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The development of pulsed magnets capable of generating magnetic fields exceeding 100 Tesla has been recognized as a crucial pursuit for advancing the scientific research on high magnetic fields. However, the operation of magnets at ultra-high magnetic fields often leads to accidental failures at their ends, necessitating a comprehensive exploration of the underlying mechanisms. To this end, this study investigates, for the first time, the mechanical behaviors of Zylon fiber-reinforced polymers (ZFRPs) within pulsed magnets from a composite perspective. The study begins with mechanical testing of ZFRPs, followed by the development of its constitutive model, which incorporates the plasticity and progressive damage. Subsequently, in-depth analyses are performed on a 95-T double-coil prototype that experienced a failure. The outcomes reveal a notable reduction of approximately 45% in both the radial and axial stiffness of ZFRPs, and the primary reason for the failure is traced to the damage incurred by the end ZFRPs of the inner magnet. The projected failure field closely aligns with the experiment. Additionally, two other magnet systems, achieving 90.6 T and 94.88 T, are analyzed. Finally, the discussion delves into the impact of transverse mechanical strength of the reinforcement and axial Lorentz forces on the structural performance of magnets. [ABSTRACT FROM AUTHOR]

Accurate structural analyses of continuous fiber-reinforced polymers (FRPs) are imperative for diverse engineering applications, demanding efficient material constitutive models. Nonetheless, the constitutive modeling of FRPs is complicated by the nonlinear behavior resulting from internal damages and the inherent plasticity. Consequently, this study presents an innovative anisotropic constitutive model for FRPs, designed to adeptly capture both the damage evolution and plasticity. All requisite parameters can be easily obtained through fundamental mechanical tests, rendering the model practical and user-friendly. The model utilizes the three-dimensional Puck criteria to determine damages, initiating the evolution process through a combination of continuum damage mechanics and linear stiffness attenuation methods. This evolution is coupled with a one-parameter plastic model. Subsequently, the numerical implementation method, integrated into ANSYS, is detailed. This emphasizes the Cauchy stress and consistent tangent stiffness solution strategy. Finally, the effectiveness of the developed model is demonstrated through comprehensive verification, encompassing existing biaxial tension and open-hole-tension tests conducted on carbon and glass FRP laminates. The simulation results exhibit a remarkable correspondence with the experimental data, validating the reliability and accuracy of the proposed model. [ABSTRACT FROM AUTHOR]

Imagery from Unmanned Aerial Vehicles can be used to generate three-dimensional (3D) point cloud models. However, final data quality is impacted by the flight altitude, camera angle, overlap rate, and data processing strategies. Typically, both overview images and redundant close-range images are collected, which significantly increases the data collection and processing time. To investigate the relationship between input resources and output quality, a suite of seven metrics is proposed including total points, average point density, uniformity, yield rate, coverage, geometry accuracy, and time efficiency. When applied in the field to a full-scale structure, the UAV altitude and camera angle most strongly affected data density and uniformity. A 66% overlapping was needed for successful 3D reconstruction. Conducting multiple flight paths improved local geometric accuracy better than increasing the overlapping rate. The highest coverage was achieved at 77% due to the formation of semi-irregular gridded gaps between point groups as an artefact of the Structure from Motion process. No single set of flight parameters was optimal for every data collection goal. Hence, understanding flight path parameter impacts is crucial to optimal UAV data collection. [ABSTRACT FROM AUTHOR]

