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Introduction: A portable spirometer is a promising alternative to a traditional pulmonary function test (PFT) spirometer for respiratory function evaluation. Objectives: This study aimed to investigate the accuracy of automated interpretation of the PFT measured by a portable Yue Cloud spirometer in Chinese adults. Methods: The PFT was performed to evaluate subjects prospectively enrolled at Ruijin Hospital (n = 220). A Yue Cloud spirometer and a conventional Jaeger MasterScreen device were applied to each patient with a 20‐min quiescent period between each measurement. Pulmonary function parameters, including forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), peak expiratory flow (PEF), maximal expiratory flow at 25%, 50%, and 75% of the FVC (MEF25, MEF50, and MEF75, respectively), and maximal mid‐expiratory flow (MMEF), were compared by correlation analyses and Bland–Altman methods. The Yue Cloud spirometer automatically interpreted the PFT results, and a conventional strategy was performed to interpret the PFT results obtained by the Jaeger machine. Concordance of the categorization of pulmonary dysfunction, small airway dysfunction, and severity was analyzed by the kappa (κ) statistic. Results: Significantly similar correlations of all variables measured with the two spirometers were observed (all p < 0.001). No significant bias was observed in any of the measured spirometer variables. A satisfactory concordance of pulmonary function and severity classification was observed between the automated interpretation results obtained with the Yue Cloud spirometer vs. a conventional spirometer interpretation strategy (all κ > 0.80). Conclusion: The portable Yue Cloud spirometer not only yields reliable measurements of pulmonary function but also can automatically interpret the PFT results. [ABSTRACT FROM AUTHOR]

Eriocheir sinensis is an aquatic species found distributed worldwide. It is found in the Yangtze River of China, where the commercial fishing of this valuable catadromous aquatic species has been banned. As an important member of the phylum Arthropoda, E. sinensis grows by molting over its whole lifespan. The central nervous system of Eriocheir sinensis plays an important regulatory role in molting growth. Nevertheless, there are no reports on the regulatory mechanisms of the nervous system in E. sinensis during the molting cycle. In this study, a comparative transcriptome analysis of E. sinensis thoracic ganglia at post-molt and inter-molt stages was carried out for the first time to reveal the key regulatory pathways and functional genes operating at the post-molt stage. The results indicate that pathways and regulatory genes related to carapace development, tissue regeneration, glycolysis and lipolysis and immune and anti-stress responses were significantly differentially expressed at the post-molt stage. The results of this study lay a theoretical foundation for research on the regulatory network of the E. sinensis nervous system during the post-molt developmental period. Detailed knowledge of the regulatory network involved in E. sinensis molting can be used as a basis for breeding improved E. sinensis species, recovery of the wild E. sinensis population and prosperous development of the E. sinensis artificial breeding industry. [ABSTRACT FROM AUTHOR]

This paper investigates the well‐posedness of solutions for the following quasilinear wave equation with strong damping and logarithmic nonlinearity in a bounded domain with homogeneous Dirichlet boundary: utt−Δu−div(∇u1+|∇u|2)−Δut=|u|r−2ulog|u|$u_{tt}-\Delta u-{\rm div}(\frac{\nabla u}{\sqrt {1+|\nabla u|^2}})-\Delta u_t=|u|^{r-2}u\log |u|$, where r≥2$r\ge 2$. By virtue of the classical Faedo–Galerkin method and some technical efforts, we first establish the local well‐posedness of solutions. Then we discuss the dynamical behaviors of solutions in detail: 1.When r≥2$r\ge 2$ and I(u0)>0$I(u_0)>0$, we show that the solutions exist globally with subcritical and critical initial energy, where I(u0)$I(u_0)$ denotes the Nehari functional with the initial value u0. Especially, under further suitable assumptions about the initial data, we show that the energy functional decays exponentially. 2.When r>2$r>2$ and I(u0)<0$I(u_0)<0$, we show that the solutions blow up in finite time with subcritical and critical initial energy. Moreover, by removing the restriction I(u0)<0$I(u_0)<0$, we prove that the solutions may blow up in finite time with arbitrary high initial energy. In particular, we derive the upper and lower bounds of the blow‐up time. 3.When r=2$r=2$ and I(u0)<0$I(u_0)<0$, we show that the maximal existence time of solutions can be extended to infinity and the solutions blow up at infinity with subcritical, critical, and arbitrary high initial energy. [ABSTRACT FROM AUTHOR]

We propose a multi-level critical point aggregation architecture based on a graph attention mechanism for 3D point cloud normal estimation, which can efficiently focus on locally important points during the feature extraction process. Wherein, the local feature aggregation (LFA) module and the global feature refinement (GFR) module are designed to accurately identify critical points which are geometrically closer to tangent plane for surface fitting at both local and global levels. Specifically, the LFA module captures significant local information from neighboring points with strong geometric correlations to the query point in the low-level feature space. The GFR module enhances the exploration of global geometric correlations in the high-level feature space, allowing the network to focus precisely on critical global points. To address indistinguishable features in the low-level space, we implement a stacked LFA structure. This structure transfers essential adjacent information across multiple levels, enabling deep feature aggregation layer by layer. Then the GFR module can leverage robust local geometric information and refines it into comprehensive global features. Our multi-level point-aware architecture improves the stability and accuracy of surface fitting and normal estimation, even in the presence of sharp features, high noise or anisotropic structures. Experimental results demonstrate that our method is competitive and achieves stable performance on both synthetic and real-world datasets. Code is available at https://github.com/CharlesLee96/NormalEstimation. [ABSTRACT FROM AUTHOR]

The article titled "Virtual reality of interior noises of vehicles based on boundary element and neural networks" has been retracted by the Editor-in-Chief and the publisher due to concerns about compromised editorial handling and peer review process, inappropriate references, and not being in scope of the journal or guest-edited issue. The investigation conducted by the publisher led to a loss of confidence in the results and conclusions of the article. The authors did not respond to correspondence from the publisher regarding this retraction. Springer Nature, the publisher, remains neutral in terms of jurisdictional claims and institutional affiliations. [Extracted from the article]

[Display omitted] • Nanoparticle-enhanced viscoelastic micellar dispersions produce a superstable aqueous foam free of polymers. • At higher temperatures, the entangled wormlike micelles coupled with CNCs significantly enhance the viscoelastic properties of foaming dispersions, thereby delaying the foam ageing process. • This foam's favourable stability and sand-carrying capacity make it an excellent subsurface fluid. The petroleum industry makes extensive use of aqueous foams; however, their efficacy is constrained considerably by their long-term stability. Polymers are frequently utilized to stabilize the foam stability, but potential formation damages by blocking pores cannot be ignored. In this work, wormlike micelles are employed as an alternative to traditional polymer, while cellulose nanocrystals (CNCs) are added to improve the viscoelasticity under higher temperatures. Our results confirm that CNCs-enhanced viscoelastic micellar dispersions could indeed generate the super-stable foam, which mainly contributed to their synergistic effects in the bulk rheology and interfacial properties of the continuous phase. In accordance with the long-term stability, our foams also exhibit a great sand-carrying capability, i.e., the foam containing 0.5% CNCs was able to retain the sands for over 10 h without visible settlements. Our findings advance the strategies of foam stabilization and provide a strong complement to the subsurface application of aqueous foam. [ABSTRACT FROM AUTHOR]

Heusler alloys with tunable electronic properties have promising catalytic applications. In this work, the hydrogen evolution reaction and the underlying catalytic mechanism of the full Heusler alloys Co 2 TiAl and Co 2 TiGa are investigated. The first-principles calculations indicate the Gibbs free energy difference (Δ G H ∗ ) of the active Co-site on the (001) surface is − 0.06 and − 0.07 eV for Co 2 TiAl and Co 2 TiGa, respectively, which is comparable to the benchmark Pt (− 0.09 eV). The high-efficiency HER activity can ascribe to the appropriate hybridization between the H- s and Co- d z 2 orbital. Noticeably, the HER activity is robust against to the electron (hole) doping until the hybridization between the H- s and Co- d x 2 − y 2 orbital emerges, in which the hole doping is equal or greater than 0.2 holes per a formula unit. In addition, the activation energy of the Tafel reaction at the Co-site is evaluated to be 0.37 and 0.41 eV for Co 2 TiAl and Co 2 TiGa, respectively, which is nearly half of the value of Pt (111) surface (0.85 eV). This work unveils the excellent and robust HER activity of Co 2 TiAl and Co 2 TiGa and reveals the s - d z 2 bonding is an important factor for designing the HER catalysts based on the L2 1 -type Heusler alloys. [Display omitted] • The Gibbs free energy difference of Co 2 TiAl and Co 2 TiGa is comparable to Pt. • The activation energy of Co 2 TiAl and Co 2 TiGa is nearly half of the Pt (111) surface. • The s - d z 2 hybridization promotes the HER activity while the s − d x 2 − y 2 hybridization restrains the HER activity. [ABSTRACT FROM AUTHOR]

