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Abstract Background In facial plastic surgery, patients with nasal deformity are often treated by rib cartilage transplantation. In recent years, cartilage tissue engineering has developed as an alternative to complex surgery for patients with minor nasal defects via injection of nasal filler material. In this study, we prepared an injectable nasal filler material containing poly‐L‐lactic acid (PLLA) porous microspheres (PMs), hyaluronic acid (HA) and adipose‐derived mesenchymal stem cells (ADMSCs). Methods We seeded ADMSCs into as‐prepared PLLA PMs using our newly invented centrifugation perfusion technique. Then, HA was mixed with ADMSC‐incorporated PLLA PMs to form a hydrophilic and injectable cell delivery system (ADMSC‐incorporated PMH). Results We evaluated the biocompatibility of PMH in vitro and in vivo. PMH has good injectability and provides a favorable environment for the proliferation and chondrogenic differentiation of ADMSCs. In vivo experiments, we observed that PMH has good biocompatibility and cartilage regeneration ability. Conclusion In this study, a injectable cell delivery system was successfully constructed. We believe that PMH has potential application in cartilage tissue engineering, especially in nasal cartilage regeneration.

Abstract Background This study investigates the clinical efficacy and safety of percutaneous endoscopic nucleotomy combined with platelet-rich plasma (PRP) injection in treating lumbar disc herniation (LDH) in young and middle-aged adults. Methods From April 2022 to September 2023, 60 patients diagnosed with LDH were randomly divided into two groups (n = 30/group). The observation group underwent percutaneous endoscopic nucleotomy combined with autologous PRP gel injection into the disc, while the control group underwent percutaneous endoscopic nucleotomy alone. Visual Analogue Scale (VAS) scores and Oswestry Disability Index (ODI) scores were recorded preoperatively and at three time points postoperatively: three days, three months, and six months. The modified Macnab criteria were employed to evaluate efficacy at the final follow-up. Additionally, MRI Pfirrmann grading of the operated disc segment and potential complications were assessed both preoperatively and at the final follow-up. Results All patients were followed for a minimum of six months. VAS and ODI scores at all postoperative time points (three days, three months, and six months) exhibited significant differences compared to preoperative scores in both groups (P 0.05). Furthermore, no patients experienced complications such as dural tears, nerve root injury, infection, or hematoma. Conclusion The combination of percutaneous endoscopic nucleotomy and PRP injection could be a safe and effective treatment for LDH in young and middle-aged adults to promote disc repair following endoscopic procedures.

Idiopathic pulmonary fibrosis (IPF) is a prevalent chronic pulmonary fibrosis disease characterized by alveolar epithelial cell damage, fibroblast proliferation and activation, excessive extracellular matrix deposition, and abnormal epithelial-mesenchymal transition (EMT), resulting in tissue remodeling and irreversible structural distortion. The mortality rate of IPF is very high, with a median survival time of 2–3 years after diagnosis. The exact cause of IPF remains unknown, but increasing evidence supports the central role of epigenetic changes, particularly microRNA (miRNA), in IPF. Approximately 10% of miRNAs in IPF lung tissue exhibit differential expression compared to normal lung tissue. Diverse miRNA phenotypes exert either a pro-fibrotic or anti-fibrotic influence on the progression of IPF. In the context of IPF, epigenetic factors such as DNA methylation and long non-coding RNAs (lncRNAs) regulate differentially expressed miRNAs, which in turn modulate various signaling pathways implicated in this process, including transforming growth factor-β1 (TGF-β1)/Smad, mitogen-activated protein kinase (MAPK), and phosphatidylinositol-3-kinase/protein kinase B (PI3K/AKT) pathways. Therefore, this review presents the epidemiology of IPF, discusses the multifaceted regulatory roles of miRNAs in IPF, and explores the impact of miRNAs on IPF through various pathways, particularly the TGF-β1/Smad pathway and its constituent structures. Consequently, we investigate the potential for targeting miRNAs as a treatment for IPF, thereby contributing to advancements in IPF research.

Pulmonary fibrosis is a progressive interstitial lung disease associated with aging. The pathogenesis of pulmonary fibrosis remains unclear, however, alveolar epithelial cell injury, myofibroblast activation, and extracellular matrix (ECM) accumulation are recognized as key contributors. Moreover, recent studies have implicated cellular senescence, endothelial-mesenchymal transition (EndMT), and epigenetic modifications in the pathogenesis of fibrotic diseases. Various signaling pathways regulate pulmonary fibrosis, including the TGF-β, Notch, Wnt, Hedgehog, and mTOR pathways. Among these, the TGF-β pathway is extensively studied, while the Notch pathway has emerged as a recent research focus. The Notch pathway influences the fibrotic process by modulating immune cell differentiation (e.g., macrophages, lymphocytes), inhibiting autophagy, and promoting interstitial transformation. Consequently, inhibiting Notch signaling represents a promising approach to mitigating pulmonary fibrosis. In this review, we discuss the role of Notch signaling pathway in pulmonary fibrosis, aiming to offer insights for future therapeutic investigations.

This study examines the effects of three interactive voice assistant (VA) features (responsiveness, ubiquitous connectivity, and personalization) on consumer happiness. An online survey was administered to 316 VA consumers, and the data were analyzed using structural equation modeling with SmartPLS 4 software. The results indicate that VA responsiveness, ubiquitous connectivity, and personalization have significant effects on consumer happiness. This study also provides evidence that consumer happiness is influenced by VA features through the mediating roles of autonomy and timeliness. Notably, perceived privacy risk has a dual effect, negatively affecting happiness but positively moderating the relationship between autonomy and happiness, suggesting a complex interplay between benefits and concerns in user interactions with VAs. This study highlights the need for VA businesses to consider both the enhancing and mitigating factors of technology for user experiences. Furthermore, our findings have significant implications for VA businesses and executives, suggesting that improved interactions through these VA features can better serve consumers and enhance their experiences.

Abstract Genetic variants can influence complex traits by altering gene expression through changes to regulatory elements. However, the genetic variants that affect the activity of regulatory elements in pigs are largely unknown, and the extent to which these variants influence gene expression and contribute to the understanding of complex phenotypes remains unclear. Here, we annotate 90,991 high-quality regulatory elements using acetylation of histone H3 on lysine 27 (H3K27ac) ChIP-seq of 292 pig livers. Combined with genome resequencing and RNA-seq data, we identify 28,425 H3K27ac quantitative trait loci (acQTLs) and 12,250 expression quantitative trait loci (eQTLs). Through the allelic imbalance analysis, we validate two causative acQTL variants in independent datasets. We observe substantial sharing of genetic controls between gene expression and H3K27ac, particularly within promoters. We infer that 46% of H3K27ac exhibit a concomitant rather than causative relationship with gene expression. By integrating GWAS, eQTLs, acQTLs, and transcription factor binding prediction, we further demonstrate their application, through metabolites dulcitol, phosphatidylcholine (PC) (16:0/16:0) and published phenotypes, in identifying likely causal variants and genes, and discovering sub-threshold GWAS loci. We provide insight into the relationship between regulatory elements and gene expression, and the genetic foundation for dissecting the molecular mechanism of phenotypes.

