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To thoroughly study the stress–strain relationship of lightweight mixed ceramic concrete, this paper conducts axial compressive strength tests on three groups of lightweight mixed ceramic concrete specimens with different types and contents as the basis. It establishes the elastic modulus calculation formula and compressive stress–strain formula for lightweight mixed ceramic concrete by combining with the current standards and related research. The results show that lightweight mixed ceramic concrete, made of a mixture of different types and densities of ceramic grains, has better mechanical properties and deformation properties. The calculation errors of the modulus of elasticity formulas, derived from the experimental results for the three groups of lightweight mixed ceramic concretes, are all controlled within 5%. The average relative errors of the fitting results of stress–strain curves for the three groups of specimens and the measured data are as low as 6.66%, 3.16%, and 3.39%. The errors between the experimental values of the modulus of elasticity of different studies and the predicted values based on the formula in this paper were controlled within 17%, and the average relative errors between the predicted and experimental results of the stress–strain curves for the three groups of specimens were 2.64%, 8.94%, and 17.50%. This paper innovatively constructs a prediction model of key mechanical parameters of lightweight mixed ceramic concrete, which can provide a reference and experimental basis for the structural analysis and application of lightweight mixed ceramic concrete. [ABSTRACT FROM AUTHOR]

The recently released ChatGPT, an artificial intelligence conversational agent, has garnered significant attention in academia and real life. A multitude of early ChatGPT users have eagerly explored its capabilities and shared their opinions on social media, providing valuable feedback. Both user queries and social media posts have been instrumental in expressing public concerns regarding this advanced dialogue system. To comprehensively understand these public concerns, a novel Self-Supervised Neural Topic Model (SSTM), which formulates topic modeling as a representation learning procedure, is proposed in this paper. The proposed SSTM utilizes Dirichlet prior matching and three regularization terms for improved modeling performance. Extensive experiments on three publicly available text corpora (Twitter Posts, Subreddit and queries from ChatGPT users) demonstrate the effectiveness of the proposed approach in extracting higher-quality public concerns. Moreover, the SSTM performs competitively across all three datasets regarding topic diversity and coherence metrics. Based on the extracted topics, we could gain valuable insights into the public's concerns regarding technologies like ChatGPT, enabling us to formulate effective strategies to address these issues. [ABSTRACT FROM AUTHOR]

Raman spectroscopy is a spectral analysis technique based on molecular vibration. It has gained widespread acceptance as a practical tool for the non-invasive and rapid characterization or identification of multiple analytes and compounds in recent years. In fruit quality detection, Raman spectroscopy is employed to detect organic compounds, such as pigments, phenols, and sugars, as well as to analyze the molecular structures of specific chemical bonds or functional groups, providing valuable insights into fruit disease detection, pesticide residue analysis, and origin identification. Consequently, Raman spectroscopy techniques have demonstrated significant potential in agri-food analysis across various domains. Notably, the frontier of Raman spectroscopy is experiencing a surge in machine learning applications to enhance the resolution and quality of the resulting spectra. This paper reviews the fundamental principles and recent advancements in Raman spectroscopy and explores data processing techniques that use machine learning in Raman spectroscopy, with a focus on its applications in detecting fruit diseases, analyzing pesticide residues, and identifying origins. Finally, it highlights the challenges and future prospects of Raman spectroscopy, offering an effective reference for fruit quality detection. [ABSTRACT FROM AUTHOR]

Achieving sustainable rural development in China requires effectively integrating agricultural growth with ecological balance. However, existing research on the coordination between agricultural economy and ecosystems has often focused on isolated aspects, such as economic growth or ecological sustainability, or has been limited to specific provinces or regions, lacking a comprehensive nationwide analysis. To address this gap, this study uses spatial data from 31 provincial-level regions in China from 2008 to 2022, developing a multidimensional framework that encompasses economic input, structure, efficiency, benefits, vitality, ecological conditions, and pressure. Using multi-factor econometric methods, we comprehensively evaluate the coordination between China's agricultural economy and ecosystems, revealing regional disparities and spatiotemporal variations in their coupling coordination, and analyzing the barriers affecting this coordination. Our findings show that: First, coupling coordination has steadily improved, narrowing regional disparities. Second, regional differences are primarily driven by variations between the eastern, central, and western regions, with structural disparities shifting from interregional to hyper-variable density. Third, development exhibits a "club convergence" pattern, where upward transitions are difficult and downward mobility is a risk. Key barriers include farmland scale, land efficiency, afforestation area, and soil erosion control. Based on these findings, we recommend regional development strategies, dynamic monitoring mechanisms, optimized land use, and enhanced ecological protection. This study provides valuable insights for policymakers and practitioners to promote the coordinated and sustainable development of agricultural economies and ecosystems in China. [ABSTRACT FROM AUTHOR]

Background/Objectives: We aimed to identify neonatal circulating metabolic alterations associated with maternal gestational diabetes mellitus (GDM) and to explore whether these altered metabolites could mediate the association of GDM with offspring neurodevelopment. Additionally, we investigated whether neonatal circulating metabolites could improve the prediction of offspring neurodevelopmental disorders over traditional risk factors. Methods: The retrospective cohort study enrolled 1228 mother–child dyads in South China. GDM was diagnosed at 24–28 weeks of gestation. Neonatal circulating amino acids and lipid metabolites (carnitines) were measured from newborn heel blood 3–7 days postpartum. Offspring neurodevelopment was assessed at age 1 year using the Children Neuropsychological and Behavioral Examination Scale. Neurodevelopmental disorders were defined as developmental delay in any domain of the scale. Results: Twenty-one metabolites associated with GDM were identified, consisting of seven amino acids and fourteen carnitines. Among these metabolites, five (glycine, myristicylcarnitine, palmitoylcarnitine, octadecadienoylcarnitine, and 3-hydroxypalmitylcarnitine) mediated the negative association of GDM with offspring neurodevelopment at 1 year (mediation proportions: 3.91–10.66%). Furthermore, six metabolites (glycine, methionine, malonylcarnitine, isovalerylcarnitine, palmitoylcarnitine, and octadecadienoylcarnitine) significantly increased the predictive performance for offspring neurodevelopmental disorders at 1 year over five traditional risk factors including GDM, parity, infant sex, birth weight, and feeding patterns (area under curve: 0.762 vs. 0.718, p = 0.012). Conclusions: GDM was associated with a variety of amino acid and lipid metabolic alterations in neonatal circulation, among which certain metabolites mediated the association of GDM with adverse neurodevelopmental outcomes in offspring. Moreover, some neonatal circulating metabolites may serve as potential biomarkers that improved the prediction of offspring neurodevelopmental disorders over GDM and other traditional risk factors. [ABSTRACT FROM AUTHOR]

