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Steganography technology which conceals a message in a carrier to make it invisible is critical for information security. Conventional optical image steganography using diffractive optical components or spatial light modulators suffers from less encoding channel and bulky volume. The emergence of multifunctional metasurface that can manipulate abundant physical dimensions of optical fields allows the multi‐channel image steganography in a compact volume. Here, the image hiding in a metasurface is demonstrated by modulating the amplitude, phase, and polarization states of terahertz (THz) waves completely. Especially, the phase channel can decouple from the amplitude channel based on a Fresnel‐diffraction‐based algorithm. By directly measuring the phase distribution using the homemade THz focal plane imaging system, the number of transmission channels can expand from N to 2N. As a proof of concept, it is shown that the secret images can encode in the phase channel and subsequently extract by using different keys, such as polarization states, detection distances, and its combinations. Moreover, different hiding strategies with different attacker behaviors are also demonstrated. The decoupling of the phase and amplitude channels with a single metasurface may open an avenue toward innovative optoelectronic devices for optical image steganography, data storage, and terahertz communication. [ABSTRACT FROM AUTHOR]

The original K-means algorithm is widely applied for clustering in Euclidean spaces. Nevertheless, due to the non-flat characteristics of the Riemannian manifold, standard Euclidean K-means algorithms yield inferior results on such data. To address this issue, this paper presents an intrinsic K-means clustering algorithm on homogeneous manifolds based on the geodesic distance. It allows the development of K-means-based methods for frequently occurring non-vector spaces in robotics, such as directional vector modelling S 2 and pose estimation S 3 . First, the Riemannian metric of the homogeneous manifold is delivered; on this basis, the intrinsic K-means is proposed using Karcher mean, and its convergence is proved. Then, differences between the proposed algorithm and four projection-based algorithms, such as embedding projection, stereographic projection, central projection and logarithmic projection, are discussed by investigating their distance preservation on manifolds. Finally, to evaluate the effectiveness of the proposed algorithm, it is compared with the projection-based algorithms on S n . The results show that the intrinsic K-means achieves better clustering results, where the clustering accuracy of the proposed method is improved by 47% and 27% on average on artificial S 2 and S 3 datasets, respectively. Meanwhile, the noise immunity of the proposed algorithm becomes more evident with the noise ratio increase. [ABSTRACT FROM AUTHOR]

Plants play an important role in maintaining the ecological balance of the biosphere, but often suffer from pathogenic fungi during growth. During our continuing mycological surveys of plant pathogens from terrestrial plants in Jiangxi and Yunnan provinces, China, 24 strains of Pestalotiopsis isolated from diseased and healthy tissues of plant leaves represented eight new species, viz. P. alpinicola, P. camelliicola, P. cyclosora, P. eriobotryae, P. gardeniae, P. hederae, P. machiliana and P. mangifericola. Multi-locus (ITS , tef1-α and tub2) phylogenetic analyses were performed using maximum-likelihood and Bayesian inference to reveal their taxonomic placement within Pestalotiopsis. Both molecular phylogenetic analyses and morphological comparisons supported them as eight independent taxa within Pestalotiopsis. Illustrations and descriptions of these eight taxa were provided, in conjunction with comparisons with closely related taxa in the genus. This work highlights the large potential for new fungal species associated with diseased plant leaves. [ABSTRACT FROM AUTHOR]

