Search Results (84)

Accurate thermospheric mass density (TMD) prediction is critical for applications in solar-terrestrial physics, spacecraft safety, and remote sensing systems. While existing deep learning (DL)-based TMD models are predominantly data-driven, their performance remains constrained by observational data limitations. This study proposes ResNet-MSIS, a novel hybrid framework that integrates prior knowledge from the empirical NRLMSIS-2.1 model into a residual network (ResNet) architecture. The incorporation of NRLMSIS-2.1 enhanced the performance of ResNet-MSIS, yielding a lower root mean squared error (RMSE) of 0.2657 × ${10}^{-12}$ kg/m³ in TMD prediction compared with 0.2750 × ${10}^{-12}$ kg/m³ from ResNet, along with faster convergence during training and better generalization on Gravity Recovery and Climate Experiment (GRACE-A) data, which was trained and validated on the CHAllenging Minisatellite Payload (CHAMP) TMD data (2000–2009, altitude of 305–505 km, avg. 376 km) under quiet geomagnetic conditions (Kp ≤ 3). The DL model was subsequently tested on the remaining CHAMP-derived TMD observations, and the results demonstrated that ResNet-MSIS outperformed both ResNet and NRLMSIS-2.1 on the test dataset. The model’s robustness was further demonstrated on GRACE-A data (2002–2009, altitude of 450–540 km, avg. 482 km) under magnetically quiet conditions, with the RMSE decreasing from 0.3352 × ${10}^{-12}$ kg/m³ to 0.2959 × ${10}^{-12}$ kg/m³, indicating improved high-altitude prediction accuracy. Additionally, ResNet-MSIS effectively captured the horizontal TMD variations, including equatorial mass density anomaly (EMA) and midnight density maximum (MDM) structures, confirming its ability to learn complex spatiotemporal patterns. This work underscores the value of merging data-driven methods with domain-specific prior knowledge, offering a promising pathway for advancing TMD modeling in space weather and atmospheric research. Full article

Recent advancements in wearable devices have significantly enhanced remote patient monitoring, enabling healthcare professionals to evaluate conditions within home settings. While electronic health records (EHRs) offer extensive clinical data, they often lack crucial contextual information about patients’ daily lives and symptoms. By integrating continuous self-reported outcomes related to vulnerability, anxiety, and depression from older adult cancer survivors with objective data from wearables, we can develop personalised risk models that address time-varying risk factors in cancer care. Our study combines real-world data from wearable devices with self-reported information, employing process mining techniques to analyse dynamic risk models for vulnerability and anxiety. Unlike traditional static assessments, this approach recognises that risk factors evolve. Collaborating with healthcare professionals, we analysed data from the LifeChamps study to create two dynamic risk models. This collaborative effort revealed how activity and sleep patterns influence self-reported vulnerability and anxiety among participants. It underscored the potential of wearable sensors and artificial intelligence techniques for deeper analysis and understanding, making us all part of a larger effort in cancer care. Overall, patients with prolonged sedentary activity had a higher risk of vulnerability, while those with highly dynamic sleep patterns were more likely to report anxiety and depression. Prostate-metastatic patients showed an increased risk of vulnerability compared to other cancer types. Full article

We incorporated a comprehensive dataset encompassing recent measurements from satellites such as the Macau Science Satgellite-1 (MSS-1), Swarm, and CHAMP, as well as aero and ocean magnetic measurements, alongside ground-based data from 1936 to 2000. This amalgamation is the basis for constructing a lithospheric magnetic field model of the Chinese mainland, employing the three-dimensional Surface Spline (3DSS) model. Additionally, we used the World Digital Magnetic Anomaly Map (WDMAM)-2.1 and CHAOS-7.13 models to address data gaps horizontally and vertically. To evaluate the efficacy of the new model, we compared it not only with established models such as SHA1050, NGDC720, and LCS-1 but also with the new model excluding the MSS-1 data. The results show a high agreement between the 3DSS model and other global models at a spatial resolution of 0.05°. Furthermore, we inspected the rapid variations in the magnetic field with increasing altitude, demonstrating a smooth transition across the altitudes covered by the three satellites. Error analyses reflected the importance of MSS-1 data, which contributed notably to modelling by capturing finer-scale magnetic structures. The increased data availability correlated positively with the model’s accuracy, as evidenced by the Root Mean Square Error (RMSE), registering an optimal value of 0.02 nT. The new model reveals additional geological details in southern Tibet, northeastern Inner Mongolia, and the adjacent areas of Liaoning and Jilin provinces, which are not discernible in other global models. The relationship between these anomalies and heat flow in northeastern China appears less evident, suggesting a complex interplay of orogenic processes and surface mineralogy in shaping these magnetic signatures. Full article

