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A broadband online X-ray spectrometer has been designed and commissioned at the SUD beamline of the Shanghai Soft X-ray Free-Electron Laser Facility, which can deliver both SASE and seeded FEL pulses to user experiments, spanning the photon energy range of 50–620 eV. The resolving powers of the spectrometer calibrated via online measurement at 92 eV and 249 eV are ∼20000 and ∼15000, respectively, and the absolute photon energy is characterized by an electron time-of-flight spectrometer. The high energy resolution provided by the spectrometer can differentiate the fine structure in the FEL spectrum, to determine its pulse length.

Abstract Cervical cancer (CC) is the fourth most common cancer among women worldwide. NLR Family CARD Domain Containing 5 (NLRC5) plays an important role in tumorigenesis. However, its effect and mechanism in CC remains unclear. In this study, we aimed to investigate the function of NLRC5 in CC. NLRC5 was found to be down-regulated in CC tissues compared with normal cervical tissues. However, patients with higher NLRC5 expression had better prognosis, patients with higher age, HPV infection, lymph node metastasis, recurrence and histological grade had worse prognosis. Univariate and multivariate analyses showed NLRC5 to be a potential prognostic indicator for CC. Pearson correlation analysis showed that NLRC5 might exert its function in CC through autophagy related proteins, especially LC3. In vitro experiments demonstrated that NLRC5 inhibited LC3 levels and promoted the proliferation, migration, and invasion of CC cells by activating the PI3K/AKT signaling pathway. Treatment with LY294002 reversed the above phenotype. Taken together, our finding suggested that NLRC5 would participate in cervical tumorigenesis and progression by regulating PI3K/AKT signaling pathway. In addition, NLRC5 and LC3 combined as possible predictors in CC.

Abstract The innate immune molecule NLR family CARD domain-containing 5 (NLRC5) plays a significant role in endometrial carcinoma (EC) immunosurveillance. However, NLRC5 also plays a protumor role in EC cells. Mismatch repair gene deficiency (dMMR) can enable tumors to grow faster and also can exhibit high sensitivity to immune checkpoint inhibitors. In this study, we attempted to determine whether NLRC5-mediated protumor role in EC is via the regulation of dMMR. Our findings revealed that NLRC5 promoted the proliferation, migration, and invasion abilities of EC cells and induced the dMMR status of EC in vivo and in vitro. Furthermore, the mechanism underlying NLRC5 regulated dMMR was also verified. We first found NLRC5 could suppress nuclear factor-kappaB (NF-κB) pathway in EC cells. Then we validated that the positive effect of NLRC5 in dMMR was restricted when NF-κB was activated by lipopolysaccharides in NLRC5-overexpression EC cell lines. In conclusion, our present study confirmed the novel NLRC5/NF-κB/MMR regulatory mechanism of the protumor effect of NLRC5 on EC cells, thereby suggesting that the NLRC5-mediated protumor in EC was depend on the function of MMR.

The Shanghai Soft X-ray Free-Electron Laser (SXFEL) is the first X-ray free-electron laser facility in China. The SASE beamline, which consists of a pink-beam branch and a mono-beam branch, is one of the two beamlines in the Phase-I construction. The pink-beam branch opened for users in 2023 after successful first-round beamline commissioning. In this paper, the design of the beamline is presented and the performance of the pink-beam branch is reported. The measured energy-resolving power of the online spectrometer is over 6000 @ 400 eV. The focusing spot size of the pink beam is less than 3 µm in both the horizontal and vertical at the endstation.

The development of the smart grid recognizes the importance of projecting electrical net load forecasting, which represents the difference between load demand and installed renewable energy sources (RES), such as wind and solar power. For net load forecasting, many approaches like statistical models, machine learning, and deep learning have been developed. Because of the significant uncertainty of RES, these models suffer from poor forecasting accuracy. In this study, we propose the TransformGraph, a novel Transformer model for electricity net load forecasting, which combines the Transformer and graph convolutional network (GCN). Firstly, the GCN is used as an input embedding layer to encode multivariate input sequences, which can fill the gap that the correlation information is not thoroughly considered in the Transformer. Then, the self-attention mechanism in the Transformer is used to capture the temporal dependence of the sequence data. Finally, the predicted load values are output using a feed forward neural network. Data from three countries derived from Open Power System Data (OPSD) sources are employed for the case study. Comparisons between the TransformGraph and the other five forecasting models demonstrate that the proposed one has higher forecasting accuracy and stability.

