Search Results (10,644)

Innovation is central to the Zero Hunger agenda, yet its distributional links to agricultural performance and policy in Eastern Europe remain unclear. This study investigates whether national innovation performance, proxied by the Global Innovation Index, is associated with agriculture’s macroeconomic weight and with public budget orientation in Bulgaria, Czechia, Hungary, Poland, Romania, and Slovakia across the past decade and a half. Using panel quantile regression with country fixed effects and bootstrapped standard errors, we estimate effects at the lower, median, and upper parts of the outcome distributions for three indicators: agriculture value added share of gross domestic product, the agriculture orientation index for government expenditures, and the agriculture share of government expenditure. Results show a robust negative association between innovation and the agricultural share of gross domestic product that strengthens toward the upper quantiles, consistent with structural transformation that reallocates value added toward higher-productivity sectors. For the orientation index, innovation is unrelated at the lower and median parts but becomes positive in mid–upper regimes, fading again at the extreme upper tail. No systematic relationship emerges for the budget share. Land endowment is positively associated with agricultural weight, while population size is negatively associated. We conclude that economy-wide innovation aligns with structural change, whereas shifting agricultural budget shares requires targeted, sector-specific policy instruments. Full article

This study provides a comprehensive assessment of the distribution, bioaccumulation, and health risks associated with heavy metals in the soil–coffee system of Pu’er City, a major coffee-producing region in China. An analysis of the soil and corresponding plant samples (including fruit, stem, and leaf) from representative plantations revealed that, although the heavy metal concentrations in soils generally exceeded the local background levels, they remained below national risk screening thresholds. Hg was identified as the primary pollutant of concern, showing moderate to significant enrichment (EF: 2–20) and posing a moderate to considerable ecological risk (E_i: 40–160). In coffee plants, most heavy metals accumulated predominantly in the stems, whereas Pb and As were more concentrated in the leaves and fruits, respectively. Among the studied metals, only Cu exhibited a notable bioconversion tendency, with a biota soil accumulation factor (BSAF) close to 1, while other metals showed limited transfer (BSAF < 1). A generally negative correlation was observed between the soil metal content and BSAF, suggesting that elevated total concentrations do not necessarily enhance bioavailability. The health risk assessment indicated that coffee consumption poses no significant non-carcinogenic risk (HI < 1). However, the carcinogenic risks for Cr and As, albeit within acceptable limits (LCR between 10⁻⁶ and 10⁻⁴), still warrant attention. These findings underscore the importance of implementing targeted source control for Hg and Cr in soils and further investigating the transfer mechanisms of As to support the sustainable and safe production of coffee in this region. Full article

Small rural water utilities in the Appalachia region of the US often experience extreme water loss while struggling to maintain water quality compliance. This study quantifies the impact of reducing water loss on distribution system water quality in Martin County, Kentucky. Hydraulic and water quality models were developed, calibrated, and validated using EPANET for chlorine residuals and KYPIPE for trihalomethane (TTHM) formation. The models evaluated water loss reduction scenarios ranging from the current 70% to the industry target of 15%. Results showed that lowering water loss increased residence times, causing chlorine residual declines of 22–68%, with one site falling to the 0.2 mg/L threshold. TTHM concentrations increased by 12–18% in winter–spring and 26–44% in summer–fall, with two sites exceeding the individual 0.080 mg/L maximum contaminant level. These novel findings indicate that reducing water loss can unintentionally degrade water quality, underscoring the need for integrated planning. Recommended mitigation strategies include seasonal operational adjustments, water source and TTHM precursor management, optimized tank management, targeted flushing, and phased infrastructure upgrades. The modeling framework developed offers potential for broader application in other rural systems facing similar challenges. Full article

