Serum cystatin C,monocyte/high-density lipoprotein-C ratio,and uric acid for the diagnosis of coronary heart disease and heart failure

BACKGROUND Coronary heart disease(CHD)and heart failure(HF)are the major causes of morbidity and mortality worldwide.Early and accurate diagnoses of CHD and HF are essential for optimal management and prognosis.However,conventional diagnostic methods such as electrocardiography,echocardiography,and cardiac biomarkers have certain limitations,such as low sensitivity,specificity,availability,and cost-effectiveness.Therefore,there is a need for simple,noninvasive,and reliable biomarkers to diagnose CHD and HF.AIM To investigate serum cystatin C(Cys-C),monocyte/high-density lipoprotein cholesterol ratio(MHR),and uric acid(UA)diagnostic values for CHD and HF.METHODS We enrolled 80 patients with suspected CHD or HF who were admitted to our hospital between July 2022 and July 2023.The patients were divided into CHD(n=20),HF(n=20),CHD+HF(n=20),and control groups(n=20).The serum levels of Cys-C,MHR,and UA were measured using immunonephelometry and an enzymatic method,respectively,and the diagnostic values for CHD and HF were evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS Serum levels of Cys-C,MHR,and UA were significantly higher in the CHD,HF,and CHD+HF groups than those in the control group.The serum levels of Cys-C,MHR,and UA were significantly higher in the CHD+HF group than those in the CHD or HF group.The ROC curve analysis showed that serum Cys-C,MHR,and UA had good diagnostic performance for CHD and HF,with areas under the curve ranging from 0.78 to 0.93.The optimal cutoff values of serum Cys-C,MHR,and UA for diagnosing CHD,HF,and CHD+HF were 1.2 mg/L,0.9×10^(9),and 389μmol/L;1.4 mg/L,1.0×10^(9),and 449μmol/L;and 1.6 mg/L,1.1×10^(9),and 508μmol/L,respectively.CONCLUSION Serum Cys-C,MHR,and UA are useful biomarkers for diagnosing CHD and HF,and CHD+HF.These can provide information for decision-making and risk stratification in patients with CHD and HF.

Tandem hydroalkylation and deoxygenation of lignin-derived phenolics to synthesize high-density fuels

Lignin is the most abundant naturally phenolic biomass,and the synthesis of high-performance renewable fuel from lignin has attracted significant attention.We propose the efficient synthesis of high-density fuels using simulated lignin cracked oil in tandem with hydroalkylation and deoxygenation reactions.First,we investigated the reaction pathway for the hydroalkylation of phenol,which competes with the hydrodeoxygenation form cyclohexane.And then,we investigated the effects of metal catalyst types,the loading amount of metallic,acid dosage,and reactant ratio on the reaction results.The phenol hydroalkylation and hydrodeoxygenation were balanced when 180℃ and 5 MPa H_(2)with the alkanes yield of 95%.By extending the substrate to other lignin-derived phenolics and simulated lignin cracked oil,we obtained the polycyclic alkane fuel with high density of 0.918 g·ml^(-1)and calorific value of41.2 MJ·L^(-1).Besides,the fuel has good low-temperature properties(viscosity of 9.3 mm^(2)·s^(-1)at 20℃ and freezing point below-55℃),which is expected to be used as jet fuel.This work provides a promising way for the easy and green production of high-density fuel directly from real lignin oil.

Real-Time 4-Mode MDM Transmission Using Commercial 400G OTN Transceivers and All-Fiber Mode Multiplexers

Weakly-coupled mode division multiplexing(MDM)technique is considered a promising candidate to enhance the capacity of an optical transmission system,in which mode multiplexers/demultiplexers(MMUX/MDEMUX)with low insertion loss and modal crosstalk are the key components.In this paper,a low-modal-crosstalk 4-mode MMUX/MDEMUX for the weakly-coupled triple-ring-core few-mode fiber(TRC-FMF)is designed and fabricated with side-polishing processing.The measurement results show that a pair of MMUX/MDEMUX and 25 km weakly-coupled TRC-FMF MDM link achieve low modal crosstalk of lower than−17.5 dB and insertion loss of lower than 11.56 dB for all the four modes.Based on the TRC-FMF and all-fiber MMUX/MDEMUX,an experiment for 25 km real-time 4-mode 3-λwavelength division multiplexing(WDM)-MDM transmission is conducted using commercial 400G optical transport network(OTN)transceivers.The experimental results prove weakly-coupled MDM techniques facilitate a smooth upgrade of the optical transmission system.