• Improving the adaptability of combine harvester to different paddy ground conditions. • A novel proposed pose vector method (PVM) is superior to the least squares method (LSM) for trajectory arc radius online fitting. • Online predicting the trajectory errors of path tracking of crawler combine harvesters using an SVR model. • High path-tracking accuracy and stable control in different paddy ground conditions. Enhancing the adaptability of agricultural machinery to different ground conditions is paramount for advancing path-tracking accuracy and control stability. Precise online perception of the steering motion state of a crawler combine harvester is essential for adapting to different paddy ground conditions (PGCs) for path-tracking control. In this study, a novel pose vector method (PVM) was proposed for the online determination of the steering radius of a crawler combine harvester. A support vector regression (SVR) model was used to forecast the error-correction factor for the steering trajectory arc radius, and a feedforward compensation control method was designed based on the steering control model. Field steering experiments revealed that the PVM outperformed the conventional least squares method (LSM) in calculating the trajectory arc radius, particularly when dealing with sparse pose data. The relative error of the PVM was several to over 10 times lower than that of the LSM fitting. The field experiments of straight-path tracking showed that the standard deviations of the lateral deviation were 0.078 m, 0.059 m, and 0.062 m, and the standard deviations of the heading deviation were 2.622°, 1.580°, and 1.593°, respectively, for the three different PGCs of soil compaction from low to high. Compared to the conventional pure tracking algorithm, the proposed PGCs adaptive tracking control algorithm enhances the adaptability of the crawler combine harvester to PGCs. These results offer a novel method for enhancing the online perception of the motion state of a crawler combine harvester and improving the adaptive control performance under different PGCs. [ABSTRACT FROM AUTHOR]

Ti interlayer provides an effective method for Mg/Al laser welding. However, the underlying mechanism of molten pool flow behavior and metal mass transfer process remains unclear. Therefore, a 3D model of Mg/Al laser welding with Ti interlayer is established to study the influences of laser power and interlayer thickness on the molten pool dynamics and metal mass transfer process. The simulation results reveal that the mechanism of metal mixing is the molten Al flows upward, breaking the Ti interlayer and mixing with Mg to form intermetallic compounds. When Ti layer thickness is fixed, the increase in laser power results in an expansion in the recoil pressure, and more molten Al flows upward to mix with Mg. As the Ti layer thickness is increased from 0.2 mm to 0.4 mm, the ideal power interval improves from 100 W to 200 W. At the ideal power interval, the effect of preventing the molten Al from flowing upward is enhanced, and the maximum upward velocity of molten Al is decreased from 0.45 m/s to 0.19 m/s. When the Ti layer thickness is more than 0.3 mm, the large amounts of Mg–Al IMCs formation are suppressed under the ideal power interval. The investigation of elemental distributions in the molten pool of Mg/Al dissimilar metals with Ti interlayer provides new insights into the inhibition of the IMCs formation, significantly contributing to the design and optimization of welding process parameters. • A simulation model of Mg/Al dissimilar metal heat and mass transfer with Ti interlayer was developed. • The effects of laser power and Ti layer thickness on keyhole formation were investigated. • The mechanism principles of metal mixing in the molten pool are investigated. • The effects of laser power and Ti layer thickness on the formation of Mg–Al intermetallic compounds were investigated, and the simulation and experimental results were in good agreement. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ni-Co alloy nanoparticles were induced to grow on layered perovskite. • The cell renders 1.53A cm−2 at 2.0 V and 850 °C for CO 2 electrolysis. • Faradic efficiencies of the SOEC are higher than 90 % above 1.6 V. • No degradation was observed in a stability test for 32 h. It has never been more important to develop new technologies that can reduce CO 2 emissions or convert them into useful chemical products. As solid-state electrochemical devices, solid oxide electrolysis cell (SOEC) is capable of converting CO 2 efficiently and selectively into CO or, when combined with water electrolysis, producing syngas (CO and H 2). Herein, we demonstrate a novel layered perovskite oxide, reduced (La 4 Sr 4) 0.9 Ti 7.2 Ni 0.4 Co 0.4 O 26 (LSTNC-r), decorated by exsolved Ni-Co alloy nanoparticles for high-efficiency CO 2 electrolysis. The cell renders a higher activity for electrolysis of CO 2 with a current density of 1.53 A cm−2 @2.0 V and 850 °C. Faradic efficiency measurement and stability test suggest that LSTNC-r are promising fuel electrodes for high-efficient CO 2 electrolysis. [ABSTRACT FROM AUTHOR]

Automated guided vehicle technology has become a hot area of scientific research due to its increasing use in manufacturing and logistics. Its main features are programming and control, remote computer eye tracking, command receiving and execution, autonomous route planning, and autonomous driving execution of tasks, with the advantages of high intelligence and flexibility. In this work, a simple vehicle model is used to study the route planning and tracking control of automatic guided vehicles. This paper uses wireless communication to find the optimal route planning problem. Using geometric methods, we develop a model of the working environment of the mobile automatic guided vehicle and develop a route finding algorithm. Based on the kinematic model, an advanced routing controller is designed to conduct experimental simulation of two trajectories and verify the effectiveness of the trajectory tracking controller. When the time is after 2 s, the position error is almost completely zero. In the path planning, when the number of iterations is greater than 10, the path length remains constant, verifying the effectiveness of the method in this paper. [ABSTRACT FROM AUTHOR]

Image fusion effectively solves the trade-off among spatial resolution, temporal resolution, and spectral resolution of remote sensing sensors. However, most of existing methods focus on the fusion of two of the spatial, temporal, and spectral metrics of remote sensing images. The few spatial–temporal–spectral fusion (STSF) methods available are mainly for fusing Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat images, which are not suitable for the characteristics of the spaceborne hyperspectral images (HSIs) with low temporal resolution, such as Hyperion, ZY-1 02D, and PRISMA. For this purpose, we proposed a novel generalized linear spectral mixing model for STSF (GLMM-STSF). In the method, the GLMM is introduced into the STSF problem, and the temporal variations of images at different times are transferred to the endmember and abundance matrix variations of images for estimation. To the best of our knowledge, for the first time, the STSF task of remote sensing images is handled from the perspective of spectral unmixing. Compared with the existing STSF fusion methods, our method targets the task of fusing spaceborne HSI with low temporal and spatial resolutions with multispectral image (MSI) featured by high temporal and spatial resolutions. Taking the STSF of ZY-1 02D hyperspectral and Sentinel-2 multispectral real datasets as an example, comparisons with related state-of-the-art methods demonstrate that our proposed method achieves superior fusion performance. [ABSTRACT FROM AUTHOR]

Deep learning (DL) based hyperspectral images (HSIs) denoising approaches directly learn the nonlinear mapping between noisy and clean HSI pairs. They usually do not consider the physical characteristics of HSIs. This drawback makes the models lack interpretability that is key to understanding their denoising mechanism and limits their denoising ability. In this paper, we introduce a novel model-guided interpretable network for HSI denoising to tackle this problem. Fully considering the spatial redundancy, spectral low-rankness, and spectral-spatial correlations of HSIs, we first establish a subspace-based multidimensional sparse (SMDS) model under the umbrella of tensor notation. After that, the model is unfolded into an end-to-end network named SMDS-Net, whose fundamental modules are seamlessly connected with the denoising procedure and optimization of the SMDS model. This makes SMDS-Net convey clear physical meanings, i.e., learning the low-rankness and sparsity of HSIs. Finally, all key variables are obtained by discriminative training. Extensive experiments and comprehensive analysis on synthetic and real-world HSIs confirm the strong denoising ability, strong learning capability, promising generalization ability, and high interpretability of SMDS-Net against the state-of-the-art HSI denoising methods. The source code and data of this article will be made publicly available at https://github.com/bearshng/smds-net for reproducible research. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method for boundary detection in close-range hyperspectral images. This method can effectively predict the boundaries of objects of similar colour but different materials. To effectively extract the material information in the image, the spatial distribution of the spectral responses of different materials or endmembers is first estimated by hyperspectral unmixing. The resulting abundance map represents the fraction of each endmember spectra at each pixel. The abundance map is used as a supportive feature such that the spectral signature and the abundance vector for each pixel are fused to form a new spectral feature vector. Then different spectral similarity measures are adopted to construct a sparse spectral-spatial affinity matrix that characterizes the similarity between the spectral feature vectors of neighbouring pixels within a local neighborhood. After that, a spectral clustering method is adopted to produce eigenimages. Finally, the boundary map is constructed from the most informative eigenimages. We created a new HSI dataset and use it to compare the proposed method with four alternative methods, one for hyperspectral image and three for RGB image. The results exhibit that our method outperforms the alternatives and can cope with several scenarios that methods based on colour images cannot handle. [ABSTRACT FROM AUTHOR]

