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Abstract Background Assessing the relationships between spatial and temporal structures and functions of plant communities is an effective way to understand the changing dynamics of plant communities in specific environments. In this study, we investigated the response of structural and functional stabilities of plant communities to stocking rate in the desert steppe over a 16-year grazing period as the research background. Methods We used classical statistical methods to investigate the quantitative characteristics of plant communities over time (2014–2019) and space (2017–2019) at four stocking rates (control, CK, 0 sheep·ha–1·month–1; light grazing, LG, 0.15 sheep·ha–1·month–1; moderate grazing, MG, 0.30 sheep·ha–1·month–1; heavy grazing, HG, 0.45 sheep·ha–1·month–1) in the Stipa breviflora desert steppe of Inner Mongolia. We then examined the relationship between structural and functional stability of plant communities. Results On the spatial scale, the structural stability of plant community was the highest in the LG treatment and the lowest in the MG treatment. The functional stability of plant community was the highest in the MG treatment and the lowest in the HG treatment. On the temporal scale, the structural stability of plant community was the highest in the MG treatment and the lowest in the LG treatment. The functional stability of plant community was the highest in the LG treatment and the lowest in the HG treatment. Affected by the stocking rate, the structural stability of plant community fluctuated more widely on the spatial scale and its functional stability varied more widely on the temporal scale. Nonetheless, the functional stability of the plant community is more responsive to the stocking rate. Conclusions Our findings suggest that influenced by the disturbance of stocking rate, the structural stability of plant community is more significant than the functional stability in the desert grassland ecosystem, which lays a solid foundation for the study of ecosystem stability.

Abstract Fungi are very common infectious pathogens, which may cause invasive and potentially life-threatening infections. However, the efficacy of antifungal medications remains limited. Herein, a Cu2+-phenolic nanoflower is designed to combat fungal infections by combining cuproptosis and cell wall digestion. Firstly, protocatechuic acid (PA)-Cu2+ (PC) nanopetals are prepared by coordination interaction. Lywallzyme (Lyw) is then added to induce the self-assembly of PC to form Lyw loaded PC (PCW) nanoflowers. PCW nanoflowers can effectively adhere to fungal surface and Lyw can digest fungal cell walls to facilitate Cu2+ to penetrate into fungal interior, thereby exerting a synergistic fungicidal effect. PCW nanoflowers exhibit excellent fungicidal activity even in protein-rich and high-salt conditions, where dissociative Cu2+ completely loses fungicidal activity. Transcriptome sequencing analysis reveals that PCW can lead to fungal cuproptosis. The in vivo fungicidal effect of PCW nanoflowers is confirmed on a murine skin fungal infection model and a murine fungal keratitis model.

Root system architecture plays an essential role in water and nutrient acquisition in plants, and it is significantly involved in plant adaptations to various environmental stresses. In this study, a panel of 242 cotton accessions was collected to investigate six root morphological traits at the seedling stage, including main root length (MRL), root fresh weight (RFW), total root length (TRL), root surface area (RSA), root volume (RV), and root average diameter (AvgD). The correlation analysis of the six root morphological traits revealed strong positive correlations of TRL with RSA, as well as RV with RSA and AvgD, whereas a significant negative correlation was found between TRL and AvgD. Subsequently, a genome-wide association study (GWAS) was performed using the root phenotypic and genotypic data reported previously for the 242 accessions using 56,010 single nucleotide polymorphisms (SNPs) from the CottonSNP80K array. A total of 41 quantitative trait loci (QTLs) were identified, including nine for MRL, six for RFW, nine for TRL, 12 for RSA, 12 for RV and two for AvgD. Among them, eight QTLs were repeatedly detected in two or more traits. Integrating these results with a transcriptome analysis, we identified 17 candidate genes with high transcript values of transcripts per million (TPM)≥30 in the roots. Furthermore, we functionally verified the candidate gene GH_D05G2106, which encodes a WPP domain protein 2 in root development. A virus-induced gene silencing (VIGS) assay showed that knocking down GH_D05G2106 significantly inhibited root development in cotton, indicating its positive role in root system architecture formation. Collectively, these results provide a theoretical basis and candidate genes for future studies on cotton root developmental biology and root-related cotton breeding.

Abstract Characterizing the nature of hydrodynamical transport properties in quantum dynamics provides valuable insights into the fundamental understanding of exotic non-equilibrium phases of matter. Experimentally simulating infinite-temperature transport on large-scale complex quantum systems is of considerable interest. Here, using a controllable and coherent superconducting quantum simulator, we experimentally realize the analog quantum circuit, which can efficiently prepare the Haar-random states, and probe spin transport at infinite temperature. We observe diffusive spin transport during the unitary evolution of the ladder-type quantum simulator with ergodic dynamics. Moreover, we explore the transport properties of the systems subjected to strong disorder or a tilted potential, revealing signatures of anomalous subdiffusion in accompany with the breakdown of thermalization. Our work demonstrates a scalable method of probing infinite-temperature spin transport on analog quantum simulators, which paves the way to study other intriguing out-of-equilibrium phenomena from the perspective of transport.

Abstract Metal–organic frameworks (MOFs) present diverse building blocks for high‐performance materials across industries, yet their crystallization mechanisms remain incompletely understood due to gaps in nucleation and growth knowledge. In this study, MOF structural evolution is probed using in situ liquid phase transmission electron microscopy (TEM) and cryo‐TEM, unveiling a blend of classical and nonclassical pathways involving liquid–liquid phase separation, particle attachment–coalescence, and surface layer deposition. Additionally, ultrafast high‐temperature sintering (UHS) is employed to dope ultrasmall Cobalt nanoparticles (Co NPs) uniformly within nitrogen‐doped hard carbon nanocages confirmed by 3D electron tomography. Lithium–sulfur battery tests demonstrate the nanocage‐Co NP structure's exceptional capacity and cycling stability, attributed to Co NP catalytic effects due to its small size, uniform dispersion, and nanocage confinement. The findings propose a holistic framework for MOF crystallization understanding and Co NP tunability through ultrafast sintering, promising advancements in materials science and informing future MOF synthesis strategies and applications.

Mitochondrial calcium uniporter (MCU) is a conserved calcium ion (Ca2+) transporter in the mitochondrial inner membrane of eukaryotic cells. How MCU proteins regulate Ca2+ flow and modulate plant cell development remain largely unclear. Here, we identified the gene GhMCU4 encoding a MCU protein that negatively regulates plant development and fiber elongation in cotton (Gossypium hirsutum). GhMCU4 expressed constitutively in various tissues with the higher transcripts in elongating fiber cells. Knockdown of GhMCU4 in cotton significantly elevated the plant height and root length. The calcium signaling pathway was significantly activated and calcium sensor genes, including Ca2+ dependent modulator of interactor of constitutively active ROP (GhCMI1), calmodulin like protein (GhCML46), calcium-dependent protein kinases (GhCPKs), calcineurin B-like protein (GhCBLs), and CBL-interacting protein kinases (GhCIPKs), were dramatically upregulated in GhMCU4-silenced plants. Metabolic processes were preferentially enriched, and genes related to regulation of transcription were upregulated in GhMCU4-silenced plants. The contents of Ca2+ and H2O2 were significantly increased in roots and leaves of GhMCU4-silenced plants. Fiber length and Ca2+ and H2O2 contents in fibers were significantly increased in GhMCU4-silenced plants. This study indicated that GhMCU4 plays a negative role in regulating cell elongation in cotton, thus expanding understanding in the role of MCU proteins in plant growth and development.