Mixing and matching N₂-fixing leguminous species is a crucial strategy to enhance quality and efficiency in sustainable forestry. Tree leaves and rhizosphere are primary sites for matter and energy exchange, functioning as key assimilation organs that forests provide for ecological services. The introduction of functional species alters soil properties, which, in turn, directly or indirectly shape leaf functional traits, soil microbial dynamics, and their association. However, the correlation between aboveground functional traits and belowground rhizosphere soil microorganisms of dominant tree species in mixed leguminous and non-leguminous forests remains unclear. In this study, the responses and correlations of leaf functional traits and rhizosphere soil microbial communities of Castanopsis hystrix Hook. f. & Thomson ex A. DC. across three forest types were investigated. A pure forest (PF) of C. hystrix was designated as control forest, while a leguminous mixed forest (LMF) consisting of C. hystrix and the leguminous species Acacia mangium Willd. as well as a non-leguminous mixed forest (NMF) comprising C. hystrix and the non-leguminous species Schima superba Gardner & Champ. served as experimental forests. Seven leaf functional trait indices were measured, and the high-throughput sequencing of soil microbial communities was included in the analysis. The results were as follows: Firstly, compared to the pure forest, the specific leaf area (SLA) of C. hystrix significantly decreased in both mixed forest types (p < 0.05). Additionally, in comparison to the pure forest, the leaf area (LA) and leaf organic carbon content (LOC) of C. hystrix significantly reduced (p < 0.05), whereas the leaf total phosphorus content (LTP) significantly increased in the non-leguminous tree species mixed forest (p < 0.01). The leaf dry matter content (LDMC), relative chlorophyll content (RCC), and leaf total nitrogen content (LTN) of C. hystrix exhibited no significant differences among the three forest types (p > 0.05). Secondly, neither the dominant phyla of rhizosphere soil microorganisms nor the bacterial richness and diversity had differences in the mixed forests. However, the richness and diversity of rhizosphere soil fungi significantly increased in the mixed forests, and those in the leguminous mixed forest exhibited more positive effects compared to those in the non-leguminous mixed forest. Finally, redundancy analysis (RDA) showed significant correlations between plant leaf functional traits and rhizosphere soil microorganisms. Specifically, LDMC, SLA, LTN, and LTP of C. hystrix showed significant correlations with differences in the structure of bacterial community (p < 0.05), and LTN was significantly correlated with differences in the structure of the fungal community (p < 0.05). In summary, we found that plant leaf functional traits and the community of rhizosphere soil microorganisms displayed significant differences in the mixed forests, and those mixed with leguminous trees may further enhance the assimilation processes by modifying the utilization of nutrients such as carbon, nitrogen, and phosphorus by plants and microorganisms. Meanwhile, our results support the interaction of physiological and ecological processes between the aboveground and belowground parts of C. hystrix. These findings emphasize the important roles of N₂-fixing leguminous trees and synergy of aboveground–belowground processes in establishing sustainable artificial forests. Full article

Non-structural carbohydrates (NSC) are important carbon pools in trees, and previous studies have mainly focused on the concentration of NSC in tree organs such as leaves, branches, trunk, and root, separately. However, the seasonality of the concentration of NSC in different organs among tree species in the subtropical forests is less known. In this study, we measured the seasonal dynamics of the concentration of NSC in four tree species (Nothotsuga longibracteata W. C. Cheng, Pinus kwangtungensis Chun ex Tsiang, Schima superba Gardn. et Champ, and Betula alnoides Buch.-Ham. Ex D.Don) in subtropical forests at organ levels including canopy, trunk, and root. The results showed that the concentration of NSC in conifer species was higher than that in broadleaf species. Also, the average concentration and range of the concentration of NSC were higher in the canopy than in other organs. The concentration of NSC decreased at the beginning of the growing season and increased at the end of the growing season for all species. Specifically, the concentration of NSC in tree species was significantly higher in the dry season than that in the wet season. Our results revealed the seasonal dynamics of NSC in different organs, which is beneficial to a better understanding of the growth strategies of different tree species in subtropical regions. Full article