Underground gas storage (UGS) is usually constructed in a formation with complex geological characteristics, which makes the operation monitoring and safety management of this facility more difficult. This paper aims to develop a method for comprehensive stability evaluation of multiple salt caverns UGS with interlayers. An index system is established as the foundation of the analysis for evaluation, which includes six important factors: cavity shape, operation pressure, interlayer parameters, surrounding salt rock parameters, mechanical properties, and cavity spacing. The improved analytic hierarchy process (AHP) and entropy method are used to calculate the subjective and objective weights of each index respectively. Then the index weights are constructed in the form of combination weights. The fuzzy membership function method is applied to obtain a quantitative evaluation result. Based on the established evaluation model, the stability level of four multiple salt caverns UGSs with interlayer are successfully evaluated. The results show that the stable states of the four UGS facilities are all good. There is only a slight threat of instability in UGS2, which has the defects of too many interlayers, too large interlayer thickness and too small space between adjacent cavities. [ABSTRACT FROM AUTHOR]

Purpose: Hemophagocytic lymphohistiocytosis (HLH) is a severe disease with high mortality. The purpose of this investigation was to build models to predict 30-day death in total and subgroup HLH patients based on available and cheap laboratory parameters. Method: The research contained 431 adults HLH patients from January 2015 to September 2021 in the hospital. Logistic regression and receiver operating characteristic (ROC) were utilized to build models. Results: Results suggested that age, ferritin, lymphocyte (LY), international normalized ratio (INR), thrombin time (TT), globulin, uric acid (UA), chloride, activated partial thromboplastin time (APTT), aspartate aminotransferase (AST), triglycerides (TG), total bilirubin (TB), and indirect bilirubin (IB) were independent factors in HLH and subgroups. Then, models adapted to patients with different underlying diseases were established based on these factors. Area under curve (AUC) of these models was excellent: HLH patients: 0.838 (p < 0.001); infection-associated HLH (I-HLH) patients: 0.913 (p < 0.001); malignancy-associated HLH (M-HLH): 0.921 (p < 0.001) and 0.809 (p < 0.001) for two or more different etiologies-associated HLH (Mix-HLH patients). In addition, UA, TT, and chloride were firstly confirmed as independent factors in adult HLH. Conclusion: Four models depending on biomarkers that available and affordable in clinical practice were built. With these models, high-risk patients with different underlying diseases could be easily identified. [ABSTRACT FROM AUTHOR]

OBJECTIVE: This study aims to explore the diagnostic values of radial endobronchial ultrasound-guided transbronchial lung biopsy with distance (rEBUS-D-TBLB) measurement and with guide sheath (rEBUS-GS-TBLB) for peripheral pulmonary lesions (PPLs) with a diameter ≥3 cm by thin bronchoscope. PATIENTS AND METHODS: Six hundred and three patients with PPL (diameter ≥3 cm) were enrolled in this study. The subjects were divided into the rEBUS-D-TBLB and rEBUS-GS-TBLB groups by the random number table method. Patients were assigned to undergo rEBUS-D-TBLB or rEBUS-GS-TBLB, respectively. The histopathology, positive diagnosis rates, duration of the procedure, and postoperative adverse effects between the two groups were examined. RESULTS: A total of 569 patients were included in this study according to the inclusion and exclusion criteria, with 282 cases in the rEBUS-D-TBLB group and 287 cases in the rEBUS-GS-TBLB group. For malignant diseases, the positive diagnosis rates of PPL in the outer/inner-middle lung bands and the right-upper/-lower lung lobes by rEBUS-D-TBLB were noninferior to those of rEBUS-GS-TBLB. The duration of the procedure of rEBUS-D-TBLB was longer than that of rEBUS-GS-TBLB. There were 14 cases of hemorrhage >50 mL, 1 case of postoperative chest pain in the rEBUS-D-TBLB group, and 3 cases of hemorrhage >50 mL in the rEBUS-GS-TBLB group. CONCLUSION: REBUS-D-TBLB by thin bronchoscope has a high diagnostic value for PPL with a diameter ≥3 cm, which may be considered a useful alternative for rEBUS-GS-TBLB in the clinic. [ABSTRACT FROM AUTHOR]

Understanding the association of pyroptosis with tumor progression, prognosis and effect on immunotherapeutic response in breast cancer (BC) is limited. This study analysed forty pyroptosis-related genes to construct the pyroptosis score. Association of the pyroptosis score with the overall survival, clinical features, tumor mutation load, immune cell infiltration, and treatment sensitivity of patients with BC was analysed. Out of 983 BC samples, 304 (30.93%) had genetic alterations with the highest TP53 frequency. We identified three separate subtypes associated with pyroptosis action. These subtypes correlate with the clinicopathological characteristics, TME immune cell infiltration, and disease prognosis. Based on the expression levels of the pyroptosis genes, we divided the pyroptosis score into a high group and a low group. The immune-activated pyroptosis subtype had a higher score with a better prognosis. We also observed that the pyroptosis score correlates with the tumor mutation burden. The pyroptosis score and disease prognosis were directly proportional. A higher pyroptosis score indicated a better prognosis. Results suggest that the pyroptosis-related gene prognosis model is closely related to the immune cell infiltration of BC. The three pyroptosis subtypes associated with BC assist in accurately identifying the tumor subtype, the prognosis of immunotherapy drugs and the patient's therapeutic response. [ABSTRACT FROM AUTHOR]

Castanea henryi is a monoecious plant with a low female-to-male ratio, which limits its yield. The phytohormone cytokinin (CK) plays a crucial role in flower development, especially gynoecium development. Here, the feminizing effect of CK on the development of C. henryi was confirmed by the exogenous spraying of N-(2-chloro-4-pyridyl)-N'-phenylurea (CPPU). Spraying CPPU at 125 mg·L−1 thrice changed the male catkin into a pure female catkin, whereas at 5 mg·L−1 and 25 mg·L−1, only a part of the male catkin was transformed into a female catkin. A comparative transcriptome analysis of male catkins subjected to CPPU was performed to study the mechanism of the role of CKs in sex differentiation. Using Pearson's correlation analysis between hormone content and hormone synthesis gene expression, four key genes, LOG1, LOG3, LOG7 and KO, were identified in the CK and GA synthesis pathways. Moreover, a hub gene in the crosstalk between JA and the other hormone signaling pathways, MYC2, was identified, and 15 flowering-related genes were significantly differentially expressed after CPPU treatment. These results suggest that CK interacts with other phytohormones to determine the sex of C. henryi, and CK may directly target floral organ recognition genes to control flower sex. [ABSTRACT FROM AUTHOR]

Hepatitis B virus (HBV) covalently closed circular DNA (cccDNA), serving as the viral persistence form and transcription template of HBV infection, hijacks host histone and non-histone proteins to form a minichromosome and utilizes posttranslational modifications (PTMs) "histone code" for its transcriptional regulation. HBV X protein (HBx) is known as a cccDNA transcription activator. In this study we established a dual system of the inducible reporter cell lines modelling infection with wildtype (wt) and HBx-null HBV, both secreting HA-tagged HBeAg as a semi-quantitative marker for cccDNA transcription. The cccDNA-bound histone PTM profiling of wt and HBx-null systems, using chromatin immunoprecipitation coupled with quantitative PCR (ChIP-qPCR), confirmed that HBx is essential for maintenance of cccDNA at transcriptionally active state, characterized by active histone PTM markers. Differential proteomics analysis of cccDNA minichromosome established in wt and HBx-null HBV cell lines revealed group-specific hits. One of the hits in HBx-deficient condition was a non-histone host DNA-binding protein high mobility group box 1 (HMGB1). Its elevated association to HBx-null cccDNA was validated by ChIP-qPCR assay in both the HBV stable cell lines and infection systems in vitro. Furthermore, experimental downregulation of HMGB1 in HBx-null HBV inducible and infection models resulted in transcriptional re-activation of the cccDNA minichromosome, accompanied by a switch of the cccDNA-associated histones to euchromatic state with activating histone PTMs landscape and subsequent upregulation of cccDNA transcription. Mechanistically, HBx interacts with HMGB1 and prevents its binding to cccDNA without affecting the steady state level of HMGB1. Taken together, our results suggest that HMGB1 is a novel host restriction factor of HBV cccDNA with epigenetic silencing mechanism, which can be counteracted by viral transcription activator HBx. Author summary: Nowadays hepatitis B virus (HBV) prevalence remains a significant burden to the worldwide healthcare. There is no cure for chronic HBV infection so far due to the lack of therapies that enable elimination of an intrahepatic persistent form of HBV DNA genome, namely, the covalently closed circular DNA (cccDNA). Inside the infected liver cells, cccDNA hijacks host structural and regulatory factors to assemble into a minichromosome, but certain intrinsic host factors are able to counteract cccDNA activity. In our study, we identified an anti-HBV host restriction factor, specifically the high mobility group box 1 protein (HMGB1), and demonstrated its potential to mediate an epigenetic silencing, i.e. functional inactivation, of the cccDNA. However, the virally encoded accessory protein HBx is able to antagonize HMGB1 and maintain an active state of cccDNA. This may contribute to a better understanding of virus-host interaction during HBV infection, and to the development of HBV infection epigenetic drugs and re-consideration of cancer therapeutics strategies, where HMGB1 is used as an anti-cancer target. [ABSTRACT FROM AUTHOR]

