Search Results (70)

This research is designed to explore the effect of roasting on the release, bioaccessibility, and bioactivity of polyphenols in highland barley (HB). The findings of in vitro digestion indicated that roasting significantly improved the bioaccessibility of polyphenols in HB flour (gastrointestinal digestion stage: raw HB: 187.28%, roasted HB: 285.65%; colonic fermentation stage: raw HB: 188.13%, roasted HB: 255.36%) and enhanced its antioxidant activity. Moreover, the inhibitory impacts of polyphenols on the activities of α -amylase, α-glucosidase, and lipase mainly occur in the small intestine. Roasting increased inhibitory activities of polyphenols on α-amylase, α-glucosidase, and lipase in the small intestine (p < 0.05), with IC50 values of 71.31 ± 1.35 μg FAE/mL, 60.44 ± 1.35 μg FAE/mL, and 52.94 ± 2.51 μg FAE/mL, respectively. HepG2 cells, a human hepatocellular carcinoma cell line, are commonly employed in oxidative stress and antioxidant studies due to their ability to mirror the protective effects of bioactive compounds against oxidative damage in liver cells. This study aimed to establish a model of H₂O₂-induced oxidative stress injury in HepG2 cells and to evaluate the protective effect of digested HB polyphenol extract against oxidative injury. It was found that the polyphenols extracted from roasted HB help reduce reactive oxygen species (ROS) and malondialdehyde (MDA) through increased activities of superoxide dismutase (SOD), glutathione (GSH), catalase (CAT), glutathione peroxidase (GPx), and total antioxidant capacity (T-AOC), thereby providing enhanced defense against oxidative damage in HepG2 cells. The findings of this research pave the way for the development of new functional foods utilizing roasted HB. Full article

All-perovskite tandem solar cells (APTSCs) offer a promising pathway to surpassing the efficiency limits of single-junction photovoltaics. The wide-bandgap (WBG) subcell, serving as the top absorber, plays a critical role in optimizing light harvesting and charge extraction in tandem architectures. This review comprehensively summarizes recent advancements in WBG subcells, focusing on material design, defect passivation strategies, and interfacial engineering to address challenges such as phase instability, halide segregation, and voltage losses. Key innovations, including compositional tuning, additive engineering, and charge transport layer optimization, are critically analyzed for their contributions to efficiency and stability enhancement. Despite significant progress, challenges remain regarding scalability, long-term stability under illumination, and cost-effective fabrication. Future research directions include the development of lead-reduced perovskites, machine learning-guided material discovery, and scalable deposition techniques. This review provides insights into advancing WBG subcells toward high-efficiency, stable, and eco-friendly APTSCs for next-generation solar energy applications. Full article

Semitransparent perovskite solar cells (PSCs) that possess a high-power conversion efficiency (PCE) and high average visible light transmittance (AVT) can be employed in applications such as photovoltaic windows. In this study, a bifacial modification comprising a buried layer of [4-(3,6-Dimethyl-9H-carbazol-9-yl) butyl] phosphonic acid (Me-4PACz) and a surface passivator of 2-(2-Thienyl) ethylamine hydroiodide (2-TEAI) was proposed to enhance device performance. When the concentrations of Me-4PACz and 2-TEAI were 0.3 mg/mL and 3 mg/mL, opaque PSCs with a 1.57 eV perovskite absorber achieved a PCE of 22.62% (with a V_OC of 1.18 V) and retained 88% of their original value after being stored in air for 1000 h. By substituting a metal electrode with an indium zinc oxide electrode, the resulting semitransparent PSCs showed a PCE of over 20% and an AVT of 9.45%. It was, therefore, suggested that the synergistic effect of Me-4PACz and 2-TEAI improved the crystal quality of perovskites and the carrier transport in devices. When employing an absorber with a wider bandgap (1.67 eV), the corresponding PSC obtained a higher AVT of 20.71% and maintained a PCE of 18.73%; these values show that a superior overall performance is observed compared to that in similar studies. This work is conductive to the future application of semitransparent PSCs. Full article