Sepsis remains a major challenge owing to its severe adverse effects and high mortality, against which specific pharmacological interventions with high efficacy are limited. Mitigation of hyperactive inflammatory responses is a key factor in enhancing the likelihood of survival in patients with sepsis. The Aloe genus has several health benefits, including anti-inflammatory properties. The toxicological implications of aloe-emodin (AE), extracted from various Aloe species, remain uncertain in clinical contexts. However, AE has been shown to inhibit inflammatory responses in lipopolysaccharide-induced mice, indicating its potential as a therapeutic approach for sepsis treatment. Nonetheless, there is a paucity of data regarding the therapeutic benefits of AE in the widely recognized cecal ligation and puncture (CLP)-induced sepsis model, which is commonly used as the gold standard model for sepsis research. This study demonstrates the potential benefits of AE in the treatment of CLP-induced sepsis and investigates its underlying mechanism, along with the efficacy of postoperative AE treatment in mice with CLP-induced sepsis. The results of this study suggest that AE can mitigate sepsis in mice by diminishing systemic inflammation and regulating the gut microbiota. The study provides novel insights into the molecular mechanisms underlying the anti-inflammatory effects of AE. [ABSTRACT FROM AUTHOR]

Due to the stratum corneum barrier, resveratrol is difficult to be absorbed transdermally, limiting its anti-aging and skin-brightening effects. Furthermore, there is a lack of systematic studies on the efficacy of resveratrol in human skin, especially in three-dimensional skin models and clinical trials. To overcome the low transdermal delivery issue, we encapsulated resveratrol into nanoliposomes using the high-pressure homogenization method to develop an efficient transdermal drug delivery system, and systematically evaluated its anti-aging and skin-brightening efficacy via cell line models, a three-dimensional skin model and human skin. The resveratrol nanoliposomes effectively improved the transdermal penetration and retention of resveratrol and enhanced cellular uptake. In addition, compared to free resveratrol, resveratrol nanoliposomes remarkably enhanced the skin-care effects by promoting the antioxidant capacity and collagen synthesis, inhibiting the secretion of matrix metalloproteinases, tyrosine activity and melanin synthesis. Notably, human clinical trials proved the anti-wrinkle and skin-brightening effectiveness of resveratrol nanoliposomes. Three levels of systematic studies indicated that resveratrol nanoliposomes could be a promising transdermal drug delivery system to enhance the anti-aging and skin-brightening effects of resveratrol. [ABSTRACT FROM AUTHOR]

Cold damage is one of the most important environmental factors influencing crop growth, development, and production. In this study, we generated a pair of near-isogenic lines (NILs), Towada and ZL31, and Towada showed more cold sensitivity than ZL31 in the rice seedling stage. To explore the transcriptional regulation mechanism and the reason for phenotypic divergence of the two lines in response to cold stress, an in-depth comparative transcriptome study under cold stress was carried out. Our analysis uncovered that rapid and high-amplitude transcriptional reprogramming occurred in the early stage of cold treatment. GO enrichment and KEGG pathway analysis indicated that genes of the response to stress, environmental adaptation, signal transduction, metabolism, photosynthesis, and the MAPK signaling pathway might form the main part of the engine for transcriptional reprogramming in response to cold stress. Furthermore, we identified four core genes, OsWRKY24, OsCAT2, OsJAZ9, and OsRR6, that were potential candidates affecting the cold sensitivity of Towada and ZL31. Genome re-sequencing analysis between the two lines revealed that only OsWRKY24 contained sequence variations which may change its transcript abundance. Our study not only provides novel insights into the cold-related transcriptional reprogramming process, but also highlights the potential candidates involved in cold stress. [ABSTRACT FROM AUTHOR]

The NAC (NAM, ATAF1/2 and CUC2) is a large gene family of plant-specific transcription factors that play a pivotal role in various physiological processes and abiotic stresses. Due to the lack of genome-wide characterization, intraspecific and interspecific synteny, and drought-responsive expression pattern of NAC genes in poplar, the functional characterization of drought-related NAC genes have been scarcely reported in Populus species. Here, we identified a total of 170 NAC domain-containing genes in the P. trichocarpa genome, 169 of which were unevenly distributed on its nineteen chromosomes. These NAC genes were phylogenetically divided into twenty subgroups, some of which exhibited a similar pattern of exon–intron architecture. The synteny and Ka/Ks analysis indicated that the expansion of NAC genes in poplar was mainly due to gene duplication events occurring before and after the divergence of Populus and Salix. Ten PdNAC (P. deltoids × P. euramericana cv.'Nanlin895') genes were randomly selected and cloned. Their drought-responsive expression profiles showed a tissue-specific pattern. The transcription factor PdNAC013 was verified to be localized in the nucleus. Our research results provide genomic information for the expansion of NAC genes in the poplar genome, and for further characterizing putative poplar NAC genes associated with water-deficit. [ABSTRACT FROM AUTHOR]

