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An artificial solid electrolyte interphase (SEI) with lithiophilic sites and chemical bonds anchoring lithium polysulfides (LiPSs) has been developed as a potential solution to protect the lithium (Li) metal anode of Lithium−sulfur (Li–S) batteries. This strategy aims to guide consistent Li deposition and relieve lithium corrosion. Herein, the evolution process of lithiophilic sites based on aluminum fluoride (AlF3) in an artificial SEI is disclosed in Li–S batteries with metal−based lithiophilic sites. The polyester polymer (PMMA and PPC)/AlF3 artificial SEI (MPAF−SEI) was homogeneously anchored on Li anode by in−situ polymerization. The conversion of AlF3 into Li–Al and LiF lithiophilic sites effectively reduce the Li nucleation overpotential and prevents the formation of Li dendrites. At the same time, the polymer can anchor LiPSs by chemical bonds and prevents Li corrosion. The optimized MPAF−SEI protected Li demonstrates excellent stability for over 3000 h at a capacity of 1 mAh cm−2 in Li || Li symmetric cells. The Li–S battery with low N/P (4) exhibits a capacity of 532.6 mAh g −1 over 300 cycles lifespan at 0.5 C.

Abstract Mung bean (Vigna radiata L.), a widely cultivated legume, belongs to the Fabaceae family’s Papilionoideae subfamily. Although Phosphatidylethanolamine-binding protein (PEBP) genes have been identified in several plant species, their presence and function in mung bean remain largely unexplored. In this study, we identified seven VrPEBP genes from mung bean and classified them into four clades: FT, MFT, TFL and FT-like. Cis-regulatory element analysis revealed that VrPEBP genes may play a role in light, hormone, and stress responses. Quantitative real-time PCR (qRT-PCR) analysis indicated that VrPEBPs were constitutively expressed in various tissues. However, tissue-specific expression patterns were observed among VrPEBP genes. Under short-day (SD) conditions, VrFT1 and VrMFT1 exhibited significantly higher expression levels than under long-day (LD) conditions at 8 and 4 h, respectively. Conversely, VrTFL2 and VrTFL3 showed significantly higher expression levels under LD conditions compared to SD conditions at 8 and 12 h, respectively. The varied expression patterns of these genes under different photoperiod suggest their potential involvement in the photoperiodic regulation of flowering in mung bean. Additionally, phenotypic analysis of transgenic Arabidopsis plants overexpressing VrFT1 revealed higher expression levels under SD conditions and predicted its role in promoting flowering. These results provide valuable insights into the evolution and function of PEBP genes in mung bean and lay the foundation for further research on their regulatory mechanisms and potential applications in mung bean improvement.

Objective: Objective: Myelomeningocele (MMC) is the most severe type of spina bifida, with an incidence of 1.87 per 10,000 live births in Taiwan. Exposure of the lesion to amniotic fluid exacerbates neurological outcomes, while fetal surgery for MMC repair, now a routine practice, improves postnatal outcomes. However, Asian women and their families often find it difficult to accept prenatal defects, leading nearly all pregnancies with fetal MMC to opt for termination without considering fetal surgery. Materials and methods: In Taiwan's first approved trial of fetoscopic MMC repair, we prospectively recruited 15 cases from 2020 to 2023. Final diagnoses were confirmed using MRI and ultrasound. The medical team provided non-direct consultations to discuss possible outcomes of fetal surgery with family members. For those opting for fetal surgery, we offered total percutaneous fetoscopic MMC repair. Results: Over 30 months, 14 of 15 cases (93%) chose to terminate their pregnancies between 18 and 26 weeks of gestational age. Decision factors included potential disabilities, morbidities, economic, social, and psychological aspects. Despite supportive groups in the country, the termination rate remained high among the Chinese population. One out of the 15 cases underwent fetal surgery successfully, resulting in a 30-month-old child without motor function delays, able to walk and run naturally. Conclusion: We initiated the first fetoscopic MMC repair in Taiwan with promising outcomes, though we faced a high termination rate here and similar situation in other Asian countries. Continuous social education through media could play a crucial role in changing perceptions and increasing acceptance of fetal surgery.

Abstract Marine heatwaves have attracted great attention for their devastating impacts on marine organisms. However, the influence of marine heatwaves on phytoplankton community structure, a key aspect of pelagic ecosystems, remains elusive, especially in the biologically productive eastern boundary upwelling systems. Here, using a combination of multi-satellite observations and model outputs, we discover that phytoplankton in these upwelling systems exhibit not only a marked reduction in biomass (~50%), but also a significant shift toward smaller species in community structures during marine heatwaves, featuring a substantially increased/decreased dominance in picophytoplankton/microphytoplankton. This change in community structure is positively related to the intensity and duration of marine heatwaves, and is likely a result of community competition under reduced nutrient supply due to weakened coastal upwelling associated with poleward wind anomalies. These findings invite us to rethink the dominance of phytoplankton in the eastern boundary upwelling systems under extreme conditions, and may have important implications for local fisheries and carbon cycle under the ongoing warming.

Abstract The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-scale CNS scRNA-seq data still encounters challenges due to the complexity and heterogeneity among CNS cell types/subtypes. In this study, we introduce a self-supervised contrastive learning method, called scCM, for integrating large-scale CNS scRNA-seq data. scCM brings functionally related cells close together while simultaneously pushing apart dissimilar cells by comparing the variations of gene expression, effectively revealing the heterogeneous relationships within the CNS cell types/subtypes. The effectiveness of scCM is evaluated on 20 CNS datasets covering 4 species and 10 CNS diseases. Leveraging these strengths, we successfully integrate the collected human CNS datasets into a large-scale reference to annotate cell types and subtypes in neural tissues. Results demonstrate that scCM provides an accurate annotation, along with rich spatial information of cell state. In summary, scCM is a robust and promising method for integrating large-scale CNS scRNA-seq data, enabling researchers to gain insights into the cellular and molecular mechanisms underlying CNS functions and diseases.

Abstract Diffuse large B cell lymphoma (DLBCL) is an aggressive blood cancer known for its rapid progression and high incidence. The growing use of immunohistochemistry (IHC) has significantly contributed to the detailed cell characterization, thereby playing a crucial role in guiding treatment strategies for DLBCL. In this study, we developed an AI-based image analysis approach for assessing PD-L1 expression in DLBCL patients. PD-L1 expression represents as a major biomarker for screening patients who can benefit from targeted immunotherapy interventions. In particular, we performed large-scale cell annotations in IHC slides, encompassing over 5101 tissue regions and 146,439 live cells. Extensive experiments in primary and validation cohorts demonstrated the defined quantitative rule helped overcome the difficulty of identifying specific cell types. In assessing data obtained from fine needle biopsies, experiments revealed that there was a higher level of agreement in the quantitative results between Artificial Intelligence (AI) algorithms and pathologists, as well as among pathologists themselves, in comparison to the data obtained from surgical specimens. We highlight that the AI-enabled analytics enhance the objectivity and interpretability of PD-L1 quantification to improve the targeted immunotherapy development in DLBCL patients.