Common carp (Cyprinus carpio) is extensively cultured and widely consumed in Heilongjiang Province, China. Due to the proximity of freshwater ponds to agricultural cultivated areas, these aquatic systems are inevitably influenced by the historical application of organochlorine pesticides (OCPs), due to their prolonged half-life and resistance to degradation. Gas chromatography-tandem mass spectrometry (GC-MS/MS) was utilized to quantify the levels of hexachlorocyclohexane (HCHs) and dichlorodiphenyltrichloroethane (DDTs) in the muscle tissue of cultured common carp. This study examined the enrichment characteristics of HCHs and DDTs in fish muscle, as well as their correlation with sediment and associated risk assessments. The results showed that the residual levels of HCHs and DDTs in fish muscle ranged from 0.387 μg·kg−1 to 3.418 μg·kg−1 and from 0.114 μg·kg−1 to 0.420 μg·kg−1, respectively. They were all below the maximum residue limits specified in GB 2763-2021 (HCHs: 100 μg·kg−1, DDTs: 500 μg·kg−1). The concentrations of HCHs and DDTs in sediment were found to be lower than those in muscle tissue. Notably, the concentrations of HCHs were higher than those of DDTs in both muscle and sediment. Among the HCHs, γ-HCH was the predominant residual substance, contributing a significant proportion of 42.16% to 86.47%. No significant residues of DDT derivatives were detected. A significant correlation was observed between the concentrations of HCHs and DDTs in the muscle tissue and those present in the sediment (p < 0.01). The health risk assessment indicated that both the carcinogenic and non-carcinogenic risks associated with OCPs from common carp muscle and sediment were within acceptable limits. Therefore, it was recommended to regulate fish consumption during the breeding period. [ABSTRACT FROM AUTHOR]

Flexible, wearable, piezoresistive sensors have significant potential for applications in wearable electronics and electronic skin fields due to their simple structure and durability. Highly sensitive, flexible, piezoresistive sensors with the ability to monitor laryngeal articulatory vibration supply a new, more comfortable and versatile way to aid communication for people with speech disorders. Here, we present a piezoresistive sensor with a novel microstructure that combines insulating and conductive properties. The microstructure has insulating polystyrene (PS) microspheres sandwiched between a graphene oxide (GO) film and a metallic nanocopper-graphene oxide (n-Cu/GO) film. The piezoresistive performance of the sensor can be modulated by controlling the size of the PS microspheres and doping degree of the copper nanoparticles. The sensor demonstrates a high sensitivity of 232.5 kPa−1 in a low-pressure range of 0 to 0.2 kPa, with a fast response of 45 ms and a recovery time of 36 ms, while also exhibiting excellent stability. The piezoresistive performance converts subtle laryngeal articulatory vibration into a stable, regular electrical signal; in addition, there is excellent real-time monitoring capability of human joint movements. This work provides a new idea for the development of wearable electronic devices, healthcare, and other fields. [ABSTRACT FROM AUTHOR]

The branching angle of tea plants is a key factor in determining their branching structure, which significantly affects yield, suitability for mechanical harvesting, and overall plant architecture. However, the mechanisms underlying branching angle formation in tea plants remain unclear. In this study, we explored the mechanism of branching angle formation in tea plants by analysing the transcriptome and plant hormone levels of tea plant cultivars with different branching angles. The results indicated that gibberellin positively regulates the branching angle of tea plants, cytokinins, auxin, and abscisic acid involved in the formation of branching angles in tea plants. The transcriptome analysis revealed that candidate regulatory factors, including plant-hormone-related genes (the gibberellin synthesis gene GA3ox1 and metabolism gene GA2ox1; the cytokinin metabolism genes CKX and UGT; the auxin signal transduction-related gene LAX3; and the abscisic acid signal transduction gene PYL4), genes regulating cell division and growth (LAZY1, TAC1, and MAX1), and transcription factors (MYBs, WRKYs, TCPs, AP2/ERFs, and MADS-box), are involved in the formation of branching angles in tea plants. These results offer insights into the mechanism of branching angle formation in tea plants, providing important theoretical reference for the selection and breeding of tea cultivars suitable for mechanical harvesting, thereby improving agricultural efficiency and sustainability. [ABSTRACT FROM AUTHOR]

Impatiens is a genus of functional herbaceous plants in the Balsaminaceae, which are not only of great ornamental value and one of the world's top three flower bedding plants but also have a wide range of medicinal and edible uses. Currently, the taxonomy and phylogenetic relationships of Impatiens species are still controversial. In order to better understand their chloroplast properties and phylogenetic evolution, nine Impatiens plants (Impatiens repens, Impatiens rectirostrata, Impatiens baishaensis, Impatiens rostellata, Impatiens faberi, Impatiens oxyanthera, Impatiens tienchuanensis, Impatiens blepharosepala, Impatiens distracta) were sequenced, and their complete chloroplast genomes were analysed. Nine species of Impatiens chloroplast genomes ranged in length from 150,810 bp (I. rectirostrata) to 152,345 bp (I. blepharosepala). The chloroplast genomes were all typical circular DNA molecules, and the GC content in each region was consistent with the published chloroplast genomes of Impatiens plants. The results showed that the seven mutational hotspots (trnL-UAG, ndhG, ycf1, ccsA, rrn23, trnA-UGC, and ycf2) could be used as supporting data for further analyses of the phylogenetic tree and species identification. In addition, the results of the phylogenetic tree support that Balsaminaceae is a monophyletic taxon, and that Hydrocera triflora is at the base of the branch, is the original species of Balsaminaceae, and is in a sister group relationship with Impatiens species. The results of this paper enrich the data of Impatiens chloroplast genomes, and the availability of these chloroplast genomes will provide rich genetic information for species identification, thus enhancing the taxonomic accuracy and phylogenetic resolution of Impatiens, and further promoting the investigation and rational use of Impatiens plant resources. [ABSTRACT FROM AUTHOR]

