Three-dimensional thermohaline structure estimation derived from HY-2 satellite data over the Maritime Silk Road and its applications

Estimated ocean subsurface fields derived from satellite observations provide potential data sources for operational marine environmental monitoring and prediction systems.This study employs a statistic regression reconstruction method,in combination with domestic autonomous sea surface height and sea surface temperature observations from the Haiyang-2(HY-2)satellite fusion data,to establish an operational quasi-realtime three-dimensional(3D)temperature and salinity products over the Maritime Silk Road.These products feature a daily temporal resolution and a spatial resolution of 0.25°×0.25°and exhibit stability and continuity.We have demonstrated the accuracy of the reconstructed thermohaline fields in capturing the 3D thermohaline variations through comprehensive statistical evaluations,after comparing them against Argo observations and ocean analysis data from 2022.The results illustrate that the reconstructed fields effectively represent seasonal variations in oceanic subsurface structures,along with structural changes resulting from mesoscale processes,and the upper ocean’s responses to tropical cyclones.Furthermore,the incorporation of HY-2 satellite observations notably enhances the accuracy of temperature and salinity reconstructions in the Northwest Pacific Ocean and marginally improves salinity reconstruction accuracy in the North Indian Ocean when compared to the World Ocean Atlas 2018 monthly climatology thermohaline fields.As a result,the reconstructed product holds promise for providing quasi-real-time 3D temperature and salinity field information to facilitate fast decisionmaking during emergencies,and also offers foundational thermohaline fields for operational ocean reanalysis and forecasting systems.These contributions enhance the safety and stability of ocean subsurface activities and navigation.

Indirubin alleviates retinal neurodegeneration through the regulation of PI3K/AKT signaling

Retinal neurodegenerative disease is a leading cause of blindness among the elderly in developed countries,including glaucoma,diabetic retinopathy,traumatic optic neuropathy and optic neuritis,etc.The current clinical treatment is not very effective.We investigated indirubin,one of the main bioactive components of the traditional Chinese medicine Danggui Longhui Pill,in the present study for its role in retinal neurodegeneration.Indirubin exhibited no detectable tissue toxicity in vivo or cytotoxicity in vitro.Moreover,indirubin improved visual function and ameliorated retinal neurodegeneration in mice after optic nerve crush injury in vivo.Furthermore,indirubin reduced the apoptosis of retinal ganglion cells induced by oxidative stress in vitro.In addition,indirubin significantly suppressed the increased production of intracellular reactive oxygen species and the decreased activity of superoxide dismutase induced by oxidative stress.Mechanically,indirubin played a neuroprotective role by regulating the PI3K/AKT/BAD/BCL-2 signaling.In conclusion,indirubin protected retinal ganglion cells from oxidative damage and alleviated retinal neurodegeneration induced by optic nerve crush injury.The present study provides a potential therapeutic medicine for retinal neurodegenerative diseases.

How to promote cooperative innovation in environmentally friendly technology:a case of agricultural biotechnology in China

This study explored the factors influencing cooperative innovation in environmentally friendly agricultural biotechnology in China.First,we constructed an evolutionary game model comprising the factors of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies.Using MATLAB simulation,we assigned different values to the aforementioned variables to explore the evolutionary trend of innovators’willingness to cooperate.Results showed that when the values of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies exceeded the threshold,innovators’willingness to cooperate was significantly enhanced.Furthermore,the proportion of innovators who cooperated with others gradually increased to 100%;otherwise,it gradually decreased to 0%.Comparing the simulation curve with the real evolution curve of cooperative innovation in agricultural biotechnology in China,we found that the gradual decline in the willingness to cooperate could be due to insufficient subsidies for cooperative innovation,low income from cooperative innovation,weak profitability of innovators,and weak market constraints.

