Search Results (10,829)

Geothermal resources in arid inland basins are important for clean energy development, yet their circulation and geochemical mechanisms remain insufficiently understood. This study investigates the hydrochemical characteristics and formation mechanisms of geothermal water in the Zhangye–Minle Basin, an arid inland region in northwestern China. A total of nine geothermal water samples were analyzed using major ion chemistry, stable isotopes (δ²H, δ¹⁸O), tritium (³H), and radiocarbon (¹⁴C) to determine recharge sources, flow paths, and geochemical evolution. The waters were predominantly of the Cl–Na and Cl·SO₄–Na types, with total dissolved solids ranging from 3432.00 to 5810.00 mg/L. Isotopic data indicated that recharge originated from atmospheric precipitation and snowmelt in the Qilian Mountains, with recharge altitudes between 2497 and 5799 m. Tritium and ¹⁴C results suggested that most samples were recharged before 1953, with maximum ages exceeding 40,000 years. Gibbs diagrams and ion ratio plots demonstrated that water–rock interaction was the primary geochemical process, while cation exchange was weak. Na⁺ was mainly derived from halite, albite, and mirabilite, while SO₄²⁻ originated largely from gypsum. The calculated reservoir temperatures using cation geothermometers ranged from 57 °C to 148 °C. The deep circulation of geothermal water was closely related to NNW-trending fault zones that facilitated infiltration and heat accumulation. These findings provide new insights into the recharge sources, circulation patterns, and geochemical processes of geothermal systems in fault-controlled basins, offering a scientific basis for their sustainable exploration and development. Full article

Medicinal plant production is essential for global health, yet how temperature, precipitation, and soil properties influence yield responses to fertilization remains poorly understood. Here, we conducted a meta-analysis of 668 observations from 79 studies, focusing on a wide range of plant species, to evaluate how nutrient inputs and environmental factors interact to shape medicinal plant productivity. We found that latitude, MAT, and MAP jointly determine global medicinal plant yield patterns. Yield increased with latitude and MAT but declined under prolonged fertilization and higher MAP. Optimal cultivation regions were identified between 15° and 35° absolute latitude, where temperature and precipitation conditions were most favorable. Compared with the arid environment of desertic climates, other regions, especially those with higher MAP in tropical areas, show a higher increase in yield. Our findings highlight that shifting precipitation-temperature regimes under climate change will affect fertilization outcomes on medicinal plant yield, emphasizing the need for spatiotemporally adaptive nutrient management strategies to ensure the sustainable yield of medicinal plants. Full article

The survival status of Lumnitzera littorea is near threatened globally and critically endangered in China. Clarifying its global distribution pattern and its changing trends under different future climate models is of great significance for the protection and restoration of its endangered status. To build a model for this purpose, this study selected 73 actual distribution points of Lumnitzera littorea worldwide, combined with 12 environmental factors, and simulated its potential suitable habitats in six periods: the Last Interglacial (130,000–115,000 years ago), the Last Glacial Maximum (27,000–19,000 years ago), the Mid-Holocene (6000 years ago), the present (1970–2000), and the future 2050s (2041–2060) and 2070s (2061–2080). The results show that the optimal model parameter combination is the regularization multiplier RM = 4.0 and the feature combination FC (Feature class) = L (Linear) + Q (Quadratic) + P (Product). The MaxEnt model has a low omission rate and a more concise model structure. The AUC values in each period are between 0.981 and 0.985, indicating relatively high prediction accuracy. Min temperature of the coldest month, mean diurnal range, clay content, precipitation of the warmest quarter, and elevation are the dominant environmental factors affecting its distribution. The environmental conditions for min temperature of the coldest month at ≥19.6 °C, mean diurnal range at <7.66 °C, clay content at 34.14%, precipitation of the warmest quarter at ≥570.04 mm, and elevation at >1.39 m are conducive to Lumnitzera littorea’s survival and distribution. The global potential distribution areas are located along coasts. Starting from the paleoclimate, the plant’s distribution has gradually expanded, and its adaptability has gradually improved. In China, the range of potential highly suitable habitats is relatively narrow. Hainan Island is the core potential habitat, but there are fragmented areas in regions such as Guangdong, Guangxi, and Taiwan. The modern centroid of Lumnitzera littorea is located at (109.81° E, 2.56° N), and it will shift to (108.44° E, 3.22° N) in the later stage of the high-emission scenario (2070s (SSP585)). Under global warming trends, it has a tendency to migrate to higher latitudes. The development of the aquaculture industry and human deforestation has damaged the habitats of Lumnitzera littorea, and its population size has been sharply and continuously decreasing. The breeding and renewal system has collapsed, seed abortion and seedling establishment failure are common, and genetic variation is too scarce. This may indicate why Lumnitzera littorea is near threatened globally and critically endangered in China. Therefore, the protection and restoration strategies we propose are as follows: strengthen the legislative guarantee and law enforcement supervision of the native distribution areas of Lumnitzera littorea, expanding its population size outside the native environment, and explore measures to improve its seed germination rate, systematically collecting and introducing foreign germplasm resources to increase its genetic diversity. Full article