Highlights Si/C Composite and Nanostructure Engineering: Advanced Si/C composites and multidimensional nanostructures address key challenges in silicon anodes, like volume expansion and unstable SEI, enhancing LIBs performance. Artificial SEI, Prelithiation, and Binders: Focus on stable artificial SEI layers, efficient prelithiation, and cutting-edge binders to improve Coulombic efficiency and reduce capacity loss, enhancing Si anode durability and efficiency. Real-World Application and Scalability: Analysis of these strategies highlights scalability and commercial viability, transitioning Si-anode technologies to practical, high-performance LIBs applications.

ObjectiveThis study aims to investigate the activation of frontotemporal functional brain areas in patients with Obsessive-Compulsive Disorder (OCD) during a Verbal Fluency Task (VFT), and to compare their brain functional connectivity in a resting state with that of healthy controls. The goal is to deepen our understanding of the neuropathological mechanisms underlying OCD.Methods32 patients with OCD and 32 controls matched for age, gender, handedness, and years of education participated in this study, they were divided into OCD group and healthy comtrol group. We conducted VFT task tests and 10-minute resting state tests on both groups by using functional Near-Infrared Spectroscopy (fNIRS). The VFT was utilized to assess the activation (beta values) and the integral and centroid values of the frontal and bilateral temporal lobes, including brain areas BA9 and 46 (dorsolateral prefrontal cortex), BA10 (frontal pole), BA45 (inferior frontal gyrus), BA21 (middle temporal gyrus), and BA22 (superior temporal gyrus). We evaluated the functional connectivity levels of these areas during the resting state. Differences in these measures between OCD patients and healthy controls were analyzed using two-sample independent t-tests and non-parametric Mann-Whitney U tests.ResultsDuring VFT, OCD had smaller integral values(z=5.371, p

Aiming at the initial alignment problem of low-cost INS/GNSS in the case of moving base, this paper proposes a set of GNSS-assisted low-cost INS combined navigation initial alignment schemes, which is designed, optimized, and verified. Firstly, this paper analyses the impact of accelerometer zero bias on the accuracy of multi-vector construction and proposes an improved vector construction method, which approximates the suppression of the error caused by the accelerometer zero bias accumulating over time by vector subtraction instead of sliding window integration and also overcomes the impact of the OBA algorithm’s computational increase and memory occupation caused by the fact that the sliding window integration needs to store and integrate the data in the window. Secondly, this paper also designs an improved Kalman filter model to reconstruct the state equation and measurement equation of the system, which can more accurately estimate the zero bias of the gyroscope online and compensate for the misalignment angle of the carrier system by using the velocity and position information of the GNSS, eliminating the influence of the zero bias of the gyroscope on the accuracy of the multi-vector, and improving the accuracy of the initial alignment of the moving base and the robustness of the algorithm. Finally, the algorithm proposed in this paper and other algorithms are compared and analyzed in simulation and vehicle test experiments. The simulation experiments verify the feasibility of the initial alignment method proposed in this paper; the vehicle test experiments use vector subtraction and sliding window integration to construct the multivector, and then estimate the zero bias of the gyroscope and compensate for the misalignment angle of the carrier system by using Kalman filtering model proposed in this paper and other Kalman filtering models, respectively. The measured results show that the proposed method has better alignment accuracy and algorithm robustness than the existing Optimization-based alignment and their improvement algorithms for the moving base of low-cost INS/GNSS combined navigation.

Abstract Snapdragon (Antirrhinum majus L.) is a widely cultivated and economically important cut flower and bedding plant worldwide due to its high ornamental value. At the same time, owing to its herbaceous features, ease of growth and cultivation, short life cycle, diploid inheritance, diverse morphological variation, and self-incompatibility, it has also been used as a model plant for studies on molecular biology, biochemistry, and plant developmental genetics. Over the past few decades, hundreds of plant genetics and physiology studies have been published on snapdragon. This review aims to summarize the advances in the characterization of snapdragon ornamental characters associated with floral organ size, shape, scent, color, and plant appearance. A broad spectrum of genes and their action mechanisms were explored and discussed, including comprehensive investigations at the genome-wide level and unraveling the functions of structural genes and master regulators and their interactions. In addition, the biosynthetic pathway involved in floral volatile scent production was summarized. Finally, the TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTORS (TCP) family in snapdragon was investigated using the latest whole-genome data. This review will lay the foundation for future molecular genetics and genomics research and applications on snapdragon. It further contributes to improve our knowledge of the mechanisms regulating morphogenesis and ornamental qualities in snapdragon.

The cathode in lithium-selenium (Li-Se) batteries has garnered extensive attention owing to its superior specific capacity and enhanced conductivity compared to sulfur. Nonetheless, the adoption and advancement of Li-Se batteries face significant challenges due to selenium’s low reactivity, substantial volume fluctuations, and the shuttle effect associated with polyselenides. Single-atom catalysts (SACs) are under the spotlight for their outstanding catalytic efficiency and optimal atomic utilization. To address the challenges of selenium’s low chemical activity and volume expansion in Li-Se batteries, through electrospun, we have developed a lotus root-inspired carbon nanofiber (CNF) material, featured internal multi-channels and anchored with molybdenum (Mo) single atoms (Mo@CNFs). Mo single atoms significantly enhance the conversion kinetics of selenium (Se), facilitating rapid formation of Li2Se. The internally structured multi-channel CNF serves as an effective host matrix for Se, mitigating its volume expansion during the electrochemical process. The resulting cathode, Se/Mo@CNF composite, exhibits a high discharge specific capacity, superior rate performance, and impressive cycle stability in Li-Se batteries. After 500 cycles at a current density of 1 C, it maintains a capacity retention rate of 82% and nearly 100% coulombic efficiency (CE). This research offers a new avenue for the application of single-atom materials in enhancing advanced Li-Se battery performance.

Abstract Non‐effectively grounded power distribution systems (NGDS) are widely used in China and other countries. However, over a long time, single‐phase‐to‐ground faults (SGF) have been misjudged or omitted by the monitoring system, threatening the security of the power supply system and human safety. Based on the reason analysis for the omitted and misjudged SGFs in NGDS, the concept of NGDS fault eigenparameters to correctly reflect fault characteristics and a method of SGF detection based on fault eigenparameters are proposed. Then, the detection mechanism of phase voltage and fault current resistive elements for SGF is revealed. The variation characteristics of typical fault parameters changing with distribution system scale (parameter) and fault transition resistance, such as residual voltage and Zero‐sequence current (iA‐iO), are analysed. The eigenparameters of SGF in certain NGDS with specific scales/parameters are also proposed, which can correctly reflect the fault characteristics under different transition resistances.

