Research and Analysis of Grammatical Error Correction Technology for Chinese Documents

With the widespread use of Chinese globally, the number of Chinese learners has been increasing, leading to various grammatical errors among beginners. Additionally, as domestic efforts to develop industrial information grow, electronic documents have also proliferated. When dealing with numerous electronic documents and texts written by Chinese beginners, manually written texts often contain hidden grammatical errors, posing a significant challenge to traditional manual proofreading. Correcting these grammatical errors is crucial to ensure fluency and readability. However, certain special types of text grammar or logical errors can have a huge impact, and manually proofreading a large number of texts individually is clearly impractical. Consequently, research on text error correction techniques has garnered significant attention in recent years. The advent and advancement of deep learning have paved the way for sequence-to-sequence learning methods to be extensively applied to the task of text error correction. This paper presents a comprehensive analysis of Chinese text grammar error correction technology, elaborates on its current research status, discusses existing problems, proposes preliminary solutions, and conducts experiments using judicial documents as an example. The aim is to provide a feasible research approach for Chinese text error correction technology.

Evolutionary Particle Swarm Optimization Algorithm Based on Collective Prediction for Deployment of Base Stations

The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.

A Facile Li_(2)TiO_(3) Surface Modification to Improve the Structure Stability and Electrochemical Performance of Full Concentration Gradient Li-Rich Oxides

Full concentration gradient lithium-rich layered oxides are catching lots of interest as the next generation cathode for lithium-ion batteries due to their high discharge voltage,reduced voltage decay and enhanced rate performance,whereas the high lithium residues on its surface impairs the structure stability and long-term cycle performance.Herein,a facile multifunctional surface modification method is implemented to eliminate surface lithium residues of full concentration gradient lithium-rich layered oxides by a wet chemistry reaction with tetrabutyl titanate and the post-annealing process.It realizes not only a stable Li_(2)TiO_(3)coating layer with 3D diffusion channels for fast Li^(+)ions transfer,but also dopes partial Ti^(4+)ions into the sub-surface region of full concentration gradient lithium-rich layered oxides to further strengthen its crystal structure.Consequently,the modified full concentration gradient lithium-rich layered oxides exhibit improved structure stability,elevated thermal stability with decomposition temperature from 289.57℃to 321.72℃,and enhanced cycle performance(205.1 mAh g^(-1)after 150 cycles)with slowed voltage drop(1.67 mV per cycle).This work proposes a facile and integrated modification method to enhance the comprehensive performance of full concentration gradient lithium-rich layered oxides,which can facilitate its practical application for developing higher energy density lithium-ion batteries.

Nonvolatile ferroelectric control of electronic properties of Bi_(2)Te_(3)

Nonvolatile electric-field control of the unique physical characteristics of topological insulators (TIs) is essential forthe fundamental research and development of practical electronic devices. Electrically tunable transport properties throughgating materials have been extensively investigated. However, the relatively weak and volatile tunability limits its practicalapplications in spintronics. Here, we demonstrate the nonvolatile electric-field control of Bi_(2)Te_(3) transport properties viaconstructing ferroelectric Rashba architectures, i.e., 2D Bi_(2)Te_(3)/a-In_(2)Se_(3) ferroelectric field-effect transistors. By switchingthe polarization states of a-In2Se3, the Fermi level, resistance, Fermi wave vector, carrier mobility, carrier density andmagnetoresistance (MR) of the Bi_(2)Te_(3) film can be effectively modulated. Importantly, a shift of the Fermi level towards aband gap with a surface state occurs as switching to a negative polarization state, the contribution of the surface state to theconductivity then increases, thereby increasing the carrier mobility and electron coherence length significantly, resulting inthe enhanced weak anti-localization (WAL) effect. These results provide a nonvolatile electric-field control method to tunethe electronic properties of TI and can further extend to quantum transport properties.

Efficient flexible dye-sensitized solar cells from rear illumination based on different morphologies of titanium dioxide photoanode

The TiO_(2) with nanoparticles(NPs),nanowires(NWs),nanorods(NRs)and nanotubes(NTs)structures were prepared by using a in-situ hydrothermal technique,and then proposed as a photoanode for flexible dye-sensitized solar cell(FDSSC).The influences of the morphology of TiO_(2) on the photovoltaic performances of FDSSCs were investigated.Under rear illumination of 100 mW·cm^(−2),the power conversion efficiencies of FDSSCs achieved 6.96%,7.36%,7.65%,and 7.83%with the TiO_(2) photoanodes of NPs,NWs,NRs,and NTs and PEDOT counter electrode.The FDSSCs based on TiO_(2) NRs and NTs photoanodes have higher short circuit current densities and power conversion efficiencies than that of the others.The enhanced power conversion efficiency is responsible for their nanotubes and rod-shaped ordered structures,which are more beneficial to transmission of electron and hole in semiconductor compared to the TiO_(2) nanoparticles and nanowires disordered structure.

