Search Results (28)

The gut microbiota of macaques, highly homologous to humans in biological characteristics and metabolic functions, serves as an ideal model for studying the mechanisms of human intestinal diseases and therapeutic approaches. A comprehensive characterization of the macaque gut microbiota provides unique insights into human health and disease. This study employs metagenomic sequencing to assess the gut microbiota of wild M. mulatta brevicaudus across various ages, sexes, and physiological states. The results revealed that the dominant bacterial species in various age groups included Segatella copri and Bifidobacterium adolescentis. The predominant bacterial species in various sexes included Alistipes senegalensis and Parabacteroides (specifically Parabacteroides merdae, Parabacteroides johnsonii, and Parabacteroides sp. CT06). The dominant species during lactation and non-lactation periods were identified as Alistipes indistinctus and Capnocytophaga haemolytica. Functional analysis revealed significant enrichment in pathways such as global and overview maps, carbohydrate metabolism and amino acid metabolism. This study enhances our understanding of how age, sex, and physiological states shape the gut microbiota in M. mulatta brevicaudus, offering a foundation for future research on (1) host–microbiome interactions in primate evolution, and (2) translational applications in human health, such as microbiome-based therapies for metabolic or immune-related disorders. Full article

Hyperlipidemia is one of the most prevalent metabolic disorders worldwide. It is a significant risk factor for a range of cardiovascular diseases, including acute pancreatitis, fatty liver disease, atherosclerosis, and coronary heart disease. In clinical practice, the management of hyperlipidemia is hindered by numerous challenges. One of the critical issues is that traditional lipid-lowering drugs often require long-term or even lifelong administration, potentially inducing a range of adverse effects that compromise patient compliance and therapeutic efficacy. Therefore, there is an urgent need to develop safer and more effective strategies for the prevention and adjunctive treatment of hyperlipidemia with the aim of reducing the risk of disease and over-reliance on medication. Recent studies have revealed a close relationship between hyperlipidemia and related metabolic disorders involving gut microbiota dysbiosis, and the administration of probiotics has been shown to improve lipid metabolism homeostasis. This review summarizes the molecular mechanisms of probiotics in hyperlipidemia treatment and the latest advances in probiotic research on lipid metabolism, enumerates the experimental and clinical applications of probiotic-based therapies, introduces methods for screening and identifying probiotics with lipid-lowering functions, and, for the first time, summarizes the roles of emerging technologies such as functional genomics and in vivo zebrafish-on-a-chip models in studying the lipid-lowering efficacy of probiotics, providing insights for researchers. By facilitating a deeper understanding of the mechanisms whereby probiotics reduce blood lipid levels and furthering the development of multifaceted screening methods, we hope that we can achieve high-throughput and efficient screening of probiotics with lipid-lowering functions, thereby promoting the sustainable, high-quality, and rapid development of the probiotics industry. Full article

Background: Camellia species are highly ornamental but sensitive to habitat temperature, making cross-border domestication challenging. Methods: In this study, physiological indicators and transcriptome data of Camellia reticulata ‘shizhitou’ were analyzed to identify key factors involved in the response to cold. Results: The findings provide a scientific basis for the conservation of Camellia germplasm resources and breeding of cold-tolerant varieties. Under prolonged low-temperature stress, significant changes were observed in the physiological indices of C. reticulata ‘shizhitou’. Among soluble substances, soluble protein content continuously increased, while soluble sugar content exhibited a fluctuation pattern of increase–decrease–increase. Under prolonged low-temperature stress, significant changes were observed in the physiological indexes of C. reticulata ‘shizhitou’, while soluble sugar content exhibited a fluctuation pattern of increase–decrease–increase. Overall, soluble sugar and soluble protein contents were significantly positively correlated. Chlorophyll content initially decreased and then increased, whereas peroxidase (POD) and catalase (CAT) activities fluctuated and were negatively correlated with chlorophyll content. Malondialdehyde (MDA) content showed an irregular fluctuation trend. A total of 56,424 unigenes were obtained by transcriptome sequencing, of which 39,278 were annotated, while 10,816 differentially expressed genes (DEGs) were identified, including 5748 up-regulated and 5068 down-regulated genes, with 143 DEGs commonly shared across conditions. Congclusions: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that low-temperature stress significantly influenced glucose metabolism, lipid metabolism, and amino acid metabolism, and the core pathways of cold stress included zeatin synthesis, hormone signaling, and galactose metabolism. Both physiological responses and transcriptome-based enrichment of DEGs indicate that the redox system and metabolic pathways play crucial regulatory roles in C. reticulata under cold stress. Full article