Kinetic-Thermodynamic Promotion Engineering toward High-Density Hierarchical and Zn-Doping Activity-Enhancing ZnNiO@CF for High-Capacity Desalination

Despite the promising potential of transition metal oxides(TMOs)as capacitive deionization(CDI)electrodes,the actual capacity of TMOs electrodes for sodium storage is significantly lower than the theoretical capacity,posing a major obstacle.Herein,we prepared the kinetically favorable Zn_(x)Ni_(1−x)O electrode in situ growth on carbon felt(Zn_(x)Ni_(1−x)O@CF)through constraining the rate of OH^(−)generation in the hydrothermal method.Zn_(x)Ni_(1−x)O@CF exhibited a high-density hierarchical nanosheet structure with three-dimensional open pores,benefitting the ion transport/electron transfer.And tuning the moderate amount of redox-inert Zn-doping can enhance surface electroactive sites,actual activity of redox-active Ni species,and lower adsorption energy,promoting the adsorption kinetic and thermodynamic of the Zn_(0.2)Ni_(0.8)O@CF.Benefitting from the kinetic-thermodynamic facilitation mechanism,Zn_(0.2)Ni_(0.8)O@CF achieved ultrahigh desalination capacity(128.9 mgNaCl g^(-1)),ultra-low energy consumption(0.164 kW h kgNaCl^(-1)),high salt removal rate(1.21 mgNaCl g^(-1) min^(-1)),and good cyclability.The thermodynamic facilitation and Na^(+)intercalation mechanism of Zn_(0.2)Ni_(0.8)O@CF are identified by the density functional theory calculations and electrochemical quartz crystal microbalance with dissipation monitoring,respectively.This research provides new insights into controlling electrochemically favorable morphology and demonstrates that Zn-doping,which is redox-inert,is essential for enhancing the electrochemical performance of CDI electrodes.

Mother-to-Child Transmission of Human Papillomavirus in Burkina Faso

Introduction: Human papillomavirus (HPV) infection is the most widespread sexually transmitted infection in the world. Today, there is growing evidence that HPV can be transmitted early in life, and one potential route is mother-to-child transmission. Data on this route of HPV transmission are scarce in Africa and particularly in Burkina Faso, where no data on the subject are yet available. The aim of our study was to estimate the rate of mother-to-child transmission of HPV infection and to identify circulating genotypes. Methodology: Cervico-uterine samples were collected from 100 full-term pregnant women and, buccal samples were obtained from their newborns at Hopital Saint Camille de Ouagadougou (HOSCO) by the specialist physician. HPV DNA amplification and genotyping were performed by PCR followed by hybridization using the HPV Direct Flow Chips kit, detecting 36 genotypes including 18 high-risk and 18 low-risk. Results: The prevalence of HPV in newborns was 8% (8/100). Six (6) HPV-positive neonates had HPV-positive mothers, while 2 HPV-positive neonates had HPV-negative mothers. The vertical transmission rate was 26.09% (6/23). Mother-newborn genotypes were concordant. However, the genotype profile of the newborns was more restricted than that of the mothers. Conclusion: HPV DNA was found in 8% of newborns in our study. The genotype profile of the mother-newborn pair was concordant. Asymptomatic HPV infection in a pregnant woman could constitute a risk factor for vertical transmission.