Background: Craniopharyngiomas have a high recurrence rate and a poor prognosis, and the key methods for reducing recurrences are unknown. The aim of this study was to explore the key points of microscopic or endoscopic transsphenoidal surgery used to treat infradiaphragmatic craniopharyngiomas. Methods: We reviewed the medical records of patients with infradiaphragmatic craniopharyngiomas who were admitted to Peking Union Medical College Hospital between 2011 and 2018. Results: When considering tumor location, all 34 patients had intrasellar tumors, with 19 of them exhibiting suprasellar extensions. Of the 34 patients, 24 patients underwent resection under the microscope and the remaining 10 patients underwent transsphenoidal endoscopic surgery. Gross total tumor resection was achieved in 16 patients. Twelve patients underwent invaded sellar diaphragm resection, while the remaining 22 patients were not. Cerebrospinal fluid leaks occurred during surgery in 18 patients. Visual acuity improved in two patients. After an average follow-up of 31.1 months, 13 patients experienced tumor recurrence. The short term recurrence rate in the sellar diaphragm resection group was significantly lower compared to the non-resected group (P

Recently, deep learning-based methods have emerged as the preferred approach for ultrasound data analysis. However, these methods often require large-scale annotated datasets for training deep models, which are not readily available in practical scenarios. Additionally, the presence of speckle noise and other imaging artifacts can introduce numerous hard examples for ultrasound data classification. In this paper, drawing inspiration from self-supervised learning techniques, we present a pre-training method based on mask modeling specifically designed for ultrasound data. Our study investigates three different mask modeling strategies: random masking, vertical masking, and horizontal masking. By employing these strategies, our pre-training approach aims to predict the masked portion of the ultrasound images. Notably, our method does not rely on externally labeled data, allowing us to extract representative features without the need for human annotation. Consequently, we can leverage unlabeled datasets for pre-training. Furthermore, to address the challenges posed by hard samples in ultrasound data, we propose a novel hard sample mining strategy. To evaluate the effectiveness of our proposed method, we conduct experiments on two datasets. The experimental results demonstrate that our approach outperforms other state-of-the-art methods in ultrasound image classification. This indicates the superiority of our pre-training method and its ability to extract discriminative features from ultrasound data, even in the presence of hard examples.

In order to improve the surface quality of zirconia ceramic workpieces, the magnetic compound fluid polishing tool were utilized. This was done to lessen the material's surface roughness, minimize surface and subsurface damage. With a focus on the effects of magnet speed, processing gap, and abrasive particle size in the polishing fluid on surface roughness and material removal rate, a 3-factor, 3-level orthogonal test was created using Taguchi's method. The weights of each factor on the two evaluation indices were then analyzed using ANOVA. The best process parameter combination for surface roughness was 300 r/min for the magnet speed, 0.5 mm for the processing gap, and 1.25 μm for the abrasive particle size; the best process parameter combination for material removal rate was 400 r/min for the magnet speed, 0.5 mm for the processing gap, and 2 μm for the abrasive particle size. With these processing parameters, the surface roughness can reach up to 4.5 nm, and the material removal rate can reach up to 0.117 μm/min. The optimization effect is significant. The polishing prediction model was developed using a BP neural network that has been genetic algorithm optimized. The prediction error was 3.948 4%.

This paper explored the in vitro inhibitory mechanism of polyphenol-rich rose extracts (REs) from an edible rose flower against α-glucosidase using multispectral and molecular docking techniques. Results showed that REs had an inhibitory effect on α-Glu activity (IC50 of 1.96 μg/mL); specifically, the samples pretreated by tri-frequency ultrasound (20/40/60 kHz) exhibited a significantly (p < 0.05) stronger inhibitory effect on α-Glu activity with an IC50 of 1.33 μg/mL. The Lineweaver–Burk assay indicated that REs were mixed-type inhibitors and could statically quench the endogenous fluorescence of α-Glu. REs increased the chance of polypeptide chain misfolding by altering the microenvironment around tryptophan and tyrosine residues and disrupting the natural conformation of the enzyme. Molecular docking results showed that polyhydroxy phenolics had a high fit to the active site of α-Glu, so REs with high polymerization and numerous phenolic hydroxyl groups had a stronger inhibitory effect. Therefore, this study provides new insights into polyphenol-rich REs as potential α-glucosidase inhibitors.

Small-hole components of Inconel 718 are widely used in aerospace engineering, medical devices, and other fields. Limited by material properties, its machining efficiency seriously restricts its wide application. The objective of this study is to investigate a novel machining technique for Inconel 718 that integrates ultrasonic machining (UM) and hydrogen embrittlement (HE) treatment. Accordingly, the technique is designated as hydrogen embrittlement-enhanced ultrasonic machining (HEUM). Prior to machining, a stress layer is formed on the surface of the workpiece. To ascertain the fundamental characteristics of Inconel 718, the influences of ultrasonic amplitude, HE time, and HE voltage on the specific material removal rate and surface roughness in the presence of HE were empirically examined. To investigate the material removal process for HEUM, the nanoscratch test and nanoindenter were also conducted with HE samples. Further, the subsurface for HEUAG samples were obtained with SEM. The specific material removal rate under experimental conditions of 10 min and 5 V HE increased by 27.4%. Finally, HEUM is proposed to be used for a 1 mm through-hole with Ra 0.318 μm. A precision hole with a diameter as small as 0.5 mm has been manufactured.

Reducing heat and improving the overall operation stability of the motor play a key role in the design of a starting engine. This paper focuses on the loss and thermal analysis of a permanent magnet (PM) brushless machine used in starter generators. The loss of the starter generator was calculated through a combination of theoretical analysis and the finite element method. A thermal analysis model was established based on the division of the fluid domain, boundary grid, heat source setting, and so on. The temperature fields of the whole motor and the main components were calculated and analyzed. The main factors affecting the air cooling effect were analyzed, including air flow rate, air temperature, and motor speed. A prototype experimental platform of the SG motor was built. The efficiency and temperature rise in the motor were tested. The temperature values were compared with the calculated values. The experimental results show that the performance of the motor is excellent, and the error between the temperature and the design calculation is less than 10% under each load torque. The accuracy of the thermal analysis method is verified. The correctness of the motor transient model was also confirmed through a temperature rise experiment under rated conditions, providing a research basis for improving operation efficiency.

The starter generator is the key component of the aircraft’s starter generation system. A high power density, efficiency, and reliability are essential for an aircraft’s starter generator. The configuration of the windings is closely related to the performance of the starter generator. In this paper, the winding performance analysis and design are studied. Considering the skin effect, circulation effect, and proximity effect, a calculation model of winding loss under high-frequency operation is established. The motor performance under different winding connections is compared. Through a comprehensive comparison of starting performance, generation loss, and process performance differences, the optimum configuration of windings is identified. The performance of the starter generator including winding resistance, current, and no-load loss was tested on the prototype platform to verify the rationality and correctness of the analysis and design methods.