The development of a city needs the accumulation of culture, and historical buildings are the most direct witness of the rise and fall of a city. Like the human body, historical buildings have a certain life cycle, but the acceleration of urbanization and unreasonable use cause an irreversible reduction in the residual life of historical buildings. There is a notable lack of quantitative analysis regarding the residual life of historical buildings. Therefore, identifying the factors that influence their residual life is crucial for both preserving these buildings and sustaining urban culture. In order to obtain a more accurate correlation degree of influencing factors, a systematic-analysis model of influencing factors on the residual life of historical buildings based on the entropy weight method (EWM) and the grey relation analysis method (GRA) was established, so as to excavate the mechanism of the influencing factors on the residual life of historical buildings, accurately identify the main influencing factors on the residual life of historical buildings, and propose preventive measures. The results show that the structural system has the greatest influence on the residual life of historical buildings, followed by the enclosure system, and the equipment system. The research findings offer valuable insights for extending the residual life of historical buildings in the future. [ABSTRACT FROM AUTHOR]

Bioretention cells (BCs) are widely used to manage urban runoff due to their positive impact on runoff control. Current research primarily focuses on optimizing the internal structural design of bioretention cells, while studies on the interactions between their spatial configuration, topography, and land use types are limited. This study employs the Storm Water Management Model (SWMM) and uses extreme rainfall to analyze the influence of typical stormwater flow paths, determined by various land use types and topography, as well as the spatial configurations of bioretention cells on catchment hydrological performance. The results show the following: (1) Different stormwater flow paths significantly affect catchment hydrological performance, with series-type pathways performing best. (2) The spatial configuration of bioretention cells significantly influences catchment hydrological performance. Decentralized BCs under series-type pathways showed better performance for reducing total outflow and peak runoff, with reduction rates increasing by 7.1% and 8.8%, while centralized BCs better delayed peak times. (3) Stormwater flow paths affect BC efficiency in catchment hydrological performance. Decentralized BCs under a series-type stormwater flow path are recommended for priority use. This study provides a novel perspective for optimizing the spatial arrangement of BCs and urban stormwater management, thereby contributing to flood risk mitigation. [ABSTRACT FROM AUTHOR]

Color variation in plant leaves has a significant impact on their photosynthesis and plant growth. Camellia chekiangoleosa yellow-leaf mutants are ideal materials for studying the mechanisms of pigment synthesis and photosynthesis, but their mechanism of leaf variation is not clear. We systematically elucidated the intrinsic causes of leaf yellowing in the new Camellia chekiangoleosa variety 'Diecui Liuji' in terms of changes in its cell structure, pigment content, and transcript levels. This study indicates that the incomplete structure of chloroplast-like vesicles, the decrease in blue-green chlorophyll a, and the increase in yellow-green chlorophyll b in yellowing leaves are the direct causes of yellowing-leaf formation. The high expression of genes that catalyze the degradation of chlorophyll a (PAO and RCCR) and its conversion to chlorophyll b (CAO) in yellowing leaves leads to a decrease in the chlorophyll a content, while the low expression of CLH genes is the main reason for the increase in the chlorophyll b content. We also found transcription factors such as ERF, E2F, WRKY, MYB, TPC, TGA, and NFYC may regulate their expression. RT-qPCR assays of 12 DEGs confirm the RNA-seq results. This study will provide a foundation for investigating the transcriptional and regulatory mechanisms of leaf color changes. [ABSTRACT FROM AUTHOR]

Most commercial citrus fruits are grown in acidic soils with high copper (Cu) and low organic matter levels in China. Sweet orange (Citrus sinensis (L.) Osbeck cv. Xuegan) seedlings were treated with 0 (HA0), 0.1 (HA0.1), or 0.5 (HA0.5) mM humic acid (HA) and 0.5 (Cu0.5) or 400 (Cu400 or Cu excess) μM CuCl2 for 24 weeks. The purpose was to validate the hypothesis that HA reduces the oxidative injury caused by Cu400 in roots and leaves via the coordination of strengthened antioxidant defense and glyoxalase systems. Copper excess increased the superoxide anion production rate by 27.0% and 14.2% in leaves and by 47.9% and 33.9% in roots, the malonaldehyde concentration by 199.6% and 27.8% in leaves and by 369.4% and 77.4% in roots, and the methylglyoxal concentration by 18.2% and 6.6% in leaves and by 381.8% and 153.3% in roots, as well as the H2O2 production rate (HPR) by 70.5% and 16.5% in roots, respectively, at HA0 and HA0.5. Also, Cu400 increased the leaf HPR at HA0, but not at HA0.5. The addition of HA reduced the Cu400-induced production and accumulation of reactive oxygen species and methylglyoxal and alleviated the impairment of Cu400 to the antioxidant defense system (ascorbate-glutathione cycle, antioxidant enzymes, sulfur-containing compounds, and sulfur-metabolizing enzymes) and glyoxalase system in roots and leaves. The HA-mediated amelioration of Cu toxicity involved reduced oxidative injury due to the coordination of strengthened antioxidant defense and glyoxalase systems. These findings highlight the promise of HA for sustainable citrus cultivation in heavy metal (Cu)-polluted soils. [ABSTRACT FROM AUTHOR]

Offshore wind power construction has seen significant development due to the high density of offshore wind energy and the minimal terrain restrictions for offshore wind farms. However, integrating this energy into the grid remains a challenge. The scientific community is increasingly focusing on hydrogen as a means to enhance the integration of these fluctuating renewable energy sources. This paper reviews the research on renewable energy power generation, water electrolysis for hydrogen production, and large-scale hydrogen storage. By integrating the latest advancements, we propose a system that couples offshore wind power generation, seawater electrolysis (SWE) for hydrogen production, and salt cavern hydrogen storage. This coupling system aims to address practical issues such as the grid integration of offshore wind power and large-scale hydrogen storage. Regarding the application potential of this coupling system, this paper details the advantages of developing renewable energy and hydrogen energy in Jiangsu using this system. While there are still some challenges in the application of this system, it undeniably offers a new pathway for coastal cities to advance renewable energy development and sets a new direction for hydrogen energy progress. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) furnished with computational servers enable user equipment (UE) to offload complex computational tasks, thereby addressing the limitations of edge computing in remote or resource-constrained environments. The application of value decomposition algorithms for UAV trajectory planning has drawn considerable research attention. However, existing value decomposition algorithms commonly encounter obstacles in effectively associating local observations with the global state of UAV clusters, which hinders their task-solving capabilities and gives rise to reduced task completion rates and prolonged convergence times. To address these challenges, this paper introduces an innovative multi-agent deep learning framework that conceptualizes multi-UAV trajectory optimization as a decentralized partially observable Markov decision process (Dec-POMDP). This framework integrates the QTRAN algorithm with a large language model (LLM) for efficient region decomposition and employs graph convolutional networks (GCNs) combined with self-attention mechanisms to adeptly manage inter-subregion relationships. The simulation results demonstrate that the proposed method significantly outperforms existing deep reinforcement learning methods, with improvements in convergence speed and task completion rate exceeding 10%. Overall, this framework significantly advances UAV trajectory optimization and enhances the performance of multi-agent systems within UAV-assisted edge computing environments. [ABSTRACT FROM AUTHOR]