An improved YOLOv7 for the state identification of sliding chairs in railway turnout

The sliding chairs are important components that support the switch rail conversion in the railway turnout.Due to the harsh environmental erosion and the attack from the wheel vibration,the failure rate of the sliding chairs accounts for up to 10%of the total failure number in turnout.However,there is little research carried out in the existing literature to diagnose the deterioration states of the sliding chairs.To fill out this gap,by utilizing the images containing the sliding chairs,we propose an improved You Only Look Once version 7(YOLOv7)to identify the state of the sliding chairs.Specifically,to meet the challenge brought by the small inter-class differences among the sliding chair states,we first integrate the Convolutional Block Attention Module(CBAM)into the YOLOv7 backbone to screen the information conducive to state identification.Then,an extra detector for a small object is customized into the YOLOv7 network in order to detect the small-scale sliding chairs in images.Meanwhile,we revise the localization loss in the objective function as the Efficient Intersection over Union(EIoU)to optimize the design of the aspect ratio,which helps the localization of the sliding chairs.Next,to address the issue caused by the varying scales of the sliding chairs,we employ K-means++to optimize the priori selection of the initial anchor boxes.Finally,based on the images collected from real-world turnouts,the proposed method is verified and the results show that our method outperforms the basic YOLOv7 in the state identification of the sliding chairs with 4%improvements in terms of both mean Average Precision@0.5(mAP@0.5)and F1-score.

Rail fastener detection of heavy railway based on deep learning

Image detection based on machine learning and deep learning currently has a good application prospect for railway fault diagnosis,with good performance in feature extraction and the accuracy of image localization and good classification results.To improve the speed of locating small target objects of fasteners,the YOLOv5 framework model with faster algorithm speed is selected.To improve the classification accuracy of fasteners,YOLOv5-based heavy-duty railway rail fastener detection is proposed.The anchor size is modified on the original basis to improve the attention to small targets of fasteners.The CBAM(Convolutional Block Attention Module)module and TPH(Transformer Prediction Head)module are introduced to improve the speed and accuracy issues.The rail fasteners are divided into 6 categories.Experiment comparisons show that before the improvement,the MAP@0.5 value of all categories are close to the peak of 0.989 after the epoch of 150,and the F1 score approaches 1 with confidence in the interval(0.2,0.95).The improved mAP@0.5 value approached the highest value of 0.991 after the epoch of 75,and the F1 score approached 1 with confidence in the interval(0.01,0.95).The experiment results indicate that the improved YOLOv5 model proposed in this paper is more suitable for the task of detecting rail fasteners.

A reasoning diagram based method for fault diagnosis of railway point system

Railway Point System(RPS)is an important infrastructure in railway industry and its faults may have significant impacts on the safety and efficiency of train operations.For the fault diagnosis of RPS,most existing methods assume that sufficient samples of each failure mode are available,which may be unrealistic,especially for those modes of low occurrence frequency but with high risk.To address this issue,this work proposes a novel fault diagnosis method that only requires the power signals generated under normal RPS operations in the training stage.Specifically,the failure modes of RPS are distinguished through constructing a reasoning diagram,whose nodes are either binary logic problems or those that can be decomposed into the problems of the binary logic.Then,an unsupervised method for the signal segmentation and a fault detection method are combined to make decisions for each binary logic problem.Based on the results of decisions,the diagnostic rules are established to identify the failure modes.Finally,the data collected from multiple real-world RPSs are used for validation and the results demonstrate that the proposed method outperforms the benchmark in identifying the faults of RPSs.

Transcriptome analysis reveals tumor antigen and immune subtypes of melanoma

Purpose:To screen potential tumor antigens for melanoma vaccine development and identify different immune subtypes.Methods:Transcriptional data(HTSEQ-FPKM)and clinical information of a 472 Melanoma cohort GDC TCGA Melanoma(SKCM)were downloaded from the UCSC XENA website(http://xena.ucsc.edu/).Subsequently,transcriptome data and clinical information of 210 melanoma cohort GSE65904 were downloaded from Gene Expression Omnibus(GEO),a large global public database.All the transcriptome expression data matrices were log2 transformed for subsequent analysis.GEPIA,TIMER,and IMMPORT databases are also used for analysis.Cell function experiments were performed to validate the role of the IDO1 gene in melanoma cell line A375.Results:Our study provides potential tumor antigens for vaccine development in melanoma patients:GZMB,GBP4,CD79A,APOBEC3F,IDO1,JCHAIN,LAG3,PLA2G2D,XCL2.In addition,we divide melanoma patients into two immune subtypes that have significant differences in tumor immunity and may have different responses to vaccination.In view of the unclear role of IDO1 in melanoma,we selected IDO1 for cell assay validation.Cell function assay showed that IDO1 was significantly overexpressed in the melanoma A375 cell line.After IDO1 knockdown,the activity,invasion,migration and healing ability of A375 cell lines were significantly decreased.Conclusion:Our study could provide a reference for the development of vaccines for melanoma patients.