Increasingly severe crises, such as climate change, water scarcity and environmental pollution, pose significant challenges to global food security and sustainable agricultural development. For efficient and sustainable tomato cultivation management under resource constraints, quantitatively describing the relationship between yield-quality harvest and water-nitrogen application is practically beneficial. Two successive greenhouse experiments with three irrigation levels (1/3 FI, 2/3 FI, and full irrigation (FI)) and four nitrogen fertilizer treatments (0 FN, 1/3 FN, 2/3 FN, and full nitrogen (FN)) were conducted on tomatoes during the whole phenological stage. The tomato evapotranspiration and nitrogen application amount, yield, comprehensive quality, solid–acid ratio, and lycopene content were measured. Based on crop water production functions, three equation forms of water-nitrogen production functions containing 20 models were established and evaluated to predict tomato harvest parameters. The results show that water increased tomato yield while decreasing fruit quality, and the effect of nitrogen was primarily contrary. Water most significantly impacted tomato formation, and the interaction of water and nitrogen changed among different harvest parameters. Tomato yield and quality formation was more sensitive to water and nitrogen at the flowering and fruit maturation stages. Model Singh-2 outweighed other models for yield estimates, with an R2 of 0.71 and an RMSE of 0.11. Singh-Log, Singh-sigmoid and Rao-Root models were effective models for comprehensive quality, solid–acid ratio, and lycopene content prediction, with an R2 of 0.41, 0.62, and 0.42, and an RMSE of 0.33, 0.50, and 0.16, respectively. Finally, models in the form of f(ETi)·f(N) were ideal for tomato harvest prevision and are recommended for water and nitrogen management in tomato cultivation. [ABSTRACT FROM AUTHOR]

High-resolution temperature forecasting plays a crucial role in various applications such as climate impact assessment, hydrological modeling, and localized weather forecasting. The existing low-resolution forecast data may not accurately capture the fine-grained temperature patterns required for localized predictions. These forecasts may contain biases that need to be corrected for accurate results. Therefore, there is a need for an effective framework that can downscale low-resolution forecast data and correct biases to generate high-resolution temperature forecasts. The paper proposes a machine learning-based spatial downscaling and bias-correction framework for high-resolution temperature forecasting. The framework utilizes low-resolution forecast data from the European Centre for Medium-Range Weather Forecasts and real-time 1km analysis product data from the National Meteorological Administration, to generate high-resolution 1km forecast temperature data. The framework consists of four modules: data acquisition module, data preprocessing module, downscaling and correction model module, and post-processing and visualization module. Through experiments, it demonstrated that the framework has superior performance and potential in meteorological data downscaling and correction and can be used to achieve real-time high-resolution temperature forecasting, which has important significance for various applications such as climate impact assessment, hydrological modeling, and localized weather forecasting. [ABSTRACT FROM AUTHOR]

Due to the high structural flexibility and controllable thermal expansion, cubic double ReO3-type negative thermal expansion (NTE) fluorides provide a solution for solving the prominent phenomenon of thermal expansion mismatch between materials. However, the expensive raw materials and complex synthesis steps limit its practical application. In this work, we have designed a more advantageous method for the synthesis of NTE material CaZrF6, and it is expected to be generalized to the synthesis of other double ReO3-fluorides. Intriguingly, a new orthorhombic phase CaZrF6 has been synthesized via this method in a lower temperature. Unlike the strong isotropic NTE of the cubic phase CaZrF6, the orthorhombic phase shows the strong anisotropic positive thermal expansion (PTE). The combined analysis of temperature-dependent X-ray diffraction (XRD), Raman spectra, and first-principles calculations shows that the low frequency phonon vibration mode with negative Grüneisen parameter in cubic CaZrF6 are strongly correlated with the transverse thermal vibration of F atoms and dominates the NTE of the material. [ABSTRACT FROM AUTHOR]

Siraitia siamensis is a traditional Chinese medicinal herb. In this study, using S. siamensis cultivated in vitro, twelve candidate reference genes under various treatments were analyzed for their expression stability by using algorithms such as GeNorm, NormFinder, BestKeeper, Delta CT, and RefFinder. The selected reference genes were then used to characterize the gene expression of cucurbitadienol synthase, which is a rate-limiting enzyme for mogroside biosynthesis. The results showed that CDC6 and NCBP2 expression was the most stable across all treatments and are the best reference genes under the tested conditions. Utilizing the validated reference genes, we analyzed the expression profiles of genes related to the synthesis pathway of mogroside in S. siamensis in response to a range of abiotic stresses. The findings of this study provide clear standards for gene expression normalization in Siraitia plants and exploring the rationale behind differential gene expression related to mogroside synthesis pathways. [ABSTRACT FROM AUTHOR]

