mohr–Coulomb failure criterion, employing four approaches: Fellenius, Janbu, Bishop, and Spencer. Pearson and Spearman correlation analyses quantified the influence of blasting parameters on slope behavior, and sensitivity analysis determined the cumulative distribution of slope failure and dynamic response under increasing seismic loads. FoS values were calculated for both east and west pit slopes under static and dynamic conditions. Among all methods, Spencer consistently yielded the highest FoS values. Under static conditions, FoS was 1.502 for the east slope and 1.254 for the west. Under dynamic loading, FoS declined to 1.308 and 1.102, reductions of 12.9% and 11.3%, respectively, as calculated using the Spencer method. The east slope exhibited greater stability due to its gentler angle. Correlation analysis revealed that burden had a significant negative impact (r = −0.81) on stability. Sensitivity analysis showed that stability deteriorates notably when PPV exceeds 10.9 mm/s. Although daily blasting did not critically compromise stability, the west slope showed greater vulnerability, underscoring the need for stricter control of blasting energy to mitigate vibration-induced instability and promote long-term operational sustainability. Full article

In the present study, three-dimensional turbulent, subcritical open-channel flow (Fr = 0.19) through submerged rigid vegetation is numerically investigated using the ANSYS FLUENT solver (v. 22. 1). The Volume of Fluid (VOF) method is applied for free-surface tracking, while the standard k-ε turbulence model is employed for turbulence closure. Vegetation is modeled as vertical rigid cylinders fixed at the bottom of the channel. Regarding the arrangement of the stems, two cases are examined. In the first case, a linear arrangement of three equally spaced vegetative stems is located transversely at the center of the channel, while in the second case, a parallel arrangement of fifteen equidistant vegetative stems is located downstream of the channel center. In both cases, the vertical velocity profile within the submerged vegetation layer deviates significantly from that of the upper non-vegetated layer, which generally adheres to the logarithmic velocity distribution. In the second case, flow field repeatability is observed after the third stem series, particularly in terms of velocity profiles. Additionally, the structure of turbulence is noticeably affected in the vicinity of the stems, resulting in higher eddy viscosity values near each stem’s crest area. Furthermore, a localized drop in the free surface is recorded above the vegetated region, while a slight rise is observed upstream of each stem series, consistent with subcritical open-channel flow. Full article

The distinctive leaf and twig heteromorphism in Euphrates poplar (Populus euphratica Oliv.) reflects its adaptive strategies to cope with arid environments across ontogenetic stages. In the key distribution area of P. euphratica forests in China, we sampled P. euphratica twigs (which grow in the current year) at different age classes (1-, 3-, 5-, 8-, and 11-year-old trees), then analyzed their morphological traits, biomass allocation, as well as allometric relationships. Results revealed significant ontogenetic shifts: seedlings prioritized vertical growth by lengthening stems (32.06 ± 10.28 cm in 1-year-olds) and increasing stem biomass allocation (0.36 ± 0.14 g), while subadult trees developed shorter stems (6.80 ± 2.42 cm in 11-year-olds) with increasesd petiole length (2.997 ± 0.63 cm) and lamina biomass (1.035 ± 0.406 g). Variance partitioning showed that 93%–99% of the trait variation originated from age and individual differences. Standardized major axis analysis demonstrated a consistent “diminishing returns” allometry in biomass allocation (lamina–stem slope = 0.737, lamina–petiole slope = 0.827), with age-modulated intercepts reflecting developmental adjustments. These patterns revealed an evolutionary trade-off strategy where subadult trees optimized photosynthetic efficiency through compact architecture and enhanced hydraulic safety, while seedlings prioritized vertical space occupation. Our findings revealed that heteromorphic twigs play a pivotal role in modular trait coordination, providing mechanistic insights into P. euphratica’s adaptation to extreme aridity throughout its lifespan. Full article

Sport can serve as a powerful tool for community building, fostering inclusion, challenging intolerance, and advancing social justice. It also supports positive youth development and active citizenship. When embedded in local life and accessible beyond athletics, sport creates unique conditions for community development and inclusive action. Sport and equity-focused community development are about relationships. The perspectives and behaviors stemming from youth participation in sport—what they learn about human relationships, relationship building, and life skills—carry forward through time in all phases and facets of their lives. The Gaelic Athletic Association (GAA), Ireland’s largest amateur sporting and cultural organization, exemplifies this potential. More than a sports organization, the GAA plays a central role in Irish society, offering opportunities for people of all ages to engage in sport, fitness, and well-being, while actively contributing to community life. GAA clubs often function as local social hubs, creating spaces for connection across generations. This article uses the GAA as a case study to explore how sport can be a unifying and inclusive structure for community building. Specifically, we will (1) examine the link between sport, youth, and active citizenship; (2) explore connections between sport, community, inclusion, and social justice; (3) offer a historical and cultural overview of the GAA; and (4) consider how organizations like the GAA can support efforts around inclusion, tolerance, and sustainability. The discussion will highlight implications for future community programming and policy. Full article

