Search

Abstract We propose a novel miniaturized optical attenuator based on the evanescent-field coupling between two nanofibers. Benefiting from a wavelength-dependent waveguiding property of the coupled structure, a tunable attenuation with maximum extinction ratio of ~ 20 dB is demonstrated with an ultrawide optical bandwidth up to 0.7 μm in experiment. The wavelength-depended waveguiding properties of both one single nanofiber and coupled nanofibers are investigated in both theory and simulation. Using an adiabatic coupling structure, an attenuation range from − 0.16 dB to − 18.46 dB is obtained within a spectrum from 1.2 μm to 1.7 μm experimentally. Moreover, the simulated results indicate that, the attenuation only shows a slight change of ~ 0.1 dB with a lateral misalignment of 0.5 μm between the two nanofibers, indicating a high tolerance of this attenuator to the lateral misalignment. Considering the wide bandwidth as well as the ultracompact structure, this attenuator shows high potential in applications such as all-fiber optical sensing and communicating.

Abstract ezSingleCell is an interactive and easy-to-use application for analysing various single-cell and spatial omics data types without requiring prior programing knowledge. It combines the best-performing publicly available methods for in-depth data analysis, integration, and interactive data visualization. ezSingleCell consists of five modules, each designed to be a comprehensive workflow for one data type or task. In addition, ezSingleCell allows crosstalk between different modules within a unified interface. Acceptable input data can be in a variety of formats while the output consists of publication ready figures and tables. In-depth manuals and video tutorials are available to guide users on the analysis workflows and parameter adjustments to suit their study aims. ezSingleCell’s streamlined interface can analyse a standard scRNA-seq dataset of 3000 cells in less than five minutes. ezSingleCell is available in two forms: an installation-free web application ( https://immunesinglecell.org/ezsc/ ) or a software package with a shinyApp interface ( https://github.com/JinmiaoChenLab/ezSingleCell2 ) for offline analysis.

Abstract The alteration of metabolic processes has been found to have significant impacts on the development of hepatocellular carcinoma (HCC). Nevertheless, the effects of dysfunction of tyrosine metabolism on the development of HCC remains to be discovered. This research demonstrated that tyrosine hydroxylase (TH), which responsible for the initial and limiting step in the bio-generation of the neuro-transmitters dopamine and adrenaline, et al. was shown to be reduced in HCC. Increased expression of TH was found facilitates the survival of HCC patients. In addition, decreased TH indicated larger tumor size, much more numbers of tumor, higher level of AFP, and the presence of cirrhosis. TH effectively impairs the growth and metastasis of HCC cells, a process dependent on the phosphorylation of serine residues (S19/S40). TH directly binds to Smad2 and hinders the cascade activation of TGFβ/Smad signaling with the treatment of TGFβ1. In summary, our study uncovered the non-metabolic functions of TH in the development of HCC and proposes that TH might be a promising biomarker for diagnosis as well as an innovative target for metastatic HCC.

Abstract Optimal integration of transcriptomics data and associated spatial information is essential towards fully exploiting spatial transcriptomics to dissect tissue heterogeneity and map out inter-cellular communications. We present SEDR, which uses a deep autoencoder coupled with a masked self-supervised learning mechanism to construct a low-dimensional latent representation of gene expression, which is then simultaneously embedded with the corresponding spatial information through a variational graph autoencoder. SEDR achieved higher clustering performance on manually annotated 10 × Visium datasets and better scalability on high-resolution spatial transcriptomics datasets than existing methods. Additionally, we show SEDR’s ability to impute and denoise gene expression (URL: https://github.com/JinmiaoChenLab/SEDR/ ).

This paper introduces a broadband triple-pole triple-throw (3P3T) RF MEMS switch with a frequency range from DC to 380 GHz. The switch achieves precise signal control and efficient modulation through its six-port design. It achieves an insertion loss of −0.66 dB across its frequency range, with isolation and return loss metrics of −32 dB and −15 dB, respectively. With its low actuation voltage of 6.8 V and rapid response time of 2.28 μs, the switch exemplifies power-efficient and prompt switching performance. The compact design is ideal for integration into space-conscious systems. This switch is pivotal for 6G research and has potential applications in satellite communications, military radar systems, and next-generation radio applications that require multi-antenna access.

Limited resources for edge computing platforms in airborne and spaceborne imaging payloads prevent using complex image processing models. Model pruning can eliminate redundant parameters and reduce the computational load, enhancing processing efficiency on edge computing platforms. Current challenges in model pruning for remote-sensing object detection include the risk of losing target features, particularly during sparse training and pruning, and difficulties in maintaining channel correspondence for residual structures, often resulting in retaining redundant features that compromise the balance between model size and accuracy. To address these challenges, we propose the L1 reweighted regularization (L1RR) pruning method. Leveraging dynamic and self-adaptive sparse modules, we optimize L1 sparsity regularization, preserving the model’s target feature information using a feature attention loss mechanism to determine appropriate pruning ratios. Additionally, we propose a residual reconstruction procedure, which removes redundant feature channels from residual structures while maintaining the residual inference structure through output channel recombination and input channel recombination, achieving a balance between model size and accuracy. Validation on two remote-sensing datasets demonstrates significant reductions in parameters and floating point operations (FLOPs) of 77.54% and 65%, respectively, and a 48.5% increase in the inference speed on the Jetson TX2 platform. This framework optimally maintains target features and effectively distinguishes feature channel importance compared to other methods, significantly enhancing feature channel robustness for difficult targets and expanding pruning applicability to less difficult targets.

Osteoarthritis (OA) is a prevalent degenerative disease that impairs limb function, and its pathogenesis is closely related to inflammation. Sakuranetin (SK) is a cherry flavonoid phytoalexin with potent anti-inflammatory, anti-oxidant, and ant-ifungal properties. In recent studies, flavonoid and phytoalexin-related medicines have shown promise in the treatment of OA. However, the effects of SK on chondrocyte inflammation and the chondrogenesis process have remained unexplored, as have its functions in OA treatment. This study sought to confirm the therapeutic effects of SK in the OA rat model and reveal the potential mechanisms for protecting chondrocytes. The relevant mechanisms of SK were analyzed by network pharmacology analysis. Chondrocytes were subjected to IL-1β intervention to simulate an inflammatory environment and received SK treatment. Then, anabolism, catabolism, and inflammatory markers were detected by western blot, qPCR, elisa, and immunofluorescence. Chondrogenic ability was evaluated by micromass and 3D culture assays. The rats were treated with destabilization of the medial meniscus (DMM) surgery to establish an OA model and SK intra-articular injections subsequently. Histological staining, immunohistochemistry, and micro-CT were performed to analyze the structural and morphological changes of cartilage and subchondral bone. In chondrocytes, IL-1β treatment reduced chondrogenic ability, promoted catabolism, and exacerbated inflammation by triggering the PI3K/AKT/NF-κB pathway, whereas SK treatment partially rescued these negative effects. In vivo, SK treatment effectively alleviated the degeneration of cartilage and subchondral bone, thereby delaying the progression of OA. In summary, SK alleviates chondrocyte inflammation and promotes chondrogenesis by inhibiting the PI3K/AKT/NF-κB pathway, thereby improving OA progression.