Background: Post-stroke depression (PSD) is closely associated with poor stroke prognosis. However, there are some challenges in identifying and assessing PSD. This study aimed to identify scales for PSD diagnosis, assessment, and follow-up that are straightforward, accurate, efficient, and reproducible. Methods: A systematic literature search was conducted in 7 electronic databases from January 1985 to December 2023. Results: Thirty-two studies were included, the Patient Health Questionnaire-9 (PHQ-9) and Hamilton Depression Scale (HDRS) had higher diagnostic accuracy for PSD. The sensitivity, specificity, and diagnostic odds ratio of PHQ-9 or diagnosing any depression were 0.82, 0.87, and 29 respectively. And for HDRS, used for diagnosing major depression, the scores were 0.92, 0.89, and 94. Furthermore, these two scales also had higher diagnostic accuracy in assessing depressive symptoms during both the acute and chronic phases of stroke. In patients with post-stroke aphasia and cognitive impairment, highly diagnostic scales have not been identified for assessing depressive symptoms yet. Conclusions: The PHQ-9 and HDRS scales are recommended to assess PSD. HDRS, which demonstrates high diagnostic performance, can replace structured interviews based on diagnostic criteria. [ABSTRACT FROM AUTHOR]

Conventional fracturing design generally only considers the propagation of a single fracture in homogeneous storage, but the heterogeneity characteristics of the reservoir and the development of complex natural fractures will affect the fracturing effect. In order to study the horizontal well fracture propagation law under the synergistic effect of complex natural fracture reservoir heterogeneity, the globally embedded cohesive element finite model is established, and the heterogeneous reservoirs are built by Python programming. The influencing factors of multi-fracture propagation with heterogeneous reservoirs are analyzed, including the in situ stress difference, the injection rate of fracturing fluid, the perforation spacing, and the perforating clusters number. The results show that the heterogeneity and the natural fracture of the reservoir will affect the in situ stress distribution and propagation direction. When the in situ stress difference is low, the reservoir heterogeneity and natural fractures have a great influence on the fracture morphology. With the increase in injection rate, the fracture length and fracture width increase. With the in situ stress difference increase, the fracture deflection angle decreases. With the increase in fracturing fluid injection rate, the fracture length increases. The number of hydraulic fractures communicating with natural fractures increases with the natural fracture number and the number of perforation clusters under the synergistic effect of complex natural fracture and reservoir heterogeneity. [ABSTRACT FROM AUTHOR]

This study investigated the association between serum albumin concentration and 12-weeks mortality of HIV/AIDS with late diagnosis in China. This retrospective cohort study included, 1079 inpatients diagnosis with late HIV/AIDS between January 2018 and December 2021. Disease progression was estimated based on the 12-weeks mortality rate. Cox proportional hazards regression models were used to evaluate the relationship between serum albumin levels and disease progression. The effects of serum albumin levels on mortality was estimated via Kaplan–Meier curves. The mortality risk decreased by 7% with every 1 g/L increase in serum albumin after adjustment ([HR] = 0.93, 95% CI: 0.88–0.97). Compared with that of the low (< 28 g/L) serum albumin group, the middle (28–34 g/L) group's mortality risk decreased by 70% (HR = 0.30, 95% CI: 0.15–0.59), and that of the high (≥ 34 g/L) group decreased by 40% (HR = 0.6, 95% CI: 0.29–1.23) after adjustment. Our findings suggest a positive correlation between the increase in serum albumin levels upon admission and a decrease in mortality at 12 weeks post-discharge among patients with late AIDS/HIV diagnosis. Further research is needed to characterize the role of serum albumin in 12-weeks mortality prevention in patients with a late diagnosis. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing technology is an effective way to develop tight sandstone reservoirs with low porosity and permeability. The tight sandstone reservoir is heterogeneous and the heterogeneity characteristics has an important influence on fracture propagation. To investigate hydraulic fracture performance in heterogeneous tight reservoir, the X-ray diffraction experiments are carried out, the Weibull distribution method and finite element method are applied to establish the uniaxial compression model and the hydraulic fracture propagation model of heterogeneous tight sandstone. Meanwhile, the sensitivity of different heterogeneity characterization factors and the multi-fracture propagation mechanism during hydraulic fracture propagation is analyzed. The results indicate that the pressure transfer in the heterogeneous reservoir is non-uniform, showing a multi-point initiation fracture mode. For different heterogeneity characterization factors, the heterogeneity characteristics based on elastic modulus are the most sensitive. The multi-fracture propagation of heterogeneous tight sandstone reservoir is different from that of homogeneous reservoir, the fracture propagation morphology is more complex. With the increase of stress difference, the fracture propagation length increases. With the increase of injection rate, the fracture propagation length increases. With the increase of cluster spacing, the propagation length of multiple fractures tends to propagate evenly. This study clarifies the influence of heterogeneity on fracture propagation and provides some guidance for fracturing optimization of tight sandstone reservoirs. [ABSTRACT FROM AUTHOR]

