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Abstract Frequent forest fires, driven by hotter and drier climates, threaten biodiversity and human health, causing significant economic losses, air pollution, soil erosion, and degeneration. Current active and passive fire protection methods often suffer from environmental pollution, poor flexibility, and limited availability in remote areas. However, fast-acting surface flame retardants for passive forest fire protection, particularly for foliage, are rare. Herein, we report an easily obtainable gelatin-based fire spray, which resulted in 1.8 and 16.3-fold extension in ignition time, 34% and 39% reductions in total heat release, 78% and 92% reductions in fire growth index for dead and fresh leaves, respectively. After the fire warning is suppressed, for instance by rain, the sprayed substances can decompose and provide nitrogen and phosphorus as leaf and soil fertilizers without affecting soil microbial function, which increase plant net photosynthesis by 84% and effective nitrogen and phosphorus by 664% and 140%, respectively. Our green flame retardant and fertilizer material allows for simultaneous tree fire protection and growth.

Abstract Background To investigate the quantitative vascular and structural differences in the foveal region of the eyes in retinopathy of prematurity children with or without anti-vascular endothelial growth factor (VEGF) therapy and healthy children using optical coherence tomography angiography (OCTA). Methods This cross-sectional study analyzed 75 eyes from 44 subjects, categorized into four groups: ROP children treated with Conbercept or Ranibizumab, spontaneously regressed ROP, and healthy age-matched children. Using spectral-domain OCT and OCTA, we assessed parameters like central foveal thickness (CFT), foveal avascular zone (FAZ), superficial/deep capillary plexus (SCP/DCP), and choroidal vessel density (VD) at the fovea. Correlations between foveal microvasculature, preterm status and visual acuity were evaluated. Results Significant differences were found in FAZ area, CFT, and VD-SCP (parafoveal) among the groups. The FAZ area was smaller in ROP children (with/without treatment) than in healthy counterparts(p = 0.009). CFT was higher in the Ranibizumab and spontaneously regressed groups compared to healthy ones (p = 0.043, p = 0.037), while Conbercept-treated children showed no significant difference (p = 0.886). Foveal VD trends were higher in groups A, B, and C compared to group D. FAZ area correlated negatively with CFT, VD-SCP (foveal), and VD-DCP (foveal) (p

Abstract On the basis of the law of conservation of energy, the three stages of rock creep are analyzed. The reasons for the difficulty in studying the accelerated creep stage of rocks using the traditional creep model are expounded. The triaxial creep deformation law and critical point parameter values of rocks are obtained by carrying out rock creep tests under different confining pressures. Based on strain energy theory, the law of conservation of energy, and Perzyna viscoplastic theory, a creep constitutive model, which can describe the whole process of primary creep, steady-state creep, and accelerated creep, is established. Results show that the model can well reflect the creep characteristics of rocks, especially when the load of rocks is greater than the long-term strength. It has an obvious effect on highlighting the accelerated creep stage of rocks. The fitting degree of the creep model curve and test curve is considerably greater than that of the Nishihara model curve and test curve. The model not only describes the whole process of rock primary creep, steady-state creep, and accelerated creep thoroughly but also compensates for the shortcomings of traditional models in describing accelerated creep. This model can provide a theoretical basis for further revealing the objective law of rock creep.

Abstract Early screening of breast cancer through image recognition technology can significantly increase the survival rate of patients. Therefore, breast cancer pathological image is of great significance for medical diagnosis and clinical research. In recent years, numerous deep learning models have been applied to breast cancer image classification, with deep CNN being a typical representative. Due to the use of multi-depth small convolutional kernels in mainstream CNN architectures such as VGG and Inception, the obtained image features often have high dimensionality. Although high dimensionality can bring more fine-grained features, it also increases the computational complexity of subsequent classifiers and may even lead to the curse of dimensionality and overfitting. To address these issues, a novel embedded kernel CNN principal component feature fusion (CNN-PCFF) algorithm is proposed. The constructed kernel function is embedded in the principal component analysis to form the multi-kernel principal component. Multi-kernel principal component analysis is used to fuse the high dimensional features obtained from the convolution base into some representative comprehensive variables, which are called kernel principal components, so as to achieve the purpose of dimensionality reduction. Any type of classifier can be added based on multi-kernel principal components. Through experimental analysis on two public breast cancer image datasets, the results show that the proposed algorithm can improve the performance of the current mainstream CNN architecture and subsequent classifiers. Therefore, the proposed algorithm in this paper is an effective tool for the classification of breast cancer pathological images.

AimsHeart failure is a critical health issue with high mortality rates. The blood urea nitrogen/creatinine ratio (BCR) has proven more effective at predicting outcomes in heart failure patients than individual assessments of each marker. Nevertheless, the implications of varying BCR levels for outcomes among heart failure patients remain to be fully understood. This study explores the impact of BCR on the outcomes of these patients.Methods and resultsEmploying a retrospective cohort design at a single center, this study examined 1,475 heart failure patients from the Medical Information Mart for Intensive Care (MIMIC-III) database, categorized into four quartiles based on their BCR levels. We analyzed survival outcomes using Kaplan–Meier and Cox proportional hazards models, supplemented by restricted cubic splines to elucidate detailed associations. The average age of the patients was 69.52 years, with males constituting 55.6% of the cohort. As BCR values escalated, the average hospital stay increased from 9.64 to 14.15 days, and average survival decreased from 685.11 to 412.68 days. Patients in the highest BCR quartile faced the most severe mortality rates, with 18.8% in-hospital and 78.3% long-term mortality. Nonlinear regression revealed a U-shaped relationship between BCR and mortality: at BCR levels below 12.5, there was no significant correlation with long-term mortality; between 12.5 and 22, BCR appeared to exert a protective effect; and above 22, it emerged as a significant risk factor.ConclusionsAdmission BCR values are non-linearly associated with mortality in heart failure patients, suggesting its utility as a prognostic tool in critical care.

Pancreatic cancer (PC) is a highly lethal malignancy with rapid progression and poor prognosis. Despite the widespread use of gemcitabine (Gem)-based chemotherapy as the first-line treatment for PC, its efficacy is often compromised by significant drug resistance. 1,2,3,4,6-Pentagaloyl glucose (PGG), a natural polyphenol, has demonstrated potential in sensitizing PC cells to Gem. However, its clinical application is limited by poor water solubility and bioavailability. In this study, we developed a novel PGG-based nanocarrier (FP) using a straightforward, one-step self-assembly method with Pluronic F127 and PGG. Our results showed that FP induced DNA damage and immunogenic cell death (ICD) in both in vitro cell experiments and patient-derived organoid models, exhibiting potent anti-tumor effects. Furthermore, in mouse KPC and PDX models, FP, when combined with Gem, showed enhanced Gem sensitization compared to pure PGG, largely due to increased DNA damage and ICD induction. These findings demonstrate the potential of FP to improve the stability and utilization of PGG as effective Gem sensitizers in the treatment of pancreatic cancer, providing a promising pathway for clinical application and translational research.