Machine learning optimization strategy of shaped charge liner structure based on jet penetration efficiency

Shaped charge liner(SCL)has been extensively applied in oil recovery and defense industries.Achieving superior penetration capability through optimizing SCL structures presents a substantial challenge due to intricate rate-dependent processes involving detonation-driven liner collapse,high-speed jet stretching,and penetration.This study introduces an innovative optimization strategy for SCL structures that employs jet penetration efficiency as the primary objective function.The strategy combines experimentally validated finite element method with machine learning(FEM-ML).We propose a novel jet penetration efficiency index derived from enhanced cutoff velocity and shape characteristics of the jet via machine learning.This index effectively evaluates the jet penetration performance.Furthermore,a multi-model fusion based on a machine learning optimization method,called XGBOOST-MFO,is put forward to optimize SCL structure over a large input space.The strategy's feasibility is demonstrated through the optimization of copper SCL implemented via the FEM-ML strategy.Finally,this strategy is extended to optimize the structure of the recently emerging CrMnFeCoNi high-entropy alloy conical liners and hemispherical copper liners.Therefore,the strategy can provide helpful guidance for the engineering design of SCL.

Investigation of Power Density Amplification in Stacked Triboelectric Nanogenerators

In engineering practice,the output performance of contact separation TENGs(CS-TENGs)increases with the increase of tribo-pair area,which includes increasing the size of single layer CS-TENGs(SCS-TENGs)or the number of units(zigzag TENGs).However,such two strategies show significant differences in output power and power density.In this study,to seek a universal CS-TENG design solution,the output performance of a SCS-TENG and a zigzag TENG(Z-TENG)is systematically compared,including voltage,current,transferred charge,instantaneous power density,and charging power density.The relationship between contact area and output voltages is explored,and the output voltage equation is fitted.The experimental results reveal that SCS-TENGs yield better performance than Z-TENGs in terms of voltage,power,and power density under the same total contact area.Z-TENGs show energy loss during the transfer of mechanical energy,and such loss is aggravated by the increasing number of units.The instantaneous peak power of the SCS-TENG is up to 22 times that of the Z-TENG(45 cm^(2)).Furthermore,the power density of capacitor charging of SCS-TENGs is 131%of that of Z-TENGs,which are relatively close.Z-TENG is a feasible alternative when the working space is limited.

Structure and electrical properties of polysilicon films doped with ammonium tetraborate tetrahydrate

Here,p-type polysilicon films are fabricated by ex-situ doping method with ammonium tetraborate tetrahydrate(ATT)as the boron source,named ATT-pPoly.The effects of ATT on the properties of polysilicon films are comprehensively analyzed.The Raman spectra reveal that the ATT-pPoly film is composed of grain boundary and crystalline regions.The preferred orientation is the(111)direction.The grain size increases from 16−23 nm to 21−47 nm,by~70%on average.Comparing with other reported films,Hall measurements reveal that the ATT-pPoly film has a higher carrier concentration(>10^(20)cm^(−3))and higher carrier mobility(>30 cm2/(V·s)).The superior properties of the ATT-pPoly film are attributed to the heavy doping and improved grain size.Heavy doping property is proved by the mean sheet resistance(Rsheet,m)and distribution profile.The R_(sheet,m)decreases by more than 30%,and it can be further decreased by 90%if the annealing temperature or duration is increased.The boron concentration of ATT-pPoly film annealed at 950℃ for 45 min is~3×10^(20)cm^(−3),and the distribution is nearly the same,except near the surface.Besides,the standard deviation coefficient(σ)of Rsheet,m is less than 5.0%,which verifies the excellent uniformity of ATT-pPoly film.