This paper investigates the preparation and properties of high-strength artificial blocks made from dredged silt with a clay content of 52.0%. A comparative analysis of the mechanical properties of dredged silt blocks produced using semi-dry pressing and vibration molding methods was conducted. The study examined the effects of using fly ash (FA) and ground granulated blast-furnace slag (GGBS) as substitutes for cement on the compressive strength, splitting tensile strength, and dry shrinkage of the blocks. Additionally, the microstructure of the dredged silt blocks was analyzed using scanning electron microscopy (SEM), mercury intrusion porosimetry (MIP), and thermogravimetric analysis. The results show that specimens prepared using the pressing method exhibit better mechanical performance with compressive and splitting tensile strength reaching 64.8 MPa and 5.6 MPa at 28 d, respectively, which increased by 111.07% and 143.48% compared to specimens prepared through vibration molding. The addition of FA and GGBS reduces the early strength of the block to a certain extent but without a significant adverse effect on later strength. GGBS demonstrates faster hydration and a better filling effect. The addition of GGBS or FA refines the pore structure and reduces the diameter of pores in the paste, which is beneficial for improving the dry shrinkage performance of the block. At 120 d, the dry shrinkage of blocks containing 50% FA and GGBS shows a reduction of 29.7% and 27.1%, respectively, compared to blocks made with cement. The properties of the silt blocks can be notably enhanced through mechanical force, particle gradation, and hydration action. The preparation of artificial blocks such as road bricks and ballast blocks using dredged soil as the main raw material has been applied in projects such as the Yangtze River waterway regulation in China and Skikda Port in Algeria.

Sea surface salinity (SSS) observed by satellite has been widely used since the successful launch of the first salinity satellite in 2009. However, compared with other oceanographic satellite products (e.g., sea surface temperature, SST) that became operational in the 1980s, the SSS product is less mature and lacks effective validation from the user end. We employed an unsupervised machine learning approach to classify the Level 3 SSS bias from the Soil Moisture Active Passive (SMAP) satellite and its observing environment. The classification model divides the samples into fifteen classes based on four variables: satellite SSS bias, SST, rain rate, and wind speed. SST is one of the most significant factors influencing the classification. In regions with cold SST, satellite SSS has an accuracy of less than 0.2 PSU (Practical Salinity Unit), mainly due to the higher uncertainty in the cold environment. A small number of observations near the seawater freezing point show a significant fresh bias caused by sea ice. A systematic bias of the SMAP SSS product is found in the mid-latitudes: positive bias tends to occur north (south) of 45°N(S) and negative bias is more common in 25°N(S)–45°N(S) bands, likely associated with the SMAP calibration scheme. A significant bias also occurs in regions with strong ocean currents and eddy activities, likely due to spatial mismatch in the highly dynamic background. Notably, satellite SSS and in situ data correlations remain good in similar environments with weaker ocean dynamic activities, implying that satellite salinity data are reliable in dynamically active regions for capturing high-resolution details. The features of the SMAP SSS shown in this work call for careful consideration by the data user community when interpreting biased values.

Abstract A marine heatwave (MHW) is typically defined as an anomalous warm event in the surface ocean, with wide-ranging impacts on marine and socio-economic systems. The surface warming associated with MHWs can penetrate into the deep ocean; however, the vertical structure of MHWs is poorly known in the global ocean. Here, we identify four main types of MHWs with different vertical structures using Argo profiles: shallow, subsurface-reversed, subsurface-intensified, and deep MHWs. These MHW types are characterized by different spatial distributions with hotspots of subsurface-reversed and subsurface-intensified MHWs at low latitudes and shallow and deep MHWs at middle-high latitudes. These vertical structures are influenced by ocean dynamical processes, including oceanic planetary waves, boundary currents, eddies, and mixing. The area and depth of all types of MHWs exhibit significant increasing trends over the past two decades. These results contribute to a better understanding of the physical drivers and ecological impacts of MHWs in a warming climate.

Abstract Background To explore the distinguishing diagnostic value and clinical application potential of deep neural networks (DNN) for pathological images of thyroid tumors. Methods A total of 799 pathological thyroid images of 559 patients with thyroid tumors were retrospectively analyzed. The pathological types included papillary thyroid carcinoma (PTC), medullary thyroid carcinoma (MTC), follicular thyroid carcinoma (FTC), adenomatous goiter, adenoma, and normal thyroid gland. The dataset was divided into a training set and a test set. Resnet50, Resnext50, EfficientNet, and Densenet121 were trained using the training set data and tested with the test set data to determine the diagnostic efficiency of different pathology types and to further analyze the causes of misdiagnosis. Results The recall, precision, negative predictive value (NPV), accuracy, specificity, and F1 scores of the four models ranged from 33.33% to 100.00%. The area under curve (AUC) ranged from 0.822 to 0.994, and the Kappa coefficient ranged from 0.7508 to 0.7713. However, the performance of diagnosing FTC, adenoma, and adenomatous goiter was slightly inferior to other types of pathological tissues. Conclusion The DNN model achieved satisfactory results in the task of classifying thyroid tumors by learning thyroid pathology images. These results indicate the potential of the DNN model for the efficient diagnosis of thyroid tumor histopathology.

Abstract Physical reservoirs holding intrinsic nonlinearity, high dimensionality, and memory effects have attracted considerable interest regarding solving complex tasks efficiently. Particularly, spintronic and strain-mediated electronic physical reservoirs are appealing due to their high speed, multi-parameter fusion and low power consumption. Here, we experimentally realize a skyrmion-enhanced strain-mediated physical reservoir in a multiferroic heterostructure of Pt/Co/Gd multilayers on (001)-oriented 0.7PbMg1/3Nb2/3O3−0.3PbTiO3 (PMN-PT). The enhancement is coming from the fusion of magnetic skyrmions and electro resistivity tuned by strain simultaneously. The functionality of the strain-mediated RC system is successfully achieved via a sequential waveform classification task with the recognition rate of 99.3% for the last waveform, and a Mackey-Glass time series prediction task with normalized root mean square error (NRMSE) of 0.2 for a 20-step prediction. Our work lays the foundations for low-power neuromorphic computing systems with magneto-electro-ferroelastic tunability, representing a further step towards developing future strain-mediated spintronic applications.

The hydrogen oxygen fuel cell is a power source with significant potential for development. The air compressor provides ample oxygen for the fuel cell, and as a key component of the air compressor, the performance of the motor greatly impacts the efficiency of the fuel cell. In order to enhance the system performance of high-speed permanent magnet motors, optimization was conducted on the motor’s geometric dimensions to minimize rotor loss and maximize power density, taking into account the comprehensive constraints of electromagnetic and mechanical properties. The finite-element method was employed to analyze the motor’s performance, conducting a multi-physical field analysis that included electromagnetic field, rotor loss, and mechanical strength analysis, as well as temperature field analysis. Aiming at the problem of high temperature rise in high-speed motor winding, the influence of the cooling water flow rate on the winding temperature rise was analyzed and simulated. Based on the analysis results, the minimum cooling water flow rate was obtained. According to the optimized design results, a prototype of an 18 kW, 100,000 rpm motor was manufactured, and the efficiency and temperature rise were tested. The experimental results verify the correctness and effectiveness of the optimal design.