The generation of high-precision ground digital elevation models (DEMs) based on synthetic aperture radar interferometry (InSAR) technology has attracted wide attention. Compared with the linear InSAR technique, the 360$^\circ$ aperture gives circular InSAR (In-CSAR) the capability to generate a full-angle DEM of the observed region. The backprojection (BP) algorithm is considered as a preferred candidate for In-CSAR imaging since it does not impose any restrictions on flight trajectories. After phase unwrapping, a global unknown phase ambiguity exists in the unwrapped phase. Up to now, high-efficient frequency-domain methods, such as the split-bandwidth technique, have commonly been used to estimate the phase ambiguity. However, the split-bandwidth technique cannot be effectively integrated with the BP-focusing image due to the highly nonlinear and nonparallel trajectories of the airborne In-CSAR platforms. We present, for the first time, the combination of BP and split-bandwidth techniques for absolute phase estimation of In-CSAR interferogram in this article. The proposed method can avoid the phase offset induced by split-bandwidth processing under the conditions of highly nonlinear and nonparallel platform trajectories. In addition, the spectral characteristics of the BP-focusing subimage are derived in detail to correct its 2-D space-variant spectral support. In order to reduce the impact of coherence, the weighted least square is adopted to estimate unknown phase ambiguity. The processing results of simulation and real data verify that the proposed approach can effectively estimate the phase ambiguity even under the conditions of highly nonlinear and nonparallel platform trajectories.

Airborne Wide angle staring Synthetic Aperture Radar (WasSAR) is a novel SAR imaging technique that enables multiangle and long-time staring imaging of an observation region. The combination of WasSAR and Ground Moving Target Indication (GMTI) facilitates the long-time tracking of moving targets in key areas, thereby obtaining dynamic sensing information. Herein, we initially constructed a moving target echo model for airborne multi-channel WasSAR, followed by an analysis of the characteristics of a moving target during WasSAR imaging. Further, group phase shift calibration and modified A2DC methods are proposed to mitigate the influence of platform attitude errors and channel imbalances. In accordance with this, an extended airborne multi-channel WasSAR ground moving target detection and tracking method is proposed, which achieves accurate detection and tracking of targets moving on complex roads. Finally, a trajectory reconstruction method for moving targets in airborne multi-channel WasSAR-GMTI is presented, demonstrating accurate trajectory reconstruction for targets on complex roads. Moreover, a flight experiment using our independently developed airborne multi-channel WasSAR-GMTI system, along with the associated real data processing results, is presented. These results confirm the validity and practicability of airborne WasSAR-GMTI for moving target dynamic surveillance and serve as a foundation for future research.

Abstract Background Chest computed tomography (CT) image quality impacts radiologists’ diagnoses. Pre-diagnostic image quality assessment is essential but labor-intensive and may have human limitations (fatigue, perceptual biases, and cognitive biases). This study aims to develop and validate a deep learning (DL)-driven multi-view multi-task image quality assessment (M $$^2$$ 2 IQA) method for assessing the quality of chest CT images in patients, to determine if they are suitable for assessing the patient’s physical condition. Methods This retrospective study utilizes and analyzes chest CT images from 327 patients. Among them, 1613 images from 286 patients are used for model training and validation, while the remaining 41 patients are reserved as an additional test set for conducting ablation studies, comparative studies, and observer studies. The M $$^2$$ 2 IQA method is driven by DL technology and employs a multi-view fusion strategy, which incorporates three scanning planes (coronal, axial, and sagittal). It assesses image quality for multiple tasks, including inspiration evaluation, position evaluation, radiation protection evaluation, and artifact evaluation. Four algorithms (pixel threshold, neural statistics, region measurement, and distance measurement) have been proposed, each tailored for specific evaluation tasks, with the aim of optimizing the evaluation performance of the M $$^2$$ 2 IQA method. Results In the additional test set, the M $$^2$$ 2 IQA method achieved 87% precision, 93% sensitivity, 69% specificity, and a 0.90 F1-score. Extensive ablation and comparative studies have demonstrated the effectiveness of the proposed algorithms and the generalization performance of the proposed method across various assessment tasks. Conclusion This study develops and validates a DL-driven M $$^2$$ 2 IQA method, complemented by four proposed algorithms. It holds great promise in automating the assessment of chest CT image quality. The performance of this method, as well as the effectiveness of the four algorithms, is demonstrated on an additional test set.

This study examines the impact of cultural involvement on brand enriching benefits and consumers’ willingness to pay a premium (WPP). Additionally, it explores the underlying mechanisms behind this impact. A partial least squares structural equation model was used to analyze the data collected from a pretest (N = 70) and an online survey (N = 1053) conducted in China. The moderating effect of brand type was examined using a multi-group analysis. The results indicate that cultural involvement has a significant and positive impact on brand enriching benefits, consequently enhancing consumers’ WPP. Additionally, brand happiness mediates the relationship between brand enriching benefits and WPP. Through a multi-group analysis, the impact of brand culture on brand equity is found to be more pronounced in functional brands compared with symbolic brands. Additionally, high perceived quality facilitates the transformation of brand enriching benefits into WPP. Managers value the ability of a brand culture to create brand equity and implement differentiation strategies based on different brand types. It is critical for managers to use a culture and its rich benefits wisely and to consider consumer happiness in the brand experience. Although brand culture and its impact on brands are crucial, previous studies have only focused on qualitative analyses, while empirical research on the direct link between brand culture and equity has been lacking. This study empirically tests a conceptual model that elucidates the relationship between brand cultural involvement, brand enriching benefits, brand happiness, WPP, brand type, and perceived quality. It extends previous research and offers suggestions for academics and brand managers interested in effectively leveraging brand culture for brand building.

Affected by a trough and shear line, a Meiyu heavy rainfall event occurred in Hubei Province from June 27th to 28th in 2020, resulting in severe disasters and significant economic losses.. To investigate the impact of microphysical processes on Meiyu front heavy rainfall and improve the forecasting and warning capabilities, the heavy rainfall case was simulated utilizing the regional model WRF 3.4.1, and the effect of cloud microphysical characteristics on the heavy rainfall was discussed. Results are as follows: (1) The heavy rainfall area and evolution of area-averaged precipitation were simulated well with a little overestimation. At the same time, the mesoscale systems were reproduced well through model results. (2) When rainfall strengthened rapidly, melting of ice phase hydrometeors (Melt) contributed more to the growth of rain drop than accretion of cloud droplet by rain drop (CLcr) and the composite radar echo developed rapidly. When the rainfall strengthened a little more smoothly, the amount of CLcr was larger than that of Melt. All the hydrometeors grew significantly and the composite radar echo intensified dramatically. Ice crystals grew more rapidly than snow and graupel. Before the peak rainfall, the content of hydrometeors (except snow), updraft and composite radar echo had reached extreme values. The center of updraft is more consistent with the area of large values of ice-phase particles and cloud droplets content, which is favorable to the riming process. Ice, graupel and the amount of water vapor condensation reached their maximum content and the composite radar echo began to decay before the strongest precipitation occurred. (3) Less ice phase hydrometeors collected cloud droplet was produced than CLcr. Auto conversion of cloud droplet to rain increased significantly when the rainfall process decayed. The main pathway of ice phased hydrometeors was Bergeron process in the initial stage of the precipitation. With the growth of ice phase hydrometeors, riming process between cloud droplet and ice phase hydrometeors was dominant until the heavy rainfall process ended.