Toll receptors are involved in the development and innate immunity of insects. BmToll9-1 is an important immune receptor in the Toll pathway. Previous studies have focused on its role as a receptor in immune response. In this study, we aimed to investigate the role of BmToll9-1 as a regulator in the immune response. The expression profiles demonstrated that BmToll9-1 was predominantly expressed in the midgut. RNA interference (RNAi) of BmToll9-1 was found to be effective in the midgut via the injection of dsRNA, which resulted in smaller and lighter larvae and cocoons. Most signaling genes in the Toll pathway and downstream effector genes were downregulated after the RNAi of BmToll9-1. The hemolymph from BmToll9-1-silenced larvae showed decreased antibacterial activity against Escherichia coli, either in growth curve or inhibition zone experiments. The above results indicate that BmToll9-1 might be positively involved in the immune pathway of silkworm. As a positive regulator, BmToll9-1 might function mainly in the gut to maintain microbial homeostasis to regulate the growth of silkworms. Silencing of BmToll9-1 downregulates the signaling genes in the Toll pathway and antimicrobial peptide (AMP) production, resulting in decreased antibacterial activity in the hemolymph.

Agroforestry management has immense potential in enhancing forest carbon sequestration and mitigating climate change. Yet the impact and response mechanism of compound fertilization rates on carbon sinks in agroforestry systems remain ambiguous. This study aims to elucidate the impact of different compound fertilizer rates on soil greenhouse gas (GHG) emissions, vegetation and soil organic carbon (SOC) sinks, and to illustrate the differences in agroforestry systems’ carbon sinks through a one-year positioning test across 12 plots, applying different compound fertilizer application rates (0 (CK), 400 (A1), 800 (A2), and 1600 (A3) kg ha−1). The study demonstrated that, after fertilization, the total GHG emissions of A1 decreased by 4.41%, whereas A2 and A3 increased their total GHG emissions by 17.13% and 72.23%, respectively. The vegetation carbon sequestration of A1, A2, and A3 increased by 18.04%, 26.75%, and 28.65%, respectively, and the soil organic carbon sequestration rose by 32.57%, 42.27% and 43.29%, respectively. To sum up, in contrast with CK, the ecosystem carbon sequestration climbed by 54.41%, 51.67%, and 0.90%, respectively. Our study suggests that rational fertilization can improve the carbon sink of the ecosystem and effectively ameliorate climate change.

Background: Placenta accreta spectrum (PAS) disorders are increasing in incidence and represent a significant contributor to severe maternal morbidity in the US. Prior uterine surgeries other than cesarean section are important, yet less common, risk factors for PAS. Case: This is a case of a 43-year-old woman with a prior history of cervical cancer necessitating radical trachelectomy. She was subsequently diagnosed with a complete placenta previa with a high degree of suspicion for PAS. Multidisciplinary teams convened to plan for delivery. A cesarean hysterectomy was performed at 32 weeks. Final surgical pathology confirmed the presence of morbidly adherent placenta invading the vaginal cuff. Conclusion: Patients who are diagnosed with early-stage cervical cancers have the option of fertility-preserving surgical management. Serial ultrasound evaluations, specifically looking for PAS, might be warranted in post-trachelectomy pregnancies.

This study aims to promote the communication and cognition of China’s national image in the world by investigating the utilization of multimodal metaphors at the Opening Ceremony of Beijing 2022 Winter Olympics and the national image that the multimodal metaphors indicate. This paper utilizes the multimodal corpus that contains multiple media types such as texts, audio and images to conduct multimodal analysis and to investigate how to achieve effective transmission from three perspectives (the cognitive, emotional, and behavioral aspects). Further, in order to confirm the effectiveness of this transmission, data analysis is carried out based on the comments about the opening ceremony of Beijing Winter Olympics on YouTube. Based on the results of data analysis and discussion, the study concludes four images of China from the Opening Ceremony: a major country with firm cultural self-confidence, with the endeavor to build a human community with a shared future, with advanced science and technology, and with persistence of sustainable development

Abstract Uterine and ovarian cancers are the most common gynecologic cancers. N6−methyladenosine (m6A), an important internal RNA modification in higher eukaryotes, has recently become a hot topic in epigenetic studies. Numerous studies have revealed that the m6A-related regulatory factors regulate the occurrence and metastasis of tumors and drug resistance through various mechanisms. The m6A-related regulatory factors can also be used as therapeutic targets and biomarkers for the early diagnosis of cancers, including gynecologic cancers. This review discusses the role of m6A in gynecologic cancers and summarizes the recent advancements in m6A modification in gynecologic cancers to improve the understanding of the occurrence, diagnosis, treatment, and prognosis of gynecologic cancers.