Hamatocaulis vernicosus is a pleurocarpous moss of conservation concern, listed in Annex II of the EU Habitats Directive due to its significant and ongoing decline across Europe. H. vernicosus is also listed as ‘Vulnerable’ on the Red List of Romanian Bryophytes. Despite its protected status, the species remains under-recorded in Romania, where many potentially suitable habitats have yet to be surveyed. The ecosystems, classified as Transition mire and quaking bog (NATURA 2000 code: 7140), are wet peatlands with oligo- to mesotrophic conditions and a pH of 5.0–7.5. H. vernicosus is recorded in 58 Romanian locations (10 confirmed by us, 5 new), spanning the Continental and Alpine bioregions. Models showed good performance (AUC 0.79–0.83; TSS 0.54–0.59), with distribution mainly shaped by mean annual temperature and temperature range, and secondarily by precipitation. The species favors cold, stable climates with high seasonal rainfall. Even though the number of localities reported for this species has increased in recent years, this does not indicate an improvement in its conservation status, but rather is an effect of recent recording efforts. To support targeted conservation planning, an ensemble species distribution model was developed in order to predict the suitable habitats of H. vernicosus across Romania. Both climate models project major range losses for the varnished hook-moss: ~30% by 2050 and ~40–60% by 2100, depending on the scenario. Losses are gradual under SSP245 but more abrupt under SSP585, with increased fragmentation, especially between the Eastern and Southern Carpathians. By integrating field observations with predictive climate change modeling, our study brings critical insights applicable to the conservation of H. vernicosus and the unique peatland ecosystems it relies on. Full article

Cryptosporidiosis is a zoonotic disease of medical and veterinary importance caused by Cryptosporidium spp. This study conducted a systematic review to assess the occurrence and distribution of Cryptosporidium spp. in humans in Brazil, with emphasis on C. parvum. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol and using five databases, 3689 articles were screened, and 48 met the inclusion criteria. Most studies were concentrated in the Southeast Region, particularly São Paulo, while major gaps were identified in the North and Midwest Regions. The mean prevalence was 8.9% using direct methods and 52.2% using indirect methods, with the highest positivity reported in the Northeast Region. Microscopy was the most frequently employed diagnostic tool, although it showed limited ability to differentiate species. When combined with molecular approaches, C. parvum and C. hominis were identified as the predominant species. Infection was most common among children and immunocompromised individuals, especially those with HIV and kidney diseases. Overall, the findings highlight substantial research gaps regarding cryptosporidiosis in Brazil and its disproportionate impact on vulnerable populations. Expanding regional studies, integrating molecular methods for species characterization, and implementing targeted public health strategies are essential to improve epidemiological knowledge and guide prevention and control measures. Full article

Estrogen is a key regulator of skeletal muscle growth and metabolism in birds, yet its specific roles in female chickens remain poorly defined. To address this gap, we established an estrogen-deficient model by surgically removing the ovaries of Wuding hens, a Chinese indigenous slow-growing breed. Growth traits, carcass yield, and meat quality were evaluated across different ages, complemented by histological examination, serum biochemical analysis, and multi-omics approaches (transcriptomics, proteomics, and lipidomics). Ovariectomized hens maintained somatic growth for a longer period and reached greater body weight and carcass yield at 330 days compared with intact controls. Thigh muscle tenderness was also enhanced in the absence of estrogen, despite no long-term differences in muscle fiber morphology. Lipidomic analysis revealed a transient increase in intramuscular triglyceride content at mid-growth (240 days), pointing to altered lipid storage and distribution. Integrated omics profiling further demonstrated significant changes in the mitogen-activated protein kinase (MAPK) and mechanistic target of rapamycin (mTOR) signaling pathways, accompanied by differential expression of key metabolic and structural genes, including mitogen-activated protein kinase 8 (MAPK8), fatty acid binding protein 4 (FABP4), ankyrin 1 (ANK1), and coenzyme Q6 monooxygenase (COQ6). These molecular adjustments suggest that estrogen withdrawal triggers broad reprogramming of muscle signaling and lipid metabolism. Overall, this study highlights the multifaceted role of estrogen in coordinating growth, muscle quality, and lipid homeostasis in hens and provides a functional model for studying estrogen deficiency in poultry with implications for meat quality improvement. Full article