Proppant is an essential material in hydraulic fracturing, and it can support artificial fractures for a long time. However, few people have applied proppant and conductive materials in the in-situ modification of shale oil. Here, we developed a graphene and resin coated (GRC) proppant with electrically conductive properties. The electrical conductivity of the GRC proppant improved by four orders of magnitude. The GRC proppant has a 54.58% improvement in suspension and 22.75% increase in settlement time at 0.25 wt% concentration compared with uncoated proppant. The GRC proppant's adhesion reached 68.34 nN under 1 μN load force, increasing by 63.13% compared to uncoated proppant. This new electrically conductive proppant can be used as a conductive carrier to improve the efficiency of electric heating in in-situ modification technology of shale oil. [ABSTRACT FROM AUTHOR]

For robot swarm applications, accurate positioning is one of the most important requirements for avoiding collisions and keeping formations and cooperation between individuals. However, in some worst cases, the GNSS (Global Navigation Satellite System) signals are weak due to the crowd being in a swarm or blocked by a forest, mountains, and high buildings in the environment. Thus, relative localization is an indispensable way to provide position information for the swarm. In this paper, we review the status and development of relative localization. It is first assessed that relative localization to obtain spatio-temporal relationships between individuals is necessary to achieve the stable operation of the group. After analyzing typical relative localization systems and algorithms from the perspective of functionality and practicality, this paper concludes that the UWB-based (ultra wideband) system is suitable for the relative localization of robots in large-scale applications. Finally, after analyzing the current challenges in the field of fully distributed localization for robotic swarms, a complete mechanism encompassing the relative localization process and the relationship between local and global localization that can be a possible direction for future research is proposed. [ABSTRACT FROM AUTHOR]

The elucidation of the molecular driving forces responsible for Liquid–liquid Phase Separation (LLPS) of proteins and nucleic acids within living cells is crucial for understanding its biological functions and its role in related diseases. In the present study, we investigated the regulation of LLPS in a series of polypeptides with repetitive proline and arginine (PR) sequences by modifying their length and the salt concentration in the solution. Our findings indicate that higher salt concentrations are necessary for LLPS of repetitive PR peptides longer than eight PRs, which emerges as a threshold value. To pinpoint the molecular forces driving the LLPS in peptides, we sequentially introduced various concentrations of hydrophobic disruptors, such as 1,6-hexanediol, and electrostatic regulators, such as ethyl alcohol and 6-Aminocaproic acid. We further modulated the electrostatic interaction by introducing ethyl alcohol and 6-Aminocaproic acid to alter the dielectric constant of the solution. The inclusion of ethyl alcohol intensified the electrostatic interaction between arginine molecules, facilitating LLPS of PR15, while 6-Aminocaproic acid yielded the reverse effect. We deduced that the phase separation in peptide systems is conjointly driven by hydrophobicity and electrostatic interactions. These insights can guide the regulation of LLPS in other peptide and protein systems, and could be pivotal in addressing abnormal aggregations of proteins and nucleic acids. [ABSTRACT FROM AUTHOR]