In order to improve the surface flashover strength of the insulation materials and solve the problem that the relatively high price of CF4 restricts the large-scale application of fluorination modification of CF4 atmospheric pressure plasma jet (APPJ) in the industrial field, He/CF4/O2 APPJ with different O2 content is used to treat epoxy resin (EP) dielectric material. By analyzing the results of scanning electron microscopy, atomic force microscopy, and x-ray photoelectron spectroscopy, the influence of O2 content on the multiple characteristics of EP surface before and after APPJ treatment is studied. Flashover experiment is also carried out on EP surface before and after APPJ treatment. It is found that the addition of 0.1% O2 can increase the mature voltage of the EP surface by about 16.10% compared with untreated EP surface. It is concluded that the improvement of the surface flashover strength with a small amount of O2 (within 0.1%) is influenced by the surface roughness and chemical composition of the dielectric. The deposition effect of APPJ on EP surface is enhanced to increase the surface roughness and reaches the best at 0.1% O2, because the addition of excessive O2 will weaken the APPJ intensity. It is speculated that the creepage distance of the EP surface is increased to inhibit the formation of electron collapse and the content of electronegative fluorine and oxygen on the EP surface is increased under a small amount of O2 addition, resulting in the inhibition of the formation of surface flashover. [ABSTRACT FROM AUTHOR]

Multi-wavelength ghost imaging usually involves extensive data processing and faces challenges such as poor reconstructed image quality. In this paper, we propose a multi-wavelength computational ghost imaging method based on feature dimensionality reduction. This method not only reconstructs high-quality color images with fewer measurements but also achieves low-complexity computation and storage. First, we utilize singular value decomposition to optimize the multi-scale measurement matrices of red, green, and blue components as illumination speckles. Subsequently, each component image of the target object is reconstructed using the second-order correlation function. Next, we apply principal component analysis to perform feature dimensionality reduction on these reconstructed images. Finally, we successfully recover a high-quality color reconstructed image. Simulation and experimental results show that our method not only improves the quality of the reconstructed images but also effectively reduces the computational and storage burden. When extended to multiple wavelengths, our method demonstrates greater advantages, making it more feasible to handle large-scale data. [ABSTRACT FROM AUTHOR]

This study investigates how dynamic fluctuations in matrix stiffness affect the behavior of cardiac fibroblasts (CFs) within a three-dimensional (3D) hydrogel environment. Using hybrid hydrogels with tunable stiffness, we created an in vitro model to mimic the varying stiffness of the cardiac microenvironment. By manipulating hydrogel stiffness, we examined CF responses, particularly the expression of α-smooth muscle actin (α-SMA), a marker of myofibroblast differentiation. Our findings reveal that increased matrix stiffness promotes the differentiation of CFs into myofibroblasts, while matrix softening reverses this process. Additionally, we identified the role of focal adhesions and integrin β1 in mediating stiffness-induced phenotypic switching. This study provides significant insights into the mechanobiology of cardiac fibrosis and suggests that modulating matrix stiffness could be a potential therapeutic strategy for treating cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Introduction: Robotics uptake in the aerospace industry is low, mainly due to the low-volume/high-accuracy production that aerospace manufacturers require. Furthermore, aerospace manufacturing and assembly sites are often unstructured environments not specifically suitable for robots to operate in. Methods: This paper introduces a robotic visual inspection system using off-the-shelf components able to inspect the mounting holes for wing slat actuators without the need for fixed-coordinate programming; the part just needs to be left within reach of the robot. Our system sets one of the opposed pairs of mounting holes as a reference (the "datum") and then compares the tilt of all other pairs of mounting holes with respect to it. Under the assumption that any deviation in the mounting hole tilt is not systematic but due to normal manufacturing tolerances, our system will either guarantee the correct alignment of all mounting holes or highlight the existence of misaligned holes. Results and Discussion: Computer-vision tilt measurements are performed with an error of below 0.03° using custom optimization for the sub-pixel determination of the center and radius of the mounting holes. The error introduced by the robot's motion from the datum to each of the remaining hole pairs is compensated by moving back to the datum and fixing the orientation again before moving to inspect the next hole pair. This error is estimated to be approximately 0.05°, taking the total tilt error estimation for any mounting hole pair to be 0.08° with respect to the datum. This is confirmed by manually measuring the tilt of the hole pairs using a clock gauge on a calibrated table (not used during normal operation). [ABSTRACT FROM AUTHOR]