Fe-S clusters are ubiquitous inorganic cofactors found in proteins across all domains of life, including viruses. Their prevalence stems from their unique redox and structural plasticity that supports functions ranging from electron transfer and catalysis to stabilization of protein structure. Although the ability of Fe-S clusters to exchange electrons is often functionally crucial, it can also act as an Achilles heel when these cofactors are exposed to oxidizing conditions, often leading to their degradation. This O2 sensitivity has rendered certain Fe-S clusters untraceable, particularly when the nascent proteins are isolated under ambient conditions. As a consequence of this O2 sensitivity, a growing number of proteins with roles in viral infection have been found to harbor Fe-S clusters rather than the annotated Zn2+ cofactor. The enigmatic protein X (HBx) of the Hepatitis B Virus is a multifunctional protein essential for viral replication and development of liver disease. Although HBx has defied biochemical characterization for over forty years, it has been shown to coordinate a redox-active Fe-S cluster that represents a significant feature for establishing its molecular function. The present review narrates the approaches to validate the HBx metallocofactor that can be broadly applied as a guide for uncovering the presence of Fe-S clusters in proteins with non-canonical sequence motifs.

【Objective】Hexose transporter (HXT) is a kind of monosaccharide transporter, which can transport mannose, fructose, glucose and other hexose substances across the membrane, and participate in the development of pollen and the growth of the whole plant, and then determine the internal quality of fruit. Bioinformatics and expression characteristics of HXT gene in pitaya were analyzed in order to provide a theoretical basis for regulating the fruit quality of pitaya.【Method】A hexose transporter gene was obtained by gene cloning. Bioinformatics analysis was conducted by using NCBI, BioEdit, DNAMAN and other software or databases. The soluble sugar contents were determined by HPLC at fruit maturity stage. The relative expression characteristics of HTX gene in different lines of pitaya and different parts of afruit were analyzed by fluorescence quantitative PCR.【Result】A HXT gene named HuHXTwas cloned from pitaya fruit by PCR amplification. The total length of the gene was 1 230 bp, encoding 410 amino acids. The protein instability coefficient was 35.59, with 32 Ser, 15 Thr and 15 Tyr. There were sucrose, glucose and fructose in pitaya, and glucose and fructose were the main components. The expression of HuHXT was the highest in No. 97 line, followed by Zhanhong No. 2 and No. 128, while No. 15 and No. 16 had the lowest expression level. The expression level of HuHXT was not significantly different in different parts of a fruit. The expression in parts near the pericarp was higher other parts of a fruit.【Conclusion】HuHXT is a member of the Sugar-tr gene family. HuHXT protein is a stable protein with strong hydrophobicity. As a membrane protein, its secondary structure is mainly α-helix and random curl. There is negative correlation between the relative expression of HuHXT and the content of glucose, that is, the higher the HuHXT expression level, the lower the glucose content.

Accurate and timely estimation of cotton yield over large areas is essential for precision agriculture, facilitating the operation of commodity markets and guiding agronomic management practices. Remote sensing (RS) and crop models are effective means to predict cotton yield in the field. The satellite vegetation indices (VIs) can describe crop yield variations over large areas but can’t take the exact environmental impact into consideration. Climate variables (CVs), the result of the influence of spatial heterogeneity in large regions, can provide environmental information for better estimation of cotton yield. In this study, the most important VIs and CVs for estimating county-level cotton yield across Xinjiang Province were screened out. We found that the VIs of canopy structure and chlorophyll contents, and the CVs of moisture, were the most significant factors for cotton growth. For yield estimation, we utilized four approaches: least absolute shrinkage and selection operator regression (LASSO), support vector regression (SVR), random forest regression (RFR) and long short-term memory (LSTM). Due to its ability to capture temporal features over the long term, LSTM performed best, with an R2 of 0.76, root mean square error (RMSE) of 150 kg/ha and relative RMSE (rRMSE) of 8.67%; moreover, an additional 10% of the variance could be explained by adding CVs to the VIs. For the within-season yield estimation using LSTM, predictions made 2 months before harvest were the most accurate (R2 = 0.65, RMSE = 220 kg/ha, rRMSE = 15.97%). Our study demonstrated the feasibility of yield estimation and early prediction at the county level over large cotton cultivation areas by integrating satellite and environmental data.