Abstract Background While small extracellular vesicles (sEVs)-derived circular RNAs (circRNAs) have been emerged as significant players in cancer, the function and underlying mechanism of sEVs-derived circRNAs in anti-cancer immunity remain unclear. Methods Gastric cancer (GC)-derived circRNAs were identified using RNA-seq data from GEO datasets and quantitative reverse transcription polymerase chain reaction (qRT-PCR), RNA immunoprecipitation, dual-luciferase assay, and bioinformatics analysis were performed to investigate the regulatory axis. Transwell assay, wound healing assay, cell counting kit-8 (CCK-8) assay, and xenograft models were used to evaluate its role in GC progression in vivo and in vitro. The delivery of specific circRNAs into sEVs were verified through electron microscopy, nanoparticle tracking analysis (NTA) and fuorescence in situ hybridization (FISH). Flow cytometric analysis and immunohistochemical staining were conducted to find out how specific circRNAs mediated CD8+ T cell exhaustion and resistant to anti-programmed cell death 1 (PD-1) therapy. Results We identified that circ_0001947, packaged by GC-derived sEVs, was obviously elevated in GC and was associated with poor clinical outcome. High circ0001947 level augmented the proliferation, migration, and invasion of GC cells. Mechanistically, circ0001947 sponged miR−661 and miR−671−5p to promote the expression of CD39, which further facilitated CD8+ T cell exhaustion and immune resistance. Conversely, blocking circ_0001947 attenuated CD8+ T cell exhaustion and increased the response to anti-PD−1 therapy. Conclusions Our study manifested the therapeutic potential of targeting sEVs-transmitted circ_0001947 to prohibit CD8+ T cell exhaustion and immune resistance in GC.

Abstract Xanthomonas oryzae pv. oryzae (Xoo) causes bacterial blight in rice. Polyhydroxyalkanoates (PHAs) consitute a diverse group of biopolyesters synthesized by bacteria under nutrient-limited conditions. The phaC gene is important for PHA polymerization. We investigated the effects of phaC gene mutagensis in Xoo strain PXO99A. The phaC gene knock-out mutant exhibited reduced swarming ability relative to that of the wild-type. Under conditions where glucose was the sole sugar source, extracellular polysaccharide (EPS) production by ΔphaC declined by 44.8%. ΔphaC showed weak hypersensitive response (HR) induction in the leaves of non-host Nicotiana tabacum, concomitant with downregulation of hpa1 gene expression. When inoculated in rice leaves by the leaf-clipping method, ΔphaC displayed reduced virulence in terms of lesion length compared with the wild-type strain. The complemented strain showed no significant difference from the wild-type strain, suggesting that the deletion of phaC in Xoo induces significant alterations in various physiological and biological processes. These include bacterial swarming ability, EPS production, transcription of hrp genes, and glucose metabolism. These changes are intricately linked to the energy utilization and virulence of Xoo during plant infection. These findings revealed involvement of phaC in Xoo is in the maintaining carbon metabolism by functioning in the PHA metabolic pathway.

Abstract Background Postoperative respiratory adverse events are the most common perioperative complications in pediatric anesthesia, particularly prevalent in children undergoing tonsillectomy and adenoidectomy, with an incidence rate as high as 50%. The choice of anesthetic induction regimen directly influences the incidence of respiratory adverse events during the induction period. However, this effect seems to have minimal impact on postoperative outcomes. The occurrence rate of postoperative respiratory adverse events is likely more closely associated with the anesthetic maintenance phase, yet this relationship remains uncertain at present. Methods The objective of this study was to assess the impact of different anesthetic maintenance regimens on postoperative respiratory adverse events in pediatric patients undergoing tonsillectomy and adenoidectomy. The AmPRAEC study is a multicenter, randomized, double-blind controlled trial. A total of 717 pediatric patients were recruited from 12 medical centers and randomly assigned to three groups: group A (intravenous maintenance group, receiving propofol infusion); group B (intravenous-inhalational combination group, maintained with 1% sevoflurane combined with propofol); and group C (inhalational maintenance group, maintained with 2–3% sevoflurane inhalation). The primary outcome measure was the incidence rate of postoperative respiratory adverse events. Discussion This clinical trial aims to elucidate the impact of various anesthetic maintenance regimens on postoperative respiratory adverse events in pediatric patients. The outcomes of this study are anticipated to facilitate anesthesiologists in devising more comprehensive perioperative management strategies, enhancing comfort, and improving the clinical outcomes for this patient population. Trial registration Chinese Clinical Trial Registry ( http://www.chictr.org.cn ) ChiCTR2300074803. Registered on August 16, 2023.

Chronic kidney disease (CKD) can cause gut microbiota dysbiosis and decreasing production of short-chain fatty acids (SCFAs), which aggravate the injury of kidney. It has been found that a variety of Chinese medicine polysaccharides can regulate gut microbiota, especially probiotics, and have beneficial effects on human health. Astragalus polysaccharide (APS) is a major component of Astragalus aceus. The aim of this study was to investigate whether APS can regulate gut microbiota–SCFAs to slow the progression of CKD. Adenine-induced CKD mice (Ade) were established and APS was treated. The renal protection of APS on CKD mice was evaluated by renal function and pathological staining of renal tissues. Feces samples were collected for 16SrRNA sequence and LC–MS/MS analysis. Kidney G protein-coupled receptor (GPR) levels were also detected in renal tissue. APS supplementation can reduce serum creatinine and urea nitrogen levels in mice model (Ade) and attenuate renal tubular interstitial injury and renal fibrosis. Further application of 16SrRNA sequencing showed that the abundance of SCFA producing bacteria, such as Kineothrix, Faecalibaculum, Akkermansia, Lactobacillus, and Roseburia, was upregulated after APS treatment. Fecal LC–MS/MS detection showed that the levels of acetate, propionate and butyrate in Ade mice increased after APS supplementation. The detection of renal GPRs showed that APS supplementing could significantly increase the levels of renal GPR41 and GPR43, and also partially increase the levels of GPR109a in Ade mice. Our research confirms that APS supplementation can upregulate the abundance of SCFA producing bacteria and increase SCFA levels to attenuate renal tubular interstitial injury and fibrosis via GPRs.

Background In-stent restenosis (ISR) is a crucial factor that affects the long-term efficacy of intracranial bare metal stent (BMS) implantation for intracranial atherosclerotic stenosis (ICAS). Patients with intracranial ISR are at a high risk of recurrent ischaemic events. The NOVA intracranial drug-eluting stent (DES) trial demonstrates that a DES can reduce ISR and stroke recurrence after intracranial bare stent implantation. However, the application of balloon-expanded DES necessitates specific vascular conditions. The objective of this study is to assess the safety and efficacy of self-expanding DES for treating symptomatic ICAS (sICAS).Methods This is a prospective, multicentre, randomised, controlled, superiority clinical trial that is conducted in 16 clinical trial centres in China. This study aims to recruit 208 patients with sICAS. Eligible subjects are randomly assigned to two groups at a ratio of 1:1. The experimental group is treated with DES (Xinwei intracranial DES system). The control group is treated with BMS (Wingspan intracranial stent system). All subjects are followed up within 7 days after surgery or before discharge; 30 days after surgery; and 6, 12 and 24 months after surgery. The primary outcome of the trial is the incidence of ISR at 6 months after surgery to verify the safety and efficacy of intracranial DESs. After 6 months of follow-up, the clinical summary report is issued for product registration application, and the follow-up of 12 months and 24 months after operation is conducted to evaluate the medium and long-term efficacy.Ethics and dissemination The study involving human participants is reviewed and approved by the Ethics Committee of Drugs (devices) Clinical Experiment in Henan Provincial People’s Hospital (reference number: AF/SC-08/05.0) and other research centres participating in the clinical trial (supplemental file 2). The results yield from this study will be presented at international conferences and sent to a peer-reviewed journal to be considered for publication.Trial registration number Registered on 2 November 2023 with Chinese clinical trial registry. Registration number is ChiCTR2300077271.

