Search Results (225,667)

The power system’s dynamic frequency stability is affected by common-mode ultra-low-frequency oscillation and differential-mode low-frequency oscillation. Traditional frequency control based on generators is facing the problem of capacity reduction. It is urgent to explore new regulation resources such as photovoltaics. To address this issue, this paper proposes a distributed active support method based on photovoltaic systems via state–disturbance observation and dynamic surface consensus control. A three-layer distributed control framework is constructed to suppress low-frequency oscillations and ultra-low-frequency oscillations. To solve the high-order problem of the regional grid model and to obtain its unmeasurable variables, a regional observer estimating both system states and external disturbances is designed. Furthermore, a distributed dynamic frequency stability control method is proposed for wide-area photovoltaic clusters based on the dynamic surface control theory. In addition, the stability of the proposed distributed active support method has been proven. Moreover, a parameter tuning algorithm is proposed based on improved chaos game theory. Finally, simulation results demonstrate that, even under a 0–2.5 s time-varying communication delay, the proposed method can restrict the frequency deviation and the inter-area frequency difference index to 0.17 Hz and 0.014, respectively. Moreover, under weak communication conditions, the controller can also maintain dynamic frequency stability. Compared with centralized control and decentralized control, the proposed method reduces the frequency deviation by 26.1% and 17.1%, respectively, and shortens the settling time by 76.3% and 42.9%, respectively. The proposed method can effectively maintain dynamic frequency stability using photovoltaics, demonstrating excellent application potential in renewable-rich power systems. Full article

Accumulative rolling bonding (ARB) Cu/Nb nanolaminates have been widely observed to exhibit unique and large numbers of interface-based plasticity mechanisms, and these have been associated with the many extraordinary properties of the material system, especially resistances in extreme engineering environments (mechanical/pressure, thermal, irradiation, etc.) and ability to self-heal defects (microstructural, as well as radiation-induced). Recently, anisotropy in the interface shearing mechanisms in the material system has been observed and much discussed. The Cu/Nb nanolaminates appear to shear on the interface planes to a much larger extent in the transverse direction (TD) than in the rolling direction (RD). Related to that, in this present study we observe interface rotation in Cu/Nb ARB nanolaminates under constrained and unconstrained loading conditions. Although the primary driving force for interface shearing was expected only in the RD, additional shearing in the TD was observed. This is significant as it represents an interface rotation, while there was no external rotational driving force. First, we observed interface rotation in in situ rectangular micropillar compression experiments, where the interface is simply sheared in one particular direction only, i.e., in the RD. This is rather unexpected as, in rectangular micropillar compression, there is no possibility of extra shearing or driving force in the perpendicular direction due to the loading conditions. This motivated us to subsequently perform in situ microbeam bending experiments (microbeam with a pre-made notch) to verify if similar interface rotation could also be observed in other loading modes. In the beam bending mode, the notch area was primarily under tensile stress in the direction of the beam longitudinal axis, with interfacial shear also in the same direction. Hence, we expect interface shearing only in that direction. We then found that interface rotation was also evident and repeatable under certain circumstances, such as under an offset loading. As this behaviour was consistently observed under two distinct loading modes, we propose that it is an intrinsic characteristic of Cu/Nb interfaces (or FCC/BCC interfaces with specific orientation relationships). This interface rotation represents another interface-based or interface-mediated plasticity mechanism at the nanoscale with important potential implications especially for design of metallic thin films with extreme stretchability and other emerging applications. Full article

Urban expansion alters environmental conditions, influencing tree physiology and performance. Urban trees provide cooling, sequester carbon, support biodiversity, filter contaminants, and enhance human health. This study examines how two common urban trees—Norway Maple (Acer platanoides L.) and Little-leaved Linden (Tilia cordata Mill.)—respond to urban site conditions by assessing leaf morphology, stomatal, and gas exchange traits across street and urban park sites in Chicago, IL. Street trees exhibited structural trait adjustments, including smaller leaf area, reduced specific leaf area, and increased stomatal density, potentially reflecting acclimation to more compact and impervious conditions. Norway Maple showed stable photosynthetic assimilation (A), stomatal conductance (g_s), and transpiration (E) across sites, alongside higher intrinsic water-use efficiency (_iWUE), indicating a conservative water-use strategy. In contrast, Little-leaved Linden maintained A and g_s but showed elevated E and _iWUE at street sites, suggesting adaptive shifts in water-use dynamics under street microenvironments. These findings highlight how species-specific physiological strategies and local site conditions interact to shape tree function in cities and underscore the importance of incorporating functional traits into urban forestry planning to improve ecosystem services and climate resilience. Full article