Fine roots (< 2 mm in diameter) are the main organ for obtaining resources from the belowground part of forest and also act as a hub linking the ecological processes of plant and soil. However, in the context of global climate change, it remains unclear how fine root dynamics and morphology in temperate forests respond to increased nitrogen deposition and reduced precipitation in growing season on a year-round time scale. In this study, the minirhizotrons were used to observe the response of fine root dynamics (production, mortality, turnover and life span) and morphology (diameter, single root surface area, single root length) to long-term nitrogen addition (N, 50 kg N ha−1 yr−1), precipitation reduction (W, −200 mm yr−1) and their interactive treatments (NW) in a broad-leaved Korean pine forest in Changbai Mountains over a two-year period. The results showed that N significantly increased the average diameter of fine roots. Compared to the control treatment, all treatments significantly reduced the average monthly number and surface area of live root. However, the morphological traits of the individual root in each treatment differed between the growing and non-growing seasons. All three treatments (N, W, NW) reduced annual production of fine root over the two observation periods, while the effect on annual mortality varied between years. N, W and the interaction of NW did not significantly change the annual turnover of fine root in the first observation period but increased significantly in the second. The median life span of fine root born in both non-growing seasons was significantly lower than that of fine root born in the growing season. Our results show that changes in the growth strategy of fine root depend on the complex interrelationship between their own morphology, soil layer and seasonal climatic conditions. [ABSTRACT FROM AUTHOR]

Following the 'people-oriented' concept, increased attention should be paid to the heterogeneity of community residents when configuring public service facilities. Taking Shanghai as an example, this study analyzed the spatial pattern of urban and rural community differentiation and evaluated spatial differences in the level of accessibility to four types of public service facilities based on the shortest travel distance. There were significant differences between community types in Shanghai, with a clear circular structure in the urban and rural spaces. Here, facility accessibility decreased from the core to the periphery. Population density, income level, and the shortest walking distance to facilities revealed a significant negative correlation. Age level, household registration, and the shortest walking distance to facilities were partially weakly correlated or uncorrelated. The spatial matching of population density and facility accessibility simultaneously presented a circular pattern and heterogeneity, while planned new towns in suburbs and mid-suburbs presented a double-medium-sized match of the same community type. From the perspective of community differentiation, mechanisms behind the formation of the spatial pattern of facility accessibility included urban-rural pattern continuity and differences in allocation specifications, the continuity of population agglomeration and the accumulation of facility construction, and urban planning guidance and population agglomeration. [ABSTRACT FROM AUTHOR]

Background: The complicated hyperglycaemic and chronic inflammation of diabetic wounds in orthopaedic surgery leads to dysregulated immune cell function and potential infection risk. Immune interventions in diabetic wounds face a possible contradiction between simultaneous establishment of the pro-inflammatory microenvironment in response to potential bacterial invasion and the anti-inflammatory microenvironment required for tissue repair. To study this contradiction and accelerate diabetic-wound healing, we developed a photocurable methacryloxylated silk fibroin hydrogel (Sil-MA) system, co-encapsulated with metformin-loaded mesoporous silica microspheres (MET@MSNs) and silver nanoparticles (Ag NPs). Results: The hydrogel system (M@M–Ag–Sil-MA) enhanced diabetic-wound healing via spatiotemporal immunomodulation. Sil-MA imparts a hydrogel system with rapid in situ Ultra-Violet-photocurable capability and allows preliminary controlled release of Ag NPs, which can inhibit bacterial aggregation and create a stable, sterile microenvironment. The results confirmed the involvement of Met in the immunomodulatory effects following spatiotemporal dual-controlled release via the mesoporous silica and Sil-MA. Hysteresis-released from Met shifts the M1 phenotype of macrophages in regions of diabetic trauma to an anti-inflammatory M2 phenotype. Simultaneously, the M@M–Ag–Sil-MA system inhibited the formation of neutrophil extracellular traps (NETs) and decreased the release of neutrophil elastase, myeloperoxidase, and NETs-induced pro-inflammatory factors. As a result of modulating the immune microenvironmental, the M@M–Ag–Sil-MA system promoted fibroblast migration and endothelial cell angiogenesis in vivo, with verification of enhanced diabetic-wound healing accompanied with the spatiotemporal immunoregulation of macrophages and NETs in a diabetic mouse model. Conclusions: Our findings demonstrated that the M@M–Ag–Sil-MA hydrogel system resolved the immune contradiction in diabetic wounds through spatiotemporal immunomodulation of macrophages and NETs, suggesting its potential as a promising engineered nano-dressing for the treatment of diabetic wounds in orthopaedic surgery. [ABSTRACT FROM AUTHOR]

This paper talks about asymptotic convergence aspects about the internal model principle (IMP) and trajectory tracking control (TTC) in linear dynamical systems. First, IMP and asymptotic TTC are re-formulated and explicated. Second, TTC under internal models of trajectory and disturbance is classified in terms of tracking error bias into bounded; nonzero steady-state; zero steady-state; unbounded (tracking failure). Third, TTC attainability and tracking error biases are examined via asymptotic convergence analysis. In particular, bounded TTC is attainable if trajectory and disturbance are essentially bounded; zero/nonzero-steady-state TTC is attainable if trajectory and disturbance t → ∞ limits are well-defined so that the Laplace ultimate value theorem holds; zero-steady-state TTC is realisable if internal models exactly reflect all unstable modes of trajectory and disturbance. Fourth, when internal models are subject to mismatches and sampled-data approximates, several interesting convergence facts are revealed. More specifically, for addressing zero-steady-state TTC to periodic trajectory and disturbance, stabilisation may be insufficient; for addressing TTC under sampled-data internal models, unknown convergence features are claimed. Finally, TTC controller parametrisation via pole assignment stabilisation is scrutinised under static output and state feedback. Numerical examples are included to illustrate the main results. [ABSTRACT FROM AUTHOR]

The mechanical properties of four types of concrete, tested under multiaxial (biaxial tension–compression, triaxial tension–compression–compression) dynamic (strain rates of 10−5, 10−4, 10−3 and 10−2 s−1) complex stress states with different stress ratios, were compared and analysed. The same test apparatus was used in order to avoid test errors caused by differences of the triaxial testing machine. The aim of this work was mainly to determine the dynamic multiaxial (DM) strengths of the four concrete types. It was found that the mechanical behaviour of the four concretes was similar to a certain extent. The DM strengths of the concretes increased with an increase in strain rate and their DM strengths in any direction were lower than the concrete static strength under uniaxial tension and compression. The influence of strain rate and stress ratio on the DM strengths of the concretes were compared and analysed. A unified failure criterion was developed, expressed by the octahedral stress space criterion, of the various concrete types under DM tension and compression. This investigation provides a theoretical foundation for the design and checking of structures subjected to DM load conditions. [ABSTRACT FROM AUTHOR]

The self-restacking of graphene nanosheets inevitably compromises the electrochemical performance of conventional graphene-based materials. Herein, to solve this problem, we prepared a new type of three-dimensional porous aerogel with partially unzipped multiwalled carbon nanotubes inserted into graphene nanosheets via a reduction-reaction-induced self-assembly process. In the resulting aerogels, the inner carbon nanotubes (CNTs) tightly attach to the unzipped outer graphene nanoribbons (GNRs), which bridge with the graphene nanosheets. These interconnections bring them excellent electrical contact; the CNTs act as spacers to prevent the restacking of adjacent graphene nanosheets, and the abundant interconnected pores in the aerogels provide large channels for charge transfer. Accordingly, the aerogels exhibit a specific capacitance of 348.4 Fg−1 at a scan rate of 5 mVs−1, with capacitance retention remaining at 89.7% at a current density of 2 Ag−1 after 5000 cycles. The results show that the aerogels are promising electrode materials for supercapacitor applications. [ABSTRACT FROM AUTHOR]