人脸识别反欺诈研究进展

当前,人脸识别理论和技术取得了巨大的成功,被广泛应用于政府、金融和军事等关键领域.与其他信息系统类似,人脸识别系统也面临着各类安全问题,其中,人脸欺诈(face spoofing,FS)是最主要的安全问题之一.所谓的人脸欺诈,是指攻击者采用打印照片、视频回放和3D面具等攻击方式,诱骗人脸识别系统做出错误判断,因而是人脸识别系统所必须解决的关键问题.对人脸反欺诈(face anti-spoofing,FAS)的最新进展进行研究:首先,概述了FAS的基本概念;其次,介绍了当前FAS所面临的主要科学问题以及主要的解决方法及其优缺点;在此基础上,将已有的FAS工作分为传统方法和深度学习方法两大类,并分别进行详细论述;接着,针对基于深度学习的FAS域泛化和可解释性问题,从理论和实践的角度进行说明;然后,介绍了FAS研究所使用的典型数据集及其特点,并给出了FAS算法的评估标准和实验对比结果;最后,总结了FAS未来的研究方向并对发展趋势进行展望.

卵巢上皮性癌组织中长链非编码RNA PURPL的表达及其意义

目的:检测长链非编码RNA PURPL(p53 upregulated regulator of p53 levels)在卵巢上皮性癌(epithelial ovarian cancer,EOC)组织中的表达情况,探讨其在卵巢癌发生发展中的作用。方法:选用开放医学数据库lncRNASNP2、GEPIA和Kaplan-Meier Plotter检索PURPL在EOC组织中的表达及其与预后的关系。收集2012年10月至2015年10月郑州大学第一附属医院105例患者的临床病理资料,其中包括正常卵巢组织20例、良性卵巢上皮性肿瘤组织20例、EOC组织65例,采用实时荧光定量PCR检测上述不同卵巢组织中的PURPL表达情况,分析EOC组织中PURPL表达与EOC临床病理指标的关系,Kaplan-Meier法分析PURPL表达对EOC患者生存的影响。结果:数据库检索显示,EOC组织中PURPL的表达显著高于正常卵巢组织,PURPL表达升高与EOC患者的总生存(overall survival,OS)率和无复发生存期(recurrence-free survival,RFS)缩短相关。实时荧光定量PCR检测显示,晚期EOC组织中的PURPL表达为0.530±0.004,显著高于正常卵巢组织的0.029±0.001、良性卵巢上皮性肿瘤组织的0.135±0.001和早期EOC组织的0.488±0.006的表达(P<0.0001)。临床分期越晚(χ2=10.785,P=0.001)、有淋巴结转移(χ2=4.481,P=0.034)的EOC组织中的PURPL高表达。PURPL表达水平相对较高的EOC患者的OS和RFS,明显短于PURPL表达水平相对较低的患者(P<0.05)。结论:PURPL高表达提示EOC患者预后不良,可作为EOC预后监测的潜在标记物。

Role of the tissue microenvironment as a therapeutic target in hepatocellular carcinoma

Hepatocellular carcinoma is difficult to treat,primarilybecause the underlying molecular mechanisms drivingclinical outcome are still poorly understood.Growingevidence suggests that the tissue microenvironmenthas a role in the biological behavior of the tumor.Themain clinical issue is to identify the best target fortherapeutic approaches.Here,we discuss the hypothesis that the entire tissue microenvironment might beconsidered as a biological target.However,the tissuemicroenvironment consists of several cellular and biochemical components,each of which displays a distinctbiological activity.We discuss the major components ofthis environment and consider how they may interactto promote tumor/host crosstalk.