The ocean is a significant global reservoir of uranium (U) and thorium (Th). These elements can be incorporated into marine sediments through processes involving organic matter (OM), redox conditions, terrigenous inputs, and mineral interactions. Helium generated through the radioactive decay of U and Th within geological formations represents a critical potential resource. Marine black shales, which are rich in U and Th, are widespread in the Ediacaran Doushantuo Formation of the Upper Yangtze Platform, making them a key target for helium exploration. However, there is limited research on the mechanisms behind U and Th accumulation in these shales. This study focuses on shales from the Doushantuo Formation in Chongqing, China, aiming to explore the mechanisms of U and Th accumulation and assess the potential for helium generation, and argillaceous dolomites are included for comparative analysis. The results show that the average U and Th content in the black shales (17.58 and 9.78 ppm, respectively) is higher than that of argillaceous dolomites (3.52 and 2.75 ppm, respectively). Uranium mainly comes from authigenic precipitation and hydrothermal inputs, while thorium is primarily sourced from terrigenous and hydrothermal inputs. The semi-humid climate in the provenance area facilitated parent rock weathering, with atmospheric precipitation and river systems transporting U and Th to the ocean. However, excessive terrigenous input can dilute the U and Th content in the sediments. In the shales, uranium is primarily adsorbed and/or complexed by organic matter (OM), with the anoxic–euxinic sedimentary environment and high OM content (TOC = 0.06–34.58 wt.%, r = 0.95) promoting U accumulation. Thorium accumulation is largely controlled by adsorption onto clay minerals. The total amount of helium generated from the Doushantuo shales is estimated to be 7.20 × 10¹⁰ m³. Full article

This study examines the potential distribution of Mackerel scad (Decapterus macarellus) in the South China Sea under future climate scenarios (SSP 1.26, SSP 2.45, SSP 5.85) using an ensemble species distribution model (SDM). Key environmental variables included sea surface salinity (SSS), sea surface height (SSH), sea surface temperature (SST), mixed-layer depth (MLD), chlorophyll-a concentration (CHL), and sea-bottom temperature (SBT). Results show that SST and MLD are the primary drivers of habitat suitability, with current suitable habitats concentrated in the northern offshore areas. Projections for the 2050s and 2090s indicate a reduction in suitable habitats, particularly under high-emission scenarios, with more gradual reductions under low-emission scenarios. Habitat loss is most pronounced in the northern South China Sea, while the central region is projected to see an expansion of suitable habitats. These findings highlight the climate impact on D. macarellus distribution and inform sustainable management strategies for the species in the region. Full article

The low solubility of CO₂ in water leads to massive CO₂ emission and extremely low CO₂ utilization in succinic acid (SA) biosynthesis. To enhance microbial CO₂ utilization, micro-nano bubbles (MNBs) were induced in SA biosynthesis by E. coli Suc260 in this study. The results showed that MNB aeration decreased CO₂ emissions and increased CO₂ solubility in the medium significantly. The CO₂ utilization of MNB aeration was 129.69% higher than that of bubble aeration in atmospheric fermentation. However, MNBs showed a significant inhibitory effect on bacterial growth in the pressurized environment, although a two-stage aerobic–anaerobic fermentation strategy weakened the inhibition. The biofilm-enhanced strain E. coli Suc260-CsgA showed a strong tolerance to MNBs. In pressurized fermentation with MNB aeration, the actual CO₂ utilization of E. coli Suc260-CsgA was 30.63% at 0.18 MPa, which was a 6.49-times improvement. The CO₂ requirement for SA synthesis decreased by 83.4%, and the fugitive emission of CO₂ was successfully controlled. The activities of key enzymes within the SA synthesis pathway were also maintained or enhanced in the fermentation process with MNB aeration. These results indicated that the biofilm-enhanced strain and CO₂-MNBs could improve carbon fixation efficiency in microbial carbon sequestration. Full article

Niobium pentoxide (T-Nb₂O₅) is a promising anode material for dual-ion batteries due to its high lithium capacity and fast ion storage and release mechanism. However, T-Nb₂O₅ suffers from the disadvantages of poor electrical conductivity and fast cycling capacity decay. Herein, a nitrogen-doped three-dimensional porous carbon (RMF) was prepared for loading niobium pentoxide to construct a composite system with excellent electrochemical performance. The obtained T-Nb₂O₅/RMF composites have a well-developed pore structure and a high specific surface area of 1568.5 m² g⁻¹, which could effectively increase the contact area between the material and electrolyte, improving the electrode reaction and lithium-ion transfer diffusion. Nitrogen doping increased surface polarity, creating more active sites and accelerating the electrode reaction rate. The introduction of T-Nb₂O₅ imparted high power density and excellent cycling stability to the battery. The composites exhibited good electrochemical performance when used as dual-ion battery anode, with a stable cycle life of 207.2 mA h g⁻¹ at 1 A g⁻¹ current density after 650 cycles and great rate performance of 181.5 mA h g⁻¹ at 5A g⁻¹ was also obtained. This work provides the possibility for applying T-Nb₂O₅/RMF as an anode for a high-performance dual-ion battery. Full article

