Search Results (193)

The utilization of steel slag (SS) in construction materials represents an effective approach to improving its overall recycling efficiency. This study incorporates SS into a conventional ground granulated blast-furnace slag (GGBS)–fly ash (FA)-based binder system to develop a ternary system comprising SS, GGBS, and FA, and investigates how this system influences the static mechanical properties of ultra-high-performance geopolymer concrete (UHPGC). An axial point augmented simplex centroid design method was employed to systematically explore the influence and underlying mechanisms of different binder ratios on the workability, axial compressive strength, and flexural performance of UHPGC, and to determine the optimal compositional range. The results indicate that steel slag has a certain negative effect on the flowability of UHPGC paste; however, with an appropriate proportion of composite binder materials, the mixture can still exhibit satisfactory flowability. The compressive performance of UHPGC is primarily governed by the proportion of GGBS in the ternary binder system; an appropriate GGBS content can provide enhanced compressive strength and elastic modulus. UHPGC exhibits ductile behavior under flexural loading; however, replacing GGBS with SS significantly reduces its flexural strength and energy absorption capacity. The optimal static mechanical performance is achieved when the mass proportions of SS, GGBS, and FA are within the ranges of 9.3–13.8%, 66.2–70.7%, and 20.0–22.9%, respectively. This study provides a scientific approach for the valorization of SS through construction material applications and offers a theoretical and data-driven basis for the mix design of ultra-high-performance building materials derived from industrial solid wastes. Full article

Routing in flying ad hoc networks (FANETs) is hindered by high mobility, trajectory-induced topology dynamics, and energy constraints. Conventional topology-based or position-based protocols often fail due to stale link information and limited neighbor awareness. This paper proposes a trajectory-informed routing protocol enhanced by Q-learning: Traj-Q-GPSR, tailored for mission-oriented UAV swarm networks. By leveraging mission-planned flight trajectories, the protocol builds time-aware two-hop neighbor tables, enabling routing decisions based on both current connectivity and predicted link availability. This spatiotemporal information is integrated into a reinforcement learning framework that dynamically optimizes next-hop selection based on link stability, queue length, and node mobility patterns. To further enhance adaptability, the learning parameters are adjusted in real time according to network dynamics. Additionally, a delay-aware queuing model is introduced to forecast optimal transmission timing, thereby reducing buffering overhead and mitigating redundant retransmissions. Extensive ns-3 simulations across diverse mobility, density, and CBR connections demonstrate that the proposed protocol consistently outperforms GPSR, achieving up to 23% lower packet loss, over 80% reduction in average end-to-end delay, and improvements of up to 37% and 52% in throughput and routing efficiency, respectively. Full article

Background: The rapid advancement of radiomics and artificial intelligence (AI) technology has provided novel tools for the diagnosis of esophageal cancer. This study innovatively combines muscle imaging features with conventional esophageal imaging features to construct deep learning diagnostic models. Methods: This retrospective study included 1066 patients undergoing radical esophagectomy. Preoperative computed tomography (CT) images covering esophageal, stomach, and muscle (bilateral iliopsoas and erector spinae) regions were segmented automatically with manual adjustments. Diagnostic models were developed using deep learning (2D and 3D neural networks) and traditional machine learning (11 algorithms with PyRadiomics-derived features). Multimodal features underwent Principal Component Analysis (PCA) for dimension reduction and were fused for final analysis. Results: Comparative analysis of 1066 patients’ CT imaging revealed the muscle-based model outperformed the esophageal plus stomach model in predicting N2 staging (0.63 ± 0.11 vs. 0.52 ± 0.11, p = 0.03). Subsequently, multimodal fusion models were established for predicting pathological subtypes, T staging, and N staging. The logistic regression (LR) fusion model showed optimal performance in predicting pathological subtypes, achieving accuracy (ACC) of 0.919 in the training set and 0.884 in the validation set. For predicting T staging, the support vector machine (SVM) model demonstrated the highest accuracy, with training and validation accuracies of 0.909 and 0.907, respectively. The multilayer perceptron (MLP) fusion model achieved the best performance among all models tested for N staging prediction, although the accuracy remained moderate (ACC = 0.704 in the training set and 0.685 in the validation set), indicating potential for further optimization. Fusion models significantly outperformed single-modality models. Conclusions: Based on CT imaging data from 1066 patients, this study systematically constructed predictive models for pathological subtypes, T staging, and N staging of esophageal cancer. Comparative analysis of models using esophageal, esophageal plus stomach, and muscle modalities demonstrated that muscle imaging features contribute to diagnostic accuracy. Multimodal fusion models consistently showed superior performance. Full article

