Search

Abstract Background To assess the capability of multimodal apparent diffusion (MAD) weighted magnetic resonance imaging (MRI) to distinguish between malignant and benign breast lesions, and to predict Ki-67 expression level in breast cancer. Methods This retrospective study was conducted with 93 patients who had postoperative pathology-confirmed breast cancer or benign breast lesions. MAD images were acquired using a 3.0 T MRI scanner with 16 b values. The MAD parameters, as flow (fF, DF), unimpeded (fluid) (fUI), hindered (fH, DH, and αH), and restricted (fR, DR), were calculated. The differences of the parameters were compared by Mann–Whitney U test between the benign/malignant lesions and high/low Ki-67 expression level. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC). Results The fR in the malignant lesions was significantly higher than in the benign lesions (P = 0.001), whereas the fUI and DH were found to be significantly lower (P = 0.007 and P

To adress the problems of insufficient consideration of charging pile resource limitations, discrete-time scheduling methods that do not meet the actual demand and insufficient descriptions of peak-shaving response capability in current electric vehicle (EV) optimization scheduling, edge intelligence-oriented electric vehicle optimization scheduling and charging station peak-shaving response capability assessment methods are proposed on the basis of the consideration of electric vehicle and charging pile matching. First, an edge-intelligence-oriented electric vehicle regulation frame for charging stations is proposed. Second, continuous time variables are used to represent the available charging periods, establish the charging station controllable EV load model and the future available charging pile mathematical model, and establish the EV and charging pile matching matrix and constraints. Then, with the goal of maximizing the user charging demand and reducing the charging cost, the charging station EV optimal scheduling model is established, and the EV peak response capacity assessment model is further established by considering the EV load shifting constraints under different peak response capacities. Finally, a typical scenario of a real charging station is taken as an example for the analysis of optimal EV scheduling and peak shaving response capacity, and the proposed method is compared with the traditional method to verify the effectiveness and practicality of the proposed method.

Abstract Thyroid cancer is the most frequently observed endocrine-related malignancy among which anaplastic thyroid cancer (ATC) is the most fatal subtype. The synthesis of protein is active to satisfy the rapid growth of ATC tumor, but the mechanisms regulating protein synthesis are still unknown. Our research revealed that kinetochore protein NUF2 played an essential role in protein synthesis and drove the progression of ATC. The prognosis of patients with thyroid carcinoma was positively correlated with high NUF2 expression. Depletion of NUF2 in ATC cells notably inhibited the proliferation and induced apoptosis, while overexpression of NUF2 facilitated ATC cell viability and colony formation. Deletion of NUF2 significantly suppressed the growth and metastasis of ATC in vivo. Notably, knockdown of NUF2 epigenetically inhibited the expression of magnesium transporters through reducing the abundance of H3K4me3 at promoters, thereby reduced intracellular Mg2+ concentration. Furthermore, we found the deletion of NUF2 or magnesium transporters significantly inhibited the protein synthesis mediated by the PI3K/Akt/mTOR pathway. In conclusion, NUF2 functions as an emerging regulator for protein synthesis by maintaining the homeostasis of intracellular Mg2+, which finally drives ATC progression.

Abstract Background Glioblastoma (GBM) is an immunosuppressive, universally lethal cancer driven by glioblastoma stem cells (GSCs). The interplay between GSCs and immunosuppressive microglia plays crucial roles in promoting the malignant growth of GBM; however, the molecular mechanisms underlying this crosstalk are unclear. This study aimed to investigate the role of POSTN in maintaining GSCs and the immunosuppressive phenotype of microglia. Methods The expression of POSTN in GBM was identified via immunohistochemistry, quantitative real-time PCR, and immunoblotting. Tumorsphere formation assay, Cell Counting Kit-8 assay and immunofluorescence were used to determine the key role of POSTN in GSC maintenance. ChIP-seq and ChIP-PCR were conducted to confirm the binding sequences of β-catenin in the promoter region of FOSL1. Transwell migration assays, developmental and functional analyses of CD4+ T cells, CFSE staining and analysis, enzyme-linked immunosorbent assays and apoptosis detection tests were used to determine the key role of POSTN in maintaining the immunosuppressive phenotype of microglia and thereby promoting the immunosuppressive tumor microenvironment. Furthermore, the effects of POSTN on GSC maintenance and the immunosuppressive phenotype of microglia were investigated in a patient-derived xenograft model and orthotopic glioma mouse model, respectively. Results Our findings revealed that POSTN secreted from GSCs promotes GSC self-renewal and tumor growth via activation of the αVβ3/PI3K/AKT/β-catenin/FOSL1 pathway. In addition to its intrinsic effects on GSCs, POSTN can recruit microglia and upregulate CD70 expression in microglia through the αVβ3/PI3K/AKT/NFκB pathway, which in turn promotes Treg development and functionality and supports the formation of an immunosuppressive tumor microenvironment. In both in vitro models and orthotopic mouse models of GBM, POSTN depletion disrupted GSC maintenance, decreased the recruitment of immunosuppressive microglia and suppressed GBM growth. Conclusion Our findings reveal that POSTN plays critical roles in maintaining GSCs and the immunosuppressive phenotype of microglia and provide a new therapeutic target for treating GBM.

The lithium niobate on insulator devices confine the light field to submicron size in monocrystalline lithium niobate, to achieve ultra-strong electro-optical interaction and nonlinear optical interaction, and thus extend the frontiers of the photonic research in the past decade. Such devices are manufactured using nano-fabrication technology over the thin-film lithium niobate wafer, which usually stands on a silica insulator layer above the substrate material, including low-loss waveguides, electro-optical modulators, domain engineered structures, high-Q microring resonators and electrical filters etc., and lead to breakthroughs in optical communication, microwave photonics and quantum integration.

Abstract Background Acute myocardial infarction (AMI) is characterized by inflammation, oxidative stress, and atherosclerosis, contributing to increased mortality risk. High-density lipoprotein (HDL) takes a crucial part in mitigating atherosclerosis and inflammation through its diverse functionalities. Conversely, fibrinogen is implicated in the development of atherosclerotic plaques. However, the mortality risk predictive capacity of fibrinogen to HDL-cholesterol ratio (FHR) in AMI patients remains unexplored. This research aimed to evaluate the effectiveness of FHR for mortality risk prediction in relation to AMI. Methods A retrospective study involving 13,221 AMI patients from the Cardiorenal ImprovemeNt II cohort (NCT05050877) was conducted. Baseline FHR levels were used to categorize patients into quartiles. The assessment of survival disparities among various groups was conducted by employing Kaplan‒Meier diagram. Cox regression was performed for investigating the correlation between FHR and adverse clinical outcomes, while the Fine-Gray model was applied to evaluate the subdistribution hazard ratios for cardiovascular death. Results Over a median follow-up of 4.66 years, 2309 patients experienced all-cause death, with 1007 deaths attributed to cardiovascular disease (CVD). The hazard ratio (HR) and its 95% confidence interval (CI) for cardiac and all-cause death among individuals in the top quartile of FHR were 2.70 (1.99–3.65) and 1.48 (1.26–1.75), respectively, in comparison to ones in the first quartile, after covariate adjustment. Restricted cubic spline analysis revealed that FHR was linearly correlated with all-cause mortality, irrespective of whether models were adjusted or unadjusted (all P for nonlinearity > 0.05). Conclusion AMI patients with increased baseline FHR values had higher all-cause and cardiovascular mortality, regardless of established CVD risk factors. FHR holds promise as a valuable tool for evaluating mortality risk in AMI patients. Trial registration The Cardiorenal ImprovemeNt II registry NCT05050877.