Background: Macrophages are key components of the tumor microenvironment and play a critical role in melanoma progression. However, the dynamics of different macrophage subsets, particularly CD68⁺ and CD163⁺ populations, in relation to tumor thickness and stage remain insufficiently characterized. Objective: This study aimed to quantitatively assess intratumoral and peritumoral CD68⁺ and CD163⁺ macrophages in cutaneous melanoma and to investigate their associations with Breslow thickness, pT stage, and AJCC stage. Methods: We conducted a retrospective cohort study of 126 patients with cutaneous melanoma (AJCC stages IA–IIID). Tumor samples were examined histologically and immunohistochemically for CD68⁺ and CD163⁺ macrophages, and quantitative analysis was performed in intratumoral and peritumoral regions. Results: This study included 126 patients with cutaneous melanoma, ranging in stage from IA to IIID. Histopathological analysis revealed that melanoma tissues were primarily composed of irregular clusters of atypical melanocytic cells infiltrating the dermis and subcutaneous fat. Immunohistochemical staining identified CD68⁺ and CD163⁺ macrophages both within the tumor and in the surrounding stroma. Macrophage infiltration significantly increased with tumor thickness (Breslow) and progression to more advanced stages. Specifically, at Breslow thickness <1.0 mm, the mean number of CD68⁺ macrophages in the intratumoral zone was 29.7 ± 4.3 cells, increasing to 70.3 ± 6.4 cells in tumors >4.0 mm. CD163⁺ macrophages showed similar trends, with a rise from 15.6 ± 2.8 cells at <1.0 mm to 39.8 ± 4.6 cells at >4.0 mm in the intratumoral zone. Additionally, macrophage density was higher in tumors with ulceration, and both CD68⁺ and CD163⁺ macrophage numbers increased progressively with tumor stage, particularly in advanced stages. The number of CD68⁺ macrophages at stage IA in the intratumoral zone was 21.6 ± 3.1 cells and increased to 56.4 ± 6.8 cells at stage IIID, while CD163⁺ macrophages rose from 13.8 ± 3.2 cells at stage IA to 36.4 ± 4.6 cells at stage IIID. This suggests that macrophage infiltration, particularly CD163⁺ cells, correlates with melanoma progression. Conclusions: Our findings highlight distinct spatial and phenotypic patterns of macrophage infiltration in melanoma progression. The prominent increase in CD68⁺ and CD163⁺macrophages suggests their important role in tumor-associated immunomodulation. Further studies are warranted to elucidate macrophage polarization states and their prognostic and therapeutic implications in melanoma. Full article

