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SmCo7/Co nanocomposite powders were prepared by high-energy ball milling of SmCo5 modified by adding Co and annealed at different temperatures. The phase evolution, microstructure and magnetic properties of the nanocomposite powders were analyzed. The results have shown that the annealing temperature and the addition of Co significantly affected the phase structures and magnetic properties of the powders. The nanocomposite powders were completely composed of the SmCo7 phase and the face-centered cubic Co phase. When annealing the SmCo5 powder at 750 °C, the SmCo7 phase decomposed into Th2Zn17-type Sm2Co17 and CaCu5-type SmCo5 phases with an average grain size of 13.9 nm, and the maximum energy product and remanence had maximum values of 10.51 MGOe and 77.92 emu/g, respectively. However, adding 28 wt% Co effectively prevented growth of the grain (11.5 nm) and enhanced the decomposition temperature (850 °C), resulting in a higher maximum magnetic energy product, coercivity, and remanence. The SmCo7 lattice contracted as Co content increased. [ABSTRACT FROM AUTHOR]

In modeling the radar rainfall uncertainty, rain gauge measurement is generally regarded as the areal "true" rainfall. However, the inconsistent scales between radar and gauge may introduce a new uncertainty (also known as gauge representative uncertainty), which is erroneously identified as radar rainfall uncertainty and therefore called pseudouncertainty. It is crucial to comprehend what percentage of the estimated radar rainfall uncertainty actually stems from such pseudouncertainty rather than radar rainfall itself. For this reason, based on a fully formulated radar rainfall uncertainty model, this study aims to explore how the gauge representative error affects the distribution, spatial dependence, and temporal dependence of hourly accumulated radar rainfall uncertainty, and consequently affects the produced radar rainfall uncertainty band. Three group scenarios that delineate various degrees of gauge representative errors were designed to configure and run the uncertainty model. In the setting of a long-term analysis (almost 7 years) of the Brue catchment in the United Kingdom, we found that the gauge representative error affected the simulation of the marginal distribution of radar rainfall error, and had a considerable effect on temporal dependence estimation of radar rainfall uncertainty. The spread of the rainfall uncertainty band decreased with the growth of the gauge density in a radar pixel. The scenario with the lowest representative error only had 78% uncertainty spread of the scenario that has the largest error. This indicated there was a large impact of the representative error on radar rainfall uncertainty models. It is hoped that more catchments with diverse climate and geographical conditions and more radar data with various spatial scales could be explored by the research community to further investigate this crucial issue. [ABSTRACT FROM AUTHOR]

This paper investigates the algebraic formulation and Nash equilibrium of competitive diffusion games by using semi-tensor product method, and gives some new results. Firstly, an algebraic formulation of competitive diffusion games is established via the semi-tensor product of matrices, based on which all the fixed points (the end of the diffusion process) are obtained. Secondly, using the algebraic formulation, a necessary and sufficient condition is presented for the verification of pure-strategy Nash equilibrium. Finally, an illustrative example is given to demonstrate the effectiveness of the obtained new results. [ABSTRACT FROM AUTHOR]

We report infection of humans with highly pathogenic avian influenza A(H7N9) virus in Shaanxi, China, in May 2017. We obtained complete genomes for samples from 5 patients and from live poultry markets or farms in 4 cities. Results indicate that H7N9 is spreading westward from southern and eastern China. [ABSTRACT FROM AUTHOR]

In this paper, a general class of memristive neural networks with variable delays is studied. By utilizing control theory and nonsmoooth analysis, two sufficient criteria ensuring input-to-state stability of memristive neural networks with variable delays are firstly obtained which are novel and more practical than the previous works in the literature. Finally, a numerical example is given to demonstrate the effectiveness of our results. [ABSTRACT FROM AUTHOR]

This paper analyzes the global convergence of serial Boolean networks (SBNs) via the semi-tensor product of matrices, and presents some new results. Firstly, an algebraic representation is obtained for SBNs, and an algorithm is established for the conversion between the algebraic representations of SBNs and the corresponding Boolean networks. Secondly, the non-equivalence of global convergence between SBNs and the corresponding Boolean networks is revealed, although they have the same fixed points. Thirdly, a necessary and sufficient condition is presented for the global convergence of SBNs. Finally, the obtained results are applied to the evolutionary behaviour analysis of evolutionary networked games with cascading myopic best response adjustment. [ABSTRACT FROM AUTHOR]