Objective: To determine and compare the serum metabolites in missed abortion versus normal early pregnancy using ultra‐high‐performance liquid chromatography and tandem time‐of‐flight mass spectrometry, and to determine how these metabolites can be used to predict the potential biomarkers and possible metabolic pathways of a missed abortion. Methods: The serum of patients with a missed abortion was used as the experimental group and the serum of patients with an induced abortion during normal early pregnancy was used as the control group. Principal component analysis and orthogonal partial least square discriminant analysis were additionally used to observe the difference in metabolite distribution between the two groups. A variable weight value (variable importance in the projection; VIP) obtained from the orthogonal partial least squares discriminant analysis model more than 1 and P less than 0.05 were taken to indicate significant differences in metabolite screening. After this, enrichment analysis of the metabolic pathways of these metabolites was conducted using Fisher precise test in order to find the metabolic pathway with the highest correlation with the differential metabolites. Results: In total, 30 patients were included in the experimental group, with 30 patients in the control group. Fifty‐five metabolites (VIP > 1, P < 0.05) with significant differences related to missed abortion were selected, among which 35 metabolites increased and 20 decreased in patients with a missed abortion. KEGG pathway enrichment analysis showed that the four metabolic pathways with the highest correlation were cholesterol metabolism, arginine biosynthesis, cell apoptosis, and the FoxO signaling pathway. Conclusion: The missed abortion serum metabolites and changes in related metabolic pathways reported in this study provide a basis for the early prediction and diagnosis of a missed abortion. Synopsis: Serum metabolites and changes in related metabolic pathways provide a basis for the early prediction and diagnosis of a missed abortion. [ABSTRACT FROM AUTHOR]

Semitransparent organic solar cells show attractive potential in the application of building‐integrated photovoltaics, agrivoltaics, floating photovoltaics, and wearable electronics, as their multiple functionalities of electric power generation, photopermeability, and color tunability. Design and exploration of semitransparent organic solar cells with optimal and balanced efficiency and average visible light transmittance and simultaneously high stability are in great demand. In this work, based on a layer‐by‐layer‐processed active layer and an ultrathin metal electrode, inverted semitransparent organic solar cells (ITO/AZO/PM6/BTP‐eC9/MoO3/Au/Ag) were fabricated. Optimal and balanced efficiency and average visible light transmittance were demonstrated, and simultaneously promising thermal and light stability were achieved for the obtained devices. The power conversion efficiency of 13.78–12.29% and corresponding average visible light transmittance of 14.58–25.80% were recorded for the ST‐OSC devices with 25–15 nm thick Ag electrodes, respectively. Superior thermal and light stability with ~90% and ~85% of initial efficiency retained in 400 h under 85 °C thermal stress and AM1.5 solar illumination were demonstrated, respectively. [ABSTRACT FROM AUTHOR]

We developed a novel method based on self-supervised learning to improve the ghost imaging of occluded objects. In particular, we introduced a W-shaped neural network to preprocess the input image and enhance the overall quality and efficiency of the reconstruction method. We verified the superiority of our W-shaped self-supervised computational ghost imaging (WSCGI) method through numerical simulations and experimental validations. Our results underscore the potential of self-supervised learning in advancing ghost imaging. [ABSTRACT FROM AUTHOR]