To investigate the genetic diversity and structure of farmed Chinese three-keeled pond turtles (Mauremys reevesii), we performed whole-genome resequencing on 238 individuals from eight farms across six Chinese regions. Genetic diversity indices (nucleotide diversity π, inbreeding coefficient F_HOM, polymorphism information content PIC, observed heterozygosity Ho), principal component analysis (PCA), phylogenetic reconstruction, and population structure analysis were integrated. The results revealed that the Guangdong Maoming (MM) and Anhui Wuwei (WW) populations exhibited the highest genetic diversity (MM: PIC = 0.149, Ho = 0.299; WW: PIC = 0.144, Ho = 0.287), while the Guangdong Huizhou (HZ) and Hunan Changhan (CH) populations showed the lowest diversity due to elevated inbreeding coefficients (HZ: F_HOM = 0.043; CH: F_HOM = 0.041). Low genetic differentiation (F_st = 0.00043–0.04758) indicated limited population divergence. However, PCA and phylogenetic analysis demonstrated that MM and Guangxi Pingxiang (PX) populations formed distinct genetic clusters, suggesting that management differences might contribute to their genetic uniqueness. Admixture analysis identified K = 2 (based on the lowest cross-validation error) as the optimal ancestral cluster number, with MM and PX populations displaying admixed genetic backgrounds while others showed homogeneous compositions. Conservation priorities should focus on preserving MM and PX’s unique genetic resources, introducing genetic material to high-inbreeding populations, and establishing interregional breeding networks. This study provides genomic insights for germplasm conservation and sustainable utilisation of M. reevesii. Full article

The rapid development of urban subway network is prompting higher requirements for daylighting in subway stations. The skylight daylighting space of shallow buried subway stations not only improves the quality of light environment but also brings challenges for the optimization of light and thermal performance, especially in areas with hot summers and cold winters. In this paper, key parameters such as illumination, air temperature, and the black sphere temperature of skylight and artificial lighting areas at stations A and B in Shanghai were tested with a field test system. The results show that the light environment in the skylight areas was significantly improved, but the need for regulation and control of the thermal environment increased. Combined with response surface analysis, 10 sample models for two types of daylighting space (partitioned and open atrium styles) were studied and constructed, including 254 simulated working conditions. The results reveal that design parameters such as the number, aspect ratio, depth of light openings, and skylight angle have significant effects on combined energy consumption. The decentralized double slope roof daylighting space has the best performance in partitioned and open atrium-style public areas, and combined energy consumption can be reduced to 385.14 kWh/m². The optimization strategies proposed in this study can provide a quantitative basis for the skylight design of shallow buried subway stations and an important reference for the design of low-carbon and energy-saving underground spaces. Full article

Spodoptera frugiperda, known as the fall armyworm (FAW), a major invasive pest in corn, is rapidly spreading all over the world. Similarly to other Lepidoptera insects, FAW pupae usually develop in soil. Therefore, the soil moisture level is expected to be an important factor impacting their growth. In order to study the development and emergence of FAW pupae in a 100% soil moisture environment, three factors were selected for experiments in this study: the duration of saturated (100%) moisture treatment (0 h, 24 h, 48 h, and 72 h), the initial soil moisture before the larvae entered the soil (0 and 50%), and pupal age (1 day, 4 days, and 7 days). We discovered that (1) the emergence percentage of FAW pupae decreased with an increase in the saturated soil moisture treatment time, and the emergence percentage dropped to 0 after 72 h of continuous treatment; (2) the younger the age of FAW pupae, the more susceptible they were to being affected by saturated soil moisture treatment, and the emergence percentage of 7-day-old pupae was higher than that of 1-day-old pupae; and (3) FAW larvae that pupated in dry soil (0% moisture) had pupae with higher survival rates under subsequent 100% soil moisture stress, whereas those pupating in moderately moist soil (50% moisture) had lower survival rates under the same condition. Our study showed that the initial moisture level of the soil and the length of time the soil is saturated have a significant impact on FAW pupal development. The three factors of excessive stress time, wet initial soil moisture (50%), and lower pupal age ultimately lead to a decrease in the emergence percentage and survival rate of FAW pupae. Full article