Path planning for Unmanned Aerial Vehicles (UAVs) plays a critical role in power line inspection. In complex inspection environments characterized by densely distributed and dynamic obstacles, traditional path-planning algorithms struggle to ensure both efficiency and safety. To address these challenges, this study proposes a dynamic path-planning method that integrates an improved Rapidly exploring Random Tree Star (RRT*) algorithm with the Dynamic Window Approach (DWA). The proposed method includes key components such as sampling-point search, random tree growth, global path-node optimization, and local dynamic obstacle avoidance. In the sampling-point search, a target-biased search strategy is introduced to guide the random tree growth toward the target point, while an attractive function is added to enhance search efficiency. Based on a breadth-first search strategy, the path obtained is optimized to reduce path complexity. To address the RRT* algorithm's limitation in dynamic obstacle avoidance, a local path-planning method combining the improved DWA algorithm is proposed, improving efficiency in areas with dense obstacles. Simulation results show that, compared to traditional algorithms, the proposed method achieves an 8% to 12% optimization in path length, more than 50% in node optimization, and over 95% in planning time optimization. Furthermore, in dynamic obstacle avoidance across different motion directions, the proposed method ensures effective local dynamic obstacle avoidance while minimizing global path fluctuations. [ABSTRACT FROM AUTHOR]

With the development of the Internet of Things, cloud networking, and 4K/8K high-definition video, global internet traffic has seen a dramatic increase. This surge in traffic has placed higher demands on the performance of optical networks, featuring higher data rates, lower latency, and lower cost. The passive optical network (PON) is a representative scenario of optical access networks. Issues such as burst-mode detection in upstream PON scenarios, flexible rate allocation in downstream scenarios, and the simplification of hardware complexity at the optical network unit (ONU) side have attracted considerable attention. Compared to intensity modulation/direct detection (IM/DD), a recently proposed coherent PON incorporates a local oscillator laser at the receiver, enabling superior receiver sensitivity, spectrally efficient modulation, linear optical field recovery, and flexible channel selection. These features significantly enhance the flexibility and data rates of PON systems. This paper provides a comprehensive review of the development of coherent PONs, particularly in aspects of preamble design for burst-mode detection in upstream scenarios, the design of flexible rate PONs in downstream scenarios, and solutions for reducing hardware complexity at the ONU side. [ABSTRACT FROM AUTHOR]

Gallium oxide (Ga2O3) has gained considerable attention due to its wide bandgap, the availability of native substrates, and its excellent properties for solar-blind photodetectors, transparent electronics, and next-generation power devices. However, the expensive Ga2O3 native substrates have restricted its widespread adoption. To reduce costs and further the development of β-Ga2O3-based devices, there is a need for bandgap-tunable oxide films with high crystal quality for deep-ultraviolet (DUV) photodetectors and high-breakdown-field power devices. This study introduces a Thermal Interdiffusion Alloying method to address these requirements. It focuses on developing deep ultraviolet (DUV) photodetectors using β-Ga2O3 thin films on sapphire substrates by promoting the diffusion of aluminum (Al) atoms from the substrate into the film, resulting in the formation of aluminum gallium oxide (β-(AlxGa1−x)2O3). The aluminum content is controlled by adjusting the process temperature, allowing for tunable detection wavelengths and enhanced DUV sensing capabilities. Radio frequency (RF) sputtering optimizes the film's quality by adjusting the sputtering power and the argon/oxygen (Ar/O2) flow ratio. Material analysis indicates that this method expands the optical bandgap and shifts the response wavelength to 210 nm, significantly boosting the performance of the fabricated photodetectors. This research presents considerable potential for advancing DUV photodetectors across various disinfection applications. [ABSTRACT FROM AUTHOR]

As a key technology for future decarbonization, storage batteries are widely used in areas such as electric vehicles and power systems. However, battery aging inevitably limits their broader application. To address the low accuracy in predicting discharge voltage under different aging states, this paper proposes the IWOA-ATCN method based on a TCN model with a sliding window mechanism. First, the improved whale optimization algorithm (IWOA) is employed to optimize the hyperparameters in the TCN model, including window size and sliding step, to obtain the optimal sample structure. Then, the temporal attention mechanism is introduced into the TCN model to accurately capture the temporal correlation of discharge voltage, thereby improving the prediction accuracy of long time series data. Finally, the model is tested on the NASA dataset with an RMSE of 0.0072, MAE of 0.0046, and R2 of 0.9984. The test results on the PL Sample dataset showed RMSE of 0.0081, MAE of 0.0040, and R2 of 0.9983. It is indicated that the prediction accuracy and stability of the IWOA-ATCN model are higher than other models, such as BP, RNN, and LSTM. [ABSTRACT FROM AUTHOR]

