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β-Ti shape-memory alloys, that show shape-memory effect or superelasticity owing to thermoelastic martensitic transformation, have potential for various applications. Herein, we propose an experimental approach for the efficient and high-throughput discovery of Ti-based shape-memory alloys with new compositions. We employed a diffusion couple composed of Ti–4.5Cr (at%) and Ti–30Al–4.5Cr (at%) alloys, and combined techniques of microstructure characterization and micro-Vickers hardness testing to uncover the surface relief attributable to martensitic transformation, correlating with varying Al concentration. By coupling with the observation of abrupt decline in the Vickers hardness and stress-induced martensitic transformation near the indent, a β-phase Ti alloy with a new composition of Ti–17Al–4.5Cr (at%) was successfully found, and excellent shape-memory effect was demonstrated. The integration of the diffusion couple, hardness test, and microstructural analysis provides a robust framework for the accelerated development of new Ti-based shape-memory alloys.

Abstract Background The use of gene therapy to deliver microRNAs (miRNAs) has gradually translated to preclinical application for the treatment of intervertebral disc degeneration (IDD). However, the effects of miRNAs are hindered by the short half-life time and the poor cellular uptake, owing to the lack of efficient delivery systems. Here, we investigated nucleus pulposus cell (NPC) specific aptamer-decorated polymeric nanoparticles that can load miR-150-5p for IDD treatment. Methods The role of miR-150-5p during disc development and degeneration was examined by miR-150-5p knockout (KO) mice. Histological analysis was undertaken in disc specimens. The functional mechanism of miR-150-5p in IDD development was investigated by qRT-PCR assay, Western blot, coimmunoprecipitation and immunofluorescence. NPC specific aptamer-decorated nanoparticles was designed, and its penetration, stability and safety were evaluated. IDD progression was assessed by radiological analysis including X-ray and MRI, after the annulus fibrosus needle puncture surgery with miR-150-5p manipulation by intradiscal injection of nanoparticles. The investigations into the interaction between aptamer and receptor were conducted using mass spectrometry, molecular docking and molecular dynamics simulations. Results We investigated NPC-specific aptamer-decorated polymeric nanoparticles that can bind to miR-150-5p for IDD treatment. Furthermore, we detected that nanoparticle-loaded miR-150-5p inhibitors alleviated NPC senescence in vitro, and the effects of the nanoparticles were sustained for more than 3 months in vivo. The microenvironment of NPCs improves the endo/lysosomal escape of miRNAs, greatly inhibiting the secretion of senescence-associated factors and the subsequent degeneration of NPCs. Importantly, nanoparticles delivering miR-150-5p inhibitors attenuated needle puncture-induced IDD in mouse models by targeting FBXW11 and inhibiting TAK1 ubiquitination, resulting in the downregulation of NF-kB signaling pathway activity. Conclusions NPC-targeting nanoparticles delivering miR-150-5p show favorable therapeutic efficacy and safety and may constitute a promising treatment for IDD. Graphical Abstract

Abstract The active Himalayan-Tibetan orogen, where India underthrusts into Asia, is an important geological source of carbon dioxide (CO2) emission into Earth’s atmosphere. However, the extent to which Indian underthrusting could stimulate the mobilization of deeply-sourced carbon and its subsequent emission remains unknown. Here, we use a combination of field observations coupled with in-situ CO2 flux measurements and helium and carbon isotopic data, to study the controls on CO2 origins and fluxes in a 400-kilometre-long rift transecting northern Himalaya and southern Tibet. High diffuse CO2 fluxes sustained by pure crustal fluids are confined to rift segments in the northern Himalaya, while toward southern Tibet, CO2 fluxes become lower but mantle fluid inputs are identified. Such rift-related CO2 degassing profile suggests metamorphic decarbonation and release of carbon-bearing fluids enhanced by the underthrusting Indian lower crust, agreeing well with Himalayan metamorphism and orogen-parallel lithospheric extension. Deep CO2 fluxes from extensional tectonics in northern Himalaya and southern Tibet, primarily of crustal origins, are comparable to mantle CO2 fluxes from global mid-ocean ridges. Our findings demonstrate that geophysical and geo-tectonic responses to continental underthrusting could facilitate massive crustal carbon mobilization and emission, making active collisional orogens globally important carbon sources.

Abstract The gasdermin (GSDM) family has garnered significant attention for its pivotal role in immunity and disease as a key player in pyroptosis. This recently characterized class of pore-forming effector proteins is pivotal in orchestrating processes such as membrane permeabilization, pyroptosis, and the follow-up inflammatory response, which are crucial self-defense mechanisms against irritants and infections. GSDMs have been implicated in a range of diseases including, but not limited to, sepsis, viral infections, and cancer, either through involvement in pyroptosis or independently of this process. The regulation of GSDM-mediated pyroptosis is gaining recognition as a promising therapeutic strategy for the treatment of various diseases. Current strategies for inhibiting GSDMD primarily involve binding to GSDMD, blocking GSDMD cleavage or inhibiting GSDMD-N-terminal (NT) oligomerization, albeit with some off-target effects. In this review, we delve into the cutting-edge understanding of the interplay between GSDMs and pyroptosis, elucidate the activation mechanisms of GSDMs, explore their associations with a range of diseases, and discuss recent advancements and potential strategies for developing GSDMD inhibitors.

Summary: Ubiquitination is essential for the proteasomal turnover of IRF3, the central factor mediating the antiviral innate immune response. However, the spatiotemporal regulation of IRF3 ubiquitination for the precise activation and timely resolution of innate immunity remains unclear. Here, we identified BRCA1-associated protein-1 (BAP1) and ubiquitin-protein ligase E3C (UBE3C) as the key deubiquitinase and ubiquitinase for temporal control of IRF3 stability during viral infection. In the early stage, BAP1 dominates and removes K48-linked ubiquitination of IRF3 in the nucleus, preventing its proteasomal degradation and facilitating efficient interferon (IFN)-β production. In the late stage, E3 ligase UBE3C, induced by IFN-β, specifically mediates IRF3 ubiquitination and promotes its proteasomal degradation. Overall, the sequential interactions with BAP1 and UBE3C govern IRF3 stability during innate response, ensuring effective viral clearance and inflammation resolution. Our findings provide insights into the temporal control of innate signaling and suggest potential interventions in viral infection.