Rapid urbanization is a global phenomenon that has altered many ecosystems and created ecological risks. Landscape ecological risk (LER) reflects the extent to which ecosystems are threatened by human activities and environmental change. LER can be also employed to effectively monitor and assess environmental quality. A large number of studies have been conducted to explore the LER in the basin from the perspective of Land Use and Land Cover (LUCC). Ecological environmental issues such as land degradation have seriously hindered the sustainable development of the Yellow River Basin (YRB). Based on the LUCC data of the YRB in the four periods of 1990, 2000, 2010 and 2020, this study aims to determine the most suitable spatial analysis scale using the coefficient of variation and semi-variogram, and analyzes the landscape pattern and LER of the YRB. We found that the landscape pattern of the YRB exhibits obvious scale dependence, and the analysis effect is most effective at the scale of 90 km × 90 km. Throughout the study period, the landscape pattern exhibited increasing fragmentation, a decrease in the degree of aggregation and an increase in the heterogeneity of distribution. In terms of LER, it is in a better state as most of the LER levels have shifted from higher to lower levels, and the proportion of lower and lowest risk is constantly increasing. This study improves the precision of spatial scale investigations and offers valuable insights for future studies on landscape pattern and LER in the basin.

Bone defects have long been a major healthcare issue because of the difficulties in regenerating bone mass volume and the high cost of treatment. G protein-coupled receptor kinase 2 interacting protein 1 (GIT1) has been proven to play an important role both in vascular development and in bone fracture healing. In this study, a type of thermoresponsive injectable hydrogel from oligoethylene glycol-based dendronized chitosan (G1-CS) was loaded with GIT1-plasmids (G1-CS/GIT1), and used to fill unicortical bone defects. RT-PCR analysis confirmed that G1-CS/GIT1 enhanced DNA transfection in MSCs both in vitro and in vivo. From the results of micro-CT, RT-PCR and histological analysis, it can be concluded that G1-CS/GIT1 accelerated the bone healing rate and increased the amount of neovascularization around the bone defects. In addition, an adeno-associated virus (AAV)-GIT1 was constructed to transfect mesenchymal stem cells. The results of capillary tube formation assay, immunofluorescence staining and western blot analysis proved that high expression of GIT1 induces mesenchymal stem cells to differentiate into endothelial cells. RT-PCR analysis and capillary tube formation assay confirmed that the Notch signaling pathway was activated in the differentiation process. Overall, we developed an efficient strategy through combination of injectable hydrogel and G1T1 for bone tissue engineering.

The occurrence of β-blocker drugs in aquatic environments worldwide has caused increasing attention to their threat to human health in recent years. It is essential to monitor these widely prescribed pharmaceuticals in natural waters and sediments, helping us investigate their potential risk to humans and ecosystems. In this study, a passive sampling technique, diffusive gradients in thin-films (DGT), was systematically developed for eight frequently detected β-blockers. The effective capacities of target compounds were large enough for the devices to deploy for several weeks. The uptake of all compounds was linearly correlated with deployment times during the 7-day laboratory experiment and agreed well with the theoretical line, except for several compounds (e.g., ATL) due to their relatively slow uptake rate. The performance of most compounds was independent of varying pH values and organic matter contents; only a few compounds were affected, while the application in high-salinity environments needs to be conducted with caution. Field deployments of DGT to detect β-blockers in situ in rivers and sediments proved that DGT is an effective tool to monitor β-blocker drugs and their fate in the natural aquatic environment, while DGT probes can provide information for us to investigate the biogeochemical processes occurred in sediment, especially at the sediment–water interface. This novel approach will help us understand the behaviour of β-blocker drugs in the aquatic environment, assess their risks, finally protect human health and maintain the sustainable development of the ecosystem.

The present study assesses the simulated precipitation and cloud properties using three microphysics schemes (Morrison, Thompson and MY) implemented in the Weather Research and Forecasting model. The precipitation, differential reflectivity (ZDR), specific differential phase (KDP) and mass-weighted mean diameter of raindrops (Dm) are compared with measurements from a heavy rainfall event that occurred on 27 June 2020 during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE). The results indicate that all three microphysics schemes generally capture the characteristics of rainfall, ZDR, KDP and Dm, but tend to overestimate their intensity. To enhance the model performance, adjustments are made based on the MY scheme, which exhibited the best performance. Specifically, the overall coalescence and collision parameter (Ec) is reduced, which effectively decreases Dm and makes it more consistent with observations. Generally, reducing Ec leads to an increase in the simulated content (Qr) and number concentration (Nr) of raindrops across most time steps and altitudes. With a smaller Ec, the impact of microphysical processes on Nr and Qr varies with time and altitude. Generally, the autoconversion of droplets to raindrops primarily contributes to Nr, while the accretion of cloud droplets by raindrops plays a more significant role in increasing Qr. In this study, it is emphasized that even if the precipitation characteristics could be adequately reproduced, accurately simulating microphysical characteristics remains challenging and it still needs adjustments in the most physically based parameterizations to achieve more accurate simulation.

In order to address fundamental questions related to the expansion history of the Universe and its primordial nature with the next generation of galaxy experiments, we need to model reliably large-scale structure observables such as the correlation function and the power spectrum. Cosmological $N$-body simulations provide a reference through which we can test our models, but their output suffers from sample variance on large scales. Fortunately, this is the regime where accurate analytic approximations exist. To reduce the variance, which is key to making optimal use of these simulations, we can leverage the accuracy and precision of such analytic descriptions using Control Variates (CV). The power of control variates stems from utilizing inexpensive but highly correlated surrogates of the statistics one wishes to measure. The stronger the correlation between the surrogate and the statistic of interest, the larger the variance reduction delivered by the method. We apply two control variate formulations to mock catalogs generated in anticipation of upcoming data from the Dark Energy Spectroscopic Instrument (DESI) to test the robustness of its analysis pipeline. Our CV-reduced measurements, of the power spectrum and correlation function, both pre- and post-reconstruction, offer a factor of 5-10 improvement in the measurement error compared with the raw measurements from the DESI mock catalogs. We explore the relevant properties of the galaxy samples that dictate this reduction and comment on the improvements we find on some of the derived quantities relevant to Baryon Acoustic Oscillation (BAO) analysis. We also provide an optimized package for computing the power spectra and other two-point statistics of an arbitrary galaxy catalog as well as a pipeline for obtaining CV-reduced measurements on any of the \textsc{AbacusSummit} cubic box outputs. We make our scripts, notebooks, and benchmark tests against existing software publicly available and report a speed improvement of a factor of $\sim$ 10 for a grid size of $N_{\rm mesh} = 256^3$ compared with \texttt{nbodykit}.