Revealing the microstructures of metal halide perovskite thin films via advancedtransmission electron microscopy

Metal halide perovskites (MHPs) are excellent semiconductors that have led to breakthroughs in applications in thinfilmsolar cells, detectors, and light-emitting diodes due to their remarkable optoelectronic properties and defect tolerance.However, the performance and stability of MHP-based devices are significantly influenced by their microstructures includingthe formation of defects, composition fluctuations, structural inhomogeneity, etc. Transmission electron microscopy(TEM) is a powerful tool for direct observation of microstructure at the atomic-scale resolution and has been used to correlatethe microstructure and performance of MHP-based devices. In this review, we highlight the application of TEMtechniques in revealing the microstructures of MHP thin films at the atomic scale. The results provide critical understandingof the performance of MHP devices and guide the design of strategies for improving the performance and stability ofMHP devices.

Effects of cross-Kerr coupling on transmission spectrum of double-cavity optomechanical system

We theoretically study the transmission spectrum of the cavity field in a double-cavity optomechanical system with cross-Kerr(CK) effect. The system consists of two tunneling coupling optomechanical cavities with a mechanical resonator as a coupling interface. By doping CK medium into the mechanical resonator, CK couplings between the cavity fields and the mechanical resonator are introduced. We investigate the effects of CK coupling strength on the transmission spectrum of the cavity field, including the transmission rate, nonreciprocity and four-wave mixing(FWM). We find that the transmission spectrum of the probe field can show two obvious transparent windows, which can be widened by increasing the CK coupling strength. For the transmission between the two cavity fields, the perfect nonreciprocity and reciprocity are present and modulated by CK coupling and phase difference between two effective optomechanical couplings. In addition, the effects of the optomechanical and CK couplings on FWM show that the single peak of FWM is split into three symmetrical peaks due to the introduction of the CK effect.

Low Stress TSV Arrays for High-Density Interconnection

In three-dimensional(3D)stacking,the thermal stress of through-silicon via(TSV)has a significant influence on chip performance and reliability,and this problem is exacerbated in high-density TSV arrays.In this study,a novel hollow tungsten TSV(W-TSV)is presented and developed.The hollow structure provides space for the release of thermal stress.Simulation results showed that the hollow W-TSV structure can release 60.3%of thermal stress within the top 2 lm from the surface,and thermal stress can be decreased to less than 20 MPa in the radial area of 3 lm.The ultra-high-density(1600 TSV∙mm2)TSV array with a size of 640×512,a pitch of 25 lm,and an aspect ratio of 20.3 was fabricated,and the test results demonstrated that the proposed TSV has excellent electrical and reliability performances.The average resistance of the TSV was 1.21 X.The leakage current was 643 pA and the breakdown voltage was greater than 100 V.The resistance change is less than 2%after 100 temperature cycles from40 to 125℃.Raman spectroscopy showed that the maximum stress on the wafer surface caused by the hollow W-TSV was 31.02 MPa,which means that there was no keep-out zone(KOZ)caused by the TSV array.These results indicate that this structure has great potential for applications in large-array photodetectors and 3D integrated circuits.

An Encode-and CRT-Based Scalability Scheme for Optimizing Transmission in Blockchain

Blockchain technology has witnessed a burgeoning integration into diverse realms of economic and societal development.Nevertheless,scalability challenges,characterized by diminished broadcast efficiency,heightened communication overhead,and escalated storage costs,have significantly constrained the broad-scale application of blockchain.This paper introduces a novel Encode-and CRT-based Scalability Scheme(ECSS),meticulously refined to enhance both block broadcasting and storage.Primarily,ECSS categorizes nodes into distinct domains,thereby reducing the network diameter and augmenting transmission efficiency.Secondly,ECSS streamlines block transmission through a compact block protocol and robust RS coding,which not only reduces the size of broadcasted blocks but also ensures transmission reliability.Finally,ECSS utilizes the Chinese remainder theorem,designating the block body as the compression target and mapping it to multiple modules to achieve efficient storage,thereby alleviating the storage burdens on nodes.To evaluate ECSS’s performance,we established an experimental platformand conducted comprehensive assessments.Empirical results demonstrate that ECSS attains superior network scalability and stability,reducing communication overhead by an impressive 72% and total storage costs by a substantial 63.6%.