Topsoil organic carbon (SOC, 0–20 cm) is crucial for terrestrial carbon stocks and the global carbon cycle. This study integrated field survey data, re-analysis climatic data, and remote sensing-derived environmental factors to examine SOC distribution and its drivers across forest types on Hainan Island using machine learning models and statistical analysis. The results showed that univariate analysis had limited explanatory power for forest SOC, with terrestrial plantations exhibiting significantly lower SOC than mangroves and natural forests. For mangroves, vapor pressure deficit (VPD) was the most influential factor, followed by precipitation (PRE), the normalized difference vegetation index (NDVI), and forest age; meanwhile, for terrestrial forests, VPD, altitude, PRE, and NDVI were vital drivers. The optimal models demonstrated relatively stronger predictive performance (R² = 0.71 for mangroves; R² = 0.81 for terrestrial forests). Mangroves showed higher average SOC (27.91 g/kg) than terrestrial forests (15.82 g/kg), while higher concentrations in the central–western region were attributed to natural terrestrial forests. This study reveals the spatial variation patterns of forest SOC and its environmental regulation mechanisms on Hainan Island, providing important references for forest carbon stock management and environmental protection. Full article

Laser powder bed fusion (L-PBF), as one of the additive manufacturing (AM) or 3D printing techniques, has been widely used for the net-shape fabrication of high-entropy alloys (HEAs). However, microstructural defects are often present in the FeCoNiCrMn high-entropy alloy fabricated via L-PBF, which necessitate subsequent heat treatment for optimization. In this study, FeCoNiCrMn HEA samples were fabricated using L-PBF and subsequently annealed at different temperatures. The influence of heat treatment on the microstructure and mechanical properties was investigated. The results revealed that the cellular substructure remained stable at 650 °C, while at 1100 °C dislocation recovery and compositional homogenization occurred, leading to the dissolution of the cellular substructure. After annealing at 1200 °C, the elongation of the alloy increased by 82%, while the yield strength and ultimate tensile strength decreased by 37% and 10%, respectively, compared to the as-built state. The cellular substructure not only contributed to strength through dislocation strengthening but also acted as nucleation sites for subsequent twinning, resulting in improved work hardening capability. Annealing-induced grain growth and substructure elimination improved the capacity of coordinated plastic deformation, while weakening the contribution of grain rotation and twinning mechanisms. Full article

The genus Mallotus oblongifolius (MO), a member of the Euphorbia family, exhibits a predominant distribution in Hainan Island and has been proven to possess diverse medicinal attributes. Research indicates that ultramicro-grinding fully exposes the active ingredients of Mallotus oblongifolius, enhancing bioavailability and efficacy, compared to before. Our study investigates the effects of ultrafine powder of Mallotus oblongifolius (MOUP) on Hainan pigs. A total of sixty-four healthy castrated pigs (ternary hybrid pigs, Duroc × Duroc × Tunchang) with comparable initial body weight (BW, 68.06 ± 1.03 kg, 150 days old) were allocated randomly into four groups: the control group (CONT), the antibiotic group (ANTI), the 0.1% MOUP group (PT1), and the 0.5% MOUP group (PT2). There were four replicate pens per treatment with four pigs per pen. The pre-test lasted for 7 days and the formal test lasted for 70 days. The CONT group was fed the basal diet, the ANTI group was fed the basal diet supplemented with 300 mg/kg colistin sulfate, the PT1 group was fed the basal diet supplemented with 0.1% MOUP, and the PT2 group was fed the basal diet supplemented with 0.5% MOUP. The findings of our study indicate that the inclusion of colistin sulfate and MOUP in the diet did not have any significant impact on the production performance or carcass indicators of Hainan pigs compared to the CONT group. However, it is noteworthy that the addition of MOUP to the diet resulted in a significant improvement in the lightness, tenderness, muscle fiber morphology, amino acid composition, and antioxidant activity of the longissimus dorsi muscle, particularly in the PT2 group, compared to the CONT group. In conclusion, the present study has demonstrated that the inclusion of MOUP in the dietary regimen yields enhancements in the meat quality of Hainan pigs, particularly when supplemented at a concentration of 0.5%. Full article