In order to better understand the bacterial distribution characteristics in a whole microecosystem, the bacterial communities in different components of an artificial aquarium (i.e., plants, fishes, sand and water) were characterized using high throughput sequencing of bacterial 16S rRNA genes. Across all samples, 2873 operational taxonomic units were identified and assigned to 771 genera in 36 phyla. In a principle coordinate analysis, samples clustered according to their origin, indicating that bacterial communities from the same component were most similar. Further taxonomic analysis revealed that most dominant genera, even those with the similar functions, were biased to one component: Nitrospira and Rhodobacter were mainly abundant in plant samples; Rhodococcus, Serratia, Ralstonia, Sphingobacterium and Pseudomonas were most common in sand samples; Cetobacterium and Aeromonas dominated fish samples; and Flavobacterium, Alpinimonas and Limnobacter were especially common in water samples. Functional predictions performed by PICRUSt and the dominant genera exhibited that bacteria detected in each component could participate in all nutrient cycles in the aquarium. However, those involved in carbon and nitrogen cycling were most common in plant and fish samples, while phosphate metabolism-related pathways were more abundant in sand and water samples. Moreover, the aquarium plants, in association with their bacterial communities might be the most important component in the aquarium, as indicated by their highest bacterial richness and diversity. This study adds to our understanding on the differences in the microbiome of different components and their possible contributions to nutrient cycling in a self-sustaining aquarium. [ABSTRACT FROM AUTHOR]

Watershed algorithm is widely used in image segmentation, but it has oversegmentation in image segmentation. Therefore, an image segmentation algorithm based on K-means and improved watershed algorithm is proposed. Firstly, Gaussian filter is used to denoise human skeleton image. K-means clustering algorithm is used to segment the denoised image and the connected component with the largest area is extracted as the initial human skeleton region. The initial bone region was morphologically opened and then morphologically closed to eliminate the noise. Morphologically open operation is used to disconnect other human tissues that adhere to the human bone region and eliminate the background noise with small area, while closed operation smoothes the edge of the human bone region and fills the fracture in the contour line. Secondly, the watershed segmentation algorithm is implemented on the image after morphological operation. The similarity degree of two blocks is defined according to the mean difference of gray level of adjacent blocks and the mean value of standard deviation of gray level of pixels in the edge of the block 4-neighborhood. The adaptive threshold T is generated by Otsu method for histogram of gradient amplitude image. If the similarity degree is greater than T, the image blocks will be merged; otherwise, the image blocks will not be merged. The proposed image segmentation algorithm is used to extract and segment the human bone region from 100 medical images containing human bone. The number of blocks segmented by watershed algorithm is 2775 to 3357, but the number of blocks segmented by the proposed algorithm is 221 to 559. The experimental results show that the proposed algorithm effectively solves the oversegmentation problem of watershed algorithm and effectively segments the image target. [ABSTRACT FROM AUTHOR]

Background. This study sought to explore the association between quantitative classification of renal surface nodularity (qRSN) based on computed tomography (CT) imaging and early renal injury (ERI) in patients with arterial hypertension. Methods. A total of 143 patients with a history of hypertension were retrospectively enrolled; clinical information (age, sex, hypertension grade, and hypertension course), laboratory tests, and qRSN were collected or assessed. The subjects were divided into an ERI group (n = 60) or a control group (CP, n = 83) according to ERI diagnosis based on the following criteria: cystatin C > 1.02 mg/L. Univariate analysis and multiple logistic regression were used to assess the association between ERI and qRSN. A receiver operating characteristic curve (ROC) was performed to compare multiple logistic regression models with or without qRSN for differentiating the ERI group from the control group. Results. In univariate analysis, hypertension grade, hypertension course, triglycerides (TG), and qRSN were related to ERI in patients with arterial hypertension (all P < 0.1), with strong interrater agreement of qRSN. Multiple logistic regression analysis showed an area under the ROC curve of 0.697 in the model without qRSN and 0.790 in the model with qRSN, which was significantly different (Z = 2.314, P = 0.021). Conclusion. CT imaging-based qRSN was associated with ERI in patients with arterial hypertension and may be an imaging biomarker of early renal injury. [ABSTRACT FROM AUTHOR]

In this paper we study existence and asymptotic behaviors of solutions for mixed-type functional differential equation with state-dependence x ˙ (t) = f (t , x (T 1 (t , x (t))) ,... , x (T n (t , x (t)))). Because of complexity of state-dependent terms, it is so difficult to discuss its stability by Lyapunov direct method. Through an order-preserving transformation, we generalize Gronwall inequality to obtain boundedness and asymptotics of solutions. It can be regarded as an extension to Lyapunov indirect method. Moreover, we indicate that Krasnoselskii fixed point theorem also can be used to study existence of sign-changing solutions. Finally, we apply our method to iterative functional differential equations and provide two concrete examples. [ABSTRACT FROM AUTHOR]

The diaryliodonium salts derived from gemfibrozil and gemfibrozil methyl ester were synthesized from ArI(OH)OTs or bis(4-methoxyphenyl)iodonium diacetate with good regioselectivity. These iodonium salts were successfully used in the derivatization of gemfibrozil or gemfibrozil methyl ester, including fluorination, alkynylation, aryl-ation, etherification, esterification, and iodination reactions. [ABSTRACT FROM AUTHOR]

Hyperspectral image (HSI) denoising is an ill-posed inverse problem. The underlying physical model is always important to tackle this problem, which is unfortunately ignored by most of the current deep learning (DL)-based methods, producing poor denoising performance. To address this issue, this article introduces an end-to-end model-aided nonlocal neural network (MAC-Net) which simultaneously takes the spectral low-rank model and spatial deep prior into account for HSI noise reduction. Specifically, motivated by the success of the spectral low-rank model in depicting the strong spectral correlations and the nonlocal similarity prior in capturing spatial long-range dependencies, we first build a spectral low-rank model and then integrate a nonlocal U-Net into the model. In this way, we obtain a hybrid model-based and DL-based HSI denoising method where the spatial local and nonlocal multi-scale and spectral low-rank structures are effectively exploited. After that, we cast the optimization and denoising procedure of the hybrid method as a forward process of a neural network and introduce a set of learnable modules to yield our MAC-Net. Compared with traditional model-based methods, our MAC-Net overcomes the difficulties of accurate modeling, thanks to the strong learning and representation ability of DL. Unlike most “black-box” DL-based methods, the spectral low-rank model is beneficial to increase the generalization ability of the network and decrease the requirement of training samples. Experimental results on the natural and remote-sensing HSIs show that MAC-Net achieves state-of-the-art performance over both model-based and DL-based methods. The source code and data of this article will be made publicly available at https://github.com/bearshng/mac-net for reproducible research. [ABSTRACT FROM AUTHOR]

Previous studies on UV-curable elastomer for digital light processing (DLP) 3D printing flexible electronics mostly focused on higher stretchability and healability, thereby ignoring rapid recoverability after a stretch which is very important for the real-time transmission of electrical signals in flexible electronics. Herein, a UV-curable elastomer is developed with a novel dynamic hierarchical crosslinking network that can be stretched up to over 800% and rapid recoverability at 300% strain. We proposed a hydrogel-elastomer assembling process to simplify the manufacturing process for stretchable conductors. The stretchable conductors served as a strain sensor exhibiting excellent stability and repeatability after 10 cycles at 20–50% strain with low signal drift and hysteresis, Moreover, the strain sensor can be utilised in recognising the different bending angles of the finger, making DLP printing of conductive elastomer a viable strategy for the rapid manufacturing of flexible electronics. [ABSTRACT FROM AUTHOR]

A microbial fuel cell (MFC) was constructed with CNTs, 0.02gMnO 2 /CNTs and 0.03gMnO 2 /CNTs modified graphite anode prepared by coating for enhancing copper wastewater treatment. The SEM, XRD and FTIR results showed that MnO 2 /CNTs and CNTs were successfully attached to the graphite electrode, indicating that the electrode was modified successfully. The surface wettability test showed that the decrease of the contact angle of the modified anode led to the increase of hydrophilicity, which was more conducive to microbial adhesion. The surface contact angle of CNTs modified electrode was the smallest, which was 11.17°. The maximum output voltage, power density and copper removal rate of 0.03gMnO 2 /CNTs modified anode MFC were 0.67 V, 1044.21 mW/m2 and 98.93% respectively, which were 52.3%, 466.3% and 50.5% higher than those of unmodified anode. XPS results showed that the reduction products were Cu 2 O and Cu. Meanwhile，high throughput sequencing showed that CNTs and MnO 2 could improve the richness and diversity of microbial community. MnO 2 /CNTs modified-anode accelerated the enrichment of electro-active bacteria such as Proteobacteria , Firmicutes and Bacteroidetes. [ABSTRACT FROM AUTHOR]