Abstract In view of the breakage of the rotary shaft of the traction motor of the locomotive, in order to ensure the reliability and safety of the equipment, this paper studies the magnetic field containing rich information in the space around the rotary shaft, so that the crack defect can be detected and the crack size can be judged in time. In order to study the influence of defect geometric parameters (width, depth and hidden depth) on the spatial magnetic field distribution around the defect in the process of eddy current testing of metal shafts, based on the principle of eddy current testing, a metal rotary shaft detection model with different defect parameters was established by COMSOL software for simulation. The horizontal magnetic induction intensity, vertical magnetic induction intensity and their respective phases are used to analyze the magnetic field distribution around the defect under different parameters. The results show that the magnetic field related parameters can qualitatively and quantitatively evaluate the crack width, qualitatively evaluate the relative size of the crack depth, and qualitatively judge whether there are hidden cracks.

This paper presents the design of a 60 GHz millimeter-wave (MMW) slot array horn antenna based on the substrate-integrated waveguide (SIW) structure. The novelty of this device resides in the achievement of a broad impedance bandwidth and high gain performance by meticulously engineering the radiation band structure and slot array. The antenna demonstrates an impressive impedance bandwidth of 14.96 GHz (24.93%), accompanied by a remarkable maximum reflection coefficient of −39.47 dB. Furthermore, the antenna boasts a gain of 10.01 dBi, showcasing its outstanding performance as a high-frequency antenna with a wide bandwidth and high gain. To validate its capabilities, we fabricated and experimentally characterized a prototype of the antenna using a probe test structure. The measurement results closely align with the simulation results, affirming the suitability of the designed antenna for radar sensing applications in future global industrial scenarios.

Graphene has garnered widespread attention, and its use is being explored for various electronic devices due to its exceptional material properties. However, the use of polymers (PMMA, photoresists, etc.) during graphene transfer and patterning processes inevitably leaves residues on graphene surface, which can decrease the performance and yield of graphene-based devices. This paper proposes a new transfer and patterning process that utilizes an Al intermediate layer to separate graphene from polymers. Through DFT calculations, the binding energy of graphene–Al was found to be only −0.48 eV, much lower than that of PMMA and photoresist with graphene, making it easier to remove Al from graphene. Subsequently, this was confirmed through XPS analysis. A morphological characterization demonstrated that the graphene patterns prepared using the Al intermediate layer process exhibited higher surface quality, with significantly reduced roughness. It is noteworthy that the devices obtained with the proposed method exhibited a notable enhancement in both consistency and sensitivity during electrical testing (increase of 67.14% in temperature sensitivity). The low-cost and pollution-free graphene-processing method proposed in this study will facilitate the further commercialization of graphene-based devices.

A terahertz band (0.1–10 THz) has the characteristics of rich spectrum resources, high transmission speed, strong penetration, and clear directionality. However, the terahertz signal will suffer serious attenuation and absorption during transmission. Therefore, a terahertz antenna with high gain, high efficiency, and wide bandwidth is an indispensable key component of terahertz wireless systems and has become a research hotspot in the field of antennas. In this paper, a high-gain broadband antenna is presented for terahertz applications. The antenna is a three-layer structure, fed by a grounded coplanar waveguide (GCPW), using polytetrafluoroethylene (PTFE) material as the dielectric substrate, and the metal through-hole of the dielectric substrate forms a substrate-integrated waveguide (SIW) structure. The metal fence structure is introduced to reduce the coupling effect between the radiation patches and increase the radiation bandwidth and gain. The center frequency is 0.6366 THz, the operating bandwidth is 0.61–0.68 THz, the minimum value of the voltage standing wave ratio (VSWR) is 1.00158, and the peak gain is 13.14 dBi. In addition, the performance of the designed antenna with a different isolation structure, the length of the connection line, the height of the substrate, the radius of the through-hole, and the thickness of the patch is also studied.

Advances in spatial transcriptomics technologies have enabled the gene expression profiling of tissues while retaining spatial context. Here the authors present GraphST, a graph self-supervised contrastive learning method that learns informative and discriminative spot representations from spatial transcriptomics data.

Pea (Pisum sativum L.) is an annual cool-season legume crop. Owing to its role in sustainable agriculture as both a rotation and a cash crop, its global market is expanding and increased production is urgently needed. For both technical and regulatory reasons, neither conventional nor transgenic breeding techniques can keep pace with the demand for increased production. In answer to this challenge, CRISPR/Cas9 genome editing technology has been gaining traction in plant biology and crop breeding in recent years. However, there are currently no reports of the successful application of the CRISPR/Cas9 genome editing technology in pea. We developed a transient transformation system of hairy roots, mediated by Agrobacterium rhizogenes strain K599, to validate the efficiency of a CRISPR/Cas9 system. Further optimization resulted in an efficient vector, PsU6.3-tRNA-PsPDS3-en35S-PsCas9. We used this optimized CRISPR/Cas9 system to edit the pea phytoene desaturase (PsPDS) gene, causing albinism, by Agrobacterium-mediated genetic transformation. This is the first report of successful generation of gene-edited pea plants by this route.

