Search Results (12,159)

In increasingly complex electromagnetic environments, wireless communication systems face the severe challenge of non-Gaussian impulse noise. The moments of impulse noise tend toward infinity, reducing the distinguishability of signal features and thereby limiting improvements in signal modulation recognition rates. First, a time–frequency analysis method based on kernel space mapping is proposed to improve the distinguishability of time–frequency features in signals under impulse noise. On this basis, a multimodal kernel harmonic feature fusion network is constructed, combining convolutional neural networks and graph convolutional networks to extract and fuse kernel harmonic features from three modalities to achieve robust and accurate modulation recognition. The simulation results show a generalized signal-to-noise ratio of −2 dB, and the modulation recognition rate reaches 93.5%. Full article

The ecological restoration process of larch plantations to mixed forests contributes to enhancing the stability and functionality of forest ecosystems, with soil microbes playing a crucial role in this process. To elucidate the changes in soil microbial communities during this transition and their relationships with soil and litter properties, the study used 16S/ITS rRNA high-throughput sequencing to investigate the diversity and composition of soil bacterial and fungal communities at two soil depths across four restoration stages, and further quantified the relative contributions of soil and litter properties to variations in microbial community structure. The results indicated that bacterial and fungal $\mathsf{\alpha }$-diversity remained relatively stable in the topsoil but varied significantly across restoration stages in the subsoil ($p<0.05$), with the highest levels observed during the broadleaf species invasion stage. Fungal community structure demonstrated greater sensitivity to the restoration process, whereas bacterial communities showed stronger spatial dependency. Variance partitioning analysis revealed that soil properties were the main contributors to the variations of bacterial and fungal communities, accounting for 41% and 28% of the total variance, respectively. Fungal communities were more closely associated with litter properties than bacterial communities. Redundancy analysis combined with hierarchical partitioning further revealed that soil available phosphorus (AP) and total nitrogen (TN) were key factors explaining the variation in both bacterial and fungal communities. Additionally, litter total nitrogen (LTN) also emerged as an important factor affecting soil fungal communities. These findings provide critical microbiological evidence for accelerating the forest restoration in Northeast China through soil fertility management and regulation of litter inputs. Full article

Influenced by various physical, chemical, and microbial factors, the aging process of Citri Reticulatae ‘Chachiensis’ Pericarpium (CRCP) poses a complex scientific challenge. Drawing inspiration from the perspective of traditional Chinese medicine, volatile oils were extracted from CRCP aged 1, 3, 5, and 7 years by steam distillation and subsequently analyzed by GC-MS. The results revealed that the relative percentage of 4-vinylguaiacol (4-VG) increased progressively with aging. Nineteen volatile oil components were further assessed for their glucose metabolism-enhancing activities, with 4-VG emerging as a key active compound. Notably, 4-VG remarkably enhanced insulin-stimulated glucose uptake in C2C12 myotubes. Moreover, 4-VG demonstrated potent antihyperglycemic effects by upregulating IRS-1/Akt/GSK-3β phosphorylation in the insulin signaling pathway on a high-fat diet and STZ-induced diabetic mouse model. In addition, the metabolic pathway of 4-VG, from ferulic acid and then to vanillin and guaiacol, was verified via HPLC-UV, metabolomics, and microbiome analyses, which confirmed the microbial conversion of 4-VG within CRCP. The metabolic pathway was ultimately validated by isolating and identifying Priestia aryabhattai, Bacillus velezensis, and Aspergillus fumigatus from CRCP, with further in vitro culture and biotransformation experiments confirming its functionality and efficiency. These findings provide new insights and experimental evidence that deepen our understanding of the aging process of CRCP. Full article

In the face of increasingly severe global environmental challenges, the development of low-cost, high-precision, and easily integrable environmental monitoring sensors is of paramount importance. Existing optical refractive index sensors are often limited in application due to their complex structures and high costs, or their bulky size and difficulty in automation. This paper proposes a novel optical microfluidic refractometer, consisting solely of a laser source, an optical microfluidic lens, and a CCD detector. Through an innovative “simple structure + algorithm” design, the sensor achieves high-precision measurement while significantly reducing cost and size and enhancing robustness. With the aid of signal processing algorithms, the device currently enables the detection of refractive index gradients as low as 1.4 × 10⁻⁵ within a refractive index range of 1.33 to 1.48. Full article