Introduction: Parkinson’s disease (PD) is characterized by motor and cognitive impairments that often manifest as distinct motor subtypes: Postural Instability Gait Difficulty (PIGD) and Tremor-Dominant (TD). Motor–cognitive interference, especially under dual-task (DT) walking conditions, may vary by subtype, providing insights into specific impairments. This study explored DT interference effects in PD subtypes, focusing on the potential impact of self-reported physical activity, which may help mitigate subtype-specific impairments and improve motor–cognitive function. Methods: PD patients classified as PIGD or TD and healthy controls completed single-task (ST) and DT walking assessments involving different cognitive tasks (Serial Subtraction, Auditory Stroop, and Clock Task). Physical activity levels were evaluated using the CHAMPS questionnaire, analyzing the self-reported frequency and duration of weekly exercise-related activities. Results: Interference effects were significantly different between PD patients and controls, with the PIGD group showing greater motor impairment under high cognitive load, primarily affecting gait, than the TD and control groups. Performance differences between groups diminished as cognitive load increased. Self-reported physical activity does not significantly moderate motor performance under DT conditions, suggesting that activity levels in this sample are insufficient to offset motor–cognitive interference. However, like group affiliation, physical activity directly influences motor performance during DT conditions, indicating that both factors independently impact motor–cognitive function in PD. Discussion: These findings suggest that DT assessments help differentiate PD motor subtypes, as group differences were minimal in ST conditions. While physical activity is associated with general improvements in motor ST and DT performance in PD and controls, the lack of a significant moderating effect from self-reported exercise-related physical activity indicates that current activity levels may not be high enough to counter motor–cognitive interference. More intensive or DT-specific exercise may be required to reduce interference effects. Future research should examine the role of structured physical activity programs, potentially incorporating DT training, to evaluate their impact on motor–cognitive interference in PD. Full article

Optimizing forest management requires a comprehensive understanding of how soil properties and microbial communities evolve across different plantation ages. This study examines variations in soil nutrient dynamics, enzyme activities, and bacterial communities in Schima superba Gardn. & Champ plantations of 10, 15, 27, 55, and 64 years. By analyzing soil from depths of 0–20 cm, 20–40 cm, and 40–60 cm, we identified significant age-related trends in soil characteristics. Notably, nutrient contents, including total organic carbon (TOC), total phosphorus (TP), total carbon (TC), total nitrogen (TN), and nitrate nitrogen (${\mathrm{NO}}_3^{-}$-N), as well as soil water content (SWC), peaked in 55-year-old mature plantations and decreased in 64-year-old over-mature plantations. Enzyme activities, such as urease, sucrase, and acid phosphatase, decreased with soil depth and exhibited notable differences across stand ages. Microbial community analysis indicated the predominance of Acidobacteria, Chloroflexi, Proteobacteria, Actinobacteria, and Verrucomicrobiota in nutrient cycling, with their relative abundances varying significantly with age and depth. Mature and over-mature plantations exhibited higher absolute abundances of functional genes related to methane metabolism, nitrogen, phosphorus, and sulfur cycling. Reduced calcium ion levels were also linked to lower gene abundance in carbon degradation, carbon fixation, nitrogen, and phosphorus cycling, while increased TOC, ${\mathrm{NH}}_4^{+}$-N, ${\mathrm{NO}}_3^{-}$-N, and AP correlated with higher gene abundance in methane metabolism and phosphorus cycling. Our findings suggest that long-term cultivation of Schima superba enhances soil nutrient cycling. Calcium ion was identified as a significant factor in assessing soil properties and microbial dynamics across different stand ages, suggesting that extended plantation rotations can improve soil health and nutrient cycling. Full article