PM2.5 is directly related to the air quality and poses a threat to human health, thus high-precision monitoring of PM2.5 is necessary. The dispersion and accumulation of PM2.5 are affected by meteorological elements near the ground and in the upper air. Nevertheless, the current PM2.5 inversion models based on the deep neural network only consider ground elements. To further optimize the model and improve the inversion accuracy, a PM2.5 hourly inversion model integrating upper-air meteorological data was proposed, and a parametric rectified linear unit was used as the activation function of the model. The results showed that among the input elements, PM2.5 had the highest correlation with AOD, with a correlation coefficient of 0.33. The proposed model achieved the highest accuracy on the test set, with RMSE, MAE, and $\text{R}^{2}$ of $14.39 \mu \text{g}/\text{m}^{3}$ , $9.67 \mu \text{g}/\text{m}^{3}$ , and 0.83, respectively. Compared with the deep neural network models for surface meteorological data and surface+850hPa meteorological data, the RMSE of the proposed model on the test set was reduced by 23.13% and 17.05%, respectively. Meanwhile, the RMSE of the proposed model on the test set was reduced by 56.15%, 39.99%, 14.60% and 5.76%, respectively, compared with adaptive boosting, gradient boosting regression, random forest, and the integrated model of these three models. During the heating season in Shanxi Province, the high-value areas of PM2.5 were mainly distributed in the basin area, the PM2.5 concentration reached the highest in November and peaked at 11 a.m. during the day.

Abstract In this paper, a novel optical MEMS accelerometer is proposed based on evanescent coupling between parallel silicon nanowaveguides. The coupling length between nanowaveguides changes due to the input acceleration, leading to a great change of coupling efficiency. As a result, the applied acceleration can be obtained by measuring the transmission of waveguiding light. Simulation results with optical displacement sensing sensitivity of 32.83%/ $$\upmu $$ μ m within measurement range of 1.68 g is obtained. This design shows high compactness with no need of assembly, suggesting great potential in applications such as integrated photonic circuits.

In this paper, an ultracompact combined sensor for displacement and angle-synchronous measurement is proposed based on the self-imaging effect of optical microgratings. Using a two-grating structure, linear and angular displacement can be measured by detecting the change of phase and amplitude of the optical transmission, respectively, within one single structure in the meantime. The optically transmitted properties of the two-grating structure are investigated in both theory and simulation. Simulated results indicate that optical transmission changes in a sinusoidal relationship to the input linear displacement. Meanwhile, the amplitude of the curve decreases with an input pitch angle, indicating the ability for synchronous measurement within one single compact structure. The synchronous measurement of the linear displacement and the angle is also demonstrated experimentally. The results show a resolution down to 4 nm for linear displacement measurement and a maximum sensitivity of 0.26 mV/arcsec within a range of ±1° for angle measurement. Benefiting from a simple common-path structure without using optical components, including reflectors and polarizers, the sensor shows ultra-high compactness for multiple-degrees-of-freedom measuring, indicating the great potential for this sensor in fields such as integrated mechanical positioning and semiconductor fabrication.

Summary: Globally, stroke is one of the leading causes of death and significant contributors to disability. Gaining a thorough comprehension of the underlying pathogenic processes is essential for stroke treatment and prevention. In this study, we investigated the role of p21-activated kinase 1 (PAK1) in stroke by using oxygen-glucose deprivation (OGD) and transient middle cerebral artery occlusion and reperfusion (tMCAO/R) models. We reported that focal ischemia and reperfusion affect the PAK1 expression and activity levels. We further demonstrated that PAK1 is responsible for the endothelial hyperpermeability that occurs in the early stages of ischemia and reperfusion. Additionally, inhibition of PAK1 was discovered to alleviate blood-brain barrier disruption and protect against brain injury induced by tMCAO/R. Mechanistically, we provide the evidence that PAK1 regulates the formation of stress fibers and expression of surface junctional proteins. Together, our findings reveal a pathogenic function of PAK1 in stroke.

Abstract Exercise training (ExT) is capable of improving the heart function of spontaneously hypertensive rats (SHRs), but the underlying molecular mechanisms remain elusive. This study was aimed to investigate whether inhibition of RhoA/ROCK signaling pathway contributes to the cardiac protection by low-intensity ExT in SHRs. The results demonstrated that, compared with Wistar-Kyoto (WKY) rats, SHRs obviously exhibited higher blood pressure, increased heart weight index and thickness of left ventricular wall, decreased left ventricular function, damaged myocardial construction, and increased collagen fiber of left ventricle (P

Abstract Background Although, micropeptides encoded by non-coding RNA have been shown to have an important role in a variety of tumors processes, there have been no reports on micropeptide in renal cell carcinoma (RCC). Based on the micropeptide MIAC (micropeptide inhibiting actin cytoskeleton) discovered and named in the previous work, this study screened its tumor spectrum, and explored its mechanism of action and potential diagnosis and treatment value in the occurrence and development of renal carcinoma. Methods The clinical significance of MIAC in RCC was explored by bioinformatics analysis through high-throughput RNA-seq data from 530 patients with kidney renal clear cell carcinoma (KIRC) in the TCGA database, and the detection of clinical samples of 70 cases of kidney cancer. In vitro and in vivo experiments to determine the role of MIAC in renal carcinoma cell growth and metastasis; High-throughput transcriptomics, western blotting, immunoprecipitation, molecular docking, affinity experiments, and Streptavidin pulldown experiments identify MIAC direct binding protein and key regulatory pathways. Results The analysis of 600 renal carcinoma samples from different sources revealed that the expression level of MIAC is significantly decreased, and corelated with the prognosis and clinical stage of tumors in patients with renal carcinoma. Overexpression of MIAC in renal carcinoma cells can significantly inhibit the proliferation and migration ability, promote apoptosis of renal carcinoma cells, and affect the distribution of cells at various stages. After knocking down MIAC, the trend is reversed. In vivo experiments have found that MIAC overexpression inhibit the growth and metastasis of RCC, while the synthetized MIAC peptides can significantly inhibit the occurrence and development of RCC in vitro and in vivo. Further mechanistic studies have demonstrated that MIAC directly bind to AQP2 protein, inhibit EREG/EGFR expression and activate downstream pathways PI3K/AKT and MAPK to achieve anti-tumor effects. Conclusions This study revealed for the first time the tumor suppressor potential of the lncRNA-encoded micropeptide MIAC in RCC, which inhibits the activation of the EREG/EGFR signaling pathway by direct binding to AQP2 protein, thereby inhibiting renal carcinoma progression and metastasis. This result emphasizes that the micropeptide MIAC can provide a new strategy for the diagnosis and treatment of RCC.