Background: The ways in which peripheral sensory nerves interact with osteosarcomas are important to understand because it could lead to development of new approaches to treat bone cancer pain. This study aimed to determine how cancer affects sensory nerve density and distribution in a murine model of osteosarcoma-induced bone pain. Methods: The femoral marrow cavities of male C3H/HeNHsd mice were injected with either NCTC 2472 primary osteosarcoma (cancer) cells or phosphate buffered saline (control). Pain behavior was assessed using limb use score and static weight bearing assays. At the experimental endpoint, femurs were collected, decalcified, immunolabeled, cleared and imaged using light sheet microscopy (Ultramicroscope Blaze, Miltenyi Biotec). The distribution of sensory nerves was traced through the marrow cavity of the proximal femur and the periosteum overlying the third trochanter (Imaris, Bitplane). Results: Weight bearing on the injected limb was decreased in osteosarcoma-injected but not saline-injected mice. Filament tracing revealed a reduced density of neurofilament 200 kDa-positive (NF200+; myelinated nerve marker) but not calcitonin gene-related peptide-positive (CGRP+; peptidergic nerve marker) sensory nerves in the marrow cavity of osteosarcoma-injected relative to saline-injected mice. There was increased density of CGRP+ but not NF200+ nerves in the periosteum of osteosarcoma-injected relative to saline-injected mice. Conclusions: Osteosarcoma differentially affects the density and distribution of different subtypes of peripheral sensory nerves in bone. Understanding how osteosarcomas affect different populations of sensory nerves could lead to more targeted mechanism-based treatments for bone cancer-induced pain. Full article

Early cellular alterations in abdominal aortic aneurysm (AAA) are scarcely investigated. Aortic remodeling inflammation-related suggested the CXCR2/CXCL1/IL-8 axis as a therapeutic target. This study investigates CXCR1/CXCR2 antagonism in primary human aortic endothelial (HAOEC) and smooth muscle cells (HAOSMC) conditioned with IL-8 or serum from patients with AAA (sPT). Ladarixin (10 μM Lad or 25 μM) served as an inhibitor. Readouts included RT-qPCR for CXCL1, CXCL8, CXCR2, MMP9, NFKB1, and VEGF-A; zymography for MMP9 activity confocal microscopy for F-actin and mitochondria; NADPH/NADH diaphorase histochemistry for redox activity; and ATP assay. In HAOEC, IL-8 downregulated CXCR2, increased MMP9 activity, and induced cytoskeletal and mitochondria disorganization without altering NADH/NADPH diaphorases but increasing ATP release. At concentration of 10 μM Lad rescued cell organization and gene expression. sPT upregulated CXCL8, CXCR2, and MMP9, decreased NADH/NADPH diaphorases, and altered cytoskeleton and mitochondria organization in HAOEC. At concentration of 10 μM Lad (partially) and 25 μM Lad reverted gene upregulation and mitochondria distribution; both doses increased diaphorase and released ATP. HAOSMC were scantily susceptible to IL-8 and weakly responsive to sPT, slightly upregulating CXCR2 and VEGF-A but increasing proMMP9 gelatinolysis. Ladarixin recovered proMMP9 activity and modulated CXCL1. AAA-like vascular cell alterations involve multiple inflammatory factors and are modulable by inhibition of IL-8 receptors. The results underline careful dose calibration. Full article

HPAM-Cr³⁺ (partially hydrolyzed polyacrylamide-chromium ion) gels are widely used in enhancing oil recovery (EOR) due to their advantages of low cost, controllability, and high strength. The propagation distance of gels within the reservoir significantly negatively impacts their gelation performance. However, the extent of this influence remains unclear, hindering precise optimization for field applications. This study first established a gelation performance characterization method based on visual inspection, rheological parameters, and long-term stability, accurately classifying gels into five types: stable strong gel (SSG), stable weak gel (SWG), colloidal dispersion gel (CDG), unstable gel (USG), and over-crosslinked gel (OCG). Subsequently, cross-experiments were conducted using varying concentrations of HPAM and Cr³⁺. Based on the contour map of visual appearance, storage modulus (G′), and water loss rate (R_w) of the gels, distribution maps of gel morphology versus concentration were constructed. The gel performance was found to depend on the HPAM concentration and the crosslinking ratio (molar ratio of HPAM carboxyl groups to Cr³⁺ ions). No gel formation occurred when the HPAM concentration was below 800 mg/L, while concentrations above 2500 mg/L effectively inhibited over-crosslinking. The crosslinking ratio range for forming SSG was 5.56 to 18.68, with an optimal value of 9.27. Furthermore, the effect of propagation distance on gelation performance was investigated through 60 m sand-packed flow experiments. Results indicated that the minimum value of the crosslinking ratio was 2.632, the stable SSG formed when the propagation distance was less than 21 m, SWG formed within the 21–34 m range, and no intact gel formed beyond 34 m. It means that only the first 35% of the designed distance formed effective SSG for plugging. Finally, an optimization method for gel dosage design was established based on the findings. This method determines the optimal gel dosage for achieving effective plugging by calculating the volume of crosslinking system passing through the target fluid diversion interface and referencing the gel morphology distribution maps. These findings provide a straightforward and effective approach for the precise design of in-depth profile control agents. Full article