Bibliometric analysis of hotspots and trends of global myopia research

AIM:To gain insights into the global research hotspots and trends of myopia.METHODS:Articles were downloaded from January 1,2013 to December 31,2022 from the Science Core Database website and were mainly statistically analyzed by bibliometrics software.RESULTS:A total of 444 institutions in 87 countries published 4124 articles.Between 2013 and 2022,China had the highest number of publications(n=1865)and the highest H-index(61).Sun Yat-sen University had the highest number of publications(n=229)and the highest H-index(33).Ophthalmology is the main category in related journals.Citations from 2020 to 2022 highlight keywords of options and reference,child health(pediatrics),myopic traction mechanism,public health,and machine learning,which represent research frontiers.CONCLUSION:Myopia has become a hot research field.China and Chinese institutions have the strongest academic influence in the field from 2013 to 2022.The main driver of myopic research is still medical or ophthalmologists.This study highlights the importance of public health in addressing the global rise in myopia,especially its impact on children’s health.At present,a unified theoretical system is still needed.Accurate surgical and therapeutic solutions must be proposed for people with different characteristics to manage and intervene refractive errors.In addition,the benefits of artificial intelligence(AI)models are also reflected in disease monitoring and prediction.

Development and research status of intelligent ophthalmology in China

This paper analyzes the current status,technological developments,academic exchange platforms,and future challenges and solutions in the field of intelligent ophthalmology(IO)in China.In terms of technology,significant progress has been made in various areas,including diabetic retinopathy,fundus image analysis,quality assessment of medical artificial intelligence products,clinical research methods,technical evaluation,and industry standards.Researchers continually enhance the safety and standardization of IO technology by formulating a series of clinical application guidelines and standards.The establishment of domestic and international academic exchange platforms provides extensive collaboration opportunities for professionals in various fields,and various academic journals serve as publication platforms for IO research.However,challenges such as technological innovation,data privacy and security,lagging regulations,and talent shortages still pose obstacles to future development.To address these issues,future efforts should focus on strengthening technological research and development,regulatory framework construction,talent cultivation,and increasing patient awareness and acceptance of new technologies.By comprehensively addressing these challenges,IO in China is poised to further lead the industry’s development on a global scale,bringing more innovation and convenience to the field of ophthalmic healthcare.

Guidelines on clinical research evaluation of artificial intelligence in ophthalmology(2023)

With the upsurge of artificial intelligence(AI)technology in the medical field,its application in ophthalmology has become a cutting-edge research field.Notably,machine learning techniques have shown remarkable achievements in diagnosing,intervening,and predicting ophthalmic diseases.To meet the requirements of clinical research and fit the actual progress of clinical diagnosis and treatment of ophthalmic AI,the Ophthalmic Imaging and Intelligent Medicine Branch and the Intelligent Medicine Committee of Chinese Medicine Education Association organized experts to integrate recent evaluation reports of clinical AI research at home and abroad and formed a guideline on clinical research evaluation of AI in ophthalmology after several rounds of discussion and modification.The main content includes the background and method of developing this guideline,an introduction to international guidelines on the clinical research evaluation of AI,and the evaluation methods of clinical ophthalmic AI models.This guideline introduces general evaluation methods of clinical ophthalmic AI research,evaluation methods of clinical ophthalmic AI models,and commonly-used indices and formulae for clinical ophthalmic AI model evaluation in detail,and amply elaborates the evaluation methods of clinical ophthalmic AI trials.This guideline aims to provide guidance and norms for clinical researchers of ophthalmic AI,promote the development of regularization and standardization,and further improve the overall level of clinical ophthalmic AI research evaluations.

Plasmon-enhanced nanosoldering of silver nanoparticles for high-conductive nanowires electrodes

The silver nanowires(Ag NWs)electrodes,which consist of incompact Ag nanoparticles(NPs)formed by multi-photon photoreduction,usually have poor conductivities.An effective strategy for enhancing conductivity of the Ag NWs elec-trodes is plasmon-enhanced nanosoldering(PLNS)by laser irradiation.Here,plasmon-enhanced photothermal effect is used to locally solder Ag NPs and then aggregates of these NPs grow into large irregular particles in PLNS process.Fi-nite element method(FEM)simulations indicate that the soldering process is triggered by localized surface plasmon-in-duced electric field enhancement at“hot-spots”.The effectiveness of PLNS for enhancing conductivity depends on laser power density and irradiation time.By optimizing the conditions of PLNS,the electrical conductivity of Ag NWs is signific-antly enhanced and the conductivityσs is increased to 2.45×107 S/m,which is about 39%of the bulk Ag.This PLNS of Ag NWs provides an efficient and cost-effective technique to rapidly produce large-area metal nanowire electrodes and capacitors with high conductivity,excellent uniformity,and good flexibility.

