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On February 6, 2023, a devastating earthquake with a moment magnitude of MW7.8 struck the town of Pazarcik in south-central Türkiye, followed by another powerful earthquake with a moment magnitude of MW7.6 that struck the nearby city of Elbistan 9 h later. To study the characteristics of surface deformation caused by this event and the influence of fault rupture, this study calculated the static coseismic deformation of 56 stations and dynamic displacement waveforms of 15 stations using data from the Turkish national fixed global navigation satellite system (GNSS) network. A maximum static coseismic displacement of 0.38 m for the MW7.8 Kahramanmaras earthquake was observed at station ANTE, 36 km from the epicenter, and a maximum dynamic coseismic displacement of 4.4 m for the MW7.6 Elbistan earthquake was observed at station EKZ1, 5 km from the epicenter. The rupture-slip distributions of the two earthquakes were inverted using GNSS coseismic deformation as a constraint. The results showed that the Kahramanmaras earthquake rupture segment was distinct and exposed on the ground, resulting in significant rupture slip along the Amanos and Pazarcik fault segments of the East Anatolian Fault. The maximum slip in the Pazarcik fault segment was 10.7 m, and rupture occurred at depths of 0–15 km. In the Cardak fault region, the Elbistan earthquake caused significant ruptures at depths of 0–12 km, with the largest amount of slip reaching 11.6 m. The Coulomb stress change caused by the Kahramanmaras earthquake rupture along the Cardak fault segment was approximately 2 bars, and the area of increased Coulomb stress corresponded to the subsequent rupture region of the MW7.6 earthquake. Thus, it is likely that the MW7.8 earthquake triggered or promoted the MW7.6 earthquake. Based on the cumulative stress impact of the MW7.8 and MW7.6 events, the southwestern segment of the East Anatolian Fault, specifically the Amanos fault segment, experienced a Coulomb rupture stress change exceeding 2 bars, warranting further attention to assess its future seismic hazard risk.

This study proposed an interpretable multi-scale infrared small object detection network (IMD-Net) design method to improve the precision of infrared small object detection and contour segmentation in complex backgrounds. To this end, a multi-scale object enhancement module was constructed, which converted artificially designed features into network structures. The network structure was used to enhance actual objects and extract shallow detail and deep semantic features of images. Next, a global object response, channel attention, and multilayer feature fusion modules were introduced, combining context and channel information and aggregated information, selected data, and decoded objects. Finally, the multiple loss constraint module was constructed, which effectively constrained the network output using multiple losses and solved the problems of high false alarms and high missed detections. Experimental results showed that the proposed network model outperformed local energy factor (LEF), self-regularized weighted sparse model (SRWS), asymmetric contextual modulation (ACM), and other state of the art methods in the intersection-over-union (IoU) and Fmeasure values by 10.8% and 11.3%, respectively. The proposed method performed best on the currently available datasets, achieving accurate detection and effective segmentation of dim and small objects in various infrared complex background images.

AbstractObjective Patients with ureteral calculi and systemic inflammatory response syndrome (SIRS) often require emergency drainage, and percutaneous nephrostomy (PCN) and retrograde ureteral stent insertion (RUSI) are the most commonly used methods. Our study aimed to identify the best choice (PCN or RUSI) for these patients and to examine the risk factors for progression to urosepsis after decompression.Methods A prospective, randomized clinical study was performed at our hospital from March 2017 to March 2022. Patients with ureteral stones and SIRS were enrolled and randomized to the PCN or RUSI group. Demographic information, clinical features and examination results were collected.Results Patients (n = 150) with ureteral stones and SIRS were enrolled into our study, with 78 (52%) patients in the PCN group and 72 (48%) patients in the RUSI group. Demographic information was not significantly different between the groups. The final treatment of calculi was significantly different between the two groups (p

Abstract Background Cervical cancer patients receiving radiotherapy and chemotherapy require accurate survival prediction methods. The objective of this study was to develop a prognostic analysis model based on a radiomics score to predict overall survival (OS) in cervical cancer patients. Methods Predictive models were developed using data from 62 cervical cancer patients who underwent radical hysterectomy between June 2020 and June 2021. Radiological features were extracted from T2-weighted (T2W), T1-weighted (T1W), and diffusion-weighted (DW) magnetic resonance images prior to treatment. We obtained the radiomics score (rad-score) using least absolute shrinkage and selection operator (LASSO) regression and Cox’s proportional hazard model. We divided the patients into low- and high-risk groups according to the critical rad-score value, and generated a nomogram incorporating radiological features. We evaluated the model’s prediction performance using area under the receiver operating characteristic (ROC) curve (AUC) and classified the participants into high- and low-risk groups based on radiological characteristics. Results The 62 patients were divided into high-risk (n = 43) and low-risk (n = 19) groups based on the rad-score. Four feature parameters were selected via dimensionality reduction, and the scores were calculated after modeling. The AUC values of ROC curves for prediction of 3- and 5-year OS using the model were 0.84 and 0.93, respectively. Conclusion Our nomogram incorporating a combination of radiological features demonstrated good performance in predicting cervical cancer OS. This study highlights the potential of radiomics analysis in improving survival prediction for cervical cancer patients. However, further studies on a larger scale and external validation cohorts are necessary to validate its potential clinical utility.

(1) Background: Laizhou Bay is an important aquaculture area in the north of China. Oplegnathus punctatus is one of the species with high economic benefits. In recent years, the water environment of Laizhou Bay has reached a mild eutrophication level, while microorganisms are an important group between the environment and species. In this study, we evaluated alterations in environmental elements, microbial populations, and antibiotic resistance genes (ARGs) along with their interconnections during Oplegnathus punctatus net culture. (2) Methods: A total of 142 samples from various water layers were gathered for metagenome assembly analysis. Mariculture increases the abundance of microorganisms in this culture area and makes the microbial community structure more complex. The change had more significant effects on sediment than on seawater. (3) Results: Certain populations of cyanobacteria and Candidatus Micrarchaecta in seawater, and Actinobacteria and Thaumarchaeota in sediments showed high abundance in the mariculture area. Antibiotic resistance genes in sediments were more sensitive to various environmental factors, especially oxygen solubility and salinity. (4) Conclusions: These findings highlight the complex and dynamic nature of microorganism–environment–ARG interactions, characterized by regional specificity and providing insights for a more rational use of marine resources.