Secondary microbial methane could provide a valuable energy source if it were better understood. Although coal seam is an ideal environment for investigating secondary microbial methane, there are few studies to trace the secondary microbial methane of high-rank coals. Here, we collected co-produced water samples from coalbeds in the Qinshui Basin (China) and analyzed the microbial community structure by 16S ribosomal RNA (16S rRNA) amplicon sequencing analysis. 16S rRNA sequencing demonstrated abundant methanogens in coalbeds including 6 orders (Methanobacteriales, Methanococcales, Methanofastidiosales, Methanomassiliicoccale, Methanomicrobiales, and Methanosarciniales) and 22 genera of methanogens. Superheavy DIC (δ13CDIC ranging from −4.2‰ to 34.8‰) and abundance of methanogenic microbes in co-produced water revealed the generation of secondary biogenic methane in high-rank coal seams in the Qingshui Basin. Hydrogenotrophic methanogenesis is the main pathway for secondary biogenic methane production. In deeply buried coal seams, biogenic methane is dominated by CO2 and H2 reduction methanogenesis, and in shallow buried coal seams, it may be produced synergistically by hydrocarbon degradation and hydrogenotrophic methanogenic microbes. The study discussed here is important for a better understanding of the generation of secondary microbial methane in high-rank coal.

A thorough comprehension of the trade-offs/synergies (TOS) among ecosystem services (ESs) and their underlying drivers are vital for promoting regional sustainable development and making informed decisions. In this study, we explored the spatial and temporal dynamics of six ESs and their driving factors at both the grid and county scales in the Central-southern Liaoning urban agglomeration (CSLUA) utilizing various analytical techniques such as Pearson correlation analysis, geographically weighted regression, self-organized mapping analysis, and Redundancy Analysis. Our results revealed that: (1) Between 2000 and 2020, water yield (WY), soil retention (SR), landscape aesthetics (LA), and food production (FP) exhibited an overall upward trend, while habitat quality (HQ) and carbon storage (CS) demonstrated a decreasing trend; (2) From grid scale to county scale, we found concentration effects of TOS relationships was weaken, mainly between supply services (WY, FP) and other services. The significant relationship between some ES pairs has become neutral. The geospatial heterogeneity of TOS relationships for all ESs was also weakened at county scale. More details of geographical features can be captured at grid scale than at county scale. (3) At both scales of analysis, we identified five ES bundles with different ecological functional characteristics and spatial patterns. We found that the Potential High-value Synergistic Bundle would shift to High-value Synergistic Bundle. Although the areas of the LA bundle increased from the grid scale to the county scale, there is less continuity. (4) The direction of the influence of the driving factor on ES is not constant in time, and the degree of the drivers’ impacts on the six ESs varies on the two scales. But NDVI was the main driver for most of the ESs. This study contributes to expanding our understanding of the relationships between ESs at different scales and could inform sustainable ecosystem management at multiple scales.

Abstract Natural killer (NK) cells, as innate lymphocytes, possess cytotoxic capabilities and engage target cells through a repertoire of activating and inhibitory receptors. Particularly, natural killer group 2, member D (NKG2D) receptor on NK cells recognizes stress‐induced ligands—the MHC class I chain‐related molecules A and B (MICA/B) presented on tumor cells and is key to trigger the cytolytic response of NK cells. However, tumors have developed sophisticated strategies to evade NK cell surveillance, which lead to failure of tumor immunotherapy. In this paper, we summarized these immune escaping strategies, including the downregulation of ligands for activating receptors, upregulation of ligands for inhibitory receptors, secretion of immunosuppressive compounds, and the development of apoptosis resistance. Then, we focus on recent advancements in NK cell immune therapies, which include engaging activating NK cell receptors, upregulating NKG2D ligand MICA/B expression, blocking inhibitory NK cell receptors, adoptive NK cell therapy, chimeric antigen receptor (CAR)‐engineered NK cells (CAR‐NK), and NKG2D CAR‐T cells, especially several vaccines targeting MICA/B. This review will inspire the research in NK cell biology in tumor and provide significant hope for improving cancer treatment outcomes by harnessing the potent cytotoxic activity of NK cells.

Cinnamyl alcohol dehydrogenase (CAD) plays a crucial role in lignin biosynthesis, and the gene family encoding various CAD isozymes has been cloned and characterized in numerous plant species. However, limited information regarding the CAD gene family in tobacco is currently available. In this study, we identified 10 CAD genes in Nicotiana tabacum, four in N. tomentosiformis, and six in N. sylvestris. The nucleotide and amino acid sequences of these tobacco CADs demonstrate high levels of similarity, whereas the putative protein sequences conservatively possessed two Zn2+ binding motifs and an NADP(H) cofactor binding motif. Both NtCAD1 and NtCAD2 had conservative substrate binding sites, similar to those possessed by bona fide CADs, and evidence from phylogenetic analysis as well as expression profiling supported their role as bona fide CADs involved in lignin biosynthesis. NtCAD1 has two paralogous genes, NtCAD1–1 and NtCAD1–2. Enzyme activity analysis revealed that NtCAD1–1 and NtCAD1–2 had a high affinity to coniferyl aldehyde, p-coumaryl aldehyde, and sinapyl aldehyde, whereas NtCAD2 preferred coniferyl aldehyde and p-coumaryl aldehyde as substrates. The kinetic parameter assay revealed that NtCAD1–2 functions as the most efficient enzyme. Downregulation of both NtCAD1–1 and NtCAD1–2 resulted in reddish-brown stems without significant changes in lignin content. Furthermore, NtCAD1–1, NtCAD1–2, and NtCAD2 showed distinct expression patterns in response to biotic and abiotic stresses, as well as different phytohormones. Our findings suggest that NtCAD1–1 and NtCAD1–2 are involved in lignin biosynthesis, with NtCAD1–2 also participating in both biological and abiotic stresses, whereas NtCAD2 plays a distinct role mainly in responding to biological and abiotic stresses in tobacco.

Individual tree detection and counting in unmanned aerial vehicle (UAV) imagery constitute a vital and practical research field. Vegetation remote sensing captures large-scale trees characterized by complex textures, significant growth variations, and high species similarity within the vegetation, which presents significant challenges for annotation and detection. Existing methods based on bounding boxes have struggled to convey semantics information about tree crowns. This paper proposes a novel deep learning network called VrsNet based on the density map information. The proposed work pioneers the segmentation and counting application by utilizing the semantic information of Gaussian contour. Besides, we sample and create the UAV vegetation remote sensing density dataset TreeFsc for experiments. In quantitative comparison across multiple datasets, the proposed method demonstrates high performance, with a 3.45 increase in MAE and a 4.75 increase in RMSE. Experiments demonstrate superior cross-region, cross-scale, and cross-species target detection capabilities of the proposed approach compared with the existing object detection methods. Our code and dataset are available at: https://github.com/luotiger123/VrsNet/tree/main/VrsNet.

Abstract Single-strand breaks are the major DNA damage in the genome and serve a crucial role in various biological processes. To reveal the significance of single-strand breaks, multiple sequencing-based single-strand break detection methods have been developed, which are costly and unfeasible for large-scale analysis. Hence, we propose SSBlazer, an explainable and scalable deep learning framework for single-strand break site prediction at the nucleotide level. SSBlazer is a lightweight model with robust generalization capabilities across various species and is capable of numerous unexplored SSB-related applications.