Accurate estimation of gross primary productivity (GPP) is necessary to better understand the interaction of global terrestrial ecosystems with climate change and human activities. Light use efficiency (LUE)-based GPP models are widely used for retrieving several GPP products with various temporal and spatial resolutions. However, most LUE-based models assume a clear-sky condition, and the influence of diffuse radiation on GPP estimations has not been well considered. In this paper, a diffuse and direct (DDA) absorbed photosynthetically active radiation (APAR)-based method is proposed for better estimation of half-hourly GPP, which partitions APAR under diffuse and direct radiation conditions. Firstly, energy balance residual (EBR) FAPAR, moderate resolution imaging spectroradiometer (MODIS) leaf area index (LAI) (MCD15A2H) and clumping index (CI) products, as well as solar radiation records supplied by FLUXNET2015 were used to calculate diffuse and direct APAR at a half-hourly scale. Then, an eddy covariance-LUE (EC-LUE) model and meteorological observations from FLUXNET2015 data sets were used for obtaining corresponding LUE values. A co-variation relationship between LUE and diffuse fraction was observed, and the LUE was higher under more diffuse radiation conditions. Finally, the DDA-based method was tested using the half-hourly FLUXNET GPP and compared with half-hourly GPP calculated using total APAR (GPP_TA). The results indicated that the half-hourly GPP estimated using the DDA-based method (GPP_DDA) was more accurate, giving higher R2 values, lower RMSE and RMSE* values (R2 varied from 0.565 to 0.682, RMSE ranged from 3.219 to 12.405 and RMSE* were within the range of 2.785 to 8.395) than the GPP_TA (R2 varied from 0.558 to 0.653, RMSE ranged from 3.407 to 13.081 and RMSE* were within the range of 3.321 to 9.625) across FLUXNET sites within different vegetation types. This study explored the effects of partitioning the diffuse and direct APAR on half-hourly GPP estimations, which demonstrates a higher agreement with FLUXNET GPP than total APAR-based GPP. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a multifaceted, chronic, progressive autoimmune disease. This study aims to explore the potential benefits of an enhanced drug delivery system utilizing optimized Gelatin Methacryloyl (GelMA) vectors in RA management. We evaluated the levels of miR-1124-3p and AGO1 in RA tissues and cell lines using qPCR, WB, and immunofluorescence. The effects of osthole on inflammatory response and joint morphology were determined by qPCR, H&E staining, and micro-CT. The data showed that miR-1224-3p was downregulated in RA tissues and HUM-iCell-s010RA cells, while the overexpression of miR-1224-3p in HUM-iCell-s010RA cells reduced the expression of IL-6 and IL-1β. Luciferase assay demonstrated that AGO1 was a direct target gene of miR-1224-3p. Additionally, osthole treatment increased miR-1224-3p levels and decreased AGO1 expression. The release data showed that osthole loaded on GelMA was released at a slower rate than free osthole. Further studies in a mouse model of CIA confirmed that osthole-loaded GelMA was more effective in attenuating osteopenia in RA as well as alleviating autoimmune arthritis. These findings suggest that osthole can regulate the miR-1224-3p/AGO1 axis in RASFs cells and has the potential to be developed as a clinical anti-RA drug. GelMA could provide a new approach to long-term RA treatment. [ABSTRACT FROM AUTHOR]