To explore the broken energy change and the specimen fragment influence of granite where the length-to-diameter ratio is 0.5–2, the SHPB device was used to perform dynamic loading on the granite specimens. The rock energy evolution law was analyzed by the energy time history curve, and according to rock fragment characteristics, the rock fractal dimension was calculated. The experimental results show that the rock energy-time history curve can be divided into four stages. The incident energy is independent of the length-to-diameter ratio of the rock specimens. When the length-to-diameter ratio of the rock specimens is 0.5–0.9, the difference of incident energy, transmitted energy, and reflection energy of rock specimens is small. With the length-to-diameter ratio increasing, the rock fragment size became larger. These rock fragments have good self-similarity. The rock specimen fractal dimension is at least 1.94, and the maximum D is 2.536. And with the length-to-diameter ratios increasing, the fractal dimension of rock specimens decreases. With the specimen fractal dimension increasing, the energy dissipation density of rock specimens also increases. The higher the energy dissipation density of a rock specimen, the more uniform rock fragments are. [ABSTRACT FROM AUTHOR]

Supervillin (SVIL) is an actin-binding and membrane-associated protein, which belongs to villin/gelsolin family. It has been reported that SVIL was involved in the regulation of macrophages' movement and lipopolysaccharide (LPS) increased the SVIL mRNA expression in neutrophils, but the underlying mechanisms remain unknown. This work investigated the underlying molecular mechanisms of LPS regulating SVIL expression in macrophages and hence the possible role of SVIL in LPS-induced inflammation. We found that in THP-1-derived macrophages, LPS obviously increased SVIL mRNA and protein expression. Inhibition of TLR4 by Resatorvid (Res) remarkably reversed the LPS-induced SVIL expression. Additionally, inhibition of ERK1/2 signaling pathway (by U0126 or GDC-0994) and NF-κB (by BAY) significantly reduced the LPS-induced SVIL expression. Interestingly, down-regulation of SVIL by SVIL-specific shRNAs significantly attenuated the expression of IL-6, IL-1β & TNF-α induced by LPS at both mRNA and protein levels. Furthermore, we also observed that SVIL knockdown decreased the proportion of cells in G2/M phase and increased the proportion of cells in S & G0-1 phase of THP-1 derived macrophages, but did not influence the cell viability. Taken together, we demonstrated that LPS induced the expression of SVIL via activating TLR4/NF-κB and ERK1/2 MAPK pathways, and SVIL participated in the inflammatory response of LPS-induced IL-6, IL-1β and TNF-α upregulation in macrophages. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Core‐shell nanostructures constituted by a plasmonic core and an ultrathin shell have drawn enormous attentions in enhanced spectroscopies, catalysis, energy, and other fields because of their splendid properties such as multifunctionality, stability, and adjustability. In this article, we summarized the endeavors made by our group in the past decade about the core‐shell nanostructures in the shell‐isolated nanoparticle‐enhanced Raman spectroscopy (SHINERS) and plasmon‐enhanced spectroscopies. Meanwhile, the potential challenges and perspectives about core‐shell nanostructures in spectroscopies have also been proposed. Thus, we believe this article would provide an avenue for a comprehensive understanding of enhanced spectroscopies with core‐shell nanostructures. What is the most favorite and original chemistry developed in your research group?? Core‐shell nanostructure enhanced Raman spectroscopy for surface analysis. How do you get into this specific field? Could you please share some experiences with our readers?? I started the studies on Raman spectroscopy since I was a Ph.D. candidate. I think most researchers should concentrate on specific fields, especially those that can hardly be solved by others, and make constant research on them. How do you supervise your students?? First, give highly challenging or unique topics to students. Then, make detailed plans for them and supervise them to execute the plans. What is the most important personality for scientific research?? Insistence and diligence. What are your hobbies? What's your favorite book(s)? Playing computer games. My favorite book is State of Divinity (笑傲江湖), by Louis Cha. What is your favorite journal(s)? The journals report systematic and pioneer works on chemistry, materials, or energy, etc. [ABSTRACT FROM AUTHOR]

The number of fault sources is helpful for accurately extracting fault features. The existing source number estimation methods have certain difficulties when realizing the source estimation of mechanical vibration signals and acoustic signals in a strong background noise environment. A variety of the fault source signals are coupled with each other, resulting in that the number of fault sources in the actual working conditions is unknown, and sometimes the number of observation signals is less than the number of fault source signals due to the limitation of sensor installation condition. A novel method for underdetermined source number estimation based on the combination of morphological filtering (MF), adaptive variational modal decomposition (AVMD) and singular value decomposition (SVD), named MF-AVMD-SVD, is proposed. First, MF is used to filter out background noise signals and enhance the impact characteristics of fault signals. Second, AVMD is used to resolve the filtered observation signals to obtain intrinsic mode function (IMF); these IMFs are recombined to obtain the covariance matrix of multidimensional observation signals. Finally, new non-zero eigenvectors are obtained by SVD, and the accurate number of rolling bearing fault source signals is determined according to the maximum value of the adjacent eigenvalue ratio. This method is applied to the simulation signal; the number of four sources can be accurately estimated by the two-channel simulation mixed signal under the condition that the signal to noise ratio (SNR) is −15 dB or even −21 dB. It can also be effectively estimated that the number of vibration sources is three from the vibration signals and acoustic signals of the double-channel rolling bearing composite fault. [ABSTRACT FROM AUTHOR]

Natural gas transmission networks (NGTNs) are the main facility connecting upstream gas sources and downstream consumers. For a cyclic NGTN with multiple gas transmission routes, different gas transportation schemes will affect not only the energy consumption of the system but also the pipeline transportation costs paid by consumers. In this paper, three operation optimization models are established to determine the optimal operating state of a multiroute cyclic NGTN under different scenarios. The three mathematical models correspond to three different objective functions: minimize the cost of compressor energy consumption, minimize the expense of pipeline transportation, and minimize the sum of the two expenses. The decision variables of the models include the pipeline flow rate, the number of operating compressors, and the outlet pressure of the compressors. In addition, a series of linear and nonlinear constraints of nodes, pipelines, and compressors is also proposed to guarantee the feasibility of solutions. The operation optimization problem is solved by the General Algebraic Modeling System (GAMS), and the effectiveness of this method is tested on a small double-route cyclic NGTN and a large three-route cyclic NGTN. The results show that the developed optimization model is able to find optimal solutions under different models. In the cyclic network, the difference in the flow distribution of gas transmission routes is the key factor affecting the optimization result. In addition, compared with the compressor energy consumption cost minimization objective, the pipeline transportation expense minimization objective can create greater economic benefits for consumers. In the two network cases, consumers can save 14.51 and 59.18×104 RMB. Finally, optimizing the two objectives at the same time makes it possible to achieve an effective balance between them. [ABSTRACT FROM AUTHOR]

• Established a three-layer planning model consisting of defense, attack, and operational layers. • Developed a robust planning model to address the uncertainty of attack resources. • Addressed pipeline protection issues under both certain and uncertain attack resource conditions. • Formulated pipeline transportation plans for scenarios where the network is damaged. • Analyzed the impact of backup pipelines on network resilience in relation to the allocation of defense resources. Using game theory techniques, a three-layer planning model (THLPM) for the defense, attack, and operational layers has been established to address malicious damage to pipelines. A robust planning model was developed for situations with uncertain attack resources. In this model, the defense layer protects critical infrastructure within the network to minimize losses. The attack layer targets unprotected facilities based on the defensive strategy. The operational layer formulates the optimal pipeline transmission strategy based on the decisions of the defense and attack layers. By utilizing the duality theorem, the THLPM is transformed into a two-layer planning problem, which is then linearized and solved using a decomposition algorithm. Taking a specific ring-shaped pipeline network as an example, the study analyzes the significant role of backup pipelines in enhancing system resilience and evaluates the offensive and defensive strategies of THLPM. The effectiveness of THLPM in protecting the network was assessed, showing that when defense and attack resources are invested at levels 3 and 10, respectively, operational costs of the network are reduced by 54.2 % compared to a scenario without any defenses. The methods proposed in this paper are applicable to other pipeline systems. [ABSTRACT FROM AUTHOR]