Hydrogen sulphide detection using near-infrared diode laser and compact dense-pattern multipass cell

Sub-ppmv level detection of hydrogen sulphide(H2 S) using a 1.578-μm distributed feedback tunable diode laser combining with wavelength modulation spectroscopy and second harmonic detection scheme is reported. A home-developed novel compact dense-pattern multipass gas cell with an effective optical path length of 29.37 m is used to improve sensitivity and reduce sample volume. Detection parameters are optimized, including modulation frequency and amplitude. The analysis of Allan variance shows that a minimum detectable concentration 60 ppbv is obtained with a lock-in time constant of 10 ms, and a detection limit of 13 ppbv can be achieved by average in 300 s. The demonstrated H2 S sensor has a strong penitential application in natural gas process for regulating and controlling H2 S concentration.

Systematic approaches to improving the performance of polyoxometalates in non-aqueous redox flow batteries

Polyoxometalates have been explored as multi-electron active species in both aqueous and non-aqueous redox flow batteries. Although non-aqueous systems in principle offer a wider voltage window for redox flow battery operation, realization of this potential requires a judicious choice of solvent as well as polyoxometalate properties. We demonstrate here the superior performance of N,N-dimethylformamide(DMF)compared to acetonitrile as a solvent for redox flow batteries based on Li3PMo12O40. This compound displays two 1-electron transfers in acetonitrile but can access an extra quasi-reversible 2-electron redox process in DMF. A cell containing 10 mM solution of Li3PMo12O40 in DMF produced a cell voltage of 0.7 V with 2-electron transfers(State of Charge = 60%) and showed a good cyclability. As a means to boost energy density, operation of the redox flow battery at a higher concentration of 0.1 M Li3PMo12O40 produced cells with cell voltage of 0.6 V in acetonitrile and a cell voltage of 1.0 V in DMF;both showed excellent coulombic efficiencies of more than 90% over the course of 30 cycles. Energy density was also increased by employing an asymmetric cell with different polyoxometalates on each side to extend cell voltage.Li6P2W18O62 exhibited 3 quasi-reversible 2-electron transfers in the potential range between-2.05 V and-0.5 V vs. Ag/Ag+. 10 mM Li6P2W18O62/Li3PMo12O40 in DMF produced a cell with cell voltage of 1.3 V involving 4-electron transfers(State of Charge = 50%) with coulombic efficiency of nearly 100% and energy efficiency of nearly 70% throughout the test with more than 20 cycles. These promising results demonstrate proof-of-concept approaches to improving the performance of polyoxometalates in non-aqueous redox flow batteries.

Null subcarriers based Doppler scale estimation with polynomial interpolation for multicarrier communication over ultrawideband underwater acoustic channels

This paper addresses the extremal problem of the null subcarriers based Doppler scale estimation in underwater acoustic （UWA） orthogonal frequency division multiplexing （OFDM） communication. The cost function constructed of the total energy of null subcarriers through discrete Fourier transform （DFT） is proposed. The frequencies of null subcarriers are identified from non-uniform Doppler shift at each tentative scaling factor. Then it is proved that the cost function can be fitted as a quadratic polynomial near the global minimum. An accurate Doppler scale estimation is achieved by the location of the global scarifying precision and increasing the computation minimum through polynomial interpolation, without complexity. A shallow water experiment is conducted to demonstrate the performance of the proposed method. Excellent performance results are obtained in ultrawideband UWA channels with a relative bandwidth of 67%, when the transmitter and the receiver are moving at a relative speed of 5 kn, which validates the proposed method.