SINEs are one type of the most frequently found DNA repetitive sequences in the eukaryotic genome. The polymorphism generated by SINE insertion may affect proximal host genes and even cause phenotypic variations in domestic animals. Glycine N-acyltransferase-like 3 (GLYATL3) is a member of the N-acyltransferase family which may play a role in amino acid and fatty acid metabolism. Previous studies have identified short interspersed nuclear element (SINE) insertion sites in the 5′UTR region of GLYATL3. This study investigated the effects of the 294 bp SINE insertion on GLYATL3 expression and phenotypic variation. The polymerase chain reaction (PCR) was used to determine the distribution of GLYATL3-SINE-RIP in 15 pig breeds. SINE insertions were absent in hybrid pigs and present in all purebred pigs. Correlation analysis further revealed significant differences in SINE+/+ and SINE−/− individuals when they reached 30 kg of body weight. In light of these findings, qPCR revealed that the SINE insertion significantly increased GLYATL3 expression in the cerebellum of Mi pigs. Additionally, dual-luciferase reporter assays confirmed that the SINE insertion significantly enhanced the activity of the Oct4 promoter. Preliminary evidence indicates the SINE insertion may modulate an increase in the growth rate of pigs through transcriptional regulation of GLYATL3. As a new type marker, this SINE-insertion polymorphism may assist genetic selection to optimize growth traits in porcine breeding programs. Full article

Background: Paratuberculosis (PTB) is a chronic wasting disease mainly caused by Mycobacterium avium subsp. paratuberculosis (MAP) in ruminants. It is difficult to diagnose, prevent, treat, and eradicate, thereby causing serious economic losses to the livestock industry. Therefore, finding a detection method with high sensitivity and specificity is crucial to preventing and controlling PTB. Methods: A total of 1585 fresh fecal samples were collected from 12 prefectures and cities across Inner Mongolia between March 2022 and October 2024. The samples were subjected to pretreatment, followed by DNA extraction. Subsequently, MAP detection and genotyping were performed using a two-step qPCR method. Results: The overall prevalence of MAP in ovines was 3.34% (53/1585), with the prevalence in 12 prefectures and cities ranging from 0% (0/100) to 7.73% (15/194). In the eastern, central, and western regions, the prevalence rates were 4.74% (31/654), 3.68% (14/394), and 1.49% (8/537); in small-scale and intensive farms, they were 3.23% (22/682), and 3.56% (31/903); and in goats and sheep, they were 0.91% (2/219) and 4.98% (36/723), respectively. The overall prevalence rates of C- and S-type MAP were 2.90% (46/1585) and 0.44% (7/1585), respectively. Conclusions: To the best of our knowledge, this study is the first to conduct an epidemiological investigation of PTB in sheep across all nine cities and three leagues in Inner Mongolia and to perform MAP typing on a large scale. It elucidated the differences in the prevalence of PTB in different regions of Inner Mongolia and found that geographical location and sheep breed are potential risk factors for the differences in MAP prevalence. Furthermore, it has been shown that C- and S-type MAP coexist in the eastern and central regions of Inner Mongolia. Full article

The unity of material and spiritual civilization is among the important criteria for sustainable development and modernization construction. However, defining the relationship between the two has posed a challenge to researchers. In terms of spiritual civilization, many studies on dialect maps reflect the dialect characteristics and cultural features of different regions. Regarding material civilization, changes in land use and behavior have attracted the attention of many scholars, who have extensively discussed their regional heterogeneity. However, few studies have focused on the connection between the two, and discussions on the possible bidirectional interaction between dialects and land use have been limited. Thus, in order to bridge the gap between the spiritual civilization related to language and the material civilization related to land use, this study proposes an interactive theoretical framework and conducts an in—depth analysis by taking Anhui Province in China as an example. Firstly, it comprehensively identifies the dialect types within Anhui Province and maps the dialects. This fundamental work provides a crucial basis for understanding the distribution of different dialect regions. Subsequently, a profound analysis of the spatiotemporal changes in land use in this province over time is carried out. To further explore the characteristics of land use behaviors, this study employs the Latent Dirichlet Allocation (LDA) model to mine the latent semantic topics in the land use-related data, thus enabling a more detailed understanding of the diverse patterns of land use behaviors in different regions. Finally, by uncovering the characteristics of land use changes and behavior differences in different dialect regions, this study explores the possible bidirectional interaction mechanisms. The results show that significant spatial heterogeneity in land use behavior and its driving factors can be observed within different dialect regions. Its bidirectional interaction is manifested in land use behaviors regulating people’s activities through constructing “fields” and forming habits that influence regional dialects and cultures. Meanwhile, under mobility mechanisms, new dialect systems replace indigenous languages in immigration destinations. Land use methods from emigration areas are spread through convenient communication, affecting the cultural psychology and land use behaviors of social groups in immigration destinations. This study expands the boundaries of linguistic and cultural geography, offering a new perspective for the identification of spatial differentiation and new ideas for the governance of spatial differences. Full article