Shanghai Soft X-ray Free-Electron Laser (SXFEL) is the first X-ray free-electron laser facility in China. The initial commissioning of the beamline was carried out in May 2021. Herein, we present a status report and the first experimental results obtained during the early commissioning of Kirkpatrick-Baez (KB) mirrors for the Coherent Scattering and Imaging (CSI) endstation, including three types of diagnostics. A bright X-ray focal spot of less than 3 μm was achieved by using edge-scan and silicon ablation imprint measurements. In order to confirm the spot size, the attenuated beam and full beam are used respectively for the two measurement methods.

Dose–response experiments and data analyses are often carried out according to an optimal design under a model assumption. A two-parameter logistic model is often used because of its nice mathematical properties and plausible stochastic response mechanisms. There is an extensive literature on its optimal designs and data analysis strategies. However, a model is at best a good approximation in a real-world application, and researchers must be aware of the risk of model mis-specification. In this paper, we investigate the effectiveness of the sequential ED-design, the D-optimal design, and the up-and-down design under the three-parameter logistic regression model, and we develop a numerical method for the parameter estimation. Simulations show that the combination of the proposed model and the data analysis strategy performs well. When the logistic model is correct, this more complex model has hardly any efficiency loss. The three-parameter logistic model works better than the two-parameter logistic model in the presence of model mis-specification.

Oxygen-free high-conductivity copper (OFHC), chromium-zirconium copper (CuCrZr), and Glidcop® AL-15 are widely used in the high heat load absorber elements at the front end of synchrotron radiation facilities. It is necessary to choose the most suitable material according to the actual engineering conditions (such as the specific heat load, material performance, and costs). In the long-term service period, the absorber elements have to bear hundreds or kilowatts of high heat load and its “load-unload” cyclic loading mode. Therefore, the thermal fatigue and thermal creep properties of the materials are critical and have been extensively studied. In this paper, based on the published pieces of the literature, the thermal fatigue theory, experimental principles, methods, test standards, test types of equipment, and key indicators of the thermal fatigue performance of typical copper metal materials used in the front end of synchrotrons radiation Facilities are reviewed, as well as the relevant studies carried out by the well-known synchrotron radiation institutions. In particular, the fatigue failure criteria for these materials and some effective methods for improving the thermal fatigue resistance performance of the high-heat load components are also presented.

Students’ behaviors have a close relationship with their learning efficiencies, particularly about professional knowledge. Different types of behaviors should have different influences. Disclosing the special relationship between undergraduate students’ conscious safety behaviors in their laboratory experiments with their learning efficiencies is important for fostering them into professional talents. In this study, a course entitled “Advanced Methods of Materials Characterization” was arranged to contain three sections: theoretical learning in the classroom, eight characterization experiments in the laboratory in sequence, and self-training to apply the knowledge. In the final examination, eighteen percent was allocated to the examination questions about safety issues. The students’ scores for this section were associated with their total roll scores. Two quantitative relationships are disclosed. One is between the students’ final examination score (y) and their subjective consciousness of safety behaviors (x) in their laboratory experiments, as y = 5.56 + 4.83 x (R = 0.9192). The other is between their grade point average (y) and safety behavior evaluation (x) as y = 0.51 + 0.15 x (R = 0.7296). Undergraduate students’ behaviors in scientific laboratories need to be verified to have a close and positive relationship with their professional knowledge learning efficiencies. This offers a hint that improving students’ safety behaviors and enhancing their subjective safety awareness are conducive to improving their learning efficiency for professional knowledge.