Targeted inhibition of osteoclastogenesis reveals the pathogenesis and therapeutics of bone loss under sympathetic neurostress

Sympathetic cues via the adrenergic signaling critically regulate bone homeostasis and contribute to neurostress-induced bone loss,but the mechanisms and therapeutics remain incompletely elucidated.Here,we reveal an osteoclastogenesis-centered functionally important osteopenic pathogenesis under sympatho-adrenergic activation with characterized micro RNA response and efficient therapeutics.We discovered that osteoclastic mi R-21 was tightly regulated by sympatho-adrenergic cues downstream theβ2-adrenergic receptor(β2AR)signaling,critically modulated osteoclastogenesis in vivo by inhibiting programmed cell death 4(Pdcd4),and mediated detrimental effects of both isoproterenol(ISO)and chronic variable stress(CVS)on bone.Intriguingly,without affecting osteoblastic bone formation,bone protection against ISO and CVS was sufficiently achieved by a(D-Asp8)-lipid nanoparticle-mediated targeted inhibition of osteoclastic mi R-21 or by clinically relevant drugs to suppress osteoclastogenesis.Collectively,these results unravel a previously underdetermined molecular and functional paradigm that osteoclastogenesis crucially contributes to sympatho-adrenergic regulation of bone and establish multiple targeted therapeutic strategies to counteract osteopenias under stresses.

Extension and application of a database for the rapid identification of Vibrio using MALDI-TOF MS

Rapid and accurate identification of Vibrio species has been problematic because phenotypic characteristics are variable within species and biochemical identification requires two or more days to complete.Matrix-assisted laser desorption ionization–time of flight mass spectrometry(MALDI-TOF MS)has become a powerful tool for rapidly distinguishing between related bacterial species.However,its accuracy depends on the number of strains in a database.In the current study,we extend and apply the Vibrio database based on MALDI-TOF MS.A total of 74 strains of Vibrio representing 28 species were identified and included in new database.A phylogenetic tree based on rpoB sequence and dendrograms were constructed.We analyzed 30 clinical Vibrio of three species to evaluate the new database and carried out PCA dendrogram analyses for differences of strains.We created a new database that offered fast and accurate Vibrio identification.MSP and PCA dendrogram analyses provided technical support to track sources and incidences of Vibrio infection.In addition,the discovery of characteristic and differential peaks is useful for the future identification of Vibrio.This represents a powerful tool for the rapid and accurate classification and identification of Vibrio and closely related species.

Atmospheric N2O gas detection based on an inter-band cascade laser around 3.939 μm

N2O is a significant atmospheric greenhouse gas that contributes to global warming and climate change.In this work,the high sensitivity detection of atmospheric N2O is achieved using wavelength modulation spectroscopy(WMS)with an inter-band cascade laser operating around 3.939μm.A Lab VIEW-based software signal generator and software lock-in amplifiers are designed to simplify the system.In order to eliminate the interference from water vapor,the detection was performed at a pressure of 0.1 atm(1 atm=1.01325×10^5 Pa)and a drying tube was added to the system.To improve the system performance for long term detection,a novel frequency locking method and 2 f/1 f calibration-free method were employed to lock the laser frequency and calibrate the power fluctuations,respectively.The Allan deviation analysis of the results indicates a detection limit of^20 ppb(1 ppb=1.81205μg/m3)for a 1 s integration time,and the optimal detection limit is^5 ppb for a 40-s integration time.

Space-to-Ground Quantum Key Distribution Using a Small-Sized Payload on Tiangong-2 Space Lab

Quantum technology establishes a foundation for secure communication via quantum key distribution （QKD）. In the last two decades, the rapid development of QKD makes a global quantum communication network feasible. In order to construct this network, it is economical to consider small-sized and low-cost QKD payloads, which can be assembled on satellites with different sizes, such as space stations. Here we report an experimental demonstration of space-to-ground QKD using a small-sized payload, from Tiangong-2 space lab to Nanshan ground station. The 57.9-kg payload integrates a tracking system, a QKD transmitter along with modules for synchronization, and a laser communication transmitter. In the space lab, a 50MHz vacuum＋weak decoy-state optical source is sent through a reflective telescope with an aperture of 200mm. On the ground station, a telescope with an aperture of 1200mm collects the signal photons. A stable and high-transmittance communication channel is set up with a high-precision bidirectional tracking system, a polarization compensation module, and a synchronization system. When the quantum link is successfully established, we obtain a key rate over 100bps with a communication distance up to 719km. Together with our recent development of QKD in daylight, the present demonstration paves the way towards a practical satellite-constellation-based global quantum secure network with small-sized QKD payloads.