Background/Objectives: Exclusive breastfeeding rates in Indonesia remain low, particularly among working mothers, despite government policies and the substantial contribution of women to the national economy. Inadequate workplace support, with only 21.5% of working mothers having access to proper lactation facilities, is a key barrier. This study aimed to analyze Google Trends search data to understand the barriers and opportunities regarding workplace breastfeeding support in Indonesia, providing a data-driven foundation for advocacy campaigns and policy development. Methods: We conducted a retrospective analysis of Google Trends data from July 2020 to July 2025. Temporal and geographic search patterns for selected keywords, along with related queries and topics, were analyzed using a normalized relative search volume index (0–100). Results: “Lactation room” was the dominant, foundational search term with sporadic, event-driven peaks. Search interest in “exclusive breastfeeding” was consistently high (“evergreen”), while “World Breastfeeding Week” showed predictable seasonal peaks. Geographically, the need for basic infrastructure was nationally distributed, but searches for practical solutions, deeper topics, and event momentum were concentrated in urban economic centers. A nationwide knowledge gap on rights was identified. Analysis of “Rising Queries” and “Topics” revealed a shift in user focus from general information toward specific needs regarding rights, policy, and community support. Conclusions: The geographic and temporal alignment of user-identified needs with campaign momentum validates a targeted, multi-layered advocacy strategy. A three-pillar approach combining data-driven communication, workplace policy change, and multi-sectoral collaboration is recommended to improve breastfeeding support for working mothers in Indonesia. Full article

Ship instance segmentation in remote sensing images is essential for maritime applications such as intelligent surveillance and port management. However, this task remains challenging due to dense target distributions, large variations in ship scales and shapes, and limited high-quality datasets. The existing YOLOv8 framework mainly relies on convolutional neural networks and CIoU loss, which are less effective in modeling global–local interactions and producing accurate mask boundaries. To address these issues, we propose CDSANet, a novel one-stage ship instance segmentation network. CDSANet integrates convolutional operations, Vision Transformers, and attention mechanisms within a unified architecture. The backbone adopts a Convolutional Vision Transformer Attention (CVTA) module to enhance both local feature extraction and global context perception. The neck employs dynamic-weighted DOWConv to adaptively handle multi-scale ship instances, while SIoU loss improves localization accuracy and orientation robustness. Additionally, CBAM enhances the network’s focus on salient regions, and a MixUp-based augmentation strategy is used to improve model generalization. Extensive experiments on the proposed VLRSSD dataset demonstrate that CDSANet achieves state-of-the-art performance with a mask AP (50–95) of 75.9%, surpassing the YOLOv8 baseline by 1.8%. Full article

The aerodynamic pressure of a car is crucial for its shape design. To overcome the time-consuming and costly bottleneck of wind tunnel tests and computational fluid dynamics (CFD) simulations, deep learning-based surrogate models have emerged as highly promising alternatives. However, existing methods that only predict on the surface of objects only learn the mapping of pressure. In contrast, a physically realistic field has values and gradients that are structurally unified and self-consistent. Therefore, existing methods ignore the crucial differential structure and intrinsic continuity of the physical field as a whole. This oversight leads to their predictions, even if locally numerically close, often showing unrealistic gradient distributions and high-frequency oscillations macroscopically, greatly limiting their reliability and practicality in engineering decisions. To address this, this study proposes the Geo-PhysNet model, a graph neural network framework specifically designed for complex surface manifolds with strong physical constraints. This framework learns a differential representation, and its network architecture is designed to simultaneously predict the pressure scalar field and its tangential gradient vector field on the surface manifold within a unified framework. By making the gradient an explicit learning target, we force the network to understand the local mechanical causes leading to pressure changes, thereby mathematically ensuring the self-consistency of the field’s intrinsic structure, rather than merely learning the numerical mapping of pressure. Finally, to solve the common noise problem in the predictions of existing methods, we introduce a physical regularization term based on the surface Laplacian operator to penalize non-smooth solutions, ensuring the physical rationality of the final output field. Experimental verification results show that Geo-PhysNet not only outperforms existing benchmark models in numerical accuracy but, more importantly, demonstrates superior advantages in the physical authenticity, field continuity, and gradient smoothness of the generated pressure fields. Full article