Due to the inherent limitations of matching algorithms and the complexities associated with image contents, mismatches are inevitable and can have detrimental effects on downstream tasks in computer vision and remote sensing. Researchers have published numerous reviews on mismatch removal, which may suffer from two primary deficiencies. Firstly, these reviews are often embedded within studies that primarily focus on image matching, thereby limiting the detailed and comprehensive analysis of mismatch removal methods. Secondly, reviews of deep learning (DL)-based methods, despite their numerous existence and interconnection, tend to be fragmentary and lack a systematic approach. To address these two shortcomings, this paper presents a comprehensive survey of DL-based mismatch removal principles and methods. We provide a summary of network architectures, techniques for extracting geometrical information, and various training modes. Specifically, we highlight the importance of permutation invariance in mining operations, enumerate a majority of existing mining methods, and provide an explanation of their permutation invariant properties. Furthermore, we present both the intuitive motivation and mathematical analysis of commonly used methods, elucidating their underlying principles and efficacy. In the conclusion, we predict upcoming trends based on the findings of our review, aiming to provide valuable insights into mismatch removal techniques and guide their practical applications.

Most learning-based methods require labelling the training data, which is time-consuming and gives rise to wrong labels. To address the labelling issues thoroughly, we propose an unsupervised learning framework to remove mismatches by maximizing the expected score of sample consensuses (MESAC). The proposed MESAC can train various permutation invariant networks (PINs) based on training data with no labels, and has three distinct merits: 1) the framework can train various PINs in an unsupervised mode such that these are immune to wrong labels; 2) the gradients of the expected score are explicitly calculated by a revised score-function estimator, which can avoid gradient explosion; 3) the distribution of matching probabilities is learned from the PIN and precisely modelled by a categorical distribution, which can decrease the sampling times and improve the computational efficiency accordingly. Experiments of testing datasets disclose that mean recall is increased by at most 77% when pure PINs are embedded in MESAC, and mean precision is also improved by 16%. Applications in pose recovery indicate that the success rates of MESAC-integrated PINs outperform the compared methods when training with neither matching labels nor ground truth epipolar geometry (EG) constraints, showing the great potential of MESAC in mismatch removal.

With the continuous development of synthetic aperture radar (SAR) technology, SAR image data are becoming increasingly abundant. For the same scene, dual-frequency (high-frequency and low-frequency) SAR images can present different details and feature information. SAR image fusion of the two frequencies can combine the advantages of both, thus describing targets more comprehensively. Because high-resolution SAR images contain a large amount of detailed information, such as edges and textures, the traditional fusion methods cannot fuse this information better, resulting in a loss of information. To solve the problem, this article proposes a fusion method suitable for airborne dual-frequency, high-resolution SAR images. First, the source SAR images are decomposed to obtain their low-pass bands and high-pass bands by using the nonsubsampled Shearlet transform (NSST). Then, we apply the improved nonnegative matrix factorization to merge the low-pass bands and use the new sum of modified Laplacian to merge the high-pass bands. After that, the fused low-pass bands and high-pass bands are reconstructed by the inverse NSST, to obtain the final fused image. Finally, by processing the airborne SAR data, the effectiveness of the proposed method is verified.

The multirotor Unmanned Aerial Vehicle (UAV) has the advantages of small size, light weight, and low cost. However, imaging signal processing is complicated due to the extremely unstable flight path. Real-time adjustment of pulse repetition frequency based on inertial navigation data can compensate for the along-track displacement error in advance, but the residual error cannot be ignored for highly squinted high-band Synthetic Aperture Radar (SAR). Therefore, the residual along-track displacement error is extracted based on the difference between the measured displacement value and the ideal one, and then the Line-of-Sight (LOS) motion error of the squint imaging geometry is modified. The traditional first-order and second-order LOS error compensation factors are improved, and the tolerance of the amplitude and frequency of the sinusoidal displacement error of a multirotor UAV is analyzed based on paired echo theory. Simulation and flight experiments verify that the proposed method can reduce the LOS motion error by an order of magnitude in large squint imaging and significantly improve the imaging performance of the squinted SAR of a multirotor UAV.

Abstract Background A comprehensive landscape of chromatin states for multiple mammalian tissues is essential for elucidating the molecular mechanism underlying regulatory variants on complex traits. However, the genome-wide chromatin accessibility has been only reported in limited tissue types in pigs. Results Here we report a genome-wide landscape of chromatin accessibility of 20 tissues in two female pigs at ages of 6 months using ATAC-seq, and identified 557,273 merged peaks, which greatly expanded the pig regulatory element repository. We revealed tissue-specific regulatory elements which were associated with tissue-relevant biological functions. We identified both positive and negative significant correlations between the regulatory elements and gene transcripts, which showed distinct distributions in terms of their strength and distances from corresponding genes. We investigated the presence of transposable elements (TEs) in open chromatin regions across all tissues, these included identifications of porcine endogenous retroviruses (PERVs) exhibiting high accessibility in liver and homology of porcine specific virus sequences to universally accessible transposable elements. Furthermore, we prioritized a potential causal variant for polyunsaturated fatty acid in the muscle. Conclusions Our data provides a novel multi-tissues accessible chromatin landscape that serve as an important resource for interpreting regulatory sequences in tissue-specific and conserved biological functions, as well as regulatory variants of loci associated with complex traits in pigs.

In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r - and z -band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo- z ) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ∼10 ^9 h ^−2 L _⊙ (or h ^−2 M _⊙ ) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function.

The Dark Energy Spectroscopic Instrument (DESI) is currently measuring the spectra of 40 million galaxies and quasars, the largest such survey ever made to probe the nature of cosmological dark energy. The 4 m Mayall telescope at Kitt Peak National Observatory has been adapted for DESI, including the construction of a 3.°2 diameter prime focus corrector that focuses astronomical light onto a 0.8 m diameter focal surface with excellent image quality over the DESI bandpass of 360–980 nm. The wide-field corrector includes six lenses, as large as 1.1 m in diameter and as heavy as 237 kilograms, including two counterrotating wedged lenses that correct for atmospheric dispersion over zenith angles from 0° to 60°. The lenses, cells, and barrel assembly all meet precise alignment tolerances on the order of tens of microns. The barrel alignment is maintained throughout a range of observing angles and temperature excursions in the Mayall dome by use of a hexapod, which is itself supported by a new cage, ring, and truss structure. In this paper we describe the design, fabrication, and performance of the new corrector and associated structure, focusing on how they meet DESI requirements. In particular, we describe the prescription and specifications of the lenses, design choices and error budgeting of the barrel assembly, stray light mitigations, and integration and test at the Mayall telescope. We conclude with some validation highlights that demonstrate the successful corrector on-sky performance, and we list some lessons learned during the multiyear fabrication phase.