Trends in per capita ecological footprint and biocapacity in China 1949-2013

This paper proposes two concepts: the ecological footprint component index(EFCI) and the biocapacity component index(BCCI), based on the ecological footprint(EF) and Shannon entropy approaches. Per capita EFCI and BCCI in China 1949-2013 are analyzed using empirical mode decomposition(EMD). Nonlinear models of per capita EFCI and BCCI in China 1949-2013 are presented and their cycles and predictions from 2014 to 2023 are analyzed. The results over the last 65 years show:(1) EFCI in China has increased constantly with fluctuations, while BCCI has slowly decreased. Their annual change rates are 2.81% and-1.26%, respectively. The increasing EFCI indicates a gradual improvement in China's sustainable development potential; the decreasing BCCI indicates severe environmental and population challenges.(2) The cycles of per capita EFCI have periods of 5.4 and 16.3 years, while cycles of per capita BCCI have periods of 3.6, 13,and 21.7 years. The predictive models indicate that EFCI will first decrease, reaching 0.02725 in2014, and will subsequently increase to 0.03261 in 2021. BCCI will increase, reaching 0.01365 in2014 and 0.01541 in 2022. EFCI and BCCI will reach 0.03037 and 0.01537, respectively, in 2023.Policymakers should ensure that the EFCI and BCCI increase in 2023.

Prompt learning in computer vision: a survey

Prompt learning has attracted broad attention in computer vision since the large pre-trained visionlanguagemodels (VLMs) exploded. Based on the close relationship between vision and language information builtby VLM, prompt learning becomes a crucial technique in many important applications such as artificial intelligencegenerated content (AIGC). In this survey, we provide a progressive and comprehensive review of visual promptlearning as related to AIGC. We begin by introducing VLM, the foundation of visual prompt learning. Then, wereview the vision prompt learning methods and prompt-guided generative models, and discuss how to improve theefficiency of adapting AIGC models to specific downstream tasks. Finally, we provide some promising researchdirections concerning prompt learning.

全膝关节置换术后康复基础上有无针刺对改善膝关节功能的影响:一项系统评价和meta分析

Objective:To assess the effect and safety of acupuncture on the base of rehabilitation for knee function after total knee arthroplasty.Methods:Relevant articles were collected from CNKI,Sinomed,Wanfang,VIP,Cochrane Library,Medline and Embase.The search was conducted by using a combination of subject terms and free words.The data were analyzed by Revman 5.4 software,and the included studies were evaluated in compliance with the Cochrane Collaboration's tool for assessing risk of bias in randomized trials.Results:A total of 10 studies of randomized controlled trial(RCT) were included,with 785 participants involved,of which,393 cases in experiment group and 392 cases in control group.The interventions were electroacupuncture in 4 RCTs,filiform needling in 4 RCTs and transcutaneous electrical acupoint stimulation in 2 RCTs.Meta-analysis results showed that,compared with rehabilitation alone,acupuncture combined with rehabilitation improved the score of Hospital for Special Surgery(HSS)(MD=4.27,95%CI=[2.77,5.78],Z=5.58,P<0.00001),increased the range of motion(ROM) of the knee(MD=3.09,95%CI-[1.47,4.70],Z=3.75,P<0.001),and decreased the postoperative score of visual analogue scale(VAS)(MD=-0.53,95%CI=[-0.74,-0.33],Z=5.04,P<0.00001),but the difference in VAS score between groups only indicated statistical significance,without clinical importance.The sensitivity analysis showed the results were stable.In subgroup analysis,the stability of VAS score was relatively poorer in electroacupuncture group and filiform needle group,which may be associated with the differences in waveform of electroacupuncture and trial setting.Conclusion:Compared with rehabilitation alone,acupuncture in combination with rehabilitation could effectively improve the knee function for the patients after total knee arthroplasty.