ObjectiveTo investigate the role of systemic immune-inflammation index (SII) in complete pathological response (pCR) of breast cancer patients after neoadjuvant chemotherapy, and to establish and validate a nomogram for predicting pCR.MethodsBreast cancer patients were selected from the First Affiliated Hospital of Xi’an Jiaotong University from January 2020 to December 2023. The optimal cut-off value of SII was calculated via ROC curve. The correlation between SII and clinicopathological characteristics was analyzed by Chi-square test. Logistic regression analysis was performed to evaluate the factors that might affect pCR. Based on the results of Logistic regression analysis, a nomogram for predicting pCR was established and validated.ResultsA total of 112 breast cancer patients were included in this study. 33.04% of the patients achieved pCR after neoadjuvant therapy. Chi-square test showed that SII was significantly correlated with pCR (P=0.001). Logistic regression analysis suggested that Ki-67 (P=0.039), therapy cycle (P

Gastric cancer, a common and severe malignancy, is associated with unfavorable outcomes and limited therapeutic options. The exploration of the potential link between plasma histone-modifying enzymes and gastric cancer through Mendelian randomization (MR) analysis offers an opportunity to identify new therapeutic targets and biomarkers. In this study, data on plasma histone-modifying enzymes were obtained from the International Working Unit Open genome-wide association studies project, and summary statistics of gastric cancer from the FinnGen study were analyzed. Forward and inverse MR were performed to determine the causal relationship between plasma histone-modifying enzymes and gastric cancer. The principal methodology for MR is the inverse variance weighted (IVW) method. Additionally, a sensitivity analysis was performed to determine the robustness of the findings. Finally, bioinformatics was used for the preliminary functional analysis. Our forward MR analysis revealed that the plasma Set1/Ash2 histone methyltransferase complex subunit ASH2 (ASH2L) was positively associated with gastric cancer risk, and the histone-lysine N-methyltransferase SETMAR (SETMAR) was negatively associated. Inverse MR analysis revealed that gastric cancer incidence was negatively correlated with the expression of plasma histone acetyltransferase KAT6A (KAT6A). These findings were consistent across different statistical methods and were deemed unlikely to have been distorted by horizontal pleiotropy. Furthermore, bioinformatics analysis indicated that ASH2L, SETMAR, and KAT6A are differentially expressed in various tumors and are significantly correlated with both the prognosis of gastric cancer and the infiltration of various immune cells. Thus, plasma histone-modifying enzymes may be causally linked to gastric cancer, and ASH2L, SETMAR, and KAT6A could play crucial roles as biomarkers and therapeutic targets in managing gastric cancer.

In order to obtain the creep characteristics of the surrounding rock of the Dianzhong water diversion tunnel and to study the long-term stability of the surrounding rock of the tunnel, a fully automated triaxial developed by Wuhan Institute of Geotechnics, Chinese Academy of Sciences, is used to carry out the uniaxial creep test of green mud shale. The axial creep curve and isochronous stress-strain curve of green mud shale are obtained. And the long-term strength value of green mud shale is determined based on the characteristics of isochronous stress-strain curve. Based on the classical creep curve characteristics and a large number of experimental creep curves, it is found that the equations describing the attenuation creep curve can be treated by symmetry. Therefore, it is assumed that the acceleration curve and the decay creep curve are symmetric about the midpoint of the stable creep curve. An accelerated creep model based on the symmetry of the creep curve is obtained. And a set of methods to determine the parameters of the creep model is proposed based on the characteristics of the creep test curve. Finally, the parameters introduced into the accelerated creep model for sensitivity analysis. The parameters introduced into the model have a clear physical meaning. The results show that with the increasing axial stress, the instantaneous strain value and creep deformation value of the rock are also increasing, and the instantaneous strain of the rock under the first stage load accounts for the largest ratio of the total creep deformation. The established creep model can not only well describe the attenuation creep and stable creep deformation law of green mud shale, it also better make up for the defects of the Nishihara model that cannot describe the accelerated creep. The agreement between the model curve and the test curve is much higher than that between the model and the test curve, and the correlation coefficients between the model curve and the test curve under different stresses are all above 0.90. Meanwhile, the validation of different types of test curves and model curves also shows that the model can be applied to the prediction of creep curves of different types of rocks. Finally, the value of parameter j is introduced to control the deformation rate and the time to enter accelerated creep. The value of parameter k controls the creep time and the creep rate in the accelerated stage.

Abstract Background Microtia is reported to be one of the most common congenital craniofacial malformations. Due to the complex etiology and the ethical barrier of embryonic study, the precise mechanisms of microtia remain unclear. Here we report a rare case of microtia with costal chondrodysplasia based on bioinformatics analysis and further verifications on other sporadic microtia patients. Results One hundred fourteen deleterious insert and deletion (InDel) and 646 deleterious SNPs were screened out by WES, candidate genes were ranked in descending order according to their relative impact with microtia. Label-free proteomic analysis showed that proteins significantly different between the groups were related with oxidative stress and energy metabolism. By real-time PCR and immunohistochemistry, we further verified the candidate genes between other sporadic microtia and normal ear chondrocytes, which showed threonine aspartase, cadherin-13, aldolase B and adiponectin were significantly upregulated in mRNA levels but were significantly lower in protein levels. ROS detection and mitochondrial membrane potential (∆ Ψ m) detection proved that oxidative stress exists in microtia chondrocytes. Conclusions Our results not only spot new candidate genes by WES and label-free proteomics, but also speculate for the first time that metabolism and oxidative stress may disturb cartilage development and this might become therapeutic targets and potential biomarkers with clinical usefulness in the future.

Abstract Traffic flow prediction based on spatial–temporal data plays a vital role in traffic management. However, it still faces serious challenges due to the complex spatial–temporal correlation in nonlinear spatial–temporal data. Some previous methods have limited ability to capture spatial–temporal correlation, and ignore the quadratic complexity problem in the traditional attention mechanism. To this end, we propose a novel spatial–temporal combination and multi-head flow-attention network (STCMFA) to model the spatial–temporal correlation in road networks. Firstly, we design a temporal sequence multi-head flow attention (TS-MFA), in which the unique source competition mechanism and sink allocation mechanism make the model avoid attention degradation without being affected by inductive biases. Secondly, we use GRU instead of the linear layer in traditional attention to map the input sequence, which further enhances the temporal modeling ability of the model. Finally, we combine the GCN with the TS-MFA module to capture the spatial–temporal correlation, and introduce residual mechanism and feature aggregation strategy to further improve the performance of STCMFA. Extensive experiments on four real-world traffic datasets show that our model has excellent performance and is always significantly better than other baselines.