Pyran- and furanocoumarins are key representatives of tetrahydropyrans and tetrahydrofurans, respectively, exhibiting diverse physiological and medical bioactivities. However, the biosynthetic mechanisms for their core structures remain poorly understood. Here we combined multiomics analyses of biosynthetic enzymes in Peucedanum praeruptorum and in vitro functional verification and identified two types of key enzymes critical for pyran and furan ring biosynthesis in plants. These included three distinct P. praeruptorum prenyltransferases (PpPT1–3) responsible for the prenylation of the simple coumarin skeleton 7 into linear or angular precursors, and two novel CYP450 cyclases (PpDC and PpOC) crucial for the cyclization of the linear/angular precursors into either tetrahydropyran or tetrahydrofuran scaffolds. Biochemical analyses of cyclases indicated that acid/base-assisted epoxide ring opening contributed to the enzyme-catalyzed tetrahydropyran and tetrahydrofuran ring refactoring. The possible acid/base-assisted catalytic mechanisms of the identified cyclases were theoretically investigated and assessed using site-specific mutagenesis. We identified two possible acidic amino acids Glu303 in PpDC and Asp301 in PpOC as vital in the catalytic process. This study provides new enzymatic tools in the epoxide formation/epoxide-opening mediated cascade reaction and exemplifies how plants become chemically diverse in terms of enzyme function and catalytic process.

Abstract Heat-based local ablation techniques are effective treatments for specific oligometastatic and localized cancers and are being studied for their potential to induce immunogenic cell death and augment systemic immune responses to immunotherapies. The diverse technologies associated with thermal therapy have an unmet need for method development to enable device-specific experimentation, optimization, calibration and refinement of the parameter space to optimize therapeutic intent while minimizing side effects or risk to the patient. Quality assurance, training, or comparing thermal dose among different modalities or techniques using animal models is time and resource intensive. Therefore, the application and use of tissue mimicking thermosensitive, thermochromic liquid crystal and thermochromic paint phantom models may reduce costs and hurdles associated with animal use. Further, their homogenous composition may enable more precise assessment of ablative techniques. This review utilized SciFinder, Web of Science, PubMed and EMBASE to systematically evaluate the literature describing the background and applications of thermochromic liquid crystal, thermochromic paint and tissue-mimicking thermochromic phantoms used to characterize the thermal effects of ablation devices with a focus on facilitating their use across the medical device development life cycle. Graphical Abstract

Abstract Amino acid metabolism plays important roles in tumor biology and tumor therapy. Accumulating evidence has shown that amino acids contribute to tumorigenesis and tumor immunity by acting as nutrients, signaling molecules, and could also regulate gene transcription and epigenetic modification. Therefore, targeting amino acid metabolism will provide new ideas for tumor treatment and become an important therapeutic approach after surgery, radiotherapy, and chemotherapy. In this review, we systematically summarize the recent progress of amino acid metabolism in malignancy and their interaction with signal pathways as well as their effect on tumor microenvironment and epigenetic modification. Collectively, we also highlight the potential therapeutic application and future expectation.

The potential of organic-inorganic hybrid perovskites, owing to their distinct photoelectric attributes and boosted photoluminescence stability, has garnered substantial attention. Despite comprehensive examinations of the synthesis and optical characteristics of FAPbBr3 crystals, the understanding of their microstructure's implication on photoelectric applications, their electronic configuration, and electron-phonon interplay remains vague. In this study, we detailed the electronic configuration, phonon dispersion, and vibrational properties using density functional theory. We further calculated the formation enthalpy stability diagram. Characterization and calculation of the crystalline structure were accomplished via Rietveld refinement. Phonon dispersion curves, as well as total and partial phonon densities of states, were also calculated. The theoretical results align well with experimental Fourier infrared and Raman spectra. Beyond elementary characterization, we explored the photoelectric qualities of FAPbBr3 crystals, thereby reaffirming the outstanding photoelectric attributes and extensive application potential. A non-contact fixed-point lighting device was designed based on the principle of electromagnetic induction coils, which proved the uniformity of crystal luminescence. According to the first principle, FAPbBr3 possesses a Poisson ratio of 0.32, indicative of high flexibility, emphasizing their superb photoelectric characteristics and vast application scope.

Industrial microbes have become the core of biological manufacturing, which utilized as the cell factory for production of plenty of chemicals, fuels and medicine. However, the challenge that the extreme stress conditions exist in production is unavoidable for cell factory. Consequently, to enhance robustness of the chassis cell lays the foundation for development of bio-manufacturing. Currently, the researches on cell tolerance covered various aspects, involving reshaping regulatory network, cell membrane modification and other stress response. In fact, the strategies employed to improve cell robustness could be summarized into two directions, irrational engineering and rational engineering. In this review, the metabolic engineering technologies on enhancement of microbe tolerance to industrial conditions are summarized. Meanwhile, the novel thoughts emerged with the development of biological instruments and synthetic biology are discussed.

Abstract Identification of fossil species is crucial to evolutionary studies. Recent advances from deep learning have shown promising prospects in fossil image identification. However, the quantity and quality of labelled fossil images are often limited due to fossil preservation, conditioned sampling and expensive and inconsistent label annotation by domain experts, which pose great challenges to training deep learning‐based image classification models. To address these challenges, we follow the idea of the wisdom of crowds and propose a multiview ensemble framework, which collects Original (O), Grey (G) and Skeleton (S) views of each fossil image reflecting its different characteristics to train multiple base models, and then makes the final decision via soft voting. Experiments on the largest fusulinid dataset with 2400 images show that the proposed OGS consistently outperforms baselines (using a single model for each view), and obtains superior or comparable performance compared to OOO (using three base models for three the same Original views). Besides, as the training data decreases, the proposed framework achieves more gains. While considering the identification consistency estimation with respect to human experts, OGS receives the highest agreement with the original labels of dataset and with the re‐identifications of two human experts. The validation performance provides a quantitative estimation of consistency across different experts and genera. We conclude that the proposed framework can present state‐of‐the‐art performance in the fusulinid fossil identification case study. This framework is designed for general fossil identification and it is expected to see applications to other fossil datasets in future work. Notably, the result, which shows more performance gains as train set size decreases or over a smaller imbalance fossil dataset, suggests the potential application to identify rare fossil images. The proposed framework also demonstrates its potential for assessing and resolving inconsistencies in fossil identification.