AC/DC hybrid distribution networks with power electronic transformers (PETs) as distribution hubs are in line with the future development direction of the AC/DC hybrid distribution network. Unlike traditional transformers, power electronic transformers introduce new node types and may transform the network topology from radial to ring structures. These changes render traditional power flow calculation methods inadequate for achieving satisfactory results in AC/DC hybrid networks. In addition, existing commercial power flow calculation software packages are mainly based on the traditional AC power flow calculation method, which have limited support for the DC network. Especially when the DC network is coupled with the AC network, it is difficult to achieve a unified calculation of its power flow. To address these challenges, this paper proposes a novel power flow calculation method for ring AC/DC hybrid distribution networks with power electronic transformers. The proposed method is based on the alternating iterative method to ensure compatibility with mature AC power flow calculation programs in commercial software, thereby improving the feasibility of engineering applications. Firstly, the steady-state power flow calculation model of PET is constructed by analyzing that the working principle and control modes of power electronic transformer are proposed based on the source-load attributes of its connected subnetworks. According to the characteristics of the power electronic transformer, AC distribution network, and DC distribution network, a hybrid alternating iteration method combining the high computational accuracy of the Newton–Raphson (NR) method with the high efficiency of the Zbus Gaussian method in dealing with ring networks is proposed. On this basis, the power flow calculation model of the AC/DC hybrid distribution network with power electronic transformers is established. Finally, the simulation of the constructed 44-node ring AC/DC hybrid distribution network example is carried out. The simulation results show that the proposed method can not only converge reliably when the convergence accuracy is 1 × 10−6 p.u., but also ensure that the voltage magnitudes of all nodes are above 0.96 p.u. whose maximum offset value is 0.789% when the outputs of the connected distributed generations fluctuate, which verifies the effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Due to the lack of agents that directly target covalently closed circular DNA and integrated HBV DNA in hepatocytes, achieving a complete cure for chronic hepatitis B (CHB) remains challenging. The latest guidelines recommend (hepatitis B surface antigen) HBsAg loss as the ideal treatment target for improving liver function, histopathology, and long-term prognosis. However, even after HBsAg loss, hepatitis B virus can persist, with a risk of recurrence, reactivation, cirrhosis, and hepatocellular carcinoma. Therefore, follow-up and surveillance are still necessary. With increasing treatment options available for achieving HBsAg loss in patients with CHB, developing effective surveillance strategies has become crucial. Recent studies on outcomes following HBsAg loss provide new insights for refining current surveillance strategies, though further improvement is needed through long-term observation and follow-up. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of salt field waste-generated bio-organic fertilizer application on the bacterial community structure within the rhizosphere soil of tea plants. After the administration of salt field waste-generated bio-organic fertilizer, the content of tea polyphenols in tea decreased, while the content of caffeine and free amino acids increased. The results showed that the dominant bacterial species in the rhizosphere soil of tea plants were Chloroflexi, Acidobacteriota, and Proteobacteria. The most dominant genus were k__Bacteria__p__Proteobacteria__c__uncultured__o__uncultured__f__uncultured__g__uncultured, k__Bacteria__p__Acidobacteriota__c__Acidobacteriae__o__Subgroup_2__f__Subgroup_2__g__Subgroup_2, k__Bacteria__p__Chloroflexi__c__AD3__o__AD3__f__AD3__g__AD3, k__Bacteria__p__Chloroflexi__c__Ktedonobacteria__o__Ktedonobacterales__f__Ktedonobacteraceae__g__HSB_OF53-F07, and g__Acidothermus. Following the application of bio-organic fertilizer, g__AD3, g__Subgroup_2, and g__HSB_OF53_F07 in the rhizosphere soil of the tea plants exhibited a decreasing trend compared to the control group. p_Proteobacteria was significantly increased, and p_Chloroflexi was considerably decreased in soils treated with bioorganic fertilizers, indicating that bio-organic fertilizers might influence the soil microbial structure in the rhizosphere soil of tea plants. Network association analyses showed a strong positive correlation between g_Candidatus_Solibacter and g_Bryobacter and a significant negative correlation between g_AD3 and g_ADurb.Bin063_1. Applying salt field waste-generated bio-organic fertilizers might effectively adjust the bacterial community structure in tea plants' rhizosphere soil, improving the quality of tea. This study provides valuable insights into the potential benefits of utilizing bio-organic fertilizer from salt field waste in tea plantations. [ABSTRACT FROM AUTHOR]

Soil aggregate stability is an important factor that impacts ecological restoration and soil erosion. Soil organic carbon (SOC) is also an important factor affecting soil characteristics and quality. The triple-cropping system has the potential to enhance soil aggregate stability by promoting a more diverse and continuous plant cover, which could lead to improved soil structure and resistance to erosion. Over two consecutive years, this study was conducted to explore the impacts of the triple-cropping system on soil aggregate stability, soil carbon pool, and carbon sequestration characteristics in the middle reaches of the Yangtze River. This study set up five planting modes, namely milkvetch–early rice–late rice (CRR, CK), milkvetch–early rice–sweet potato||soybean (CRI), rape–early rice–late rice (RRR), rape–early rice–sweet potato||soybean (RRI) and potato–early rice–late rice (PRR). The contribution of soil aggregates > 2 mm under CRI increased by 20.77%, 6.71%, and 2.19% to the control in winter cropping and early and late rice harvesting periods, respectively. During the winter harvest period, the geometric mean diameter (GMD) and mean weight diameter (MWD) of the CRI treatment were significantly higher than other treatments (p < 0.05), with increases of 7.53–16.28% and 4.67–10.28% respectively. After the late rice harvest, the GMD values of the CRI and PRR treatments were significantly higher than the control treatment by 13.56%, and the MWD values were higher than those of other treatments by 4.24–13.17%, 3.74–12.63% (p < 0.05). Furthermore, CRI also improved the GMD and MWD of soil aggregates, and the stability of soil aggregates was improved by winter milkvetch (treatment of CRI) and paddy-upland multi-crop models (treatment of PRR). RRR treatment was beneficial to the accumulation of soil organic carbon and slowed the loss of soil organic carbon. Irrigation and drought multiple cropping can effectively increase the content of soil active organic carbon, among which the treatment of CRI had the best performance and the most significant effect in increasing the content of soil active organic carbon. After the late rice harvest, the soil's active organic carbon content in the CRI treatment was the highest, which was significantly different from the control treatment and increased by 35.62% compared with the control (p < 0.05). Compared with before planting, the soil microbial biomass carbon content in each treatment increased by 12.07–27.59% after the late rice harvest. The soil-dissolved organic carbon content in CRI treatment was the highest, which was significantly higher than CK treatment, RRR, and PRR, with an increase of 46.88%, 42.42%, and 30.56%, respectively (p < 0.05). In addition, the accumulation of soil microbial biomass carbon, soil dissolved organic carbon content, and soil easily oxidized organic carbon content was promoted by multi-cropping in rice fields, and the increase from CRI and RRI treatment was more significant. In conclusion, in the triple-cropping area of paddy fields in the middle reaches of the Yangtze River, the milkvetch–early rice–sweet potato||late soybean and rape–early rice–sweet potato||late soybean models are conducive to the optimal management of the soil carbon pool and carbon sequestration. These models can improve the multiple cropping index, reduce costs, and increase revenue. [ABSTRACT FROM AUTHOR]