BackgroundDistinguishing between prostatic cancer (PCa) and chronic prostatitis (CP) is sometimes challenging, and Gleason grading is strongly associated with prognosis in PCa. The continuous-time random-walk diffusion (CTRW) model has shown potential in distinguishing between PCa and CP as well as predicting Gleason grading.PurposeThis study aimed to quantify the CTRW parameters (α, β & Dm) and apparent diffusion coefficient (ADC) of PCa and CP tissues; and then assess the diagnostic value of CTRW and ADC parameters in differentiating CP from PCa and low-grade PCa from high-grade PCa lesions.Study typeRetrospective (retrospective analysis using prospective designed data).PopulationThirty-one PCa patients undergoing prostatectomy (mean age 74 years, range 64–91 years), and thirty CP patients undergoing prostate needle biopsies (mean age 68 years, range 46–79 years).Field strength/SequenceMRI scans on a 3.0T scanner (uMR790, United Imaging Healthcare, Shanghai, China). DWI were acquired with 12 b-values (0, 50, 100, 150, 200, 500, 800, 1200, 1500, 2000, 2500, 3000 s/mm2).AssessmentCTRW parameters and ADC were quantified in PCa and CP lesions.Statistical testsThe Mann-Whitney U test was used to evaluate the differences in CTRW parameters and ADC between PCa and CP, high-grade PCa, and low-grade PCa. Spearman’s correlation of the pathologic grading group (GG) with CTRW parameters and ADC was evaluated. The usefulness of CTRW parameters, ADC, and their combinations (Dm, α and β; Dm, α, β, and ADC) to differentiate PCa from CP and high-grade PCa from low-grade PCa was determined by logistic regression and receiver operating characteristic curve (ROC) analysis. Delong test was used to compare the differences among AUCs.ResultsSignificant differences were found for the CTRW parameters (α, Dm) between CP and PCa (all P

IntroductionRemimazolam (RMZ) is a novel intravenous sedative drug of ultra-short benzodiazepine. The optimal dose of RMZ plus butorphanol for sedation during first trimester artificial abortion is unknown. Therefore, the present study aimed to evaluate the median effective dose (ED50) of RMZ combined with different doses of butorphanol on the sedative effect for first-trimester artificial abortion.MethodsSixty-one female patients were randomly assigned to Group B10 (31 patients) and Group B15 (30 patients). RMZ was administered 5 min after IV butorphanol at doses of 10 μg/kg (Group B10) and 15 μg/kg (Group B15). Cervical dilatation at the time of using a cervical dilating rod, if the patient has body movement and affects the gynecologist’s operation, we define it as “Ineffective.” Therefore, the dose of RMZ was increased in the next patient. Otherwise, it was defined as “Effective,” and the dose of RMZ was reduced in the next patient. According to the pre-experiment, the first dose of RMZ in the first patient was 0.35 mg/kg, and the adjacent geometric dose ratio was 0.9. The centered isotonic regression was performed to determine the ED50 of RMZ. The total RMZ dose administered, recovery time, and anesthesia-related adverse events were all recorded.ResultsThe ED50 (90% CI) of RMZ was 0.263 (0.215–0.310) mg/kg in Group B10, and 0.224 (0.191–0.261) mg/kg in Group B15, respectively. The recovery time in Group B10 was significantly shorter than in Group B15 (9.8 ± 2.3 vs. 12.5 ± 3.6 min, p ≤ 0.001). There was no significant difference in the incidence rate of all anesthesia-related adverse events between the two groups (p > 0.05).ConclusionThe ED50 of RMZ combined with a 10 μg/kg or 15 μg/kg dose of butorphanol was 0.263 and 0.224 mg/kg during painless first trimester artificial abortion. However, RMZ combined with a 10 μg/kg dose of butorphanol seems to have a shorter recovery time.Clinical trial registrationhttps://www.chictr.org.cn/bin/project/edit?pid=166623.

Abstract Background Sterile-fertile heteroblasty is a common phenomenon observed in ferns, where the leaf shape of a fern sporophyll, responsible for sporangium production, differs from that of a regular trophophyll. However, due to the large size and complexity of most fern genomes, the molecular mechanisms that regulate the formation of these functionally different heteroblasty have remained elusive. To shed light on these mechanisms, we generated a full-length transcriptome of Ceratopteris chingii with PacBio Iso-Seq from five tissue samples. By integrating Illumina-based sequencing short reads, we identified the genes exhibiting the most significant differential expression between sporophylls and trophophylls. Results The long reads were assembled, resulting in a total of 24,024 gene models. The differential expressed genes between heteroblasty primarily involved reproduction and cell wall composition, with a particular focus on expansin genes. Reconstructing the phylogeny of expansin genes across 19 plant species, ranging from green algae to seed plants, we identified four ortholog groups for expansins. The observed high expression of expansin genes in the young sporophylls of C. chingii emphasizes their role in the development of heteroblastic leaves. Through gene coexpression analysis, we identified highly divergent expressions of expansin genes both within and between species. Conclusions The specific regulatory interactions and accompanying expression patterns of expansin genes are associated with variations in leaf shapes between sporophylls and trophophylls.

In this paper, multifunctional, multilevel phase plates of quartz substrate were efficiently prepared by using a newly developed polygon scanner-based femtosecond laser photolithography system combined with inductively coupled discharge plasma reactive-ion etching (ICP-RIE) technology. The femtosecond laser photolithography system can achieve a scanning speed of 5 m/s and a preparation efficiency of 15 cm2/h while ensuring an overlay alignment accuracy of less than 100 nm and a writing resolution of 500 nm. The ICP-RIE technology can control the etching depth error within ±5 nm and the mask-to-mask edge error is less than 1 μm. An 8-level Fresnel lens phase plate with a focal length of 20 mm and an 8-level Fresnel axicon phase plate with a cone angle of 5° were demonstrated. The diffraction efficiency was greater than 93%, and their performance was tested for focusing and glass cutting, respectively. Combined with the high-speed femtosecond laser photolithography system’s infinite field-of-view (IFOV) processing capability, the one-time direct writing preparation of phase plate masks of different sizes was realized on a 6-inch wafer. This is expected to reduce the production cost of quartz substrate diffractive optical elements and promote their customized mass production.