Optical sensors serve as pivotal components in the realm of non-invasive blood glucose measurement (NBGM) devices, where their efficacy directly influences the detection of weak glucose signals. This research introduces three fundamental design key points tailored for diffuse reflectance optical sensors employed for NBGM: depth resolution, detection signal-to-noise ratio, and human–sensor interface coupling. Guided by these design key points, we presented feasible design proposals for near-infrared diffuse reflectance sensors operating in the range of 1000–1700 nm. As an example, a sensor composed of five-ring detectors with a ring-shaped mask were made and tested on human skin. The innovative sensor developed herein holds promising potential for NBGM.

Remote sensing images captured by satellites play a critical role in Earth observation (EO). With the advancement of satellite technology, the number and variety of remote sensing satellites have increased, which provide abundant data for precise environmental monitoring and effective resource management. However, existing satellite imagery often faces a trade-off between spatial and temporal resolutions. It is challenging for a single satellite to simultaneously capture images with high spatial and temporal resolutions. Consequently, spatiotemporal fusion techniques, which integrate images from different sensors, have garnered significant attention. Over the past decade, research on spatiotemporal fusion has achieved remarkable progress. Nevertheless, traditional fusion methods often encounter difficulties when dealing with complicated fusion scenarios. With the development of computer science, deep learning models, such as convolutional neural networks (CNNs), generative adversarial networks (GANs), Transformers, and diffusion models, have recently been introduced into the field of spatiotemporal fusion, resulting in efficient and accurate algorithms. These algorithms exhibit various strengths and limitations, which require further analysis and comparison. Therefore, this paper reviews the literature on deep learning-based spatiotemporal fusion methods, analyzes and compares existing deep learning-based fusion algorithms, summarizes current challenges in this field, and proposes possible directions for future studies.

In non-invasive blood glucose measurement (NBGM) based on near-infrared spectroscopy, fluctuations in blood flow represent a primary source of interference. This paper proposes a local blood flow pre-stimulation method in which the local skin is heated to dilate blood vessels and increase blood flow. This approach aims to mitigate the impact of environmental temperature variations, emotional fluctuations, and insulin secretion on blood flow, thereby enhancing the accuracy of glucose measurement. To evaluate the effectiveness of this method, a blood flow interference experiment was conducted to compare the stability of the measured spectra with and without blood flow pre-stimulation. The results demonstrated that the pre-stimulation method presents good anti-interference capabilities. Furthermore, 45 volunteers underwent oral glucose tolerance tests (OGTTs) as a part of the validation experiments. In these tests, the forearm skin blood flow of 24 volunteers was pre-stimulated using elevated temperature, while the skin of the remaining 21 subjects was maintained at a natural temperature level without stimulation. The results indicate that compared to the non-stimulated condition, the correlation between the optical signal at 1550 nm and blood glucose levels was significantly enhanced under the pre-stimulation condition. Furthermore, the root mean square error (RMSE) of the linear prediction model was reduced to just 0.92 mmol/L. In summary, this paper presents a feasible blood flow control strategy that effectively stabilizes internal blood flow, thereby improving the accuracy of NBGM.

Driven by the necessitates of wide-area quantum secure communication networks, ground-to-satellite quantum key distribution (QKD) has been highlighted in the field of quantum information. Continuous variable QKD (CV-QKD) shows the advantages of a high secure key rate generation and compatibility in the fiber channel, but the communication range is limited by low attenuation tolerance. In this study, the feasibility of the uplink CV-QKD for Very Low Earth Orbit satellite is studied, and the influence of practical factors such as atmospheric turbulence and beam pointing errors under dynamic time-varying satellite orbital parameters is analyzed to model realistic transmission channels. A parameter optimization scheme for orbital parameters, spot size, receiving telescope aperture, and modulation variance has been proposed to enhance the performance of the actual uplink CV-QKD, providing a reference for parameter selection in CV-QKD experiments.

The exocyst complex in eukaryotic cells modulates secretory vesicle transportation to promote exocytosis. The exocyst is also required for the hyphal growth and pathogenic development of several filamentous phytopathogens. Obligate biotrophic powdery mildew fungi cause considerable damage to many cash crops; however, the exocyst’s roles in this group of fungi is not well studied. To verify the functions of the exocyst in powdery mildew fungus, we identified two exocyst subunits, EqSec5 and EqSec6, from Erysiphe quercicola, a powdery mildew fungus that infects the rubber tree Hevea brasiliensis. When GFP-fused EqSec5 and EqSec6 were introduced into E. quercicola and another phytopathogenic fungus, Magnaporthe oryzae, they primarily localized to the hyphal tip region. Inducing gene silencing of EqSec5 or EqSec6 caused growth and infection defects, and those defects could not be fully restored under the NADPH oxidase inhibitor treatment to the plant. The silenced strains also induced the host defense response including reactive oxygen species accumulation and callose deposition. The silencing of EqSec5 or EqSec6 also inhibited the secretion of the effector protein EqIsc1, interrupting plant salicylic acid biosynthesis. Yeast two-hybrid and gene overexpression assays suggested that EqSec5 and EqSec6 interact with each other and can complement each other’s function during host infection. Overall, our study provides evidence that the exocyst in this powdery mildew fungus facilitates effector secretion, hyphal growth, and infection.

The effects of starting mode and outlet temperature of heat sink (OTHS) on the starting performances of direct-heated heat pump water heater using natural blend were investigated experimentally. The results indicated that both starting mode and OTHS had notable impact on starting time of transient performance parameters. Both warm start and lower OTHS helps to quickly obtain hot water at the target temperature, mainly because the system startup time in the warm start was 16.73 % shorter than that in the cold start and the system gained the shortest startup time (1015 s) in low temperature condition. The transient heat sink outlet temperature had a rapid temperature rise section and a slow temperature rise section (STRS), and the STRS consumed 56.58 %–66.67 % of the system starting time, so the improvement of STRS is the key to realize the fast startup. The effects of startup mode on the trends of transient performance parameters were memorably different, but the OTHS had no apparent effect on their trends. The transient refrigerant pressures and transient refrigerant temperatures had the fluctuations. The transient suction pressures had the minimum values (0.3925–0.5575 MPa), and both cold start mode and higher OTHS resulted in a decrease in the minimum value.

As a rapidly expanding family of 2D materials, MXenes have recently gained considerable attention. Herein, by developing a coating method that enables transfer‐free and layer‐by‐layer film coating, the nonlinear optical absorption (NOA) of Ti3C2Tx MXene films is investigated. Using the Z‐scan technique, the NOA of the MXene films is characterized at ≈800 nm. The results show that there is a strong and layer‐dependent NOA behavior, transitioning from reverse saturable absorption (RSA) to saturable absorption (SA) as the layer number increases from 5 to 30. Notably, the nonlinear absorption coefficient β changes significantly from ≈7.13 × 102 cm GW−1 to ≈−2.69 × 102 cm GW−1 within this range. The power‐dependent NOA of the MXene films is also characterized, and a decreasing trend in β is observed for increasing laser intensity. Finally, the NOA of 2D MXene films at ≈1550 nm is characterized by integrating them onto silicon nitride waveguides, where an SA behavior is observed for the films including 5 and 10 layers of MXene, in contrast to the RSA observed at ≈800 nm. These results reveal intriguing nonlinear optical properties of 2D MXene films, highlighting their versatility and potential for implementing high‐performance nonlinear photonic devices.