In recent years, the stability problems of memristor-based neural networks have been studied extensively. This paper not only takes the unavoidable noise into consideration but also investigates the global exponential stability of stochastic memristor-based neural networks with time-varying delays. The obtained criteria are essentially new and complement previously known ones, which can be easily validated with the parameters of system itself. In addition, the study of the nonlinear dynamics for the addressed neural networks may be helpful in qualitative analysis for general stochastic systems. Finally, two numerical examples are provided to substantiate our results. [ABSTRACT FROM AUTHOR]

The segregation of Cu is crucial for the magnetic properties of 2:17 type SmCo magnets, which is firstly affected by the ordering process during aging treatment. In this research, the ordering process is successfully regulated by doping nano ZrO 2 , which achieves a prolonged ordering process and an increased duration of twin boundaries in 2:17 type SmCo magnets. The continuous migration of twin boundaries in a longer period drives extra Cu to converge towards the cell boundary center, resulting in about 10.52 kOe coercivity only by isothermal aging treatment. The precipitation sequence of the lamellar phase and the cell boundary phase is exchanged. A new understanding of Cu segregation contributes to the development of high performance 2:17 type SmCo magnets. [Display omitted] • The ordering porcess was significantly prolonged with ~17 h in 2:17 type SmCo magnets. • The coercivity with over 1 T was achieved without slow cooling treatment. • The higher efficient of Cu segregation was achieved. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are a class of small, single-stranded, and non-coding RNA molecules that act as post-transcriptional regulators of gene expression, participating in the regulation of a variety of important biological activities. Accumulating evidence suggests that miRNAs are closely related to many major human diseases, especially cancer, and they are considered to be highly promising diagnostic biomarkers and therapeutic targets for disease diagnosis and treatment. To this end, the development of highly accurate, selective, and sensitive strategies for miRNA detection is essential for realizing the early diagnosis of diseases and improving the success rate of treatment. Over the past decade, functional nucleic acid nanostructures have emerged as powerful tools for detecting disease-related miRNAs because of their unique advantages, e.g. , high stability, specificity, and activity. Particularly, thanks to the rapid advancement of systematic evolution of ligands by exponential enrichment (SELEX) technology, it is now feasible to strictly select and reasonably design functional nucleic acids with high specificity and activity toward targets of interest, and thereby enhance the performance of miRNA detection. In this article, we present a comprehensive review of the application of functional nucleic acids including RNA aptamers and DNAzymes selected by SELEX in the construction of biosensors for miRNA detection in recent years. We also provide insights into the impact of the advantages of RNA aptamers and DNAzymes on the enhancement of the performance of miRNA biosensors. We hope this review will serve as a valuable foundation to inspire more exciting research in this emerging field in near future. • MiRNAs are considered to be promising diagnostic biomarkers and therapeutic targets for disease diagnosis and treatment. • SELEX technology could select and design functional nucleic acids (FNA) toward targets of interest. • FNA nanostructures have the advantages of high stability, specificity, and activity. • FNA can be functionalized and generate various types of detection signals for miRNA detection. • The application of RNA aptamers and DNAzymes in the construction of biosensors for miRNA detection is clearly discussed. [ABSTRACT FROM AUTHOR]