Soil erodibility (K) refers to the inherent ability of soil to withstand erosion. Accurate estimation and spatial prediction of K values are vital for assessing soil erosion and managing land resources. However, as most K-value estimation models are empirical, they suffer from significant extrapolation uncertainty, and traditional studies on spatial prediction focusing on individual empirical K values have neglected to explore the spatial pattern differences between various empirical models. This work proposed a universal framework for selecting an optimal soil-erodibility map using empirical models enhanced by machine learning. Specifically, three empirical models, namely, the erosion-productivity impact calculator model (K_EPIC), the Shirazi model (K_Shirazi), and the Torri model (K_Torri) were used to estimate K values. Random Forest (RF) and Gradient-Boosting Decision Tree (GBDT) algorithms were employed to develop prediction models, which led to the creation of three K-value maps. The spatial distribution of K values and associated environmental covariates were also investigated across varying empirical models. Results showed that RF achieved the highest accuracy, with R2 of K_EPIC, K_Shirazi, and K_Torri increasing by 46%, 34%, and 22%, respectively, compared to GBDT. And distinctions among environmental variables that shape the spatial patterns of empirical models have been identified. The K_EPIC and K_Shirazi are influenced by soil porosity and soil moisture. The K_Torri is more sensitive to soil moisture conditions and terrain location. More importantly, our study has highlighted disparities in the spatial patterns across the three K-value maps. Considering the data distribution, spatial distribution, and measured K values, the K_Torri model outperformed others in estimating soil erodibility in the plateau lake watershed. This study proposed a framework that aimed to create optimal soil-erodibility maps and offered a scientific and accurate K-value estimation method for the assessment of soil erosion.

This study investigates waterlogging disasters in winter wheat using the Agricultural Production Systems Simulator (APSIM) model. This research explores the effects of soil hypoxia on wheat root systems and the tolerance of wheat at different growth stages to waterlogging, proposing a model to quantify the degree of waterlogging in wheat. Remote sensing data on soil moisture and wheat distribution are utilized to establish a monitoring system for waterlogging disasters specific to winter wheat. The analysis focused on affected areas in Bengbu and Jingzhou. Experimental results from 2017 to 2022 indicate that the predominant levels of waterlogging disasters in Bengbu and Jingzhou were moderate and mild, with the proportion of mild waterlogging ranging from 30.1% to 39.3% and moderate waterlogging from 14.8% to 25.6%. A combined analysis of multi-source remote sensing data reveals the key roles of precipitation, evapotranspiration, and altitude in waterlogging disasters. This study highlights regional disparities in the distribution of waterlogging disaster risks, providing new strategies and tools for precise assessment of waterlogging disasters.

Abstract Background Anaplastic thyroid carcinoma (ATC) was a rare and extremely malignant endocrine cancer with the distinct hallmark of high proportion of cancer stem cell-like characteristics. Therapies aiming to cancer stem-like cells (CSCs) were emerging as a new direction in cancer treatment, but targeting ATC CSCs remained challenging, mainly due to incomplete insights of the regulatory mechanism of CSCs. Here, we unveiled a novel role of ISG15 in the modulation of ATC CSCs. Methods The expression of ubiquitin-like proteins were detected by bioinformatics and immunohistochemistry. The correlation between ISG15 expression and tumor stem cells and malignant progression of ATC was analyzed by single-cell RNA sequence from the Gene Expression Omnibus. Flow cytometry combined with immunofluorescence were used to verify the enrichment of ISG15 and ISGyaltion in cancer stem cells. The effect and mechanism of ISG15 and KPNA2 on cancer stem cell-like characteristics of ATC cells were determined by molecular biology experiments. Mass spectrometry combined with immunoprecipitation to screen the substrates of ISG15 and validate its ISGylation modification. Nude mice and zebrafish xenograft models were utilized to demonstrate that ISG15 regulates stem cell characteristics and promotes malignant progression of ATC. Results We found that among several ubiquitin proteins, only ISG15 was aberrantly expressed in ATC and enriched in CSCs. Single-cell sequencing analysis revealed that abnormal expression of ISG15 were intensely associated with stemness and malignant cells in ATC. Inhibition of ISG15 expression dramatically attenuated clone and sphere formation of ATC cells, and facilitated its sensitivity to doxorubicin. Notably, overexpression of ISGylation, but not the non-ISGylation mutant, effectively reinforced cancer stem cell-like characteristics. Mechanistically, ISG15 mediated the ISGylation of KPNA2 and impeded its ubiquitination to promote stability, further maintaining cancer stem cell-like characteristics. Finally, depletion of ISG15 inhibited ATC growth and metastasis in xenografted mouse and zebrafish models. Conclusion Our studies not only provided new insights into potential intervention strategies targeting ATC CSCs, but also uncovered the novel biological functions and mechanisms of ISG15 and ISGylation for maintaining ATC cancer stem cell-like characteristics. Graphical Abstract

Abstract Watershield (Brasenia schreberi) is an aquatic plant that belongs to the basal angiosperm family Cabombaceae. This species has been cultivated as an aquatic vegetable for more than 3000 years in East Asia, but the natural populations have greatly declined in recent decades and have become endangered in several countries of East Asia. In this study, by using PacBio long reads, Illumina short reads, and Hi-C sequencing data, we assembled the genome of B. schreberi, which was approximately 1170.4 Mb in size with a contig N50 of 7.1 Mb. Of the total assembled sequences, 93.6% were anchored to 36 pseudochromosomes with a scaffold N50 of 28.9 Mb. A total of 74,699 protein-coding genes were predicted in the B. schreberi genome, and 558 Mb of repetitive elements occupying 47.69% of the genome were identified. BUSCO analysis yielded a completeness score of 95.8%. The assembled high-quality genome of B. schreberi will be a valuable reference for the study of conservation, evolution and molecular breeding in this species.

Abstract The development of head and neck squamous cell carcinoma (HNSCC) is a multi-step process, and its survival depends on a complex tumor ecosystem, which not only promotes tumor growth but also helps to protect tumor cells from immune surveillance. With the advances of existing technologies and emerging models for ecosystem research, the evidence for cell-cell interplay is increasing. Herein, we discuss the recent advances in understanding the interaction between tumor cells, the major components of the HNSCC tumor ecosystem, and summarize the mechanisms of how biological and abiotic factors affect the tumor ecosystem. In addition, we review the emerging ecological treatment strategy for HNSCC based on existing studies.

Abstract Anaplastic thyroid carcinoma (ATC) is an extremely malignant type of endocrine cancer frequently accompanied by extrathyroidal extension or metastasis through mechanisms that remain elusive. We screened for the CREB3 transcription-factor family in a large cohort, consisting of four microarray datasets. This revealed that CREB3L1 was specifically up regulated in ATC tissues and negatively associated with overall survival of patients with thyroid cancer. Consistently, high expression of CREB3L1 was negatively correlated with progression-free survival in an independent cohort. CREB3L1 knockdown dramatically attenuated invasion of ATC cells, whereas overexpression of CREB3L1 facilitated the invasion of papillary thyroid carcinoma (PTC) cells. Loss of CREB3L1 inhibited metastasis and tumor growth of ATC xenografts in zebrafish and nude mouse model. Single-cell RNA-sequencing analysis revealed that CREB3L1 expression gradually increased during the neoplastic progression of a thyroid follicular epithelial cell to an ATC cell, accompanied by the activation of the extracellular matrix (ECM) signaling. CREB3L1 knockdown significantly decreased the expression of collagen subtypes in ATC cells and the fibrillar collagen in xenografts. Due to the loss of CREB3L1, ATC cells were unable to activate alpha-smooth muscle actin (α-SMA)-positive cancer-associated fibroblasts (CAFs). After CREB3L1 knockdown, the presence of CAFs inhibited the growth of ATC spheroids and the metastasis of ATC cells. Further cytokine array screening showed that ATC cells activated α-SMA-positive CAFs through CREB3L1-mediated IL-1α production. Moreover, KPNA2 mediated the nuclear translocation of CREB3L1, thus allowing it to activate downstream ECM signaling. These results demonstrate that CREB3L1 maintains the CAF-like property of ATC cells by activating the ECM signaling, which remodels the tumor stromal microenvironment and drives the malignancy of ATC. Graphical Abstract