This study investigates the feasibility of using mudstone to enhance poorly graded gravel in certain arid regions of the S21 Altay-Urumqi Highway project in Xinjiang. Despite mudstone typically being considered a poor-quality rock, its combination with higher-performance materials like cement, lime, and fly ash can stabilize expansive soils for use as roadbed fill. In the experiments, 30% and 40% mudstone were added to the gravel mixture. The experiments were compared with unmodified K80 and 35% crushed rock mixes. The findings reveal that adding 30% mudstone substantially increased the California Bearing Ratio (CBR) of the gravel mix by over 20%. However, excessive mudstone inclusion could weaken load-bearing capacity. Moreover, mudstone-modified specimens exhibited superior unconfined compressive strength (UCS), splitting strength, compressive resilience modulus (CRM), drying shrinkage resistance, and temperature shrinkage resistance. Under optimum cement dosage, the UCS of mudstone-modified specimens outperformed unmodified specimens, consistently surpassing fly ash-altered groups. Although mixed fly ash initially exhibited lower strength, it gradually approached cement-stabilized strength with an extended curing time. Incorporating crushed stone into the grading curve significantly increased splitting strength due to its high strength and hardness. In contrast, adding mudstone introduced a notable proportion of fine aggregates, resulting in a looser grading skeleton prone to early cracking. This research demonstrates that mudstone enhancement significantly improves roadbed performance, including increased CBR, splitting strength, and crack resistance. The use of mudstone in arid desert areas enhances overall performance while reducing shrinkage coefficients. The suggested approach for semi-rigid pavements in arid deserts recommends specific mineral proportions, various aggregate sizes, an appropriate amount of cement, and 30% mudstone to create dense structures with a higher quantity of coarse aggregate.

BackgroundPepper veinal mottle virus (PVMV) belongs to the genus Potyvirus within the family Potyviridae and is a major threat to pepper production, causing reduction in yield and fruit quality; however, efficient pesticides and chemical treatments for plant protection against viral infections are lacking. Hence, there is a critical need to discover highly active and environment-friendly antiviral agents derived from natural sources. Bacillus spp. are widely utilized as biocontrol agents to manage fungal, bacterial, and viral plant diseases. Particularly, Bacillus velezensis HN-2 exhibits a strong antibiotic activity against plant pathogens and can also induce plant resistance.MethodsThe experimental subjects employed in this study were Bacillus velezensis HN-2, benzothiadiazole, and dufulin, aiming to evaluate their impact on antioxidant activity, levels of reactive oxygen species, activity of defense enzymes, and expression of defense-related genes in Nicotiana benthamiana. Furthermore, the colonization ability of Bacillus velezensis HN-2 in Capsicum chinense was investigated. ResultsThe results of bioassays revealed the robust colonization capability of Bacillus velezensis HN-2, particularly in intercellular spaces, leading to delayed infection and enhanced protection against PVMV through multiple plant defense mechanisms, thereby promoting plant growth. Furthermore, Bacillus velezensis HN-2 increased the activities of antioxidant enzymes, thereby mitigating the PVMV-induced ROS production in Nicotiana benthamiana. Moreover, the application of Bacillus velezensis HN-2 at 5 dpi significantly increased the expression of JA-responsive genes, whereas the expression of salicylic acid-responsive genes remained unchanged, implying the activation of the JA signaling pathway as a crucial mechanism underlying Bacillus velezensis HN-2-induced anti-PVMV activity. Immunoblot analysis revealed that HN-2 treatment delayed PVMV infection at 15 dpi, further highlighting its role in inducing plant resistance and promoting growth and development. ConclusionsThese findings underscore the potential of Bacillus velezensis HN-2 for field application in managing viral plant diseases effectively.

Road transportation plays a crucial role in society and daily life, as the functioning and durability of roads can significantly impact a nation's economic development. In the whole life cycle of the road, the emergence of disease is unavoidable, so it is necessary to adopt relevant technical means to deal with the disease. This study comprehensively reviews the advancements in computer vision, artificial intelligence, and mobile robotics in the road domain and examines their progress and applications in road detection, diagnosis, and treatment, especially asphalt roads. Specifically, it analyzes the research progress in detecting and diagnosing surface and internal road distress and related techniques and algorithms are compared. In addition, also introduces various road governance technologies, including automated repairs, intelligent construction, and path planning for crack sealing. Despite their proven effectiveness in detecting road distress, analyzing diagnoses, and planning maintenance, these technologies still confront challenges in data collection, parameter optimization, model portability, system accuracy, robustness, and real-time performance. Consequently, the integration of multidisciplinary technologies is imperative to enable the development of an integrated approach that includes road detection, diagnosis, and treatment. This paper addresses the challenges of precise defect detection, condition assessment, and unmanned construction. At the same time, the efficiency of labor liberation and road maintenance is achieved, and the automation level of the road engineering industry is improved.

The hot deformation behavior and microstructure of Fe-12.5Cr–4Al–2Mo-0.03Nb-0.08Y alloy were studied under conditions of 800 °C–1200 °C/0.01 s−1∼10 s−1 using a combination of hot compression experiments, EBSD and TEM characterization. The results indicate that the deformation temperature and strain rate have a significant impact on the flow stress and microstructure of the alloy, especially the deformation temperature. The constitutive equation constructed in this paper can reflect the hot deformation process and accurately calculate flow stress value of the FeCrAl alloy in corresponding states. The FeCrAl alloy undergoes DRV and DRX during hot deformation. DDRX grains distributed along the original grain boundaries mainly formed at low deformation temperatures and high strain rates, while CDRX grains mainly formed at high deformation temperatures and low strain rates and characterized by the internal distribution of the original grains. Moreover, the orientation of DDRX grains is mostly different from that of adjacent original grains, while the orientation of CDRX grains is relatively close to that of the original grains.

Accurately predicting traffic flow is paramount for the efficient operation of transportation systems. The key to enhancing prediction accuracy lies in effectively mining the intricate spatio-temporal correlations within traffic flow data. However, traditional traffic flow prediction methods that combine Graph Convolutional Network and Recurrent Neural Network have limitations in capturing comprehensive spatial correlation information and face challenges in modeling long-term temporal dependencies, consequently leading to suboptimal prediction performance. This study proposes a hybrid traffic flow prediction model based on fusion graph convolutional network and enhanced gate recurrent unit. Initially, a fusion graph structure is constructed based on adjacency graph and adaptive graph to better represent the correlations between nodes in the road network. Subsequently, the stacked fusion graph convolution module is utilized to capture multi-level spatial correlations and the enhanced gated recurrent unit is applied to extract multi-scale temporal correlations. In addition, the model integrates the extracted spatio-temporal features with the direct features through residual connection units, and utilizes the fused features for prediction, achieving superior predictive performance. The experimental results from four authentic datasets demonstrate that our proposed model outperforms state-of-the-art baseline models, showcasing an average enhancement of 3% in Mean Absolute Error(MAE), 3.3% in Root Mean Square Error(RMSE), and 2.7% in Mean Absolute Percentage Error(MAPE) across the four datasets.