PRRSV poses a persistent global challenge to the swine industry due to its rapid evolution. This study aimed to characterize a novel PRRSV2 strain, HeB2023092, isolated from a suspected outbreak in China in September 2023. We performed virus isolation in porcine alveolar macrophages (PAMs), genome sequencing, phylogenetic analysis, and comprehensive genetic characterization. HeB2023092 replicated effectively in PAMs but not in Marc-145 cells. Phylogenetic analysis consistently grouped it with NADC30-like strains (L1.8). Notably, genomic analysis revealed a unique 41-amino acid deletion (478–518 aa) in Nsp2, in addition to the characteristic 111-amino acid deletion of NADC30-like strains. Significant amino acid variations were also found in the antigenic epitopes and N-glycosylation patterns of GP3 and GP5. Comprehensive recombination analysis identified three distinct recombinant regions, revealing a mosaic genome with a predominant NADC30-like backbone. The backbone incorporated genetic sequences from JXA1-like (L8.7) strains in two regions and from NADC34-like (L1.5) strains in one region. These findings highlight the continuous genetic evolution and complex epidemiology of PRRSV, underscoring the critical need for sustained surveillance and detailed characterization of circulating strains to inform effective control and vaccine development strategies. Full article

Extreme natural disasters can force microgrids into islanded operation, where low system inertia and asynchronous, time-varying communication delays present severe challenges to frequency stability. These challenges threaten not only short-term reliability but also the sustainable operation of renewable-dominated energy systems. Existing frequency control methods are often unable to robustly handle heterogeneous delays, thereby limiting the resilience of power systems with high shares of renewables. To address this issue, we propose a parametric Riccati equation-based frequency control method that adaptively adjusts control parameters to balance system robustness and optimality under asynchronous delays. Controller stability is guaranteed by Barbalat’s lemma. The main contributions include: (i) developing a microgrid frequency control model that incorporates asynchronous delays, (ii) designing a delay-aware controller using the parametric Riccati equation, and (iii) validating its effectiveness on a modified New England 39-bus system. Simulation results confirm that the proposed method enhances frequency stability under disaster-induced islanding scenarios. By ensuring robust and reliable operation of renewable-rich power systems, the proposed approach contributes to the sustainable integration of renewable energy, reduces blackout risks, and supports long-term environmental and socio-economic sustainability goals. Full article

Heart failure (HF) marks the culmination of numerous cardiac pathologies, presenting a major medical hurdle in prevention and treatment. In recent years, with the advancements in genomics and metabolomics, research has demonstrated that gut microbiota plays a significant role in the pathogenesis of HF. Trimethylamine N-oxide (TMAO) is a gut microbiota-derived metabolite and primarily sourced from foods abundant in choline, L-carnitine, and betaine. Research has shown that patients with HF exhibit higher levels of TMAO. Accumulating evidence has indicated that TMAO directly or indirectly mediates the occurrence and development of HF through multiple mechanisms. Furthermore, TMAO functions as a crucial prognostic marker in HF. Therefore, TMAO emerges as a potential therapeutic target for HF. This article reviews the generation and metabolic pathways of TMAO, emphasizes its pathophysiological mechanisms in HF, and explores promising therapeutic approaches targeting TMAO, offering novel insights and strategies for HF management. Full article

Purple pakchoi (Brassica rapa subsp. chinensis (L.) Hanelt) is rich in anthocyanins, which contribute to its significant edible, ornamental, and potential health-promoting value. The previous research on the purple-leaf trait of pakchoi was rather insufficient, key gene controlling the purple-leaf trait remains to be further elucidated. Fine mapping of the genes responsible for the purple-leaf trait is essential for establishing molecular marker-assisted breeding and facilitating genetic improvement. In this study, we used the inbred purple-leaf line ‘PQC’ and green-leaf line ‘HYYTC’ as parents to construct a six-generation genetic segregation population. We analyzed the inheritance pattern of the purple-leaf trait and combined Bulked Segregant Analysis Sequencing (BSA-seq) with penta-primer amplification refractory mutation system (PARMS) to map the causal gene. The main findings are as follows: the purple-leaf trait is controlled by a single dominant gene. Using BSA-seq and PARMS, the genes were mapped to a 470 kb region (31.18–31.65 Mb) on chromosome A03. Within this interval, 29 candidate genes were identified. Bra017888 which encoding trehalose phosphate synthase 10 (TPS10), was highlighted as a potential regulator of anthocyanin biosynthesis. A developed molecular marker, SNP31304070, based on the final candidate region, successfully distinguished between purple homozygous and purple heterozygous plants in the F₂ and F₃ populations, showing complete co-segregation with the trait. The marker could be applied to molecular-assisted breeding in purple pakchoi. Full article