Studies have shown that functional abnormalities in the locus coeruleus (LC) are strongly associated with depressive symptoms, but the pattern of LC functional connectivity in Alzheimer's disease patients with depressive symptoms (D-AD) remains unclear. The current study aimed to investigate the characteristics of LC functional connectivity (FC) in D-AD using resting-state functional magnetic resonance imaging (rsfMRI). We obtained rsfMRI data in 24 D-AD patients (aged 66–76 years), 14 non-depressive AD patients (nD-AD) (aged 69–79 years) and 20 normal controls (aged 67–74 years) using a 3 T scanner. We used the FC approach to investigate abnormalities in the LC brain network of D-AD patients. One-way ANCOVA and post-hoc two-sample t-tests were performed to compare the strength of functional connectivity from the LC among the three groups. Our results showed that, compared with normal controls, D-AD showed decreased left LC FC with the right caudate and left fusiform gyrus, whereas nD-AD showed decreased left LC FC with the right caudate, right middle frontal gyrus and left fusiform gyrus. Compared to nD-AD, D-AD showed increased left LC FC with right superior frontal gyrus and right precentral gyrus. These findings contribute to our understanding of the neural mechanisms of D-AD.

Enhancing the assessment of compressive strength and the efficiency of rebound hammers in non-destructive testing for high-strength concrete is an urgent issue in construction engineering. This study involved C50 to C90 high-strength concrete specimens, utilizing rebound hammers with nominal energies of 4.5 J and 5.5 J, along with a compression machine. A regression analysis was performed on the compressive strength and rebound values, resulting in linear, polynomial, power, exponential, and logarithmic equations for two different types of rebound hammers. Additionally, the precision of rebound hammers with different nominal energies and the representativeness of various rebound representative values in the measurement area were investigated. The experimental results indicate that the precision of the regionally representative strength curve in Xinjiang meets national specifications. The 4.5 J nominal energy rebound hammer exhibited a higher testing accuracy. When reducing the high-strength concrete measurement area’s rebound representative values from 16 to 14, 12, and 10, the coefficients of variation for the different rebound representative values were mostly below 10%. Within high-strength concrete structures, the strength curve formula derived from rebound representative value 16 is equally applicable to 14, 12, and 10. In practical engineering applications, prioritizing 10 ensures testing accuracy while reducing on-site testing efforts. The outcomes of this experiment establish a foundation for the development and promotion of rebound method-testing technology for high-strength concrete in Xinjiang.

The scales of the power distribution networks in real-world power grids expand quickly while the network structures are becoming more and more complex. The power grid companies analyze the power distribution networks in different business scenarios with different topology models. In this work, we propose a hierarchical graph model to describe the medium-voltage distribution network (which is a typical power distribution network in power grids) based on homeomorphic transformation. The hierarchical graph model preserves the basic network topology described by the traditional Common Information Model (CIM). Firstly, the nodes in the distribution network topology are classified according to graph theory. Secondly, three typical business scenarios of distribution network topology analysis are summarized, and the original model is simplified by progressive dimensionality reduction method to meet the analysis requirements of different scenarios, the simplified method consists of three abstract levels: critical path, core path and minimal path, and can effectively reduce the space complexity of the model while maintaining the topological properties. Thirdly, a multi-level distribution network topology construction and mapping method based on the graph database is proposed. It is used to realize the rapid conversion and traceability between different levels of topology. Finally, a practical distribution network in a county is used as an example to verify the effectiveness of the proposed method in the aspects such as topology rendering and path searching. The evaluation indicates that the proposed model can visualize the distribution network intuitively. The model can also speed up the visualization and path searching significantly.

Non-coding RNAs (ncRNAs), including miRNAs, lncRNAs, and circRNAs, emerge as crucial components for gene regulation. Nelumbo nucifera (lotus), a horticulturally important plant, differentiates into a temperate ecotype of enlarged rhizomes and a tropical ecotype of thin rhizomes. Nevertheless, whether and how ncRNAs can be rewired in expression and differentially methylated contributing to adaptive divergence of this storage organ in lotus ecotypes is unclear. Herein, we study the expression behaviors and DNA methylation patterns of ncRNAs in temperate and tropical lotus rhizomes. By whole transcriptome sequencing, we found both mRNAs and lncRNAs have divergent expression patterns between ecotypes, whereas miRNAs and circRNAs tended to be accession-specific or noisier in expression. The differentially expressed ncRNAs are involved in phenotypic differentiation of lotus rhizome between ecotypes, as the genes that interacted with them in the competing endogenous RNA network are enriched in functions including carbohydrate metabolism and plant hormone signaling, being critical to rhizome enlargement. Intriguingly, ncRNA-targeted genes are less prone to show positive selection or differential expression during ecotypic divergence due to constraints from ncRNA-mRNA interactions. The methylation levels of ncRNAs generally tend to be higher in temperate lotus than in tropical lotus, and differential methylation of lncRNAs also tends to have expression changes. Overall, our study of ncRNAs and their targets highlights the role of ncRNAs in rhizome growth variation between lotus ecotypes through expression rewiring and methylation modification.

Different from ground-based or airborne early warning radar, space-based radar (SBR) possesses large coverage capability. As a result, several discrete strong scatter points from the antenna side-lobe shares the same feature with the real targets in range-Doppler domain, which leads to false alarms when conducting constant false alarm rate (CFAR) detection process, and the detection performance with regard to SBR deteriorates seriously. In this paper, a discrete side-lobe clutter recognition method based on sliding filter response loss is proposed for space-based radar. Firstly, considering both the echo inhomogeneity and the limited degrees of freedom (DOFs) after dimension-reduced space-time adaptive processing (STAP), the sliding window design strategy is employed to segment range cells for the observation scene. Then, the images related to different range segments are registered after clutter suppression, in this way, the candidate target parameters, including the position information and the amplitude information are counted. On this basis, the reliable recognition scheme between the real target and the discrete side-lobe clutter can be realized by comparing these filter response losses. Compared with recent works, experimental results based on real measured data show that the proposed method significantly improves the fault-tolerant discrimination ability, which possesses high robustness in algorithm performance as well as good prospect in engineering application.