In plants, WRKY transcription factors play a crucial role in plant growth, development, and response to abiotic and biotic stress. Cowpea (Vigna unguiculata) is an important legume crop. However, cowpea Fusarium wilt (CFW), caused by Fusarium oxysporum f. sp. tracheiphilum (Fot), poses a serious threat to its production. In this study, we systematically identified members of the cowpea WRKY (VuWRKY) gene family and analyzed their expression patterns under CFW stress. A total of 91 WRKY transcription factors were identified in the cowpea genome. Phylogenetic and synteny analyses indicated that the expansion of VuWRKY genes in cowpea is primarily due to recent duplication events. Transcriptome analysis of cowpea inoculated with Fo revealed 31 differentially expressed VuWRKY genes, underscoring their role in the response to CFW infection. Four differentially expressed WRKY genes were selected for validation. Subcellular localization and Western blot assays showed their nuclear localization and normal expression in N. benthamiana. Additionally, yeast one-hybrid assays demonstrated that VuWRKY2 can bind to the promoter region of the Catalase (CAT) gene, indicating its potential role in transcriptional regulation. This study establishes a foundation for further exploration of the role and regulatory mechanisms of VuWRKY genes in response to CFW stress.

In this research, the mitochondrial genome of the Streptopelia decaocto was sequenced and examined for the first time to enhance the comprehension of the phylogenetic relationships within the Columbidae. The complete mitochondrial genome of Streptopelia decaocto (17,160 bp) was structurally similar to the recognized members of the Columbidae family, but with minor differences in gene size and arrangement. The structural AT content was 54.12%. Additionally, 150 mitochondrial datasets, representing valid species, were amassed in this investigation. Maximum likelihood (ML) and Bayesian inference (BI) phylogenetic trees and evolutionary time relationships of species were reconstructed based on cytb gene sequences. The findings from the phylogenetic evaluations suggest that the S. decaocto was classified under the Columbinae subfamily, diverging from the Miocene approximately 8.1 million years ago, indicating intricate evolutionary connections with its close relatives, implying a history of species divergence and geographic isolation. The diversification of the Columbidae commenced during the Late Oligocene and extended into the Miocene. This exploration offers crucial molecular data for the S. decaocto, facilitating the systematic taxonomic examination of the Columbidae and Columbiformes, and establishing a scientific foundation for species preservation and genetic resource management.

As virtual reality technology advances, 3D environment design and modeling have garnered increasing attention. Applications in networked virtual environments span urban planning, industrial design, and manufacturing, among other fields. However, existing 3D modeling methods exhibit high reconstruction error precision, limiting their practicality in many domains, particularly environmental design. To enhance 3D reconstruction accuracy, this study proposes a digital image processing technology that combines binocular camera calibration, stereo correction, and a convolutional neural network (CNN) algorithm for optimization and improvement. By employing the refined stereo-matching algorithm, a 3D reconstruction model was developed to augment 3D environment design and reconstruction accuracy while optimizing the 3D reconstruction effect. An experiment using the ShapeNet dataset demonstrated that the evaluation indices—Chamfer distance (CD), Earth mover’s distance (EMD), and intersection over union—of the model constructed in this study outperformed those of alternative methods. After incorporating the CNN module in the ablation experiment, CD and EMD increased by an average of 0.1 and 0.06, respectively. This validates that the proposed CNN module effectively enhances point cloud reconstruction accuracy. Upon adding the CNN module, the CD index and EMD index in the dataset increased by an average of 0.34 and 0.54, respectively. These results indicate that the proposed CNN module exhibits strong predictive capabilities for point cloud coordinates. Furthermore, the model demonstrates good generalization performance.

Co-N-CDs-based MXene nanocomposites (MXene@PDA/Co-N-CDs) were constructed by decorating Co-N-CDs on polydopamine-functionalized MXene nanosheets. Both Co-N-CDs and MXene nanosheets have peroxidase-like activity; when the two materials are combined to form MXene@PDA/Co-N-CDs nanocomposites, the peroxide-like activity can be further enhanced. MXene@PDA/Co-N-CDs could oxidize the substrate 3,3′5,5′-tetramethylbenziline (TMB) to form ox-TMB, as confirmed by detecting the absorption of the blue products. A highly selective colorimetric biosensor was developed for the determination of glutathione (GSH) in the concentration range of 0.3 to 20 µM with a lower detection limit (LOD) of 0.12 µM, which realized the accurate detection of GSH in human serum and urine samples. Moreover, in the tumor microenvironment, MXene@PDA/Co-N-CDs could catalyze hydrogen peroxide to produce hydroxyl free radicals and produce a photothermal effect under the exposure of NIR-I irradiation. The catalytic activity of MXene@PDA/Co-N-CD nanocomposites was fully achieved for the death of cancer cells through photothermal/photodynamic synergistic therapy. The MXene@PDA/Co-N-CDs nanozyme offers multiple applications in GSH detection and tumor therapy.

This study proposes a new deep neural network to solve the multi-band image synchronous fusion problem (MBF-Net). Unlike other deep learning-based methods, our network architecture design combines the ideas of model-driven and data-driven methods, so it is more interpretable. First, a new multi-band image synchronous fusion model is proposed. The source image in the data fidelity terms and the prior regularization are implicitly represented by the deep learning network and jointly learned from the training data. The proposed model is then solved using a half quadratic splitting (HQS) algorithm and unfolded into a deep fusion network. In addition, a new saliency loss function is proposed to retain thermal radiation information to enhance the fusion effect. Finally, the experimental results on the TNO dataset demonstrated the effectiveness of the proposed MBF-Net.