When picking strawberries outdoors, due to factors such as light changes, obstacle occlusion, and small target detection objects, the phenomena of poor strawberry recognition accuracy and low recognition rate are caused. An improved YOLOv5n strawberry high-precision recognition algorithm is proposed. The algorithm uses FasterNet to replace the original YOLOv5n backbone network and improves the detection rate. The MobileViT attention mechanism module is added to improve the feature extraction ability of small target objects so that the model has higher detection accuracy and smaller module sizes. The CBAM hybrid attention module and C2f module are introduced to improve the feature expression ability of the neural network, enrich the gradient flow information, and improve the performance and accuracy of the model. The SPPELAN module is added as well to improve the model's detection efficiency for small objects. The experimental results show that the detection accuracy of the improved model is 98.94%, the recall rate is 99.12%, the model volume is 53.22 MB, and the mAP value is 99.43%. Compared with the original YOLOv5n, the detection accuracy increased by 14.68%, and the recall rate increased by 11.37%. This technology has effectively accomplished the accurate detection and identification of strawberries under complex outdoor conditions and provided a theoretical basis for accurate outdoor identification and precise picking technology. [ABSTRACT FROM AUTHOR]

Objective: This research investigated the prospective association of serum homocysteine with lumbar bone mineral density (BMD) and the risk of osteoporosis in the Chinese population. Methods: In this cohort, 2551 Chinese individuals aged ≥50 years underwent annual health examinations. Among them, 2551, 1549, and 926 completed two, three, and more than three examinations, respectively. We used generalized estimating equations to analyze the connection between serum homocysteine and lumbar BMD. Additionally, we assessed the connection between serum homocysteine and the incidence of osteoporosis using Cox proportional hazard models. Subgroup analyses based on covariates were performed to identify important at-risk populations. Results: Participants with higher homocysteine levels showed decreased lumbar BMD compared to those with lower homocysteine levels (p-trend < 0.05). Specifically, lumbar BMD decreased by −0.002 (−0.003, −0.001) g/cm2 for every standard deviation increase in log-transformed serum homocysteine. Compared to the lowest quartile of homocysteine levels, lumbar BMD decreased by −0.006 (−0.010, −0.002) g/cm2 in the highest quartile in men. In smokers, lumbar BMD decreased by −0.007 (−0.012, −0.003) g/cm2 in the highest quartile. During the follow-up period, 175 incidences of osteoporosis were recorded. Serum homocysteine was linked to an increased risk of osteoporosis (p-trend < 0.05). Furthermore, for every standard deviation rise in log-transformed homocysteine, the HR for osteoporosis was 1.33 (95% CI, 1.12–1.58). Conclusions: Elevated homocysteine levels may be responsible for reduced lumbar BMD in middle-aged and older Chinese people, especially men and smokers. In addition, elevated homocysteine levels may be a risk factor for the development of osteoporosis. [ABSTRACT FROM AUTHOR]

Background: Nutritional supplements are widely used by swimmers, but the effectiveness of various supplements and the identification of the most effective intervention require further investigation. Purpose: This paper evaluated and compared the effectiveness of various nutrition-based interventions on swimming performance through both direct and indirect comparisons. Methods: PubMed, Embase, Web of Science, Cochrane Library, and SPORTDiscus databases were thoroughly searched up to 4 April 2024. The risk of bias was judged using the Cochrane risk of bias tool. A random-effect model was adopted to compute standardized mean differences (SMD) and 95% confidence intervals (CI). Results: L-arginine (Arg) demonstrated superior performance to the placebo (SMD = −1.66, 95% CI [−2.92, −0.44]), emerging as the most effective intervention for reducing 100 swimming time (SUCRA = 89.5%). Beta-alanine (BA) was the best intervention for improving blood lactate (SUCRA = 80%). Creatine combined with sodium bicarbonate (Creatine_NaHCO3) significantly increased blood pH compared to the placebo (SMD = 3.79, 95% CI [1.85, 5.80]), with a SUCRA score of 99.9%, suggesting it is the most effective intervention for this parameter. No prominent differences were noted among the interventions in 50 m time, 200 m time, heart rate, and body mass. Conclusions: Dietary supplements might provide benefits for improving swimming performance. Arg emerged as the most efficacious modality for reducing 100 m time. BA proved to be the preeminent strategy for decreasing blood lactate. Creatine_NaHCO3 was distinguished as the optimal approach for improving blood pH. [ABSTRACT FROM AUTHOR]

Aims: The screening and diagnosis of dengue virus infection play a crucial role in controlling the epidemic of dengue fever, highlighting the urgent need for a highly sensitive, simple, and rapid laboratory testing method. This study aims to assess the clinical performance of MAGLUMI Denv NS1 in detecting dengue virus NS1 antigen. Methods: A retrospective study was conducted to assess the sensitivity and specificity of MAGLUMI Denv NS1 using residual samples. Dengue-confirmed and excluded samples, validated by qPCR, were subjected to testing with MAGLUMI Denv NS1 in accordance with the manufacturer's instructions. The linear range, endogenous interference, and cross-reactivity of MAGLUMI Denv NS1 were verified, and a consistency analysis with commercial comparator products was carried out. Results: The diagnostic specificity of MAGLUMI Denv NS1 is 98.41% (62/63), and the sensitivity is 98.32% (117/119). It effectively detects various serotypes of dengue virus, with no observed endogenous interference or cross-reactivity. Additionally, the consistency of NS1, IgM, and IgG tests on the MAGLUMI platform compared to commercial comparator reagents reaches 85.71%, 99.25%, and 98.97%, respectively. Conclusions: The MAGLUMI Denv NS1 represents a highly sensitive laboratory testing method capable of enhancing the diagnostic accuracy and efficiency of dengue virus infection detection. [ABSTRACT FROM AUTHOR]