Abstract The quantum Hall effect, fundamental in modern condensed matter physics, continuously inspires new theories and predicts emergent phases of matter. Here we experimentally demonstrate three types of Chern insulators with synthetic dimensions on a programable 30-qubit-ladder superconducting processor. We directly measure the band structures of the 2D Chern insulator along synthetic dimensions with various configurations of Aubry-André-Harper chains and observe dynamical localisation of edge excitations. With these two signatures of topology, our experiments implement the bulk-edge correspondence in the synthetic 2D Chern insulator. Moreover, we simulate two different bilayer Chern insulators on the ladder-type superconducting processor. With the same and opposite periodically modulated on-site potentials for two coupled chains, we simulate topologically nontrivial edge states with zero Hall conductivity and a Chern insulator with higher Chern numbers, respectively. Our work shows the potential of using superconducting qubits for investigating different intriguing topological phases of quantum matter.

Single-phase broken faults occur frequently, affecting the reliability of distribution network. In order to effectively identify the fault type of single-phase broken fault, this paper proposes a new identification method, which is based on the combination of variational mode decomposition and stacked auto encoder with double optimization (AO-VMD-PSO-SAE). Firstly, the zero sequence voltage, which collected in line, is decomposed into a set of variational modal components. Nextly, the stack automatic encoder is used to conduct unsupervised training on the denoised data to establish a depth learning model, and the AO optimization algorithm and the PSO optimization algorithm are used to determine the super parameters in the model.​ Finally, simulation results supported and the validity of the method was verified. What the results show is that the proposed model named AO-VMD-PSO-SAE can accurately predict the types of single-phase broken fault under noise interference.

When using traditional 3D printing equipment to manufacture overhang models, it is often necessary to generate support structures to assist in the printing of parts. The post-processing operation of removing the support structures after printing is time-consuming and wastes material. In order to solve the above problems, a support-free five-degree-of-freedom additive manufacturing (SFAM) method is proposed. Through the homogeneous coordinate transformation matrix, the forward and inverse kinematics equations of the five-degree-of-freedom additive manufacturing device (FAMD) are established, and the joint variables of each axis are solved to realize the five-axis linkage of the additive manufacturing (AM) device. In this research work, initially, the layered curve is obtained through the structural lines of the overhang model, and a continuous path planning of the infill area is performed on it, and further, the part printing experiments are conducted on the FAMD. Compared with the traditional three-axis additive manufacturing (TTAM) method, the SFAM method shortens the printing time by 23.58% and saves printing materials by 33.06%. The experimental results show that the SFAM method realizes the support-free printing of overhang models, which not only improves the accuracy of the parts but also the manufacturing efficiency of the parts.

The research on additive manufacturing (AM) path planning mainly focuses on the traditional three-axis AM path planning and five-degree-of-freedom (DOF) AM path planning, while there is less research on six-DOF AM path planning. In the traditional AM path planning algorithm, the filling path is discontinuous and there is long straight-line printing in a certain direction, which can easily lead to warpage deformation. Therefore, in this work, the six-DOF manipulator is taken as the main object to build an AM platform, and the mechanism of AM path planning of the manipulator is studied. The path planning algorithm combining the contour offset filling method and Hilbert curve filling is optimized by using a cubic uniform B-spline curve, and an AM path planning algorithm suitable for a six-DOF manipulator is obtained. A continuous printing path can be generated by this algorithm. It reduces the existence of long straight-line printing in a certain direction, thereby reducing the warpage deformation of the model and improving the molding quality of the model. The traditional three-axis AM device and the six-DOF AM platform were used to print two kinds of models. By comparing the printing time, the six-DOF AM platform was 43.70% and 37.94% shorter than the traditional three-axis AM device. The same model was printed on a six-DOF AM platform by using the parallel scanning filling method, the path planning algorithm combining contour offset and Hilbert curve, and the method proposed in this paper. Through experimental verification, the average warpage deformation of the model printed by the method proposed in this paper was reduced by 37.81% and 13.79%, respectively, compared with the other two methods.

Abstract Hawking radiation is one of the quantum features of a black hole that can be understood as a quantum tunneling across the event horizon of the black hole, but it is quite difficult to directly observe the Hawking radiation of an astrophysical black hole. Here, we report a fermionic lattice-model-type realization of an analogue black hole by using a chain of 10 superconducting transmon qubits with interactions mediated by 9 transmon-type tunable couplers. The quantum walks of quasi-particle in the curved spacetime reflect the gravitational effect near the black hole, resulting in the behaviour of stimulated Hawking radiation, which is verified by the state tomography measurement of all 7 qubits outside the horizon. In addition, the dynamics of entanglement in the curved spacetime is directly measured. Our results would stimulate more interests to explore the related features of black holes using the programmable superconducting processor with tunable couplers.

The wheat kernel moisture content (KMC) plays a pivotal role in determining the quality, storage viability, and economic profitability of wheat. Monitoring wheat KMC in-field before harvest provides decision-making information to ensure harvested wheat meeting trade standards. The study aims to expand the feasibility of spectroscopy to estimate wheat KMC at multi-scales. In addition to using ground hyperspectral reflectance for single-point measurement of wheat KMC, satellite multispectral images were also utilized to monitor the field distribution of wheat KMC on large-scale. For each estimation task, we extracted sensitive spectral features and compared the accuracy of three machine learning methods including Ridge, Support Vector Regression (SVR) and Random Forest Regression (RFR). We also adopted Two-stage Tradaboost.R2 to address the issue of uneven distribution of samples corresponding to satellite imagery. Experimental results showed that, based on optimized spectral features, the R2 of RFR model outperformed other machine learning models (Ridge and SVR) for wheat KMC estimation (R2 > 0.85). Among all spectral features, the B5 band and PSRI vegetation index from PlanetScope satellite, as well as the B11, and B12 bands and VARI vegetation index from Sentinel-2, proved to be effective features for wheat KMC estimation. Moreover, the incorporation of hyperspectral reflectance and multispectral imagery can improve the estimation accuracy on large-scale through the transfer learning algorithm of Two-stage Tradaboost.R2. Leveraging its superior temporal and spatial resolution, PS imagery emerges as an ideal data source for monitoring rapid fluctuations in wheat KMC during the physiological maturity period, which enabled a multi-day wheat KMC simulation. Overall, This study contributes a reliable and convenient spectroscopy tool for wheat KMC estimation for multi-scenes, offering scientific insights to support agricultural water management and wheat quality.