Abstract Purpose To compare the genomic testing based on specimens obtained from percutaneous core-needle biopsy (CNB) before and immediately after coaxial microwave ablation (MWA) in solid non-small cell lung cancer (NSCLC), and to investigate the diagnostic performance of CNB immediately after coaxial MWA in solid NSCLC. Methods Coaxial MWA and CNB were performed for NSCLC patients, with a power of 30 or 40 watts (W) in MWA between the pre- and post-ablation CNB, followed by continuous ablation after the second CNB on demand. The paired specimens derived from the same patient were compared for pathological diagnosis and genomic testing. DNA/RNA extracted from the paired specimens were also compared. Results A total of 33 NSCLC patients with solid lesions were included. There were two patients (6.1%) without atypical cells and three patients (9.1%) who had the technical failure of genomic testing in post-ablation CNB. The concordance rate of pathological diagnosis between the twice CNB was 93.9% (kappa = 0.852), while that of genomic testing was 90.9% (kappa = 0.891). For the comparisons of DNA/RNA extracted from pre- and post-ablation CNB in 30 patients, no significant difference was found when the MWA between twice CNB has a power of 30 or 40 W and ablation time within five minutes (P = 0.174). Conclusions If the pre-ablation CNB presented with a high risk of pneumothorax or hemorrhage, the post-ablation CNB could be performed to achieve accurate pathological diagnosis and genomic testing and the maximum effect of ablation, which might allow for the diagnosis of genomic testing in 90.9% of solid NSCLC.

A new discretization technique is proposed for a three-dimensional (3D) tunnel face in weak strata with a random position in space. This method limits the angle, height, and thickness of the strata on the tunnel face. The original whole piece of soil is separated by a series of parallel planes, and two parallel planes are used as a stratum. Each radial discrete plane is separated when it passes through the strata, and the change in the soil properties of discrete points on the truncated plane is considered separately inside the strata. Considering the spatial and temporal characteristics of seismic waves, a pseudo-dynamic analysis of the tunnel face is carried out. The tunnel face active damage types under earthquake conditions are quantitatively analyzed, and the corresponding support pressure design diagrams are given for the case without weak strata. For the case containing weak strata, the presence of weak strata can have adverse effects on the face. The failure mechanism of the weak strata is given by the discretization method. For different friction angles, the presence of the weak strata changes the friction angles of the soils. For the thickness, location and angle of the weak strata, the variation in the support pressure is given in this paper. To more intuitively depict the change in the failure mechanism in the presence of weak strata, the change in the failure mechanism under different thicknesses and weaknesses of weak strata is plotted.

The photoelectric field has witnessed notable progress with the emergence of perovskite quantum dots. However, their practical utility is constrained by their susceptibility to degradation and malfunction when exposed to external environmental factors like light, heat, and humidity. To overcome these limitations, a potential solution lies in the growth of perovskite quantum dots within glasses, leveraging the dense network structure of inorganic glasses to achieve a seamless encapsulation of the quantum dots. This approach effectively addresses the challenges of quantum dot stability and the risk of lead contamination by isolating the quantum dots from the external environment. This study utilizes an in situ nanocrystallization approach to cultivate CsPbBr3 perovskite quantum dots within a matrix of glasses. The resulting CsPbBr3 perovskite quantum dots glasses (CsPbBr3 PQDs@glasses) demonstrate a vibrant green emission due to exciton recombination radiation. The investigation focused on the luminescent characteristics of CsPbBr3 PQDs@glasses subjected to pressures ranging from 0 to 7 GPa, which resulted in a significant red shift in the spectra, transitioning from 519 nm to 525 nm. Electronic structure, dispersion and vibrational properties of CsPbBr3 was investigated under varying pressure conditions through the utilization of first-principles methods. Furthermore, an examination of the pressure distribution within the diamond anvil cells was conducted from a macroscopic perspective employing the finite element method. Subsequently, contactless underwater electroluminescence devices incorporating CsPbBr3 PQDs@glasses were devised, employing the principle of electromagnetic induction. This study offers essential insights into the physics of perovskite materials subjected to high pressure, thereby establishing a groundwork for prospective applications.

Simultaneous localization and mapping (SLAM) is a hot research area that is widely required in many robotics applications. In SLAM technology, it is essential to explore an accurate and efficient map model to represent the environment and develop the corresponding data association methods needed to achieve reliable matching from measurements to maps. These two key elements impact the working stability of the SLAM system, especially in complex scenarios. However, previous literature has not fully addressed the problems of efficient mapping and accurate data association. In this article, we propose a novel hash multi-scale (H-MS) map to ensure query efficiency with accurate modeling. In the proposed map, the inserted map point will simultaneously participate in modeling voxels of different scales in a voxel group, enabling the map to represent objects of different scales in the environment effectively. Meanwhile, the root node of the voxel group is saved to a hash table for efficient access. Secondly, considering the one-to-many (1 ×103 order of magnitude) high computational data association problem caused by maintaining multi-scale voxel landmarks simultaneously in the H-MS map, we further propose a bidirectional matching algorithm (MSBM). This algorithm utilizes forward–reverse–forward projection to balance the efficiency and accuracy problem. The proposed H-MS map and MSBM algorithm are integrated into a completed LiDAR SLAM (HMS-SLAM) system. Finally, we validated the proposed map model, matching algorithm, and integrated system on the public KITTI dataset. The experimental results show that, compared with the ikd tree map, the H-MS map model has higher insertion and deletion efficiency, both having O(1) time complexity. The computational efficiency and accuracy of the MSBM algorithm are better than that of the small-scale priority matching algorithm, and the computing speed of the MSBM achieves 49 ms/time under a single CPU thread. In addition, the HMS-SLAM system built in this article has also reached excellent performance in terms of mapping accuracy and memory usage.

Abstract The Karakoram fault (KKF) is an important strike‐slip boundary for accommodating deformation following the India‐Asia collision. However, whether the deformation is confined to the crust or whether it extends into the mantle remains highly debated. Here, we show that the KKF is overwhelmingly dominated by crustal degassing related to a 4He‐ and CO2‐rich fluid reservoir (for example, He contents up to ∼1.0–1.6 vol.%; 3He/4He = 0.027 ± 0.013 RA (1σ, n = 47); CO2/N2 up to 3.7–57.8). Crustal‐scale active deformation driven by strike‐slip faulting could mobilize 4He and CO2 from the fault zone rocks, which subsequently accumulate in the hydrothermal system. The KKF may have limited fluid connections to the mantle, and if any, the accumulated crustal fluids would efficiently dilute the uprising mantle fluids. In both cases, crustal deformation is evidently the first‐order response to strike‐slip faulting.