• The accurate identification of nerve in ultrasound images is a critical step for effectively processing PNB procedures. How to accurately segment the nerve structure from ultrasound images is not only a medical problem, but also it is a challenging task for computer vision. • A novel brachial plexus segmentation network (named MallesNet) integrated with prior medical knowledge of nerve identification, is proposed to improve the segmentation performance of nerve structure by simultaneously segmenting multi objects in ultrasound images. • The SLCF module is proposed to obtain contrast features at different scales to effectively obtain useful features for small objects. Moreover, the SAG is utilized to add attention on each channel to further improve the network performance. Furthermore, we improve the upsampling mechanism in FPN by adopting the transpose convolution and skip concatenation to fine tune feature maps. Benefiting from these simple yet effective modules, the proposed method achieves better segmentation performance, especially on nerve structure, in comparison with other state-of-the-art methods. • A brachial plexus ultrasound image dataset named UBPD is constructed, which consists of 1055 ultrasound images with four objects (i.e., nerve, artery, vein, and muscle) and their corresponding labeled masks. This dataset dedicates to the research about segmenting nerves and surrounding anatomical structures. Ultrasound-guided injection is widely used to help anesthesiologists perform anesthesia in peripheral nerve blockade (PNB). However, it is a daunting task to accurately identify nerve structure in ultrasound images even for the experienced anesthesiologists. In this paper, a M ulti-object a ssistance based Brachia l P le xus S egmentation Net work, named MallesNet, is proposed to improve the nerve segmentation performance in ultrasound image with the assistance of simultaneously segmenting its surrounding anatomical structures (e.g., muscle, vein, and artery). The MallesNet is designed by following the framework of Mask R-CNN to implement the multi object identification and segmentation. Moreover, a spatial local contrast feature (SLCF) extraction module is proposed to compute contrast features at different scales to effectively obtain useful features for small objects. And the self-attention gate (SAG) is also utilized to capture the spatial relationships in different channels and further re-weight the channels in feature maps by following the design of non-local operation and channel attention. Furthermore, the upsampling mechanism in original Feature Pyramid Network (FPN) is improved by adopting the transpose convolution and skip concatenation to fine-tune the feature maps. The Ultrasound Brachial Plexus Dataset (UBPD) is also proposed to support the research on brachial plexus segmentation, which consists of 1055 ultrasound images with four objects (i.e., nerve, artery, vein and muscle) and their corresponding label masks. Extensive experimental results using UBPD dataset demonstrate that MallesNet can achieve a better segmentation performance on nerves structure and also on surrounding structures in comparison to other competing approaches. [ABSTRACT FROM AUTHOR]

This paper studies the convergence properties of a recently proposed distributed algorithm for weighted least-squares (WLS) estimation in networked systems. This algorithm is suitable for large-scale networks with a vector parameter (variable) in each node of the network. By establishing the connection between this algorithm and the celebrated Gaussian Belief Propagation (BP) algorithm for statistical learning with scalar variables, asymptotic convergence of the algorithm is established under the assumption of generalised block diagonal dominance. This result generalises the known asymptotic convergence result of the Gaussian BP algorithm for networks with scalar variables. By extending the notion of diagonal dominance to block matrices, we are able to generalise the so-called walk-sum approach for convergence analysis of the Gaussian BP algorithm to this distributed WLS algorithm and show a similar asymptotic convergence property for networks with vector parameters. The significance of our work is that it gives theoretical guarantee for the distributed WLS algorithm for a new class of large-scale networked systems with vector parameters. [ABSTRACT FROM AUTHOR]

Raindrop size distribution (RSD) is a key parameter in the Weather Research and Forecasting (WRF) model for rainfall estimation, with gamma distribution models commonly used to describe RSD under WRF microphysical parameterizations. The RSD model sets the shape parameter (μ) as a constant of gamma distribution in WRF double-moment bulk microphysics schemes. Here, we propose to improve the gamma RSD model with an adaptive value of μ based on the rainfall intensity and season, designed using a genetic algorithm (GA) and the linear least-squares method. The model can be described as a piecewise post-processing function that is constant when rainfall intensity is <1.5 mm/h and linear otherwise. Our numerical simulation uses the WRF driven by an ERA-interim dataset with three distinct double-moment bulk microphysical parameterizations, namely, the Morrison, WDM6, and Thompson aerosol-aware schemes for the period of 2013–2017 over the United Kingdom at a 5 km resolution. Observations were made using a disdrometer and 241 rain gauges, which were used for calibration and validation. The results show that the adaptive-μ model of the gamma distribution was more accurate than the gamma RSD model with a constant shape parameter, with the root-mean-square error decreasing by averages of 23.62%, 11.33%, and 22.21% for the Morrison, WDM6, and Thompson aerosol-aware schemes, respectively. This model improves the accuracy of WRF rainfall simulation by applying adaptive RSD parameterization and can be integrated into the simulation of WRF double-moment microphysics schemes. The physical mechanism of the RSD model remains to be determined to improve its performance in WRF bulk microphysics schemes. [ABSTRACT FROM AUTHOR]