The investigation of the fluorescence mechanism of carbon dots (CDs) has attracted significant attention, particularly the role of the oxygen-containing groups. Dual-CDs exhibiting blue and green emissions are synthesized from glucose via a simple ultrasonic treatment, and the oxidation degree of the CDs is softly modified through a slow natural oxidation approach, which is in stark contrast to that aggressively altering CDs’ surface configurations through chemical oxidation methods. It is interesting to find that the intensity of the blue fluorescence gradually increases, eventually becoming the dominant emission after prolonging the oxidation periods, with the quantum yield (QY) of the CDs being enhanced from ~0.61% to ~4.26%. Combining the microstructure characterizations, optical measurements, and ultrafiltration experiments, we hypothesize that the blue emission could be ascribed to the surface states induced by the C–O and C=O groups, while the green luminescence may originate from the deep energy levels associated with the O–C=O groups. The distinct emission states and energy distributions could result in the blue and the green luminescence exhibiting distinct excitation and emission behaviors. Our findings could provide new insights into the fluorescence mechanism of CDs.

With the development of the electronics industry, the requirements for chips are getting higher and higher, and thinner and thinner wafers are needed to meet the processing of chips. In this study, a model of the adhesion state of semiconductor wafers in the stacking–clamping process based on microarray adsorption was established, the composition adhesion was discussed, the microarrays of different materials and pressures were experimentally studied, and a molecular dynamics model was established. The molecular dynamics analysis showed that the adhesion force was only related to the type of atom, and the applied pressure did not change the adhesion force. According to the simulation results, the tangential adhesion between the metal and the wafer is greater than that between the ceramic and the wafer, the adsorption force between the aluminum–magnesium alloy and the silicon wafer is shown in the normal direction, and the repulsion force between other materials and the silicon wafer is shown in the normal direction. During the pressure process, the metal is in the elastic deformation stage between the metal and the wafer, the wafer is plastically deformed in the silicon carbide ceramic and wafer, and the wafer is elastically deformed in the alumina ceramic and wafer. In this paper, the adhesion between the substrate and the wafer is studied, a method of constructing microarrays to enhance adhesion is proposed, and the tangential deformation of the array unit under pressure is studied, which provides theoretical support for increasing the adhesion by constructing microarrays.

PurposeNo multi-center radiomics models have been built to predict delayed remission (DR) after transsphenoidal surgery (TSS) in Cushing’s disease (CD). The present study aims to build clinical and radiomics models based on data from three centers to predict DR after TSS in CD.MethodsA total of 122 CD patients from Peking Union Medical College Hospital, Xuanwu Hospital, and Fuzhou General Hospital were enrolled between January 2000 and January 2019. The T1-weighted gadolinium-enhanced MRI images and clinical data were used as inputs to build clinical and radiomics models. The regions of interest (ROI) of MRI images were automatically defined by a deep learning algorithm developed by our team. The area under the curve (AUC) of receiver operating characteristic (ROC) curves was used to evaluate the performance of the models. In total, 10 machine learning algorithms were used to construct models.ResultsThe overall DR rate is 44.3% (54/122). According to multivariate Logistic regression analysis, patients with higher BMI and lower postoperative cortisol levels are more likely to achieve a higher rate of delayed remission. Among the 10 models, XGBoost achieved the best performance among all models in both clinical and radiomics models with AUC values of 0.767 and 0.819 respectively. The results from SHAP value and LIME algorithms revealed that postoperative cortisol level (PoC) and BMI were the most important features associated with DR.ConclusionRadiomics models can be built as an effective noninvasive method to predict DR and might be useful in assisting neurosurgeons in making therapeutic plans after TSS for CD patients. These results are preliminary and further validation in a larger patient sample is needed.

Surface defects generated during the production process of steel balls can lead to bearing failures, which makes it crucial to promptly detect and classify these defects. Defects classify is helpful for analysis and improving the production process. An algorithm that incorporates K-fold cross-validation (K-CV) with improved grid search is proposed to optimize the parameters of SVM, in order to detect surface defects with steel balls. Principal Component Analysis (PCA) was employed to reduce the dimensionality of the effective features data. The K-CV algorithm was employed in conjunction with an improved grid search method to find the optimal parameters “c” and “g.” This approach not only reduced the search time but also diminished the influence of individual samples on the model, thereby enhancing its robustness and ultimately improving the classification accuracy. The model’s performance was evaluated using a confusion matrix, and a comparison was made with three other machine learning models. The experimental results demonstrated the effectiveness of the proposed algorithm in classifying defects on highly reflective metal surfaces such as steel balls. The model achieved a classification accuracy of 97.15%.

IntroductionPediatric pituitary neuroendocrine tumor is a rare condition, and despite previous research focusing on this specific group, the main factors influencing the surgical cure rate have not been identified.MethodsWe conducted a single-center retrospective study on pediatric pituitary neuroendocrine tumor patients who visited Peking Union Medical College Hospital between 2010 and 2023. We collected data on their clinical characteristics, imaging features, surgical outcomes, and follow-up information. Additionally, we used multiple-factor logistic regression to investigate the factors affecting the surgical cure rate of pediatric pituitary neuroendocrine tumor.Results232 patients were diagnosed with pediatric pituitary neuroendocrine tumors, with a higher incidence in females. The most common type was ACTH-secreting adenoma (90/232), followed by prolactin-secreting adenoma (63/232), and growth hormone-secreting adenoma (41/232). The majority of pediatric adenomas were macroadenomas (139/232), and some tumors were associated with cystic changes or hemorrhage (58/232), while a few exhibited invasion of the cavernous sinus (33/232). The results of the multivariate analysis indicated that the different hormone secretion types, macroadenoma or the presence of cystic changes or hemorrhage were not significant risk factors for the cure rate after the first surgery. However, the invasion of the cavernous sinus was found to be an important factor influencing the postoperative cure rate. Most pediatric pituitary neuroendocrine tumors with cavernous sinus invasion were macroadenomas, and some displayed characteristics of refractory pituitary neuroendocrine tumors, with some patients experiencing irreversible complications after surgery.ConclusionPediatric pituitary neuroendocrine tumors are complex, and the postoperative cure rate is particularly poor for tumors with cavernous sinus invasion. Although macroadenoma itself does not significantly impact the postoperative cure rate, it is still recommended to diagnose and treat early to avoid unnecessary surgery or surgical complications.