BackgroundsOral squamous cell carcinoma is a malignant tumor of the head and neck, and its molecular mechanism remains to be explored.MethodsBy analyzing the OSCC data from the TCGA database, we found that SLC2A3 is highly expressed in OSCC patients. The expression level of SLC2A3 was verified by RT-PCR and western blotting in OSCC cell lines. The function of SLC2A3 in OSCC cell lines and Lactic acid in SLC2A3-knockdown OSCC cells were detected by colony formation, CCK8, transwell, and wound healing assays. The effect of SLC2A3 on tumor growth and metastasis was tested in vivo. GSEA and Western blot were used to analyze and validate tumor phenotypes and signaling pathway molecules.ResultsWe analyzed OSCC datasets in the TCGA database and found that SLC2A3 had abnormally high expression and was associated with poor prognosis. We also found that oral squamous cell carcinoma cells had increased proliferation, migration, invasion, EMT phenotype, and glycolysis due to SLC2A3 overexpression. Conversely, SLC2A3 knockdown had the opposite effect. Our in vivo experiments confirmed that SLC2A3 overexpression promoted tumor growth and metastasis while knockdown inhibited it. We also observed that high SLC2A3 expression led to EMT and the activation of the TGF-β signaling pathway, while knockdown inhibited it. Interestingly, exogenous lactic acid restored the EMT, proliferation, migration, and invasion abilities of oral cancer cells inhibited by knocking down SLC2A3.ConclusionsOur study reveals that SLC2A3 expression was up-regulated in OSCC. SLC2A3 activates the TGF-β signaling pathway through lactic acid generated from glycolysis, thus regulating the biological behavior of OSCC.

The rapid spread of oil pollution owing to river flow has vast consequences for human activities and ecosystems within the affected river basin. In the context of the profound impact of oil spills on river basins, an integrated riverine oil spill impact assessment framework is proposed. The framework combines a risk-matrix approach with an oil trajectory model and the environmental sensitivity index (ESI) methodology to estimate the impact level of the affected river basin. The framework was applied in simulation to the middle reaches of the Nenjiang River, China, to evaluate the impact of a hypothetical oil spill accident during different seasons. Our findings revealed similar propagation trends of the oil and impact level maps during normal water and flood seasons, largely owing to the regulating function of a downstream dam. Specifically, the oil front edge spread over 2 km/h along the initial 30-km downstream segment in normal water and flood seasons, and the speed slowed to 1.2 km/h in the dry season. The length of the polluted river during normal water and flood seasons was approximately 1.4 times that in the dry season, with contaminated zone lengths averaging 0.45, 0.61, and 0.82 km in the dry, normal water, and flood seasons, respectively. The output impact-level maps, which highlight the severely affected areas over time after the spill, are especially useful for decision makers. This framework is shown to be a valuable tool for quantitatively evaluating the dynamic impacts that a river basin may face following an oil spill, and is particularly useful for facilitating the initial emergency response.

Ethnopharmacological relevance: Pearl oyster (Pinctada martensii) is used in Chinese traditional medicine use in photoprotective, anti-inflammatory, and wound treatment.Aim of the study: This study explored whether the mucus protein of Pearl oyster (protein of Pinctada martensii, PMP) affects human skin fibroblast (HSF) proliferation, migration, collagen-related gene expression related to collagen formation, and in vivo healing effects. Materials and methods: The PMP component was analyzed by LC-MS/MS. The cell viability was evaluated using a CCK-8 kit. The expression genes were measured by reverse transcription polymerase chain reaction. A full-thickness excisional wounding model in Sprague-Dawley (SD) rats was used to test the repairing effect of PMP in vivo, and Hematoxylin-Eosin (H&E) and Masson's Trichrome staining were applied to evaluate skin structure. Results: The components of PMP were identified using LC-MS/MS proteomics, and a total of 3023 proteins were detected. The results of PMP-treated HSF showed that PMP effectively promoted cell proliferation by 1.6-fold and cell migration by 1.5-fold at a concentration of 1 mg/mL. Additionally, PMP treatment up-regulated the expression levels of collagen-related genes COL1A1, COL3A1, and MMP-1 in fibroblasts. Furthermore, PMP was applied in the therapy of full-thickness excisional wounds in rats. The results demonstrated that PMP significantly accelerated wound healing time, resulted in the recovery of dermal and epithelial thickness, and stimulated collagen regeneration. The regenerated skin closely resembled the structure of normal skin. Conclusions: These findings provide solid evidence supporting the potential of PMP as a promising candidate for the treatment of skin wounds.

Based on 2013–2019 panel data covering 31 provinces and cities in China, this paper uses the entropy weight technique for order of preference by similarity to ideal solution (TOPSIS) method to measure rural common prosperity (CP). Based on the global and local Moran's I methods, we analyze the dynamic evolutionary characteristics of China's rural CP and the regional differences. Additionally, we use the necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) methods to explore how six antecedents at the technology-organization-environment (TOE) level interact to affect CP. This research finds that, first, China's rural CP showed a fluctuating upward trend, with the highest level of CP in rural areas in the eastern region, followed by the central and western regions. Additionally, the gap between the three gradually narrowed. Second, China's rural CP had ''high-high'' and ''low-low'' agglomeration characteristics, with positive spatial autocorrelation, no transition changes, and strong spatial stability. Third, individual digital economic elements and organizational and environmental elements were not necessary conditions for promoting rural CP. Fourth, the multiple concurrent factors of the digital economy, organizations and the environment constituted three diversified configurations of rural CP, showing that the driving path of rural CP was characterized by ''different paths that lead to the same goal”. Moreover, ''perfect digital facilities'' and ''high entrepreneurial activity'' had a universal role in promoting rural CP. The conclusions of this research hold important theoretical and practical significance for improving China's rural CP.

Background: Chronic rhinosinusitis (CRS) is a complex chronic inflammatory disease of the nose, paranasal sinus, and upper respiratory tract. Its treatment methods mainly include antibiotic treatment and surgical treatment. However, the molecular mechanism of its inflammation is still unclear. Pyroptosis is a programmed cell death. As an important natural immune response, pyroptosis plays an essential role in fighting infection. Methods: In this paper, a weighted co-expression network (WGCNA) was used to screen gene modules significantly related to CRS. Then it intersects with the genes related to scorching death (PRGs). We evaluated the immune landscape of CRS by the expression of intersecting genes. In addition, in the enrichment analysis of intersection genes and PPI network analysis, we verified the pathways closely related to CRS and hub genes. Finally, the interaction network between the hub gene, miRNA, and TF was constructed. In this paper, qRT-qPCR technology was also used to detect the hub gene related to CRS. Results: Hub genes (CASP3, IL18, NAIP, NLRC4, and TP53) found in this paper are directly or indirectly related to CRS, and these genes were proved to be of diagnostic significance to CRS by ROC curve and qRT-qPCR vertification. In the infiltration abundance of CRS and its control group, the infiltration abundance of Plasma cells, T cells follicular helper, Macrophages M2, Dendritic cells activated, and Neutrophils cells in the two groups were significantly different. We also constructed the interaction network between the hub genes and miRNAs and the interaction network between hub genes and TFs. Most of these miRNAs and TFs were also related to CRS. Conclusions: With the help of the WGCNA and PPI analysis, our results provide a better understanding of the role of biomarkers CASP3, IL18, NAIP, NLRC4, and TP53 in the development of CRS and provide a research basis for the mining of biomarkers related to the diagnosis and treatment of CRS.