Persistent human papillomavirus (HPV) infection will eventually lead to clinical problems, varying from verrucous lesions to malignancies like cervical cancer, oral cancer, anus cancer, and so on. To address the aforementioned problems, nanotechnology-based strategies have been applied to detect the virus, prevent the interaction between virus and mammalian cells, and treat the virus-infected cells, due mainly to the unique physicochemical properties of nanoparticles. In this regard, many nanotechnology-based chemotherapies, gene therapy, vaccination, or combination therapy have been developed. In this Minireview, we outline the pathogenesis of HPV infection and the recent advances in nanotechnology-based weapons that can be applied in combating HPV-associated diseases.

Once an emergency event (EE) happens, emergency decision-making (EDM) plays a key role in mitigating the loss. EDM is a complex problem. Compared with conventional decision-making problems, more experts participate in decision-making. It usually has the feature of large group emergency decision-making (LGEDM). This paper proposes a large group emergency decision-making method based on Bayesian theory, relative entropy, and Euclidean distance, which is used for large group emergency decision-making with uncertain probabilities of occurrence, unknown attribute weights, and expert weights. In order to improve the accuracy of decision-making, Bayesian method is introduced into the calculation of scenario probability in the process of LGEDM. In the decision-making process, the experts’ risk preference is considered. The experts’ decision preference information is a symmetric and uniformly distributed interval value. The perceived utility values of the experts are obtained by introducing prospect theory. Euclidean distance is used to measure the contributions of experts to aggregation similarity, and different weights are given to experts according to their contributions. A relative entropy model with completely unknown weight information constraints is established to obtain attribute weights, which takes into account the differences of different alternatives under the same attribute and the differences between alternatives and the ideal solution. An example of nuclear power emergency decision-making illustrates the effectiveness of this method.

Two new species of Microplitis Förster, 1862, M. bomiensis Zhang, sp. nov., and M. paizhensis Zhang, sp. nov. from Tibet, China are described and illustrated. A key to the species of the genus Microplitis Förster from China is added.

For the emergency evacuation of cruise ships in case of sudden fire, this research proposes a dynamic route optimization method based on the improved A∗ algorithm for real-time information, in order to obtain the real-time optimal evacuation route. Initially, a basic network topology diagram is established according to the internal structure of the cruise ship. Before the occurrence of the accident, the A∗ algorithm can be applied to obtain an a priori evacuation network consisting of all the optimal routes from each node to the exit. At the time of the accident, the dynamic diffusion of fire can be simulated using Fire Dynamics Simulator (FDS) based on the preliminary information of the fire, so as to estimate the impact of the fire domain on each node of the network. Then, according to the fire dynamic diffusion data, the evacuation route planning is carried out by the improved A∗ algorithm applying the breadth-first search strategy, so as to determine the optimal route from the current node to the safety exit and to reduce the possibility of casualties due to the uncertainty of the fire during the evacuation. This model allows for both people’s safety and evacuation time to dynamically avoid fire-affected nodes and helps people to reach the safe area as soon as possible. Finally, the evacuation model is established according to the open-source cruise ship structure, and the evacuation process of people under the dynamic spread of cruise ship fire is simulated. The results show that the route planning method proposed in this research works out well in evacuating mass people, which can effectively reduce the evacuation time and improve the safety of the evacuation process.

A dual-mode hybrid step-up circuit for electromagnetic energy harvesting (EVEH) is proposed in this paper, with the merits of continuous output power delivery with and without external vibrations, simple architecture, and no need for extra circuits to start up. The proposed hybrid converter combines a multi-stage voltage multiplier (VM) with a boost regulator, which utilizes the winding inductance of the electromagnetic energy harvester as a boost inductor. With external vibration, the proposed circuit powers the load and stores energy in the super-capacitor through VM mode. When external vibration disappears, it automatically switches to boost mode and powers the load using the energy stored in the supercapacitor. For hybrid mode operation, the number of VM stages is optimized considering the following three aspects: sufficient voltage gains when vibration is on, time durations to provide constant power when vibration is off for as long as possible, and low losses at VM stage. A GaN-based dual-mode hybrid converter is built to verify the output regulation capability with an in-house-designed electromagnetic energy harvester. The outputs of the hybrid circuit achieve 4.05 V and 1.64 mW at a 100-Hz external vibration frequency and an acceleration of 0.7 g. The peak efficiency of the proposed hybrid converter reaches 60.7%. When external vibration disappears, the circuit is able to maintain a stable output for 13 s with a super-capacitor of 0.1 F.