The navigation obstacle avoidance method based on deep reinforcement learning has stronger adaptability and better performance compared to traditional algorithms in complex unknown dynamic environments, and has been widely developed and applied. However, when using multimodal information input, deep reinforcement learning strategy networks extract features that differ significantly between simulated and real world environments, resulting in poor algorithm output strategies and difficulty in transferring models obtained from simulation training to actual environments. To address the aforementioned issues, this article utilizes image segmentation to narrow the gap in environmental features, integrates multimodal information, and designs a deep reinforcement learning multimodal local obstacle avoidance algorithm, MMSEG-PPO, based on proximal strategy optimization algorithms. The algorithm is then ported to practical environments for deployment and testing. The experiment shows that the algorithm proposed in this article reduces the gap between the simulation environment and the actual environment, and has better performance and generalization when transplanted to the real world environment. Full article

To satisfy the obstacle avoidance requirements of unmanned agricultural machinery during autonomous operation and address the challenge of rapid obstacle detection in complex field environments, an improved field obstacle detection model based on YOLOv8 was proposed. This model enabled the fast detection and recognition of obstacles such as people, tractors, and electric power pylons in the field. This detection model was built upon the YOLOv8 architecture with three main improvements. First, to adapt to different tasks and complex environments in the field, improve the sensitivity of the detector to various target sizes and positions, and enhance detection accuracy, the CBAM (Convolutional Block Attention Module) was integrated into the backbone layer of the benchmark model. Secondly, a BiFPN (Bi-directional Feature Pyramid Network) architecture took the place of the original PANet to enhance the fusion of features across multiple scales, thereby increasing the model’s capacity to distinguish between the background and obstacles. Third, WIoU v3 (Wise Intersection over Union v3) optimized the target boundary loss function, assigning greater focus to medium-quality anchor boxes and enhancing the detector’s overall performance. A dataset comprising 5963 images of people, electric power pylons, telegraph poles, tractors, and harvesters in a farmland environment was constructed. The training set comprised 4771 images, while the validation and test sets each consisted of 596 images. The results from the experiments indicated that the enhanced model attained precision, recall, and average precision scores of 85.5%, 75.1%, and 82.5%, respectively, on the custom dataset. This reflected increases of 1.3, 1.2, and 1.9 percentage points when compared to the baseline YOLOv8 model. Furthermore, the model reached 52 detection frames per second, thereby significantly enhancing the detection performance for common obstacles in the field. The model enhanced by the previously mentioned techniques guarantees a high level of detection accuracy while meeting the criteria for real-time obstacle identification in unmanned agricultural equipment during fieldwork. Full article

Tritium (³H) is one of the most critical nuclides for environmental monitoring, yet it is challenging to measure. Its high natural mobility and its potential to enter the human body through the food chain underscore the importance of not overlooking the radiation safety risks associated with tritium. The need for the online measurement of tritium at low concentrations is becoming increasingly apparent. This review examines the two principal stages of current measurement methodologies: sample preparation and radiation signal detection. It provides a summary of the tritium sample preparation and detection techniques, highlighting advances in the research with potential applications in online monitoring. The review concludes with an analysis of the issues inherent in the current techniques and offers perspectives on possible technological enhancements and future trajectories for the development of online monitoring systems for trace tritium levels. Full article

This paper investigated the opportunities and challenges of integrating ports into hydrogen (H₂) supply chains in the context of Australia and Japan because they are leading countries in the field and are potential leaders in the upcoming large-scale H₂ trade. Qualitative interviews were conducted in the two countries to identify opportunities for H₂ ports, necessary infrastructure and facilities, key factors for operations, and challenges associated with the ports’ development, followed by an online survey investigating the readiness levels of H₂ export and import ports. The findings reveal that there are significant opportunities for both countries’ H₂ ports and their respective regions, which encompass business transition processes and decarbonisation. However, the ports face challenges in areas including infrastructure, training, standards, and social licence, and the sufficiency and readiness levels of port infrastructure and other critical factors are low. Recommendations were proposed to address the challenges and barriers encountered by H₂ ports. To optimise logistics operations within H₂ ports and facilitate effective integration of H₂ applications, this paper developed a user-oriented working process framework to provide guidance to ports seeking to engage in the H₂ economy. Its findings and recommendations contribute to filling the existing knowledge gap pertaining to H₂ ports. Full article