Solar radiation is a key driver of ecosystem carbon and water fluxes. However, the impacts of radiation quantity and quality on the carbon-water coupling are not well distinguished. In this study, we used simultaneous flux and radiation measurements at two grassland sites in northeastern China to explore the joint impacts of photosynthetically active radiation (PAR) and diffuse fraction ( K _d ) on carbon and water fluxes and their coupling relationships. Under the low to medium PAR levels (280 W m ^−2 ), the GPP continued to grow at the southern site but showed limited responses to K _d at the northern site, likely due to the temperature constraint in the latter. Meanwhile, the contribution of evaporation to ET increased under the high radiation conditions, resulting in a decreased ET due to the reduced direct radiation following K _d increment at both sites. Consequently, water use efficiency (WUE) increased with K _d for all radiation levels but showed low sensitivity to PAR changes due to the synchronized GPP and ET responses to PAR. This study unraveled the positive dependence of ecosystem WUE on the increased K _d though with varied sensitivities of GPP and ET under different PAR levels, highlighting the strong impacts of diffuse radiation on ecosystem fluxes over the regions with aerosol pollution and cloud variations.

As an important carrier of science education, ecological landscape development and regional ecological civilization construction, the quality of geological landscape resources has a direct impact on its landscape charm, and the protection of landscape resources is directly related to its sustainable development ability and regional ecological civilization construction. To avoid or reduce the negative impact of architecture on the environment, the development of architectural landscape based on the perspective of geology and ecology is the top priority of healthy and sustainable development. In this paper, the visual sensitivity of the landscape was assessed by GIS (Geographic Information System, GIS) software technology, by calculating and analyzing the relative slope of the terrain, and visualizing the results through visual sensitivity classification. Based on summarizing and analyzing the previous research results, this paper expounds the geological landscape system and resource system, and introduces the architectural landscape features of environmental landscape protection. Combined with the geological environment planning architectural landscape, the concept of architectural planning and landscape design is integrated, the architectural landscape based on geological environment protection is constructed, and the spatial organization and layout of buildings in the environmental landscape is planned. Finally, landscape visual sensitivity was evaluated based on GIS. The research results show that the architectural landscape and geological environment protected by geological environment landscape can be organically combined, and the landscape has strong visual attraction. The research results of this paper solve the conflict between architecture and geological ecology and provide scientific basis for environmental landscape protection of geological ecology. The composite score of visual sensitivity was obtained by GIS calculation. The most visually sensitive place ranked 25th, while the most visually sensitive place ranked 13th.

BackgroundElderly patients having esophagectomies often become hypothermic which may promote complications. We tested the hypothesis that aggressive warming to a core temperature of 37°C reduces postoperative pulmonary complications (PPCs) in elderly patients having esophageal cancer resections.MethodsThis study was a pre-defined sub-study of a multi-center, parallel group, superiority trial (PROTECT). Patients aged >65 years and having elective radical resection of esophageal cancer in a single center were randomly allocated into either aggressive warming group (target intraoperative core temperatures of 37°C) or routine thermal management group (target intraoperative core temperatures of 35.5°C). The primary endpoint was the incidence of PPCs. Secondary endpoints included duration of chest tube drainage and other postoperative complications.ResultsA total of 300 patients were included in the primary analysis. PPCs occurred in 27 (18%) of 150 patients in the aggressive warming group and 31 (21%) of 150 patients in the routine thermal management group. The relative risk (RR) of aggressive versus routine thermal management was 0.9 (95% CI: 0.5, 1.4; p = 0.56). The duration of chest drainage in patients assigned to aggressive warming was shorter than that assigned to routine thermal management: 4 (3, 5) days vs. 5 (4, 7) days; hazard ratio (HR) 1.4 [95% CI: 1.1, 1.7]; p = 0.001. Fewer aggressively warmed patients needed chest drainage for more than 5 days: 30/150 (20%) vs. 51/150 (34%); RR:0.6 (95% CI: 0.4, 0.9; p = 0.03). The incidence of other postoperative complications were similar between the two groups.ConclusionAggressive warming does not reduce the incidence of PPCs in elderly patients receiving esophagectomy. The duration of chest drainage was reduced by aggressive warming. But as a secondary analysis of a planned sub-group study, these results should be considered exploratory.Clinical trial registrationhttps://www.chictr.org.cn/showproj.aspx?proj=37099, ChiCTR1900022257.

Abstract The shipborne‐passive bistatic inverse synthetic aperture radar system with digital video broadcasting terrestrial (DVB‐T) signals is very important in the fields of radar imaging, but it suffers from the problems of grating lobes caused by the spectral gaps when multiple DVB‐T channels are applied, and the non‐stationary echo signal for the complex motions of the ship. In this paper, a new algorithm based on the Missing Data Iterative Adaptive Approach (MIAA) combined with the Range Instantaneous Doppler (RID) technique is proposed to address these problems. First, the authors establish the imaging geometry and signal model. Based on these models, the range resolution and Doppler frequency are analysed. Then, the bandwidth synthesis in the frequency domain for the DVB‐T signal is derived. Finally, the MIAA method is used to recover the spectral gaps of the range profile for multiple DVB‐T channels, and the azimuth compression is carried out by the RID method after the translational motion compensation. Simulation results show the effectiveness of the algorithm proposed in this paper.