Background and Aims: Soft drink consumption is suspected to negatively impact bone health in children, but longitudinal evidence is limited. This study assessed the association between soft drink intake and bone health outcomes in Danish schoolchildren aged 7.7–12 years, within a physical activity intervention framework. Methods: This study was nested in the CHAMPS-DK trial, a quasi-experimental study. Participants (n = 529) were recruited from intervention schools offering 270 min of physical education (PE) per week (active arm) and control schools with 90 min of standard PE. Soft drink intake was assessed via a food-frequency questionnaire at baseline. Dual-energy X-ray absorptiometry (DXA) was used to measure Bone Mineral Content (BMC), Bone Area (BA), and Bone Mineral Density (BMD) at baseline and two-year follow-up (primary outcomes). Fracture incidence over a five-year period was recorded using the SMS-Track parental reporting system (secondary outcome). Multilevel mixed-effects linear regression and Weibull survival models were used to analyze associations. Results: Soft drink intake of more than twice per month did not significantly affect BMC, BA, or BMD over two years (Total body BMD: β = 0.004; 95% CI: (−0.007; 0.016). Adjustment for confounders such as age, sex, BMI, pubertal status, socioeconomic status, and physical activity did not change the results. Additionally, no significant difference in fracture risk was observed (HR = 0.86; 95% CI: [0.43; 1.71]). Conclusions: Soft drink intake had no measurable impact on bone health indices or fracture risk in children, irrespective of PE intervention. Future studies should investigate the effects of specific soft drink types (carbonated vs. non-carbonated) on bone development. Full article

Revealing the interactions between stand structure factors and ecosystem functions is crucial for enhancing forest soil and water conservation, as well as carbon storage. However, the optimal stand structure configuration for achieving superior ecological functions remains unclear, particularly in complex subtropical evergreen broad-leaved forests. Using Schima superba Gardn. et Champ. forests in Dongbai Mountain as a case study, this study investigated the effects of seven stand structure factors—stand density, canopy density, uniform angle index, and mixing degree—on three key ecosystem functions, water-holding function, soil improvement function, and carbon sequestration. Redundancy analysis (RDA) and structural equation modeling (SEM) were employed to quantify these relationships. The results identified stand density as the most influential factor, directly or indirectly affecting ecosystem functions by regulating other structural attributes. Optimal structural configurations were determined, including stand densities of 1228, 1532, and 1675 plants·hm⁻² for maximizing water-holding function, soil improvement function, and carbon sequestration, respectively. Recommendations emphasize adjusting stand density, canopy density, uniform angle index, and mixing degree according to site-specific conditions. Practical strategies, such as replanting, intercropping, and introducing functionally complementary species, should aim to enrich vertical structure, maintain species randomness, and avoid dominance by a single species or excessive density. These findings offer actionable insights for improving the ecological functions of subtropical forests and have broader implications for sustainable forestry management, advancing regional carbon neutrality, and addressing global ecological challenges. Full article

Obesity is a chronic disease that profoundly impacts human health, and the role of plant-based formulas (PBFs) in combating obesity has garnered significant interest. Studies have revealed that fermentation significantly enhances the taste, aroma, quality, and health benefits of PBF water extract, with pasteurization being the preferred sterilization technology. However, few studies have investigated the effects of pasteurization on the active components and potential functions of PBF water extract fermentation broth. To examine the impact of pasteurization on fermented water extract of Millettia speciosa Champ (FH08F) and its potential anti-obesity properties, the components of FH08F and thermal-pasteurized FH08F (FH08FS) were analyzed in this study. The analysis revealed a substantial rise in ester content following sterilization. This can be attributed to the acidic environment that promotes the esterification reaction during the heating phase. Network pharmacology was employed to thoroughly examine seven active components of upregulated compounds (URCs) with potential obesity targets, which constituted 92.97% of the total URC content, and four of them were nitrogen-containing aromatic heterocyclic compounds (NAHCs), which accounted for 90.33% of the total URC content. Upregulated NAHCs appear to actively contribute to efficacy against obesity. Molecular docking analyses have shown that theophylline, an NAHC, has the strongest binding affinity with the obesity-related target PTGS2 (Prostaglandin G/H synthase 2, 5FLG). These results imply that theophylline may directly activate PKA/PKG-mediated phosphorylated hormone-sensitive lipase (p-HSL), thereby promoting lipolysis through the cAMP signaling pathway and stimulating the catabolism of triglycerides (TGs) to combat obesity. In conclusion, pasteurization substantially alters the composition of FH08F, and NAHCs are likely to play a significant role in its potential anti-obesity function. These findings provide a scientific foundation for the potential therapeutic effect of FH08FS on obesity and associated metabolic diseases. Full article