To investigate the mechanical and energy evolution characteristics of fractured rock under true triaxial stresses, true triaxial strength compression experiments on fractured sandstone were conducted with varying crack lengths and widths. The results indicate that under true triaxial stresses, the peak stress of the rock exhibits a gradual decline with an increase in crack length and width. Meanwhile, crack initiation stress and crack damage stress of fractured sandstone also demonstrate a declining trend overall, and the influence of crack length on the characteristic stress (crack initiation stress and crack damage stress) of sandstone is more pronounced than that of crack width. According to the energy analysis results, the total strain energy of fractured sandstone gradually decreases with an increase in crack length and width. The results offer a theoretical foundation for the strength assessment and stability management of fractured rock materials during deep coal mining operations. [ABSTRACT FROM AUTHOR]

In the context of the booming construction of smart cities, multi-source data fusion and analysis algorithms play a key role in optimizing real estate management and improving urban efficiency. In this review, we comprehensively and systematically review the relevant algorithms, covering the types, characteristics, fusion techniques, analysis algorithms, and their synergies of multi-source data. We found that multi-source data, including sensors, social media, citizen feedback, and GIS data, face challenges such as data quality and privacy security when being fused. Data fusion algorithms are diverse and have their own advantages and disadvantages. Data analysis algorithms help urban management in areas such as spatial analysis and deep learning. Algorithm collaboration can improve decision-making accuracy and efficiency and promote the rational allocation of urban resources. In the future, algorithm development will focus on data quality, real-time, deep mining, interdisciplinary research, privacy protection, and collaborative application expansion, providing strong support for the sustainable development of smart cities. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer is a major global health burden, with biochemical recurrence (BCR) following radical prostatectomy affecting 20–40% of patients and posing significant challenges to prognosis and treatment. Emerging evidence suggests a critical role for differentially expressed in normal and neoplastic cell (DENN) domain-containing genes in oncogenesis; however, their implications in prostate cancer and BCR risk remain underexplored. Methods: This study systematically evaluated 151 single-nucleotide polymorphisms in DENN domain-containing genes in 458 patients with prostate cancer and BCR, followed by validation in an independent cohort of 185 patients. Results: Multivariate Cox regression analyses identified DENND2D rs610261 G>A as significantly associated with improved BCR-free survival in both cohorts (adjusted hazard ratio = 0.39, 95% confidence interval = 0.23–0.66, p = 0.001). Functional analysis revealed rs610261's regulatory potential, with the protective A allele correlating with increased DENND2D expression in various human tissues. Compared to normal prostate tissues, DENND2D expression was reduced in prostate cancer, with higher expression being linked to favorable patient prognosis (p = 0.03). Gene set enrichment analysis revealed an association between DENND2D expression and the negative regulation of MYC target genes, including MAD2L1, ERH, and CLNS1A, which are overexpressed in prostate cancer and associated with poor survival. Furthermore, the elevated DENND2D expression promotes immune infiltration in prostate cancer, supporting its role in immune modulation. Conclusions: DENND2D is a prognostic biomarker for BCR in prostate cancer and offers new avenues for personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Ingestion of foreign bodies is a prevalent issue in clinical practice, with fish bones being the predominant cause. While the upper gastrointestinal tract is commonly affected, small intestine impactions pose significant diagnostic challenges due to nonspecific symptoms and lack of awareness of foreign body ingestion. Herein, we describe a case presenting with recurrent, unexplained abdominal pain and hematochezia. Multiple diagnostic investigations, including esophagogastroduodenoscopy and colonoscopy, conducted over several months failed to identify the underlying cause until a retrograde single-balloon enteroscopy for obscure gastrointestinal bleeding revealed a 2.3 cm fish bone embedded in the distal ileum. The successful removal of the fish bone led to the resolution of the patient's symptoms. This case highlights that foreign bodies in the small intestine can be a cause of hematochezia and emphasizes the growing importance of deep enteroscopy techniques in detecting and retrieving these foreign objects, thereby reducing the need for surgery. [ABSTRACT FROM AUTHOR]

One of the most important characteristics of ornamental plants is leaf color, which enhances the color of plant landscapes and attracts pollinators for reproduction. The leaves of Impatiens hawkeri 'Sakimp005' are initially green, then the middle part appears yellow, then gradually become white, while the edge remains green. In the study, leaves of I. hawkeri 'Sakimp005', in four developmental stages (S1-G, S2-C, S3-C, and S4-C), were selected for the determination of pigment content, chromaticity values, integrative metabolomics, and transcriptomics analyses. The carotenoid content of leaves varied significantly and regularly at four stages, and the colorimetric values corroborated the phenotypic observations. The results of integrative metabolomics and transcriptomics analysis show that the accumulation of two carotenoids (lutein and zeaxanthin), to different degrees in the leaves of I. hawkeri 'Sakimp005' at four stages, led to the vary yellowing phenomenon. We speculated that the carotenoid biosynthesis (containing two branches: α-branch and β-branch) in leaves by IhLUT1 and IhLUT5 in the α-branch and IhBCH2 genes in the β-branch differed. These findings provide a molecular basis for Impatiens plants' leaf color breeding and improve the knowledge of the leaf color mechanism. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the effectiveness of astigmatism correction between topographic- and manifest-based methods in individuals who underwent second-generation keratorefractive lenticule extraction (KLEx) surgery. Methods: This study was conducted with participants who underwent second-generation KLEx surgery. After exclusion, there were 46 and 43 participants in the manifest and topographic groups, respectively. The main outcomes were postoperative uncorrected distance visual acuity (UDVA), spherical equivalent (SE), and residual astigmatism. The independent T-test and generalized estimate equation were used to investigate differences between the two groups. Results: Three months postoperatively, UDVA was 0.02 ± 0.04 in the manifest group and 0.00 ± 0.06 in the topographic group which also revealed no significant difference (p = 0.155). Also, the SE value in the two groups three months postoperatively was statistically similar (−0.57 ± 0.48D versus −0.63 ± 0.62D, p = 0.574). The final residual astigmatism was −0.26 ± 0.27 in the topographic group which was significantly lower than the −0.51 ± 0.40 in the manifest group (p < 0.001). Moreover, the amplitude of astigmatism change was significantly lower in the topographic group (p = 0.002). In the subgroup analysis, UDVA and residual astigmatism were significantly better in the topographic group than in the manifest group (both p < 0.05). Conclusions: The topographic-based method represents a better astigmatism correction than the manifest-based method in second-generation KLEx surgery, especially in the low astigmatism population. [ABSTRACT FROM AUTHOR]