Food recommendation systems are becoming increasingly vital in modern society, given the fast-paced lifestyle and diverse dietary habits. Existing research and implemented solutions often rely on user preferences and past behaviors for recommendations, which poses significant issues. Firstly, this approach inadequately considers the nutritional content of foods, potentially leading to recommendations that are overly homogeneous and lacking in diversity. Secondly, it may result in repetitive suggestions of the same types of foods, thereby encouraging users to develop unhealthy dietary habits that could adversely affect their overall health. To address this issue, we introduce a novel nutrition-related knowledge graph (NRKG) method based on graph convolutional networks (GCNs). This method not only enhances users’ ability to select appropriate foods but also encourages the development of healthy eating habits, thereby contributing to overall public health. The NRKG method comprises two key components: user nutrition-related food preferences and recipe nutrition components. The first component gathers nutritional information from recipes that users show interest in and synthesizes these data for user reference. The second component connects recipes with similar nutritional profiles, forming a complex heterogeneous graph structure. By learning from this graph, the NRKG method integrates user preferences with nutritional data, resulting in more accurate and personalized food recommendations. We evaluated the NRKG method against six baseline methods using real-world food datasets. In the 100% dataset, the five metrics exceeded the performance of the best baseline method by 2.8%, 5.9%, 1.5%, 9.7%, and 6.0%, respectively. The results indicate that our NRKG method significantly outperforms the baseline methods, including FeaStNet, DeepGCN, GraphSAGE, GAT, UniMP, and GATv2, demonstrating its superiority and effectiveness in promoting healthier and more diverse eating habits. Unlike these baseline methods, which primarily focus on hierarchical information propagation, our NRKG method offers a more comprehensive approach by integrating the nutritional information of recipes with user preferences. Full article

2,2′,4,4′-tetra-bromodiphenytol ether (BDE-47) is one of the ubiquitous organic pollutants in mangrove sediments. To reveal the toxic effects of BDE-47 on mangrove plants, the mangrove species Kandelia obovate was used to investigate the photosynthetic capacity effects and the molecular mechanisms involved after BDE-47 exposure at environment-related levels (50, 500, and 5000 ng g⁻¹ dw). After a 60-day exposure, the photosynthetic capacity was inhibited in K. obovata seedlings, and a decrease in the stomatal density and damage in the chloroplast ultrastructure in the leaves were found. Transcriptome sequencing showed that, following exposure to BDE-47, gene expression in photosynthesis-related pathways was predominantly suppressed in the leaves. The bioinformatics analysis indicated that BDE-47 exerts toxicity by inhibiting photosystem I activity and chlorophyll a/b-binding protein-related genes in the leaves of K. obovata. Thus, this study provides preliminary theoretical evidence for the toxic mechanism effect of BDE-47 on photosynthesis in mangrove species. Full article

Biosensors play a crucial role in detecting cancer signals by orchestrating a series of intricate biological and physical transduction processes. Among various cancers, breast cancer stands out due to its genetic underpinnings, which trigger uncontrolled cell proliferation, predominantly impacting women, and resulting in significant mortality rates. The utilization of biosensors in predicting survival time becomes paramount in formulating an optimal treatment strategy. However, conventional biosensors employing traditional machine learning methods encounter challenges in preprocessing features for the learning task. Despite the potential of deep learning techniques to automatically extract useful features, they often struggle to effectively leverage the intricate relationships between features and instances. To address this challenge, our study proposes a novel smart biosensor architecture that integrates a multi-view multi-way graph learning (MVMWGL) approach for predicting breast cancer survival time. This innovative approach enables the assimilation of insights from gene interactions and biosensor similarities. By leveraging real-world data, we conducted comprehensive evaluations, and our experimental results unequivocally demonstrate the superiority of the MVMWGL approach over existing methods. Full article

The analysis of the genetic diversity and historical dynamics of endemic endangered goose breeds structure has attracted great interest. Although various aspects of the goose breed structure have been elucidated, there is still insufficient research on the genetic basis of endemic endangered Chinese goose breeds. In this study, we collected blood samples from Lingxiang White (LX), Yan (YE), Yangjiang (YJ), Wuzong (WZ), Xupu (XP), and Baizi (BZ) geese (Anser cygnoides) and used Sanger sequencing to determine the partial sequence of the cytochrome b (CYTB) gene in a total of 180 geese. A total of 117 polymorphic sites were detected in the 707 bp sequence of the mtDNA CYTB gene after shearing and correction, accounting for approximately 16.55% of the entire sequence. The AT content (51.03%) of the processed sequence was slightly higher than the GC content (48.97%), indicating a preference for purine bases. The YJ, YE, and WZ breeds had the highest population genetic diversity, with a haplotype diversity greater than 0.9 (Hd > 0.9) and average population nucleotide difference of 8.01 (K > 8.01). A total of 81 haplotypes were detected and divided into six major branches. Among the six goose breeds, there were frequent genetic exchanges among LX, YJ, YE, and WZ geese (Nm > 15.00). We analyzed the distribution of base-mismatch differences in goose breeds and tested their historical dynamics for neutrality in Tajima’s D and Fu’s Fs. For YJ and WZ geese, Tajima’s D > 0, but the difference was not significant (p > 0.05). The actual values for the two breeds exhibited multimodal Poisson distributions. The population patterns of the WZ and YJ geese are purportedly relatively stable, and the breeds have not experienced population expansions or bottleneck effects, which is consistent with the neutrality test results. This study provides new insights into the diverse genetic origins and historical dynamics that sustain endemic endangered goose breeds. Full article