• The study found notable distinctions in the visual, somatomotor, dorsal network, as well as in the DMN, frontoparietal network, and cerebellum when comparing EC and EO states. • The graph theory analysis revealed that the weakened degree and functional connectivity in the SFG and the MCC among StD individuals. The SFG and the MCC connections were correlated with perceived stress. • The functional connectivity between the SFG and the SFGmed was discovered to modulate the relationship between perceived stress and StD. Perceived stress is an acknowledged risk factor for subthreshold depression (StD), and fluctuations in perceived stress are thought to disrupt the harmony of brain networks essential for emotional and cognitive functioning. This study aimed to elucidate the relationship between eye-open (EO) and eye-closed (EC) states, perceived stress, and StD. We recruited 27 individuals with StD and 33 healthy controls, collecting resting state fMRI data under both EC and EO conditions. We combined intrinsic connectivity and seed-based functional connectivity analyses to construct the functional network and explore differences between EC and EO conditions. Graph theory analysis revealed weakened connectivity strength in the right superior frontal gyrus (SFG) and right median cingulate and paracingulate gyrus (MCC) among participants with StD, suggesting an important role for these regions in the stress-related emotions dysregulation. Notably, altered SFG connectivity was observed to significantly relate to perceived stress levels in StD, and the SFG connection emerges as a neural mediator potentially influencing the relationship between perceived stress and StD. These findings highlight the role of SFG and MCC in perceived stress and suggest that understanding EC and EO states in relation to these regions is important in the neurobiological framework of StD. This may offer valuable perspectives for early prevention and intervention strategies in mental health disorders. [ABSTRACT FROM AUTHOR]

Underground gas storage plays a crucial role in ensuring the supply and demand balance of natural gas pipeline network. However, the peak shaving function of underground gas storage or its injection-withdrawal hydraulic characteristics are often overlooked in the optimization of pipeline network scheduling. This paper develops an integrated scheduling optimization model of complex natural gas pipeline network system with underground gas storage, which responds to multi-period consumer demand changes to balance supply and demand, while considering both economic and environmental benefits. The optimization model comprehensively considers the elements of underground gas storage, including reservoir, injection-withdrawal well, and compressor group. A mixed integer linear programming relaxation method combining the linearization of univariate and bivariate functions and convex relaxation of feasible regions is designed. The case study results show that underground gas storage peak shaving function can effectively compensate for gas supply shortage. Compared to the non-relaxation method, the relaxation method reduced the transportation and injection-withdrawal energy cost by 10.21 % and 15.89 %, and carbon emissions by 20,426 tons. Furthermore, the study analyzed the advantages of the comprehensive underground gas storage model, the coordinated injection-withdrawal strategies of multiple underground gas storages, and the response strategies under system abnormal conditions. • A comprehensive underground gas storage model considering hydraulics is developed. • Pipeline network scheduling strategies integrating gas peak-shaving are proposed. • The carbon emission optimization of gas transportation and storage is considered. • A method combining the linearization and convex relaxation is designed. [ABSTRACT FROM AUTHOR]

Persistent auditory verbal hallucinations (pAVHs) are a fundamental manifestation of schizophrenia (SCZ), yet the exact connection between pAVHs and brain structure remains contentious. This study aims to explore the potential correlation between pAVHs and alterations in grey matter volume (GMV) within specific brain regions among individuals diagnosed with SCZ. 76 SCZ patients with pAVHs (pAVH group), 57 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group) were investigated using 3 T magnetic resonance imaging. The P3 hallucination item of the Positive and Negative Syndrome Scale was used to assess the severity of pAVHs. Voxel-based morphometry was used to analyze the GMV profile between the three groups. Compared to the non-AVH and HC groups, the pAVH group exhibited extensive reduction in GMV within the frontotemporal cortex. Conversely, no significant difference in GMV was observed between the non-AVH and HC groups. The severity of pAVHs showed a negative correlation with GMV in several regions, including the right fusiform, right inferior temporal, right medial orbitofrontal, right superior frontal, and right temporal pole (p = 0.0036, Bonferroni correction). Stepwise linear regression analysis revealed that GMV in the right temporal pole (β = −0.29, p = 0.001) and right fusiform (β = −0.21, p = 0.01) were significantly associated with the severity of pAVHs. Widespread reduction in GMV is observed within the frontotemporal cortex, particularly involving the right temporal pole and right fusiform, which potentially contribute to the pathogenesis of pAVHs in individuals with chronic SCZ. [ABSTRACT FROM AUTHOR]

Moiré superlattices, induced by an angular mismatch in layered materials provide a new index of freedom to manipulate the correlated electron states and many‐body properties of excitons. Here, trilayer MoS2 homostructures with the 3R configuration between the middle (M) and the bottom (B) layer and the top‐to‐middle (T‐M) interlayer twists ranging from 10° to 40° are fabricated via NaCl‐assisted chemical vapor deposition. The twist‐dependent interlayer interactions are systematically investigated by polarized low frequency (PLF) and high frequency (HF) Raman spectroscopy. PLF Raman results show that the energy shift in the shear mode, the breathing modes of LB31 and LB32 is respectively the much in 14°‐ and 28°‐T‐M twisted trilayer, among as‐prepared trilayer MoS2 homostructures. Moreover, the T‐M twist further affects the optical properties of the twisted MoS2 trilayer, evidenced by the photoluminescence (PL) spectroscopy. Moiré excitons are enhanced in the top‐layer twisted MoS2 trilayer with a T‐M twists of 28°, which may originate from the interlayer exciton trapped by the periodical moiré potential. The present work demonstrates that the trilayer homostructures tuned by interlayer twists can be an ideal system to tune the energy band structures and exciton properties for their potential applications in the nano‐optical electronics. [ABSTRACT FROM AUTHOR]

Palladium is one of the most utilized metals in catalysis, particularly for hydrogenation and oxidation, cross C–C coupling, hydrogen formation, photocatalytic and electrocatalytic energy conversion reactions. Heterogeneous catalysis is undergoing a considerable move involving molecular aspects, which allows a better control and understanding of the structure–reactivity relationship toward optimization of the catalyst performances and selectivities. Inspired by organometallic catalysis, nanocatalytic materials that provide heterogeneization, nanocatalyst stabilization and optimized synergies include iron oxides, polymers, dendrimers, magnetic iron oxides, metal–organic and covalent-organic frameworks, carbons, atomically precise nanoclusters and other subnanoclusters such as single atoms, dual atoms and their combination and synergies with nanoparticles. In these nanocomposites, the number of catalytically utilized expansive Pd atoms is minimized. This mini-review addresses new trends of Pd nanocatalysis including these aspects with selected examples and examines perspectives.Progress of Pd nanocatalysis are reviewed including dramatic recent decrease of Pd sub-nanoparticle size utilizing modern organic or inorganic framework matrices.Graphical Abstract: Palladium is one of the most utilized metals in catalysis, particularly for hydrogenation and oxidation, cross C–C coupling, hydrogen formation, photocatalytic and electrocatalytic energy conversion reactions. Heterogeneous catalysis is undergoing a considerable move involving molecular aspects, which allows a better control and understanding of the structure–reactivity relationship toward optimization of the catalyst performances and selectivities. Inspired by organometallic catalysis, nanocatalytic materials that provide heterogeneization, nanocatalyst stabilization and optimized synergies include iron oxides, polymers, dendrimers, magnetic iron oxides, metal–organic and covalent-organic frameworks, carbons, atomically precise nanoclusters and other subnanoclusters such as single atoms, dual atoms and their combination and synergies with nanoparticles. In these nanocomposites, the number of catalytically utilized expansive Pd atoms is minimized. This mini-review addresses new trends of Pd nanocatalysis including these aspects with selected examples and examines perspectives.Progress of Pd nanocatalysis are reviewed including dramatic recent decrease of Pd sub-nanoparticle size utilizing modern organic or inorganic framework matrices. [ABSTRACT FROM AUTHOR]

• Establishing a novel rice fertilization recommendation model. • Employing a combination of knowledge graph and case-based reasoning. • Achieving high-precision fertilization plans with limited real-time field data. • Improving the intelligence level of the rice fertilization system. Rice fertilization management plays an important role in rice yield and quality; however, making automatic fertilization plans according to the rice life cycle is difficult. This study proposes a rice fertilization recommendation model using a knowledge graph and a case-based reasoning method. To build the recommendation model, an initial fertilization scheme was first obtained by retrieving information from a knowledge graph. It was further enriched through operating vectors of all entities and relations in the knowledge graph obtained using the PairRE model. Next, k historical cases similar to the target event were retrieved using the fertilization scheme, attributes of the target event, and entity vectors of the knowledge graph. Finally, the fertilization rates for the target were predicted according to the k cases. The results showed that by employing the proposed model, the error rate of the fertilization scheme was approximately 19.5% and the prediction accuracies for N, P 2 O 5 , and K 2 O were 95.69%, 79.04%, and 81.67%, respectively. The model not only improves the accuracy of recommendations but also has strong interpretability and high practical value, and can be easily replicated and applied in the design of agricultural recommendation systems. [ABSTRACT FROM AUTHOR]