Root-knot nematode (RKN) is a major factor that limits the growth and productivity of important Cucumis crops, such as cucumber and melon, which lack RKN-resistance genes in their genome. Cucumis metuliferus is a wild Cucumis species that displays a high degree of RKN-resistance. WRKY transcription factors were involved in plant response to biotic stresses. However, little is known on the function of WRKY genes in response to RKN infection in Cucumis crops. In this study, Cucumis metuliferus 60 WRKY genes (CmWRKY) were identified in the C. metuliferus genome, and their conserved domains were classified into three main groups based on multiple sequence alignment and phylogenetic analysis. Synteny analysis indicated that the WRKY genes were highly conserved in Cucumis crops. Transcriptome data from of C. metuliferus roots inoculated with RKN revealed that 16 CmWRKY genes showed differential expression, of which 13 genes were upregulated and three genes were downregulated, indicating that these CmWRKY genes are important to C. metuliferus response to RKN infection. Two differentially expression CmWRKY genes (CmWRKY10 and CmWRKY28) were selected for further functional analysis. Both CmWRKY genes were localized in nucleus, indicating they may play roles in transcriptional regulation. This study provides a foundation for further research on the function of CmWRKY genes in RKN stress resistance and elucidation of the regulatory mechanism.

This study examined the relative difficulty of oral speech act production tasks involving eight different types of speech acts for Chinese English as a foreign language (EFL) learners and the effects of three contextual variables, namely, power, social distance, and imposition, on such difficulty. Eight Oral Discourse Completion Task items, each representing a unique combination of the three contextual variables, were designed for each speech act. Eighty Chinese EFL learners responded to these items and their responses were rated for appropriateness by two native-speaking college English instructors. A Many-facet Rasch Measurement analysis suggested that the eight speech acts can be ordered by ascending difficulty as follows: Thank, Request, Suggestion, Disagreement, Invitation, Refusal, Offer, and Apology. Significant effects on performance scores were found for the interaction between each of the three contextual variables and speech act, and the specific effects observed varied by speech act. The implications of our findings for L2 pragmatics testing are discussed.

Abstract Background Peanut is the most essential oil and food crop globally due to its high oil and protein content. Root-knot nematode infects peanut roots, causing poor development and severely limiting peanut yields worldwide. The discovery of peanut genome identified a considerable number of genetic loci controlling the peanut root-knot nematode; however, the molecular mechanism of root-knot nematode remains unknown. Results The heterogeneous response to root-knot nematode stress in peanut roots was identified using whole-transcriptome RNA-seq. A total of 430 mRNAs, 111 miRNAs, 4453 lncRNAs, and 123 circRNAs were found to have differential expression between infected and non-infected peanuts. The expression profiles of the lncRNA/circRNA-miRNA-mRNA network were developed to understand the potential pathways that lead to root-knot nematodes in peanut roots. During root-knot nematodes stress, a total of 10 lncRNAs, 4 circRNAs, 5 miRNAs, and 13 mRNAs can create competing endogenous RNA and participate in the oxidation–reduction process as well as other biological metabolism processes in peanuts. The findings will highlight the role of peanut ceRNAs in response to root-knot nematodes. Conclusion The GO classification and KEGG pathway enrichment study of core regulatory networks revealed that ceRNAs are involved in oxidation–reduction, peroxidase activity, lignin synthesis in the xylem, and flavonoid synthesis. Overall, these findings may help researchers better understand the role of non-coding RNAs in response to root-knot nematodes.

A well-focused and high-resolution inverse synthetic aperture radar (ISAR) image of ship target is appropriate to the target classification and recognition, especially for the ISAR image presenting the ship's top or side view. For this purpose, a novel optimal time window determination (OTWD) approach based on the imaging projection plane (IPP) selection is proposed in this article. First, the proposed OTWD approach determines the view of ship target in the ISAR image via the IPP selection. Then, the Doppler frequency is estimated via the time-frequency distribution (TFD) calculation for the azimuth signal of one scatterer. For the case of one range bin with multiple scatterers, a novel TFD extraction approach based on the clustering analysis is proposed. Afterward, the Doppler frequency is analyzed with sharpness to determine the optimal imaging time window, which can ensure the high image quality and optimal azimuth resolution. The proposed OTWD method is verified as accurate and effective with the experiments on simulated and real measured data.

Abstract To minimise the noise interference in the radar received echoes and optimise the detection issue for a wideband radar system, a novel wideband radar track‐before‐detect detector via Wiener Filter is proposed. The Wiener Filter can effectively remove the noise mixed in the echoes and make the filtered signal consistent with the original signal. After applying maximum likelihood estimation to the echoes, the authors can reconstruct the desired signal required for Wiener filtering by extracting the range information of each scatterer. Then Wiener Filtering is performed on the echo containing noise with the desired signal to complete the denoising. Subsequently, we exploit the correlation between the adjacent echoes for detection. The effectiveness of the detector can be verified by the numerical simulation results of synthetic and real radar data. The proposed detector is superior to the waveform contrast detector, inter‐period correlation processor and modified correlation matrix detector.

Abstract Background Histone deacetylases (HDACs) engage in the regulation of various cellular processes by controlling global gene expression. The dysregulation of HDACs leads to carcinogenesis, making HDACs ideal targets for cancer therapy. However, the use of HDAC inhibitors (HDACi) as single agents has been shown to have limited success in treating solid tumors in clinical studies. This study aimed to identify a novel downstream effector of HDACs to provide a potential target for combination therapy. Methods Transcriptome sequencing and bioinformatics analysis were performed to screen for genes responsive to HDACi in breast cancer cells. The effects of HDACi on cell viability were detected using the MTT assay. The mRNA and protein levels of genes were determined by quantitative reverse transcription‐PCR (qRT‐PCR) and Western blotting. Cell cycle distribution and apoptosis were analyzed by flow cytometry. The binding of CREB1 (cAMP‐response element binding protein 1) to the promoter of the KDELR (The KDEL (Lys‐Asp‐Glu‐Leu) receptor) gene was validated by the ChIP (chromatin immunoprecipitation assay). The association between KDELR2 and protein of centriole 5 (POC5) was detected by immunoprecipitation. A breast cancer‐bearing mouse model was employed to analyze the effect of the HDAC3‐KDELR2 axis on tumor growth. Results KDELR2 was identified as a novel target of HDAC3, and its aberrant expression indicated the poor prognosis of breast cancer patients. We found a strong correlation between the protein expression patterns of HADC3 and KDELR2 in tumor tissues from breast cancer patients. The results of the ChIP assay and qRT‐PCR analysis validated that HDAC3 transactivated KDELR2 via CREB1. The HDAC3‐KDELR2 axis accelerated the cell cycle progression of cancer cells by protecting the centrosomal protein POC5 from proteasomal degradation. Moreover, the HDAC3‐KDELR2 axis promoted breast cancer cell proliferation and tumorigenesis in vitro and in vivo. Conclusion Our results uncovered a previously unappreciated function of KDELR2 in tumorigenesis, linking a critical Golgi‐the endoplasmic reticulum traffic transport protein to HDAC‐controlled cell cycle progression on the path of cancer development and thus revealing a potential therapeutical target for breast cancer.