Texture, a significant visual attribute in images, plays an important role in many pattern recognition tasks. While Convolutional Neural Networks (CNNs) have been among the most effective methods for texture analysis, alternative architectures such as Vision Transformers (ViTs) have recently demonstrated superior performance on a range of visual recognition problems. However, the suitability of ViTs for texture recognition remains underexplored. In this work, we investigate the capabilities and limitations of ViTs for texture recognition by analyzing 25 different ViT variants as feature extractors and comparing them to CNN-based and hand-engineered approaches. Our evaluation encompasses both accuracy and efficiency, aiming to assess the trade-offs involved in applying ViTs to texture analysis. Our results indicate that ViTs generally outperform CNN-based and hand-engineered models, particularly when using strong pre-training and in-the-wild texture datasets. Notably, BeiTv2-B/16 achieves the highest average accuracy (85.7%), followed by ViT-B/16-DINO (84.1%) and Swin-B (80.8%), outperforming the ResNet50 baseline (75.5%) and the hand-engineered baseline (73.4%). As a lightweight alternative, EfficientFormer-L3 attains a competitive average accuracy of 78.9%. In terms of efficiency, although ViT-B and BeiT(v2) have a higher number of GFLOPs and parameters, they achieve significantly faster feature extraction on GPUs compared to ResNet50. These findings highlight the potential of ViTs as a powerful tool for texture analysis while also pointing to areas for future exploration, such as efficiency improvements and domain-specific adaptations. Full article

Bruises in beef cattle carcasses are important indicators related to pre-slaughter handling and transport conditions, with implications for animal welfare and meat quality. This study analysed 19.4 million cattle carcasses transported from 42,805 farms to 38 slaughterhouses in Brazil to identify factors associated with bruising. Logistic regression models were used to assess the effects of sex, age, transport distance from farm to industry, and truck class. At least one bruise was found in 33.8% of the analysed carcasses. Older animals had a greater prevalence of bruising, and females were the most affected. The relationship between transport distance and bruising varied across carcass regions, showing distinct patterns rather than a uniform trend. Compared with larger-capacity vehicles, smaller trucks increased the risk of bruising. The round, rump, and flank regions presented the greatest number of bruises. The models assessing individual effects demonstrated good overall performance, with accuracy ranging from 75% to 82% in identifying bruises. The best performance was observed for round-rump, likely due to the higher frequency of bruises in these cuts. These findings highlight the need to improve transport logistics, adopt better handling practices, and implement specific interventions to reduce bruising. Full article

With the impact of fossil energy on the climate environment and the development of energy technologies, new energy vehicles, represented by electric cars, have begun to receive increasing attention and emphasis. The rapid proliferation of public charging infrastructure for NEVs has concurrently influenced traditional petrol station networks, creating measurable disparities in their spatial distributions that warrant systematic investigation. This research examines Wenzhou City, China, as a representative case area, employing multi-source Point of Interest (POI) data and spatial analysis models to analyse differential characteristics in spatial layout accessibility, service equity, and underlying driving mechanisms between public electric vehicle charging stations (EV) and traditional gas stations (GS). The findings reveal that public electric vehicle charging stations exhibit a pronounced “single-centre concentration with weak multi-centre linkage” spatial configuration, heavily reliant on dual-core drivers of population density and economic activity. This results in marked service accessibility declines in peripheral areas, resembling a cliff-like drop, and a relatively low spatial equity index. In contrast, traditional gas stations demonstrate a “core-axis linkage” diffusion pattern with strong coupling to urban road networks, showing gradient attenuation in service coverage efficiency along transportation arteries, fewer suburban service gaps, and more gradual accessibility reductions. Location entropy analysis further indicates that charging station deployment shows significant capital-oriented tendencies, with certain areas exhibiting paradoxical “excess facilities” phenomena, while gas station distribution aligns more closely with road network topology and transportation demand dynamics. Furthermore, the layout characteristics of public charging stations feature a more complex and diverse range of land use types, while traditional gas stations have a strong dependence on industrial land. This research elucidates the spatial distribution patterns of emerging and legacy energy infrastructure in the survey regions, providing critical empirical evidence for optimising energy infrastructure allocation and facilitating coordinated transportation system transitions. The findings also offer practical insights for the construction of energy supply facilities in urban development frameworks, holding substantial reference value for achieving sustainable urban spatial governance. Full article

