Search Results (41)

The importance of chaotic systems as the main pseudo-random cryptographic generator of encryption algorithms in the field of communication secrecy cannot be overstated, but in practical applications, researchers often choose to build upon traditional chaotic maps, such as the logistic map, for study and application. This approach provides attackers with more opportunities to compromise the encryption scheme. Therefore, based on previous results, this paper theoretically investigates discrete chaotic mappings in the real domain, constructs a general method for a class of quadratic chaotic mappings, and justifies its existence based on a robust chaos determination theorem for S single-peaked mappings. Based on the theorem, we construct two chaotic map examples and conduct detailed analysis of their Lyapunov exponent spectra and bifurcation diagrams. Subsequently, comparative analysis is performed between the proposed quadratic chaotic maps and the conventional logistic map using the 0–1 test for chaos and SE complexity metrics, validating their enhanced chaotic properties. Full article

With the growing global demand for clean energy, the accuracy of wind-power forecasting plays a vital role in ensuring the stable operation of power systems. However, wind-power generation is significantly influenced by meteorological conditions and is characterized by high uncertainty and multiscale fluctuations. Traditional recurrent neural network (RNN) and long short-term memory (LSTM) models, although capable of handling sequential data, struggle with modeling long-term temporal dependencies due to the vanishing gradient problem; thus, they are now rarely used. Recently, Transformer models have made notable progress in sequence modeling compared to RNNs and LSTM models. Nevertheless, when dealing with long wind-power sequences, their quadratic computational complexity (O(L²)) leads to low efficiency, and their global attention mechanism often fails to capture local periodic features accurately, tending to overemphasize redundant information while overlooking key temporal patterns. To address these challenges, this paper proposes a wind-power forecasting method based on dimension-transformed collaborative multidimensional multiscale attention (DTCMMA). This method first employs fast Fourier transform (FFT) to automatically identify the main periodic components in wind-power data, reconstructing the one-dimensional time series as a two-dimensional spatiotemporal representation, thereby explicitly encoding periodic features. Based on this, a collaborative multidimensional multiscale attention (CMMA) mechanism is designed, which hierarchically integrates channel, spatial, and pixel attention to adaptively capture complex spatiotemporal dependencies. Considering the geometric characteristics of the reconstructed data, asymmetric convolution kernels are adopted to enhance feature extraction efficiency. Experiments on multiple wind-farm datasets and energy-related datasets demonstrate that DTCMMA outperforms mainstream methods such as Transformer, iTransformer, and TimeMixer in long-sequence forecasting tasks, achieving improvements in MSE performance by 34.22%, 2.57%, and 0.51%, respectively. The model’s training speed also surpasses that of the fastest baseline by 300%, significantly improving both prediction accuracy and computational efficiency. This provides an efficient and accurate solution for wind-power forecasting and contributes to the further development and application of wind energy in the global energy mix. Full article

Declining freshwater resources have spurred interest in saline–alkali (SA) water aquaculture, with species like tilapia and rainbow trout demonstrating ecological plasticity in such environments. However, the molecular mechanisms underlying fish adaptation and quality impacts remain unclear. This study investigated the hybrid fish “Xianfeng No. 1” (Erythroculter ilishaeformis × Ancherythroculter nigrocauda), a key aquaculture species in China, under 60-day SA exposure. The results showed increased levels of oxidative stress markers (MDA) and antioxidant enzymes (SOD, CAT, GSH-Px), alongside improved quality traits. Transcriptomics revealed differentially expressed genes (DEGs) in muscle tissue associated with oxidative stress (UQCRFS1, UQCR10, CYC1), ion transport (COX5A, COX7C, COX7B), and the immune response (ATG9A, ATG2B, ATG2A, ULK1, ULK2, CFI, CFH). Metabolomics identified increased non-volatile flavors (e.g., glycine, proline) and collagen-related compounds. Integrated analysis highlighted the upregulation of GSR and GGT, and the downregulation of CHDH and GBSA, potentially driving glycine accumulation. These findings suggest that SA stress enhances antioxidant capacity, activates immune pathways, and modulates ion transport, enabling adaptation while improving meat quality. This study elucidates molecular mechanisms of fish acclimation to SA environments, providing insights for sustainable aquaculture development and breeding of stress-tolerant species in SA regions. Full article