To fabricate thermoelectric generators (TEGs) with high mechanical strength using single-walled carbon nanotubes (SWCNTs), we combined SWCNTs, poly(3, 4-ethylenedioxythiophene):poly(4-styrenesulfonate) (PEDOT:PSS), and sodium alginate (SA) to synthesize flexible SWCNT/PEDOT:PSS/SA composite yarns via wet spinning. The composite yarns were flexible and dense, with a diameter of approximately 290 µm. Their tensile strength and breaking strain were 151 MPa and 12.7%, respectively, which were approximately 10 and 4 times those of the SWCNT films. However, the thermoelectric properties of the composite yarns were inferior to those of the SWCNT films. The temperature distribution and output voltage of the fabricated TEG with composite yarns were measured at a heater temperature of 100 °C. The temperature difference generated by the TEG with composite yarns was approximately 75% of that generated by the TEG with SWCNT films because the composite yarn had a smaller specific surface area. The output voltage of the TEG with two composite yarns (0.21 mV) was lower than that of the TEG with two SWCNT films. However, arranging the composite yarns at a high density resulted in an output voltage exceeding that for the TEGs with SWCNT films. These findings are highly beneficial for yarn-based TEGs used in wearable sensors. Full article

Urban roof segmentation plays a pivotal role in applications such as urban planning, infrastructure management, and renewable energy deployment. This study explores the evolution of deep learning techniques from traditional Convolutional Neural Networks (CNNs) to cutting-edge transformer-based models in the context of roof segmentation from satellite imagery. We highlight the limitations of conventional methods when applied to urban environments, including resolution constraints and the complexity of roof structures. To address these challenges, we evaluate two advanced deep learning models, Mask R-CNN and MaskFormer, which have shown significant promise in accurately segmenting roofs, even in dense urban settings with diverse roof geometries. These models, especially the one based on transformers, offer improved segmentation accuracy by capturing both global and local image features, enhancing their performance in tasks where fine detail and contextual awareness are critical. A case study on Ben Guerir City in Morocco, an urban area experiencing rapid development, serves as the foundation for testing these models. Using high-resolution satellite imagery, the segmentation results offer a deeper understanding of the accuracy and effectiveness of these models, particularly in optimizing urban planning and renewable energy assessments. Quantitative metrics such as Intersection over Union (IoU), precision, recall, and F1-score are used to benchmark model performance. Mask R-CNN achieved a mean IoU of 74.6%, precision of 81.3%, recall of 78.9%, and F1-score of 80.1%, while MaskFormer reached a mean IoU of 79.8%, precision of 85.6%, recall of 82.7%, and F1-score of 84.1% (pixel-level, micro-averaged at IoU = 0.50 on the held-out test set), highlighting the transformative potential of transformer-based architectures for scalable and precise urban imaging. The study also outlines future work in 3D modeling and height estimation, positioning these advancements as critical tools for sustainable urban development. Full article

The endometrium is a highly dynamic tissue central to female reproductive function, undergoing nearly 500 cycles of proliferation, differentiation, shedding, and regeneration throughout a woman’s reproductive life. This remarkable regenerative capacity is driven by a reservoir of endometrial stem/progenitor cells (ESCs), which are crucial for maintaining tissue homeostasis. Dysregulation of these cells is linked to a variety of clinical disorders, including menstrual abnormalities, infertility, recurrent pregnancy loss, and serious gynecological conditions such as endometriosis and endometrial cancer. Recent advancements in organoid technology and lineage-tracing models have provided insights into the complex cellular hierarchy that underlies endometrial regeneration and differentiation. This review highlights the latest breakthroughs in endometrial stem cell biology, focusing particularly on 3D in vitro platforms that replicate endometrial physiology and disease states. By integrating these cutting-edge approaches, we aim to offer new perspectives on the pathogenesis of endometrial disorders and establish a comprehensive framework for developing precision regenerative therapies. Full article