Variational Learned Talking-Head Semantic Coded Transmission System

Video transmission requires considerable bandwidth,and current widely employed schemes prove inadequate when confronted with scenes featuring prominently.Motivated by the strides in talkinghead generative technology,the paper introduces a semantic transmission system tailored for talking-head videos.The system captures semantic information from talking-head video and faithfully reconstructs source video at the receiver,only one-shot reference frame and compact semantic features are required for the entire transmission.Specifically,we analyze video semantics in the pixel domain frame-by-frame and jointly process multi-frame semantic information to seamlessly incorporate spatial and temporal information.Variational modeling is utilized to evaluate the diversity of importance among group semantics,thereby guiding bandwidth resource allocation for semantics to enhance system efficiency.The whole endto-end system is modeled as an optimization problem and equivalent to acquiring optimal rate-distortion performance.We evaluate our system on both reference frame and video transmission,experimental results demonstrate that our system can improve the efficiency and robustness of communications.Compared to the classical approaches,our system can save over 90%of bandwidth when user perception is close.

A semantic segmentation-based underwater acoustic image transmission framework for cooperative SLAM

With the development of underwater sonar detection technology,simultaneous localization and mapping(SLAM)approach has attracted much attention in underwater navigation field in recent years.But the weak detection ability of a single vehicle limits the SLAM performance in wide areas.Thereby,cooperative SLAM using multiple vehicles has become an important research direction.The key factor of cooperative SLAM is timely and efficient sonar image transmission among underwater vehicles.However,the limited bandwidth of underwater acoustic channels contradicts a large amount of sonar image data.It is essential to compress the images before transmission.Recently,deep neural networks have great value in image compression by virtue of the powerful learning ability of neural networks,but the existing sonar image compression methods based on neural network usually focus on the pixel-level information without the semantic-level information.In this paper,we propose a novel underwater acoustic transmission scheme called UAT-SSIC that includes semantic segmentation-based sonar image compression(SSIC)framework and the joint source-channel codec,to improve the accuracy of the semantic information of the reconstructed sonar image at the receiver.The SSIC framework consists of Auto-Encoder structure-based sonar image compression network,which is measured by a semantic segmentation network's residual.Considering that sonar images have the characteristics of blurred target edges,the semantic segmentation network used a special dilated convolution neural network(DiCNN)to enhance segmentation accuracy by expanding the range of receptive fields.The joint source-channel codec with unequal error protection is proposed that adjusts the power level of the transmitted data,which deal with sonar image transmission error caused by the serious underwater acoustic channel.Experiment results demonstrate that our method preserves more semantic information,with advantages over existing methods at the same compression ratio.It also improves the error tolerance and packet loss resistance of transmission.

Inferring Mycobacterium Tuberculosis Drug Resistance and Transmission using Whole-genome Sequencing in a High TB-burden Setting in China

Objective China is among the 30 countries with a high burden of tuberculosis(TB)worldwide,and TB remains a public health concern.Kashgar Prefecture in the southern Xinjiang Autonomous Region is considered as one of the highest TB burden regions in China.However,molecular epidemiological studies of Kashgar are lacking.Methods A population-based retrospective study was conducted using whole-genome sequencing(WGS)to determine the characteristics of drug resistance and the transmission patterns.Results A total of 1,668 isolates collected in 2020 were classified into lineages 2(46.0%),3(27.5%),and 4(26.5%).The drug resistance rates revealed by WGS showed that the top three drugs in terms of the resistance rate were isoniazid(7.4%,124/1,668),streptomycin(6.0%,100/1,668),and rifampicin(3.3%,55/1,668).The rate of rifampicin resistance was 1.8%(23/1,290)in the new cases and 9.4%(32/340)in the previously treated cases.Known resistance mutations were detected more frequently in lineage 2 strains than in lineage 3 or 4 strains,respectively:18.6%vs.8.7 or 9%,P<0.001.The estimated proportion of recent transmissions was 25.9%(432/1,668).Multivariate logistic analyses indicated that sex,age,occupation,lineage,and drug resistance were the risk factors for recent transmission.Despite the low rate of drug resistance,drug-resistant strains had a higher risk of recent transmission than the susceptible strains(adjusted odds ratio,1.414;95%CI,1.023–1.954;P=0.036).Among all patients with drug-resistant tuberculosis(DR-TB),78.4%(171/218)were attributed to the transmission of DR-TB strains.Conclusion Our results suggest that drug-resistant strains are more transmissible than susceptible strains and that transmission is the major driving force of the current DR-TB epidemic in Kashgar.