Abstract The centenary of insulin discovery represents an important opportunity to transform diabetes from a fatal diagnosis into a medically manageable chronic condition. Insulin is a key peptide hormone and mediates the systemic glucose metabolism in different tissues. Insulin resistance (IR) is a disordered biological response for insulin stimulation through the disruption of different molecular pathways in target tissues. Acquired conditions and genetic factors have been implicated in IR. Recent genetic and biochemical studies suggest that the dysregulated metabolic mediators released by adipose tissue including adipokines, cytokines, chemokines, excess lipids and toxic lipid metabolites promote IR in other tissues. IR is associated with several groups of abnormal syndromes that include obesity, diabetes, metabolic dysfunction-associated fatty liver disease (MAFLD), cardiovascular disease, polycystic ovary syndrome (PCOS), and other abnormalities. Although no medication is specifically approved to treat IR, we summarized the lifestyle changes and pharmacological medications that have been used as efficient intervention to improve insulin sensitivity. Ultimately, the systematic discussion of complex mechanism will help to identify potential new targets and treat the closely associated metabolic syndrome of IR.

IntroductionAgeing in the human bone marrow is associated with immune function decline that results in the elderly being vulnerable to illnesses. A comprehensive healthy bone marrow consensus atlas can serve as a reference to study the immunological changes associated with ageing, and to identify and study abnormal cell states.MethodsWe collected publicly available single cell transcriptomic data of 145 healthy samples encompassing a wide spectrum of ages ranging from 2 to 84 years old to construct our human bone marrow atlas. The final atlas has 673,750 cells and 54 annotated cell types.ResultsWe first characterised the changes in cell population sizes with respect to age and the corresponding changes in gene expression and pathways. Overall, we found significant age-associated changes in the lymphoid lineage cells. The naïve CD8+ T cell population showed significant shrinkage with ageing while the effector/memory CD4+ T cells increased in proportion. We also found an age-correlated decline in the common lymphoid progenitor population, in line with the commonly observed myeloid skew in haematopoiesis among the elderly. We then employed our cell type-specific ageing gene signatures to develop a machine learning model that predicts the biological age of bone marrow samples, which we then applied to healthy individuals and those with blood diseases. Finally, we demonstrated how to identify abnormal cell states by mapping disease samples onto the atlas. We accurately identified abnormal plasma cells and erythroblasts in multiple myeloma samples, and abnormal cells in acute myeloid leukaemia samples.DiscussionThe bone marrow is the site of haematopoiesis, a highly important bodily process. We believe that our healthy bone marrow atlas is a valuable reference for studying bone marrow processes and bone marrow-related diseases. It can be mined for novel discoveries, as well as serve as a reference scaffold for mapping samples to identify and investigate abnormal cells.

Given the shortage of spectrum resources and the demand for communication systems of diminutive size, multi-function, and adaptive characteristics, this paper proposes an L-slot frequency reconfigurable antenna based on the MEMS switch. The antenna size is 4.07 × 5.27 mm2 and is suitable for the U-band. The antenna structure consists of two RF MEMS switches, a Rogers RT5880 dielectric substrate, an L-slot patch, and a full-coverage ground. The switch is of a series contact structure and is arranged at the corner of an L-slot. By controlling the on and off state of the switch, the antenna can switch between four states of 42.36, 47.65, 53.13, and 56.72 GHz. According to the simulation results in CST STUDIO SUITE 2018, the maximum gain of the antenna is 7.90 dB, the impedance bandwidth of each state is above 1 GHz, and the direction is mainly consistent. The antenna can meet the demand for multi-frequency millimeter wave communication.

Abstract Aging inducing the development of senescent cells (SNCs) in various tissues is considered as the main cause of the age-related diseases. Senotherapy has become a promising anti-aging therapy. However, the effectivity and side-effect of senolytic agents are still concern. Here, we observed the downregulation of senescence-related genes by adoptive infusion of natural killer (NK) cells in 26 cases in peripheral blood CD3+ T cells. NK cell treatment also significantly decreased levels of senescence markers and senescence-associated secretory phenotypes (SASPs) in three senescent adipose tissues when culturing them together. Interestingly, cytotoxic activity of mouse NK cells against SNCs was significantly enhanced by dopamine in vitro through D1-like receptors. Acein, dopamine-releasing peptide, promoted the adoptive infusion of NK cells in effectively eliminating SNCs in a variety of tissues and reduced local and systemic SASPs in aging mice but Acein alone did not have the senolytic effect. These data demonstrated that adoptive infusion of NK cells is an effective means in removing SNCs, and peptide Acein combined with NK cells further enhances this effect in aging mice.

Abstract Background Faba bean is an important legume crop in the world. Plant height and yield are important traits for crop improvement. The traditional plant height and yield measurement are labor intensive and time consuming. Therefore, it is essential to estimate these two parameters rapidly and efficiently. The purpose of this study was to provide an alternative way to accurately identify and evaluate faba bean germplasm and breeding materials. Results The results showed that 80% of the maximum plant height extracted from two-dimensional red–green–blue (2D-RGB) images had the best fitting degree with the ground measured values, with the coefficient of determination (R2), root-mean-square error (RMSE), and normalized root-mean-square error (NRMSE) were 0.9915, 1.4411 cm and 5.02%, respectively. In terms of yield estimation, support vector machines (SVM) showed the best performance (R2 = 0.7238, RMSE = 823.54 kg ha−1, NRMSE = 18.38%), followed by random forests (RF) and decision trees (DT). Conclusion The results of this study indicated that it is feasible to monitor the plant height of faba bean during the whole growth period based on UAV imagery. Furthermore, the machine learning algorithms can estimate the yield of faba bean reasonably with the multiple time points data of plant height.