This study examined the relationship of linguistic complexity, captured using a set of lexical richness, syntactic complexity, and discoursal complexity indices, to second language (L2) learners' perception of text difficulty, captured using L2 raters' comparative judgment on text comprehensibility and reading speed. Testing materials were 180 texts abridged from college English coursebooks, and raters were 90 advanced Chinese learners of L2 English. Forty-five raters read paired texts and determined which text was harder to understand in each pair, and another 45 raters read paired texts and determined which text they read faster in each pair. Two stepwise linear regression models containing lexical, syntactic, and discoursal features explained 48.1% and 54.6% of the variance in L2 learners' estimates of text comprehensibility and reading speed, respectively, outperforming four commonly used language readability models. These findings contribute useful insights into the relationship between linguistic complexity and L2 learners' perception of text difficulty.

The airborne synthetic aperture radar (SAR) image of ship target will be blurred for the complex motion of the target, which will influence the performance of feature extraction and target classification. In this article, a refocusing method of ship target in airborne SAR image though the inverse synthetic aperture radar (ISAR) technique is presented. The novel contributions of this article can be summarized as follows: 1) the residual phase of processed signal is analyzed in detail to illustrate the necessity of adopting ISAR technique; 2) a valid, labor-saving, and automatic image segmentation approach via clustering algorithm is put forward for automatic data extraction and inverse mapping. The clustering algorithm we choose is the agglomerative hierarchical cluster algorithm, which does not require the number of categories in advance; 3) the refocused individual ISAR image of individual ship target is yielded though the range-instantaneous Doppler algorithm. Finally, the simulated and real measured data are processed, and imaging results verify the effectiveness of the novel algorithm presented in this article.

In this work, multicolor fluorescent carbon dots with red (R-CDs), yellow (Y-CDs), and blue (B-CDs) emissions were prepared by choosing proper aromatic precursors with different amounts of benzene rings through a simple solvothermal method. The characterization showed that the prepared carbon dots were spherical with a size under 10 nm, rich surface functional groups, and good stability. The emission wavelengths were located at 440, 530, and 580 nm under the excitation of 370 nm. The relative fluorescence quantum yield (QY) of R-CDs, Y-CDs, and B-CDs was 11%, 59%, and 33%, respectively. The related characterization demonstrated that the redshift in the photoluminescence was caused by the synergistic effect of the increasing graphitic nitrogen content, quantum size effect and surface oxidation state. By mixing the three prepared CDs into a PVA matrix, the transparent and flexible films produced relucent blue, yellow, and red emissions under 365 nm UV light, and solid-state quenching was effectively avoided. LEDs were fabricated by using B-CDs, Y-CDs, and R-CDs/PVA with a semiconductor chip. These CDs-based LEDs produced bright blue, yellow, and red light with CIE color coordinates of (0.16, 0.02), (0.38, 0.58), and (0.50, 0.49) were successfully manufactured utilizing the prepared blue, yellow and red multicolor carbon dots as the solid luminescent materials. The results showed that the synthesized CDs can be potentially applied in multi-color monitors as a promising candidate for light-emitting diodes (LEDs). This work blazes a novel trail for the controllable preparation of multicolor fluorescent carbon dots.

Decarbonization has become an urgent affair to restrain global warming. CO2 hydrogenation coupled with H2 derived from water electrolysis is considered a promising route to mitigate the negative impact of carbon emission and also promote the application of hydrogen. It is of great significance to develop catalysts with excellent performance and large-scale implementation. In the past decades, metal–organic frameworks (MOFs) have been widely involved in the rational design of catalysts for CO2 hydrogenation due to their high surface areas, tunable porosities, well-ordered pore structures, and diversities in metals and functional groups. Confinement effects in MOFs or MOF-derived materials have been reported to promote the stability of CO2 hydrogenation catalysts, such as molecular complexes of immobilization effect, active sites in size effect, stabilization in the encapsulation effect, and electron transfer and interfacial catalysis in the synergistic effect. This review attempts to summarize the progress of MOF-based CO2 hydrogenation catalysts up to now, and demonstrate the synthetic strategies, unique features, and enhancement mechanisms compared with traditionally supported catalysts. Great emphasis will be placed on various confinement effects in CO2 hydrogenation. The challenges and opportunities in precise design, synthesis, and applications of MOF-confined catalysis for CO2 hydrogenation are also summarized.

Climate exerts both short-term and long-term impacts on the ecosystem carbon assimilation. However, the main climatic drivers for the variability of gross primary productivity (GPP) remain unclear across various timescales and vegetation types. Here, we combine the state-of-the-art machine learning algorithms with a well-established explanatory method to explore the impacts of climatic factors on long-term GPP variability at global FLUXNET sites across four timescales and six plant functional types. Results show that diffuse shortwave radiation (SWdif) dominates GPP variability at the sub-daily (half-hourly to three hourly) timescales especially for the tree species, and acts as the secondary contributor after air temperature at the daily or longer timescales. Attribution analyses further showed that the main effects of SWdif are much higher than their interactive effects with other climatic factors in regulating the GPP variability. By identifying the main climatic drivers, this study improves the understanding of the climate-driven GPP variability and provides important implications for the future projection of ecosystem carbon assimilation under global climate change.