The continuous advancement of urbanization and the expansion of cities inevitably have certain impacts on urban wildlife. Birds are a highly visible group of urban wildlife, widely distributed and sensitive to environmental changes. Birds’ song is an important way of conveying information; the effective conveyance and transmission of bird songs are crucial for attracting mates and successful reproduction. However, the impact of urban development on the songs of many birds remains unknown. This study compared the differences in song characteristics (maximum frequency, minimum frequency, main frequency, and duration) of the Eurasian Nuthatch (Sitta europaea) at six different research sites with different levels of urbanization, in order to explore the song response patterns of birds to urbanization. The results indicate that urbanization leads to a reduction in avian song diversity and a convergence in song parameters. Birds in different life history stages show inconsistent responses to urbanization. During the overwintering period, there are no significant differences in the minimum frequency and duration of the Eurasian Nuthatch’s song, almost no significant differences in the maximum frequency, and the main frequency of the Eurasian Nuthatch’s song, as distributed in the Forest Botanical Garden (FBG) shows some differences compared to other study sites. During the breeding period, there are no significant differences in the main frequency of the Eurasian Nuthatch’s song, while other parameters exhibit varying degrees of differences. Comprehensive analysis reveals that urbanization has varying impacts on the song diversity of the Eurasian Nuthatch across different life history stages. During the overwintering period, there is a significant reduction in song diversity, with a pronounced homogenization effect; during the breeding period, the birds’ songs are more diverse, with only the main frequency showing a significant homogenization effect. It is speculated that birds may strike a certain balance between adapting to urbanization and survival reproduction. Full article

The mismatch between urban livability and population distribution can result in overcrowding and excessive pressure on ecosystem services if population growth surpasses urban capacity. Conversely, if urban expansion outpaces population needs, it can lead to underutilized infrastructure and inefficient land use. This study aims to assess the coordination between urban livability and population distribution in five major urban agglomerations in China: Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), Mid-Yangtze River (MYR), and Chengdu–Chongqing (CC). A comprehensive index for urban livability is established, from the aspects of social–economic development and ecosystem service. Additionally, a Coordination Distance Index (CDI) is developed to measure the relationship between urban livability and population distribution. Data from 2010, 2015, and 2020 are analyzed to evaluate the coordination levels and trends across the five urban agglomerations. The results show that from 2010 to 2020, most cities within these urban agglomerations experience improvements in their coordination levels, with the most notable advancements in the PRD and YRD regions. By 2020, the PRD and YRD were classified as having “high coordination”, while BTH, MYR, and CC were categorized as having “moderate coordination”. However, certain cities, such as Chengde in BTH, Shanghai in YRD, Ya’an in CC, and Zhuhai in PRD, still exhibited “low coordination”, highlighting areas requiring spatial planning adjustments. This study introduces a method for quantitatively assessing the coordination between urban livability and population distribution, providing essential insights for policymakers and urban planners to refine urbanization development strategies and population regulation policies in China’s major urban agglomerations. Full article

Blueberries are one of the more economically rewarding fruits for fruit growers. Identifying blueberry fruit at different stages of maturity is economically important and can aid fruit growers in planning pesticide applications, estimating yields, and efficiently conducting harvesting operations, among other benefits. Visual methods for identifying the different ripening stages of fruits are increasingly receiving widespread attention. However, due to the complex natural environment and the serious shading caused by the growth characteristics of blueberries, the accuracy and efficiency of blueberry detection are reduced to varying degrees. To address the above problems, in the study presented herein, we constructed an improved YOLOv9c detection model to accurately detect and identify blueberry fruits at different ripening stages. The size of the network was reduced by introducing the SCConv convolution module, and the detection accuracy of the network in complex and occluded environments was improved by introducing the SE attention module and the MDPIoU loss function. Compared to the original model, the mAP0.5 and mAP0.5:0.95 of the improved YOLOv9c network improved by 0.7% and 0.8%, respectively. The model size was reduced by 3.42 MB, the number of model parameters was reduced by 1.847 M, and the detection time of a single image was reduced by 4.5 ms. The overall performance of the detection model was effectively improved to provide a valuable reference for accurate detection and localization techniques for agricultural picking robots. Full article