• The correlations between the radar rainfall uncertainty and atmospheric fields are strong. • Three radar rainfall uncertainty adjustment schemes are proposed using a LSTM network. • The schemes can decrease the radar–gauge rainfall discrepancy by 22.52%, averagely. The unstable performance of radar rainfall measurement hinders its application in hydrology. Radar rainfall uncertainties induced by atmospheric conditions as raindrops fall from the radar sampling altitude to the ground are critical to radar-based quantitative precipitation estimation. However, these have rarely been considered in previous radar rainfall correction procedures. This study first demonstrates that the correlations between the radar–gauge rainfall discrepancy (RGD) and atmospheric fields are strong. A systematic radar-rainfall adjustment method is then proposed to decrease the discrepancies originating from changes in atmospheric conditions using a long short-term memory (LSTM) network. Three RGD adjustment models were established using a mass-variation scheme, a wind-drift scheme, and a combined mass-variation and wind-drift scheme, based on long-term (2013–2017) data covering most of the United Kingdom. The evaluation results demonstrate that all of the designed models performed well from overall, single-site, and event perspectives. Overall, the combined model, which exhibited the best performance, decreased the root-mean-square error between the rainfall levels measured by radar and gauges by 23.84%, increased Pearson's correlation coefficient from 0.23 to 0.53, and improved the critical success index of the radar rainfall estimation from 0.56 to 0.92. The results indicate that the performances of the proposed models improved with an increase in average relative humidity or wind speed, which demonstrates that they can correct rainfall under high levels of relative humidity and wind speed. This study establishes a highly capable and comprehensive adjustment framework for radar rainfall estimation uncertainty induced by atmospheric conditions, which is essential for achieving high-quality radar products. [ABSTRACT FROM AUTHOR]

Introducing continuous mesochannels into covalent organic frameworks (COFs) to increase the accessibility of their inner active sites has remained a major challenge. Here, we report the synthesis of COFs with an ordered bicontinuous mesostructure, via a block copolymer self‐assembly‐guided nanocasting strategy. Three different mesostructured COFs are synthesized, including two covalent triazine frameworks and one vinylene‐linked COF. The new materials are endowed with a hierarchical meso/microporous architecture, in which the mesochannels exhibit an ordered shifted double diamond (SDD) topology. The hierarchically porous structure can enable efficient hole‐electron separation and smooth mass transport to the deep internal of the COFs and consequently high accessibility of their active catalytic sites. Benefiting from this hierarchical structure, these COFs exhibit excellent performance in visible‐light‐driven catalytic NO removal with a high conversion percentage of up to 51.4 %, placing them one of the top reported NO‐elimination photocatalysts. This study represents the first case of introducing a bicontinuous structure into COFs, which opens a new avenue for the synthesis of hierarchically porous COFs and for increasing the utilization degree of their internal active sites. [ABSTRACT FROM AUTHOR]

Previously we have generated inducible liver tumor models by transgenic expression of an oncogene and robust tumorigenesis can be rapidly induced by activation of the oncogene in both juvenile and adult fish. In the present study, we aimed at chemical intervention of tumorigenesis for understanding molecular pathways of tumorigenesis and for potential development of a chemical screening tool for anti-cancer drug discovery. Thus, we evaluated the roles of several major signaling pathways in krasV12- or Myc-induced liver tumors by using several small molecule inhibitors: SU5402 and SU6668 for VEGF/FGF signaling; IWR1 and cardionogen 1 for Wnt signaling; and cyclopamine and Gant61 for Hedgehog signaling. Inhibition of VEGF/FGF signaling was found to deter both Myc- and krasV12-induced liver tumorigenesis while suppression of Wnt signaling relaxed only Myc- but not krasV12-induced liver tumorigenesis. Inhibiting Hedgehog signaling did not suppress either krasV12 or Myc-induced tumors. The suppression of liver tumorigenesis was accompanied with a decrease of cell proliferation, increase of apoptosis, distorted liver histology. Collectively, our observations suggested the requirement of VEGF/FGF signaling but not the hedgehog signaling in liver tumorigenesis in both transgenic fry. However, Wnt signaling appeared to be required for liver tumorigenesis only in Myc but not krasV12 transgenic zebrafish. [ABSTRACT FROM AUTHOR]