Fusarium oxysporum f. sp. phaseoli, the causal agent of cowpea fusarium wilt, is a serious threat to cowpea production in China. In this study, a sample of cowpea fusarium wilt was identified as Fusarium oxysporum f. sp. phaseoli using the methods of morphological characters and molecular detection. We further reported the first genome assembly for Fusarium oxysporum f. sp. phaseoli, with 53.7 Mb genome sequence comprising 14,694 genes. Comparative genomic analysis among five Fusarium oxysporum genomes showed that four accessory chromosomes in the five Fusarium oxysporum display similar characteristics, with low sequence similarity (55.35%, vs. overall average of 81.76%), low gene density (2.18 genes/10 kb vs. 3.02 genes/Mb) and highly transposable element density (TEs) (15.01/100 kb vs. 4.89/100 kb), indicating that variable accessory chromosomes are the main source of Fusarium oxysporum evolution. We identified a total of 100 Fusarium oxysporum f. sp. phaseoli-specific effectors in the genome and found 13 specific effector genes located in large insertion or deletion regions, suggesting that insertion or deletion events can cause the emergence of species-specific effectors in Fusarium oxysporum. Our genome assembly of Fusarium oxysporum f. sp. phaseoli provides a valuable resource for the study of cowpea fusarium wilt, and the comparative genomic study of Fusarium oxysporum could contribute to the knowledge of genome and effector-associated pathogenicity evolution in Fusarium oxysporum study.

Fusarium oxysporum f. sp. conglutinans (FOC), the causal agent of cabbage fusarium wilt, is a serious threat to cabbage production in northern China, and most Chinese FOC isolates were identified as FOC race 1 (FOC1). To better understand the genetic diversity of FOC1 in northern China, we collected FOC isolates from five provinces in northern China and identified them as FOC1 through pathogenicity and race test. To evaluate the genome-level diversity of FOC1, we performed a genome assembly for a FOC1 isolate (FoYQ-1) collected from Yanqing, Beijing, where cabbage fusarium wilt was first reported in China. Using resequencing data of FOC1 isolates, we conducted a genome-wide SNP (single nucleotide polymorphism) analysis to investigate the genetic diversity and population structure of FOC1 isolates in northern China. Our study indicated that Chinese FOC1 can be grouped into four populations and revealed that the genetic diversity of FOC1 were closely associated with geographical locations. Our study further suggests that genetic differentiation occurred when FOC1 spread to the northwest provinces from Beijing Province in China. The FOC1 genetic diversity based on whole-genome SNPs could deepen our understanding of FOC1 variation and provide clues for the control of cabbage fusarium wilt in China.

BackgroundMismatch repair proficient colorectal cancer (pMMR CRC) lacks effective treatments and has a poor prognosis, which can be attributed to the complexity of tumor microenvironment. The coordinated function of immune cells is vital to anti-tumor immunity. However, the spatial characteristics of immune cells in the pMMR CRC immune microenvironment and their relationship with clinical prognosis are not fully understood. Meanwhile, the immune modulatory effect of neoadjuvant chemotherapy (NCT), which is the first-line treatment of pMMR CRC, needs further investigation. Therefore, this study aims to explore the spatial dynamics of immune cells and its prognostic value in pMMR CRC.MethodsWe analyzed the various immune cells in formalin-fixed, paraffin-embedded tumor tissues which were collected from 77 patients with stage II/III of pMMR CRC, including 39 non-NCT treated and 38 NCT treated patients. We used the optimized multiplex immunohistochemistry (mIHC) to identify and quantify the density, type and location of immune cells in pMMR CRC. Multivariate survival analysis was performed to assess the relationship of immune profiles and clinical prognosis of pMMR CRC patients.ResultsThe densities of most T cell subsets, B cells and macrophages were higher in the central region of the pMMR CRC than in the invasion margin. Tumor infiltrating lymphocytes (TILs), especially the infiltration of CD4+ GzmB+ T cells in the central region of the tumor was identified to be positively correlated with the prognosis of the patients. Multivariate analysis confirmed that CD4+ GzmB+ T cells population was an independent predictor of disease-free survival (DFS) in non-NCT group. Meanwhile, NCT enhanced the infiltration of CD4+ GzmB+ T cells in the central region of the pMMR CRC, which was also identified as an independent protective factor of overall survival (OS) and DFS in NCT group.ConclusionWe demonstrated that the level of CD4+ GzmB+ T cells located in the center of tumor could provide great prognostic value for pMMR CRC patients. And the application of neoadjuvant chemotherapy further improves the infiltration of CD4+ GzmB+ T cells in the central compartment. Further studies into the application of CD4+ GzmB+ T cells in tumor immunotherapy are needed.

Previous studies of the lexical psycholinguistic properties (LPPs) in second language (L2) production have assessed the degree of an LPP dimension of an L2 corpus by computing the mean ratings of unique content words in the corpus for that dimension, without considering the possibility that learners at different proficiency levels may perceive the degree of that dimension of the same words differently. This study extended a dynamic semantic similarity algorithm to estimate the degree of five different LPP dimensions of several sub-corpora of the Education First-Cambridge Open Language Database representing L2 English learners at different proficiency levels. Our findings provide initial evidence for the validity of the algorithm for assessing the LPPs in L2 production and contribute useful insights into between-proficiency relationships and cross-proficiency differences in the LPPs in L2 production as well as the relationships among different LPP dimensions.

