Search Results (2,630)

The single-crystal diamond (SCD), owing to its extreme physical and chemical properties, serves as an ideal substrate for quantum sensing and high-frequency devices. However, crystal anisotropy imposes significant challenges on fabricating high-quality micro-nano structures, directly impacting device performance. This work investigates the effects of femtosecond laser processing on the SCD under two distinct crystallographic orientations via single-pulse ablation. The results reveal that ablation craters along the <100> orientation exhibit an elliptical shape with the major axis parallel to the laser polarization, whereas those along the <110> orientation form near-circular craters with the major axis at a 45° angle to the polarization. The single-pulse ablation threshold of the SCD along <110> is 9.56 J/cm², representing a 7.8% decrease compared to 10.32 J/cm² for <100>. The graphitization threshold shows a more pronounced reduction, dropping from 4.79 J/cm² to 3.31 J/cm² (31% decrease), accompanied by enhanced sp² carbon order evidenced by the significantly intensified G-band in the Raman spectra. In addition, a phase transition layer of amorphous carbon at the nanoscale in the surface layer (thickness of ~40 nm) and a narrow lattice spacing of 0.36 nm are observed under TEM, corresponding to the interlayer (002) plane of graphite. These observations are attributed to the orientation-dependent energy deposition efficiency. Based on these findings, an optimized crystallographic orientation selection strategy for femtosecond laser processing is proposed to improve the quality of functional micro-nano structures in the SCD. Full article

The planktonic pteropod Limacina helicina is increasingly studied as a bioindicator of climate-driven changes in polar marine ecosystems. Although broadly distributed across the Arctic Basin and the North Pacific, its population structure and dispersal pathways remain poorly understood, especially in the Siberian Arctic. We analyzed mitochondrial COI sequences from populations sampled in the Barents, Kara, Laptev, East Siberian, and White Seas, as well as adjacent Pacific regions. Three major haplogroups (H1, H2, H3) were identified with distinct spatial patterns. H1 is widespread, occurring across the Pacific and most Arctic seas except the White Sea. H2 is confined to the western Arctic shelves (Barents–Kara–Laptev), and H3 is unique to the White Sea. We found a pronounced genetic discontinuity corresponding to hydrographic barriers, particularly the strong freshwater inflow from the Lena River, which restricts eastward dispersal of H2 from the Laptev to the East Siberian Sea. These patterns suggest postglacial expansions from geographically separated populations that survived the Last Glacial Maximum in isolated marine regions. The White Sea population is highly isolated and genetically distinct. Our results highlight how both glacial history and modern oceanography shape Arctic plankton diversity and define biogeographic boundaries in a rapidly changing climate. Full article

Heatwaves intensified by climate change increasingly threaten urban populations, especially the elderly. However, most existing studies have concentrated on short-term or single-scale analyses, lacking a comprehensive understanding of how land cover changes and urbanization affect the vulnerability of the elderly to extreme heat. This study aims to investigate the spatiotemporal distribution patterns of heat-related health risks among the elderly in Nanchang City and to identify their key driving factors within the context of rapid urbanization. This study employs Crichton’s risk triangle framework to the heat-related health risks for the elderly in Nanchang, China, from 2002 to 2020 by integrating meteorological records, land surface temperature, land cover data, and socioeconomic indicators. The model captures the spatiotemporal dynamics of heat hazards, exposure, and vulnerability and identifies the key drivers shaping these patterns. The results show that the heat health risk index has increased significantly over time, with notably higher levels in the urban core compared to those in suburban areas. A 1% rise in impervious surface area corresponds to a 0.31–1.19 increase in the risk index, while a 1% increase in green space leads to a 0.21–1.39 reduction. Vulnerability is particularly high in economically disadvantaged, medically under-served peripheral zones. These findings highlight the need to optimize the spatial distribution of urban green space and control the expansion of impervious surfaces to mitigate urban heat risks. In high-vulnerability areas, improving infrastructure, expanding medical resources, and establishing targeted heat health monitoring and early warning systems are essential to protecting elderly populations. Overall, this study provides a comprehensive framework for assessing urban heat health risks and offers actionable insights into enhancing climate resilience and health risk management in rapidly urbanizing regions. Full article