As the application of the Global Navigation Satellite System (GNSS) continues to expand, its stability and safety issues are receiving more and more attention, especially the interference problem. Interference reduces the signal reception quality of ground terminals and may even lead to the paralysis of GNSS function in severe cases. In recent years, Low Earth Orbit (LEO) satellites have been highly emphasized for their unique advantages in GNSS interference detection, and related commercial and academic activities have increased rapidly. In this context, based on the signal-to-noise ratio (SNR) and radio-frequency interference (RFI) measurements data from COSMIC-2 satellites, this paper explores a method of predicting RFI measurements using SNR correlation variations in different GNSS signal channels for application to the detection and localization of civil terrestrial GNSS interference signals. Research shows that the SNR in different GNSS signal channels shows a correlated change under the influence of RFI. To this end, a CNN-BiLSTM-Attention model combining a convolutional neural network (CNN), bi-directional long and short-term memory network (BiLSTM), and attention mechanism is proposed in this paper, and the model takes the multi-channel SNR time series of the GNSS as the input and outputs the maximum measured value of RFI in the multi-channels. The experimental results show that compared with the traditional band-pass filtering inter-correlation method and other deep learning models, the model in this paper has a root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (R²) of 1.0185, 1.8567, and 0.9693, respectively, in RFI prediction, which demonstrates a higher RFI detection accuracy and a wide range of rough localization capabilities, showing significant competitiveness. Since the correlation changes in the SNR can be processed to decouple the signal strength, this model is also suitable for future GNSS-RO missions (such as COSMIC-1, CHAMP, GRACE, and Spire) for which no RFI measurements have yet been made. Full article

Mixed stands of tree species with complementary traits can modulate stand growth and timber quality. At the Fengshushan Forest Farm, mixtures of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) with Liquidambar formosana Hance, Schima superba Gardner & Champ., Elaeocarpus sylvestris (Lour.) Poir., Cinnamomum camphora (L.) Presl, and Chinese fir monoculture were established. Differences in stand growth and timber quality among these mixtures were assessed and a test was conducted to evaluate the factors influencing the mixture effects. The average diameter at breast height, tree height, stand volume, and individual tree annual increment of mixtures generally exceeded those of Chinese fir monocultures but not necessarily those of broad-leaved monocultures. When the net interaction between species was complementary, overyielding in mixtures occurred (RP_fir,bl > 0), which was influenced significantly by stand density, soil properties, and timber quality. The timber quality and wood production of Chinese fir were enhanced by mixture with some broad-leaved species, with reduced slenderness and knottiness in mixtures, and notable increases in medium- (average outturn rates of 56.13%) and large-diameter (11.71%) timber in C. lanceolata/C. camphora mixture. The growth and timber quality of Chinese fir are largely promoted when grown mixed with broad-leaved species. Overyielding at the stand level occurs where Chinese fir compensates for the underperformance of broad-leaved trees. Full article