Directional-dependent Goos-H a ¨ nchen (GH) shift describes its dependence on the propagation direction of the incident wave. That is to say, the GH shifts are different when the incident wave propagates along two opposite directions (we call them the forward and backward incidence later). We demonstrate, using the transfer matrix method and stationary phase method, that the multilayered structure with the recently advanced Dirac semimetal can realize the directional-dependent GH shift. It is found that the maximum absolute value of the GH shift for the forward incidence is just 22 times of the incident wavelength (22 λ) but it is up to 2286 λ for the backward incidence. We clarify the mechanism behind the directional-dependence of the GH shift in the multilayered structure and highlight that the mirror asymmetry of this structure is the dominated factor to produce this kind of directional dependent optical effect. Our work allows the unique chance of the multilayered structure with Dirac semimetal for producing the directional-dependent GH shift and designing the directional devices, such as, directional amplifier, unidirectional couplers and splitters. • A new type of three-dimensional exotic topological quantum material-- Dirac semimetal is used to research Goos-Hänchen shift. • Goos-Hänchen shift is greatly enhanced. • Goos-Hänchen shifts are directional-dependent in our structure. [ABSTRACT FROM AUTHOR]

Objective To analyze the characteristics of pattern elements and the distribution of patterns of femoral head necrosis, hip osteoarthritis, and hip rheumatoid arthritis, in order to provide a theoretical basis for the "different diseases with the same pattern" of chronic bone diseases. Methods A cross-sectional survey was conducted to select patients with femoral head necrosis Association Research Circulation Osseous I-II stages, hip osteoarthritis Kellgren & Lawrence I-II stages, and acute or subacute hip rheumatoid arthritis who visited the Minimally Invasive Arthrology Department, Traumatology Department, and Rheumatology and Immunology Department of Beijing University of Chinese Medicine Third Affiliated Hospital from June 2020 to June 2022. The "case report form - traditional Chinese medicine pattern manifestation scale" previously developed by our team was used to collect the pattern manifestations, which were included into an Excel 2020 spreadsheet to establish a database. SPSS 20.0 software was used for factor analysis and cluster analysis to extract pattern element information, such as disease nature and location, in order to summarize the characteristics of pattern elements, the distribution of patterns, and the similarities and differences of the three kinds of early hip joint diseases. Results A total of 410 patients were included, including 150 patients with femoral head necrosis, 160 patients with hip osteoarthritis, and 100 patients with hip rheumatoid arthritis. The pattern elements of the disease nature of femoral head necrosis include phlegm (dampness), blood stasis, yang deficiency, essence deficiency, and qi deficiency. The pattern types were initially divided into four categories: syndrome of meridian obstruction (43.33%), syndrome of phlegm and blood stasis blocking collaterals (38.00%), syndrome of liver and kidney deficiency (12.00%), and syndrome of kidney essence deficiency (6.67%). The pattern elements of the disease nature of hip osteoarthritis include phlegm (dampness), blood stasis, qi deficiency, essence deficiency, yang deficiency, and cold (dampness). The pattern types were preliminarily divided into five categories: syndrome of spleen and kidney deficiency (37.50%), syndrome of meridian obstruction (26.87%), syndrome of cold and dampness obstruction (18.75%), syndrome of phlegm and blood stasis obstruction (9.38%), and syndrome of liver and kidney deficiency (7.50%). The pattern elements of the disease nature of hip rheumatoid arthritis include phlegm (dampness), blood stasis, qi deficiency, yin and yang deficiency, cold (dampness), and essence deficiency. The pattern types were preliminarily divided into four categories: syndrome of phlegm and blood stasis obstruction (34.00%), syndrome of cold and dampness obstruction (28.00%), syndrome of blood stasis blocking collaterals (23.00%), and syndrome of liver and kidney deficiency (15.00%). Overall, the top five pattern manifestations of the three kinds of hip joint diseases were hip joint pain (96.59%), tenderness (93.90%), fixed pain (87.56%), heavy joints (85.37%), and sourness of lower limbs (75.37%). The pattern elements of the disease nature include phlegm (dampness), blood stasis, qi deficiency, etc. The pattern types were preliminarily divided into five categories: syndrome of phlegm stasis blocking collaterals (33.17%), syndrome of meridian obstruction (31.95%), syndrome of cold dampness obstruction (21.46%), syndrome of liver and kidney deficiency (7.32%), and syndrome of spleen and kidney deficiency (6.10%). There were 21 similar pattern manifestations in the three kinds of early hip joint diseases, with blood stasis and spleen deficiency being the main pattern. Conclusion The common pattern characteristics of three kinds of early hip joint diseases are spleen deficiency and blood stasis. In addition, femoral head necrosis is accompanied with phlegm-dampness pattern, hip osteoarthritis is accompanied with kidney deficiency and phlegm-dampness pattern, hip rheumatoid arthritis is accompanied with kidney deficiency and cold-dampness pattern. [ABSTRACT FROM AUTHOR]

This study presents the synthesis of a non-toxic, water-soluble chitosan oligosaccharide derivative, quaternary ammonium vanillyl aldehyde oligosaccharide (GCOS), using chitosan oligosaccharide, vanillin, and 2,3-epoxypropyltrimethylammonium chloride as precursors, aimed at serving as a novel eco-friendly corrosion inhibitor. The successful synthesis of the derivative was confirmed through Fourier Transform Infrared Spectroscopy (FTIR) and Proton Nuclear Magnetic Resonance (1H NMR) analysis. The corrosion inhibition properties of GCOS on 20# carbon steel were investigated in a 60 °C CO 2 -saturated 3.0 wt% NaCl solution employing an array of methods including weight loss measurements, Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM), electrochemical characterization, and molecular dynamics simulation. Additionally, the synergistic effect of protonated GCOS with halide ion Cl- on corrosion inhibition was analyzed at the molecular level. The results indicated an enhancement in inhibition efficiency with increasing concentrations of the inhibitor. Weight loss measurements showed a maximum inhibition efficiency of 90.9% at 200 ppm of GCOS after 3 days. The adsorption of GCOS on the carbon steel surface was found to follow the Langmuir adsorption isotherm, predominantly through chemisorption. Potentiodynamic polarization measurements classified GCOS as a mixed-type inhibitor, affecting both anodic and cathodic reactions by blocking the active corrosion sites. SEM and AFM analyses confirmed the formation of a protective inhibitor film on the metal surface. Furthermore, molecular dynamics simulations elucidated the synergistic corrosion inhibition effect between the protonated GCOS molecules and Cl- ions in the acidic solution. [Display omitted] [ABSTRACT FROM AUTHOR]

Multimodal emotion analysis is an important endeavor in human–computer interaction research, as it enables the accurate identification of an individual's emotional state by simultaneously analyzing text, video, and sound features. Although current emotion recognition algorithms have performed well using multimodal fusion strategies, two key challenges remain. The first challenge is the efficient extraction of modality-invariant and modality-specific features prior to fusion, which requires deep feature interactions between the different modalities. The second challenge concerns the ability to distinguish high-level semantic relations between modality features. To address these issues, we propose a new modality-binding learning framework and redesign the internal structure of the transformer model. Our proposed modality binding learning model addresses the first challenge by incorporating bimodal and trimodal binding mechanisms. These mechanisms handle modality-specific and modality-invariant features, respectively, and facilitate cross-modality interactions. Furthermore, we enhance feature interactions by introducing fine-grained convolution modules in the feedforward and attention layers of the transformer structure. To address the second issue, we introduce CLS and PE feature vectors for modality-invariant and modality-specific features, respectively. We use similarity loss and dissimilarity loss to support model convergence. Experiments on the widely used MOSI and MOSEI datasets show that our proposed method outperforms state-of-the-art multimodal sentiment classification approaches, confirming its effectiveness and superiority. The source code can be found at https://github.com/JackAILab/TMBL. • Develop binding learning mechanism to facilitate cross-modal feature interaction. • Introduce optimized transformer structure to filter out inconsistent noise. • Introduce CLS and PE feature vectors in the modality fusion process. [ABSTRACT FROM AUTHOR]