Ground moving targets (GMT), due to the existence of velocity in range and azimuth direction, will lead to the deviation from their true position and defocus in the azimuth direction during the synthetic aperture radar (SAR) imaging process. To address this problem and compress the amount of echo data, a sparse SAR imaging method for ground moving targets is proposed. Specifically, we first constructed a two-dimensional sparse observation model of the GMT based on matched filter operators. Then, the observation model was solved by a deep network, GMT sparse imaging network (GMTSI-Net), which was mainly obtained by unfolding an iterative soft threshold algorithm (ISTA)-based iterative solution. Furthermore, we designed an adaptive unfolding module in the imaging network to improve the adaptability of the network to the input of echo data with different sampling ratios. The proposed imaging network can achieve faster and more accurate SAR images of ground moving targets under a low sampling ratio and signal-to-noise ratio (SNR). Simulated and measured data experiments were conducted to demonstrate the performance of imaging quality of the proposed method.

Abstract Interferometric synthetic aperture radar and teleseismic P‐wave data were combined to investigate the source rupture characteristics of the 2020 Mw 6.3 Yutian, China, earthquake. We first utilized the near‐field displacements together with 29 broadband teleseismic P waveforms to investigate the uniform slip model by using a Bayesian bootstrap optimization nonlinear inversion method to resolve the nucleation point location, origin time and fault geometrical parameters. Based on these results, the kinematic rupture process of the earthquake was inverted. We conclude that the 2020 Yutian earthquake occurred on a west‐dipping blind normal fault with a dip of ∼60° at the junction of Bayan Har block (BHB) and western Kunlun block (WKB). The rupture nucleation point was located at longitude = 82.435°E, latitude = 35.619°N, and a depth of 6.377 km, making it shallower than estimated from other point source inversions. The earthquake started at 21:05:20 UTC on June 25, 2020 and was delayed by ∼2.07 s compared with GeoForschungsZentrum. The rupture lasted for ∼12 s, with a total seismic moment of ∼3.28 × 1018 Nm, corresponding to a moment magnitude of 6.3. The slip was mainly confined between ∼3.0 and 9.0 km in depth and the peak slip was ∼1.40 m, which occurred at a depth of ∼6.377 km. The slip was predominantly normal slip with slight right‐lateral strike‐slip components, which agrees with the southeastward movement of the BHB relative to the WKB.

Deep learning has been used in inverse synthetic aperture radar (ISAR) imaging to improve resolution performance, but there still exist some problems: the loss of weak scattering points, over-smoothed imaging results, and the universality and generalization. To address these problems, an ISAR resolution enhancement method of exploiting a generative adversarial network (GAN) is proposed in this paper. We adopt a relativistic average discriminator (RaD) to enhance the ability of the network to describe target details. The proposed loss function is composed of feature loss, adversarial loss, and absolute loss. The feature loss is used to get the main characteristics of the target. The adversarial loss ensures that the proposed GAN recovers more target details. The absolute loss is adopted to make the imaging results not over-smoothed. Experiments based on simulated and measured data under different conditions demonstrate that the proposed method has good imaging performance. In addition, the universality and generalization of the proposed GAN are also well verified.

Large Unmanned Aerial Vehicle (UAV) clusters, containing hundreds of UAVs, have widely been used in the modern world. Therein, mission planning is the core of large UAV cluster collaborative systems. In this paper, we propose a mission planning method by introducing the Simple Attention Model (SAM) into Dynamic Information Reinforcement Learning (DIRL), named DIRL-SAM. To reduce the computational complexity of the original attention model, we derive the SAM with a lightweight interactive model to rapidly extract high-dimensional features of the cluster information. In DIRL, dynamic training conditions are considered to simulate different mission environments. Meanwhile, the data expansion in DIRL guarantees the convergence of the model in these dynamic environments, which improves the robustness of the algorithm. Finally, the simulation experiment results show that the proposed method can adaptively provide feasible mission planning schemes with second-level solution speed and that it exhibits excellent generalization performance in large-scale cluster planning problems.

Most patients with primary central system lymphoma (PCNSL) have immune dysfunction. PCNSL without immune dysfunction is rare and extremely challenging to diagnose. Here, we report the case of a 52-year-old woman without immune dysfunction who presented with PCNSL. The patient died a few months after diagnosis and during treatment. A review of this PCNSL patient’s case highlighted that poor interpretation of imaging features and the poor correlation of laboratory test results with clinical findings led to a difficulty in making a diagnosis and administering the best treatment. For an accurate diagnosis of early stage PCNSL, positron-emission tomography computed tomography and corticosteroids should be used cautiously before stereotactic biopsy.

The effects of learner- and task-related variables on second language (L2) writing syntactic complexity (SC) have been extensively investigated. However, previous research has rarely assessed the reliability of computational tools for analyzing the SC of L2 spoken production, and we know less about the effects of such variables on L2 speaking SC. Using data from the International Corpus Network of Asian Learners of English, this study explores data preprocessing issues for preparing L2 English speech samples for automated SC analysis, evaluates the reliability of L2 Syntactic Complexity Analyzer on preprocessed L2 English speech samples, and examines the effects of proficiency, first language (L1) background, and topic on L2 speaking SC. Our manual analysis of 30 random speech samples identified several issues that can be addressed through preprocessing to improve the accuracy of automated SC analysis. Results from multiple linear mixed-effects models revealed significant effects of proficiency, L1 background, and topic on the mean length of clause, the number of complex AS-units per AS-unit, and the number of dependent clauses and complex nominals per clause in L2 learners' spoken production. Our findings have useful implications for L2 speaking pedagogy and assessment as well as future L2 speaking SC research.