The attitude sensor of the aircraft can give feedback on the perceived flight attitude information to the input of the flight controller to realize the closed-loop control of the flight attitude. Therefore, the fault diagnosis of attitude sensors is crucial for the flight safety of aircraft, in view of the situation that the existing diagnosis methods fail to give consideration to both the diagnosis rate and the diagnosis accuracy. In this paper, a fast and high-precision fault diagnosis strategy for aircraft sensor is proposed. Specifically, the aircraft's dynamics model and the attitude sensor's fault model are built. The SENet attention mechanism is used to allocate weights for the collected time-domain fault signals and transformed time-frequency signals, and then inject the fused feature signals with weights into the RepVGG based on the convolutional neural network structure for deep feature mining and classification. Experimental results show that the proposed method can achieve good precision speed tradeoff. [ABSTRACT FROM AUTHOR]

Studying the characteristics of precipitation diurnal variation is beneficial for understanding precipitation formation and underlying mechanisms. In this study, using hourly rain gauge data from 108 stations in the Yangtze River Delta Urban Agglomeration (YRDUA) from 1980–2021, the diurnal variations of the precipitation amount (PA), precipitation frequency (PF), precipitation duration (PD), and precipitation intensity (PI) were analyzed. The effects of elevation, distance of the station from the east coastline, and urbanization on the characteristics of different precipitation duration events were determined. The results indicated that (1) the spatial distributions of PA, PD, and PF were similar in short-duration (SD), long-duration (LD), and ultra-long-duration (ULD), with high values in the south and low values in the north. Most of PA, PD, and PF showed an increasing trend after breakpoint in LD and ULD, but precipitation characteristics in SD showed a decreasing trend before and after breakpoint; (2) the diurnal cycles of PA presented two comparable peaks in the late afternoon and early morning, which occurred SD and ULD precipitation events, respectively. A single peak in the late afternoon (15:00 local solar time [LST]) occurred during the diurnal cycle of PI. The start and peak times occurred mainly in the afternoon for SD and LD. In contrast, the peak time of ULD mainly occurred in the early morning, accounting for 63% of the stations. The start and peak times of LD and ULD occurred in the early morning mainly along the Yangtze River; (3) from the plains to the mountains, the diurnal peaks of PA and PI had gradual variations from noon to afternoon. In addition, dominant diurnal peak values of PA and PI, which are affected by the distance from the east coast, were observed in the early morning in ULD. The effect of urbanization on the difference between urban and rural areas changed from negative to positive after 2000. In addition, urbanization had a significant impact on SD. After 2000, the increase of PA in urban areas was mainly due to the obvious increase of PD and PF in SD, while the increasing trend of LD and ULD in urban areas was smaller than that in rural areas. [ABSTRACT FROM AUTHOR]

Overwhelming macrophage M1 polarization induced by malfunction of the renin–angiotensin–aldosterone system (RAAS) initiates inflammatory responses, which play a crucial role in various cardiovascular diseases. However, the underlying regulatory mechanism remains elusive. Here, we identified adaptor protein HIP-55 as a critical regulator of macrophage M1 polarization. The expression of HIP-55 was upregulated in M1 macrophage induced by Ang II. Overexpression of HIP-55 significantly promoted Ang II-induced macrophage M1 polarization, whereas genetic deletion of HIP-55 inhibited the Ang II-induced macrophage M1 polarization. Mechanistically, HIP-55 facilitated activator protein-1 (AP-1) complex activation induced by Ang II via promoting ERK1/2 and JNK phosphorylation. Moreover, blocking AP-1 complex activation can attenuate the function of HIP-55 in macrophage polarization. Collectively, our results reveal the role of HIP-55 in macrophage polarization and provide potential therapeutic insights for cardiovascular diseases associated with RAAS dysfunction. • Adaptor protein HIP-55 promotes macrophage M1 polarization triggered by RAAS overactivation. • HIP-55, a key bridge, links macrophage M1 polarization and RAAS overactivation. • Targeting HIP-55 presents a novel therapeutic strategy for preventing cardiovascular diseasesrelated to RAAS dysfunction. [ABSTRACT FROM AUTHOR]

The article titled "Retraction Note: Artificial photoactive chlorophyll conjugated vanadium carbide nanostructure for synergistic photothermal/photodynamic therapy of cancer" has been retracted by the Editors-in-Chief of the Journal of Nanobiotechnology. The retraction was made at the request of the corresponding author due to concerns raised about the images presented in the figures. The editors found similarities and overlaps in the images, and the authors were unable to provide the original data for validation. Springer Nature, the publisher, remains neutral in this matter. [Extracted from the article]