The significant heterogeneity of continental shale reservoirs within the Permian Lucaogou Formation of the Jimsar Sag presents a major challenge for shale oil exploration. This study aims to quantitatively characterize the pore structure complexity of different lithofacies to identify favorable “sweet spots.” By integrating geochemical, petrological, and high-resolution pore characterization data with fractal theory, we introduce a comprehensive fractal dimension (D_c) for evaluation. Five distinct lithofacies are identified: massive felsic siltstone (MFS), bedded dolostone (BD), bedded felsic dolostone (BFD), laminated dolomitic felsic shale (LDFS), and laminated mud felsic shale (LMFS). Pore structures vary significantly: MFS is dominated by mesopores (100–2000 nm), BD and BFD exhibit a bimodal distribution (<30 nm and >10 μm), while LDFS and LMFS are characterized by nanopores (<50 nm). D_c analysis reveals a descending order of pore structure complexity: BFD > LMFS > LDFS > MFS > BD. Furthermore, D_c shows positive correlations with clay mineral and feldspar contents but a negative correlation with carbonate minerals. A significant negative correlation between D_c and measured permeability confirms its effectiveness in characterizing reservoir heterogeneity. We propose that MFS and LDFS, with higher pore volumes and relatively lower D_c values, represent the most favorable targets due to their superior storage and seepage capacities. This study provides a theoretical foundation for the efficient development of continental shale oil reservoirs. Full article

Climate change is shifting where suitable habitats occur for many species across the planet. Sarracenia purpurea L., the most widely distributed pitcher plant species in North America, already faces significant threats from land use change. While S. purpurea is well studied at physiological and local scales, threat assessments for this species at biogeographic scales are absent. Here, we remedy this by using Habitat Suitability Models to predict current suitable habitats and estimate climate-based shifts in the suitable habitat for S. purpurea in the near (2040) and long term (2100). The models predicted large areas of habitat loss in the southeastern United States and the western portion of the Great Lakes region by 2040. While the models also predict significant gains in suitable habitats north of the current S. purpurea range, the limited dispersal ability of this species precludes the possibility of natural migration to newly suitable habitats. Our results suggest that the degradation of considerable portions of current suitable habitats is already occurring and will continue in the future. Particularly threatened are the southern subspecies (e.g., Sarracenia purpurea subsp. venosa) of S. purpurea. We therefore urge land managers to make conservation efforts targeting threatened subspecies and encourage further the biogeographic investigation of less widely distributed congenerics of S. purpurea. Full article

The aim of this study was to rigorously quantify and analyse the concentrations of atmospheric pollutants (PM₁₀, PM_2.5, SO₂, NO₂, CO, H₂S, and O₃) emitted by artisanal brick kilns in Juliaca City, Peru. The AERMOD dispersion model and a network of low-cost sensors (LCSs) were employed to characterise air quality at specific receptor sites. A georeferenced inventory of kiln operations was created to determine their parameters and operational intensity, providing a foundation for estimating emission factors and rates. Data were obtained from the United States Environmental Protection Agency (EPA) and supplemented with locally gathered meteorological records, which were processed for integration into the AERMOD model. The findings revealed that brick kilns are a principal source of atmospheric pollution in the region, with carbon monoxide (CO) emissions being especially pronounced. The LCSs facilitated the identification of pollutant concentrations at various locations and enabled the quantification of the specific contribution of brick production to ambient aerosol levels. Comparative assessments determined that these sources account for approximately 85% of CO emissions within the study area, underscoring a significant adverse impact on air quality and public health. Background pollutant levels, emission rates, spatial distributions, and concentration patterns were analysed within the assessment zones, resulting in solid model performance. These results provide a sound scientific basis for the formulation and implementation of targeted environmental mitigation policies in urban areas and the outskirts of Juliaca. Full article