Peanut pod shape is a heritable trait which affects the market acceptance of in-shell peanut products. In order to determine the genetic control of pod shape, six component traits of pod shape (pod length, pod width, pod length/width ratio, pod roundness, beak degree and constriction degree) were measured using an image-based phenotyping method. A recombinant inbred line (RIL) population consisting of 181 lines was phenotyped across three environments. Continuous distributions and transgressive segregations were demonstrated in all measured traits and environments. Significant correlations were found among most component traits with broad-sense heritability ranging from 0.87 to 0.95. Quantitative trait locus (QTL) analysis yielded 26 additive QTLs explaining 3.79 to 52.37% phenotypic variations. A novel, stable and major QTL region conditioning multiple shape features was detected on chromosome 2, which spans a 10.81-Mb genomic region with 543 putative genes. Bioinformatics analysis revealed several candidate genes in this region. In addition, 73 pairs of epistatic interactions involving 92 loci were identified for six component traits explaining 0.94–6.45% phenotypic variations. These results provide new genetic loci to facilitate genomics-assisted breeding of peanut pod shape.

The establishment of government investment funds serves as a crucial measure for governments at all levels to leverage their certification role and financial resources in attracting social capital to support enterprise development. This paper empirically examines the guiding certification effect and governance supervision effect of government investment funds on enterprise value enhancement, utilising panel data from listed companies and government investment fund investment event data spanning the period from 2011 to 2021. The research findings reveal that government investment funds significantly enhance the value of recipient enterprises. By leveraging their guidance and certification effects and governance supervision effects, these funds alleviate financing constraints, actively participate in corporate governance, and ultimately enhance corporate value. The impact of government investment funds is negatively moderated by the age and size of the enterprise, indicating that the “invest in early-stage and small businesses” investment strategy yields better results in promoting value enhancement. Furthermore, heterogeneity analysis demonstrates that government investment funds have a more pronounced impact on the value of non-heavily polluting industries, enterprises located in the eastern and southern regions of China, and non-state-owned enterprises. This article expands the research scope of government investment funds at the micro level, providing empirical evidence and theoretical support for optimising government investment funding policies and fostering the development of a modern capital market with distinctive Chinese characteristics.

Chaperonin containing tailless complex polypeptide 1 (CCT) is a molecular chaperone protein that consists of eight completely different subunits and assists in the folding of newly synthesized peptides. The zeta subunit of CCT is a regulatory factor for the folding and assembly of cytoskeletal proteins as individuals or complexes. In this study, the zeta subunit of Nosema bombycis (NbCCTζ) is identified for the first time. The complete ORF of the NbCCTζ gene is 1533 bp in length and encodes a 510 amino acid polypeptide. IFA results indicate that NbCCTζ is colocalized with actin and β-tubulin in the cytoplasm during the proliferative phase and that NbCCTζ is completely colocalized with NbCCTα in the cytoplasm of N. bombycis throughout the entire life cycle. Furthermore, the yeast two-hybrid assay revealed that the NbCCTζ interacts with NbCCTα. The transcriptional level of NbCCTζ is significantly downregulated by knocking down the NbCCTα gene, while the transcriptional level of NbCCTα is downregulated after knocking down the NbCCTζ gene. These results suggest that NbCCTζ may play a vital role in the proliferation of N. bombycis by coordinating with NbCCTα.

Image-guided liver biopsies can improve their success rate when combined with the optical detection of Indocyanine Green (ICG) fluorescence accumulated in tumors. Previous works used a camera coupled to a thin borescope to capture and quantify images from fluorescence emission during procedures; however, light-scattering prevented the formation of sharp images, and the time response for weakly fluorescent tumors was very low. Instead, replacing the camera with a photodiode detector shows an improved temporal resolution in a more compact and lighter device. This work presents the new design in a comparative study between both detection technologies, including an assessment of the temporal response and sensitivity to the presence of background fluorescence.

Magnetically manipulated interventional robotic systems offer outstanding advantages for improving vascular interventions, including minimizing radiation exposure to physicians and increasing the controllability of magnetic interventional devices in hard‐to‐reach vessels. However, automatic control of magnetic guidewires (MGs) is still challenging in terms of modeling of guidewires and trajectory planning. Herein, a magnetically controlled guidewire robotic system (MCGRS) with steering and propulsion capabilities is proposed based on adequate modeling and trajectory planning methods. The steering kinematics of MG is first modeled by constant curvature theory. Then, a continuum mechanics model is built to predict the deformation of the magnetic tip by combining the dipole model and the Cosserat‐rod model. Moreover, a trajectory planning algorithm is developed to navigate the MG through vessels. Furthermore, trajectory following experiments within three vascular phantoms confirm that the proposed model and algorithm are reliable and capable of navigating the MG through the desired trajectory. Finally, two extra navigation experiments are implemented in 3D vascular phantom, which show that the MCGRS can be remotely controlled to manipulate the MG to actively steer and reach the target site. The system and methods will build the foundation for automatic control of MG and help to improve the autonomy.

Land disturbance (LD), commonly reflecting anthropogenic-induced land surface changes, has received unprecedented attention due to its contribution to achieving Sustainable Development Goal 15: life on land. Considerable LD in China, such as urban sprawl, farmland expansion and forest loss, have resulted in a spectrum of environmental problems in recent decades. To present function-based solutions to mitigate LD, the “productive-living-ecological” system (PLES) theory released by China’s government is more conducive to investigating LD and supporting plan-makers concerning regional territorial spatial planning. Currently, there is a relative lack of attention to LD studies in China’s mountainous areas. Hence, we selected the western Sichuan urban agglomeration (WSUA), a typical mountainous-hills urban agglomeration, as the study area, and presented a work that investigates the tempo-spatial dynamics of LD from 2000 − 2020, based on the PLES theroy and an interdisciplinary LD assessment framework of “process-structures” in WSUA. Finally, the contribution of the driving factors system, including geophysical, economic, and social, was investigated using a spatially geo-detector and bivariate Moran's I methodologies. In this work, we found the remarkable living land sprawl, and the productive-ecological and ecological land showed a dramatic decline trend, with a total 21,845.2 ha decline from 2000 to 2020 in WSUA. Although an encouraging increase in ecological land has been observed after 2010 with a total of 220,650 ha, urban sprawl has offset ecological restoration efforts. The LD hotspot patterns in SWUA were categorized into four types, which have led to general fragmentation of PLES land, and mainly clustering under 14° slope due to the scarcity of suitable land resources. In addition, we found that the geophysical driving force also significantly influences LD in mountains urban compared with the socioeconomic pillars. Finally, we provided SWUA’s plan-makers with recommendations and spatial solutions programs for harmonizing the PLES land disturbance and achieving sustainable development.