Background/Objectives: Geographical variations in outcomes and oral anticoagulant (OAC) initiation among patients with nonvalvular atrial fibrillation (NVAF) in the United States (US) have been characterized; however, regional effects on OAC persistence are unknown. The study described variation in persistence with OACs among patients with NVAF across different US regions. Methods: The Komodo Healthcare Map was used to evaluate adult patients with NVAF, elevated stroke risk, and ≥1 pharmacy claim for an OAC between 1 January 2015 and 31 August 2022. Patients initiating treatment with an OAC (treatment-naïve) and having ≥12 months continuous enrollment were included. Persistence rates were assessed at 6, 9, 12 and 18 months among OAC- and direct OAC (DOAC)-naïve patients by 3-digit zip codes. Results: Of the 260,001 (Northeast = 72,507, Midwest = 59,979, South = 83,880, West = 42,778, Other/Unknown = 857) OAC-naïve patients identified, 82.2% were DOAC-naïve while 17.8% initiated warfarin. Mean follow-up time was 1101 (median = 964) and 1073 days (median = 938) in OAC and DOAC cohorts, respectively, while mean time to discontinuation was 342 (median = 190) and 329 days (median = 181), respectively. At 12 months, persistence rates ranged from 40.3% to 78.8% for OAC-naïve patients and 40.6% to 81.4% for DOAC-naïve patients. Average OAC and DOAC 12-month persistence rates were highest in the Northeast (63.5% and 63.7%, respectively) and lowest in the South (57.1% and 56.9%, respectively). Conclusions: Variations in 12-month persistence were consistent with existing evidence on geographic variation in NVAF-related disease burden and treatment initiation. Understanding geographic trends in prescribing patterns may provide insights into differences in treatment persistence that are relevant for clinicians seeking to address real-world barriers to care. Full article

Background and Objectives: Automated insulin delivery (AID) systems represent a major advancement in type 1 diabetes (T1D) management, particularly in pediatric populations. However, real-world evidence comparing their effectiveness to conventional multiple daily injection (MDI) therapy in youth remains limited. This study aimed to evaluate the impact of transitioning from MDI therapy to AID systems on glycemic control in children and adolescents with T1D, and to explore potential differences based on baseline HbA1c levels and device type. Materials and Methods: In this single-center, retrospective observational study, 76 children and adolescents with T1D were evaluated before and after switching from MDI to either the Medtronic MiniMed™ 780G or Tandem t:slim X2™ Control-IQ system. Glycemic control was assessed using continuous glucose monitoring (CGM)-derived metrics at three time points: the last 15 days of MDI therapy (T0), 15 days after (T1), and 6 months after (T2) AID initiation. Statistical comparisons were conducted across time points and between subgroups stratified by baseline HbA1c and AID system. Results: Significant improvements in glycemic control were observed as early as 15 days after AID initiation, with sustained benefits at 6 months. Time in range (TIR) increased from 62.0% at baseline to 76.7% at 15 days and 75.8% at 6 months, and time in tight range (TITR) from 39.8% to 53.9% at T1 and 52.1% at T2 (both p < 0.001). Improvements were more pronounced in participants with higher baseline HbA1c (+16.9% for TITR and +22.3% for TIR). No significant differences in glycemic outcomes were observed between device groups, although algorithm-driven differences in insulin delivery patterns were noted. Total daily insulin dose and BMI increased significantly over time (p < 0.001 and p = 0.008, respectively). Conclusions: AID therapy leads to rapid and sustained improvements in glycemic control among youth with T1D, particularly in those with suboptimal baseline control. These benefits highlight the clinical value of AID systems, while also emphasizing the need for monitoring potential metabolic impacts. Full article