Diachasmimorpha longicaudata is the most widely used endoparasitoid in biocontrol programmes against various species of tephritids and is continuously mass-reared under laboratory conditions at a constant temperature; however, little is known about how varying the temperature might affect the effectiveness of the mass rearing of immature D. longicaudata. This study aimed to determine the optimum temperature for the development of larvae D. longicaudata the larvae of its host, Bactrocera dorsalis. Third-instar B. dorsalis were exposed for 4 h to five pairs of parasitoids, and then they were kept at one of six temperatures ranging from 19°C to 34°C. The activities of three major antioxidant enzymes (CAT, POX, SOD) were individually measured 4, 24, 48 and 72 h after exposure to each of the six temperatures. The results were as follows: for CAT the highest CAT activities were recorded at 25°C (intervals 5-24 h and 25-48 h), at 28°C (interval 0-4 h) and at 31°C (interval 49-72 h), and for POX and SOD identically at 25°C (intervals 0-4 h, 5-24 h) and at 31°C (intervals 25-48 h, 49-72 h), respectively. Subsequently, the effects keeping the parasitized larvae at these different temperatures on the biological attributes of D. longicaudata reared under laboratory conditions were investigated. The percentage of their eggs that hatched, percentage of adults that emerged, pupal weight and longevity were significantly greater than that recorded for the control when the parasitized host larvae were kept at 28°C for 4 h, 25°C for 5 and 48 h and 31°C for 49 and 72 h.

Finite mixture models are widely used in scientific investigations. Due to their non-regularity, there are many technical challenges concerning inference problems on various aspects of the finite mixture models. After decades of effort by statisticians, substantial progresses are recorded recently in characterising large sample properties of some classical inference methods when applied to finite mixture models, providing effective numerical solutions for mixture model-based data analysis, and the invention of novel inference approaches. This paper aims to provide a comprehensive summary on large sample properties of some classical statistical methods and recently developed modified likelihood ratio test and EM-test for the order of the finite mixture model. The presentation de-emphasises the rigour in order to gain some insights behind some complex technical issues. The paper wishes to recommend the EM-test as the most promising approach to data analysis problems from all models with mixture structures.

In this work, a spherical nano core-shell material was constructed by encapsulating Fe3O4 microsphere into conductive polymer-metal composite shell. The Fe3O4 microspheres were fabricated by assembling large amounts of Fe3O4 nano-crystals, which endowed the microspheres with super-paramagnetic property and high saturation magnetization. The polymer-metal composite shell was constructed by inserting Pt nano-particles (NPs) into the conductive polymer polypyrrole (PPy). As size and dispersion of the Pt NPs has an important influence on their surface area and surface energy, it was effective to enlarge the interface area between PPy and Pt NPs, enhance the electron transfer efficiency of PPy/Pt composite shell, and reinforced the shell’s structural stability just by tuning the size and dispersion of Pt NPs. Moreover, core-shell structure of the materials made it convenient to investigate the PPy/Pt shell’s shielding effect on the Fe3O4 core’s magnetic response to external magnetic fields. It was found that the saturation magnetization of Fe3O4/PPy/Pt core-shell material could be reduced by 20.5% by regulating the conductivity of the PPy/Pt shell. Keywords: Super-paramagnetic, Conductivity, Magnetic shielding, Structural stability

The paper presents a novel pressure sensor based on a silicon nitride (SiNx) nanocoated long-period grating (LPG). The high-temperature, radio-frequency plasma-enhanced chemical-vapor-deposited (RF PECVD) SiNx nanocoating was applied to tune the sensitivity of the LPG to the external refractive index. The technique allows for deposition of good quality, hard and wear-resistant nanofilms as required for optical sensors. Thanks to the SiNx nanocoating it is possible to overcome a limitation of working in the external-refractive-index range, which for a bare fiber cannot be close to that of the cladding. The nanocoated LPG-based sensing structure we developed is functional in high-refractive-index liquids (nD > 1.46) such as oil or gasoline, with pressure sensitivity as high as when water is used as a working liquid. The nanocoating developed for this experiment not only has the highest refractive index ever achieved in LPGs (n > 2.2 at λ = 1,550 nm), but is also the thinnest (