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.

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.

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.

Abstract Stratified water columns are often found in lakes and oceans. Stratifications result from differences in density due to salt concentration, temperature, solid content and oxygenation. The stability of stratifications affects bioactivity, sedimentation, contaminant transport and environmental remediation. This study investigates the evolution of 6 stratified water columns created by differences in salinity, suspended minerals and the presence of a bottom heat source. We use acoustic wave reflection, photography, and both electrical conductivity and temperature profiles to track changes in stratification. Results show that multiple concurrent processes emerge across layers in otherwise quiescent water bodies. Dissimilar chemo-thermo conditions give rise to chemical and thermal diffusion, convection, and double-diffusion convection. When stratification involves suspended particles, interlayer processes include diffusiophoresis, flocculation/aggregation, sedimentation, osmosis, and chemo-consolidation; in this case, the specific surface and surface charge of suspended particles, and the salt concentration in contiguous layers determine aggregation-sedimentation-consolidation patterns. The interlayer transition zone acts as a high-pass filter that preferentially reflects low-frequency long-wavelength P-waves; invasive thermal and electrical conductivity probes provide complementary information and may identify stratification even when it is undetected by acoustic signals.

BackgroundDysphagia is a common complication of stroke that can result in serious consequences. In recent years, more and more papers on post-stroke dysphagia have been published in various journals. However, there is still a lack of bibliometric analysis of post-stroke dysphagia. This study visually analyzes the global research situation of post-stroke dysphagia from 2013 to 2022, aiming to explore the current research status, frontier trends, and research hotspots in this field.MethodsArticles and reviews relevant to post-stroke dysphagia were obtained and retrieved from the Web of Science core collection database in the last 10 years (from 2013 to 2022). CiteSpace and Microsoft Excel 2019 were used for bibliographic analysis.ResultsA total of 1,447 articles were included in the analysis. The number of publications showed an overall upward trend, from 72 in 2013 to 262 in 2022. The most influential authors, institutions, journals, and countries were Hamdy S, University of London, Dysphagia, and the People's Republic of China. An analysis of keywords and the literature indicated that current studies in the field of post-stroke dysphagia focused on dysphagia and aspiration, dysphagia classification, dysphagia rehabilitation, and daily living.ConclusionThis bibliometric analysis reveals the latest advancements and emerging trends in the field of post-stroke dysphagia, spanning the years 2013 to 2022. It highlights the paramount importance of conducting large-scale randomized controlled trials examining the efficacy of dysphagia screening protocols and non-invasive intervention techniques in improving the quality of life for these patients. Such research efforts hold significant academic implications for the development of evidence-based treatment strategies in this field.

This article proposes a novel lightweight attention spatiotemporal joint distribution adaptation network fault diagnosis model to address the key challenges of domain transfer and high model complexity in traditional methods. The novelty lies in 1. Using model compression techniques to reduce the complexity of the network model and improve its computational efficiency; 2. Introducing new domain adaptation and adversarial methods to solve the domain transfer problem. The effectiveness of the proposed model is verified through a transfer experiment of planetary gearbox vibration data. The experimental results show that the proposed model reduces the parameters and computational complexity to 18 % and 15 % of the original model, respectively, and has a diagnostic accuracy of over 98 % in cross-condition transfer tasks, and still maintains an accuracy of over 88 % even under high noise levels. This indicates that the proposed model is an efficient and accurate fault diagnosis model. [ABSTRACT FROM AUTHOR]

Objective • To investigate the impact of an Internet + WeChat platform-based “trinity” remote rehabilitation model involving the hospital, community, and family on stroke patient rehabilitation nursing. Methods • 159 patients with stroke who were discharged from Beijing Luhe Hospital of Capital Medical University from January 1, 2018, to December 31, 2019, were selected and divided into a control group (79 cases) and an experimental group (80 cases) by the random drawing method. The control group was given routine nursing, and the experimental group was given remote rehabilitation nursing intervention by using the WeChat network platform based on the control group. Limb function [Fugl-Meyer Assessment Scale (FMA)] and activities of daily living [Modified Barthel Index (MBI)] were evaluated at enrollment and at the end of 3 months, 6 months and 12 months in both groups. The compliance and satisfaction surveys in the two groups were evaluated after 6 months and 12 months of intervention. Results • (1) Before the intervention, there was no statistical significance in FMA score between the two groups (t = 0.798, P > .05). After 3 months, 6 months and 12 months of intervention, the FMA score in the two groups was increased compared with that before intervention (t = 2.463, P < .05), and the FMA scores in the experimental group at the above time points were higher than those in the control group (ts = 7.057, 14.285, Ps < .05). (2) There was no statistical difference in MBI scores between the two groups before intervention (t = 0.798, P > .05). After 3 months, 6 months, and 12 months of intervention, the MBI score in the two groups was increased compared with that before intervention (t = 0.232, P < .05), and MBI scores in the experimental group at the above time points were higher compared to the control group (ts = 4.959, 8.842, 8.131, Ps < .05). (3) The compliance scores in the experimental group were higher than those in the control group after 6 months and 12 months of intervention (ts = 4.959, 8.842, 8.131, Ps < .05). (4) The satisfaction survey scores in the experimental group after 6 months and 12 months of intervention were higher than those in the control group (ts = 2.120 ~ 14.554, Ps < .05). Conclusion • The Hospital-community-family “trinity” stroke rehabilitation model on the WeChat network platform holds significant importance. Enhancing limb function and daily living for stroke patients improves their quality of life and lessens reliance on caregivers. This positively impacts both survivors’ well-being and healthcare resources. Increased patient satisfaction and compliance suggest a potential revolution in post-stroke care, favoring a more patient-centered approach. Overall, this model has transformative potential for stroke treatment, offering holistic and patient-focused strategies. Its success promises better rehabilitation outcomes, patient satisfaction, and cost reduction, while paving the way for innovative research in stroke treatment and rehabilitation. [ABSTRACT FROM AUTHOR]