Action recognition is a fundamental research topic in the field of video understanding, but classical action recognition relies on a large amount of manually annotated video data, which limits its development. Small sample action recognition is a promising topic that can overcome the dependence on large-scale annotated data. However, the current small sample action recognition has a series of shortcomings such as temporal singularity and a lack of perception of global information. Therefore, this work proposes an interactive perception network by designing a multi-scale temporal feature extraction module to capture global temporal dependencies between all frames and local temporal information between frames. Then the algorithm proposes a cross scale matching strategy to achieve robust matching between videos with different motion speeds, maximizing the consistency between local and global features of the same type of action. Finally, the experimental results on the SSV2 dataset and the HMDB51 dataset show that the proposed method outperforms the current mainstream methods. Compared with the backbone network, which is the most advanced method of ResNet, this method achieved performance improvements of 0.8% and 0.4% on HMDB51 and SSV2, respectively.

This article focuses on the resilient event-triggered $H_{\infty }$ control for networked control systems (NCSs) against external disturbances and network constraints on communication delays, efficiency, and attacks. First, a resilient event-based mechanism is presented considering the consequences of the DoS attacks disruption, where resilience refers to the tolerance of the attack behavior during data triggering. Then, the studied system is integrated into a class of switching time-delay systems, and a series of sufficient conditions are derived to ensure the internally exponential stability of the system and to design the resilient event-triggered $H_{\infty }$ controllers. Particularly, the relationship between attack periods, network-induced delays, and decay coefficients is identified, which potentially forms an early warning of attacks. Finally, the effectiveness of the proposed methods is examined through application to a networked offshore structure system.

Abstract Background Itaconic acid, an unsaturated C5 dicarbonic acid, has significant market demand and prospects. It has numerous biological functions, such as anti-cancer, anti-inflammatory, and anti-oxidative in medicine, and is an essential renewable platform chemical in industry. However, the development of industrial itaconic acid production by Aspergillus terreus, the current standard production strain, is hampered by the unavoidable drawbacks of that species. Developing a highly efficient cell factory is essential for the sustainable and green production of itaconic acid. Results This study employed combinatorial engineering strategies to construct Escherichia coli cells to produce itaconic acid efficiently. Two essential genes (cis-aconitate decarboxylase (CAD) encoding gene cadA and aconitase (ACO) encoding gene acn) employed various genetic constructs and plasmid combinations to create 12 recombination E. coli strains to be screened. Among them, E. coli BL-CAC exhibited the highest titer with citrate as substrate, and the induction and reaction conditions were further systematically optimized. Subsequently, employing enzyme evolution to optimize rate-limiting enzyme CAD and synthesizing protein scaffolds to co-localize ACO and CAD were used to improve itaconic acid biosynthesis efficiency. Under the optimized reaction conditions combined with the feeding control strategy, itaconic acid titer reached 398.07 mM (51.79 g/L) of engineered E. coli BL-CAR470E-DS/A-CS cells as a catalyst with the highest specific production of 9.42 g/g(DCW) among heterologous hosts at 48 h. Conclusions The excellent catalytic performance per unit biomass shows the potential for high-efficiency production of itaconic acid and effective reduction of catalytic cell consumption. This study indicates that it is necessary to continuously explore engineering strategies to develop high-performance cell factories to break through the existing bottleneck and achieve the economical commercial production of itaconic acid.

The authors present a wearable photoacoustic patch, which integrates laser diodes and piezoelectric transducers for three-dimensional imaging of hemoglobin and temperature in deep tissues.

Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits auxiliary torque and is connected to the upper limb by bypassing the shoulder. Based on the K-nearest neighbors (KNN) algorithm and integrated fuzzy PID control strategy, the ULE identifies the handling posture and provides accurate active auxiliary force automatically. Overall, it has the quality of being light and easy to wear. In unassisted mode, the wearer’s upper limbs minimally affect the range of movement. The KNN algorithm uses multi-dimensional motion information collected by the sensor, and the test accuracy is 94.59%. Brachioradialis muscle (BM), triceps brachii (TB), and biceps brachii (BB) electromyogram (EMG) signals were evaluated by 5 kg, 10 kg, and 15 kg weight conditions for five subjects, respectively, during lifting, holding, and squatting. Compared with the ULE without assistance and with assistance, the average peak values of EMG signals of BM, TB, and BB were reduced by 19–30% during the whole handling process, which verified that the developed ULE could provide practical assistance under different load conditions.

This study introduces a novel deep learning network that integrates a single-layer bidirectional long short-term memory (Bi-LSTM) network with a coding layer to analyze the hot deformation behavior of various alloys. The single-layer Bi-LSTM model adeptly predicts experimental stress–strain curves obtained under different deformation temperatures and strain rates, demonstrating superior effectiveness and excellent performance in modeling hot deformation behaviors of the FGH98 nickel-based alloy and TiAl intermetallic alloy. The present model achieves the coefficient of determination of 0.9051 for FGH98 and 0.9307 for TiAl alloys, whereas the corresponding values of 0.8105 and 0.8356 are obtained by the conventional strain-compensated Sellars constitutive equation (SCS model). Additionally, the mean absolute percentage error of the single-layer Bi-LSTM model are 11.37% for FGH98 and 7.16% for TiAl alloys, while the SCS model gains the corresponding error of 15.29% and 17.01%. These results show that the present model has enhances the predictive accuracy exceeding 10% for both FGH98 and TiAl alloys over the SCS model. Consequently, the proposed single-layer Bi-LSTM model provides substantial potential for optimizing manufacturing processes and improving material properties.

Arctic navigation faces numerous challenges, including uncertain ice conditions, rapid weather changes, limited communication capabilities, and lack of search and rescue infrastructure, all of which increase the risks involved. According to an Arctic Council statistical report, a remarkable 2638 maritime accidents were recorded in Arctic waters between 2005 and 2017, showing a fluctuating upward trend. This study collected and analyzed ship accident data in Arctic waters to identify the various accident scenarios and primary risk factors that impact Arctic navigation safety. By utilizing data-driven algorithms, a model for predicting ship navigation accidents in Arctic waters was constructed, providing an in-depth understanding of the risk factors that make accidents more likely. The research findings are of practical significance for enhancing quantitative risk assessment, specifically focusing on the navigational risks in Arctic waters. The results of this study can assist maritime authorities and shipping companies in conducting risk analysis and implementing accident prevention measures for safe navigation in Arctic waters.