Urban vitality, a critical emergent property of complex urban systems, is pivotal for sustainable, human-oriented urbanization. While land use mix (LUM) is recognized as a key strategy for shaping these systems, the systemic mechanisms through which its multifaceted dimensions influence urban vitality across spatio-temporal scales remain underexplored. This study examines the complex and spatially heterogeneous impacts of land use mix on 24 h urban vitality in Ningbo, China, conceptualizing the city as a dynamic socio-spatial system. By integrating multi-source data (Baidu Maps, POI, and OSM) and employing OLS and geographically weighted regression (GWR) models, we unravel these systemic relationships. Key findings include the following: (1) LUM significantly enhances urban vitality, acting as a crucial urban system configuration for both daytime and nighttime activity. (2) The efficacy of LUM stems more from systemic interconnections—convenient access to adjacent spaces (proximity) and functional coordination among diverse land uses—than mere compositional diversity, emphasizing the importance of interrelated elements within the urban fabric. (3) The system’s response to LUM exhibits significant spatial and temporal heterogeneity; proximity’s impact is most variable, while diversity and coordination effects are more stable, underscoring the dynamic and context-dependent nature of these interactions. (4) System-adaptive strategies are crucial: newly developed urban areas benefit from foundational infrastructure and land use diversity (system inputs), while revitalizing older towns requires optimizing spatial accessibility and functional coordination (enhancing existing system linkages). These findings advance the theoretical systems-based theoretical understanding of the LUM–vitality nexus while offering practical insights for urban planners and policymakers. Full article

This article stems from the PRIN GOV_REL (Urban Governance of Interreligious Dialogue) research project carried out in four Italian cities in 2023–2025 and reports on some preliminary results of the empirical enquiry held in the city of Brescia. The Brescia area is characterised by high rates of residents with an immigrant background and a consolidated presence of religious minorities (Muslim, Orthodox, Sikh, Hindu and Protestant groups), many recognised centres (mosques, temples and Christian non-Catholic churches) and a significant commitment of ethnic–religious communities to local public life. This paper examines the creation of grassroots-level interreligious dialogue, seen as a communicative process. The empirical evidence is based on material collected by participant observations and semi-structured interviews regarding four initiatives that occurred in 2024. A sociocultural analysis outlines the communicative frame: text; context; aims; acts; interlocutors and their power/freedom of expression; interactions; results. The article examines the communicative pattern of each initiative, considering an intercultural orientation and a pluralistic model of interfaith dialogue. It seeks to answer the following questions: what was the fundamental message that the promoters wanted to convey? How do the single actors communicate their perspective of religious “others”, and what results did they achieve or not achieve? The analysis leads to identifying the patterns that facilitate and/or hamper dialogue, taking into account misunderstandings and “cul-de-sac” aspects. Final recommendations highlight the recurrent breaking points that should be prevented and some premises to guarantee successful communication between members of different religions in multicultural urban spaces. Full article

Forest fire detection is vital for ecological conservation and disaster management. Existing visual detection methods exhibit instability in smoke-obscured or illumination-variable environments. Although multimodal fusion has demonstrated potential, effectively resolving inconsistencies in smoke features across diverse modalities remains a significant challenge. This issue stems from the inherent ambiguity between regions characterized by high temperatures in infrared imagery and those with elevated brightness levels in visible-light imaging systems. In this paper, we propose MCDet, an RGB-T forest fire detection framework incorporating target-aware fusion. To alleviate feature cross-modal ambiguity, we design a Multidimensional Representation Collaborative Fusion module (MRCF), which constructs global feature interactions via a state-space model and enhances local detail perception through deformable convolution. Then, a content-guided attention network (CGAN) is introduced to aggregate multidimensional features by dynamic gating mechanism. Building upon this foundation, the integration of WIoU further suppresses vegetation occlusion and illumination interference on a holistic level, thereby reducing the false detection rate. Evaluated on three forest fire datasets and one pedestrian dataset, MCDet achieves a mean detection accuracy of 77.5%, surpassing advanced methods. This performance makes MCDet a practical solution to enhance early warning system reliability. Full article

Cell technologies have provided promising tools for modulating the properties of multipotent mesenchymal stem/stromal cells (MSCs) to meet the needs of cell therapy as well as tissue engineering and regenerative medicine (TERM). Ex vivo preconditioning is directed at enhancing the engraftment of MSCs and activating their secretory activity, primarily the production of soluble mediators. The present review aims to highlight the underestimated effect of the most accepted preconditioning approaches on the modification of the important set of insoluble molecules secreted by MSCs into extracellular space—the extracellular matrix (ECM). A thorough review of the published literature was performed, with particular emphasis on ECM-related data. The analysis of data on ECM changes showed that most of the applied preconditioning methods—hypoxia, inflammatory priming, pharmacological agents, 3D culture, and scaffolds—generally stimulate ECM production, increase the deposition of growth factors, promote alignment, and increase ECM stiffness. There are already preliminary results demonstrating the successful application of preconditioned ECM for promoting angiogenesis, targeted stromal lineage differentiation, and other therapeutic goals. The prospects for further research in this area are discussed. Full article