Machine vision systems have become key unmanned vehicle (UAV) sensing systems. However, under different weather conditions, the lighting direction and the selection of exposure parameters often lead to insufficient or missing object features in images, which could fail to perform various tasks. As a result, images need to be restored to secure information that is accessible when facing a light exposure difference environment. Many applications require real-time and high-quality images; therefore, efficiently restoring images is also important for subsequent tasks. This study adopts supervised learning to solve the problem of images under lighting discrepancies using a U-Net as our main architecture of the network and adding suitable modules to its encoder and decoder, such as inception-like blocks, dual attention units, selective kernel feature fusion, and denoising blocks. In addition to the ablation study, we also compared the quality of image light restoration with other network models using BAID and considered the overall trainable parameters of the model to construct a lightweight, high-exposure-difference image restoration model. The performance of the proposed network was demonstrated by enhancing image detection and recognition. Full article

Monitoring mangrove phenology requires frequent, high-resolution remote sensing data, yet satellite imagery often suffers from coarse resolution and cloud interference. Traditional methods, such as denoising and spatiotemporal fusion, faced limitations: denoising algorithms usually enhance temporal resolution without improving spatial quality, while spatiotemporal fusion models struggle with prolonged data gaps and heavy noise. This study proposes an optimized mangrove phenology extraction approach (OMPEA), which integrates Landsat and MODIS data with a denoising algorithm (e.g., Gap Filling and Savitzky–Golay filtering, GF–SG) and a spatiotemporal fusion model (e.g., Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model, ESTARFM). The key of OMPEA is that GF–SG algorithm filled data gaps from cloud cover and satellite transit gaps, providing high-quality input to ESTARFM and improving its accuracy of NDVI imagery reconstruction in mangrove phenology extraction. By conducting experiments on the GEE platform, OMPEA generates 1-day, 30 m NDVI imagery, from which phenological parameters (i.e., the start (SoS), end (EoS), length (LoS), and peak (PoS) of the growing season) are derived using the maximum separation (MS) method. Validation in four mangrove areas along the coastal China shows that OMPEA significantly improves the potential to capture mangrove phenology in the presence of incomplete data. The OMPEA significantly increased usable data, adding 7–33 Landsat images and 318–415 MODIS images per region. The generated NDVI series exhibits strong spatiotemporal consistency with original data (R²: 0.788–0.998, RMSE: 0.007–0.253) and revealed earlier SoS and longer LoS at lower latitudes. Cross-correlation analysis showed a 2–3 month lagged effects of temperature on mangroves’ growth, with precipitation having minimal impact. The proposed OMPEA improves the possibility of capturing mangrove phenology under non-continuous and low-resolution data, providing valuable insights for large-scale and long-term mangrove conservation and management. Full article

Integrative conservation research on animal behavior and nutritional health can contribute to the ex situ conservation of endangered species. Stereotypic behavior, a repetitive behavior without practical function, is associated with animal welfare in its manner and frequency for captive animals. Exploring the potential relationship between stereotypic behavior and internal factors, such as intestinal flora, could improve ex situ conservation, especially for endangered species. In this study, we analyzed the typical behavior characteristics of the endangered sun bears (Helarctos malayanus) under captive conditions based on the behavior sampling method. The seasonal and annual changes in the intestinal flora of H. malayanus in captivity were studied by 16S rDNA high-throughput sequencing technology based on non-invasive fecal sample collection. This study provides the first evidence of a potential association between the gut microbiota and stereotypic behavior characteristics of captive H. malayanus. The results can significantly improve our understanding of the stereotypical behavior of H. malayanus in captivity and contribute to the captive breeding and conservation efforts of this endangered species. Full article