Sichuan paocai, a microbial food predominantly fermented by lactic acid bacteria and hosting a complex and diverse microbial ecosystem, serves as an ideal habitat for bacteriophages. However, relatively few studies have been conducted on isolating bacteriophages from fermented vegetables and their application in vegetable fermentation. In this study, three staphylococcal bacteriophages, ΦSx-2, ΦSs-1, and ΦSs-2, were isolated and purified from Sichuan paocai using the spot test method. The morphological features of the phages were characterized using transmission electron microscopy (TEM), while key biological properties such as one-step growth kinetics were systematically evaluated, ultimately verifying their taxonomic placement within the Caudoviricetes class. Furthermore, the potential effects of these phages on the microbial community structure and physicochemical properties during paocai fermentation were investigated using high-throughput sequencing and standard physicochemical assays. Microbial community analysis demonstrated that introducing the phages significantly increased the relative abundance of lactic acid bacteria while reducing the prevalence of spoilage bacteria such as Erwinia, Pantoea, and Enterobacter. Physicochemical assessments revealed that adding phages accelerated the acidification process of paocai, effectively reduced nitrite levels, and increased the concentrations of lactic and acetic acids. Additionally, notable differences in color and flavor were observed between the two groups of paocai during the fermentation process. In summary, the inoculation of bacteriophages ΦSx-2, ΦSs-1, and ΦSs-2 optimized the microbial community structure, enhanced the fermentation process, and improved the quality of Sichuan paocai. Full article

Background: Heart failure (HF), the terminal stage of cardiovascular disease with high morbidity and mortality, remains poorly managed by current therapies. Ventricular remodeling in HF is fundamentally characterized by myocardial fibrosis. While ginsenoside Rb₁ has demonstrated anti-fibrotic effects in HF, the underlying mechanism remains unclear. Twist1, an upstream regulator of energy metabolism factors PGC-1α and PPARα, may attenuate fibrosis by preserving systemic energy homeostasis, suggesting its pivotal role in HF pathogenesis. This study explores ginsenoside Rb₁′s anti-HF mechanisms through the regulation of ginsenoside Rb₁ on these metabolic regulators. Methods: Sprague Dawley rats were subjected to a ligation of the left anterior descending coronary artery to induce an HF model, followed by ginsenoside Rb₁ treatment for 6 weeks. Therapeutic effects were evaluated through cardiac function assessment, myocardial histopathological staining (HE, Masson, immunofluorescence, immunohistochemistry), mitochondrial morphology observation (transmission electron microscopy), energy metabolism analysis (electron transport chain efficiency, mitochondrial membrane potential, ATP content), and protein expression profiling (Twist1, PGC-1α, PPARα, GLUT4, PPARγ). Additionally, H9c2 cells induced with endothelin-1 to model HF were employed as an in vitro model to further investigate ginsenoside Rb₁′s regulatory effects on the Twist1/PGC-1α/PPARα signaling pathway. Results: Ginsenoside Rb₁ can restore cardiac function in HF rats, improve mitochondrial function, alleviate energy metabolism disorders, and inhibit ventricular remodeling. By modulating the Twist1/PGC-1α/PPARα signaling pathway, ginsenoside Rb₁ suppressed the abnormal overexpression of Twist1 and maintained normal expression of downstream PGC-1α and PPARα. In vitro experiments further demonstrated that ginsenoside Rb₁ significantly inhibited Twist1 expression in H9c2 cardiomyocytes with HF while promoting PGC-1α and PPARα expression, thereby restoring myocardial energy metabolism and mitigating ventricular remodeling in HF. Conclusions: Ginsenoside Rb₁ can inhibit the upregulation of Twist1 and activate the expression of its downstream PGC-1α and PPARα expression, by modulating the Twist1/PGC-1α/PPARα signaling pathway, alleviating ventricular remodeling in HF patients and improving myocardial energy metabolism dysfunction. Twist1 may be a key target for the treatment of HF. This study not only elucidates the mechanism by which ginsenoside Rb₁ alleviates HF, but also provides new insights into the clinical treatment of HF. Full article