Mulberry flavonoids can modulate the composition of rumen microbiota in ruminants to improve nutrient digestibility, owing to their strong biological activities. This study aimed to explore the effect of mulberry leaf flavonoids (MLF) on rumen bacteria, fermentation kinetics, and metagenomic functional profile in water buffalo. Forty buffaloes (4 ± 1 lactations) with almost same body weight (av. 600 ± 50 Kg) and days in milk (90 ± 20 d) were randomly allocated to four treatments having different levels of MLF: 0 g/d (control), 15 g/d (MLF15), 30 g/d (MLF30), and 45 g/d (MLF45) supplemented in a basal diet. After 35 days of supplementation, rumen contents were collected to determine rumen fermentation parameters. The 16S rRNA gene sequencing was performed to elucidate rumen bacteria composition. The obtained taxonomic data were analyzed to explore the rumen bacteriome and predict the associated gene functions and metabolic pathways. Results demonstrated a linear increase (p < 0.01) in rumen acetate, propionate, and total VFAs in the MLF45 group as compared to control. No effect of treatment was observed on rumen pH and butyrate contents. Acetate to propionate ratio in the MLF45 group linearly and quadratically decreased (p = 0.001) as compared to MLF15 and control groups. Similarly, MLF45 linearly increased (p < 0.05) the microbial protein (MCP) and NH3-N as compared to other treatments. Treatment adversely affected (p < 0.01) almost all alpha diversity parameters of rumen bacteria except Simpson index. MLF promoted the abundance of Proteobacteria while reducing the relative abundances of Actinobacteria, Acidobacteria, Chloroflexi, and Patescibacteria. The MLF supplementation tended to substantially reduce (0.05 < p < 0.1) the abundance of Actinobacteria, and Patescibacteria while completely eliminating Acidobacteria (p = 0.029), Chloroflexi (p = 0.059), and Gemmatimonadetes (p = 0.03) indicating the negative effect of flavonoids on the growth of these bacteria. However, MLF45 tended to substantially increase (p = 0.07) the abundance (~21.5%) of Acetobacter. The MLF treatment exhibited negative effect on five genera by significantly reducing (Sphingomonas) or eliminating (Arthobactor, unclassified_c__Actinobacteria, norank_c__Subgroup_6, norank_o__Saccharimonadales, and Nocardioides) them from the rumen microbiota. Pearson correlation analysis revealed 3, 5 and 23 positive correlations of rumen bacteria with milk yield, rumen fermentation and serum antioxidant parameters, respectively. A positive correlation of MCP was observed with three bacterial genera (Acetobacter, Enterobacter, and Klebsiella). The relative abundance of Pseudobutyrivibrio and Empedobacter also showed a positive correlation with the ruminal acetate and propionate. The present study indicated 45 g/d as an appropriate dose of MLF which modulated rumen bacteria and its functional profile in water buffalo.

Abstract This study evaluated the influence of dietary sodium nitrate on ruminal fermentation profiles, milk production and composition, microbial populations and diversity in water buffaloes. Twenty-four female water buffaloes were randomly divided into four groups and fed with 0, 0.11, 0.22, 044 g sodium nitrate per kg body weight diets, respectively. Results showed that the concentration of acetate, propionate, butyrate and total VFA in all sodium nitrate–adapted water buffaloes were greater than the control group (P 0.05). Compared to the control group, the archaea richness (ace and chao1) and diversity (Shannon index) indices were increased by nitrate supplementation (P

Abstract A high-precision micro-displacement sensor based on tunnel magneto-resistance effect is reported.We designed and simulated magnetic characteristics of the sensor, and employed chip-level Au-In bonding to implement low-temperature assembly of the TMR devices. We employed the subdivision interpolation technique to enhance the resolution by translating the sine-cosine outputs of a TMR sensor into an output that varies linearly with the displacement. Simultaneously, using the multi-bridge circuit method to suppress external magnetic and geomagnetic interference. Experimental result shows that the micro-displacement sensor has a resolution of 800 nm, accuracy of 0.14 $$\%$$ % and a full-scale range of up to millimeter level. This work enables a high-performance displacement sensor, and provides a significant guide for the design of a micro-displacement sensor in practical applications.

Although face recognition has achieved great success due to deep learning, many factors may affect the quality of faces in the wild, such as pose changes, age variations, and light changes, which can seriously affect the performance of face recognition. In this work, an effective approach called Efficient Lightweight Attention Networks (ELANet) is proposed to address the challenge brought by the impacts of poses and ages on face recognition performance. First, similar local patches are particularly important when the geometry and appearance of a face change drastically. To alleviate this challenge, spatial attention is used to capture important locally similar patches and channel attention is employed to focus on features with different levels of importance. Furthermore, Efficient Fusion Attention (EFA) module is designed to achieve better performance, which can alleviate the computational effort required by fusing spatial and channel attention. Second, multi-scale features learning is necessary because pose or large expression changes can cause similar recognition regions to appear at different scales. For this purpose, pyramid multi-scale module is presented, which constructs a series of features at different scales via pooling operations. Third, to unite low-level local detail information with high-level semantic information, the features of different layers are fused by Adaptively Spatial Feature Fusion (ASFF) instead of simply utilizing addition or concatenation. Compared to recent lightweight networks, the ELANet improved performance by 1.83% and 2.17% on the CPLFW and VGG2_FP datasets, respectively, and by 0.92% on the CALFW dataset. The ELANet addresses the challenge regarding the impacts of poses and ages on face recognition performance with few parameters and computational effort and is suitable for embedded and mobile devices.

This paper designs a five-bit microelectromechanical system (MEMS) time delay consisting of a single-pole six-throw (SP6T) RF switch and a coplanar waveguide (CPW) microstrip line. The focus is on the switch upper electrode design, power divider design, transmission line corner compensation structure design, CPW loading U-shaped slit structure design, and system simulation. The switch adopts a triangular upper electrode structure to reduce the cantilever beam equivalent elastic coefficient and the closed contact area to achieve low drive voltage and high isolation. The SP6T RF MEMS switch uses a disc-type power divider to achieve consistent RF performance across the output ports. When designed by loading U-shaped slit on transmission lines and step-compensated tangents at corners, the system loss is reduced, and the delay amount is improved. In addition, the overall size of the device is 2.1 mm × 2.4 mm × 0.5 mm, simulation results show that the device has a delay amount of 0–60 ps in the frequency range of 26.5–40 GHz, the delay accuracy at the center frequency is better than 0.63 ps, the delay error in the whole frequency band is less than 22.2%, the maximum insertion loss is 3.69 dB, and the input–output return rejection is better than 21.54 dB.

To study the influence of the geometric structure of the probe coil on the electromagnetic characteristics of the eddy current probe in the process of eddy current testing, based on the principle of eddy current testing, different probe coil models were established using finite element software. These geometric structure parameters include the difference between the inner and outer radius, thickness, and equivalent radius. The magnetic field distribution around the probe is simulated and analyzed under different parameters, and the detection performance of the probe is judged in combination with the change rate of the magnetic field around the probe coil. The simulation results show that at a closer position, increasing the difference between the inner and outer radii, reducing the thickness, and reducing the equivalent radius are beneficial to improve the resolution of the probe coil. At a far position, reducing the difference between the inner and outer radii, increasing the thickness, and reducing the equivalent radius are beneficial to improve the resolution of the probe coil. At the same time, the accuracy of the simulation data is verified by comparing the theoretical values with the simulated values under different conditions. Therefore, the obtained conclusions can provide a reference and basis for the optimal design of the probe structure.