Amidst escalating urbanization and increasing extreme climatic events, strengthening flood resilience strategies in global cities has become imperative. This study introduces an innovative spatiotemporal urban flood simulation model that seamlessly integrates diverse refined and multi-spatiotemporal scales, ranging from 7.5 to 60 min and 100–2000 m, respectively. The model comprises multi-scale radar rainfall inversion (MRI), fine-grained coupled flood simulation model (FGCFS), and transformer-CNN flood prediction (TCFP) modules. Employing the Nanjing urban area as a case study, the model's efficacy is subjected to rigorous assessment. The advantages derived from integrated refinement coupling and boundary conditions through FGCFS and TCFP are accentuated. Impressively, the results underscore the robust performance of radar rainfall inversion across most scales, revealing a correlation coefficient surpassing 0.8 and a root-mean-square error of under 5.2 mm. FGCFS achieves optimal simulated water depth changes at 7.5 min × 500 m resolution, with the Nash efficiency coefficient exceeding 0.69 (0.94 at YS observation point and 0.89 at SXM observation point), alongside percentage deviations below 12.89 (3.59 at SXM observation point and 2.42 at XJL observation point). TCFP's learning proficiency is showcased through error convergence to 0.002 m after twenty iterations, particularly suitable for resolutions below 4 m. Notably, both FGCFS and TCFP demonstrate efficient utilization of resources, enabling streamlined simulations across varying data resolutions. Consequently, our study propels a sophisticated framework harmonizing multi-scale data integration, refinement coupling, and dynamic allocation. Our work extends beyond practical solutions, offering a glimpse into the future of flood simulation modeling, and reaffirming its pivotal role within the realm of environmental research and management. • A spatiotemporal flood simulation model for urban areas is proposed. • Utilizing radar rainfall inversion to enhance urban flood simulations. • The model is applied to a case study in the Nanjing urban area. • It offers a mature framework for integrating multi-scale data, refinement coupling, and dynamic allocation. [ABSTRACT FROM AUTHOR]

Low coefficient of thermal expansion (CTE) in the range of 40–400 °C is a crucial factor for polyimide (PI) films serving as the flexible substrate for display devices. The introduction of hydrogen bonds (H-bonds) is an effective method to obtain high Tg and low in-plane CTE below polyimide (PI) film. However, these H-bonds commonly exhibit low thermal stability and would be ruptured at high temperature (>300 °C), which leads to a remarkable increase of CTE. Herein, we report a strategy to improve thermal stability of H-bonds at the high temperature via intermolecular crosslinking. For neat PI, its in-situ FTIR results confirm severe dissociation of H-bonds above 300 °C, While after the crosslinking reaction, the content of strong H-bonds at 400 °C is 110% higher than that of neat PI, which indicates this intermolecular crosslinking restrains dissociation of H-bonds. Correspondingly, CTE values of crosslinked PI films at 300oC–400 °C are sharply decreased from 33.8 ppm/K to 6.0 ppm/K. Moreover, decrease of in-plane orientation accompanying lower CTEs in crosslinked PI deviates from common rule reported in linear PIs, implying the important roles of H-bonds and crosslinking. More over, the contribution of H-bonds and crosslink to the decrease of CTE are performed by Pearson correlation analysis and the results indicate that the decrease of CTE in crosslinked PIs at low temperatures is completely attributed to confinement effect of crosslinking, but contribution of stable H-bonds becomes more prominent above 300 °C. Consequently, the obtained PI films exhibit ultra low CTE (1.9 ppm/K) at the range of 40oC–400 °C, along with high Tg (>450 °C) exhibiting great potential for flexible-display substrates. Schematic diagram of effect of chemical crosslinking and hydrogen bonding interactions on dimensional stability is presented here. At low temperature (40–300 °C), hydrogen bonding dissociation is not so dramatic and group vibration is inhibited to some degree. Thus, CTE of PI-0 is very low (2.9 ppm/K) in this temperature range. At high temperature, dissociation of most of hydrogen bonds weakens interchain interaction and consequently intensifies group vibration and dimensional expansion, leading to high CTEs (33.8 ppm/K). Introducing a small portion of crosslinking sites, confinement of covalent bond suppresses group vibration and consequently inhibits extension of distance between hydrogen bonding donors and accepters at high temperature, leading to the enhancement of stability of hydrogen bonding. Those stable hydrogen bonds further promote dimensional stability especially at high temperature, leading to significant decrease of CTE of PI-DCX-0.35 from 33.8 ppm/K to 6.0 ppm/K in the range of 300oC–400 °C. Image 1 • Stability of H-bonds in PI films at high temperature is obviously enhanced via confinement effect of chemical crosslinking. • It was verified that, in heating procession, s-H-bonds are weakened, which induces vibration of benzimidazole ring and imide ring. • It was verified by Pearson correlation analysisthat contribution of stable H-bonds on decrease of CTE becomes prominent only above 300 °C. [ABSTRACT FROM AUTHOR]