Background and Objectives: Circadian fluctuations in blood pressure, particularly the non-dipping pattern characterized by the absence of a nocturnal decline, are associated with an increased risk of microvascular complications. The retina, as a highly sensitive microvascular tissue, offers a valuable window into systemic hemodynamic alterations. However, the literature lacks detailed structural analyses that evaluate all retinal regions by segmenting nighttime into specific time intervals. Notably, the early morning period (04:00–08:00), during which stress hormones such as cortisol and catecholamines rise physiologically, leads to increased blood pressure that may significantly affect retinal microcirculation. This prospective study aims to assess retinal microvascular structures in dipper and non-dipper individuals using structural optical coherence tomography and to investigate their relationship with blood pressure parameters by dividing nighttime into distinct time segments. Materials and Methods: A total of 60 participants were classified as dipper (n = 26) or non-dipper (n = 34) based on 24 h ambulatory blood pressure monitoring results. Structural optical coherence tomography was used to evaluate superficial and deep capillary plexus densities in the foveal, parafoveal, and perifoveal regions, along with the area and perimeter of the foveal avascular zone (FAZ) and flow density (FD). Blood pressure values, including systolic, diastolic, mean arterial, and pulse pressure, were recorded during two nighttime intervals (00:00–04:00 and 04:00–08:00), and correlations with retinal parameters were analyzed. Results: No significant differences were observed in retinal microvascular parameters between the dipper and non-dipper groups. Deep capillary densities, particularly in the parafoveal and perifoveal regions, showed significant positive correlations with serum total protein, albumin, and very low-density lipoprotein (VLDL) levels. Furthermore, systolic and mean arterial pressures measured during the 04:00–08:00 interval demonstrated significant positive correlations with deep retinal vascular densities. The FAZ perimeter was negatively correlated with pulse pressure variability, while FD showed a negative correlation with mean arterial pressure variability. Conclusions: This prospective study is among the first to investigate the effects of circadian blood pressure patterns on retinal microvascular structures by segmenting nighttime into specific intervals and employing comprehensive structural optical coherence tomography across the entire retina. The findings suggest that retinal microvascular structure may be associated with fluctuations in blood pressure. Analyses of blood pressure measurements between 04:00 and 08:00 may offer supplementary insights into the evaluation of retinal microvascular structure. Full article

The sustainability of Arctic ecosystems that are extremely vulnerable is contingent upon the state of cryosoils. Understanding the principles of ecosystem stability in permafrost conditions, particularly under external natural or human-induced influences, necessitates an examination of the thermal and moisture regimes of the seasonally thawed soil layer. The study concentrated on the variability in the soil’s thermophysical properties in Central Siberia’s permafrost zone (the northern part of Krasnoyarsk Region, Taimyr, Russia). In the industrially affected area of interest, we evaluated and contrasted the differences in the thermophysical properties of soils between two opposing types of landscapes. On the one hand, these are soils that are characteristic of the natural landscape of flat shrub tundra, with a well-developed moss–lichen cover. An alternative is the soils in the landscape, which have exhibited significant degradation in the vegetation cover due to both natural and human-induced factors. The heat-insulating properties of background areas are controlled by the layer of moss and shrubs, while its disturbance determines the excessive heating of the soil at depth. In comparison to the background soil characteristics, degradation of on-ground vegetation causes the active layer depth of the soils to double and the temperature gradient to decrease. With respect to depth, we examine the changes in soil temperature and heat flow dynamics (q, W/m²). The ranges of thermal conductivity (λ, W/(m∙K)) were assessed using field-measured temperature profiles and heat flux values in the soil layers. The background soil was discovered to have lower thermal conductivity values, which are typical of organic matter, in comparison to the soil of the transformed landscape. Thermal diffusivity coefficients for soil layers were calculated using long-term temperature monitoring data. It is shown that it is possible to use an adjusted model of the thermal conductivity coefficient to reconstruct the dynamics of moisture content from temperature dynamics data. A satisfactory agreement is shown when the estimated ($W_{calc}$, %) and observed ($W_{exp}$, %) moisture content values in the soil layer are compared. The findings will be employed to regulate the effects on landscapes in order to implement sustainable nature management in the region, thereby preventing the significant degradation of ecosystems and the concomitant risks to human well-being. Full article