Sensitive skin is defined as skin with low tolerance and high reactivity. Natural products, such as paeoniflorin and madecassoside, have unique skin care functionality. However, because they are hampered by the skin barrier, paeoniflorin and madecassoside have difficulty penetrating the stratum corneum, resulting in weakened skin barrier repair and anti-inflammatory effects. In addition, there is a lack of detailed studies on the efficacy of paeonol and madecassic in human skin, especially in 3D skin models and clinical trials. To overcome the low transdermal delivery issue, we developed nanoemulsions (PM-NEs) loaded with paeonol and madecassoside to improve their delivery efficiency and promote sensitive skin repair and anti-inflammation effects. Furthermore, systematic evaluations of the efficacy in cell line models, 3D skin models, and clinical trials were conducted. The PM-NEs effectively improved the efficacy of paeonol and madecassoside glucoside transdermal penetration and retention and enhanced cellular uptake. Cellular assays and 3D epidermal models showed that the PM-NEs significantly promoted the secretion of filamentous protein, aquaporin 3, Claudin-1, and hyaluronic acid, and considerably inhibited the secretion of interleukin 1α, interleukin 6, tumor necrosis factor-α, and prostaglandin E2 compared to free components. Notably, clinical trial data showed that the PM-NEs significantly reduced transepidermal water loss, a* values, erythropoietin, the amount of non-inflammatory acne, and the amount of inflammatory acne in the facial skin. Three levels of systematic studies suggest that co-delivery of paeoniflorin and madecassoside via nanoemulsions is a promising strategy to improve topical delivery efficiency and anti-inflammatory repair efficacy in sensitive skin. [ABSTRACT FROM AUTHOR]

We propose explicit K-symplectic and explicit symplectic-like methods for the charged particle system in a general strong magnetic field. The K-symplectic methods are also symmetric. The charged particle system can be expressed both in a canonical and a non-canonical Hamiltonian system. If the three components of the magnetic field can be integrated in closed forms, we construct explicit K-symplectic methods for the non-canonical charged particle system; otherwise, explicit symplectic-like methods can be constructed for the canonical charged particle system. The symplectic-like methods are constructed by extending the original phase space and obtaining the augmented separable Hamiltonian, and then by using the splitting method and the midpoint permutation. The numerical experiments have shown that compared with the higher order implicit Runge-Kutta method, the explicit K-symplectic and explicit symplectic-like methods have obvious advantages in long-term energy conservation and higher computational efficiency. It is also shown that the influence of the parameter ε in the general strong magnetic field on the Runge-Kutta method is bigger than the two kinds of symplectic methods. [ABSTRACT FROM AUTHOR]

In this study, we conducted two surveys in the central and southern parts of the South China Sea, in autumn 2012 and spring 2013. Six juvenile tuna species were caught in each survey. Gradient forest analysis (GFA) and a generalized additive model (GAM) were used to analyze the relationship between the catch per unit effort (CPUE) for the juvenile tuna species and six sea temperature indices for the South China Sea. In the GFA, the temperature difference between the sea surface and 50 m depth (D50) showed the highest importance to CPUE than other indices, which indicates that D50 was the best predictor of the abundance of juvenile tuna species. The GAM analysis showed that lower deep-water temperature, a shallow mixed layer depth, and a higher difference in temperature between the surface and deeper water were associated with increased CPUE. The results indicate that a relatively rapid decrease in vertical water temperature is favorable for the aggregation of juvenile tuna. These results contribute to understanding of the distribution mechanism of juvenile tuna species in the South China Sea and provide a scientific basis for the rational development and utilization of tuna resources. [ABSTRACT FROM AUTHOR]