This study investigates the genetic diversity and population structure of Castanopsis tribuloides, a vital tree species in Asian forest ecosystems. Understanding the genetic patterns of keystone forest species provides critical insights into forest resilience and ecosystem function and informs conservation strategies. We analyzed population samples collected from three distinct locations within Doi Suthep Mountain in northern Thailand using Short Tandem Repeat (STR) markers to assess both intra- and inter-population genetic relationships. DNA was extracted from leaf samples and analyzed using a panel of polymorphic microsatellite loci specifically optimized for Castanopsis species. Statistical analyses included the assessment of forensic parameters (number of alleles, observed and expected heterozygosity, gene diversity, polymorphic information content), population differentiation metrics (G_ST), inbreeding coefficients (F_IS), and gene flow estimates (N_m). We further examined population history through bottleneck analysis using three models (IAM, SMM, and TPM) and visualized genetic relationships through principal coordinate analysis and cluster analysis. Our results revealed significant patterns of genetic structuring across the sampled populations, with genetic distance metrics showing statistically significant differentiation between certain population pairs. The PCA and cluster analyses confirmed distinct population groupings that correspond to geographic distribution patterns. These findings provide the first comprehensive assessment of C. tribuloides population genetics in this region, establishing baseline data for monitoring genetic diversity and informing conservation strategies. This research contributes to our understanding of how landscape features and ecological factors shape genetic diversity patterns in essential forest tree species, with implications for managing forest genetic resources in the face of environmental change. Full article

What elements of nature do people involved in conservation projects seek to protect, and why? How do they identify and relate to nature? Answers to such fundamental questions are shaped by normative assumptions that can result in distinct conservation strategies and practices. Despite their importance, normative assumptions are rarely explicitly stated in conservation sciences, possibly because an epistemology of modern science suggests that normative backgrounds are not relevant to the production of objective knowledge, or because researchers and practitioners are unaware of the diversity of positions that exist. Using a combination of qualitative and quantitative methods, we created a catalogue of existing normative positions in conservation literature and described their key characteristics. We described 72 distinctive normative positions about human–nature relationships. Each position was characterized by unique combinations of value-states belonging to one or more of the following five dimensions: ontology (the positionality of human with respect to nature), axiology (value systems and ethical frameworks), pragmatism (extent of human interventions), epistemology (knowledge sources), and agency (agents of change). We then scored each position in terms of its alignment (support, opposition, or neutrality) with respect to all value-states within each dimension. A fuzzy correspondence analysis revealed that the field of conservation is heterogeneous beyond the conventional gradient of intrinsic–instrumental–relational values. The frequency and circumstances under which stakeholders adopt different normative positions are unknown, but the list of dimensions and associated values provided in this study may serve as a checklist for scoping this diversity. Consideration of values stemming from alternative normative positions may help broaden support for conservation actions. Full article

The experimental tests needed for the estimation of the fatigue limit generally require extensive time and many specimens. A valid but not standardized alternative is the thermographic analysis of the self-heating phenomenon. The present work is aimed at using Infrared thermography to determine the fatigue limit in two kinds of Ti-6Al-4V samples obtained by hot rolling: (1) with the standard dog-bone shape (unnotched specimen) and (2) with two opposed semicircular notches at the sides (notched specimen). Uniaxial tensile experiments are performed on unnotched samples, and the surface temperature variation during loading is monitored. The stress corresponding to the end of the thermoelastic stage gives a rough indication of the fatigue limit. Then, fatigue tests at different sinusoidal loads are performed, and the thermographic signal is monitored and processed. The results obtained using lock-in thermography in dissipative mode, e.g., analyzing the second harmonic, showed a sudden change in slope when the applied stress exceeded a certain limit. This slope change is related to the fatigue limit. In addition, the ratio between the fatigue limits obtained for notched and unnotched specimens, e.g., the fatigue strength reduction factor, is consistent with literature values based on the selected geometry. Full article