We present the final data from the Sloan Digital Sky Survey (SDSS) Reverberation Mapping (RM) project, a precursor to the SDSS-V Black Hole Mapper RM program. This data set includes 11 yr photometric and 7 yr spectroscopic light curves for 849 broad-line quasars over a redshift range of 0.1 < z < 4.5 and a luminosity range of L _bol = 10 ^44−47.5 erg s ^−1 , along with spectral and variability measurements. We report 23, 81, 125, and 110 RM lags (relative to optical continuum variability) for broad H α , H β , Mg ii , and C iv using the SDSS-RM sample, spanning much of the luminosity and redshift ranges of the sample. Using 30 low-redshift RM active galactic nuclei with dynamical-modeling black hole masses, we derive a new estimate of the average virial factor of $\left\langle \mathrm{log}f\right\rangle =0.62\pm 0.07$ for the line dispersion measured from the rms spectrum. The intrinsic scatter of individual virial factors is 0.31 ± 0.07 dex, indicating a factor of 2 systematic uncertainty in RM black hole masses. Our lag measurements reveal significant R – L relations for H β and Mg ii at high redshift, consistent with the latest measurements based on heterogeneous samples. While we are unable to robustly constrain the slope of the R – L relation for C iv given the limited dynamic range in luminosity, we found substantially larger scatter in C iv lags at fixed L _1350 . Using the SDSS-RM lag sample, we derive improved single-epoch (SE) mass recipes for H β , Mg ii , and C iv , which are consistent with their respective RM masses as well as between the SE recipes from two different lines, over the luminosity range probed by our sample. The new H β and Mg ii recipes are approximately unbiased estimators at given RM masses, but there are systematic biases in the C iv recipe. The intrinsic scatter of SE masses around RM masses is ∼0.45 dex for H β and Mg ii , increasing to ∼0.58 dex for C iv .

Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong-lensing systems on an unprecedented scale, which requires efficient tools to extract them from billions of astronomical objects. The existing mainstream lens-finding tools are based on machine-learning algorithms and applied to cutout-centered galaxies. However, according to the design and survey strategy of optical surveys by the China Space Station Telescope (CSST), preparing cutouts with multiple bands requires considerable efforts. To overcome these challenges, we have developed a framework based on a hierarchical visual transformer with a sliding window technique to search for strong-lensing systems within entire images. Moreover, given that multicolor images of strong-lensing systems can provide insights into their physical characteristics, our framework is specifically crafted to identify strong-lensing systems in images with any number of channels. As evaluated using CSST mock data based on a semianalytic model named CosmoDC2, our framework achieves precision and recall rates of 0.98 and 0.90, respectively. To evaluate the effectiveness of our method in real observations, we have applied it to a subset of images from the DESI Legacy Imaging Surveys and media images from Euclid Early Release Observations. A total of 61 new strong-lensing system candidates are discovered by our method. However, we also identified false positives arising primarily from the simplified galaxy morphology assumptions within the simulation. This underscores the practical limitations of our approach while simultaneously highlighting potential avenues for future improvements.

We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z = 0.1 to 0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey. In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab , which enables the rapid, precise prediction of CiC for any HOD model available in halotools . This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in z ∼ 0.15 samples with limiting absolute magnitude M _r < −20.0 and M _r < −20.5 samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter M _r < −21.0 sample at z ∼ 0.25 (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at z ∼ 0.15. We provide our constraints for each threshold sample’s characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3.

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-percent Survey. The One-percent Survey was one of DESI’s survey validation programs conducted from 2021 April to May, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the r < 19.5 magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface-brightness- and color-selected BGS Faint sample over z < 0.6. We derive pSMFs from posteriors of stellar mass, M _* , inferred from DESI photometry and spectroscopy using the Hahn et al. PRObabilistic Value-Added BGS (PROVABGS) Bayesian spectral energy distribution modeling framework. We use a hierarchical population inference framework that statistically and rigorously propagates the M _* uncertainties. Furthermore, we include correction weights that account for the selection effects and incompleteness of the BGS observations. We present the redshift evolution of the pSMF in BGS, as well as the pSMFs of star-forming and quiescent galaxies classified using average specific star formation rates from PROVABGS. Overall, the pSMFs show good agreement with previous stellar mass function measurements in the literature. Our pSMFs showcase the potential and statistical power of BGS, which in its main survey will observe >100 × more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision.

Changing-look active galactic nuclei (CL AGNs) can be generally confirmed by the emergence (turn-on) or disappearance (turn-off) of broad emission lines (BELs), associated with a transient timescale (about 100 ∼ 5000 days) that is much shorter than predicted by traditional accretion disk models. We carry out a systematic CL AGN search by crossmatching the spectra coming from the Dark Energy Spectroscopic Instrument and the Sloan Digital Sky Survey. Following previous studies, we identify CL AGNs based on H α , H β , and Mg ii at z ≤ 0.75 and Mg ii , C iii ], and C iv at z > 0.75. We present 56 CL AGNs based on visual inspection and three selection criteria, including 2 H α , 34 H β , 9 Mg ii , 18 C iii ], and 1 C iv CL AGN. Eight cases show simultaneous appearances/disappearances of two BELs. We also present 44 CL AGN candidates with significant flux variation of BELs, but remaining strong broad components. In the confirmed CL AGNs, 10 cases show additional CL candidate features for different lines. In this paper, we find: (1) a 24:32 ratio of turn-on to turn-off CL AGNs; (2) an upper-limit transition timescale ranging from 330 to 5762 days in the rest frame; and (3) the majority of CL AGNs follow the bluer-when-brighter trend. Our results greatly increase the current CL census (∼30%) and would be conducive to exploring the underlying physical mechanism.

Extremely metal-poor galaxies (XMPGs) at relatively low redshift are excellent laboratories for studying galaxy formation and evolution in the early universe. Much effort has been spent on identifying them from large-scale spectroscopic surveys or spectroscopic follow-up observations. Previous work has identified a few hundred XMPGs. In this work, we obtain a large sample of 223 XMPGs at z < 1 from the early data of the Dark Energy Spectroscopic Instrument (DESI). The oxygen abundance is determined using the direct T _e method based on the detection of the [O iii ] λ 4363 line. The sample includes 95 confirmed XMPGs based on the oxygen abundance uncertainty; the remaining 128 galaxies are regarded as XMPG candidates. These XMPGs are only 0.01% of the total DESI observed galaxies. Their coordinates and other properties are provided in the paper. The most XMPGs have an oxygen abundance of ∼1/34 Z _⊙ , a stellar mass of about 1.5 × 10 ^7 M _⊙, and a star formation rate of 0.22 M _⊙ yr ^−1 . The two most XMPGs present distinct morphologies suggesting different formation mechanisms. The local environmental investigation shows that XMPGs preferentially reside in relatively low-density regions. Many of them fall below the stellar mass–metallicity relations (MZRs) of normal star-forming galaxies. From a comparison of the MZR with theoretical simulations, it appears that XMPGs are good analogs to high-redshift star-forming galaxies. The nature of these XMPG populations will be further investigated in detail with larger and more complete samples from the ongoing DESI survey.

Galactic conformity is the phenomenon whereby a galaxy of a certain physical property is correlated with its neighbors of the same property, implying a possible causal relationship. The observed auto correlations of emission-line galaxies (ELGs) from the highly complete DESI One-Percent Survey exhibit a strong clustering signal on small scales, providing clear evidence for the conformity effect of ELGs. Building upon the original subhalo abundance-matching (SHAM) method developed by Gao et al., we propose a concise conformity model to improve the ELG–halo connection. In this model, the number of satellite ELGs is boosted by a factor of ∼5 in the halos whose central galaxies are ELGs. We show that the mean ELG satellite number in such central halos is still smaller than 1 and that the model does not significantly increase the overall satellite fraction. With this model, we can well recover the ELG auto correlations to the smallest scales explored with the current data (i.e., r _p > 0.03 Mpc h ^−1 in real space and at s > 0.3 Mpc h ^−1 in redshift space), while the cross correlations between luminous red galaxies and ELGs are nearly unchanged. Although our SHAM model has only eight parameters, we further verify that it can accurately describe the ELG clustering in the entire redshift range from z = 0.8 to 1.6. We therefore expect that this method can be used to generate high-quality ELG lightcone mocks for DESI.