Photo-assisted lithium–oxygen (Li–O2) batteries have been developed as a new system to reduce a large overpotential in the Li–O2 batteries. However, constructing an optimized photocatalyst is still a challenge to achieve broad light absorption and a low recombined rate of photoexcited electrons and holes. Herein, oxygen vacancy-rich molybdenum trioxide (MoO3−x) nanorods are employed as photocatalysts to accelerate kinetics of cathode reactions in the photo-assisted Li–O2 batteries. Oxygen vacancies on the MoO3−x nanorods can not only increase light-harvesting capability but also improve electrochemical activity for the cathode reactions. Under illumination, the photoexcited electrons and holes are effectively separated on the MoO3−x nanorods. During discharging, activated O2 is reduced to Li2O2 by the photoexcited electrons from the MoO3−x nanorods. The photoexcited holes can promote the decomposition of Li2O2 during subsequent charging. Accordingly, the photo-assisted Li–O2 batteries with the MoO3−x nanorods deliver an ultralow overpotential of 0.22 V, considerable rate capability, and good reversibility. We think that this work could give a reference for the exploitation and application of the photocatalysts in the photo-assisted Li–O2 batteries.

Abstract Combined magnetic bearing with radial and axial unites is an important supporting element for high speed and high energy density motor. Accurate calculation of the magnetic field is a key to design and optimise a Combined Radial and Axial Magnetic Bearing (CRAMB). This study focuses on magnetic field analytical calculation method for radial Unite of CRAMB. The analytical calculation model of magnetic field is based on subdomain method. The Laplace's equations in the air‐gap subdomain are solved by the variable separation method. The magnetic field of magnetic bearing with large diameter rotor is analysed and calculated in Cartesian coordinate system. Considering the influence of curvature the magnetic field distribution of magnetic bearing with small diameter rotor is deduced and calculated analytically in polar coordinate system. The effectiveness of the analytical method is verified by finite element and experimental results.

Here, the authors use an advanced data-mining method to show how “extreme modes” of large-scale climate variability, such as El Niño, can lead to devastating marine heatwaves.

PurposeTo investigate the prevalence of low blood testosterone level (LTL) and its determinant factors among active male acromegaly patients, as well as the effect of surgery on LTL in male acromegaly patients.MethodsA retrospective, single-center study focused on 252 male acromegaly patients aged 18 years–60 years diagnosed in the Peking Union Medical College Hospital from January 2015 to December 2018 was carried out. The measurements of preoperative and postoperative testosterone levels, serum growth hormone (GH), insulin-like growth factor 1 (IGF-1), and other clinical data were analyzed.ResultsForty per cent of subjects included were diagnosed with LTL pre surgery. Patients were divided into normal testosterone level (NTL) and LTL groups based on their testosterone level. There were significant differences (p < 0.01) between groups in the presence of macroadenomas, invasion of the cavernous sinus, compression of the optic chiasm, and serum GH and prolactin levels pre surgery. Invasion of the cavernous sinus [odds ratio (OR) = 4.299; p = 0.000] and serum prolactin level (OR = 1.023, p = 0.001) were independent predictors of LTLs in male patients before surgical intervention. A total of 67.9% of LTL patients recovered during the follow-up, with a new-onset rate of 3.4%. Body mass index, invasion of the cavernous sinus, GH, IGF-1, and prolactin levels, the presence of a prolactin-secreting tumor, and recovery from acromegaly were significantly different (p < 0.05) in the NTL group and in the LTL group during the follow-up. The presence of a prolactin-secreting tumor (OR = 0.224; p = 0.001) and recovery from acromegaly (OR = 0.168; p = 0.006) were independent predictors of LTLs in male acromegaly patients during the follow-up.ConclusionThe invasiveness of tumor and levels of blood prolactin are independent factors for LTLs before surgery, whereas GH and IGF-1 levels are not. Most male patients can recover from LTL after tumor restriction surgery: those who recover from acromegaly have a better chance of recovering from LTL.

Abstract Understanding patterns of gene flow and processes driving genetic differentiation is important for a broad range of conservation practices. In marine organisms, genetic differentiation among populations is influenced by a range of spatial, oceanographic, and environmental factors that are attributed to the seascape. The relative influences of these factors may vary in different locations and can be measured using seascape genetic approaches. Here, we applied a seascape genetic approach to populations of the seagrass, Thalassia hemprichii, at a fine spatial scale (~80 km) in the Kimberley coast, western Australia, a complex seascape with strong, multidirectional currents greatly influenced by extreme tidal ranges (up to 11 m, the world's largest tropical tides). We incorporated genetic data from a panel of 16 microsatellite markers, overwater distance, oceanographic data derived from predicted passive dispersal on a 2 km‐resolution hydrodynamic model, and habitat characteristics from each meadow sampled. We detected significant spatial genetic structure and asymmetric gene flow, in which meadows 12–14 km apart were less connected than ones 30–50 km apart. This pattern was explained by oceanographic connectivity and differences in habitat characteristics, suggesting a combined scenario of dispersal limitation and facilitation by ocean current with local adaptation. Our findings add to the growing evidence for the key role of seascape attributes in driving spatial patterns of gene flow. Despite the potential for long‐distance dispersal, there was significant genetic structuring over small spatial scales implicating dispersal and recruitment bottlenecks and highlighting the importance of implementing local‐scale conservation and management measures.

Presence of pituitary metastases (PMs) is a relatively rare clinical situation, especially when originating from hepatocellular carcinoma (HCC). A 73-year-old man presented with headaches, diplopia, and soon impaired vision, as well as gastrointestinal symptoms. Computed tomography (CT) and magnetic resonance imaging (MRI) of the brain revealed a space-occupying mass in the sellar region. The patient had a history of hepatocellular carcinoma and recent abdominal ultrasound and positron emission tomography (PET) indicated recurrence and metastases. Endoscopic transnasal transsphenoidal tumor excision was performed, and postoperative pathological report confirmed the diagnosis of HCC PM. In the literature review, 17 published cases of HCC PMs were summarized. Both the diagnosis and management of HCC PMs are difficult. Patients who had HCC-related history and new-onset headaches or diplopia should be inspected with a suspicion of metastatic lesions. Surgical intervention with transnasal endoscope is only recommended to ameliorate the symptoms and improve the life quality.