Background: Chronic migraine (CM) is a common complex nervous system disease, often accompanied by symptoms of the digestive tract that interact with each other, leading to prolonged and difficult-to-cure migraines. These symptoms are associated with abnormalities in 5-HT and its receptors. Wuzhuyu decoction (WZYD) is a traditional Chinese medicine prescription commonly used in clinics to treat CM; it relieves gastrointestinal symptoms, such as nausea and vomiting; however, its mechanism is still unclear. Investigating the differences in the role of WZYD compared to existing drugs targeting 5-HT receptors in the treatment of CM not only helps elucidate its pathogenesis but also provides possibilities for the development of new therapeutic approaches. Methods: An inflammation soup (IS)-induced CM male rat model was established. Based on a preliminary experiment, the target of WZYD in treating CM was determined by network pharmacology, and verified by molecular docking. ELISA, immunofluorescence, western blot, and real-time quantitative polymerase chain reaction (RT-qPCR) were used to evaluate the expression levels of CM-related indicators (5-HT, calcitonin gene-related peptide (CGRP), and c-Fos) to ensure the successful establishment of the CM model and the effectiveness of the drug. On this basis, the protein expression levels of 5-HT1A/3A receptors and their cAMP-response element binding protein (CREB) signaling pathway were detected by western blot and immunohistochemistry. The role of 5-HT1A/3A receptors in the treatment of CM by WZYD was validated using a 5-HT1A receptor antagonist (WAY 100635) and a 5-HT3A receptor agonist (SR 57227). Results: The results showed that WZYD increased the expression of 5-HT in the brain, decreased the expression of CGRP, c-Fos, ionized calcium-binding adapter molecule 1 (Iba1), and relieved CM. At the same time, WZYD also increased the expression of the 5-HT1A receptor and decreased the expression of the 5-HT3A receptor in the brain and colon of CM rats. Subsequently, WZYD further exerted its brain-gut integrated therapeutic effects by regulating the CREB signaling pathway mediated by 5-HT1A/3A receptors in the brain and colon of CM rats. Conclusions: WZYD not only regulates neurotransmitters in the brain and colon at the same time, but also specifically regulates 5-HT1A/3A receptors in the brain and colon, which explains the characteristics and advantages of WZYD from a new perspective. While effectively relieving headache symptoms, it also improves related gastrointestinal symptoms, which is more conducive to the treatment of CM. Full article

Accurate segmentation of the liver and liver tumors is crucial for clinical diagnosis and treatment. However, the task poses significant challenges due to the complex morphology of tumors, indistinct features of small targets, and the similarity in grayscale values between the liver and surrounding organs. To address these issues, this paper proposes an enhanced 3D UNet architecture, named ELANRes-MSCA-UNet. By incorporating a structural re-parameterized residual module (ELANRes) and a multi-scale convolutional attention module (MSCA), the network significantly improves feature extraction and boundary optimization, particularly excelling in segmenting small targets. Additionally, a two-stage strategy is employed, where the liver region is segmented first, followed by the fine-grained segmentation of tumors, effectively reducing false positive rates. Experiments conducted on the LiTS2017 dataset demonstrate that the ELANRes-MSCA-UNet achieved Dice scores of 97.2% and 72.9% for liver and tumor segmentation tasks, respectively, significantly outperforming other state-of-the-art methods. These results validate the accuracy and robustness of the proposed method in medical image segmentation and highlight its potential for clinical applications. Full article