Smart cities and urban planning have succeeded in gathering the attention of researchers worldwide, especially in the last decade, as a result of a series of technological, social and economic developments that have shaped the need for evolution from the traditional way in which the cities were viewed. Technology has been incorporated in many sectors associated with smart cities, such as communications, transportation, energy, and water, resulting in increasing people’s quality of life and satisfying the needs of a society in continuous change. Furthermore, with the rise in machine learning (ML) and artificial intelligence (AI), as well as Geographic Information Systems (GIS), the applications of big data analytics in the context of smart cities and urban planning have diversified, covering a wide range of applications starting with traffic management, environmental monitoring, public safety, and adjusting power distribution based on consumption patterns. In this context, the present paper brings to the fore the papers written in the 2015–2024 period and indexed in Clarivate Analytics’ Web of Science Core Collection and analyzes them from a bibliometric point of view. As a result, an annual growth rate of 10.72% has been observed, showing an increased interest from the scientific community in this area. Through the use of specific bibliometric analyses, key themes, trends, prominent authors and institutions, preferred journals, and collaboration networks among authors, data are extracted and discussed in depth. Thematic maps and topic discovery through Latent Dirichlet Allocation (LDA) and doubled by a BERTopic analysis, n-gram analysis, factorial analysis, and a review of the most cited papers complete the picture on the research carried on in the last decade in this area. The importance of big data analytics in the area of urban planning and smart cities is underlined, resulting in an increase in their ability to enhance urban living by providing personalized and efficient solutions to everyday life situations. Full article

The Strait of Sicily represents a biogeographically rich and complex region. The diverse geological origin and past continental connection of its islands have shaped a highly heterogeneous fauna, mainly composed of both African and European taxa. The Italian sea-slater, Ligia italica (Fabricius, 1798), is a small isopod inhabiting rocky shores of the Mediterranean Sea, Black Sea, and Atlantic Ocean. Despite its wide distribution, the phylogeography of this species is poorly understood, with limited available data suggesting a remarkable level of cryptic diversity. In this study, we investigated the mitochondrial genetic diversity (COX1) of L. italica across nine Italian and Maltese islands across the Strait of Sicily, aiming to clarify the biogeographic patterns underlying the distribution of these insular populations. Our results reveal an unexpectedly high genetic diversity within our study area, with eight different haplogroups, each characterized by low internal genetic variation and mutual distances ranging from 5.5% to 17.9%. These values are comparable to those associated with species-level rank within the genus Ligia. Overall, the phylogenetic relationships between the lineages appear well supported; however, the same relationships are not clearly correlated with geographic proximity or connectivity among the sampled localities. The distribution patterns of some of the detected haplogroups suggest possible passive dispersal mechanisms (e.g., rafting), while others indicate more intricate biogeographic scenarios. The overall diversity of L. italica within the Strait of Sicily, as well as the unclear origin of some insular populations, cannot be fully explained with the current data. In particular, the high genetic structure observed within the Maltese Archipelago, may partially reflect human-mediated dispersal (e.g., maritime transport), possibly involving source populations that remain unsampled or genetically uncharacterized. Our results highlight that the Strait of Sicily can be considered a diversity hot spot for L. italica and support the designation of this taxon as a putative species complex, with a cryptic diversity worthy of an exhaustive taxonomic revision. Full article

Light Electric Vehicles (LEVs) offer a promising response to environmental and urban mobility challenges. This study is among the first to exploratorily examine their use, user characteristics, and owner evaluations. A qualitative pre-study with four LEV owners was conducted and informed a subsequent quantitative phase involving 23 owners. Over two weeks, participants recorded all LEV trips using GPS tracking and completed two questionnaires. Findings show that LEVs are regularly used for commuting, shopping, and work-related trips. Notably, many users live outside urban centers, indicating strong potential for short-distance travel in rural and small-town contexts for our sample. This challenges the view of LEVs as primarily urban or recreational vehicles. Within our sample, usage patterns were diverse, indicating that even among early adopters there is no single typical usage profile. While cars were perceived as slightly safer, no participant reported feeling unsafe in their LEV. User satisfaction was high: 24 of 27 respondents would choose the same vehicle again. Overall, LEVs emerge as a versatile and satisfying mobility option, relevant beyond city limits. Given their wide range of uses and positive user feedback, LEVs should be more strongly considered in transport policy to promote more sustainable and needs-based mobility. Full article