VW63Z magnesium alloy, known for its high strength-to-weight ratio and excellent mechanical properties, is a promising candidate for applications in the automotive industries. Among the anti-corrosion technologies for VW63Z alloys, organic electrophoretic coatings have gained significant attention due to their ability to provide a uniform and controlled coating thickness, high coating adhesion, and excellent corrosion protection properties. In this work, to investigate the aging behaviors of an organic electrophoretic coating for magnesium alloys, water absorption kinetics curves of the coatings after immersion in 3.5 wt.% NaCl at 20 °C and 40 °C were measured, and parameters such as the saturated water absorption and saturation time of the free film coatings were fitted to determine the densification evolution of the organic coatings. A tensile test was used to test the tensile strength of the organic coating during service to determine the evolution of the strength and toughness of the organic coating. The evolution of wet adhesion of organic coatings with service time was tested by ASTM D4541-02. The impedance spectra of the organic coatings under the above conditions were detected by EIS, and finally, the failure behavior of the organic coatings under immersion was analyzed. Full article

Ga₂O₃, with its large band gap, is a promising material suitable for utilization in solar-blind photodetection. Sapphire with a higher lattice match with Ga₂O₃ was used as the substrate for epitaxial growth of Ga₂O₃. Here, the epitaxial layers of Ga₂O₃ were deposited by MOCVD on patterned sapphire substrates. The structure of epitaxial Ga₂O₃ layers on patterned substrates has been identified by X-ray diffractometry. To investigate the influence of the patterned substrates on the formation of epitaxial layers, thin Ga₂O₃ layers were grown on a flat sapphire substrate under the same conditions. Both types of samples were β-phase. However, no improvement in the layers’ crystalline quality was discovered when utilizing patterned sapphire substrates. In addition, the performance of the obtained two types of Ga₂O₃ photodetectors was compared. The photoelectric properties, such as responsivity, response speed, and detection capability, were different in the case of flat samples. Full article

Bruising is a common occurrence in apples that can lead to gradual fruit decay and substantial economic losses. Due to the lack of visible external features, the detection of early-stage bruising (occurring within 0.5 h) is difficult. Moreover, the identification of stems and calyxes is also important. Here, we studied the use of the short-wave infrared (SWIR) camera and the Faster RCNN model to enable the identification of bruises on apples. To evaluate the effectiveness of early bruise detection by SWIR bands compared to the visible/near-infrared (Vis/NIR) bands, a hybrid dataset with images from two cameras with different bands was used for validation. To improve the accuracy of the model in detecting apple bruises, calyxes, and stems, several improvements are implemented. Firstly, the Feature Pyramid Network (FPN) structure was integrated into the ResNet50 feature extraction network. Additionally, the Normalization-based Attention Module (NAM) was incorporated into the residual network, serving to bolster the attention of model towards detection targets while effectively mitigating the impact of irrelevant features. To reduce false positives and negatives, the Intersection over Union (IoU) metric was replaced with the Complete-IoU (CIoU). Comparison of the detection performance of the Faster RCNN model, YOLOv4P model, YOLOv5s model, and the improved Faster RCNN model, showed that the improved model had the best evaluation indicators. It achieved a mean Average Precision (mAP) of 97.4% and F1 score of 0.87. The results of research indicate that it is possible to accurately and effectively identify early bruises, calyxes, and stems on apples using SWIR cameras and deep learning models. This provides new ideas for real-time online sorting of apples for the presence of bruises. Full article

The pore structure determines the desorption, diffusion and migration of coalbed methane, and the heterogeneity of the pore structure seriously restricts the diffusion and seepage process and productivity of coalbed methane. Therefore, this paper takes eight coal samples in the Linxing area as the research target and uses the high-pressure mercury injection test to describe the pore structure distribution. On this basis, three kinds of single and multifractal models are used to calculate the progressive mercury removal curve, and the correlation analysis is carried out to determine the physical significance of the mercury removal fractal dimension. Finally, the relationship between the fractal dimension of the mercury curve and the pore structure parameters is defined, and the applicability of fractal models in characterizing pore structure heterogeneity is discussed. The conclusions of this paper are as follows. (1) Samples can be divided into two categories according to porosity and mercury removal efficiency. Among them, the mercury removal efficiency of sample 1–3 is higher than 35%, and porosity is less than 9.5%, while those of sample 4–8 are the opposite. The seepage pore volume percentage of sample 1–3 is 35–60%, which is higher than that in sample 4–8. (2) The difference of the samples’ fractal dimension calculated with the Menger and Sierpinski models is small, indicating that the pore structure distribution heterogeneity of the two types is similar. The multifractal model shows that the adsorption pore and macro-pore heterogeneity of sample 4–8 are stronger than those of sample 1–3, and the pore distribution heterogeneity is controlled by the low value of pore volume. (3) The results of the two single fractal calculations show that the pore structure distribution heterogeneity of sample 4–8 is stronger than that of sample 1–3. The multifractal model calculation shows that the adsorption pore distribution heterogeneity of sample 4–8 is stronger, and the low value of pore volume controls the pore distribution heterogeneity. (4) The mercury fractals based on the Menger model can reflect the adsorption pore distribution and macro-pore distribution heterogeneity, while the Sierpinski model can only reflect the adsorption pore distribution heterogeneity at the mercury inlet stage. Full article