Abstract We demonstrate that superconducting gatemon qubits based on superconductor-semiconductor-superconductor Josephson junctions can be constructed on hole-type Ge/Si core/shell nanowires. The frequency of the qubit can be set firstly by controlling the diffusion of Al in the nanowire via thermal annealing, which yields a suitable critical supercurrent allowing the qubit frequency to be within the experimentally accessible range, and then by fine tuning of a gate voltage, by which an accurate adjustment of the frequency can be realized. On the resulted qubit, Rabi oscillation with an energy relaxation time $${T}_{1} \sim 180\,{\rm{ns}}$$ T 1 ~ 180 ns was observed in the time domain, an average decoherence time $${T}_{2}^{* } \sim 15\,{\rm{ns}}$$ T 2 * ~ 15 ns was obtained, and the gate voltage dependence of both $${T}_{1}$$ T 1 and $${T}_{2}^{* }$$ T 2 * was investigated. Such a hole-type superconducting gatemon qubit, based on materials with strong spin-orbit coupling and potentially the absence of hyperfine interaction after isotope purification, could be used for exploring the quantum coherence phenomena of hole-gas and even Majorana physics in Ge-based quantum devices.

Previous studies of the effects of elevated CO2 (eCO2) concentrations and heavy metal stress conditions on plant growth and physiology have mostly focused on crops rather than vegetables. In this study, we investigated the effects of Cd stress on the growth and antioxidant system of pak choi (Brassica rapa L.), water spinach (Ipomoea aquatica Forssk.), cherry radish (Raphanus raphanistrum subsp. sativus (L.) Domin) and pepper (Capsicum annuum L.) growing in pots under ambient CO2 (aCO2) or eCO2 conditions. In general, Cd stress reduced plant biomass and SPAD values under aCO2 and eCO2 conditions; however, the reduction was smaller under eCO2. Cd stress significantly reduced vegetable superoxide dismutase (SOD) and catalase (CAT) activities under both aCO2 and eCO2 conditions; however, the decrease in cherry radish and pepper peroxidase and SOD activities and in pak choi SOD and CAT activities was significantly less under eCO2. The Cd content of the edible parts of pak choi, water spinach and pepper was significantly lower under eCO2 than under aCO2. Our data suggest that eCO2 concentrations could be beneficial for the growth of some vegetables and reduce the Cd content.

Abstract Quantum simulation enables study of many-body systems in non-equilibrium by mapping to a controllable quantum system, providing a powerful tool for computational intractable problems. Here, using a programmable quantum processor with a chain of 10 superconducting qubits interacted through tunable couplers, we simulate the one-dimensional generalized Aubry-André-Harper model for three different phases, i.e., extended, localized and critical phases. The properties of phase transitions and many-body dynamics are studied in the presence of quasi-periodic modulations for both off-diagonal hopping coefficients and on-site potentials of the model controlled respectively by adjusting strength of couplings and qubit frequencies. We observe the spin transport for initial single- and multi-excitation states in different phases, and characterize phase transitions by experimentally measuring dynamics of participation entropies. Our experimental results demonstrate that the recently developed tunable coupling architecture of superconducting processor extends greatly the simulation realms for a wide variety of Hamiltonians, and can be used to study various quantum and topological phenomena.

Abstract This paper presents a sound source localization (SSL) model based on residual network and channel attention mechanism. The method takes the combination of log-Mel spectrogram and generalized cross-correlation phase transform (GCC-PHAT) as the input features, and extracts the time–frequency information by using the residual structure and channel attention mechanism, thus obtaining a better localizing performance. The residual blocks are introduced to extract deeper features, which can stack more layers for high-level features and avoid gradient vanishing or exploding at the same time. The attention mechanism is taken into account for the feature extraction stage in the proposed SSL model, which can focus on the most important information on the input features. We use the signals collected by microphone array to explore the performance of the model under different features, and find the most suitable input features of the proposed method. We compare our method with other models on public dataset. Experience results show a quite substantial improvement of sound source localizing performance.

It has been predicted that entanglement phase diagrams of Haar-measure random states can show interesting phenomenology, including entanglement phase transitions. Here, the authors confirm these predictions using up to 15 qubits in a fully-connected superconducting quantum processor.

Abstract Objective The relationship between anti-SSA/RO antibodies and pregnancy has been reported previously, and we aim to visualize the rates of maternal and infant outcomes with anti-SSA/RO. Methods We systematically searched records from Pubmed, Cochrane, Embase, and Web of Science databases, pooled incidence rates of adverse outcomes of pregnancy, and 95% confidence intervals (CIs) were performed with RStudio. Results A total of 890 records comprising 1675 patients and 1920 pregnancies were searched from the electronic databases. For maternal outcomes, the pooled estimate rates were 4% for termination of pregnancy, 5% for spontaneous abortion, 26% for preterm labor, and 50% for cesarean operation. While for fetal outcomes, the pooled estimate rates were 4% for perinatal death, 3% for intrauterine growth retardation, 6% for endocardial fibroelastosis, 6% for dilated cardiomyopathy, 7% for congenital heart block, 12% for congenital heart block recurrence, 19% for cutaneous neonatal lupus erythematosus, 12% for hepatobiliary disease and 16% for hematological manifestations. A subgroup analysis of congenital heart block prevalence was performed, diagnostic method and study region were found to affect heterogeneity to some extent. Conclusion Cumulative analysis of data from real-world studies confirmed adverse pregnancy outcomes of women with anti-SSA/RO, serves as a reference and a guide for the diagnosis and subsequent treatment of these women, thereby enhancing maternal and infant health. Additional studies with real-world cohorts are required to validate these results.

Existing image processing methods usually divide image denoising and image fusion into two directions for research, and even the best current image denoising methods such as DnCNN can cause information loss during image processing, and the image fusion method mainly considers the fusion between multiple source images to complement the image information, but does not take into account the degradation of the fusion quality due to the noise in the source images. Therefore, aiming at the problem that various existing image denoising methods cannot reduce noise efficiently in complex noise situations while performing multi-source image fusion, preserving texture details, highlighting edge contour structures, and enriching image energy, a method of reconstructing remote sensing images by simplified adaptive dual-channel PCNN (Dual-PCNN) fusion in the NSCT transform domain is proposed to unify image noise reduction and image fusion under the same framework to obtain a noisy image information reconstruction method, which completes the complementary advantages between two image processing methods. Firstly, the impulse noise in the image is removed using IMFLED filtering, and then the Gaussian noise is processed by DnCNN and FFDNet respectively, and the results are imported into simplified parametric adaptive dual-channel PCNN to fuse the preprocessed images respectively. Then the DnCNN image and the preprocessed image are decomposed by NSCT to obtain each low-frequency sub-band and high-frequency sub-band. The low-frequency sub-band is stimulated with detail using the guided filter, and the high-frequency sub-band is enhanced by separating the detail layer through the guided filter to obtain the energy-detail-enhanced high-frequency sub-band. Finally, the corresponding sub-bands are fused into the simplified parametric adaptive dual-channel PCNN respectively, and the fused sub-band coefficients are reconstructed by NSCT inversion to obtain the final reconstructed remote sensing image. The experiments on grayscale images and remote sensing images show that this method achieves excellent results in both visual subjective and quantitative index evaluation, and the reconstructed images perform well in texture details, contour structure, and energy enrichment. After the information reconstruction of remote sensing images, the quality and resolution of remote sensing images are effectively improved, so that terrain information, landform features, and structural features can be extracted more accurately, which are widely used in remote sensing and geographic information fields such as landform analysis, agricultural monitoring, building inspection and environmental protection.