• IRF7 is highly expressed in colon tissues of mice with intestinal inflammation. • IRF7 induces macrophage M1 polarization to enhance intestinal inflammation. • IRF7 promotes macrophage M1 polarization by activating NLR signaling pathway. • NF-κB p65 and SETD1B synergistically induce histone methylation to upregulate IRF7. • This study offers a theoretical basis for preventing intestinal inflammation. Macrophages exhibit distinct phenotypes that are pro-inflammatory (M1) or anti-inflammatory (M2) in response to inflammation. In this study, we tried to identify the roles and mechanisms of interferon regulatory factor 7 (IRF7) in modulating the phenotypes of macrophages in lipopolysaccharide (LPS)-induced intestinal inflammation. The mouse model of intestinal inflammation was induced by lipopolysaccharide (LPS), and mouse bone marrow-derived macrophages (BMDMs) and mouse intestinal epithelial cells were selected for experimental verification in vitro. Results demonstrated that IRF7 was highly expressed in the mouse model of intestinal inflammation, while IRF7 deficiency repressed macrophage M1 polarization and attenuated intestinal inflammation in mice. p65 and SET domain bifurcated 1 (SETDB1) synergistically promoted histone 3 lysine 4 trimethylation (H3K4me3) methylation to elevate IRF7 expression, which activated the Nod-like receptor (NLR) pathway to induce macrophage M1 polarization. Through this mechanism, IRF7 in BMDMs functioned to accelerate intestinal epithelial cell apoptosis and their release of pro-inflammatory proteins. Furthermore, the promoting effect of p65 and SETDB1 on LPS-induced intestinal inflammation was validated in vivo. To sum up, NF-κB p65 and SETDB1 facilitated IRF7-mediated macrophage M1 polarization, thereby aggravating the LPS-induced intestinal inflammation. Hence, this study highlights the appealing value of these factors as anti-inflammatory targets. [ABSTRACT FROM AUTHOR]

A novel grain boundary diffusion process (GBDP) with low-pressure technology was employed to develop RE-Fe-B sintered magnets with a thickness of 2 mm. The gas pressure promotes Tb atoms to permeate the deeper of the magnets due to the uniform and continuous RE-rich phase, increasing the diffusion depth from 345 µm to 880 µm. According to the results acquired by computation, diffusion coefficients (D) of vacuum grain boundary diffusion process (VGBDP) and low-pressure grain boundary diffusion process (LPGBDP) rose from 2.27 × 10−13 m2/s to 2.95 × 10−12 m2/s, respectively. The increasing magnetocrystalline anisotropic field (122.2 kOe) and the optimized microstructure jointly determine the improvement of coercivity, which increases significantly from 17.47 kOe to 27.73 kOe by low-pressure diffusion treatment, 58.7% higher than the original magnet. Meanwhile, the homogeneous grain boundary phase and the thicker Tb-shell were mainly responsible for the excellent temperature stability in 20°C-200°C. This work proposes a viable method for preparing the RE-Fe-B magnets with slight HREE and high comprehensive performance. • High-performance Nd-Fe-B permanent magnets are prepared by low-pressure GBDP method. • Gas pressure promotes the diffusion coefficient and depth of Tb elements in magnets. • The homogeneous distribution of Nd-rich phase weakens the exchange coupling between adjacent main phase. • Low-pressure diffused magnets can operate in extreme temperatures. [ABSTRACT FROM AUTHOR]