Urban forests play a crucial role in both emitting and absorbing atmospheric pollutants. Understanding the ecological processes of biogenic volatile organic compounds (BVOCs) and secondary organic aerosols (SOAs) and their interactions in urban forests can help to assess how they influence air quality. Additionally, exploring the adaptation and feedback mechanisms between urban forests and their surrounding environments can identify new pollutants and potential risks in urban forests. However, the relationship between BVOC emissions and SOA formation is complex due to the influence of meteorological conditions, photochemical reactions, and other factors. This complexity makes it challenging to accurately describe this relationship. In this study, we used time-of-flight mass spectrometry and aerosol particle size spectrometry to monitor concentrations of BVOCs and particulate matter with a diameter less than 1 µm (PM₁; representing SOAs) at a frequency of 10–12 times per min in an urban forest near Shanghai. We then analyzed the temporal changes in concentrations of BVOCs, SOAs, and other chemical pollutants in different periods of the day by using subsequence clustering and causal inference methods. The results showed that after using this method for diurnal segmentation, PM₁ prediction accuracy was improved by 26.77%–47.51%, and the interaction rules of BVOCs and SOAs had sequential interaction characteristics. During the day, BVOCs are an important source of SOAs and have a negative feedback relationship with O₃. From night to early morning, BVOCs have a positive, balanced relationship with O₃, SOAs are affected by wind speed or deposition, BVOCs have no obvious relationship with O₃, and SOAs are affected by temperature or humidity. This study is the first to apply Toeplitz inverse covariance-based clustering and causal inference methods for the high-frequency monitoring of BVOCs and SOAs, revealing the temporal effects and characteristics of BVOCs and SOAs and providing a scientific basis and new methods for understanding the dynamic effects of urban forest communities on the environment. Full article

With the Internet of Vehicles (IOV), a lot of self-driving vehicles (SDVs) need to handle a variety of tasks but have very seriously limited computing and storage resources, meaning they cannot complete intensive tasks timely. In this paper, a joint edge computing and caching based on a Dueling Double Deep Q Network (D3QN) is proposed to solve the problem of the multi-task joint edge calculation and caching process. Firstly, the processes of offloading tasks and caching them to the base station are modeled as optimization problems to maximize system revenues, which are limited by system latency and energy consumption as well as cache space for computing task constraints. Moreover, we also take into account the negative impact of the number of unfinished tasks in relation to the optimization problem—the higher the number of unfinished tasks, the lower the system revenue. Secondly, we use the D3QN algorithm together with the cache models to solve the formulated NP-hard problem and select the optimal caching and offloading action by adopting an e-greedy strategy. Moreover, two cache models are proposed in this paper to cache tasks, namely the active cache, based on the popularity of the task, and passive cache, based on the D3QN algorithm. Additionally, tasks which deal with cache space are updated by computing the expulsion value based on type of popularity. Finally, simulation results show that the proposed algorithm has good performance in terms of the latency and energy consumption of the system and that it improves utilization of cache space and reduces the probability of unfinished tasks. Compared to the Deep Q Network with caching policy, with the Double Deep Q Network with caching policy and Dueling Deep Q Network with caching policy, the system revenue of the proposed algorithm is improved by 65%, 35% and 66%, respectively. The scenario of the IOV proposed in this article can be expanded to larger-scale IOV systems by increasing the number of SDVs and base stations, and the content caching and download functions of the Internet of Things can also be achieved through collaboration between multiple base stations. However, only the cache model is focused on in this article, and the design of the replacement model is not good enough, resulting in a low utilization of cache resources. In future work, we will analyze how to make joint decisions based on multi-agent collaboration for caching, offloading and replacement in IOV scenarios with multiple heterogeneous services to support different Vehicle-to-Everything services. Full article