Callerya speciosa (Champ. ex Benth.) Schot is a significant leguminous plant valued for its edible tuberous roots, which are a plentiful source of isoflavonoids. Basic helix–loop–helix (bHLH) transcription factors (TFs) have been reported to regulate secondary metabolism in plants, especially flavonoid biosynthesis. However, the bHLH genes in C. speciosa have not yet been reported, and their regulatory role in isoflavonoid biosynthesis remains unexplored. Here, 146 CsbHLH genes were identified in the C. speciosa genome, classifying them into 23 subfamilies based on the gene structures and phylogenetic relationships. All the CsbHLH proteins contained both motifs 1 and 2, whereas motif 8 was only distributed in subgroup III (d + e). Collinearity analysis demonstrated that fragmental replications are the primary driver of CsbHLH evolution, with the majority of duplicated CsbHLH gene pairs experiencing selective pressure. Nine candidate CsbHLH genes were found to play a potential role in regulating isoflavonoid biosynthesis through a combination of gene-to-metabolite correlation analysis and weighted gene co-expression network analysis (WGCNA). Additionally, the cis-regulatory elements and response to MeJA of these nine genes were characterized and confirmed through quantitative real-time PCR (qRT-PCR) analysis. Among them, three CsbHLHs (CsbHLH9, CsbHLH89, and CsbHLH95) were selected for further investigation. Yeast two-hybrid (Y2H), dual-luciferase (LUC) assays, bimolecular fluorescence complementation (BiFC) assays, and transient transformation demonstrated that CsbHLH9 acted as a transcriptional activator through its interaction with CsMYB36 and binding to the promoters of isoflavonoid biosynthesis genes in a MeJA-induced manner, such as CsIFR2, CsI3′H2, and CsCHS4, to promote isoflavonoid (calycosin, calycosin-7-o-glucoside, and formononetin) accumulation. Our results establish a basis for the functional analysis of bHLH genes and investigations into the molecular mechanisms underlying isoflavonoid biosynthesis in C. speciosa. Full article

This review examines ultra-low frequency (ULF) waves across different planetary environments, focusing on Earth, Mercury, and Saturn. Data from spacecraft missions (CHAMP, Swarm, and Oersted for Earth; MESSENGER for Mercury; and Cassini for Saturn) provide insights into ULF wave dynamics. At Earth, compressional ULF waves, particularly Pc3 waves, show significant power near the equator and peak around Magnetic Local Time (MLT) = 11. These waves interact complexly with Alfvén waves, impacting ionospheric responses and geomagnetic field line resonances. At Mercury, ULF waves transition from circular to linear polarization, indicating resonant interactions influenced by compressional components. MESSENGER data reveal a lower occurrence rate of ULF waves in Mercury’s foreshock compared to Earth’s, attributed to reduced backstreaming protons and lower solar wind Alfvénic Mach numbers, as ULF wave activity increases with heliocentric distance. Short Large-Amplitude Magnetic Structures (SLAMS) observed at Mercury and Saturn show distinct characteristics compared to those of Earth, including the presence of whistler precursos waves. However, due to the large differences in heliospheric distances, SLAMS (their temporal scale size correlate with the ULF wave frequency) at Mercury are significantly shorter in duration than at Earth or Saturn, since the ULF wave frequency primarily depends on the strength of the interplanetary magnetic field. This review highlights the variability of ULF waves and SLAMS across planetary environments, emphasizing Earth’s well-understood ionospheric interactions and the unique behaviours observed for Mercury and Saturn. These findings enhance our understanding of space plasma dynamics and underline the need for further research regarding planetary magnetospheres. Full article

The genus Ilex belongs to the sole family and is the single genus within the order Aquifoliales, exhibiting significant phenotypic diversity. However, the genetic differences underlying these phenotypic variations have rarely been studied. In this study, collinearity analyses of three Ilex genomes, Ilex latifolia Thunb., Ilex polyneura (Hand.-Mazz.) S. Y. Hu, and Ilex asprella Champ. ex Benth., indicated a recent fusion event contributing to the reduction of chromosomes in I. asprella. Comparative genome analyses showed slight differences in gene annotation among the three species, implying a minimal disruption of genes following chromosomal fusion in I. asprella. Comprehensive annotation of transposable elements (TEs) revealed that TEs constitute a significant portion of the Ilex genomes, with LTR transposons being predominant. TEs exhibited an inverse relationship with gene density, potentially influencing gene regulation and chromosomal architecture. TE insertions were shown to affect the conformation and binding sites of key genes such as 7-deoxyloganetin glucosyltransferase and transmembrane kinase (TMK) genes, highlighting potential functional impacts. The structural variations caused by TE insertions suggest significant roles in the evolutionary dynamics, leading to either loss or gain of gene function. This study underscores the importance of TEs in shaping the genomic landscape and evolutionary trajectories of Ilex species. Full article