Abstract This paper interweaved scaffolds with poly(ether ether ketone) (PEEK) and poly(lactic acid)/Walnut shell/hydroxypatite (PLA/WS/HA) composites by using fused filament fabrication technology, although there was a huge difference in thermal property term between PLA and PEEK. In order to keep mechanical properties of PEEK scaffold and remedy the stress loss produced by pores, PLA/WS/HA composites were used to fill the pores with gradient form outside-in (0.4-0.8 mm, 0.6-1.0 mm, 0.8-1.2 mm and 1.6-2.0 mm). The thermal stability, tensile and compression properties, tensile fracture surface morphology, cytotoxicity and in vivo experiment were investigated. The results showed: the scaffolds were intact without any flashes and surface destruction, and kept a well thermal stability. Compared with the PEEK porous scaffolds, the tensile fracture stress and strain, compression yield stress and strain of interweaved scaffolds were dramatically enhanced by 24.1%, 438%, 359.1% and 921.2%, respectively, and they climbed to the climax at 8 wt% of WS. In vivo experiment showed that the degradation of PLA/WS/HA composites synchronized with the adhesion, proliferation and ingrowth of bone cells, keeping the stable biomechanical properties of interweaved scaffolds. Those experiments showed that interweaved PEEK-PLA/WS/HA scaffolds had the potential to be used as bone implant in tissue engineering.

Rheumatoid arthritis (RA) is a progressive autoimmune disease characterized by chronic synovitis and articular destruction. Pain is the earliest and most important symptom. The Janus kinase/stat signaling pathway not only participates in the physiological processes such as the growth and differentiation of normal cells, but also plays a significant role in the pathological mechanisms such as pain in RA patients. Pain in RA patients is mediated by both inflammatory and non-inflammatory factors, including central sensitization and peripheral sensitization. Cytokines can regulate the nociceptor threshold through the JAK pathway, which leads to sensitization. In this review, we provide an overview of the physiological basis of pain modulation, the underlying importance of cytokines and JAK/STAT pathway in pain modulation, and finally introduce the performance of JAK inhibitors in clinical research. Having a better understanding of the mechanism of pain in RA may provide new therapeutic ideas and directions for the clinical improvement of pain in RA patients.

The v-MYB avivan myoblastsis virus oncogene homolog (MYB) family is the largest gene family of the transcription factor in plants, involved in plant growth and development, secondary metabolism and resistance to biotic/abiotic stress. Antirrhinum majus (snapdragon) is an ideal material for studying ornamental traits. Nevertheless, there has been no systematic investigation into the AmMYB family of snapdragons. In this study, we identified a total of 162 members of the AmMYB gene family in snapdragons. Gene structure analysis showed that the AmMYB family within the same subgroup had a similar structure and motifs. Analysis of gene duplication events revealed that the amplification of the AmMYB family was driven by whole-genome duplication (WGD) and dispersed duplication. The analysis of cis-acting elements in the promoter region of AmMYB genes reveals a collaborative involvement of light-responsive growth and development elements, stress resistance elements, and hormone-responsive elements jointly participating in the regulation of the AmMYB gene. Collinearity analysis demonstrates significant functional distinctions between AmMYB and monocotyledonous plants. The classification of AmMYB members results in 3 main subgroups with 36 smaller subgroups. All AmMYB genes are distributed across all eight chromosomes, with no apparent correlation between subfamily distribution and chromosome length. Through phylogenetic analysis and RNA-seq analysis, we have identified 9 R2R3-MYB genes that potentially play a role in the regulation of floral volatile organic compounds (FVOCs) biosynthesis. Their expression patterns were verified by qRT-PCR experiments. This study establishes a robust foundation for further investigations into the functionality of AmMYB genes and their molecular mechanisms underlying FVOC biosynthesis in snapdragons.

Siamese trackers based on classification and regression have drawn extensive attention due to their appropriate balance between accuracy and efficiency. However, most of them are prone to failure in the face of abrupt motion or appearance changes. This paper proposes a Siamese-based tracker that incorporates spatial-semantic-aware attention and flexible spatiotemporal constraint. First, we develop a spatial-semantic-aware attention model, which identifies the importance of each feature region and channel to target representation through the single convolution attention network with a loss function and increases the corresponding weights in the spatial and channel dimensions to reinforce the target region and semantic information on the target feature map. Secondly, considering that the traditional method unreasonably weights the target response in abrupt motion, we design a flexible spatiotemporal constraint. This constraint adaptively adjusts the constraint weights on the response map by evaluating the tracking result. Finally, we propose a new template updating the strategy. This strategy adaptively adjusts the contribution weights of the tracking result to the new template using depth correlation assessment criteria, thereby enhancing the reliability of the template. The Siamese network used in this paper is a symmetric neural network with dual input branches sharing weights. The experimental results on five challenging datasets show that our method outperformed other advanced algorithms.

Abstract In this work, fused deposition modeling (FDM) technology was used to prepare poly(lactic acid)/walnut shell/hydroxyapatite (PLA/WS/HA) composite filaments. HA was treated with silane and characterized by Fourier transform infrared spectroscopy (FTIR). The composites were investigated by using simultaneous thermal analyzer, scanning electron microscopy (SEM) and a universal mechanical testing machine. The results showed that incorporating either HA or WS improved the thermal stability and water absorption of PLA, but lowered the tensile and compression strength. Fillers toughened the PLA matrix, resulting in higher tensile elongation and compressive strain. The tensile and compressive strengths of samples significantly dropped after water-immersion for 6 weeks. Finally, scaffolds were manufactured by using FDM. The compression modulus and structural feature of scaffolds indicated that the PLA/WS/HA composites have the potential to be applied in structural parts, such as bone implants.