This paper investigates the complex relations between the Italian states, particularly Venice and Florence, and France at the beginning (c. 1560–1565) of the French Wars of Religion (c. 1560–1598). Focusing on the early years of the conflict, it highlights the “Italian” perception of France’s politico-religious upheavals and their profound implications for governance and state stability. Drawing on diplomatic correspondence and political reflections, the analysis reveals contrasting approaches among Venetian ambassadors: in particular, Giovanni Michiel advocated conciliatory policies to avert civil war, while Michele Suriano favored uncompromising anti-heresy measures. Niccolò Tornabuoni, serving as the Florentine ambassador in France, evolved from moderate criticism to a rigidly anti-Protestant position, mirroring Cosimo de’ Medici’s shift toward Counter-Reformation policies. This study situates these early reflections within the broader context of Venice’s internal tensions, marked by the diffusion of Reformation ideas and anti-papal currents, and Florence’s strategic alignment with Spain. It also underscores the role of these conflicts in shaping the politico-diplomatic strategies and reinforcing the perceived necessity of religious uniformity as a safeguard against political and social destabilization. The final part is directly linked to the sources and arguments as it contextualizes the diplomatic responses of Venetian and Florentine envoys within the broader political–religious transformations of the period. Full article

In recent years, a long list of relevant studies has highlighted the engagement of the nervous system in the fine-tuning of tumor development and progression. Several authors have shown that different types of nerve fibres (sympathetic, parasympathetic/vagal or somatosensory fibres) may contribute to tumor innervation affecting cancer initiation, progression and metastasis. A large presence of nerve fibres is frequently observed in tumors with respect to the corresponding healthy tissues. In this regard, it is worth noting that in some cases a reduced innervation may associate with slow tumor growth in a tissue-specific manner. Current studies have begun to shed light over the role played in this specific process by Schwann cells (SCs), the most abundant glial cells of the peripheral nervous system. SCs observed in cancer tissues share strong similarities with repair SCs that appear after nerve injury. A large body of research indicates that SCs may have a role in shaping the microenvironment of tumors by regulating the immune response and influencing their invasiveness. In this review, we summarize data relevant to the role of peripheral innervation in general, and of SCs in particular, in defining the progression of different tumors: melanoma that originate in the skin with mainly sensory innervation; pancreatic and liver-derived tumors (e.g., pancreatic adenocarcinoma and cholangiocarcinoma) with mainly autonomous innervation. We conclude by summarizing data regarding hepatocarcinoma (with anatomical predominance of small autonomic nerve fibres) in which the potential relationship between innervation and tumor progression has been little explored, and largely remains to be defined. Full article

This paper presents a formulation for the dynamic analysis of dam–reservoir–foundation systems, employing a coupled finite element model that integrates displacements and reservoir pressures. An innovative coupled approach, without separating the solid and fluid equations, is proposed to directly solve the single non-symmetrical governing equation for the whole system with non-proportional damping. For the modal analysis, a state–space method is adopted to solve the coupled eigenproblem, and complex eigenvalues and eigenvectors are computed, corresponding to non-stationary vibration modes. For the seismic analysis, a time-stepping method is applied to the coupled dynamic equation, and the stress–transfer method is introduced to simulate the nonlinear behavior, innovatively combining a constitutive joint model and a concrete damage model with softening and two independent scalar damage variables (tension and compression). This formulation is implemented in the computer program DamDySSA5.0, developed by the authors. To validate the formulation, this paper provides the experimental and numerical results in the case of the Cahora Bassa dam, instrumented in 2010 with a continuous vibration monitoring system designed by the authors. The good comparison achieved between the monitoring data and the dam–reservoir–foundation model shows that the formulation is suitable for simulating the modal response (natural frequencies and mode shapes) for different reservoir water levels and the seismic response under low-intensity earthquakes, using accelerograms measured at the dam base as input. Additionally, the dam’s nonlinear seismic response is simulated under an artificial accelerogram of increasing intensity, showing the structural effects due to vertical joint movements (release of arch tensions near the crest) and the concrete damage evolution. Full article