Room-temperature sodium–sulfur (RT Na–S) batteries offer a superior, high-energy-density solution for rechargeable batteries using earth-abundant materials. However, conventional RT Na–S batteries typically use sulfur as the cathode, which suffers from severe volume expansion and requires pairing with a sodium metal anode, raising significant safety concerns. Utilizing Na2S as the cathode material addresses these issues, yet challenges such as Na2S’s low conductivity as well as the shuttle effect of polysulfide still hinder RT Na–S battery development. Herein, we present a simple and cost-effective method to fabricate a Na2S–Na6CoS4/Co@C cathode, wherein Na2S nanoparticles are embedded in a conductive carbon matrix and coupled with dual catalysts, Na6CoS4 and Co, generated via the in situ carbothermal reduction of Na2SO4 and CoSO4. This approach creates a three-dimensional porous composite cathode structure that facilitates electrolyte infiltration and forms a continuous conductive network for efficient electron transport. The in situ formed Na6CoS4/Co electrocatalysts, tightly integrated with Na2S, exhibit strong catalytic activity and robust physicochemical stabilization, thereby accelerating redox kinetics and mitigating the polysulfide shuttle effect. As a result, the Na2S–Na6CoS4/Co@C cathode achieves superior capacity retention, demonstrating a discharge capacity of 346 mAh g−1 after 100 cycles. This work highlights an effective strategy for enhancing Na2S cathodes with embedded catalysts, leading to enhanced reaction kinetics and superior cycling stability.

Mildew in maize kernels is typically caused by various fungi, necessitating prompt detection and treatment to minimize losses during harvest and storage. In this study, a deep learning YOLOv5s algorithm based on machine vision technology was employed to develop a maize seed surface mildew detection model and to enhance its portability for deployment on additional mobile devices. To guarantee the fruitful progression of this research, an initial experiment was conducted on maize seeds to obtain a sufficient number of images of mildewed maize kernels, which were classified into three grades (sound, mild, and severe). Subsequently, a maize seed image was extracted to create an image of a single maize seed, which was then divided to establish the data set. An enhanced YOLOv5s–ShuffleNet–CBAM model was ultimately developed. The results demonstrated that the model achieved with an mAP50 value of 0.955 and a model size of 2.4 MB. This resulted in a notable reduction in the model parameters and calculation amount while simultaneously enhancing model precision. Furthermore, K-fold cross-validation demonstrated the model stability, and Grad-CAM validated the model effectiveness. In the future, the proposed lightweight model in this study can be applied to other crops in the context of portable or online inspection systems, thus advancing effective and high-quality agricultural applications.

Kiwifruit, as a climacteric fruit, undergoes rapid ripening and senescence after harvest, making it highly susceptible to softening, rotting, and spoilage. Therefore, monitoring the key quality parameters of kiwifruit, particularly the accurate detection of soluble solids content (SSC), is considered crucial. The performance of two spectral acquisition methods—diffuse reflectance and diffuse transmission—in detecting SSC in kiwifruit was compared. Various preprocessing methods and feature wavelength selection techniques were employed, and regression models were constructed using partial least squares (PLS) analysis. The stability and accuracy of the models were validated through an independent validation set. The results indicated that the spectral data acquired by the diffuse reflectance method, preprocessed using Savitzky–Golay smoothing and combined with competitive adaptive reweighted sampling (CARS), yielded a coefficient of determination (R2) of 0.98 for the prediction set, with a root-mean-square error (RMSE) of 0.66. In contrast, the spectral data obtained by the diffuse transmission method, preprocessed using multiplicative scatter correction and combined with CARS, achieved an R2 of 0.95 and an RMSE of 0.93 for the prediction set. This study demonstrated that both methods were effective for detecting SSC in kiwifruit, with the diffuse reflectance method showing the greater advantage.

This paper reports the successful application of a self-developed, miniaturized, low-power nano-star tracker for precise attitude measurement of a 5-m-long satellite extension boom. Such extension booms are widely used in space science missions to extend and support payloads like magnetometers. The nano-star tracker, based on a CMOS image sensor, weighs 150 g (including the baffle), has a total power consumption of approximately 0.85 W, and achieves a pointing accuracy of about 5 arcseconds. It is paired with a low-cost, commercial lens and utilizes automated calibration techniques for measurement correction of the collected data. This system has been successfully applied to the precise attitude measurement of the 5-m magnetometer boom on the Chinese Advanced Space Technology Demonstration Satellite (SATech-01). Analysis of the in-orbit measurement data shows that within shadowed regions, the extension boom remains stable relative to the satellite, with a standard deviation of 30′′ (1σ). The average Euler angles for the “X-Y-Z” rotation sequence from the extension boom to the satellite are [−89.49°, 0.08°, 90.11°]. In the transition zone from shadow to sunlight, influenced by vibrations and thermal factors during satellite attitude adjustments, the maximum angular fluctuation of the extension boom relative to the satellite is approximately ±2°. These data and the accuracy of the measurements can effectively correct magnetic field vector measurements.

Indium phosphide (InP) is widely utilized in the fields of electronics and photovoltaics due to its high electron mobility and high photoelectric conversion efficiency. Strain engineering has been extensively employed in semiconductor devices to adjust physical properties and enhance material performance. In the present work, the band structure and electronic effective mass of InP under different strains are investigated by ab initio calculations. The results show that InP consistently exhibits a direct bandgap under different strains. Both uniaxial strain and biaxial tensile strain exhibit linear effects on the change in bandgap values. However, the bandgap of InP is significantly influenced by uniaxial compressive strain and biaxial tensile strain, respectively. The study of the InP bandgap under different hydrostatic pressures reveals that InP becomes metallic when the pressure is less than −7 GPa. Furthermore, strain also leads to changes in effective mass and the anisotropy of electron mobility. The studies of electronic properties under different strain types are of great significance for broadening the application of InP devices.

Indium phosphide (InP) is an excellent material used in space electronic devices due to its direct band gap, high electron mobility, and high radiation resistance. Displacement damage in InP, such as vacancies, interstitials, and clusters, induced by cosmic particles can lead to the serious degradation of InP devices. In this work, the analytical bond order potential of InP is modified with the short-range repulsive potential, and the hybrid potential is verified for its reliability to simulate the atomic cascade collisions. By using molecular dynamics simulations with the modified potential, the primary damage defects evolution of InP caused by 1–10 keV primary knock-on atoms (PKAs) are studied. The effects of electronic energy loss are also considered in our research. The results show that the addition of electronic stopping loss reduces the number of point defects and weakens the damage regions. The reduction rates of point defects caused by electronic energy loss at the stable state are 32.2% and 27.4% for 10 keV In-PKA and P-PKA, respectively. In addition, the effects of electronic energy loss can lead to an extreme decline in the number of medium clusters, cause large clusters to vanish, and make the small clusters dominant damage products in InP. These findings are helpful to explain the radiation-induced damage mechanism of InP and expand the application of InP devices.

Background: Previous single-center studies have demonstrated that drug-coated balloons (DCBs) may reduce restenosis rates, which is an important factor affecting the prognosis for intracranial interventional therapy. However, currently available cardiac DCBs are not always suitable for the treatment of intracranial atherosclerotic stenosis (ICAS). This study aimed to evaluate the safety and efficacy of a novel DCB catheter designed for patients with severely symptomatic ICAS. Methods: This prospective, multicenter, single-arm, target-value clinical trial was conducted in 9 Chinese stroke centers to evaluate the safety and efficacy of a novel DCB catheter for treating symptomatic severe ICAS. Primary metrics and other indicators were collected and analyzed using SAS version 9.4 (SAS Institute, Cary, NC, USA). Results: A total of 155 patients were enrolled in this study. The preliminary collection of follow-up data has been completed, while data quality control is ongoing. Conclusion: Results of this study demonstrated the patency rate, safety, and effectiveness of a novel on-label paclitaxel DCB designed for the treatment of ICAS. Trial registration: ChiCTR, ChiCTR2100047223. Registered June 11, 2021-Prospective registration, https://www.chictr.org.cn/ChiCTR2100047223.