A train traction system is an important part of an urban rail transit system. However, a train traction system has many components and a high risk of internal faults. How to systematically evaluate the fault coverage and diagnosis ability of testing equipment is a fundamental problem in the technical field of train operation. In response to this problem, this study attempts to apply testability technology to the test capability analysis of train traction systems for rail transit. In view of the uncertainty in actual tests, a method for constructing a fault diagnosis strategy for a traction system under unreliable testing is proposed. The concept of test credibility is introduced for the first time, and the quantitative evaluation of test credibility is realized using a cloud model, so as to construct a new “fault-test” credibility correlation matrix. On this basis, a single-fault diagnosis strategy of the traction system is constructed and compared based on information theory. The results show that a using a fault diagnosis strategy under the condition of unreliable testing is more similar to actual maintenance work, proving the significance of the diagnosis strategy constructed using this method for the practical application of the project.

An ultrasensitive single-axis in-plane micro-optical-electro-mechanical-system (MOEMS) accelerometer based on the Talbot effect of dual-layer gratings is proposed. Based on the Talbot effect of gratings, the acceleration can be converted into the variation of diffraction intensity, thus changing the voltage signal of photodetectors. We investigated and optimized the design of the mechanical structure; the resonant frequency of the accelerometer is 1878.9 Hz and the mechanical sensitivity is 0.14 μm/g. And the optical grating parameters have also optimized with a period of 4 μm and a grating interval of 10 μm. The experimental results demonstrated that the in-plane MOEMS accelerometer with an optimal design achieved an acceleration sensitivity of 0.74 V/g (with better than 0.4% nonlinearity), a bias stability of 75 μg and an acceleration resolution of 2.0 mg, suggesting its potential applications in smartphones, automotive electronics, and structural health detection.

Abstract Natural killer (NK) cells have been suggested to be associated with type 2 diabetes by regulating systemic inflammation. However, the mechanism by which NK cells regulate insulin sensitivity remains unknown. This study shows that NK-derived exosomes from lean mice attenuate obesity-induced insulin resistance and inflammation in mice of type 2 diabetes. Moreover, lean NK-derived exosomes enhance insulin sensitivity and relieve inflammation in adipocytes and hepatocytes. MiR-1249-3p, which is significantly upregulated in lean NK-derived exosomes, can be transferred from NK cells to adipocytes and hepatocytes via exosomes. NK-derived exosomal miR-1249-3p dramatically induces cellular insulin sensitivity and relieves inflammation. Mechanistically, exosomal miR-1249-3p directly targets SKOR1 to regulate the formation of ternary complex SMAD6/MYD88/SMURF1, which mediates glucose homeostasis by suppressing the TLR4/NF-κB signaling pathway. This study reveals an emerging role for NK-derived exosomal miR-1249-3p in remission of insulin resistance, and provides a series of potential therapeutic targets in type 2 diabetes.

Integrins are transmembrane receptors that have been implicated in the biology of various human physiological and pathological processes. These molecules facilitate cell–extracellular matrix and cell–cell interactions, and they have been implicated in fibrosis, inflammation, thrombosis, and tumor metastasis. The role of integrins in tumor progression makes them promising targets for cancer treatment, and certain integrin antagonists, such as antibodies and synthetic peptides, have been effectively utilized in the clinic for cancer therapy. Here, we discuss the evidence and knowledge on the contribution of integrins to cancer biology. Furthermore, we summarize the clinical attempts targeting this family in anti-cancer therapy development.

Abstract Background Heat stress in tropics is generally associated with significant economic losses resulting from reduced performance, morbidity, and mortality of livestock. To avoid serious consequences of heat stress, it is imperative to better understand the physiological responses and biochemical changes under the state of altered body homeostasis during different seasons of the year. Objectives This study aimed to evaluate the seasonal dynamics of physiological, oxidative and metabolic responses of lactating Nili‐Ravi buffaloes to the tropical climate of South China. Methods Physiological responses including rectal temperature (RT), body surface temperature (BST) and respiratory rate (RR) along with serum biochemical and antioxidant parameters of 20 lactating Nili‐Ravi buffaloes were evaluated during different seasons of the year. Results Higher temperature‐humidity Index (THI) during the summer season (>80) resulted in a significant increases in RR and BST as compared to the winter season. Higher oxidative stress was observed in the summer season as revealed by significantly higher MDA while lower serum antioxidant enzyme (TAC, GSH‐Px, SOD and CAT) contents. Moreover, serum cortisol was also significantly higher in summer and autumn. The levels of growth hormone and ACTH were also significantly (P

Grid formation inspection is the future development trend of grid inspection. Aim to the robust control problem of multi-agent grid inspection system in complex environment, this paper proposes a formation control algorithm with prescribed performance. The dynamic model of follower distance error is given in the leader-follower framework using a symbolic Laplace matrix. Performance bounds are set on the sliding mode error by prescribed performance control. Then, the convergence and stability of the proposed control algorithm are not only proved by the Lyapunov stability theorem, but also the error state of the system converges to the prescribed performance bound. Finally, the simulation results show that the follower can follow the leader despite external interference and the validity of the proposed algorithm.

Recent breakthroughs in sequencing technology and technological developments have made it easier to analyze the entire human genome than ever before. In addition to disease-specific genetic mutations and chromosomal aberrations, epigenetic alterations in individuals can also be analyzed using genomics. Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) caused by genetic and/or environmental factors. More than a thousand genes associated with ASD have been identified which are known to be involved in brain development. However, it is difficult to decode the roles of ASD-associated genes without in vitro and in vivo validations, particularly in the process of brain development. In this review, we discuss genomic strategies for understanding the pathological mechanisms underlying ASD. For this purpose, we discuss ASD-associated genes and their functions, as well as analytical strategies and their strengths and weaknesses in cellular and animal models from a basic research perspective.

Thermo-reliability of physical vapor deposition (PVD) Cr/Au on sapphire substrates was systematically investigated to improve the routing interconnection for high-temperature sensors. Cr and Au films were sequentially deposited on sapphire through magnetron sputtering. Samples with various Au layer thicknesses were subjected to annealing experiments at different temperatures and times. The temperature and processing time affected the dimension of Au particles and changed the surface roughness. With the increase in the temperature and treatment time, the agglomeration of Au particles increased, and the diameter enlarged substantially. Furthermore, the agglomeration effect is enhanced with the increase in the Au film thickness. However, the annealing time under the same temperature had a limited effect on the resistance. All the samples exhibited a low resistance at 700 °C. Moreover, compared with 100/500 nm Cr/Au films, the resistance of 100/1000 nm Cr/Au films slightly changed before and after annealing at 500 °C. Thus, thermo-reliability of PVD Cr/Au was beneficial for high-temperature sensors. The results of this study provided theoretical support for the practical applications of Cr/Au films.