BackgroundCoronavirus disease 2019 (COVID-19) and inflammatory bowel disease (IBD) are both caused by a disordered immune response and have direct and profound impacts on health care services. In this study, we implemented transcriptomic and single-cell analysis to detect common molecular and cellular intersections between COVID-19 and IBD that help understand the linkage of COVID-19 to the IBD patients.MethodsFour RNA-sequencing datasets (GSE147507, GSE126124, GSE9686 and GSE36807) from Gene Expression Omnibus (GEO) database are extracted to detect mutual differentially expressed genes (DEGs) for IBD patients with the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to find shared pathways, candidate drugs, hub genes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980) are used to analyze the immune characteristics of hub genes and the proportion of immune cell types, so as to find common immune responses between COVID-19 and IBD.ResultsA total of 121 common DEGs were identified among four RNA-seq datasets, and were all involved in the functional enrichment analysis related to inflammation and immune response. Transcription factors-DEGs interactions, miRNAs-DEGs coregulatory networks, and protein-drug interactions were identified based on these datasets. Protein-protein interactions (PPIs) was built and 59 hub genes were identified. Moreover, scRNA-seq of peripheral blood monocyte cells (PBMCs) from COVID-19 patients revealed a significant increase in the proportion of CD14+ monocytes, in which 38 of 59 hub genes were highly enriched. These genes, encoding inflammatory cytokines, were also highly expressed in inflammatory macrophages (IMacrophage) of intestinal tissues of IBD patients.ConclusionsWe conclude that COVID-19 may promote the progression of IBD through cytokine storms. The candidate drugs and DEGs-regulated networks may suggest effective therapeutic methods for both COVID-19 and IBD.

Background Sagittaria trifolia Linn. is a widespread macrophyte in Asia and southeast Europe and cultivated in parts of Asia. Although a few genomic studies have been conducted for S. trifolia var. sinensis, a crop breed, there is limited genomic information on the wild species of S. trifolia. Effective microsatellite markers are also lacking. Objective To assemble transcriptome sequence and develop effective EST-SSR markers for S. trifolia. Methods Here we developed microsatellite markers based on tri-, tetra-, penta-, and hexa-nucleotide repeat sequences by comparatively screening multiple transcriptome sequences of eleven individuals from ten natural populations of S. trifolia. Results A total of 107,022 unigenes were de novo assembled, with a mean length of 730 bp and an N50 length of 1,378 bp. The main repeat types were mononucleotide, trinucleotide, and dinucleotide, accounting for 55.83%, 23.51%, and 17.56% of the total repeats, respectively. A total of 86 microsatellite loci were identified with repeats of tri-, tetra-, penta-, and hexa-nucleotide. For SSR verification, 28 polymorphic loci from 41 randomly picked markers were found to produce stable and polymorphic bands, with the number of alleles per locus ranging from 2 to 11 and a mean of 5.2. The range of polymorphic information content (PIC) of each SSR locus varied from 0.25 to 0.80, with an average of 0.58. The expected heterozygosity ranged from 0.29 to 0.82, whereas the observed heterozygosity ranged from 0.25 to 0.90. Conclusion The assembled transcriptome and annotated unigenes of S. trifolia provide a basis for future studies on gene functions, pathways, and molecular mechanisms associated with this species and other related. The newly developed EST-SSR markers could be effective in examining population genetic structure, differentiation, and parentage analyses in ecological and evolutionary studies of S. trifolia.

Programmable photonic circuits performing universal linear-optical transformations underpin vital functions in photonic quantum information processing, quantum-enhanced sensor networks, machine learning, and many other intriguing applications. Recent advances in photonic integrated circuits facilitate monolithic integration of externally controlled Mach-Zehnder interferometers (MZIs) which can implement arbitrary unitary transformation on a large number of input/output modes. In this work, we demonstrate a 4×4 programmable linear photonic circuit on lithium niobate on an insulator platform employing fast, power-efficient, and low-loss electro-optical phase shifters, showing enormous advantages in terms of configuration rate and power consumption. Our device composed of cascaded MZIs possesses a total on-chip power dissipation of only 1.5 mW when operating at 100 MHz modulation rate. Our MZIs exhibit high bandwidth of 22.5 GHz, fast switching with 160-ps rise time and 120-ps fall time, low insertion loss of 0.15 dB, and on-chip extinction ratio of −34 dB for both cross and bar routes.

Understanding the genetic variants responsible for floral trait diversity is important for the molecular breeding of ornamental flowers. Widely used in water gardening for thousands of years, the sacred lotus exhibits a wide range of diversity in floral organs. Nevertheless, the genetic variations underlying various morphological characteristics in lotus remain largely unclear. Here, we performed a genome-wide association study of sacred lotus for 12 well-recorded ornamental traits. Given a moderate linkage disequilibrium level of 32.9 kb, we successfully identified 149 candidate genes responsible for seven flower traits and plant size variations, including many pleiotropic genes affecting multiple floral-organ-related traits, such as NnKUP2. Notably, we found a 2.75-kb presence-and-absence genomic fragment significantly associated with stamen petaloid and petal number variations, which was further confirmed by re-examining another independent population dataset with petal number records. Intriguingly, this fragment carries MITE transposons bound by siRNAs and is related to the expression differentiation of a nearby candidate gene between few-petalled and double-petalled lotuses. Overall, these genetic variations and candidate genes responsible for diverse lotus traits revealed by our GWAS highlight the role of transposon variations, particularly MITEs, in shaping floral trait diversity.

We experimentally investigated clean optical emissions from multiple combustion intermediates including free radicals C2, CH, and CN at multiple wavelengths induced by ultrashort 1,030-nm laser pulses. We systematically study the evolution of the fluorescence emissions induced by the femtosecond laser filament in the combustion field with the parameters such as the laser pulse energy, pulse duration, and focal length. Compared with the previous work, we promote that the fluorescence emissions of the combustion product can be manipulated effectively by controlling the femtosecond laser characteristics including pulse energy, duration, and the focusing conditions. This process helps to optimize its signal-to-noise ratio, which provides a further application of the femtosecond laser pulses to sense the combustion intermediates.

Distributed radar systems promise to significantly enhance target localization by virtue of the superiority of multi-view observations from widely separated radars, compared to their monostatic counterparts. Nevertheless, when the radar number is limited, performing target localization bears the brunt of the parameter identifiability requirement that the parameter number must be no less than the number of independent measurements. In this way, the canonical two-stage target localization method, as well as its developments, is no longer appropriate for direct application. Hence, in this paper, we propose a novel target localization method using time-difference-of-arrival (TDOA) measurements with the minimum number of radars under platform position uncertainties. The referred distributed system is a bistatic multi-receiver system, where the primary signal is transmitted by a geostationary Earth orbit (GEO) satellite while receivers are equipped on several unmanned aerial vehicles (UAVs). In the first stage, the reference range from the reference radar to the target is estimated by a quadratic function, and then the weighted least squares (WLS) solution of the target location is updated by substituting the range estimate back into it. In the second stage, we invoke the Taylor series approximation to further refine the target localization obtained by the first stage. It can be foreseen that the developed method is beneficial for scenarios with a limited number of radars, including engineering projects such as fire control, surveillance, and guidance, to support high-accuracy target localization. The simulation results show the superiority of the localization performance of the proposed method over other existing methods.