Leaf chlorophyll content (LCC) is a prominent plant physiological trait and a proxy for leaf photosynthetic capacity. The acquisition of LCC data over large spatial and temporal scales facilitates vegetation growth monitoring and terrestrial carbon cycle modeling. In this study, a global 500 m LCC weekly dataset (GLCC) was produced from ENVISAT MERIS and Sentinel-3 OLCI satellite data using a physical radiative transfer modeling approach that considers the influence of canopy structure and soil background. Firstly, five look-up-tables (LUTs) were generated using PROSPECT-D+4-Scale and PROSAIL-D models for woody and non-woody plants. For the four LUTs applicable to woody plants, each LUT contains three sub-LUTs corresponding to three types of crown height. The one LUT applicable to non-woody vegetation type includes 25 sub-LUTs corresponding to five kinds of canopy structures and five kinds of soil backgrounds. The final retrieval was considered the aggregation of the LCC inversion results of all sub-LUTs for each plant function type (PFT). Then, the GLCC dataset was generated and validated using field measurements, yielding an overall accuracy of R2 = 0.41 and RMSE = 8.94 μg cm−2. Finally, the GLCC dataset presented acceptable consistency with the existing MERIS LCC dataset. OLCI, as the successor to MERIS data, was used for the first time to co-produce LCC data from 2003–2012 to 2018–2020 in conjunction with MERIS data. This new GLCC dataset spanning nearly 20 years will provide a valuable opportunity to analyze variations in vegetation dynamics. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNNs) are widely used for hyperspectral image (HSI) classification due to their better ability to model the local details of HSI. However, CNNs tends to ignore the global information of HSI, and thus lack the ability to establish remote dependencies, which leads to computational cost consumption and remains challenging. To address this problem, we propose an end-to-end Inception Transformer network (IFormer) that can efficiently generate rich feature maps from HSI data and extract high- and low-frequency information from the feature maps. First, spectral features are extracted using batch normalization (BN) and 1D-CNN, while the Ghost Module generates more feature maps via low-cost operations to fully exploit the intrinsic information in HSI features, thus improving the computational speed. Second, the feature maps are transferred to Inception Transformer through a channel splitting mechanism, which effectively learns the combined features of high- and low-frequency information in the feature maps and allows for the flexible modeling of discriminative information scattered in different frequency ranges. Finally, the HSI features are classified via pooling and linear layers. The IFormer algorithm is compared with other mainstream algorithms in experiments on four publicly available hyperspectral datasets, and the results demonstrate that the proposed method algorithm is significantly competitive among the HSI classification algorithms. [ABSTRACT FROM AUTHOR]

The estimation of non-stationary random medium parameters of petrophysical parameters is the key to the application of random medium theory in fine seismic exploration. We proposed a method for estimating non-stationary random medium parameters of petrophysical parameters using seismic data. Based on the linear petrophysical model, the relationship between seismic data and porosity, clay volume, and water saturation in the random medium was described, and the principle and method of estimating the autocorrelation parameters of the petrophysical parameter random medium were introduced in this study. Subsequently, the specific steps of applying the power spectrum method, for parameter estimation in non-stationary random media with petrophysical parameters, were explained. The feasibility and correctness of the method were verified through the estimation test of the two-dimensional theoretical model. Eventually, the estimation test of non-stationary random medium parameters of petrophysical parameters was carried out by field seismic data, and the results indicated that the non-stationary random medium parameters can better portray the information of subsurface medium petrophysical parameters. The method can provide a reference for the construction of a priori information on petrophysical parameters, and it can also provide a theoretical basis for the in-depth application of random medium theory to practical data. [ABSTRACT FROM AUTHOR]

The classification accuracy of ground objects is improved due to the combined use of the same scene data collected by different sensors. We propose to fuse the spatial planar distribution and spectral information of the hyperspectral images (HSIs) with the spatial 3D information of the objects captured by light detection and ranging (LiDAR). In this paper, we use the optimized spatial gradient transfer method for data fusion, which can effectively solve the strong heterogeneity of heterogeneous data fusion. The entropy rate superpixel segmentation algorithm over-segments HSI and LiDAR to extract local spatial and elevation information, and a Gaussian density-based regularization strategy normalizes the local spatial and elevation information. Then, the spatial gradient transfer model and l 1 -total variation minimization are introduced to realize the fusion of local multi-attribute features of different sources, and fully exploit the complementary information of different features for the description of ground objects. Finally, the fused local spatial features are reconstructed into a guided image, and the guided filtering acts on each dimension of the original HSI, so that the output maintains the complete spectral information and detailed changes of the spatial fusion features. It is worth mentioning that we have carried out two versions of expansion on the basis of the proposed method to improve the joint utilization of multi-source data. Experimental results on two real datasets indicated that the fused features of the proposed method have a better effect on ground object classification than the mainstream stacking or cascade fusion methods. [ABSTRACT FROM AUTHOR]