A multi-frequency microstrip antenna loaded with a ring-like structure has been proposed. The radiating patch on the antenna surface consists of three split-ring resonator structures, and the ground plate consists of a bottom metal strip and three ring-shaped metals with regular cuts to form a defective ground structure. The proposed antenna works in six different frequency bands covering 1.10, 1.33, 1.63, 1.97, 2.08, and 2.69 GHz and works entirely when connected to 5G NR (FR1, 0.45–3 GHz), 4GLTE (1.6265–1.6605 GHz), Personal Communication System (1.85–1.99 GHz), Universal Mobile Telecommunications System (1.92–2.176 GHz), WiMAX (2.5–2.69 GHz), and other communications frequency bands. Moreover, such antennas also have stable omnidirectional radiation properties across different operating frequency bands. This antenna meets the needs of portable multi-frequency mobile devices and provides a theoretical approach for the development of multi-frequency antennas.

Global sea level rise is a major environmental concern for many countries and cities, particularly for low-lying coastal areas where urban development is threatened by the combined effects of sea level rise and land subsidence. This study employed an improved two-layer network Persistent Scatterers Interferometric Synthetic Aperture Radar (PS-InSAR) technology to obtain high-precision land subsidence in Singapore from 2015 to 2019. Landsat images from 1973 to 2020 were also utilized to extract changes in Singapore’s coastline. Geological, topographical, and global sea level rise data were integrated to investigate the causes and impacts of land subsidence in Singapore. The results indicate that the areas with severe subsidence coincide with land reclamation areas, where subsidence is mainly due to soil consolidation. Based on WorldDEM, land subsidence, and sea level rise data, the maximum inundation depth in Singapore by 2050 is estimated to be 1.24 m, with the Marina Bay area in Singapore’s central business district being the most vulnerable to sea level rise. This study provides data support and a scientific basis for understanding the impact of land subsidence on Singapore’s coastal areas under the influence of multiple factors using advanced InSAR technology.

In this article, a terahertz metamaterial biaxial strain pressure sensor structure is proposed, which can address the problems of the low sensitivity, the narrow pressure measurement range, and the uniaxial-only detection of existing terahertz pressure sensors. The performance of the pressure sensor was studied and analyzed using the time-domain finite-element-difference method. By changing the substrate material and optimizing the structure of the top cell, the size of the structure that can simultaneously improve the range and sensitivity of the pressure measurements was determined. The simulation results show that the sensor has a pressure-sensing effect in the frequency range of 1.0–2.2 THz under the conditions of transverse electric (TE) and transverse magnetic (TM) polarization, and the sensitivity can reach up to 346 GHz/μm. The proposed metamaterial pressure sensor has significant applications in the remote monitoring of target structure deformation.

Sodium nitrate is used as a non-protein nitrogen supplement while methionine is considered as a common methionine additive for ruminants. This study investigated the effects of sodium nitrate and coated methionine supplementation on milk yield, milk composition, rumen fermentation parameters, amino acid composition, and rumen microbial communities in lactating buffaloes. Forty mid-lactation multiparous Murrah buffaloes within the initial days in milk (DIM) = 180.83 ± 56.78 d, milk yield = 7.63 ± 0.19 kg, body weight = 645 ± 25 kg were selected and randomly allocated into four groups (N = 10). All of animals received the same total mixed ratio (TMR) diet. Furthermore, the groups were divided into the control group (CON), 70 g/d sodium nitrate group (SN), 15 g/d palmitate coated L-methionine group (MET), and 70 g/d sodium nitrate +15 g/d palmitate coated L-methionine group (SN+MET). The experiment lasted for six weeks, including two weeks of adaption. The results showed that most rumen-free amino acids, total essential amino acids, and total amino acids in Group SN increased (p < 0.05), while the dry matter intake (DMI) and rumen acetate, propionate, valerate, and total volatile fatty acids (TVFA) in Group MET decreased (p < 0.05). However, there was no significant difference in milk yield, milk protein, milk fat, lactose, total solid content, and sodium nitrate residue in milk among groups (p > 0.05). Group SN+MET had a decreased rumen propionate and valerate (p < 0.05), while increasing the Ace, Chao, and Simpson indices of alpha diversity of rumen bacteria. Proteobacteria and Actinobacteriota were significantly increased (p < 0.05) in Group SN+MET, but Bacteroidota, and Spirochaetota were decreased (p < 0.05). In addition, Group SN+MET also increased the relative abundance of Acinetobacter, Lactococcus, Microbacterium, Chryseobacterium, and Klebsiella, which were positively correlated with cysteine and negatively correlated with rumen acetate, propionate, valerate, and TVFA. Rikenellaceae_RC9_gut_group was identified as a biomarker in Group SN. Norank_f__UCG-011 was identified as a biomarker in Group MET. Acinetobacter, Kurthia, Bacillus, and Corynebacterium were identified as biomarkers in Group SN+MET. In conclusion, sodium nitrate increased rumen free amino acids, while methionine decreased dry matter intake (DMI) and rumen volatile fatty acids. The combined use of sodium nitrate and methionine enriched the species abundance of microorganisms in the rumen and affected the composition of microorganisms in the rumen. However, sodium nitrate, methionine, and their combination had no significant effect on the milk yield and milk composition. It was suggested that the combined use of sodium nitrate and methionine in buffalo production was more beneficial.

Designing ultra small metal nanoclusters or single atoms with metallic state is a challenge. Here, the authors demonstrate the stabilization of ultra small silver clusters in the nearly-metallic state by oxygen adsorption at high temperature, using in situ spectroscopy and microscope technologies.

Soot blowing optimization and health management of coal-fired power plant boiler has received increasing attention in recent years. The ash fouling monitoring and prediction are the basis for achieve this goal. Nowadays, with the development of neural network technology, the new data-driven methodologies are provided for ash fouling monitoring and prediction. This paper presents a comprehensive method based on neural-network for ash fouling prediction. Firstly, the health factor-clearness factor of the heated surface was established from the actual heat transfer coefficient and the theoretical heat transfer coefficient. Wavelet threshold denoising algorithm will be used as data preprocessing method. Secondly, use Ensemble Empirical Mode Decomposition (EEMD) to obtain a series of frequency stable parts. Finally, Encoder-Decoder based Attention (EDA) is used to predict the ash deposit on the heat transfer surface. The EDA model consists of an encoder, a decoder and an attention mechanism. The encoder and decoder are composed of Bidirectional Long Short-Term Memory (BI-LSTM) and Long Short-term Memory Network (LSTM) respectively. The function of the attention mechanism is that the output of each time step of the encoder is given a different degree of attention, and it is sent to the decoder as an attention vector after a weighted average operation. Ash accumulation data on the heat transfer surface of various devices are used to verify the effectiveness of the proposed hybrid model. In addition, the experimental results show that this method has better prediction accuracy than other variant models.