N6-methyladenine (6mA) DNA methylation has emerged as an important epigenetic modification in eukaryotes. Nevertheless, the evolution of the 6mA methylation of homologous genes after species and after gene duplications remains unclear in plants. To understand the evolution of 6mA methylation, we detected the genome-wide 6mA methylation patterns of four lotus plants (Nelumbo nucifera) from different geographic origins by nanopore sequencing and compared them to patterns in Arabidopsis and rice. Within lotus, the genomic distributions of 6mA sites are different from the widely studied 5mC methylation sites. Consistently, in lotus, Arabidopsis and rice, 6mA sites are enriched around transcriptional start sites, positively correlated with gene expression levels, and preferentially retained in highly and broadly expressed orthologs with longer gene lengths and more exons. Among different duplicate genes, 6mA methylation is significantly more enriched and conserved in whole-genome duplicates than in local duplicates. Overall, our study reveals the convergent patterns of 6mA methylation evolution based on both lineage and duplicate gene divergence, which underpin their potential role in gene regulatory evolution in plants.

The calculation and analysis of a power distribution network (PDN) require accurate device parameters. However, a PDN has many points, and the distribution area is very wide. The PDN parameters are influenced by manual entry, and most are relatively random. Additionally, these parameters are affected by the operating status. Thus, this paper proposes an algorithm that accurately identifies PDN parameters based on the Markov chain and Monte Carlo (MCMC) method. The algorithm assumes that the PDN parameters conform to a nonlinear probability space. The parameters are the line resistance $R_{L} $ , line reactance $X_{L} $ , short-circuit loss $P_{k} $ , short-circuit voltage percentage $U_{k}$ %, no-load loss $P_{0} $ , no-load current percentage $I_{0} $ %, etc. The algorithm in this paper uses the Monte Carlo method to provide parameter values that conform to the initial probability distribution and then combines the data collected from the actual feeder to perform power flow calculations to obtain the loss function. The data include the head and end voltages and active and reactive power on the low voltage side. The Markov chain and loss function update the initial parameter probability distribution. The low voltage side voltage of the power flow calculation is iteratively calculated under the new given parameters to obtain the new loss function, and finally, the PDN line and transformer parameter values are identified. Actual feeder data verification results show that this MCMC PDN parameter identification method can obtain high-precision parameter values without phase angle information; additionally, this method is insensitive to the initial values and exhibits fast convergence.

Measurement(s) reference genome data • whole genome sequencing • transcriptome Technology Type(s) Hi-C • PacBio Sequel System • Illumina sequencing • RNA sequencing • DNA sequencing Sample Characteristic - Organism Nelumbo nucifera Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13487271

Abstract The accurate placement of an ancient whole-genome duplication (WGD) in relation to the lineage divergence is important. Here, we re-investigated the Aquilegia coerulea WGD and found it is more likely lineage-specific rather than shared by all eudicots.

Abstract Background Gene expression is complex and regulated by multiple molecular mechanisms, such as miRNA-mediated gene inhibition and alternative-splicing of pre-mRNAs. However, the coordination of interaction between miRNAs with different splicing isoforms, and the change of splicing isoform in response to different cellular environments are largely unexplored in plants. In this study, we analyzed the miRNA and mRNA transcriptome from lotus (Nelumbo nucifera), an economically important flowering plant. Results Through RNA-seq analyses on miRNAs and their target genes (isoforms) among six lotus tissues, expression of most miRNAs seem to be negatively correlated with their targets and tend to be tissue-specific. Further, our results showed that preferential interactions between miRNAs and hub gene isoforms in one coexpression module which is highly correlated with leaf. Intriguingly, for many genes, their corresponding isoforms were assigned to different co-expressed modules, and they exhibited more divergent mRNA structures including presence and absence of miRNA binding sites, suggesting functional divergence for many isoforms is escalated by both structural and expression divergence. Further detailed functional enrichment analysis of miRNA targets revealed that miRNAs are involved in the regulation of lotus growth and development by regulating plant hormone-related pathway genes. Conclusions Taken together, our comprehensive analyses of miRNA and mRNA transcriptome elucidate the coordination of interaction between miRNAs and different splicing isoforms, and highlight the functional divergence of many transcript isoforms from the same locus in lotus.

With the extensive use of antibiotics, antibiotics and their induced resistance genes (ARGs) have become new types of pollutants widely distributed in a variety of environmental media. The contamination of antibiotics and ARGs occurring in important living and agricultural regions has aroused wide concern worldwide, especially in lake basins. The Dongting Lake basin is one of the important aquaculture and livestock areas in China, which is accompanied by a large amount of antibiotic use and discharge. However, the occurrence characteristics of antibiotics and ARGs in a multi-environment medium are still unclear. In this study, surface water and sediment samples in East Dongting Lake were collected by season, antibiotics and ARGs were quantitatively analyzed, and the risk quotient method was used to evaluate the ecological risk of antibiotics in surface water. 1) The concentration of antibiotics in the surface water of East Dongting Lake ranged from ND to 943.49 ng/L, with the maximum average concentration of 20.92 ng/L in spring. The concentration of antibiotics in sediments ranged from ND to 177.43 ng/g, with the maximum average concentration of 16.38 ng/g in fall. Ofloxacin (OFL) and sulfamethoxazole (SMX) were the main antibiotic pollutants in East Dongting Lake Basin. 2) sul1 and sul2 were the dominant ARGs in East Dongting Lake Basin. For spatial change, the total abundance of ARGs upstream was higher than that downstream. For seasonal change, the surface water and sediment were characterized by spring > summer > fall. 3) OFL and sulfamethoxazole might pose a significant high risk to aquatic organisms both in three seasons, and the ecological risk of antibiotics in East Dongting Lake is more significant at low temperatures than high. This study could provide important data information of the occurrence and concentration of antibiotics and ARGs in East Dongting Lake Basin.

Accurate network parameters are of great importance for the accurate control of the power distribution network (PDN). In fact, the line parameters of the PDN are always affected by external operating conditions. However, most of the line parameters in the PDN account are static parameters. In order to obtain the dynamic parameters that reflect the line operating condition, this study presents a method that uses only the RMS voltage of the first section of the line and the RMS voltage and power at the low-voltage side of the transformer. This study introduces the processing method of abnormal measurement data, constructs a derivative-free identification equation represented by a matrix, and uses the designed loss function combined with a heuristic method to solve the equation. An actual feeder is used in the experimental part. The experimental data show that the method has some antipower noise ability, and the identification accuracy of this method is better than that of the genetic algorithm and random search algorithm.

Accurate device parameters play a critical role in the calculation and analysis of power distribution networks (PDNs). However, device parameters are always affected by the operating status and influenced by manual entry. Besides, the distribution area of PDN is very wide, which brings more challenges to parameter identification work. Therefore, developing appropriate algorithms for accurately identifying PDN parameters has attracted much more attention from researchers recently. Most of the existing parameter identification algorithms are gradient-free and based on heuristic schemes. Herein, an adaptive gradient-based method is proposed for parameter identification in PDN. The analytical expressions of the gradients of the loss function with respect to the parameters are derived, and an adaptive updating scheme is utilized. By comparing the proposed method and several heuristic algorithms, it is found that the errors in both three criteria via our solution are much lower with a much smoother and more stable convergence of loss function. By further taking a linear transformation of the loss function, the method of this work significantly promotes the parameter identification performance with much lower variance in repeat experiments, indicating that the proposed method in this work achieves a more robust performance to identify PDN parameters. This work gives a practical demonstration by utilizing the gradient-based method for parameter identification of PDN.