Human immunodeficiency virus (HIV) continues to be a threat to public health. An emerging technique with promise in the context of fighting HIV type 1 (HIV-1) focuses on targeting ribosomal frameshifting. A crucial –1 programmed ribosomal frameshift (PRF) has been observed in several pathogenic viruses, including HIV-1. Altered folds of the HIV-1 RNA frameshift element (FSE) have been shown to alter frameshifting efficiency. Here, we use RNA-As-Graphs (RAG), a graph-theory based framework for representing and analyzing RNA secondary structures, to perform conformational analysis in motif space to propose how sequence length may influence folding patterns. This combined analysis, along with all-atom modeling and experimental testing of our designed mutants, has already proven valuable for the SARS-CoV-2 FSE. As a first step to launching the same computational/experimental approach for HIV-1, we compare prior experiments and perform SHAPE-guided 2D-fold predictions for the HIV-1 FSE embedded in increasing sequence contexts and predict structure-altering mutations. We find a highly stable upper stem and highly flexible lower stem for the core FSE, with a three-way junction connecting to other motifs at increasing lengths. In particular, we find little support for a pseudoknot or triplex interaction in the core FSE, although pseudoknots can form separately as a connective motif at longer sequences. We also identify sensitive residues in the upper stem and central loop that, when minimally mutated, alter the core stem loop folding. These insights into the FSE fold and structure-altering mutations can be further pursued by all-atom simulations and experimental testing to advance the mechanistic understanding and therapeutic strategies for HIV-1. Full article

In this study, we model a solution surface, with each point having nine components using artificial intelligence (AI), to optimise the effects of ground vibration during blasting operations in an open-pit diamond mine. This model has eight input parameters that can be adjusted by blasting engineers to arrive at a desired output value of ground vibration. It is built using the best performing artificial neural network architecture that best fits the blasting data from 100 blasting events provided by the Debswana diamond mine. Other AI algorithms used to compare the model’s performance were the k-nearest neighbour, support vector machine, and random forest—together with more traditional statistical approaches, i.e., multivariate and regression analyses. The input parameters were burden, spacing, stemming length, hole depth, hole diameter, distance from the blast face to the monitoring point, maximum charge per delay, and powder factor. The optimised model allows for variations in the input values, given the constraints, such that the output ground vibration will be within the minimum acceptable value. Through unconstrained optimisation, the minimum value of ground vibration is around 0.1 mm/s, which is within the vibration range caused by a passing vehicle. Full article

When education in STEM, social science, and the humanities are disconnected from each other and from place, it is inauthentic and nonresponsive to the lived experiences of people and communities. In rural spaces, the Food–Energy–Water (FEW) Nexus, a framework for problem solving and decision-making around these central resources, is salient because of the concentration of FEW resource production and extraction present. Storying the FEW Nexus is an interdisciplinary pedagogical framework that is theoretically rooted in a critical pedagogy of place and socio-ecological systems. Storying the FEW Nexus brings together these two related but distinct frameworks, calling attention to the need for relevant, place-based, and rural-focused narratives within STEM instruction. Developed for K-12 learners in rural places, Storying the FEW Nexus positions STEM knowledge and skills as resources that, alongside local narratives, are vital to the sustainability and viability of communities with unique and intertwined environmental justice histories and current realities. The FEW Nexus is leveraged to support rural learners in developing sustainable solutions to local socio-ecological systems issues. In this conceptual paper, we review the literature base supporting this integrated approach, describe the framework within the context of these aims, and make suggestions for researchers and practitioners. Full article

Light Detection and Ranging (LiDAR) point clouds are an essential perception modality for artificial intelligence systems like autonomous driving and robotics, where the ubiquity of small objects in real-world scenarios substantially challenges the visual tracking of small targets amidst the vastness of point cloud data. Current methods predominantly focus on developing universal frameworks for general object categories, often sidelining the persistent difficulties associated with small objects. These challenges stem from a scarcity of foreground points and a low tolerance for disturbances. To this end, we propose a deep neural network framework that trains a Siamese network for feature extraction and innovatively incorporates two pivotal modules: the target-awareness prototype mining (TAPM) module and the regional grid subdivision (RGS) module. The TAPM module utilizes the reconstruction mechanism of the masked auto-encoder to distill prototypes within the feature space, thereby enhancing the salience of foreground points and aiding in the precise localization of small objects. To heighten the tolerance of disturbances in feature maps, the RGS module is devised to retrieve detailed features of the search area, capitalizing on Vision Transformer and pixel shuffle technologies. Furthermore, beyond standard experimental configurations, we have meticulously crafted scaling experiments to assess the robustness of various trackers when dealing with small objects. Comprehensive evaluations show our method achieves a mean Success of 64.9% and 60.4% under original and scaled settings, outperforming benchmarks by +3.6% and +5.4%, respectively. Full article