Abstract Dramatic phenotypic differences between domestic pigs and wild boars (Sus scrofa) provide opportunities to investigate molecular mechanisms underlying the formation of complex traits, including morphology, physiology and behaviour. Most studies comparing domestic pigs and wild boars have focused on variations in DNA sequences and mRNA expression, but not on epigenetic changes. Here, we present a genome‐wide comparative study on H3K27ac enhancer activities and the corresponding mRNA profiling in the brain and liver tissues of adult Bama Xiang pigs (BMXs) and Chinese wild boars (CWBs). We identified a total of 1,29,487 potential regulatory elements, among which 11,241 H3K27ac peaks showed differential activity between CWBs and BMXs in at least one tissue. These peaks were overrepresented by binding motifs of FOXA1, JunB, ATF3 and BATF, and overlapped with differentially expressed genes that are involved in female mating behaviour, response to growth factors and hormones, and lipid metabolism. We also identified 4118 nonredundant super‐enhancers from ChIP‐Seq data on H3K27ac. Notably, we identified differentially active peaks located close to or within candidate genes, including TBX19, MSTN, AHR and P2RY1, which were identified in DNA sequence‐based population differentiation studies. This study generates a valuable dataset on H3K27ac profiles of the brain and liver from domestic pigs and wild boars, which helps gain insights into the changes in enhancer activities from wild boars to domestic pigs.

Abstract Background Short tandem repeats (STRs) were recently found to have significant impacts on gene expression and diseases in humans, but their roles on gene expression and complex traits in pigs remain unexplored. This study investigates the effects of STRs on gene expression in liver tissues based on the whole-genome sequences and RNA-Seq data of a discovery cohort of 260 F6 individuals and a validation population of 296 F7 individuals from a heterogeneous population generated from crosses among eight pig breeds. Results We identified 5203 and 5868 significantly expression STRs (eSTRs, FDR

In this paper, a barrier adaptive iterative learning control scheme is proposed to solve the trajectory-tracking problem for tank gun control systems under nonzero initial error condition. A novel construction method of rectified reference trajectory is presented for dealing with the initial position problem of iterative learning control for tank gun control systems. With a quadratic form barrier Lyapunov function adopted to controller design, the quadratic form of system error is constrained within the preset range during each iteration. Adaptive iterative learning control technique and robust control technique are jointly used to compensate for the parametric/nonparametric uncertainties and nonsymmetric deadzone nonlinearity. As the iteration number increases, the system state of tank gun control systems may accurately track the rectified reference trajectory, which leads to a excellent tracking performance during the part operation interval of tank gun control systems. Simulation results are presented to verify the effectiveness of the proposed barrier adaptive iterative control scheme.

We utilize ∼17,000 bright luminous red galaxies (LRGs) from the novel Dark Energy Spectroscopic Instrument Survey Validation spectroscopic sample, leveraging its deep (∼2.5 hr galaxy ^−1 exposure time) spectra to characterize the contribution of recently quenched galaxies to the massive galaxy population at 0.4 < z < 1.3. We use Prospector to infer nonparametric star formation histories and identify a significant population of recently quenched galaxies that have joined the quiescent population within the past ∼1 Gyr. The highest-redshift subset (277 at z > 1) of our sample of recently quenched galaxies represents the largest spectroscopic sample of post-starburst galaxies at that epoch. At 0.4 < z < 0.8, we measure the number density of quiescent LRGs, finding that recently quenched galaxies constitute a growing fraction of the massive galaxy population with increasing look-back time. Finally, we quantify the importance of this population among massive ( $\mathrm{log}({M}_{\star }/{M}_{\odot })$ > 11.2) LRGs by measuring the fraction of stellar mass each galaxy formed in the gigayear before observation, f _1 Gyr . Although galaxies with f _1 Gyr > 0.1 are rare at z ∼ 0.4 (≲0.5% of the population), by z ∼ 0.8, they constitute ∼3% of massive galaxies. Relaxing this threshold, we find that galaxies with f _1 Gyr > 5% constitute ∼10% of the massive galaxy population at z ∼ 0.8. We also identify a small but significant sample of galaxies at z = 1.1–1.3 that formed with f _1 Gyr > 50%, implying that they may be analogs to high-redshift quiescent galaxies that formed on similar timescales. Future analysis of this unprecedented sample promises to illuminate the physical mechanisms that drive the quenching of massive galaxies after cosmic noon.

This study investigates the effect of nano-ZnO on modified asphalt’s adhesion characteristics by preparing various mixtures with 0%, 1%, 2%, and 3% nano-ZnO contents. Within the study context, the adhesion characteristics of asphalt mixtures with different nano-ZnO to limestone, basalt, and granite contents are studied using a boiling test. The surface-free energy (SFE) parameters of four asphalt and three aggregate types are evaluated using a theoretical approach and then verified by performing pull-off tests, and the adhesion work between different asphalt and aggregates is calculated. In addition, the effect of nano-ZnO on moisture-sensitive properties of the asphalt mixture is assessed using a freeze-thaw split test and semicircle bending (SCB) test. The study results have shown that nano-ZnO can enhance adhesion characteristics of the asphalt. The surface energy of modified asphalt with high ZnO content is relatively larger, and the adhesion between asphalt and limestone is better than the basalt and granite. The aggregates’ chemical composition and the SFE’s parameters significantly affect the adhesion between asphalt and aggregates. Furthermore, the correlation between the surface-free energy theory and the pull-off test results is better than the boiling test ones. Nano-ZnO enhances the asphalt mixture’s moisture sensitivity before and after freeze-thaw cycles and impacts the initial state’s tensile strength and cracks resistance, especially after freeze-thaw cycles where the improvement is obvious.

Fishing closures, commonly used to manage fisheries’ catch, involve temporarily closing a body of water to particular fishing gears to control fishing effort and protect feeding and spawning areas. In recent years in Qiantang River of China, with the socio-economic development, protection of fish stock has become increasingly urgent. The year 2019 was the first year that Qiantang River was included in the unified fishing ban system for the south of Yangtze River basin. Here, fish captures and hydroacoustic surveys were carried out in the research area of Qiantang River in order to present comparative descriptions of the dominant fish species, the temporal changes of fish size, density, biomass, and distribution affected by the four-month fishing closure in 2019. The results showed that Pseudobrama simoni (Bleeker, 1864) was the most dominant species both before and after the closure by using the traditional capture method. The mean target strength (TS) of overall fish after closure was –50.28 ± 0.19 dB, which was lower than that before, resulting in a significantly shorter derived mean length (13.42 ± 0.74 cm). The mean fish density and calculated biomass after closure were both significantly higher than that before it. More than 50% of fish species were distributed in the water of 5–20 m depth after the closure, which likely occurred in water deeper than 20 m before. Meanwhile, fewer outliers were found in different depth categories after closure. It is concluded that the four-month closure in 2019 had a positive effect on fish size, density, and biomass, leading to protection of pelagic fishes and a more even distribution of fish.