With the rapid proliferation of unmanned aerial vehicles (UAVs) and the associated rise in security concerns, there is a growing demand for robust detection and identification systems capable of operating reliably in complex electromagnetic environments. To address this challenge, this paper proposes a deep learning-based passive UAV detection and identification system leveraging radio frequency (RF) spectrograms. The system employs a high-resolution RF front-end comprising a multi-beam directional antenna and a wideband spectrum analyzer to scan the target airspace and capture UAV signals with enhanced spatial and spectral granularity. A YOLO-based detection module is then used to extract frequency hopping signal (FHS) regions from the spectrogram, which are subsequently classified by a convolutional neural network (CNN) to identify specific UAV models. Extensive measurements are carried out in both line-of-sight (LoS) and non-line-of-sight (NLoS) urban environments. The proposed system achieves over 96% accuracy in both detection and identification under LoS conditions. In NLoS conditions, it improves the identification accuracy by more than 15% compared with conventional full-spectrum CNN-based methods. These results validate the system’s robustness, real-time responsiveness, and strong practical applicability. Full article

To investigate the geographical and species differences regarding mineral element content of camel milk, this research used camel milk from the Tacheng, Altay, and Ili regions of Xinjiang and cow milk, goat milk, and horse milk from the Tacheng region as subjects. The contents of 22 mineral elements were measured using inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectrometry (ICP-OES). The results showed that the contents of macro elements Ca, P, K, and Na in camel milk were significantly higher than those in other milk sources (p < 0.01). The contents of trace elements such as Se, Sr, and Ni were very significantly higher than those in other milk sources (p < 0.01). The content of 12 mineral elements in camel milk was very significantly higher than in other types of milk (p < 0.01). Principal component analysis (PCA) and factor analysis emphasized the relationship between element distribution and different milk sources, and the linear discriminant analysis (LDA) model could identify the species type of milk. Geographical analysis indicated that trace elements such as Sr, Ni, and Cr were highly significantly enriched in Tacheng camel milk (p < 0.01). The established LDA model achieved traceability of the geographical origin of Xinjiang camel milk. This research reveals the mineral nutritional advantages of camel milk and its geographical differentiation patterns, providing theoretical support for exploring the functional properties of camel milk and for identifying species and regions through minerals. It is important to promote the upgrading of the specialty dairy product industry. Full article

Disassembly is a crucial step in the remanufacturing of end-of-life (EoL) electronic products. Disassembly depth refers to the disassembly stop point determined by the disassembly sequence. For the disassembly depth optimization of EoL electronic products, a feasibility model with a fast convergence and low mean squared error (MSE) is needed to improve optimization accuracy. However, the use of a backpropagation neural network (BPNN) model or mathematical model often results in a slow convergence and high MSE due to the randomness of the initial weights and biases. In this study, an improved method for the disassembly depth optimization of smartphones based on a Particle Swarm Optimization-BPNN (PSO-BPNN) predictive model is proposed. Compared with the traditional BPNN optimization method, the proposed method in this study is that the BPNN predictive model is optimized by using PSO, which shows a superior predictive performance and reduces the MSE. The case of ‘Huawei P7’ is used to verify the feasibility of the method. The results show that the method maintains disassembly profit while reducing the disassembly time and carbon emissions by 17.1% and 7.8%, respectively. Compared with the BPNN model, the PSO-BPNN model converges 18.6%, 32.8%, and 16.6% faster in predicting the disassembly time, profit, and carbon emissions, respectively, with MSE reductions of 92.95%, 96.51%, and 92.74%, respectively. Full article

The four buckets phase demodulation method is a widely used sinusoidal modulation and demodulation technique in interferometry. Strict calibration is essential to minimize nonlinear errors in subsequent measurements. The core of the algorithm calibration lies in determining the initial phase value of the modulation signal that matches the modulation depth while overcoming the influence of system phase delay. Currently, there are few systematic calibration methods specifically designed for optical fiber interferometry. This paper proposes a self-calibration method based on triangular wave mixing for four buckets phase demodulation in fiber optic interferometric probes, which efficiently achieves self-calibration of the phase demodulation while the measured object remains stationary. Simulations and experimental validations were conducted, demonstrating that the optimal initial phase value of 0.62 rad during phase demodulation can be accurately identified under static conditions. The calibrated phase value was then applied to the displacement measurement, where the target displacement was effectively detected, resulting in a root mean square (RMS) error of 3.0337 nm and an average error of 2.4479 nm. Full article