BackgroundWhether serum apolipoprotein B (ApoB) is a risk factor for the development of Chronic kidney disease (CKD) has not been fully established in the general population. Therefore, our study evaluated the correlation between serum ApoB level and CKD to look for an alternative approach for CKD prevention and treatment in the general population.MethodsThere were 146,533 participants in this cross-sectional study. 3,325 participants with more than 2 measurements were enrolled in the retrospective longitudinal study with at least a 3-year follow-up. ApoB was measured by the immunoturbidimetric method in 6 centers. Our study defined CKD as an estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73 m2. The Spearman rank correlation analysis and the Random Forest algorithm were applied to rank the importance of variables determining the levels of eGFR. We used the logistic regression model to explain the correlation between serum ApoB and CKD. We used the Cox model to detect the correlation between baseline serum ApoB and the subsequent occurrence of CKD.ResultsBased on a cross-sectional study, 66.5% of the participants were males, with a median age of 49 (interquartile range [IQR] 43-55). Compared to the non-CKD group, the CKD group has higher levels of lipid profile and fasting glucose as well as the proportion of hypertension and hyperuricemia. The Spearman rank correlation analysis and the Random Forest algorithm revealed that ApoB has the highest correlation with eGFR decline among lipid profiles. The logistic regression analysis revealed that ApoB had a positive correlation with the prevalence of CKD after fully controlling confounders (odds ratio [OR], 1.07; 95% confidence interval [CI]: 1.02-1.11). Moreover, baseline ApoB level was correlated with a new-onset CKD in the longitudinal cohort after full adjustment for confounding factors (hazard ratio [HR], 1.61; 95% CI: 1.02-2.54). The correlation between ApoB level and the new-onset CKD was consistently observed in all sensitivity analyses.ConclusionSerum ApoB had the strongest correlation with CKD among all lipid variables. Moreover, high serum ApoB levels might precede the occurrence of CKD, suggesting that monitoring and reducing serum ApoB levels may provide an alternative method to prevent and treat CKD.

Abstract Background Global distributions and trends of the risk-attributable burdens of chronic obstructive pulmonary disease (COPD) have rarely been systematically explored. To guide the formulation of targeted and accurate strategies for the management of COPD, we analyzed COPD burdens attributable to known risk factors. Methods Using detailed COPD data from the Global Burden of Disease study 2019, we analyzed disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), and deaths attributable to each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. The population attributable fraction (PAF) and summary exposure value (SEV) of each risk factor are also presented. Results From 1990 to 2019, the age-standardized DALY and death rates of COPD attributable to smoking and household air pollution, occupational particles, secondhand smoke, and low temperature presented consistently declining trends in almost all socio-demographic index (SDI) regions. However, the decline in YLD was not as dramatic as that of the death rate. In contrast, the COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure showed undesirable increasing trends in the low- and low-middle-SDI regions. In addition, the age-standardized DALY and death rates attributable to each risk factor except household air pollution and low temperature were the highest in the low-middle-SDI region. In 2019, the COPD burden attributable to smoking ambient particulate matter, ozone, occupational particles, low and high temperature was obviously greater in males than in females. Meanwhile, the most important risk factors for female varied across regions (low- and low-middle-SDI regions: household air pollution; middle-SDI region: ambient particles; high-middle- and high-SDI region: smoking). Conclusions Increasing trends of COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure in the low-middle- and low-SDI regions call for an urgent need to implement specific and effective measures. Moreover, considering the gender differences in COPD burdens attributable to some risk factors such as ambient particulate matter and ozone with similar SEV, further research on biological differences between sexes in COPD and relevant policy-making of disease prevention are required.

Capripox viruses (CaPVs), including sheep pox virus (SPV), goat pox virus (GPV), and lumpy skin disease virus (LSDV), are the cause of sheep pox (SPP), goat pox (GTP), and lumpy skin disease (LSD) in cattle. These diseases are of great economic significance to farmers, as they are endemic on farms and are a major constraint to international trade in livestock and their products. Capripoxvirus (CaPV) infections produce similar symptoms in sheep and goats, and the three viruses cannot be distinguished serologically. In this study, we developed a real-time quantitative polymerase chain reaction (qPCR) method for identifying CaPV in goats, sheep, and cattle. Clinical samples were tested and verified. The developed assay was highly specific for target viruses, including GPVSPV and LSDV, which had no cross-reaction with other viruses causing similar clinical symptoms. An artificially synthesized positive control plasmid using the CaPV 32 gene inserted into the vector pMD19-T was used as a template, and the correlation coefficient of the linear regression curve (R2) was 0.9916, the estimated amplification efficiency (E) was 96.06%, and the sensitivity (limit of detection, LOD) was 3.80 copies per reaction. Using the clinical samples as a template, the limit of detection (LOD) was 4.91 × 10−5 ng per reaction (1.60 × 10−5–2.13 × 10−3 ng, 95% confidence interval (CI)), which means that this method was one of the most sensitive detection assays for CaPVs. A total of 85 clinical samples from CaPV-infected animals (goats, sheep, and cattle) and 50 clinical samples from healthy animals were used to test and compare the diagnostic results using the Synergy Brands (SYBR) Green-based PCR method recommended by the World Organization of Animal Health (WOAH). Both diagnostic sensitivity (DSe) (95.8–100%, 95% CI) and diagnostic specificity (DSp) (92.9–100%, 95% CI) results of the real-time quantitative PCR (qPCR) and SYBR Green PCR were 100%, and the kappa value (κ) was 1.0 (1-1, 95% CI). In summary, the assay established based on TaqMan probes was advantageous in high specificity, sensitivity, and general applicability and could be a competitive candidate tool for the diagnosis of CaPV in clinically suspected animals.

In neurorehabilitation, motor performances may improve if patients could accomplish the training by overcoming mechanical loads. When the load inertia is increased, it has been found to trigger linear responses in motor-related cortices. The cortical responses, however, are unclear whether they also correlate to changes in muscular patterns. Therefore, it remains difficult to justify the magnitude of load during rehabilitation because of the gap between cortical and muscular activation. Here, we test the hypothesis that increases in load inertia may alter the muscle synergies, and the change in synergy may correlate with cortical activation. Twelve healthy subjects participated in the study. Each subject lifted dumbbells (either 0, 3, or 15 pounds) from the resting position to the armpit repetitively at 1 Hz. Surface electromyographic signals were collected from 8 muscles around the shoulder and the elbow, and hemodynamic signals were collected using functional near-infrared spectroscopy from motor-related regions Brodmann Area 4 (BA4) and BA6. Results showed that, given higher inertia, the synergy vectors differed farther from the baseline. Moreover, synergy similarity on the vector decreased linearly with cortical responses in BA4 and BA6, which associated with increases in inertia. Despite studies in literature that movements with similar kinematics tend not to differ in synergy vectors, we show a different possibility that the synergy vectors may deviate from a baseline. At least 2 consequences of adding inertia have been identified: to decrease synergy similarity and to increase motor cortical activity. The dual effects potentially provide a new benchmark for therapeutic goal setting.

The objective of this study was to estimate the number of motor units in 5 muscles from healthy individuals using the MScanFit program based on compound muscle action potential (CMAP) scan recordings. The examined muscles included first dorsal interosseous (FDI), abductor pollicis brevis (APB), abductor digiti minimi (ADM), second lumbrical (SL), and abductor hallucis (AH). CMAP scans were recorded from a total of 24 healthy participants. Motor unit number estimation (MUNE) values were derived from the MScanFit program. The average MUNE was 136.1 ± 31.1 (mean ± standard deviation) for the FDI, 134.9 ± 37.4 for the APB, 127.3 ± 32.3 for the ADM, 39.6 ± 8.3 for the SL, and 143.9 ± 28.9 for the AH muscles. Findings of the study provide useful information of the MScanFit MUNE for the examined muscles of healthy subjects from a single center.