A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)technique.The fractional dengue transmission model(FDTM)consists of 12 compartments.The human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and infectious.We investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression analysis.The effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).

Review of the Configuration and Transient Stability of Large-scale Renewable Energy Generation through Hybrid DC Transmission

Based on the complementary advantages of Line Commutated Converter(LCC)and Modular Multilevel Converter(MMC)in power grid applications,there are two types of hybrid DC system topologies:one is the parallel connection of LCC converter stations and MMC converter stations,and the other is the series connection of LCC and MMC converter stations within a single station.The hybrid DC transmission system faces broad application prospects and development potential in large-scale clean energy integration across regions and the construction of a new power system dominated by new energy sources in China.This paper first analyzes the system forms and topological characteristics of hybrid DC transmission,introducing the forms and topological characteristics of converter-level hybrid DC transmission systems and system-level hybrid DC transmission systems.Next,it analyzes the operating characteristics of LCC and MMC inverter-level hybrid DC transmission systems,provides insights into the transient stability of hybrid DC transmission systems,and typical fault ride-through control strategies.Finally,it summarizes the networking characteristics of the LCC-MMC series within the converter station hybrid DC transmission system,studies the transient characteristics and fault ridethrough control strategies under different fault types for the LCC-MMC series in the receiving-end converter station,and investigates the transient characteristics and fault ride-through control strategies under different fault types for the LCC-MMC series in the sending-end converter station.

Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

While the interaction between information and disease in static networks has been extensively investigated,many studies have ignored the characteristics of network evolution.In this study,we construct a new two-layer coupling model to explore the interactions between information and disease.The upper layer describes the diffusion of disease-related information,and the lower layer represents the disease transmission.We then use power-law distributions to examine the influence of asymmetric activity levels on dynamic propagation,revealing a mapping relationship characterizing the interconnected propagation of information and diseases among partial nodes within the network.Subsequently,we derive the disease outbreak threshold by using the microscopic Markov-chain approach(MMCA).Finally,we perform extensive Monte Carlo(MC)numerical simulations to verify the accuracy of our theoretical results.Our findings indicate that the activity levels of individuals in the disease transmission layer have a more significant influence on disease transmission compared with the individual activity levels in the information diffusion layer.Moreover,reducing the damping factor can delay disease outbreaks and suppress disease transmission,while improving individual quarantine measures can contribute positively to disease control.This study provides valuable insights into policymakers for developing outbreak prevention and control strategies.

Semantic segmentation-based semantic communication system for image transmission

With the rapid development of artificial intelligence and the widespread use of the Internet of Things, semantic communication, as an emerging communication paradigm, has been attracting great interest. Taking image transmission as an example, from the semantic communication's view, not all pixels in the images are equally important for certain receivers. The existing semantic communication systems directly perform semantic encoding and decoding on the whole image, in which the region of interest cannot be identified. In this paper, we propose a novel semantic communication system for image transmission that can distinguish between Regions Of Interest (ROI) and Regions Of Non-Interest (RONI) based on semantic segmentation, where a semantic segmentation algorithm is used to classify each pixel of the image and distinguish ROI and RONI. The system also enables high-quality transmission of ROI with lower communication overheads by transmissions through different semantic communication networks with different bandwidth requirements. An improved metric θPSNR is proposed to evaluate the transmission accuracy of the novel semantic transmission network. Experimental results show that our proposed system achieves a significant performance improvement compared with existing approaches, namely, existing semantic communication approaches and the conventional approach without semantics.