Phylogenetic relationships of the zokor genus Eospalax(Mammalia,Rodentia,Spalacidae)inferred from whole-genome analyses,with description of a new species endemic to Hengduan Mountains

Zokors in the genus Eospalax,which are endemic to northern and western China,are subterranean rodents that inhabit various niches,including grasslands,high-altitude meadows,forests,and farmlands.Six species in Eospalax were described a century ago but their taxonomy and phylogeny remain controversial.In this study,we performed high-depth whole-genome sequencing of 47 zokor samples,comprising all six previously described species.Genomic analyses revealed a reliable and robust phylogeny of Eospalax and supported the validity of the six named species.According to the inferred phylogenetic relationships,Eospalax first divergent into two clades in the early Pliocene(ca.4.68 million years ago(Ma)),one inhabiting the highaltitude Qinghai-Xizang(Tibet)Plateau(QTP)and adjacent regions,and the another inhabiting the lowaltitude Loess Plateau and Qinling-Daba Mountains.The most recent divergences occurred between E.baileyi and E.smithii and between E.rufescens and E.rothschildi in the late Pliocene(ca.2.09 and 2.19 Ma,respectively).We also collected specimens of zokors in the southern Hengduan Mountains(Muli County,Sichuan Province),far from the known distributions of all other zokors.Morphological and molecular analyses strongly suggested that the specimens represent a new species,formally described here as Eospalax muliensis sp.nov.The new species belongs to the high-altitude clade and diverged from closely related species(ca.4.22 Ma)shortly after the first divergence in Eospalax.Interestingly,Eospalax muliensis sp.nov.possesses more supposedly plesiomorphic characters,suggesting a possible origin of the genus in the Hengduan Mountains.

Engineering Multi‑field‑coupled Synergistic Ion Transport System Based on the Heterogeneous Nanofluidic Membrane for High‑Efficient Lithium Extraction

The global carbon neutrality strategy brings a wave of rechargeable lithium‐ion batteries technique development and induces an ever-growing consumption and demand for lithium(Li).Among all the Li exploitation,extracting Li from spent LIBs would be a strategic and perspective approach,especially with the low energy consumption and eco-friendly membrane separation method.However,current membrane separation systems mainly focus on monotonous membrane design and structure optimization,and rarely further consider the coordination of inherent structure and applied external field,resulting in limited ion transport.Here,we propose a heterogeneous nanofluidic membrane as a platform for coupling multi-external fields(i.e.,lightinduced heat,electrical,and concentration gradient fields)to construct the multi-field-coupled synergistic ion transport system(MSITS)for Li-ion extraction from spent LIBs.The Li flux of the MSITS reaches 367.4 mmol m^(−2)h^(−1),even higher than the sum flux of those applied individual fields,reflecting synergistic enhancement for ion transport of the multi-field-coupled effect.Benefiting from the adaptation of membrane structure and multi-external fields,the proposed system exhibits ultrahigh selectivity with a Li^(+)/Co^(2+)factor of 216,412,outperforming previous reports.MSITS based on nanofluidic membrane proves to be a promising ion transport strategy,as it could accelerate ion transmembrane transport and alleviate the ion concentration polarization effect.This work demonstrated a collaborative system equipped with an optimized membrane for high-efficient Li extraction,providing an expanded strategy to investigate the other membrane-based applications of their common similarities in core concepts.

Trade-offs between ion-conducting and mechanical properties: The case of polyacrylate electrolytes

Polymer electrolytes(PEs)have been long recognized as the key materials to enable energy-dense batteries and render flexible energy devices practically viable,owing to their chemical and mechanical reliability.However,much of their promise is yet to be realized.The roomtemperature ion conductivity of existing PEs still falls short of the implementation criterion of 10^(-4) S cm^(-1) on the promise of acceptable mechanical properties,thereby precluding their practical application.The twin but inversely related duties of polymers,that is,functioning as both an ion-conducting medium and a structural backbone,underlie this issue but are less elucidated systematically.The polyacrylate(PA)family is among promising polymer matrices on account of ester polarity,electrode compatibility,chemical tunability,and mechanical durability.The extensive applicability of PA in plasticized gels,dry solids,and emerging composites makes PA-based PEs representative to illustrate the trade-off between ion conduction and mechanical strength.We herein seek to outline the stated long-standing conflict exemplified by PA-based PEs,focusing on crucial strategies toward balancing and reconciling the two mutually exclusive properties,with the intention of offering designing guidelines for next-generation PEs.