Face recognition has achieved great success due to the development of deep convolutional neural networks (DCNNs) and loss functions based on margin. However, complex DCNNs bring a large number of parameters as well as computational effort, which pose a significant challenge to resource-constrained embedded devices. Meanwhile, the popular margin-based loss functions all introduce only one type of margin and cannot further introduce a larger margin to achieve tighter classification boundary. In contrast to the common approach, we believe that additive and multiplicative margins should be used jointly to introduce larger margins from the margin perspective. Therefore, we propose a new margin-based loss function called UnifiedFace. First, we introduce an additive margin in the target angle activation function. Second, we add a multiplicative margin in the non-target angle. UnifiedFace introduces both additive and multiplicative margins, allowing for the introduction of large margins to achieve more compact intra-class variance and closer separated inter-class variance. In addition, we specifically design efficient face recognition models called GhostFaceNet for resource-constrained embedded devices. Experimental results demonstrate that UnifiedFace achieves state-of-the-art performance or performance competed with popular methods in training datasets of different sizes. UnifiedFace achieves optimal performance in models of varying complexity. Moreover, competitive results are achieved in the large-scale test set IJBB/C, especially the state-of-the-art performance achieved in TAR (FAR=1e−6). GhostFaceNet can significantly improve operational efficiency without significantly degrading recognition performance, making it ideal for embedded devices with limited resources.

This article presents the design method of a compact MEMS switched-line true-time delay line (TTDL) network over a wide frequency range extending from 2 to 42 GHz using TTDL units. The TTDL units, namely the cascading radio frequency micro-electromechanical system (RF MEMS) switches and GCPW, were employed in the proposed TTDL network to improve the delay-bandwidth product (DBW) while maintaining its compact size and low delay variation (DV). For comparison, a theoretical analysis of the RF MEMS switch was performed while observing the switch performance with various top electrodes. The MEMS TTDL network has a compact size of 5 mm × 5 mm, with a maximum delay of 200 ps and a minimum of 30 ps. The maximum insertion loss of 9 states is 10 dB, and the in/out return loss is better than 20 dB across 2-42 GHz. The group delay variations are within ±2.5% for all the delay states over the operating frequency range. To the best of our knowledge, the proposed TTDL network obtains the most control bits among the TTDL networks offered to date.

Sexual differentiation is a major developmental process. Sex differences resulting from sexual differentiation have attracted the attention of researchers. Unraveling what contributes to and underlies sex differences will provide valuable insights into the development of neurodevelopmental disorders that exhibit sex biases. Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects an individual’s social interaction and communication abilities, and its male preponderance has been consistently reported in clinical studies. The etiology of male preponderance remains unclear, but progress has been made in studying prenatal sex hormone exposure. The present review examined studies that focused on the association between prenatal testosterone exposure and ASD development, as well as sex-specific behaviors in individuals with ASD. This review also included studies on maternal immune activation-induced developmental abnormalities that also showed striking sex differences in offspring and discussed its possible interacting roles in ASD so as to present a potential approach for future studies on sex biases in ASD.

Here, we report an ultracompact angular displacement sensor based on the Talbot effect of optical microgratings. Periodic Talbot interference patterns were obtained behind an upper optical grating. By putting another grating within the Talbot region, the total transmission of the two-grating structure was found to be approximatively in a linear relationship with the relative pitch angle between the two gratings, which was explained by a transversal shift of the Talbot interference patterns. The influence of the grating parameters (e.g., the grating period, the number of grating lines and the gap between the two gratings) was also studied in both a simulation and an experiment, showing a tunable sensitivity and range by simply changing the grating parameters. A sensitivity of 0.19 mV/arcsec was experimentally obtained, leading to a relative sensitivity of 0.27%/arcsec within a linear range of ±396 arcsec with the 2 μm-period optical gratings. Benefitting from tunable properties and an ultracompact structure, we believe that the proposed sensor shows great potential in applications such as aviation, navigation, robotics and manufacturing engineering.

We propose a functionally tunable terahertz (THz) metamaterial absorber, which has the switching performance between broadband-narrowband and dual-broadband near-perfect absorption due to the phase transition of Vanadium dioxide (VO2) and the tunable electrical property of graphene. The switching absorption properties are verified by computer simulation technology (CST) microwave study. The simulation results show that when VO2 is in the metallic phase, over 90% broadband absorption is realized in the 3.85–6.32 THz range. When the VO2 is in the insulating phase, the absorber shows quadruple narrowband absorption. By changing the Fermi level of graphene and the conductivity of VO2, the low-frequency broadband of 3.85–6.32 THz can be switched to the high-frequency broadband of 6.92–8.92 THz, and the absorber can be switched from a quadruple narrowband to a nearly singlefold narrowband. In addition, the proposed absorber is insensitive to polarization due to its symmetry and wide incident angle. The design may have potential applications in the THz range, such as switches, electromagnetic shielding, cloaking objects, filtering, sensing, and so on.

For the state estimation problem of a multi-source localization nonlinear system with unknown and bounded noise, a distributed sequential ellipsoidal intersection fusion estimation algorithm based on the dual set-membership filtering method is proposed to ensure the reliability of the localization system. First, noise with unknown and bounded characteristics is modeled by using bounded ellipsoidal regions. At the same time, local estimators are designed at the sensor link nodes to filter out the noise interference in the localization system. The local estimator is designed using the dual set-membership filtering algorithm. It uses the dual principle to find the minimizing ellipsoid that can contain the nonlinear function by solving the optimization problem with semi-infinite constraints, and a first-order conditional gradient algorithm is used to solve the optimization problem with a low computational complexity. Meanwhile, the communication confusion among multiple sensors causes the problem of unknown correlation. The obtained estimates of local filters are fused at the fusion center by designing a distributed sequential ellipsoid intersection fusion estimation algorithm to obtain more accurate fusion localization results with lower computational cost. Finally, the stability and reliability of the proposed distributed fusion algorithm are verified by designing a simulation example of a multi-source nonlinear system.