Bisphenol A (BPA) is a prevalent environmental contaminant found in plastics and known for its endocrine-disrupting properties, posing risks to both human health and the environment. Despite its widespread presence, the impact of BPA on papillary thyroid cancer (PTC) progression, especially under realistic environmental conditions, is not well understood. This study examined the effects of BPA on PTC using a 3D thyroid papillary tumor spheroid model, which better mimicked the complex interactions within human tissues compared to traditional 2D models. Our findings demonstrated that BPA, at environmentally relevant concentrations, could induce significant changes in PTC cells, including a decrease in E-cadherin expression, an increase in vimentin expression, and reduced thyroglobulin (TG) secretion. These changes suggest that BPA exposure may promote epithelial–mesenchymal transition (EMT), enhance invasiveness, and reduce cell differentiation, potentially complicating treatment, including by increasing resistance to radioiodine therapy. This research highlights BPA’s hazardous nature as an environmental contaminant and emphasizes the need for advanced in vitro models, like 3D tumor spheroids, to better assess the risks posed by such chemicals. It provides valuable insights into the environmental implications of BPA and its role in thyroid cancer progression, enhancing our understanding of endocrine-disrupting chemicals. Full article

Rapeseed (Brassica napus L.) is one of the four major oilseed crops in the world and is rich in fatty acids. Changes in the fatty acid composition affect the quality of rapeseed. Fatty acids play various roles in plants, but the functions of the genes involved in the fatty acid composition during plant development remain unclear. β-Ketoacyl-CoA synthase (KCS) is a key enzyme involved in the elongation of fatty acids. Various types of fatty acid products are used to build lipid molecules, such as oils, suberin, wax, and membrane lipids. In B. napus, BnaKCSA8 and BnaKCSC3 belong to the KCS family, but their specific functions remain unclear. This study cloned BnaKCSA8 and BnaKCSC3 from Brassica napus L. and analyzed their functions. The gene structures of BnaKCSA8 and BnaKCSC3 were similar and they were localized to the endoplasmic reticulum (ER). In yeast, overexpression of BnaKCSA8 increased the ratios of palmitoleic acid and oleic acid, while BnaKCSC3 decreased the ratios of oleic acid. In Arabidopsis, overexpression of BnaKCSA8 and BnaKCSC3 lead to an increase in the proportion of linoleic acid and a decrease in the erucic acid. In summary, BnaKCSA8 and BnaKCSC3 altered the composition ratios of fatty acids. These findings lay the foundation for an understanding of the role of KCS in the fatty acids in rapeseed, potentially improving its health and nutritional qualities. Full article

Paratuberculosis (PTB), primarily caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic infection that affects ruminants and is difficult to prevent, diagnose, and treat. Investigating how MAP infections affect the gut microbiota in sheep can aid in the prevention and treatment of ovine PTB. This study examined fecal samples from eight small-tail Han sheep (STHS) at various stages of infection and from three different field areas. All samples underwent DNA extraction and 16S rRNA sequencing. Among all samples, the phyla p. Firmicutes and p. Bacteroidota exhibited the highest relative abundance. The dominant genera in groups M1–M6 were UCG-005, Christensenellaceae_R-7_group, Rikenellaceae_RC9_gut_group, Akkermansia, UCG-005, and Bacteroides, whereas those in groups A–C were Christensenellaceae_R-7_group, Escherichia–Shigella, and Acinetobacter, respectively. The microbial community structure varied significantly among groups M1–M6. Specifically, 56 microbiota consortia with different taxonomic levels, including the order Clostridiales, were significantly enriched in groups M1–M6, whereas 96 microbiota consortia at different taxonomic levels, including the family Oscillospiraceae, were significantly enriched in groups A–C. To the best of our knowledge, this is the first study to report that MAP infection alters the intestinal microbiota of STHS. Changes in p. Firmicutes abundance can serve as a potential biomarker to distinguish MAP infection and determine the infection stage for its early diagnosis. Our study provides a theoretical basis for the treatment of PTB by regulating the intestinal microbiota, including p. Firmicutes. Full article