The predation capacity and functional responses of adult females of the phytoseiid mites Amblyseius largoensis (Muma), Proprioseiopsis lenis (Corpuz and Rimando), Paraphytoseius cracentis (Corpuz and Rimando), and Amblyseius swirskii (Athias-Henriot) were studied on eggs and first instars of the western flower thrips, Frankliniella occidentalis (Pergande), in the laboratory at 25 °C and 30 °C. At both temperatures, the functional response of all four phytoseiid mites was type II to first instars of the thrips. In contrast, when offered thrips eggs, the functional response was type III. At both temperatures tested, A. swirskii had the highest mean daily consumption of first-instar F. occidentalis, followed by A. largoensis, P. cracentis, and P. lenis. Amblyseius largoensis had the shortest handling time and the highest maximum attack rate when first-instar thrips were the prey. When fed on thrips eggs, A. largoensis had the highest mean daily consumption, followed by A. swirskii, P. cracentis, and P. lenis. On thrips eggs, A. swirskii showed the shortest handling time and highest maximum attack rate. Our findings indicate that all four phytoseiids had a better ability to prey on first-instar larvae of F. occidentalis compared to thrips eggs. At 25 and 30 °C, A. largoensis was the better predator on thrips larvae, whereas A. swirskii was superior in consuming eggs of F. occidentalis. Proprioseiopsis lenis was the inferior predator on both thrips larvae and eggs compared to the other phytoseiids tested. Full article

Accurate estimation of surface evapotranspiration (ET) in the Heihe River Basin using remote sensing data is crucial for understanding water dynamics in arid regions. In this paper, by coupling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization. A hybrid modeling algorithm, two physical process-based ET algorithms (Penman–Monteith-based and Priestley–Taylor-based ET algorithms), and three pure machine learning algorithms (Random Forest, Extreme Gradient Boosting, and K Nearest Neighbors) are comparatively analyzed for estimating the ET. The results showed that, in general, the machine learning model optimized by parameters was able to better predict the surface conductance of the hybrid model. Driver analyses showed that radiation, normalized difference vegetation index (NDVI), and air temperature had high correlations with ET. The hybrid model had a better prediction performance for ET than the other five models, and it improved the R₂ of the two physical process-based algorithms to 0.9, reduced the root mean square error (RMSE) to 0.5 mm/day, reduced the BIAS to 0.2 mm/day, and improved the Kling–Gupta efficiency (KGE) to 0.9. The hybrid model outperformed the others across different time scales, displaying lower BIAS, RMSE, and higher KGE. Spatially, its ET patterns aligned with regional vegetation changes, with superior accuracy in annual ET estimation compared to the other models. Comparison with other ET products shows that the estimation results based on the hybrid model have better performance. This approach not only improves the accuracy of ET estimation but also improves the understanding of the physical mechanism of ET estimation by pure machine learning models. This study can provide important support for understanding ET and hydrological processes under different climatic and biotic vegetation in other arid and semi-arid regions. Full article

Objective: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors’ puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. Methods: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. Results: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors’ planning efficiency. Conclusion: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value. Full article

To address the lack of effective monitoring, evaluation, and prediction methods for water stress in citrus seedlings, we conducted 10 sets of water stress gradient experiments. Based on the experimental dataset, we constructed, trained, and improved an MLP classification model for citrus seedling water stress. In addition, we developed a monitoring, evaluation, and prediction system based on this model. The experiments demonstrated that 7 days of slight water stress can induce changes in overall root wilting and growth stagnation, and the chlorophyll content in the leaves can decrease by up to 11.78%. Furthermore, the optimal VWC for seedlings was [45%, 50%], the boundary of drought was [20%, 25%], and the boundary of waterlogging was [50%, 55%]. We validated the effectiveness of the system in assessing the growth status of seedlings over the past 7 days and predicting it after 7 days through testing sets and experiments on slight water stress. We found that the system achieved non-destructive remote monitoring, evaluation, and prediction of slight water stress in citrus seedlings, thus enhancing seedling quality. These research findings provide valuable insights into water stress management in citrus seedlings and other crops. Full article

The first quantum revolution has brought us the classical Internet and information technology. Today, as technology advances rapidly, the second quantum revolution quietly arrives, with a crucial moment for quantum technology to establish large-scale quantum networks. However, solid-state quantum bits (such as superconducting and semiconductor qubits) typically operate in the microwave frequency range, making it challenging to transmit signals over long distances. Therefore, there is an urgent need to develop quantum transducer chips capable of converting microwaves into optical photons in the communication band, since the thermal noise of optical photons at room temperature is negligible, rendering them an ideal information carrier for large-scale spatial communication. Such devices are important for connecting different physical platforms and efficiently transmitting quantum information. This paper focuses on the fast-developing field of optomechanical quantum transducers, which has flourished over the past decade, yielding numerous advanced achievements. We categorize transducers based on various mechanical resonators and discuss their principles of operation and their achievements. Based on existing research on optomechanical transducers, we compare the parameters of several mechanical resonators and analyze their advantages and limitations, as well as provide prospects for the future development of quantum transducers. Full article