Abstract Background RNA splicing plays significant roles in fundamental biological activities. However, our knowledge about the roles of alternative splicing and underlying mechanisms during spermatogenesis is limited. Results Here, we report that Serine/arginine-rich splicing factor 2 (SRSF2), also known as SC35, plays critical roles in alternative splicing and male reproduction. Male germ cell-specific deletion of Srsf2 by Stra8-Cre caused complete infertility and defective spermatogenesis. Further analyses revealed that deletion of Srsf2 disrupted differentiation and meiosis initiation of spermatogonia. Mechanistically, by combining RNA-seq data with LACE-seq data, we showed that SRSF2 regulatory networks play critical roles in several major events including reproductive development, spermatogenesis, meiotic cell cycle, synapse organization, DNA recombination, chromosome segregation, and male sex differentiation. Furthermore, SRSF2 affected expression and alternative splicing of Stra8, Stag3 and Atr encoding critical factors for spermatogenesis in a direct manner. Conclusions Taken together, our results demonstrate that SRSF2 has important functions in spermatogenesis and male fertility by regulating alternative splicing.

Epigenomic imbalance drives abnormal transcriptional processes, promoting the onset and progression of cancer. Although defective gene regulation generally affects carcinogenesis and tumor suppression networks, tumor immunogenicity and immune cells involved in antitumor responses may also be affected by epigenomic changes, which may have significant implications for the development and application of epigenetic therapy, cancer immunotherapy, and their combinations. Herein, we focus on the impact of epigenetic regulation on tumor immune cell function and the role of key abnormal epigenetic processes, DNA methylation, histone post-translational modification, and chromatin structure in tumor immunogenicity, and introduce these epigenetic research methods. We emphasize the value of small-molecule inhibitors of epigenetic modulators in enhancing antitumor immune responses and discuss the challenges of developing treatment plans that combine epigenetic therapy and immunotherapy through the complex interaction between cancer epigenetics and cancer immunology.

To improve the gel quality of chicken blood, a by-product of concentrated slaughter, the effects of different concentrations and formulations of xanthan gum (XG) and guar gum (GG) on the gel properties of chicken blood were investigated using the indices of water retention, texture, and rheological properties, as well as analysis of molecular interactions and sensory scores. The results showed that while individual treatment with either XG or GG improved the water-holding capacity of the chicken blood gel, the action of XG was superior. Addition of 4.0 g/L of XG resulted in a cooking loss rate of 10.02%, centrifugation loss of 12.73%, and syneresis rate of 10.96% (at 48 h), while the hardness, cohesiveness, gelation, mastication, and recovery of the gel were decreased. Addition of 6.0 g/L of GG significantly improved the textural properties of the gel, resulting in a hardness of 366.95 N, elasticity of 0.94 mm, cohesiveness of 0.77, adhesiveness of 281.94, masticatory value of 263.72 mJ, and recovery of 0.25. Analysis of dynamic rheology and intermolecular forces showed that the gelation transformation of the chicken blood gel system was mainly determined by the elastic response. The formulation of XG and GG had a synergistic effect in stabilizing the chicken blood gel, with strengthened ionic bonds (from 29.18% to 32.62%) and hydrogen bonds (from 2.48% to 6.43%), reduced hydrophobic force (from 22.68% to 16.28%), increased water-holding capacity of the gel, and enhanced gel stability. The addition of 4.0 g/L of formulated colloid (XG and GG in a ratio of 7:3) to chicken blood resulted in optimal water retention and texture, together with high sensory scores of the gel.

To address the real-time detection challenge of deploying deep learning-based tomato leaf disease detection algorithms on embedded devices, an improved tomato leaf disease detection algorithm based on YOLOv8n is proposed in this paper. It is able to achieve the efficient, real-time detection of tomato leaf diseases while maintaining model’s lightweight requirements. The algorithm incorporated the LMSM (lightweight multi-scale module) and ALSA (Attention Lightweight Subsampling Module) to improve the ability to extract lightweight and multi-scale semantic information for the specific characteristics of tomato leaf disease, which include irregular spot size and lush tomato leaves. The head network was redesigned utilizing partial and group convolution along with a parameter-sharing method. Scalable auxiliary bounding box and loss function optimization strategies were introduced to further enhance performance. After undergoing the pruning technique, computation decreased by 61.7%, the model size decreased by 55.6%, and the FPS increased by 44.8%, all while a high level of accuracy was maintained. A detection speed of 19.70FPS on the Jetson Nano was obtained after undergoing TensorRT quantization, showing a 64.85% improvement compared to the initial detection speed. This method met the high real-time performance and small model size requirements for embedded tomato leaf disease detection systems, indirectly reducing the energy consumption of online detection. It provided an effective solution for the online detection of tomato leaf disease.

During the γ phase–δ phase transition, U-50Zr fuel experiences spinodal decomposition, which has a significant effect on fuel properties. However, little is known about the spinodal decomposition of U-50Zr. The spinodal decomposition behavior in U-50Zr is studied in this research using the phase-field approach. The mechanism of spinodal decomposition from a thermodynamic perspective is studied, and the effects of temperature and grain boundary (GB) on spinodal decomposition are analyzed. It is found that the concentration of U atoms in the U-rich phase formed during spinodal decomposition is as high as 90%. The U-rich phase first appears at the GB position, and precipitation phases appear inside the grain later. Ostwald ripening occurs when larger precipitation phases on the GB absorb isolated smaller precipitation phases inside the grain. The coarsening rate of precipitation phases and the time it takes for spinodal decomposition to achieve equilibrium are both influenced by temperature.

Real-time semantic segmentation is a challenging task in computer vision, especially in complex scenes. In this study, a novel three-branch semantic segmentation model is designed, aiming to effectively use boundary information to improve the accuracy of semantic segmentation. The proposed model introduces the concept of containment control in a pioneering way, which treats image interior elements as well as image boundary elements as followers and leaders in containment control, respectively. Based on this, we utilize two learnable feature fusion matrices in the high-level semantic information stage of the model to quantify the fusion process of internal and boundary features. Further, we design a dedicated loss function to update the parameters of the feature fusion matrices based on the criterion of containment control, which enables fine-grained communication between target features. In addition, our model incorporates a Feature Enhancement Unit (FEU) to tackle the challenge of maximizing the utility of multi-scale features essential for semantic segmentation tasks through the meticulous reconstruction of these features. The proposed model proves effective on the publicly available Cityscapes and CamVid datasets, achieving a trade-off between effectiveness and speed.