Fatigue damage of yawed wind turbine components can be caused by repeated long-term unsteady asymmetric inflow loads across the rotor swept area, necessitating fatigue load analysis to ensure the in-operation safety of wind turbines. This study investigates the impact of geometric nonlinearity on the fatigue loads of wind turbine components. The geometrically exact beam theory (GEBT), implemented in BeamDyn of OpenFAST, is employed to model full geometric nonlinearity. For comparison, ElastoDyn in OpenFAST, which uses the generalized Euler–Bernoulli beam theory for straight isotropic beams, is also utilized. Aeroelastic simulations were conducted for the national renewable energy laboratory (NREL 5 MW) and international energy agency (IEA) 15 MW wind turbines. Fatigue loads, quantified by the damage equivalent load (DEL) based on Palmgren–Miner’s rule, were analyzed for critical components, including blade out-of-plane (OOP) moments, low-speed shaft (LSS) torque, LSS bending moment (LSSBM), and tower base bending moment (TBBM). Results indicate that geometric nonlinearity significantly influences fatigue damage in critical turbine components, with significant differences observed between BeamDyn and ElastoDyn simulations. Full article

The study provides valuable insights into the sustainable utilization of edible tuber peels from the high mountains of the Argentinian Puna, which constitutes promising reserves of bioactive phenolic compounds with the potential to enhance the biofunctional properties of lactic acid bacteria. Thirty-two extracts derived from peels of different varieties of tubers, such as Oxalis tuberosa Mol., Ullucus tuberosus Caldas, and Solanum tuberosum L. were incorporated into lactobacilli cultures and individually evaluated. These selectively enhance the development of the probiotic strain Lactiplantibacillus plantarum ATCC 10241 and of Lacticaseibacillus paracasei CO1-LVP105 from ovine origin, without promoting the growth of a pathogenic bacteria set (Escherichia coli O157:H12 and ATCC 35218, Salmonella enterica serovar Typhimurium ATCC 14028, and S. corvalis SF2 and S. cerro SF16), in small amounts. To determine the main phenolic group concentrated in the phytoextracts, a bio-guided study was conducted. The most significant results were obtained by O. tuberosa phytochemicals added to the culture medium at 50 µg/mL, yielding promising increases in biofilm formation (78% for Lp. plantarum and 43% for L. paracasei) and biosurfactant activity (112% for CO1-LVP105 strain). These adaptive strategies developed by bacteria possess key biotechnological significance. Furthermore, the bio-detoxification capacity of phenol and o-phenyl phenol, particularly of the novel strain CO1-LVP105, along with its mode of action and genetic identification, is described for the first time to our knowledge. In conclusion, lactobacilli strains have potential as fermentation starters and natural products, recovered from O. tuberosa peels, and added into culture media contribute to multiple bacterial biotechnological applications in both health and the environment. Full article

The critically endangered African wild ass is found in low population densities and there may be as few as 600 individuals in the Danakil Desert of Ethiopia and Eritrea. An understanding of suitable habitats is important for prioritizing the conservation and management of the African wild ass. In this study, we recorded presence locations of the African wild ass and independently prepared environmental covariates to identify suitable habitats using the maximum entropy (Maxent) model. Model performances were high, with the area under the curve (AUC) values of 0.927 and 0.950 for wet and dry seasons, respectively. The predicted moderately suitable habitat area extent was greater during the wet season (15,223 km²) than during the dry season (6052 km²). Precipitation, temperature, and distance from water sources were vital variables for the wet season, while distance from water sources and distance from the settlements were important determinant covariates for the dry season. This information prioritizes where protected areas should be established for African wild ass conservation and also indicates potential new undocumented locations to guide surveys in the Danakil Desert of the Afar Region, Ethiopia. Full article