Existing methods for detecting cotton boll diseases frequently exhibit high rates of both false negatives and false positives under complex field conditions (e.g., lighting variations, shadows, and occlusions) and struggle to achieve real-time performance on edge devices. To address these limitations, this study proposes an enhanced YOLOv11n model (YOLOv11n-ECS) for improved detection accuracy. A dataset of cotton boll diseases under different lighting conditions and shooting angles in the field was constructed. To mitigate false negatives and false positives encountered by the original YOLOv11n model during detection, the EMA (efficient multi-scale attention) mechanism is introduced to enhance the weights of important features and suppress irrelevant regions, thereby improving the detection accuracy of the model. Partial Convolution (PConv) is incorporated into the C3k2 module to reduce computational redundancy and lower the model’s computational complexity while maintaining high recognition accuracy. Furthermore, to enhance the localization accuracy of diseased bolls, the original CIoU loss is replaced with Shape-IoU. The improved model achieves floating point operations (FLOPs), parameter count, and model size at 96.8%, 96%, and 96.3% of the original YOLOv11n model, respectively. The improved model achieves an mAP@0.5 of 85.6% and an mAP@0.5:0.95 of 62.7%, representing improvements of 2.3 and 1.9 percentage points, respectively, over the baseline YOLOv11n model. Compared with CenterNet, Faster R-CNN, YOLOv8-LSW, MSA-DETR, DMN-YOLO, and YOLOv11n, the improved model shows mAP@0.5 improvements of 25.7, 21.2, 5.5, 4.0, 4.5, and 2.3 percentage points, respectively, along with corresponding mAP@0.5:0.95 increases of 25.6, 25.3, 8.3, 2.8, 1.8, and 1.9 percentage points. Deployed on a Jetson TX2 development board, the model achieves a recognition speed of 56 frames per second (FPS) and an mAP of 84.2%, confirming its suitability for real-time detection. Furthermore, the improved model effectively reduces instances of both false negatives and false positives for diseased cotton bolls while yielding higher detection confidence, thus providing robust technical support for intelligent cotton boll disease detection. Full article

This in vitro study aims to compare the trueness of digital impressions obtained using two intraoral scanners (IOS) and one photogrammetry device for full-arch implant-supported rehabilitations. According to the Caramês Classification I, three models were produced with Straumann implants arranged in different spatial distributions: Option A with six implants and Options B and C with four implants each. The three models were scanned using a 12-megapixel scanner to create digital master casts. For each reference model, 30 digital impressions were acquired: 10 with the 3Shape Trios 3 intraoral scanner, 10 with the Medit i500 intraoral scanner, and 10 with the PIC Dental photogrammetry device. Trueness was assessed through best-fit superimpositions between the digital master casts and the corresponding virtual models. The Shapiro–Wilk test was applied to assess the normality of the data distribution, and Levene’s test was used to evaluate the homogeneity of variances. The non-parametric Kruskal–Wallis test was employed to compare group differences, with post hoc adjustments made using the Bonferroni correction. A significance threshold of p = 0.05 was adopted for all statistical tests. Statistically significant differences were observed in the root mean square values among the three devices. The Medit i500 demonstrated the highest trueness, with a median (interquartile range) deviation of 24.45 (18.18) µm, whereas the PIC Dental exhibited the lowest trueness, with a median deviation of 49.45 (9.17) µm. Among the implant distribution, the Option C showed the best trueness, with a median deviation of 19.00 (27.83). Considering the results of this in vitro study, intraoral scanners demonstrated comparable trueness, whereas the photogrammetry-based system exhibited lower trueness values. Additionally, a smaller number of implants and reduced inter-implant distances were associated with improved trueness in digital impressions for full-arch implant rehabilitation. Full article

The present study adopts the social constructivism theory and consumer decision-making process model with the aim of examining the social identity that consumers build through the purchase of electric vehicles (EVs) in line with their income, age, gender, and education. The study’s findings indicate that this social identity, shaped by income, age, gender and education, exerts a significant influence on consumer decision-making behavior. This identity is shaped not only by the make and model of EVs chosen, but also by their preferences for vehicle performance and technical features. The adoption of EVs by consumers is driven by dual objectives: the fulfilment of practical needs and the shaping of social identities in social interactions that correspond to their income, age, gender, and education. The study’s findings are of significant value in understanding the social identity aspirations of consumers in the electric vehicle consumer market, and provide a theoretical foundation for future electric vehicle companies to create products and corporate cultures that meet their target customers, thereby effectively promoting the popularization of electric vehicles. Full article