A phase-field model for the precipitation of Fe-Cr-Al alloy is established incorporating grain boundary (GB) effects and irradiation-accelerated diffusion. The radiation source and grain boundary effect are incorporated to broaden the applicability of the Fe-Cr-Al precipitated phase-field model. The model is firstly employed to simulate the precipitation of the Cr-rich α’ phase in a single-crystal alloy. The precipitation rate and the size distribution of the precipitated phase were analyzed. Subsequently, the model is utilized to simulate segregation at GBs in a double-crystal system, analyzing the enrichment of Cr and depletion of Al near these boundaries. The simulation results are consistent with experimental observations reported in the references. Finally, the model is applied to simulate the precipitation in a polycrystalline Fe-Cr-Al system. The simulated results revealed that the presence of GBs induces the formation of localized regions with enhanced Cr and Al content as well as depleted zones adjacent to these boundaries. GBs also diminish both the quantity and precipitation rate of the formed phase within the grains.

Uranium silicide (U3Si2) is regarded as a viable fuel option for improving the safety of nuclear power plants. In the present work, phase-field simulations were employed to investigate grain growth phenomena, encompassing both isotropic and anisotropic grain growth. In simulations of isotropic grain growth, it is commonly assumed that the energy and mobility of the grain boundaries (GBs) remain constant, represented by average values. The calculated grain growth kinetic rate constant, K, exhibits a close correspondence with the experimental measurements, indicating a strong agreement between the two. In simulations of anisotropic grain growth, the values of GB energy and mobility are correlated with the angular disparity between GBs. The simulation results demonstrated that the growth rate of U3Si2 can be influenced by both the energy anisotropy and mobility anisotropy of GBs. Furthermore, the anisotropy in mobility results in a greater prevalence of low-angle GB distribution in comparison to high-angle GBs. However, the energy anisotropy of GBs does not impact the frequency distribution of the angle difference between GBs.

Summary: Magnesium alloy is an excellent material for biodegradable cerebrovascular stents. However, the rapid degradation rate of magnesium alloy will make stent unstable. To improve the biocompatibility of magnesium alloy, in this study, biodegradable sodium alginate and carboxymethyl chitosan (SA/CMCS) was used to coat onto hydrothermally treated the surface of magnesium alloy by a dipping coating method. The results show that the SA/CMCS coating facilitates the growth, proliferation, and migration of endothelial cells and promotes neovascularization. Moreover, the SA/CMCS coating suppresses macrophage activation while promoting their transformation into M2 type macrophages. Overall, the SA/CMCS coating demonstrates positive effects on the safety and biocompatibility of magnesium alloy after implantation, and provide a promising therapy for the treatment of intracranial atherosclerotic stenosis in the future.

Abstract Drought is an important meteorological event in China and can cause severe damage to both livelihoods and socio‐ecological systems, but current seasonal prediction skill for drought is far from successful. This study used convolutional neural network (CNN) to build an effective seasonal forecast model for the summer consecutive dry days (CDD) over China. The principal components (PC) of the six leading empirical orthogonal function modes of CDD anomaly were predicted by CNN, using the previous winter precipitation, 2‐m temperature and 500 hPa geopotential height as predictors. These predicted PCs were then projected onto the observed spatial patterns to obtain the final predicted summer CDD anomaly over China. In the independent hindcast period of 2007–2018, the interannual variabilities of first six PCs were significantly predicted by CNN. The spatial patterns of CDD were then skillfully predicted with anomaly correlation coefficient skills generally higher than 0.2. The interannual variability of summer CDD over the middle and lower Yangtze River valley, northwestern China and northern China were significant predicted by our CNN model three months in advance. CNN identified that the previous winter precipitation was the important predictor for PC1–PC3, whereas the previous winter 2‐m temperature and 500 hPa geopotential height were important for the prediction of PC4–PC6. This research provides a new and effective method for the seasonal prediction of summer drought.

Agriculture is the primary source of human survival, which provides the most basic living and survival conditions for human beings. As living standards continue to improve, people are also paying more attention to the quality and safety of agricultural products. Therefore, the detection of agricultural product quality is very necessary. In the past decades, the spectroscopy technique has been widely used because of its excellent results in agricultural quality detection. However, traditional spectral inspection methods cannot accurately describe the internal information of agricultural products. With the continuous research and development of optical properties, it has been found that the internal quality of an object can be better reflected by separating the properties of light, such as its absorption and scattering properties. In recent years, spatially resolved spectroscopy has been increasingly used in the field of agricultural product inspection due to its simple compositional structure, low-value cost, ease of operation, efficient detection speed, and outstanding ability to obtain information about agricultural products at different depths. It can also separate optical properties based on the transmission equation of optics, which allows for more accurate detection of the internal quality of agricultural products. This review focuses on the principles of spatially resolved spectroscopy, detection equipment, analytical methods, and specific applications in agricultural quality detection. Additionally, the optical properties methods and direct analysis methods of spatially resolved spectroscopy analysis methods are also reported in this paper.

To solve the problem of poor heat transfer effect in the subcooled region of integrated condenser, a combined condenser for instant heat pump water heater (IHPWH) was proposed and designed based on the condenser design model, aiming at obtaining an optimal design method of condenser. The off-design performances of heat pump water heater (HPWH) with a combined condenser (HPWHCC) and HPWH with an integrated condenser (HPWHIC) were investigated and compared based on the Mopt IHPWH test unit, aiming at verifying the feasibility of using a combined condenser replacement of an integrated condenser in the IHPWH. The results show that the heat transfer area of combined condenser is only 83.33 % of that of integrated condenser. Compared with the HPWHIC, the HPWHCC achieves basically equivalent COP and heating capacities and slightly higher discharge temperatures under variable heat sink outlet temperature (HSOT) condition and variable heat sink inlet temperature (HSIT) condition. Therefore, the combined condenser has the obvious potential to replace the integrated condenser in the IHPWH. The HSOT has a remarkable influence on the COP of HPWHIC and HPWHCC but a small influence on their heat capacities, while the HSIT has a small influence on their COP and heat capacities.

The red-bed soft rocks in South China have obvious creep characteristics and are prone to engineering geological disasters such as landslide and foundation settlement under the action of rainfall, groundwater, and load. In order to reveal its creep characteristics and mechanism under complex conditions, a step-loading creep test was carried out under chemical-stress-seepage coupling, and the energy evolution law of the whole creep process was analyzed based on linear energy storage and energy dissipation theory. The results also show that the acid chemical solution has the greatest influence on the triaxial strength and creep strength, and the creep damage and energy evolution of red-bed soft rock are universal. The creep damage and total strain increase with the increase of acidity, the decrease of confining pressure, and the increase of seepage pressure. The evolution law of creep damage shows the characteristics of slow-acceleration-rapid growth, and with the increase of load level, it has obvious transfer and accumulation. After entering the constant velocity creep stage, the damage rate begins to accelerate. The proportion of instantaneous strain and creep strain in the total strain increment is about 50%, and confining pressure has little influence on their respective proportions. The instantaneous strain is more sensitive to the acidity of the chemical solution, and the proportion of creep strain increases gradually with the increase of seepage pressure. The relationship between elastic energy density and total energy density is linear. The elastic energy density and dissipated energy density in the loading stage and creep stage all increase nonlinearly with loading time. The density of dissipated energy in the creep phase is lower than that in the loading phase, but the opposite is true in the higher stress phase, and the law of energy dissipation can explain the hardening damage effect in the creep process of soft rock samples. The research results provide a new perspective for us to reveal the mechanical properties and failure mechanism of red-bed soft rocks and provide an important theoretical basis for predicting and evaluating the creep instability and long-term stability of such rocks.