ObjectiveNeuronavigation and classification of craniopharyngiomas can guide surgical approaches and prognostic information. The QST classification has been developed according to the origin of craniopharyngiomas; however, accurate preoperative automatic segmentation and the QST classification remain challenging. This study aimed to establish a method to automatically segment multiple structures in MRIs, detect craniopharyngiomas, and design a deep learning model and a diagnostic scale for automatic QST preoperative classification.MethodsWe trained a deep learning network based on sagittal MRI to automatically segment six tissues, including tumors, pituitary gland, sphenoid sinus, brain, superior saddle cistern, and lateral ventricle. A deep learning model with multiple inputs was designed to perform preoperative QST classification. A scale was constructed by screening the images.ResultsThe results were calculated based on the fivefold cross-validation method. A total of 133 patients with craniopharyngioma were included, of whom 29 (21.8%) were diagnosed with type Q, 22 (16.5%) with type S and 82 (61.7%) with type T. The automatic segmentation model achieved a tumor segmentation Dice coefficient of 0.951 and a mean tissue segmentation Dice coefficient of 0.8668 for all classes. The automatic classification model and clinical scale achieved accuracies of 0.9098 and 0.8647, respectively, in predicting the QST classification.ConclusionsThe automatic segmentation model can perform accurate multi-structure segmentation based on MRI, which is conducive to clearing tumor location and initiating intraoperative neuronavigation. The proposed automatic classification model and clinical scale based on automatic segmentation results achieve high accuracy in the QST classification, which is conducive to developing surgical plans and predicting patient prognosis.

Abstract Rational design of porous conductive hosts with high electrical conductivity, large surface area, and adequate interior space is desirable to suppressing dendritic lithium growth and accommodating large volume change of lithium metal anode during the Li plating/stripping process. However, due to the conductive nature of the conductive hosts, Li is easily deposited directly on the top of the hosts, which hinders it from fully functioning. To circumvent the issue, in this study, we designed a novel porous carbon host with a gradient‐pore‐size structure based on one‐dimensional (1D) carbon with different diameters. With this kind of host, stable cycling with high and stable Coulombic efficiency of ~98% is achieved at 0.5 mA cm−2 with an areal capacity of 1 mAh cm−2 over 320 cycles. In contrast, the normal three‐dimensional (3D) carbon nanotube host presents a moss‐like Li morphology with wildly fluctuating Coulombic efficiency after 100 cycles. The results reveal that the unique gradient‐pore‐size structure of the 3D conductive host greatly improves the performance of lithium metal batteries.

Abstract Background Cushing’s disease (CD) is rare in pediatric patients. It is characterized by elevated plasma adrenocorticotropic hormone (ACTH) from pituitary adenomas, with damage to multiple systems and development. In recent years, genetic studies have shed light on the etiology and several mutations have been identified in patients with CD. Case presentation A girl presented at the age of 10 years and 9 months with facial plethora, hirsutism and acne. Her vision and eye movements were impaired. A quick weight gain and slow growth were also observed. Physical examination revealed central obesity, moon face, buffalo hump, supra-clavicular fat pads and bruising. Her plasma ACTH level ranged between 118 and 151 pg/ml, and sella enhanced MRI showed a giant pituitary tumor of 51.8 × 29.3 × 14.0 mm. Transsphenoidal pituitary debulk adenomectomy was performed and immunohistochemical staining confirmed an ACTH-secreting adenoma. Genetic analysis identified a novel germline GPR101 (p.G169R) and a somatic USP8 (p. S719del) mutation. They were hypothesized to impact tumor growth and function, respectively. Conclusions We reported a rare case of pediatric giant pituitary ACTH adenoma and pointed out that unusual concurrent mutations might contribute to its early onset and large volume.

We improve by a factor of 4–20 the energy accuracy of the strongest soft X-ray transitions of Fe xvii ions by resonantly exciting them in an electron beam ion trap with a monochromatic beam at the P04 beamline of the PETRA III synchrotron facility. By simultaneously tracking instantaneous photon-energy fluctuations with a high-resolution photoelectron spectrometer, we minimize systematic uncertainties down to 10–15 meV, or velocity equivalent ±∼5 km s ^−1 in their rest energies, substantially improving our knowledge of this key astrophysical ion. Our large-scale configuration-interaction computations include more than 4 million relativistic configurations and agree with the experiment at a level without precedent for a 10-electron system. Thereby, theoretical uncertainties for interelectronic correlations become far smaller than those of quantum electrodynamics (QED) corrections. The present QED benchmark strengthens our trust in future calculations of many other complex atomic ions of interest to astrophysics, plasma physics, and the development of optical clocks with highly charged ions.

Gel systems are widely used as plugging materials in the oil and gas industry. Gas channeling can be mitigated by reducing the heterogeneity of the formation and the mobility ratio of CO2 to crude oil. Cracks and other CO2 leaking pathways can be plugged during the geological storage of CO2 to increase the storage stability. By adding CO2-responsive groups to the classic polymer gel’s molecular chain, CO2 responsive gel is able to seal and recognize CO2 in the formation while maintaining the superior performance of traditional polymer gel. The application of CO2 responsive gels in oil and gas production is still in the stage of laboratory testing on the whole. To actually achieve the commercial application of CO2 responsive gels in the oil and gas industry, it is imperative to thoroughly understand the CO2 responsive mechanisms of the various types of CO2 responsive gels, as well as the advantages and drawbacks of the gels and the direction of future development prospects. This work provides an overview of the research progress and response mechanisms of various types of CO2 responsive groups and CO2 responsive gels. Studies of the CO2 responsive gel development, injectivity, and plugging performance are comprehensively reviewed and summarized. The shortcomings of the existing CO2 responsive gels system are discussed and the paths for future CO2 responsive gel development are suggested.

Cystic lesions are common lesions of the sellar region with various pathological types, including pituitary apoplexy, Rathke’s cleft cyst, cystic craniopharyngioma, etc. Suggested surgical approaches are not unique when dealing with different cystic lesions. However, cystic lesions with different pathological types were hard to differentiate on MRI with the naked eye by doctors. This study aimed to distinguish different pathological types of cystic lesions in the sellar region using preoperative magnetic resonance imaging (MRI). Radiomics and deep learning approaches were used to extract features from gadolinium-enhanced MRIs of 399 patients enrolled at Peking Union Medical College Hospital over the past 15 years. Paired imaging differentiations were performed on four subtypes, including pituitary apoplexy, cystic pituitary adenoma (cysticA), Rathke’s cleft cyst, and cystic craniopharyngioma. Results showed that the model achieved an average AUC value of 0.7685. The model based on a support vector machine could distinguish cystic craniopharyngioma from Rathke’s cleft cyst with the highest AUC value of 0.8584. However, distinguishing cystic apoplexy from pituitary apoplexy was difficult and almost unclassifiable with any algorithms on any feature set, with the AUC value being only 0.6641. Finally, the proposed methods achieved an average Accuracy of 0.7532, which outperformed the traditional clinical knowledge-based method by about 8%. Therefore, in this study, we first fill the gap in the existing literature and provide a non-invasive method for accurately differentiating between these lesions, which could improve preoperative diagnosis accuracy and help to make surgery plans in clinical work.