For distributed satellite constellations, detection performance can be equivalently regarded as a single large satellite by the cooperative operation of multiple small satellites, which is a promising research topic of the Next-Generation Radar (NGR) system. However, dense grating lobes inevitably occur in the synthetic transmit pattern due to its distributed configuration, as a result of which the detection performance of dynamic coherent radar is seriously weakened. In this paper, a novel transmit beampattern optimization method for dynamic coherent radar based on a distributed satellite constellation is presented. Firstly, the effective coherent detection range interval is determined by several influence factors, i.e., coherent detection, far-field, and system link constraints. Then, we discuss the quantitative evaluation method for coherent integration in terms of synchronization error, beam pointing error, and high-speed motion characteristics and we allocate the corresponding terms in a reasonable way from the perspective of engineering. Finally, the space–time–frequency degrees of freedom (DOFs), which can be collected from satellite spacing, carrier frequencies, and platform motion characteristics, are utilized to realize a robust transmit beampattern with low sidelobe by invoking a genetic algorithm (GA). Simulation results validate the effectiveness of our theoretic analysis, and unambiguous coherent transmit beamforming with a satellite constellation of limited scale is accomplished.

Abstract Background Majority of the species within Senecioneae are classified in Senecio, making it the tribe’s largest genus. Certain intergeneric relationships within the tribe are vaguely defined, with the genus Senecio being partly linked to this ambiguity. Infrageneric relationships within Senecio remain largely unknown and consequently, the genus has undergone continuous expansion and contraction over the recent past due to addition and removal of taxa. Dendrosenecio, an endemic genus in Africa, is one of its segregate genera. To heighten the understanding of species divergence and phylogeny within the tribe, the complete chloroplast genomes of the first five Senecio and six Dendrosenecio species were sequenced and analyzed in this study. Results The entire length of the complete chloroplast genomes was ~ 150 kb and ~ 151 kb in Dendrosenecio and Senecio respectively. Characterization of the 11 chloroplast genomes revealed a significant degree of similarity particularly in their organization, gene content, repetitive sequence composition and patterns of codon usage. The chloroplast genomes encoded an equal number of unique genes out of which 80 were protein-coding genes, 30 transfer ribonucleic acid, and four ribosomal ribonucleic acid genes. Based on comparative sequence analyses, the level of divergence was lower in Dendrosenecio. A total of 331 and 340 microsatellites were detected in Senecio and Dendrosenecio, respectively. Out of which, 25 and five chloroplast microsatellites (cpSSR) were identified as potentially valuable molecular markers. Also, through whole chloroplast genome comparisons and DNA polymorphism tests, ten divergent hotspots were identified. Potential primers were designed creating genomic tools to further molecular studies within the tribe. Intergeneric relationships within the tribe were firmly resolved using genome-scale dataset in partitioned and unpartitioned schemes. Two main clades, corresponding to two subtribes within the Senecioneae, were formed with the genus Ligularia forming a single clade while the other had Dendrosenecio, Pericallis, Senecio and Jacobaea. A sister relationship was revealed between Dendrosenecio and Pericallis whereas Senecio, and Jacobaea were closely placed in a different clade. Conclusion Besides emphasizing on the potential of chloroplast genome data in resolving intergeneric relationships within Senecioneae, this study provides genomic resources to facilitate species identification and phylogenetic reconstructions within the respective genera.

In this work, the parameter identifiability of sensor position perturbations in a distributed network is analyzed through establishing the link between rank of the Jacobian matrix and parameter identifiability under Gaussian noise. Here, the calibration is classified as either external or internal, dependent on whether auxiliary sources are exploited. It states that, in the case of internal calibration, sensor position perturbations can be precisely calibrated when the position of a sensor and orientation to a second sensor along with the coordinate of a third sensor along some axis, are known. In the case of external calibration where auxiliary sources are introduced to support the process, the identifiability condition for configuration calibration is to have at least three noncollinear auxiliary sources with the distributed sensor network avoiding the collinear and coplanar geometries. As the assumption of small perturbations is considered, the parameter identifiability is capable of being measured by virtue of the Bayesian Cramer–Rao lower bound (BCRLB), after asymptotical tightness of the BCRLB is verified. Simulations corroborate well with the theoretical development.

To solve the current privacy leakage problems of cloud storage services, research on users’ payment intention for cloud storage services with privacy protection is extremely important for improving the sustainable development of cloud storage services. An evolutionary game model between cloud storage users and providers that considers privacy is constructed. Then, the model’s evolutionary stability strategies via solving the replication dynamic equations are analyzed. Finally, simulation experiments are carried out for verifying and demonstrating the influence of model parameters. The results show that the evolutionary stable strategies are mainly affected by the privacy protection profit growth coefficient of both parties, input costs, free-riding gains, and other factors. If the profit growth coefficient is very small, users will not choose to pay and providers will not choose to actively protect user information. As the profit growth coefficient increases, both parties will promote the development of privacy protection with a higher probability. The results are beneficial for cloud storage providers to increase the number of paid users and thus to achieve the sustainable development of cloud storage service.

Eragrostis tef is an important cereal crop in Ethiopia with excellent storage properties, high–quality food, and the unique ability to thrive in extreme environmental conditions. However, the application of advanced molecular tools for breeding and conservation of these species is extremely limited. Therefore, developing chloroplast genome resources and high-resolution molecular markers are valuable to E. tef population and biogeographic studies. In the current study, we assembled and compared the complete plastomes of 32 E. tef accessions. The size of the plastomes ranged from 134,349 to 134,437 bp with similar GC content (∼38.3%). Genomes annotations revealed 112 individual genes, including 77 protein-coding, 31 tRNA, and 4 rRNA genes. Comparison of E. tef plastomes revealed a low degree of intraspecific sequence variations and no structural differentiations. Furthermore, we found 34 polymorphic sites (13 cpSSRs, 12 InDels, and 9 SNPs) that can be used as valuable DNA barcodes. Among them, the majority (88%) of the polymorphic sites were identified in the noncoding genomic regions. Nonsynonymous (ka) and synonymous (ks) substitution analysis showed that all PCGs were under purifying selection (ka/ks

Surface albedo is an essential parameter in many solar radiation applications. Although several models are available, it remains debatable whether they are applicable to other locations. Using long-term daily measurements of radiation acquired by observational networks in China, this study examined the applicability of six existing albedo models: Ineichen model (IeM), Gueymard model (GM), Dong model (DeM), Iziomon-Mayer model (IMM), Morton model (MM), and Zhou model (ZeM). The evaluation results of model performance through statistical analysis showed that among the available ground albedo models, ZeM had the best overall performance at 12 selected stations, IeM was shown to provide acceptable estimations for locations where albedo records are readily available. The statistical results of individual station have shownthat the number of input parameters is not the only key factor for determining the predictive performance of ground albedo models. In other words, a simple model has potential for accurate estimation of ground albedo with appropriate model parameters. Therefore, the simple two-parameter DeM was selected to re-calibrate with in-situ radiometric measurements, which can be adopted as a surrogate for ZeM to predict surface albedo in China.