The effect of gravity on self-similarity of Worthington jet after water entry of a two-dimensional wedge

The effect of gravity on the self-similarity of jet shape at late stage of Worthington jet development is investigated by experiment in the study.In addition,the particle image velocimetry(PIV)method is introduced to analyze the development of flow field.There is a linear scaling regarding the axial velocity of the jet and the scaling coefficient increases with the Froude number.

Parameter optimization of control system design for uncertain wireless power transfer systems using modified genetic algorithm

The closed-loop wireless power transfer(WPT)system can realize constant voltage output in the presence of perturbation.However,the parameter design of the controller is a difficult problem.The traditional trial-and-error method is time-consuming and difficult to find optimal parameters.A parameter optimization strategy of control systems for uncertain WPT systems using the modified genetic algorithm(MGA)is proposed.Firstly,because the system has different characteristics at different periods,the simulation process is divided into three stages.The first one is the start-up stage,in which we mainly consider the overshoot and the rate of the voltage rise.The second one is the tracking stage,in which the tracking time and switching loss are mainly considered.The third one is the stabilisation stage,in which the steady-state error and switching loss are mainly considered.Secondly,three cost functions are designed according to the characteristics of the three stages,and then the optimal controller parameters of each stage are obtained by using MGA.Finally,the effectiveness of the proposed method is verified by simulation.The optimization results show that compared with the previous parameter optimization method,the optimal controller parameters obtained by the proposed method make the WPT system achieve better performance.

Demands and technical developments of clinical flow cytometry with emphasis in quantitative,spectral,and imaging capabilities

As the gold-standard method for single-cell analysis,flow cytometry enables high-throughput and multiple-parameter characterization of individual biological cells.This review highlights the demands for clinical flow cytometry in laboratory hematology(e.g.,diagnoses of minimal residual disease and various types of leukemia),summarizes state-of-the-art clinical flow cytometers(e.g.,FACSLyricTMby Becton Dickinson,DxFLEX by Beckman Coulter),then considers innovative technical improvements in flow cytometry(including quantitative,spectral,and imaging approaches)to address the limitations of clinical flow cytometry in hematology diagnosis.Finally,driven by these clinical demands,future developments in clinical flow cytometry are suggested.

Smart palm-size optofluidic hematology analyzer for automated imaging-based leukocyte concentration detection

A critical function of flow cytometry is to count the concentration of blood cells,which helps in the diagnosis of certain diseases.However,the bulky nature of commercial flow cytometers makes such tests only available in hospitals or laboratories,hindering the spread of point-of-care testing(POCT),especially in underdeveloped areas.Here,we propose a smart Palm-size Optofluidic Hematology Analyzer based on a miniature fluorescence microscope and a microfluidic platform to lighten the device to improve its portability.This gadget has a dimension of 35×30×80 mm and a mass of 39 g,less than 5%of the weight of commercially available flow cytometers.Additionally,automatic leukocyte concentration detection has been realized through the integration of image processing and leukocyte counting algorithms.We compared the leukocyte concentration measurement between our approach and a hemocytometer using the Passing-Bablok analysis and achieved a correlation coefficient of 0.979.Through Bland-Altman analysis,we obtained the relationship between their differences and mean measurement values and established 95%limits of agreement,ranging from−0.93×10^(3)to 0.94×10^(3)cells/μL.We anticipate that this device can be used widely for monitoring and treating diseases such as HIV and tumors beyond hospitals.

Research on Facial Fatigue Detection of Drivers with Multi-feature Fusion

In order to solve the shortcomings of current fatigue detection methods such as low accuracy or poor real-time performance,a fatigue detection method based on multi-feature fusion is proposed.Firstly,the HOG face detection algorithm and KCF target tracking algorithm are integrated and deformable convolutional neural network is introduced to identify the state of extracted eyes and mouth,fast track the detected faces and extract continuous and stable target faces for more efficient extraction.Then the head pose algorithm is introduced to detect the driver’s head in real time and obtain the driver’s head state information.Finally,a multi-feature fusion fatigue detection method is proposed based on the state of the eyes,mouth and head.According to the experimental results,the proposed method can detect the driver’s fatigue state in real time with high accuracy and good robustness compared with the current fatigue detection algorithms.