In this work, willow fiber was extracted from willow inner bark and modified with alkali solution of various concentrations, temperature and time. The morphology, surface functional group, crystal and thermal stability were investigated by using a scanning electron microscopy, a Fourier transform infrared spectroscopy, an X-ray powder diffractometer, and a simultaneous thermal analyzer, respectively. The acid (H 2 SO 4 , 2 ml/l) extraction procedure removed the hemicellulose and part of lignin from willow bark, cleared the aggregation of WB, kept the crystal structure of willow fiber, dramatically increased the crystal length of fiber (from 18.46 to 30.15 nm), and enhanced the onset degradation temperature (from 262.23℃ to 297.62℃) and chemical reactivity (DTG: from 0.57%/s to 0.84%/s). The alkali treatment further removed lignin from willow fiber, smoothed the fiber surface, increased the intensity of cellulose ( I 002 ) from 646 counts to 1292 counts, and lengthened the crystal length from 30.15 to 41.84 nm. Varying the alkali treating condition, the crystal index and thermal stability reached to the climax at 60℃ of treating temperature and 7 h treating time. The treated willow fiber may have potential applications to composite with polymer, and to be used in pharmaceutical field as additives.

We use the numerical simulation to investigate an optimized metallized barrier layer for enhancing the performance of the Bi2Te3-based thermoelectric cooler (TEC). The maximal cooling capacity of 15.627 W and 5.646 W has been obtained under perfect and rough contact TEC. For the actual rough contact TEC, the Ag layer has the best cooling performance among conventional materials such as Ag, Ni, Ti, Co and Pd. The maximal cooling capacity (Qc max) for the rough contact TEC with Ag layer is 84.5% of the perfect contact TEC, which is 2.33 times of the rough contact TEC without any barrier layers. Subsequently, the roughness slope of the TEC and the pressure applied on the TEC have been researched. The Qc max can achieve 90% of the perfect contact TEC when the slope of the roughness is higher than 0.8. Under pressure over 3000 kPa, the Qc max can reach 91% of the perfect contact TEC. For practical production of Bi2Te3-based TEC can introduce Ag as the metallized layer to reduce the contact resistance and improve the cooling performance.

Reliable and fast active reset protocols are key to the functioning of quantum computing systems. Here, the authors use parametric driving to swap an excitation from a transmon qubit to its readout resonator within 34 ns, with negligible effects on neighboring qubits.

The non/hypo-response rate of the hepatitis B vaccine among hemodialysis (HD) patients is still high, it is of great significance to explore the influencing factors and their relationships. To study the related factors and their relationships using logistic regression model and Chi-squared Automatic Interaction Detection (CHAID) decision tree model. A randomized controlled trial was conducted between February 2014 and May 2015 in China. HD patients being serologically negative for HBsAg and anti-HBs were randomly assigned to receive three intramuscular injections of the standard dose (20 µg) or high dose (60 µg) of recombinant hepatitis B vaccine at months 0, 1, and 6. Those with anti-HBs concentrations 4 times per 2 weeks) (OR = 1.918, 95%CI: 1.015–3.626) had a significant risk of non/hypo-response. While the CHAID analysis showed that gender, dose, and dialysis frequency were influencing factors of non/hypo-response, and gender is most important. The interaction between gender and dialysis frequency had the greatest effect on immunization, and followed by the interaction between dialysis frequency and vaccine dose. Taken together, gender, dose and dialysis frequency were influencing factors of hepatitis B vaccine in HD patients.

Background and aimsThe epidemiological characteristics of MAFLD and its relationship with atrial fibrillation (AF) are limited in China. Therefore, we explored the epidemiological characteristics of MAFLD from adults along with the association of MAFLD and 12-ECG diagnosed AF in a nationwide population from health check-up centers.MethodsThis observational study used cross-sectional and longitudinal studies with 2,083,984 subjects from 2009 to 2017. Age-, sex-, and regional-standardized prevalence of MAFLD was estimated. Latent class analysis (LCA) was used to identify subclusters of MAFLD. Multivariable logistic regression and mixed-effects Cox regression models were used to analyze the relationship between MAFLD and AF.ResultsThe prevalence of MAFLD increased from 22.75% to 35.58% during the study period, with higher rates in males and populations with high BMI or resided in northern regions. The MAFLD population was clustered into three classes with different metabolic features by LCA. Notably, a high proportion of MAFLD patients in all clusters had overweight and prediabetes or diabetes. The MAFLD was significantly associated with a higher risk of AF in the cross-sectional study and in the longitudinal study. In addition, the coexistence of prediabetes or diabetes had the largest impact on subsequent AF.ConclusionOur findings suggested a high prevalence of MAFLD and a high prevalence of other metabolic diseases in the MAFLD population, particularly overweight and glucose dysregulation. Moreover, MAFLD was associated with a significantly higher risk for existing and subsequent subclinical AF in the Chinese population.

Aiming at the problems of the complex shape, difficult three-dimensional (3D) digital modeling and high manufacturing quality requirements of gas turbine blades (GTB), a method of fitting the blade profile line based on a cubic uniform B-spline interpolation function was proposed. Firstly, surface modeling technology was used to complete the fitting of the blade profile of the GTB, and the 3D model of the GTB was synthesized. Secondly, the processing parameters of the additive manufacturing were set, and the GTB model was printed by fused deposition technology. Then, the rapid investment casting was completed with the printed model as a wax model to obtain the GTB casting. Finally, the blade casting was post-processed and measured, and it was found to meet the requirements of machining accuracy and surface quality.

Lattice gauge theories (LGTs) are one of the most fundamental subjects in many-body physics, and has recently attracted considerable research interests in quantum simulations. Here we experimentally investigate the emergent Z_{2} gauge invariance in a 1D superconducting circuit with 10 transmon qubits. By precisely adjusting staggered longitudinal and transverse fields to each qubit, we construct an effective Hamiltonian containing an LGT and gauge-broken terms. The corresponding matter sector can exhibit a localization, and there also exists a 3-qubit operator, of which the expectation value can retain nonzero for a long time in low-energy regimes. The above localization can be regarded as the confinement of matter fields, and the 3-body operator is the Z_{2} gauge generator. These experimental results demonstrate that, despite the absence of gauge structure in the effective Hamiltonian, Z_{2} gauge invariance can still emerge in low-energy regimes. Our work provides a method for both theoretically and experimentally studying the rich physics in quantum many-body systems with emergent gauge invariance.