There is little research exploring the grey area of sexual violence (SV), considered in the literature as being a more subtle manifestation of SV, and therefore tending to be trivialized, legitimized, and normalized by society. This study aimed to compare students’ perceptions of the grey area of SV based on the gender of those involved, in a cis-hetero context, as well as potential sex differences in these perceptions. A vignette methodology was employed to gain valuable insights into the topic. The sample consisted of 164 university students living in Portugal, 71.3% (n = 117) female, with an average age of 23 (SD = 5.84). The thematic analysis revealed a central theme, Severity, reflecting participants’ perceptions of the seriousness of sexual violence within the “grey area”. This theme is expressed through four sub-themes: Attribution of severity, referring to how seriousness is assigned depending on context and beliefs; Identifying sexual violence, highlighting difficulties in recognizing certain behaviors as abusive; Frequency, capturing perceptions of how often such situations occur; and Report, addressing the barriers and facilitators to formal reporting. Our results indicated that while some participants minimized the scenario, the majority of the sample considered the situation as somewhat or very serious. Only few participants trivialized subtle forms of SV, perceiving incidents without overt physical force as less severe. Notably, sex differences emerged, despite being in the minority of the sample, female participants were more inclined to recognize these behaviors as abusive and to view the allegations as credible, whereas male participants tended to downplay the severity. Full article

Purpose: To investigate regional changes in tear film quality associated with orthokeratology (Ortho-K) lens wear using high-resolution spatial mapping and to evaluate the potential of artificial intelligence (AI) models in anticipating these changes. Methods: This study analysed tear film quality in 92 Ortho-K wearers divided into three groups based on lens wear duration (10–29 days, 30–90 days, and ≥91 days). Placido-based topographer measurement was used to generate regional tear film maps before and after treatment. A custom MATLAB pipeline enabled regional comparisons and statistical mapping. A feedforward neural network was trained to forecast local tear film quality using spatial data. Results: Single-value global mean metrics showed minimal changes in tear film quality across groups. However, regional mean mapping revealed significant mid-peripheral and peripheral deterioration over time, particularly in nasal and temporal corneal zones. These changes were often overlooked by global averaging and remained invisible through tear film breakup time (TBUT) measurements. The AI model predicted spatial tear quality with high accuracy (R ≥ 0.9 in testing), capturing nuanced regional variations. Conclusions: The regional analysis uncovers subtle, clinically relevant tear film disruptions caused by Ortho-K lens wear, particularly in peripheral areas. These insights challenge the adequacy of traditional single-value global mean assessments. The AI model demonstrates the potential for non-invasive, predictive evaluation of tear stability, supporting more personalised and effective Ortho-K care. Full article

This study examines the ethical problems of using artificial intelligence (AI) applications in higher education, focusing on activities performed by university educators. Drawing on Slovak legislation that defines educators’ responsibilities, the study classifies their activities into three categories: teaching, scientific research, and other (academic management and self-directed professional development). From standpoint of methodology, a thematic review of 42 open-access, peer-reviewed articles published between 2022 and 2025 was conducted across the Web of Science and Scopus databases. Relevant AI applications and their associated ethical issues were identified and thematically categorized. Results of this study show that AI applications are extensively used across all analysed areas of university educators’ activities. Most notably used are applications that are generative language models, editing and paraphrasing tools, learning and assessment software, management and search tools, visualizing and design tools, and analysis and management systems. Their adoption raises ethical concerns which can be thematically grouped into six categories: privacy and data protection, bias and fairness, transparency and accountability, autonomy and oversight, governance gaps, and integrity and plagiarism. The results provide universities with a structured analytical framework to assess and address ethical risks related to AI use in specific academic activities. Although the study is limited to open-access literature, it offers a conceptual foundation for future empirical research and the development of ethical, institutionally grounded AI policies in higher education. Full article

This study explores the potential of Digital Earth Africa (DE Africa) coastlines products for assessing the Coastal Vulnerability Index (CVI) along the Casablanca coastline, Morocco. The analysis integrates remotely sensed shoreline data with elevation, slope, and geomorphological information from ASTER GDEM and geological maps within a GIS environment. Shoreline change metrics, including Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), Linear Regression Rate (LRR), and End Point Rate (EPR), were used to evaluate erosion trends from 2000 to 2023. Results show that sandy beach areas, particularly those below 12 m elevation, are highly exposed to erosion (up to 1.5 m/yr) and vulnerable to coastal hazards. Approximately 44% and 23% of the study area were classified as having very high and high vulnerability, respectively. The results indicate that remotely sensed data and GIS techniques are valuable and cost-effective tools for multi-scale geo-hazard coastal assessment studies. The study demonstrates that DE Africa products, combined with local landscape data, provide a valuable tool for coastal vulnerability assessment and monitoring in Africa. Full article