Measurement(s) temperature of water • temperature of sea surface Technology Type(s) ocean time series station • satellite • ship-based water sampling • ship-based CTD profiles Sample Characteristic - Environment coastal sea water • sea water environment • continental shelf Sample Characteristic - Location Australia • Tasman Sea coastal waters of continental Australia • Western Australia

The sluggish reaction kinetics at the oxygen cathode is one of the important issues hindering the commercialization of the metal-air batteries. Although the noble metal can be used as the high-efficiency electrocatalyst to solve the problems to some extent, the high cost and scarcity of these noble-metal catalysts have limited their application in electrocatalysis. In this review, we discussed the mechanisms of the ORR and OER, and proposed the principles for the bifunctional electrocatalysts firstly, and then the state-of-the-art bifunctional catalysts, including carbon-based materials and transition-metal-based materials. On the basis of that, the self-supporting 3D noble-metal-free bifunctional ORR/OER catalysts were also discussed. Finally, the perspectives for the bifunctional electrocatalysts were discussed.

Abstract Objective Pituitary adenomas are the most common type of pituitary disorders, which usually occur in young adults and often affect the patient’s physical development, labor capacity and fertility. Clinical free texts noted in electronic medical records (EMRs) of pituitary adenomas patients contain abundant diagnosis and treatment information. However, this information has not been well utilized because of the challenge to extract information from unstructured clinical texts. This study aims to enable machines to intelligently process clinical information, and automatically extract clinical named entity for pituitary adenomas from Chinese EMRs. Methods The clinical corpus used in this study was from one pituitary adenomas neurosurgery treatment center of a 3A hospital in China. Four types of fine-grained texts of clinical records were selected, which included notes from present illness, past medical history, case characteristics and family history of 500 pituitary adenoma inpatients. The dictionary-based matching, conditional random fields (CRF), bidirectional long short-term memory with CRF (BiLSTM-CRF), and bidirectional encoder representations from transformers with BiLSTM-CRF (BERT-BiLSTM-CRF) were used to extract clinical entities from a Chinese EMRs corpus. A comprehensive dictionary was constructed based on open source vocabularies and a domain dictionary for pituitary adenomas to conduct the dictionary-based matching method. We selected features such as part of speech, radical, document type, and the position of characters to train the CRF-based model. Random character embeddings and the character embeddings pretrained by BERT were used respectively as the input features for the BiLSTM-CRF model and the BERT-BiLSTM-CRF model. Both strict metric and relaxed metric were used to evaluate the performance of these methods. Results Experimental results demonstrated that the deep learning and other machine learning methods were able to automatically extract clinical named entities, including symptoms, body regions, diseases, family histories, surgeries, medications, and disease courses of pituitary adenomas from Chinese EMRs. With regard to overall performance, BERT-BiLSTM-CRF has the highest strict F1 value of 91.27% and the highest relaxed F1 value of 95.57% respectively. Additional evaluations showed that BERT-BiLSTM-CRF performed best in almost all entity recognition except surgery and disease course. BiLSTM-CRF performed best in disease course entity recognition, and performed as well as the CRF model for part of speech, radical and document type features, with both strict and relaxed F1 value reaching 96.48%. The CRF model with part of speech, radical and document type features performed best in surgery entity recognition with relaxed F1 value of 95.29%. Conclusions In this study, we conducted four entity recognition methods for pituitary adenomas based on Chinese EMRs. It demonstrates that the deep learning methods can effectively extract various types of clinical entities with satisfying performance. This study contributed to the clinical named entity extraction from Chinese neurosurgical EMRs. The findings could also assist in information extraction in other Chinese medical texts.

Jasmine flower residue (JFR) is a by-product retained in the production process of jasmine tea and can be used as an unconventional feed due to its rich nutrient value. This study aimed to evaluate the effects of the addition of JFR to the diet of goats on their meat quality and flavor. Twenty-four castrated Nubian male goats were randomly divided into two groups and fed a mixed diet containing 10% JFR (JFR, n = 12) or a conventional diet (CON, n = 12) for 45 days. Meat quality and flavor were measured at the end of the treatment. The addition of JFR to the diet could reduce the shear force of the longissimus dorsi muscle, as well as, the cross-sectional area and diameter of muscle fibers, indicating that the addition of JFR improved meat quality. JFR also increased the content of glutamic acid and ω-3 polyunsaturated fatty acid (C18:3n3 and C20:5N3) and reduced the content of C24:1 and saturated fatty acid (C20:0 and C22:0). In addition, the use of JFR increased the content of acetaldehyde and hexanal in the meat. Furthermore, JFR introduced new volatile components in the meat. The umami, saltiness, and richness of the meat also improved. In conclusion, the addition of jasmine flower residue to the diet can improve the meat quality and flavor of goat.

Exosomes are small extracellular vesicles that carry various bioactive molecules including various RNAs that modulate the activities of recipient cells. It has drawn considerable attention as means of cell communication and drug delivery. Exosome plays important role in various tumors, but it is rarely summarized in pituitary adenoma (PA). PA is the second most common primary central nervous system tumor, and its recurrence and persistent postoperative hormone hypersecretion lead to compromised quality of life. How exactly exosomes impact tumor development and hormone secretion is important for the development of this tumor diagnosis and treatment. In this review, we discuss how exosomal RNAs impact PAs and their potential as future clinical therapies. In our literature review, first, we found that exosomal microRNA hsa-miR-1180-3p is a potential early biomarker for NFPAs. Since NFPAs are typically difficult to diagnose, this is an especially important finding. Second, exosomal protein transcripts are potential invasive biomarker, such as MMP1, N-cadherin, CDK6, RHOU, INSM1, and RASSF10. Third, exosomal contents such as hsa-miR-21-5p promote distant bone formation of GHPA patients. Fourth, tumor suppressors in the exosome constitute novel therapeutic application of exosome, including long noncoding RNA (lncRNA) H19, miR-149-5p, miR-99a-3p, and miR-423-5p. This review discusses the possible mechanisms of exosome and their contents in PA and promotes the use of exosomes in both clinical diagnosis and treatment of this tumor.

ObjectiveCOVID-19 infection may affect thyroid function. However, changes in thyroid function in COVID-19 patients have not been well described. This systematic review and meta-analysis assess thyroxine levels in COVID-19 patients, compared with non-COVID-19 pneumonia and healthy cohorts during the COVID-19 epidemic.MethodsA search was performed in English and Chinese databases from inception to August 1, 2022. The primary analysis assessed thyroid function in COVID-19 patients, comparing non-COVID-19 pneumonia and healthy cohorts. Secondary outcomes included different severity and prognoses of COVID-19 patients.ResultsA total of 5873 patients were enrolled in the study. The pooled estimates of TSH and FT3 were significantly lower in patients with COVID-19 and non-COVID-19 pneumonia than in the healthy cohort (P < 0.001), whereas FT4 were significantly higher (P < 0.001). Patients with the non-severe COVID-19 showed significant higher in TSH levels than the severe (I2 = 89.9%, P = 0.002) and FT3 (I2 = 91.9%, P < 0.001). Standard mean differences (SMD) of TSH, FT3, and FT4 levels of survivors and non-survivors were 0.29 (P= 0.006), 1.11 (P < 0.001), and 0.22 (P < 0.001). For ICU patients, the survivors had significantly higher FT4 (SMD=0.47, P=0.003) and FT3 (SMD=0.51, P=0.001) than non-survivors.ConclusionsCompared with the healthy cohort, COVID-19 patients showed decreased TSH and FT3 and increased FT4, similar to non-COVID-19 pneumonia. Thyroid function changes were related to the severity of COVID-19. Thyroxine levels have clinical significance for prognosis evaluation, especially FT3.