The demand for the power grid system’s capacity to undergo peak-shaving is increasing as the proportion of renewable energy rises. In China, nuclear power units usually only provide a base load operation in the view of safety and economic considerations, but they do not provide load adjustment services, which undoubtedly increases the pressure of grid load adjustment. In this paper, a novel flexibility load adjustment strategy of the CHP nuclear unit is studied, which is achieved by introducing the thermal storage tank (TST) into the Rankine cycle without changing the output of the nuclear reactor. The AP1000 pressurized water reactor nuclear power unit for combined heat and power is taken as an example, and the thermodynamic model is established through the water vapor equation. Furthermore, the reference system is simulated for the goal of minimizing the imbalance between power supply and demand, and the flexibility–environment–economy benefits are evaluated. The results show that the heat storage/release of the TST may achieve power output flexible adjustment of the nuclear unit, and the power imbalance of the reference energy system is reduced from 1107.99 MWh to 457.24 MWh, a reduction of 58.73%. The introduction of a 600 MWh TST can enable the reference unit to contribute 335 MWh of peak electricity within the reference day. From the perspective of replacing the power generation output increment of coal-fired power units with equal amounts, it can achieve a reduction of 106.09 tons of coal consumption in the case day, which means that 277.73 tons of CO₂ emissions can be reduced. The profit of the reference unit can be improved by CHY 70,125 via participating in load adjustment in the case day if following the time-of-use electricity price. Full article

Non-typhoidal salmonellosis is a dangerous foodborne disease that causes enormous economic loss and threatens public health worldwide. The consumption of food, especially poultry or poultry products, contaminated with non-typhoidal Salmonella (NTS) is the main cause of human salmonellosis. To date, no research has identified the molecular epidemiological characteristics of NTS strains isolated from breeder chicken farms in different provinces of China. In our study, we investigated the antimicrobial resistance, phylogenetic relationships, presence of antimicrobial resistance and virulence genes, and plasmids of NTS isolates recovered from breeder chicken farms in five provinces of China between 2020 and 2021 by using a whole-genome sequencing (WGS) approach and phenotypic methods. All sequenced isolates belonged to six serovars with seven sequence types. Nearly half of the isolates (44.87%) showed phenotypic resistance to at least three classes of antimicrobials. Salmonella enterica serotype Kentucky harbored more antimicrobial resistance genes than the others, which was highly consistent with phenotypic resistance. Furthermore, the carried rate of 104 out of 135 detected virulence genes was 100%. Overall, our WGS results highlight the need for the continuous monitoring of, and additional studies on, the antimicrobial resistance of NTS. Full article

Performance evaluation of microorganisms that have emulsifying and degrading effects on crude oil has been extensively conducted in the laboratory. However, the ultimate goal of microbial enhanced oil recovery is field application, so the pilot simulation experiments are crucial. In this study, a micro-visualization model and the real cores were chosen to investigate the actual recovery efficiency and the mechanism of the consortium bacteria B-ALL, which has been proven to have good emulsification and degradation effects in lab studies in porous media. At the same time, the cast thin sections and rate-controlled porosimetry were combined to analyze the pore throat structure of the displacement core. It was found that the recovery efficiency was positively correlated with the microbial injection volume as well as the incubation time. For the microscopic model with high pores and high permeability, the efficiency of secondary water flooding can be increased by 44.77% after six days of incubation with two pore volume microbes. For the real tight cores, the maximum secondary water flooding efficiency under the same condition was 6.98%. Through visual modeling, microorganisms increase the oil washing efficiency mainly by emulsification and changing the wettability. The generated oil droplets will play a role in plugging and improving the wave efficiency. However, tight reservoirs have the characteristics of large pores and small throats, and curved and necking throats are developed, greatly reducing permeability. The microbial recovery efficiency was lower under shorter cultivation times. This study provides a practical basis for the application of consortium bacteria in tight oil fields to enhance recovery. Full article