Predictive value of intracranial high-density areas in neurological function

BACKGROUND Intracranial high-density areas(HDAs)have attracted considerable attention for predicting clinical outcomes;however,whether HDAs predict worse neurological function and mental health remains controversial and unclear,which requires further investigation.In this prospective study,96 patients with acute ischemic stroke(AIS)who accepted endovascular mechanical thrombectomy(EMT)were included.The enrolled patients underwent cranial computed tomography(CT)examination within 24 hours after EMT.Clinical data in terms of National Institutes of Health Stroke Scale(NIHSS),the 3-month modified Rankin Scale(mRS),self-rating depression scale(SDS),and self-rating anxiety scale(SAS)scores were collected and compared between patients with HDAs and non-HDAs and between patients with good and poor clinical prognosis.Compared to patients without HDAs,patients with HDAs presented severe neurological deficits(admission NIHSS score:18±3 vs 19±4),were more likely to have post-stroke disabilities(mRS<3:35%vs 62%),and suffered more severe depression(SDS score:58±16 vs 64±13)and anxiety disorder(SAS score:52±8 vs 59±10).Compared to patients with a good prognosis,patients with a poor prognosis presented severe neurological deficits(admission NIHSS score:17±4 vs 20±3),were more likely to have HDAs on CT images(64%vs 33%),and suffered more severe depression(SDS score:55±19 vs 65±11)and anxiety(SAS score:50±8 vs 58±12).Multivariate analysis revealed that HDAs were independent nega-tive prognostic factors.CONCLUSION In conclusion,HDAs on CT images predicted poor prognosis and severe depressive and anxiety symptoms in patients with AIS who underwent EMT.

Characterization of local chemical ordering and deformation behavior in high entropy alloys by transmission electron microscopy

Short-range ordering(SRO)is one of the most important structural features of high entropy alloys(HEAs).However,the chemical and structural analyses of SROs are very difficult due to their small size,complexed compositions,and varied locations.Transmission electron microscopy(TEM)as well as its aberration correction techniques are powerful for characterizing SROs in these compositionally complex alloys.In this short communication,we summarized recent progresses regarding characterization of SROs using TEM in the field of HEAs.By using advanced TEM techniques,not only the existence of SROs was confirmed,but also the effect of SROs on the deformation mechanism was clarified.Moreover,the perspective related to application of TEM techniques in HEAs are also discussed.

Deep Learning-Based Secure Transmission Strategy with Sensor-Transmission-Computing Linkage for Power Internet of Things

The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing linkage is proposed in this paper. The primary objective of this strategy is to maximize the confidentiality capacity of the system. To tackle this, an optimization problem is formulated, taking into consideration interruption probability and interception probability as constraints. To efficiently solve this optimization problem, a low-complexity algorithm rooted in deep reinforcement learning is designed, which aims to derive a suboptimal solution for the problem at hand. Ultimately, through simulation results, the validity of the proposed strategy in guaranteed communication security, stability, and timeliness is substantiated. The results confirm that the proposed intelligent security transmission strategy significantly contributes to the safeguarding of communication integrity, system stability, and timely data delivery.

Probing the Nucleation and Growth Kinetics of Bismuth Nanoparticles via In-situ Transmission Electron Microscopy

The nucleation and growth mechanism of nanoparticles is an important theory,which can guide the preparation of nanomaterials.However,it is still lacking in direct observation on the details of the evolution of intermediate state structure during nucleation and growth.In this work,the evolution process of bismuth nanoparticles induced by electron beam was revealed by in-situ transmission electron microscopy(TEM)at atomic scale.The experimental results demonstrate that the size,stable surface and crystallographic defect have important influences on the growth of Bi nanoparticles.Two non-classical growth paths including single crystal growth and polycrystalline combined growth,as well as,corresponding layer-by-layer growth mechanism along{012}stable crystal plane of Bi nanoparticles with dodecahedron structure were revealed by in-situ TEM directly.These results provide important guidance and a new approach for in-depth understanding of the nucleation and growth kinetics of nanoparticles.