Underwater acoustic (UWA) communications have been widely used but greatly impaired due to the complicated nature of the underwater environment. In order to improve UWA communications, modeling and understanding the UWA channel is indispensable. However, there exist many challenges due to the high uncertainties of the underwater environment and the lack of real-world measurement data. In this work, the capability of reservoir computing and deep learning has been explored for modeling the UWA communication channel accurately using real underwater data collected from a water tank with disturbance and from Lake Tahoe. We leverage the capability of reservoir computing for modeling dynamical systems and provided a data-driven approach to modeling the UWA channel using Echo State Network (ESN). In addition, the potential application of transfer learning to reservoir computing has been examined. Experimental results show that ESN is able to model chaotic UWA channels with better performance compared to popular deep learning models in terms of mean absolute percentage error (MAPE), specifically, ESN has outperformed deep neural network by 2% and as much as 40% in benign and chaotic UWA respectively.

The in-situ formed MgAl2O4–CaAl12O19 (MA–CA6) composites were fabricated in this study. To clarify the influence of the evolution of CA6 phase on the properties of MA–CA6 composites, the sintering temperature was carried out at 1200–1700 °C for 2 h. The results show that the growth and development of CA6 grains improves the densification and flexural strength of MA–CA6 composites. The formation of MA phase occurs at 1200 °C, while the CA6 phase is formed by the reaction of CaAl4O7 (CA2) and Al2O3 appears at 1400 °C. The plate-like CA6 grains intersect with each other, presenting regular hexagonal morphology with a high aspect ratio at 1500 °C. The CaO–Al2O3–SiO2 phase acts as an interface phase to regulate the growth and development of MA and CA6 grains. The CA6 phase was crystallized from the transient liquid phase CaO–Al2O3–SiO2 to significantly increase its thickness at 1600 °C. At the same time, as the sintering temperature rises, the apparent porosity of the sample decreases from 24% at 1400 °C to 4% at 1600 °C, and the flexural strength correspondingly increases from 96.6 MPa to 167 MPa. However, the suitable sintering temperature should not exceed 1600 °C for better properties of the composites.

Fusarium wilt, which affects common bean all across the world, is caused by Fusarium oxysporum f. sp. Phaseoli (Fop). It is necessary to have functional genes in response to Fop infection because they might be used to manage disease. As a crucial regulator, TGA-binding transcription factor (TGA) is engaged in the defense mechanism of plants against pathogens. The role of TGA regulators in common bean in response to Fop infection, however, has not been documented. Hence, we performed genome-wide identified and characterized eight TGA genes in common bean. In this study, eight PvTGA genes were distributed on six chromosomes and classified into four subgroups. The PvTGA genes have the same conserved bZIP and DOG1 domains, but there are specific sequence structures in different PvTGAs. Phylogenetic and synteny analysis explained that PvTGA gene has a close genetic relationship with legume TGAs and that PvTGA03 and PvTGA05 may play an important role in evolution. Transcriptome data explained that expression levels of PvTGA genes showed diversity in different tissues. After Fop inoculation, the expression levels of PvTGA03 and PvTGA07 were significantly different between resistant and susceptible genotypes. Under SA treatment, the expression levels of PvTGA03, PvTGA04, PvTGA06, PvTGA07 and PvTGA08 were significantly different. These results imply that PvTGA03 and PvTGA07 play key roles in SA-mediated resistance to Fusarium wilt. Together, these findings advance knowledge of the PvTGA gene family in common bean and will help future studies aimed at reducing Fusarium wilt.

The Madden–Julian oscillation (MJO) and its associated air–sea interactions during the onset process of the 2018/2019 Indonesian–Australian summer monsoon (IASM) are investigated based on the in situ data from a moored buoy off the coast of northwest Australia, along with ERA5 reanalysis and satellite data. The results verify that the IASM onset in mid-December 2018 was triggered by the first-branch eastward-propagating MJO (FEMJO) originating from the tropical Indian Ocean. However, the strong negative SST anomaly (SSTA) was evident off northwest Australia, which weakens FEMJO over northern Australia and shifts the convective center further northward. The mixed layer heat budget analysis based on the buoy observations reveals that the increased latent heat loss that occurred before the arrival of the FEMJO convection was primarily attributed to the large air–sea temperature difference and strong winds, resulting in the pronounced SSTA.

The East Australian Current (EAC) is an important western boundary current of the South Pacific subtropical Circulation with high mesoscale eddy kinetic energy (EKE). Based on satellite altimeter observations and outputs from the eddy-resolving ocean general circulation model (OGCM) for the Earth Simulator (OFES), the seasonal variability of EKE and its associated dynamic mechanism in the EAC region are studied. High EKE is mainly concentrated in the shear-region between the poleward EAC southern extension and the equatorward EAC recirculation along Australia's east coast, which is confined within the upper ocean (0-300 m). EKE in this area exhibits obvious seasonal variation, strong in austral summer with maximum (465±89 cm² s-²) in February and weak in winter with minimum (334±48 cm² s-²) in August. Energetics analysis from OFES suggests that the seasonal variability of EKE is modulated by the mixed instabilities composed of barotropic and baroclinic instabilities confined within the upper ocean, and barotropic instability (baroclinic instability) is the main energy source of EKE in austral summer (winter). The barotropic process is mainly controlled by the zonal shear of meridional velocities of the EAC southern extension and the EAC recirculation. The poleward EAC southern extension and the equatorward EAC recirculation are synchronously strengthened (weakened) due to the local positive (negative) sea level anomalies (SLA) under geostrophic equilibrium, and the barotropic instability dominated by zonal shear is enhanced (slackened), which results in a high (low) level of EKE in the EAC region.

Abstract Inflammatory bowel disease (IBD) has a close association with transketolase (TKT) that links glycolysis and the pentose phosphate pathway (PPP). However, how TKT functions in the intestinal epithelium remains to be elucidated. To address this question, we specifically delete TKT in intestinal epithelial cells (IECs). IEC TKT-deficient mice are growth retarded and suffer from spontaneous colitis. TKT ablation brings about striking alterations of the intestine, including extensive mucosal erosion, aberrant tight junctions, impaired barrier function, and increased inflammatory cell infiltration. Mechanistically, TKT deficiency significantly accumulates PPP metabolites and decreases glycolytic metabolites, thereby reducing ATP production, which results in excessive apoptosis and defective intestinal barrier. Therefore, our data demonstrate that TKT serves as an essential guardian of intestinal integrity and barrier function as well as a potential therapeutic target for intestinal disorders.