Environmental sustainability is essential in tourism literature, and sun-and-beach tourism (SBT) is one of the most popular subsections of the tourism field. The appropriate policies and strategies during the COVID-19 pandemic to revive SBT growth through the lens of the regulatory dimension (RED) and risk dimension (RID) of environmental sustainability are gaining timely ground to conduct this research. The current study examined the nexus between SBT, RED, and RID utilizing three novel indexes (i.e., weighted sun-and-beach tourism index, weighted regulatory dimension index, and weighted risk dimension index) by employing the principal component analysis within the framework of six stages of empirical estimation strategy. These three novel indexes combine the most commonly used SBT, RED, and RID indicators. This research tested the CSD and homogeneous, then employed the second generation CIPS-CADF panel unit root test, used an AMG estimator, and employed the panel Toda-Yamamoto (PTY) causality test. The findings revealed that the RED positively influences SBT while the RID mitigates SBT. Results also indicate bidirectional causality between SBT, RID, and RED. In other words, changes in RID and RED have predictive power for the SBT, which further highlights the role of SBT on the RID and RED. Therefore, concerned authorities can focus on environmental sustainability design initiatives and appropriate policy/strategy implications to boost SBT.

This study analyzes the different impacts of autoconversion of cloud droplets to raindrops (ACR) in a Meiyu front rainfall event by comparing two simulations using different parameterizations (KK00 and LD04) in the Weather Research and Forecasting (WRF) model. The Meiyu frontal clouds are further classified into stratiform and deep-convective cloud categories, and the precipitation and microphysical characteristics of the two simulations are compared with a budget analysis of raindrops. The simulated precipitation, radar composite reflectivity distribution, and rain rate evolution are overall consistent with observations while precipitation is overestimated, especially in the rainfall centers. The intensity and vertical structure of the ACR process between the two simulations are significantly different. The ACR rate in LD04 is larger than that in KK00 and there are two peak heights in LD04 but only one in KK00. Accretion of droplets by raindrops (CLcr), melting of ice-phase particles (ML), evaporation of raindrops (VDrv), and accretion of raindrops by ice-phase particles (CLri) are the dominant pathways to raindrop production. Limited distributional differences can be found in both the deep-convective and stratiform clouds between the two simulations during the growth stage of the Meiyu event. Stronger ACR in LD04 results in less cloud droplet content (Lc), more raindrop content (Lr), and larger raindrop number concentration (Nr) and the effect of ACR on Nr is greater than that on Lr. The ACR process also impacts other microphysical processes indirectly, and the influences vary in the two cloud categories. Less CLcr (especially), ML, and VDrv content, caused by stronger ACR, lead to less raindrop production in the LD04 deep-convective clouds, which is different from stratiform clouds, and finally correct the overestimated rainfall center to better match the observations.

As important man-made targets, bridges have been a major focus of Synthetic Aperture Radar (SAR) image interpretation, and many researchers have developed methods for bridge detection. The core frameworks of these methods are analogical, a river is first extracted, and a water bridge is detected based on the positional relationship between the river and bridge. However, existing bridge detection methods relying on river extraction; cannot be utilized detect land bridges. This is because the background environment under a bridge is land, not river, which has different scattering characteristics and shape layouts. As such, the traditional method for extracting rivers is not suitable for extracting land background, and it is impossible to locate a bridge based on prior knowledge of its location of. To resolve this problem, in this study, we propose a land bridge detection method based on polarized Circular SAR (CSAR) images. In our proposed method, the Circular Polarization Entropy (CPE) of an observed scene is introduced to separate possible bridge targets from a land background (In our experiment, the average CPE of the bridge is 0.4018, and that of the land background is 0.7819; thus there is a clear difference between the bridge and background). False targets are removed based on the difference in the polarization entropy variance features of the bridges and other ground objects; and the size characteristics of the bridges. Finally, accurate extractions of land bridges are obtained based on the geometric characteristics of the bridges. Experimental results based on real airborne L-band polarized CSAR data verify the correctness of the theoretical analysis and effectiveness of the proposed method.

The tourist experience is a core indicator of destination management for the comprehensive evaluation of destination value. Tourist experience and tourist inspiration are important concepts in the stream of research on destination marketing and management. However, these relationships remained under-explored in the extant literature. This study examined the impact of tourist experience on tourist inspiration under the moderating impact of destination familiarity. To achieve the objective of this study, data were collected online from 622 Chinese tourists. We employed partial least squares structural equation modeling (PLS-SEM) to statistically analyze the gathered data. Findings show that four types of tourist experiences, namely education, esthetics, entertainment, and escapism, significantly and positively influenced the inspired-by state of tourist inspiration, which further influenced the inspired-to-state of tourist inspiration. Destination familiarity exerted a significantly negative moderating impact on the relationship between education experience and inspired-by state of tourist inspiration. Sensitivity analysis presents that education experience was the strongest predictor of the inspired-by state followed by aesthetics, escapism, and entertainment facets of the tourist experience. Findings contribute to the theory and practice of tourism management with a robust interpretation of tourist experience, tourist inspiration, and destination familiarity to solidify the effective management of tourist destinations. Limitations and future research directions are noted.

Although online communities with a supportive climate encourage members to participate and exchange their information openly and freely, participants may perceive the community to be unsafe without proper control. Do controlling climates also contribute to the accumulation of social capital in online brand communities (OBCs)? The purpose of our study was to investigate how controlling and supportive climates jointly influence community identification, and to examine the mediating effects of social capital and the moderating effects of community age. A conceptual framework was proposed and tested with data collected from an online survey of 481 online brand community members. We found that both controlling and supportive climates had positive effects on social capital (trust and norms of reciprocity), which exerted a partial mediation between community climate and community identification in the OBCs examined. Developing a community climate was particularly effective in generating trust in older communities. This research contributes to the community literature and has important implications for community climate management. We identified the boundary conditions of the community climate-trust association.

The buckling response of functionally graded (FG) porous spherical caps reinforced by graphene platelets (GPLs) is assessed here, including both symmetric and uniform porosity patterns in the metal matrix, together with five different GPL distributions. The Halpin–Tsai model is here applied, together with an extended rule of mixture to determine the elastic properties and mass density of the selected shells, respectively. The equilibrium equations of the pre-buckling state are here determined according to a linear three-dimensional (3D) elasticity basics and principle of virtual work, whose solution is determined from classical finite elements. The buckling load is, thus, obtained based on the nonlinear Green strain field and generalized geometric stiffness concept. A large parametric investigation studies the sensitivity of the natural frequencies of FG porous spherical caps reinforced by GPLs to different parameters, namely, the porosity coefficients and distributions, together with different polar angles and stiffness coefficients of the elastic foundation, but also different GPL patterns and weight fractions of graphene nanofillers. Results denote that the maximum and minimum buckling loads are reached for GPL-X and GPL-O distributions, respectively. Additionally, the difference between the maximum and minimum critical buckling loads for different porosity distributions is approximately equal to 90%, which belong to symmetric distributions. It is also found that a high weight fraction of GPLs and a high porosity coefficient yield the highest and lowest effects of the structure on the buckling loads of the structure for an amount of 100% and 12.5%, respectively.