Cancer treatment remains challenging due to the complexity of the tumor microenvironment, which promotes tumor heterogeneity and contributes to the development of multidrug resistance, ultimately hindering drug delivery and reducing therapeutic efficacy. In recent years, biomimetic nanocarriers have emerged as promising tools to address these challenges. Among them, cancer cell membrane (CCM)-coated nanoparticles (CCM-NPs) have attracted increasing attention due to their unique advantages, including homologous targeting, prolonged circulation mediated by self-recognition, and enhanced tumor penetration. Moreover, CCM-NPs can serve as versatile platforms for tumor vaccines by leveraging their inherent tumor-associated antigens and immunomodulatory potential. By leveraging CCMs to functionalize NPs, researchers have developed innovative approaches to improve drug delivery, enhance tumor immunotherapy, and optimize cancer vaccine efficacy. Despite these advancements, a comprehensive review summarizing the latest progress in CCM-based biomimetic nanocarriers for tumor treatment is lacking. This review integrates recent advances in CCM-NPs for targeted drug delivery and cancer vaccination, and discusses their fabrication, characterization, mechanisms and applications across multiple cancer types, which provides timely insights to guide their future development in precision tumor therapy. Full article

Conventional separation methods often prove ineffective for complex, refractory high-phosphorus iron ores. Recent advances propose a coal-based direct reduction dephosphorization-magnetic separation process, achieving significant dephosphorization efficiency. This review systematically analyzes phosphorus occurrence states in high-phosphorus oolitic iron ores across global deposits, particularly within iron minerals. We categorize contemporary research and elucidate dephosphorization mechanisms during coal-based direct reduction. Key factors influencing iron mineral phase transformation, iron enrichment, and phosphorus removal are comprehensively evaluated. Phosphorus primarily exists as apatite and collophane gangue m horization agents function by: (1) inhibiting phosphorus-bearing mineral reactions or binding phosphorus into soluble salts to prevent incorporation into metallic iron; (2) enhancing iron oxide reduction and coal gasification; (3) disrupting oolitic structures, promoting metallic iron particle growth, and improving the intergrowth relationship between metallic iron and gangue. Iron mineral phase transformations follow the sequence: Fe₂O₃ → Fe₃O₄ → FeO (FeAl₂O₄, Fe₂SiO₄) → Fe. Critical parameters for effective dephosphorization under non-reductive phosphorus conditions include reduction temperature, duration, reductant/dephosphorization agent types/dosages. Future research should focus on: (1) investigating phosphorus forms in iron minerals for targeted ore utilization; (2) reducing dephosphorization agent consumption and developing sustainable alternatives; (3) refining models for metallic iron growth and improving energy efficiency; (4) optimizing reduction atmosphere control; (5) implementing low-carbon emission strategies. Full article

In response to the issues of insufficient shredding efficiency, severe straw entanglement with equipment, and prone blade damage in existing banana straw crushing and returning machines, this paper innovatively proposes a liquid nitrogen (LN₂) cryo-pretreatment combined with a mechanical incorporation method by, firstly, conducting shear, tensile, and cooling timeliness mechanical experiments on banana straw sheaths using LN₂ low-temperature pretreatment, and then designing a corresponding spray device. Subsequently, an improved BAO-Fuzzy-PID control algorithm is presented, which significantly enhances the control performance of the fuzzy PID controller, with the steady-state error, overshoot, rise time, and settling time being 0, 0, 0.31 s, and 0.25 s, respectively. Finally, field experiments are executed, and the flow control accuracy test results indicated a maximum error of 3.32%, meeting the test requirements. Using spray height and spray angle as experimental factors and banana straw crushing qualification rate as the experimental indicator, a two-factor and five-level banana straw crushing experiment is presented. The optimal spray parameters are determined to be a spray height of 250 mm and a spray angle of 90°. At this point, the banana straw crushing qualification rate is 96.98%, meeting the quality requirements for banana straw crushing and significantly reducing straw entanglement. Full article