The autonomous shipping industry is increasingly focusing on enhancing the safety and reliability of software-based systems. Conducting a risk assessment is a requirement for demonstrating the safety equivalence of autonomous ships based on such systems to conventional vessels. Traditional risk assessment models, however, primarily focus on hardware failures, often overlooking potential software-related failures and functional inadequacies. This study proposes a framework integrating Software Failure Mode and Effects Analysis (FMEA), System–Theoretic Process Analysis (STPA), and Bayesian Network (BN) for risk identification of autonomous ship software systems. The results of a case study reveal that the framework sufficiently addresses the multifaceted nature of risks related to software in autonomous ships. Based on the findings of this study, we suggest the need for standardization of software architecture development in the autonomous ship industry and highlight the necessity for an enhanced understanding of AI-specific risks and the development of tailored risk assessment methodologies.

Purpose – With the Chinese marine economy developing rapidly, the environmental problem has been occurring frequently, which needs green finance that supports energy conservation, environmental protection, and sustainable development to solve. Design/methodology/approach – In this paper, the entropy method is used to measure the development level of green finance, the DEA-ML index is used to measure the green total factor productivity which is used to indicate the high-quality development level of the marine economy in 11 coastal provinces (cities), then the grey correlation degree between them whose result shows that there is a certain correlation between the two variables is calculated. The fixed-effect model was used to analyze the relationship between them. Findings – The results show that the development level of green finance can promote the high-quality development of the marine economy, but there are still some problems in the process of green finance supporting the marine economy. Originality/value – This paper seeks new growth drivers, green finance, for the high-quality development of the marine economy, which few scholars have studied.

Abstract Background Polyamide (nylon) is an important material, which has aroused plenty of attention from all aspects. PA 5.4 is one kind of nylon with excellent property, which consists of cadaverine and succinic acid. Due to the environmental pollution, bio-production of cadaverine and succinic acid has been more attractive due to the less pollution and environmental friendliness. Microbes, like Escherichia coli, has been employed as cell factory to produce cadaverine and succinic acid. However, the accumulation of cadaverine will cause severe damage on cells resulting in inhibition on cell growth and cadaverine production. Herein, a novel two stage co-production of succinic acid and cadaverine was designed based on an efficient thermos-regulated switch to avoid the inhibitory brought by cadaverine. Results The fermentation process was divided into two phase, one for cell growth and lysine production and the other for cadaverine and succinic acid synthesis. The genes of ldhA and ackA were deleted to construct succinic acid pathway in cadaverine producer strain. Then, a thermal switch system based on pR/pL promoter and CI857 was established and optimized. The fermentation conditions were investigated that the optimal temperature for the first stage was determined as 33 ℃ and the optimal temperature for the second stage was 39 ℃. Additionally, the time to shifting temperature was identified as the fermentation anaphase. For further enhance cadaverine and succinic acid production, a scale-up fermentation in 5 L bioreactor was operated. As a result, the titer, yield and productivity of cadaverine was 55.58 g/L, 0.38 g/g glucose and 1.74 g/(L·h), respectively. 28.39 g/L of succinic acid was also obtained with yield of 0.19 g/g glucose. Conclusion The succinic acid metabolic pathway was constructed into cadaverine producer strain to realize the co-production of succinic acid and cadaverine. This study provided a novel craft for industrial co-production of cadaverine and succinic acid.

The street trees coverage ratio provides reliable data support for urban ecological environment assessment, which plays an important part in the ecological environment index calculation. Aiming at the statistical estimation of urban street trees coverage ratio, an integrated model based on YOLOv4 and Unet network for detecting and extracting street trees from remote sensing images is proposed, and obtain the estimated street trees coverage ratio in images accurately. The experiments are carried out under self-made dataset, and the results show that the accuracy of street trees detection is 94.91%, and the street trees coverage ratio is 16.30% and 13.81% in the two experimental urban scenes. The MIoU of contour extraction is 98.25%, and the estimated coverage accuracy is improved by 6.89% and 5.79%, respectively. The result indicates that the proposed model achieves the automation of contour extraction of street trees and more accurate estimation of street trees coverage ratio.

Engineering metals often suffer from a small elastic deformation with a linear stress-strain relationship obeying Hooke’s law. Here the authors observe a large nonlinear tensile elastic deformation with a strain of >4.3% in a bulk Cu alloy that offers potential for elastic strain engineering.

Abstract Gestational diabetes mellitus (GDM) is the most common disease in pregnancy and can cause a series of maternal and infant complications. A new study shows that GDM affects one in six deliveries. Identifying and screening for risk factors for GDM can effectively help intervene and improve the condition of women and their children. Therefore, the aim of this paper is to determine the risk factors for GDM and to use the ensemble learning method to judge whether pregnant women suffer from GDM more accurately. First, this study involves six commonly used machine learning algorithms to analyze the GDM data from the Tianchi competition, selects the risk factors according to the ranking of each model, and uses the Shapley additive interpreter method to determine the importance of the selected risk factors. Second, the combined weighting method was used to analyze and evaluate the risk factors for gestational diabetes and to determine a group of important factors. Lastly, a new integrated light gradient-boosting machine-extreme gradient boosting-gradient boosting tree (LightGBM-Xgboost-GB) learning method is proposed to determine whether pregnant women have gestational diabetes mellitus. We used the gray correlation degree to calculate the weight and used a genetic algorithm for optimization. In terms of prediction accuracy and comprehensive effects, the final model is better than the commonly used machine learning model. The ensemble learning model is comprehensive and flexible and can be used to determine whether pregnant women suffer from GDM. In addition to disease prediction, the model can also be extended for use to many other areas of research.

Enterococcus faecium is sometimes used in food production; however, its acquisition of antibiotic resistance has become an alarming health concern. The E. lactis species is closely related to E. faecium and has good probiotic potential. This study aimed to investigate the antibiotic resistance of E. lactis. We analyzed the antibiotic resistance phenotype and whole-genome sequences of 60 E. lactis isolates (23, 29, and 8 isolates from dairy products, Rice wine Koji, and human feces, respectively). These isolates showed varying degree of resistance to 13 antibiotics, and were sensitive to ampicillin and linezolid. The E. lactis genomes carried only a subset of commonly reported antibiotic resistance genes (ARGs) in E. faecium. Five ARGs were detected across the investigated E. lactis, including two universally present genes (msrC and AAC(6′)-Ii) and three rarely detected ARGs (tet(L), tetM, and efmA). To identify other undescribed antibiotic resistance-encoding genes, a genome-wide association study was performed, returning 160 potential resistance genes that were associated with six antibiotics, namely chloramphenicol, vancomycin, clindamycin, erythromycin, quinupristin-dalfopristin, and rifampicin. Only around one-third of these genes encode known biological functions, including cellular metabolism, membrane transport, and DNA synthesis. This work identified interesting targets for future study of antibiotic resistance in E. lactis. The fact that the lower number of ARGs present in E. lactis supports that it may be an alternative to E. faecalis for use in the food industry. Data generated in this work is of interest to the dairy industry.