Recent upgrades to China’s radar network now allow for polarimetric measurements of convective systems in central China, providing an effective data set with which to evaluate the microphysics schemes employed in local squall line simulations. We compared polarimetric radar variables derived by Weather Research and Forecasting (WRF) and radar forward models and the corresponding hydrometeor species with radar observations and retrievals for a severe squall line observed over central China on 16 March 2022. Two microphysics schemes were tested and were able to accurately depict the contrast between convective and stratiform regions in terms of the drop size distribution (DSD) and reproduce the classical polarimetric signatures of the observed differential reflectivity (ZDR) and specific differential phase (KDP) columns. However, for the convective region, the simulated DSDs in both schemes exhibited lower proportions of large drops and lower liquid water content; by contrast, for the stratiform region, the proportion of large drops was found to be too high in the Morrison (MORR) scheme. The underprediction of ice-phase processes in the convective region, particularly the riming processes associated with graupel and hail, was likely responsible for the bias toward large raindrops at low levels. In the stratiform region, raindrop evaporation in the WRF Double-Moment 6-Class (WDM6) scheme, which partially offsets the overestimation of ice-phase processes, produced ground DSDs that more closely matched the observational data, and did not exhibit the overly strong warm-rain collisional growth processes of MORR.

Monopulse technique is used in scanning radar systems to improve image quality in the forward-looking area. However, monopulse measurements fail to resolve multiple targets in the same resolution cell because of angular glint which often results to image blurring. In response to this, we propose a monopulse forward-looking imaging method utilizing Doppler estimates of sum-difference measurements. First, target multiplicity is resolved by exploiting the different Doppler shifts caused by the relative motion between the platform and the targets at different directions. High azimuthal angle measurement accuracy of the Doppler estimates is then obtained using the Sum-Difference Amplitude-Comparison (SDAC) monopulse technique. Subsequently, the intensity of the sum channel estimates is projected onto the image plane according to the range and angle measurements. To further improve the precision of angle measurements, a Chirp-Z Transform (CZT)-based algorithm is proposed for the reconstruction of the Doppler estimates of the sum-difference channels. Simulation results demonstrate the capability of the proposed methods in resolving multiple targets at high squint angles in a large scanning field. Real data experiments show significant improvement of image profiles using the CZT-based algorithm compared to that of the conventional monopulse imaging method.

The polar format algorithm (PFA) is a frequency-domain algorithm with high computational efficiency especially for the high resolution imaging applications in wide-angle staring synthetic aperture radar (WAS-SAR). Because of the image distortion and defocus caused by plane wave assumption, the effective imaging scene is limited to a small region which is defined as the defocus-negligible region. In this article, a novel sub-block imaging algorithm which first applied to WAS-SAR is proposed. This method combines sub-block imaging and spatially variant post-filtering (SVPF) which can not only effectively extend the depth of focus of PFA but also greatly reduces the computational burden. What's more, the method of mosaic image is proposed in this article which can eliminate discontinuity between adjacent sub-blocks. First, the large scene is segmented into multiple regions along range direction and the size of each region is still larger than that of the defocus-negligible region. Second, refocusing is implemented by a phase compensation of the already de-chirped signal with the center of sub-blocks, respectively, and each sub-block image is formed by PFA. Third, the region in each sub-block that exceeds the defocus-negligible region is corrected by SVPF and the image distortion can be corrected by 2-D interpolation. Finally, the mosaic image method is applied to get the large-scene image with high quality. The algorithm proposed in this article is efficient and solves the problems in the process of SAR image mosaic such as dislocation and grayscale differences. The simulated and experimental data results demonstrate the effectiveness and practicability of the proposed algorithm.

Circular synthetic sperture radar (CSAR) can observe the target in 360° and obtain the target's total scattering information. By dividing the CSAR imaging data into subapertures, the target digital elevation model (DEM) information can be directly obtained. Aiming at the problems existing in the division and selection of subapertures when acquiring DEM, this article proposes a chain correlation method. First, the echo data of the full aperture is divided into multiple subapertures; then, the correlation between the two adjacent subapertures is used to perform correlation processing on the subaperture image, and then the DEM information is obtained. The chain correlation method proposed in this article takes advantage of the stronger correlation between adjacent subapertures, improves the accuracy of the algorithm, and effectively improves the overall efficiency of the algorithm. Finally, the effectiveness and reliability of the proposed method is verified by different measured data, and it is the first time our own collected Ku-band experimental data are used.

Laccase, a multicopper oxidase, is well known for its industrial potentials to remove environmental pollutants due to its low substrate specificity to oxidize phenols and thus catalytic versatility. Many efforts focused on the metabolic mechanism, yet to decipher the structural determinants responsible for the differentiation between substrates. Aflatoxin B1 (AFB1), a new substrate for laccase, is a mycotoxin with a formidable environmental threat to public health and food safety. In the present study, we combined biochemical, in silico mutational and molecular-docking data to gain an insight to the function of key residues in the active cavity close to the T1 copper site in a characterized recombinant laccase from Cerrena unicolor (rCuL). Kinetic data for computer-assisted virtual mutants established the binding affinity of hydrogen bonds and residues (Asn336, Asp207, Val391, and Thr165) in rCuL to AFB1. The augmented binding affinity to AFB1 may be related to the conformational rearrangements of the laccase and its ability to hydrogen-bond with the substrate. Furthermore, the optimal pH and temperature for rCuL and variants mediated AFB1 degradation may depend on their pH stability and thermostability. Our findings reinforce the importance of the structure-function relationship of fungal laccases in degrading AFB1, providing mechanistic guidance for future biocatalyst and bioengineering applications.

In this paper, the rainstorm event on 4 July 2018 in central China was simulated using YHGS model product driven WRF, and the application capability of YHGS model product in this forecast was evaluated by comparing to the initial field simulation results with ERA-interim data. The conclusions are as follows. (1) WRF-YHGS has a certain ability to forecast the rainstorm in central China on 4 July 2018. The simulated large-scale circulation situation and the variation trend of water vapor budget are in good agreement with WRF-ERA. YHGS model product driven mesoscale numerical prediction is feasible. (2) The simulated skill of WRF-YHGS is worse than WRF-ERA, but WRF-ERA wet deviation of heavy rain is larger. There is a certain gap between the simulation results of each physical quantity in the two tests, and the difference gradually increases with the increase of integration time. (3) The difference between WRF-YHGS and WRF-ERA simulation results mainly comes from two aspects: the subsynoptic-scale motion between YHGS and ERA in the initial field and the prediction field error of YHGS global model.

In this study, forecast error is devived into two components, i.e., systematic forecast error and non-systematic forecast error. After the correction of systematic forecast error, variational method is used to estimate and correct the non-systematic forecast error by building the mapping relationship between the state variable and non-systematic forecast error. The mapping relationship can be built by two schemes. One is by using the historical samples of the same period (DEM), and the other is by using "similarity samples"(SEM). The hind-cast data of 48 h forecast of 500 hPa height field generated by GRAPES model in July from 2002 to 2010 is used to test the effectiveness of the above two methods. The analysis data from NCEP-FNL is used as validation data to assess the result of the methods. The result shows that the correction efficiency is 98.566% for DEM and 100% for SEM. Both the DEM method and SEM method has certain capability to esti-mate the non-systematic forecast error.