We present a novel sketch generation scheme from an image using the flowpath and the value through the flow (VTF). The first stage of our scheme is to produce grayscale noisy sketch using a deep learning-based approach. In the second stage, the unclear contour and unwanted noises in the grayscale noisy sketch are resolved using our flowpath and VTF-based schemes. We build a flowpath by integrating the tangent flow extracted from the input image. The integrated tangent flow produces a strong clue for the salient contour of the shape in the image. We further compute VTF by sampling values through the flowpath to extract line segments that correspond to the sketch stroke. By combining the deep learning-based approach and VTF, we can extract salient sketch strokes from various images that suppresses unwanted noises. We demonstrate the excellence of our scheme by generating sketches from various images including portrait, landscape, objects, animals, and animation scenes. Full article

The article presents a long-term assessment of the surface water quality of six small rivers in the East Kazakhstan region (Breksa, Tikhaya, Ulba, Glubochanka, Krasnoyarka, and Oba) based on hydrochemical monitoring data from the Kazhydromet State Enterprise for the period 2017–2024. A unified water quality classification system was applied, along with statistical methods, including multiple linear regression. The Glubochanka and Krasnoyarka rivers were identified as the most polluted (reaching classes 4–5), with multiple exceedances of Zn (up to 2.96 mg/dm³), Cd (up to 0.8 mg/dm³), and Cu (up to 0.051 mg/dm³). The most stable and highest water quality was recorded in the Oba River, where from 2021 to 2024, water consistently corresponded to Class 2. Regression models of water quality class as a function of time and annual precipitation were constructed to assess the influence of climatic factors. Statistical analysis revealed no consistent linear correlation between average annual precipitation and water quality (correlation coefficients ranging from −0.49 to +0.37), indicating a complex interplay between climatic and anthropogenic factors. Significant relationships were found for the Breksa (R² = 0.903), Glubochanka (R² = 0.602), and Tikhaya (R² = 0.555) rivers, suggesting an influence of temporal and climatic factors on water quality. In contrast, the Oba (R² = 0.130), Ulba (R² = 0.100), and Krasnoyarka (R² = 0.018) rivers exhibited low coefficients, indicating the predominance of other, likely local, sources of pollution. It was found that summer periods are characterized by the highest pollution due to low water flow, while episodes of acid runoff occur in spring. A decrease in pH below 7.0 was first recorded in 2023–2024 in the Ulba and Tikhaya rivers. Forecasts to 2030 suggest relative stability in water quality under current climatic conditions; however, by 2050, the risk of water quality deterioration is expected to rise due to increased precipitation and extreme weather events. This study presents, for the first time, a systematic long-term analysis of small rivers in the East Kazakhstan region, offering deeper insight into the dynamics of surface water quality and providing a scientific foundation for developing adaptive strategies for the protection and sustainable use of water resources under climate change and anthropogenic pressure. The results emphasize the importance of prioritizing rivers with high variability in water quality for regular monitoring and the development of adaptive conservation measures. The research holds strong applied significance for shaping a sustainable water use strategy in the region. Full article

This study aims to explore how Corporate Digital Responsibility (CDR) influences Jordanian banks’ performance. It focuses on four CDR dimensions—“social, technological, economic, and environmental”—and examines the mediating role of firm size in these relationships. This study is the first to empirically test the mediating effect of firm size in the relationship between CDR and firm performance in the Jordanian banking sector, providing a novel perspective on how digital ethics shape organizational success. Data were collected through a structured survey from 299 bank employees in Jordan. Structural Equation Modeling (SEM) was employed to assess the direct and indirect effects of CDR dimensions on firm performance, with firm size tested as a mediating variable. All four dimensions of CDR significantly and positively affect firm performance. Additionally, firm size plays a partial mediating role in the relationship between CDR and firm performance, indicating that larger banks may better leverage digital responsibility initiatives to enhance performance. The study relies on self-reported data from a single country (Jordan), which may limit generalizability. Future studies could adopt a longitudinal design or expand to other MENA countries for comparative analysis and broader insights. The findings suggest that Jordanian banks should invest in and prioritize CDR strategies, especially in economic and technological domains, to improve their organizational outcomes and stakeholder relationships. Enhancing firm size may amplify the positive impact of CDR. The findings of this study are robust, as validated by further analysis utilizing data from a customer survey. The results derived from customer viewpoints correspond with staff data, substantiating the beneficial influence of Corporate Digital Responsibility (CDR) on banking performance and affirming the substantial mediating effect of company size. Full article