Simple Summary: To elucidate the regulatory role of Histone Deacetylase Complex 1 (HDC1) in the primary root growth of Arabidopsis thaliana under potassium (K+) deficiency, we examined primary root growth changes in the hdc1-2 mutant under K+ deficiency stress. The hdc1-2 mutant exhibited significantly inhibited primary root growth compared to the wild-type (WT) plants under low-potassium (LK) conditions, indicating that HDC1 positively regulates root growth under LK conditions. We measured various root zones and found that the inhibition of root growth in hdc1-2 was attributed to reduced apical meristem cell proliferation. The root growth of hdc1-2 showed reduced sensitivity compared to WT after auxin treatment under LK conditions. Moreover, HDC1 negatively regulated the expression of the CBL-CIPK module genes. These findings suggest that HDC1 connects histone deacetylation, auxin signaling, and the CBLs-CIPKs pathway in response to K+ deficiency. Plants frequently encounter relatively low and fluctuating potassium (K+) concentrations in soil, with roots serving as primary responders to this stress. Histone modifications, such as de-/acetylation, can function as epigenetic markers of stress-inducible genes. However, the signaling network between histone modifications and low-K+ (LK) response pathways remains unclear. This study investigated the regulatory role of Histone Deacetylase Complex 1 (HDC1) in primary root growth of Arabidopsis thaliana under K+ deficiency stress. Using a hdc1-2 mutant line, we observed that HDC1 positively regulated root growth under LK conditions. Compared to wild-type (WT) plants, the hdc1-2 mutant exhibited significantly inhibited primary root growth under LK conditions, whereas HDC1-overexpression lines displayed opposite phenotypes. No significant differences were observed under HK conditions. Further analysis revealed that the inhibition of hdc1-2 on root growth was due to reduced apical meristem cell proliferation rather than cell elongation. Notably, the root growth of hdc1-2 showed reduced sensitivity compared to WT after auxin treatment under LK conditions. HDC1 may regulate root growth by affecting auxin polar transport and subsequent auxin signaling, as evidenced by the altered expression of auxin transport genes. Moreover, the organ-specific RT-qPCR analyses unraveled that HDC1 negatively regulates the expression of CBL-CIPK-K+ channel-related genes such as CBL1, CBL2, CBL3, AKT1, and TPK1, thereby establishing a molecular link between histone deacetylation, auxin signaling, and CBLs-CIPKs pathway in response to K+ deficiency. [ABSTRACT FROM AUTHOR]

Optimizing urban spatial form has become an important research topic for promoting urban sustainable development and improving energy efficiency. This study selects 164 high-rise residential blocks in the Changsha area as the research object and constructs three multi-objective optimization frameworks and mathematical models for the spatial form of high-rise residential blocks based on the Rhino and Grasshopper parametric platform. The TOPSIS comprehensive evaluation method is combined to further screen the Pareto front solutions, and global sensitivity analysis of spatial form parameters is conducted using Simlab to explore the multi-objective optimization strategies for the spatial form of high-rise residential blocks in the Changsha area, guided by energy performance. Practical cases are selected for verification. The results show that, (1) after multi-objective optimization, the optimal scheme for the determinant type reduces EUI by 7.22%, increases PVP by 28.84%, and reduces CGR by 2.21%. The optimal scheme for the point-cluster type reduces EUI by 3.80%, increases PVP by 7.34%, and reduces CGR by 2.30%. The optimal scheme for the staggered type reduces EUI by 6.66%, increases PVP by 17.65%, and reduces CGR by 2.26%. (2) The potential order of spatial form optimization for the three types of high-rise residential blocks in the Changsha area is determinant type > staggered type > point-cluster type. (3) The spatial form parameters most sensitive to the three architectural performance goals of EUI, PVP, and CGR are floor area ratio and average number of floors. The research results will provide quantifiable references for scientific decision-making in the design practice of high-rise residential blocks in the Changsha area and even in regions with hot summers and cold winters. [ABSTRACT FROM AUTHOR]

Leakage in water distribution systems (WDSs) causes a waste of water resources and increased carbon emissions. Rapid and accurate leakage localization to reduce the waste of water resources caused by leakages is an important way to overcome the problem. Using spatiotemporal correlation in monitoring data forms the basis of a leakage localization method proposed in a previous study. It is crucial to acknowledge that the chosen parameter settings significantly influence the localization performance of this method. This paper primarily seeks to optimize three essential parameters of this method: localization metrics weight (LMW), score threshold (ST), and the indicator of detection priority (IDP). LMW evaluates the similarity between simulated and measured pressure residuals. ST determines the size of the datasets involved in the spatial clustering, and IDP quantifies the likelihood of a true leakage within the candidate region. The leakage localization method is tested on a realistic full-scale distribution network to assess leakage flow rates and sensor noise. The results show that the optimized parameter settings could improve the efficiency and accuracy of leakage localization. Further, the findings indicate that the optimized parameter settings can enhance the effectiveness and precision of leakage localization. [ABSTRACT FROM AUTHOR]

This study proposes an Additive Wavelet Transform (AWT)-based method to fuse Multispectral UAV (MS UAV, 5 cm resolution) and Sentinel-2 satellite imagery (10–20 m resolution), generating 5 cm resolution fused images with a focus on near-infrared and shortwave infrared bands to enhance the accuracy of mango canopy water content monitoring. The fused Sentinel-2 and MS UAV data were validated and calibrated using field-collected hyperspectral data to construct vegetation indices, which were then used with five machine learning (ML) models to estimate Fuel Moisture Content (FMC), Equivalent Water Thickness (EWT), and canopy water content (CWC). The results indicate that the addition of fused Sentinel-2 data significantly improved the estimation accuracy of all parameters compared to using MS UAV data alone, with the Genetic Algorithm Backpropagation Neural Network (GABP) model performing best (R2 = 0.745, 0.859, and 0.702 for FMC, EWT, and CWC, respectively), achieving R2 improvements of 0.066, 0.179, and 0.210. Slope, canopy coverage, and human activities were identified as key factors influencing the spatial variability of FMC, EWT, and CWC, with CWC being the most sensitive to environmental changes, providing a reliable representation of mango canopy water status. [ABSTRACT FROM AUTHOR]