In the presence of unknown array errors, sparse recovery based space-time adaptive processing (SR-STAP) methods usually directly use the ideal spatial steering vectors without array errors to construct the space-time dictionary; thus, the steering vector mismatch between the dictionary and clutter data will cause a severe performance degradation of SR-STAP methods. To solve this problem, in this paper, we propose a two-stage SR-STAP method for suppressing nonhomogeneous clutter in the presence of arbitrary array errors. In the first stage, utilizing the spatial-temporal coupling property of the ground clutter, a set of spatial steering vectors with array errors are well estimated by fine Doppler localization. In the second stage, firstly, in order to solve the model mismatch problem caused by array errors, we directly use these spatial steering vectors obtained in the first stage to construct the space-time dictionary, and then, the constructed dictionary and multiple measurement vectors sparse Bayesian learning (MSBL) algorithm are combined for space-time adaptive processing (STAP). The proposed SR-STAP method can exhibit superior clutter suppression performance and target detection performance in the presence of arbitrary array errors. Simulation results validate the effectiveness of the proposed method.

This study presents a comparative analysis of the deformation control effect of the hydraulic servo steel struts and ordinary steel struts of a foundation pit based on the measured axial force of the steel struts, lateral wall deflection, and ground surface settlement due to pit excavation. The results indicate that ordinary steel struts installed via axial preloading exhibit a disadvantageous axial force loss with a maximum value equal to 86.7% of the axial preloading force. When compared with ordinary steel struts, the hydraulic servo steel strut exhibits a superior supporting effect. The hydraulic servo steel strut adjusts the axial force in real time based on the deformation of the retaining structure and the axial force of the struts. Thus, the ratio of maximum lateral deflection to the excavation depth of a deep foundation pit in soft soil is less than 0.3%. Concrete struts undergo unsupported exposure during the excavation process, leading to sharply increasing deformation of the retaining structure. Therefore, regarding a foundation pit with strict requirements for deformation control, the use of hydraulic servo steel struts rather than concrete struts is recommended.

We report generation of spectrally bright vacuum ultraviolet (VUV) and deep UV (DUV) coherent radiations at the wavelengths of 192 nm, 198 nm and 204 nm. These DUV/VUV radiations originate from resonant four-wave mixing assisted by quantum coherence in tunnel-ionized CO molecules. The electronic coherence is created when the pump pulses resonantly excite electronic transitions of CO ^+ . The technique allows for the selective switch of DUV/VUV wavelengths provided by the abundant energy levels of molecular ions. The developed source can have arbitrary polarization states by manipulating the polarization of the pump pulse. It also exhibits a spectral bandwidth of 5∼7 cm ^−1 , a divergence angle of 3∼5 mrad, a pulse duration of ∼10 ps, and a photon flux of ∼10 ^10 photons/s. The superior temporal and spectral properties give rise to a broadband Raman comb in the DUV/VUV region.

Many plant species exhibit different leaf morphologies within a single plant, or heterophylly. The molecular mechanisms regulating this phenomenon, however, have remained elusive. In this study, the transcriptomes of submerged and floating leaves of an aquatic heterophyllous plant, Potamogeton octandrus Poir, at different stages of development, were sequenced using high-throughput sequencing (RNA-Seq), in order to aid gene discovery and functional studies of genes involved in heterophylly. A total of 81,103 unigenes were identified in submerged and floating leaves and 6,822 differentially expressed genes (DEGs) were identified by comparing samples at differing time points of development. KEGG pathway enrichment analysis categorized these unigenes into 128 pathways. A total of 24,025 differentially expressed genes were involved in carbon metabolic pathways, biosynthesis of amino acids, ribosomal processes, and plant-pathogen interactions. In particular, KEGG pathway enrichment analysis categorized a total of 70 DEGs into plant hormone signal transduction pathways. The high-throughput transcriptomic results presented here highlight the potential for understanding the molecular mechanisms underlying heterophylly, which is still poorly understood. Further, these data provide a framework to better understand heterophyllous leaf development in P. octandrus via targeted studies utilizing gene cloning and functional analyses.

To detect the robustness of communication module of intelligent electronic devices（IED）in smart station,a device robustness test method was presented based on abnormal messages,and a robustness testing system was achieved.Some devices were selected for robustness test experiment to verify the rationality and feasibility.Results show that the method can effectively detect the robustness of devices and locate the abnormal messages which cause devices' failure.

Hagenia is an endangered monotypic genus endemic to the topical mountains of Africa. The only species, Hagenia abyssinica (Bruce) J.F. Gmel, is an important medicinal plant producing bioactive compounds that have been traditionally used by African communities as a remedy for gastrointestinal ailments in both humans and animals. Complete chloroplast genomes have been applied in resolving phylogenetic relationships within plant families. We employed high-throughput sequencing technologies to determine the complete chloroplast genome sequence of H. abyssinica. The genome is a circular molecule of 154,961 base pairs (bp), with a pair of Inverted Repeats (IR) 25,971 bp each, separated by two single copies; a large (LSC, 84,320 bp) and a small single copy (SSC, 18,696). H. abyssinica’s chloroplast genome has a 37.1% GC content and encodes 112 unique genes, 78 of which code for proteins, 30 are tRNA genes and four are rRNA genes. A comparative analysis with twenty other species, sequenced to-date from the family Rosaceae, revealed similarities in structural organization, gene content and arrangement. The observed size differences are attributed to the contraction/expansion of the inverted repeats. The translational initiation factor gene (infA) which had been previously reported in other chloroplast genomes was conspicuously missing in H. abyssinica. A total of 172 microsatellites and 49 large repeat sequences were detected in the chloroplast genome. A Maximum Likelihood analyses of 71 protein-coding genes placed Hagenia in Rosoideae. The availability of a complete chloroplast genome, the first in the Sanguisorbeae tribe, is beneficial for further molecular studies on taxonomic and phylogenomic resolution within the Rosaceae family.

Atmospheric lasing has aroused much interest in the past few years. The ‘air–laser’ opens promising potential for remote chemical sensing of trace gases with high sensitivity and specificity. At present, several approaches have been successfully implemented for generating highly coherent laser beams in atmospheric condition, including both amplified-spontaneous emission, and narrow-bandwidth stimulated emission in the forward direction in the presence of self-generated or externally injected seed pulses. Here, we report on generation of multiple-wavelength Raman lasers from nitrogen molecular ions ( ${{\rm{N}}}_{2}^{+}$ ), driven by intense mid-infrared laser fields. Intuitively, the approach appears problematic for the small nonlinear susceptibility of ${{\rm{N}}}_{2}^{+}$ ions, whereas the efficiency of Raman laser can be significantly promoted in near-resonant condition. More surprisingly, a Raman laser consisting of a supercontinuum spanning from ∼310 to ∼392 nm has been observed resulting from a series near-resonant nonlinear processes including four-wave mixing, stimulated Raman scattering and cross phase modulation. To date, extreme nonlinear optics in molecular ions remains largely unexplored, which provides an alternative means for air–laser-based remote sensing applications.