Abstract Background Numerous quantitative trait loci (QTLs) and candidate genes associated with yield-related traits have been identified in cotton by genome-wide association study (GWAS) analysis. However, most of the phenotypic data were from a single or few environments, and the stable loci remained to be validated under multiple field environments. Results Here, 242 upland cotton accessions collected from different origins were continuously investigated for phenotypic data of four main yield components, including boll weight (BW) and lint percentage (LP) under 13 field environments, and boll number per plant (BN) and seed index (SI) under 11 environments. Correlation analysis revealed a positive correlation between BN and LP, BW and SI, while SI had a negative correlation with LP and BN. Genetic analysis indicated that LP had the highest heritability estimates of 94.97%, followed by 92.08% for SI, 86.09% for BW, and 72.92% for BN, indicating LP and SI were more suitable traits for genetic improvement. Based on 56,010 high-quality single nucleotide polymorphisms (SNPs) and GWAS analysis, a total of 95 non-redundant QTLs were identified, including 12 of BN, 23 of BW, 45 of LP, and 33 of SI, respectively. Of them, 10 pairs of homologous QTLs were detected between A and D sub-genomes. We also found that 15 co-located QTLs with more than two traits and 12 high-confidence QTLs were detected under more than six environments, respectively. Further, two NET genes (GH_A08G0716 and GH_A08G0783), located in a novel QTL hotspot (qtl24, qtl25 and qlt26) were predominately expressed in early fiber development stages, exhibited significant correlation with LP and SI. The GH_A07G1389 in the stable qtl19 region encoded a tetratricopeptide repeat (TPR)-like superfamily protein and was a homologous gene involved in short fiber mutant ligon lintless-y (Liy), implying important roles in cotton yield. Conclusions The present study provides a foundation for understanding the regulatory mechanisms of yield components and may enhance yield improvement through molecular breeding in cotton.

Abstract The Bloch oscillation (BO) and Wannier-Stark localization (WSL) are fundamental concepts about metal-insulator transitions in condensed matter physics. These phenomena have also been observed in semiconductor superlattices and simulated in platforms such as photonic waveguide arrays and cold atoms. Here, we report experimental investigation of BOs and WSL simulated with a 5-qubit programmable superconducting processor, of which the effective Hamiltonian is an isotropic X Y spin chain. When applying a linear potential to the system by properly tuning all individual qubits, we observe that the propagation of a single spin on the chain is suppressed. It tends to oscillate near the neighborhood of their initial positions, which demonstrates the characteristics of BOs and WSL. We verify that the WSL length is inversely correlated to the potential gradient. Benefiting from the precise single-shot simultaneous readout of all qubits in our experiments, we can also investigate the thermal transport, which requires the joint measurement of more than one qubits. The experimental results show that, as an essential characteristic for BOs and WSL, the thermal transport is also blocked under a linear potential. Our experiment would be scalable to more superconducting qubits for simulating various of out-of-equilibrium problems in quantum many-body systems.

Normalized difference vegetation index (NDVI) time series data, derived from optical images, play a crucial role for crop mapping and growth monitoring. Nevertheless, optical images frequently exhibit spatial and temporal discontinuities due to cloudy and rainy weather conditions. Existing algorithms for reconstructing NDVI time series using multi-source remote sensing data still face several challenges. In this study, we proposed a novel method, an enhanced gap-filling and Whittaker smoothing (EGF-WS), to reconstruct NDVI time series (EGF-NDVI) using Google Earth Engine. In EGF-WS, NDVI calculated from MODIS, Landsat-8, and Sentinel-2 satellites were combined to generate high-resolution and continuous NDVI time series data. The MODIS NDVI was employed as reference data to fill missing pixels in the Sentinel–Landsat NDVI (SL-NDVI) using the gap-filling method. Subsequently, the filled NDVI was smoothed using a Whittaker smoothing filter to reduce residual noise in the SL-NDVI time series. With reference to the all-round performance assessment (APA) metrics, the performance of EGF-WS was compared with the conventional gap-filling and Savitzky–Golay filter approach (GF-SG) in Fusui County of Guangxi Zhuang Autonomous Region. The experimental results have demonstrated that the EGF-WS can capture more accurate spatial details compared with GF-SG. Moreover, EGF-NDVI of Fusui County exhibited a low root mean square error (RMSE) and a high coefficient of determination (R2). In conclusion, EGF-WS holds significant promise in providing NDVI time series images with a spatial resolution of 10 m and a temporal resolution of 8 days, thereby benefiting crop mapping, land use change monitoring, and various ecosystems, among other applications.

Improving public willingness toward organ donation is an important solution to the low organ donation rate. This study aimed to explore factors impacting public willingness for organ donation in China from a multi-agent perspective and further explore the impact of these factors on high or low willingness, using a social–ecological framework. Data from a total of 11,028 (effective rate, 94.18%) participants were analysed. Generalised linear model (GLM) and quantile regression were used to explore factors associated with willingness and high/low willingness toward organ donation, respectively. The mean willingness toward organ donation was 56.9 (range, 0–100) points. GLM regression revealed that age, family health, males, lower educational levels, and agricultural hukou were negatively associated with willingness. For personality, conscientiousness was negatively associated with willingness, whereas openness was positively associated with willingness. Health literacy perceived social support, and media utilisation were positively associated with willingness. Quantile regression further indicated that educational levels of college, bachelor, master’s, and PhD, openness, health literacy, perceived social support, and media utilisation were positively associated with organ donation willingness at all percentiles. It is necessary to adopt more targeted and diversified publicity, education, and guidance for different types of individuals. Meanwhile, social support needs to be strengthened. To enhance the willingness of the residents to donate organs, media publicity should be strengthened, particularly by using modern ways to improve their health literacy.

The frequent fast closing action of the governing valve in a 1000 MW ultra-supercritical unit occurred during the cold running process, which caused the valve body to sway greatly and could not continue to speed up. The problem had not been solved by governing the impulse parameters, checking the solenoid valve oil circuit, retesting the control oil quality and other measures. Therefore, starting from the speed control logic, the conditions of fast closing action and the change of proportional integral (PI) regulating quantity were analyzed. It was concluded that the main factor affecting the total flow instruction (the final valve position opening) in the process of fast closing is the feedforward change of speed regulation, not the change of PI output. Based on this analysis, the boundary value of feedforward quantity of speed control was calculated without changing the impulse parameters and the flow characteristic curve of the valve. Through many attempts to establish the optimal value of feedforward quantity, the fast closing action of the governing valve can be avoided due to the unreasonable parameter setting in the control logic. After optimization, the actual speed rises steadily with the set value, the valve opening is opened linearly, and there is no more frequent swing, which meets the requirements of speed up control.

Abstract Background Porcine circovirus type 3 (PCV3) has been an emerging porcine virus spread around the world. The conserved DNA sequence of PCV3 enabled good performance in molecular biological assays. Result In this study, we developed a real-time fluorescence PCR assay for the detection of PCV3. The conserved region within Capsid genome of PCV3 was selected for the design of primer pairs and probes. After optimizing, a primer pair and probe was screened, providing high sensitivity (10 copies/μL) and specificity (no cross reaction with other porcine viruses or common bacterium). In addition, this method was applied in the detection of 110 clinical samples, and the performance was compared with other previously reported PCR and real-time PCR methods. This method provided higher detection rate. Conclusion A real-time fluorescence PCR assay has been developed for the detection of PCV3, with high sensitivity and specificity, exhibiting good performance in detecting clinical samples.