The seasonal differences of soil organic carbon (SOC) responding to N deposition have rarely been considered. In this study, two levels of canopy addition of N (25 and 50 kg N ha−1 yr−1; i.e., CAN25 and CAN50, respectively) and one control (CK) were designed in a subtropical forest to investigate the seasonal effects on the content of SOC and its fractions. The results showed that soil pH, the content of SOC and N were not significantly altered after 3 years of canopy N addition. However, in 0–5 cm soils, significant variations were observed in the proportion of the micro-aggregates (53–250 μm) and the clay microstructures (250 μm), microbial biomass C, readily oxidized C, and recalcitrant organic C in the wet season. The findings implied that atmospheric N deposition may have negative and no effects on SOC in subtropical evergreen forest in the wet and the dry season, respectively. Although the effects were primarily detected in the uppermost soils, the different responses of SOC to atmospheric N deposition between the dry and the wet seasons should be considered in the future modeling research. Keywords: Atmospheric N deposition, Canopy N addition, Seasonal effect, Soil organic carbon, Subtropical forest

A novel methylcyclohexane (MCH) dehydrogenation system driven by solar energy with a hydrogen permeation membrane (HPM) reactor is proposed in this study. It is a promising method, via this novel system, to generate pure hydrogen and store intermittent solar energy. In this research, the thermodynamic analysis of MCH dehydrogenation via the HPM reactor was conducted based on numerical simulation. The conversion rates and thermodynamic efficiencies under different temperatures (150–350 °C), permeate pressures from 0.001 to 0.5 bar, and solar irradiation in the four seasons were studied and analyzed. Under a hydrogen partial pressure difference, HPM can separate hydrogen and shift the reaction equilibrium forward for a higher conversion rate of MCH, which can reach nearly 99.7% in this system. The first-law of thermodynamic efficiency, the solar-to-fuel efficiency, and the exergy efficiency are up to 95.58%, 38.65%, and 94.22%, respectively. This study exhibits the feasibility and potential of MCH dehydrogenation via the HPM reactor driven by solar energy and provides a novel approach for solar energy storage.

The instantaneous frequency (IF) is a vital parameter for the analysis of non-stationary multicomponent signals, and plays an important role in space cone-shaped target recognition. For a cone-shaped target, IF estimation is not a trivial issue due to the proximity of the energy of the IF components, the intersections among different IF components, and the existence of noise. Compared with the general parameterized time-frequency (GPTF), the traditional Kalman filter can perform better when the energy of different signal components is close. Nevertheless, the traditional Kalman filter usually makes association mistakes at the intersections of IF components and is sensitive to the noise. In this paper, a novel IF estimation method based on modified Kalman filter (MKF) is proposed, in which the MKF is used to associate the intersecting IF trajectories obtained by the synchroextracting transform (SET). The core of MKF is the introduction of trajectory correction strategy in which a trajectory survival rate is defined to judge the occurrence of association mistakes. When the trajectory survival rate is below the predetermined threshold, it means that an association mistakes occurs, and then the new trajectories generated by the random sample consensus algorithm are used to correct the wrong associations timely. The trajectory correction strategy can effectively obviate the association mistakes caused by the intersections of IF components and the noise. The windowing technique is also used in the trajectory correction strategy to improve computational speed. The experimental results based on the electromagnetic computation data show that the proposed method is more robust and precise than the traditional Kalman filter. Moreover, the proposed method has great performance advantages compared with other methods (i.e., the multiridge detection, the ant colony optimization, and the GPTF methods) especially in the case of low signal noise ratio (SNR).

Life-threatening diseases (e.g., cancer) affect people’s future time perspective (FTP) and affect their mental health. When one’s lifetime is perceived as running out, the individual possesses a future limitation perspective (FLP), which is one of factors in FTP. In this study, we explored the structural relationship between FLP, fear of cancer recurrence (FCR), mental health status (MHS), and brain activity in patients with cancer. Cancer patients were divided into two groups using the FTP scale and Feelings About Life Scale: a strong FLP group (S-FLP) and a weak FLP group (W-FLP). For these groups, we measured cancer patients’ MHS using the Symptom Checklist (SCL-90) and FCR using the Cancer Acceptance Scale; brain activity was measured using resting-state functional magnetic resonance imaging (rs-fMRI). Behavioral results showed that the S-FLP group had higher mental symptoms and FCR scores than did the W-FLP group. Neuroimaging results revealed that spontaneous brain activity in the ventromedial prefrontal cortex (vmPFC) was stronger in the W-FLP group than in the S-FLP group. Moreover, brain activity in the vmPFC negatively correlated with FLP, FCR, and SCL-90 scores only in the S-FLP group, and the model constructed further indicated that FCR and SCL-90 scores fully mediated the relationship between FLP and vmPFC activities. These findings suggested that a strong FLP might lead to mental disorders and greater FCR, which might change the spontaneous activity of the vmPFC in cancer patients.

In this study, the influence of temperature on biogas production efficiency and the microbial community structure was investigated in a two-phase anaerobic digestion reactor for co-digestion of cow manure and corn straw. The results illustrated that the contents of solluted chemical oxygen demand (SCOD) and volatile fatty acid (VFA) in the acidogenic phase and biogas production in the methanogenic phase maintained relatively higher levels at temperatures ranging from 35–25 °C. The methane content of biogas production could be maintained higher than 50% at temperatures above 25 °C. The microbial community structure analysis indicated that the dominant functional bacteria were Acinetobacter, Acetitomaculum, and Bacillus in the acidogenic phase and Cenarchaeum in the methanogenic phase at 35–25 °C. However, the performances of the acidogenic phase and the methanogenic phase could be significantly decreased at a lower temperature of 20 °C, and microbial activity was inhibited obviously. Accordingly, a low temperature was adverse for the performance of the acidogenic and methanogenic phases, while moderate temperatures above 25 °C were more conducive to high biogas production efficiency.

PURPOSE:Elevated plasma fibrinogen levels are associated with tumor progression and poor outcomes in different cancer patients. The objective of this study was to investigate the clinical and prognostic value of preoperative plasma fibrinogen levels in patients with operable breast cancer. METHODS:Two hundred and twenty-three patients diagnosed with breast cancer were retrospectively evaluated in this study. Plasma fibrinogen levels were examined before treatment and analyzed along with patient clinicopathological parameters, disease-free survival (DFS) and overall survival (OS). Both univariate and multivariate analyses were performed to identify the clinicopathological parameters associated with DFS and OS. RESULTS:Elevated preoperative plasma fibrinogen levels were directly associated with age of diagnose (≤47 vs. >47, p