Loop heat pipes are efficiently two-phase heat transfer devices in the field of aircraft thermal management. To investigate the startup behavior and thermal instability of loop heat pipes under acceleration force, this study designed a novel loop heat pipe featuring two visual compensation chambers and a visual condenser. Elevated acceleration experiments were conducted across four different heat loads, acceleration magnitudes, and directions. The heat load ranged from 30 W to 150 W, while the acceleration magnitude varied from 1 g to 15 g, with four acceleration directions (A, B, C, and D). The startup behavior, thermal instability, internal flow pattern, and phase distribution were analyzed systematically. The experimental results reveal the following: (i) The startup behaviors vary across the four acceleration directions. In direction A, startup is more difficult due to additional resistance induced by the acceleration force. In direction C, startup time generally decreases with increasing heat load and acceleration up to 7 g. The longest startup time observed is 372 s at 30 W and 11 g. (ii) At high heat load, periodic temperature fluctuations are observed, particularly in directions B and C. Simultaneously, the vapor–liquid phase interface in the condenser exhibits periodic back-and-forth movement. (iii) The visual DCCLHP exhibits a loss of temperature control under the combined influence of high heat loads and acceleration force, often accompanied by working fluid reverse flow, periodic temperature fluctuations, or wick dry-out. Full article

Background/Objectives: Type 1 diabetes mellitus (T1D) is the most common metabolic disorder in children, with significant physical and emotional impacts. Achieving optimal glucometric control is challenging due to the complex management and limitations of insulin therapy. Advances in pharmacology and technology, including continuous glucose monitoring (CGM) systems, offer new options for diabetes management. We developed Andiacare, an open-source platform for macro/micro-management of diabetes and analyzed its application in a pediatric T1D cohort to evaluate glucometric control patterns. Methods: A retrospective cohort study was conducted in a pediatric population (<18 years old) in Andalusia, Spain. Patients treated with Multiple Daily Injections of Insulin (MDI) and FreeStyle Libre 2 System (Abbott, Spain) were included. The patient data were analyzed using the Andiacare platform, which categorizes patients based on the Advanced Technologies and Treatments for Diabetes (ATTD) panel’s targets for glucometric control. Results: The study included 2215 patients from 18 pediatric hospitals. The Andiacare platform categorized patients into four groups based on glucometric control parameters, enabling patient stratification based on their glucometric control. Only 25.8% of the cohort achieved the recommended Time in Range (TIR), and 9.5% of the patients achieved all target parameters of glucometric control. Age is a determinant factor in adherence and achievement of set goals. Conclusions: This study offers insights into glucometric control in a large pediatric population with T1D in Andalusia. Few patients achieved the recommended glucometric control targets, highlighting the need for improved management strategies. The use of digital platforms such as Andiacare might contribute to facilitating the management of large pediatric cohorts. New algorithms integrating glucometric and non-glucometric parameters are required for improved individual and cohort categorization to optimize therapeutic interventions. Full article

Tropical and subtropical forests account for approximately one-third of global terrestrial gross primary productivity (GPP), and the diurnal patterns of GPP strongly regulate the land–atmosphere CO₂ interactions and feedback to the climate. Combined with ground eddy-covariance (EC) flux towers, geostationary satellites offer significant advantages for continuously monitoring these diurnal variations in the “breathing of biosphere”. Here we utilized half-hourly optical signals from the Himawari-8 Advanced Himawari Imager (H8/AHI) geostationary satellite and tower-based EC flux data to investigate the diurnal variations in subtropical forest GPP and its drivers. Results showed that three machine learning models well estimated the diurnal patterns of subtropical forest GPP, with the determination coefficient (R²) ranging from 0.71 to 0.76. Photosynthetically active radiation (PAR) is the primary driver of the diurnal cycle of GPP, modulated by temperature, soil water content, and vapor pressure deficit. Moreover, the effect magnitude of PAR on GPP varies across three timescales. This study provides robust technical support for diurnal forest GPP estimations and the possibility for large-scale estimations of diurnal GPP over tropics in the future. Full article