Research Progress of Systemic Immune Inflammatory Index in Prostate Cancer

Prostate cancer has gradually risen to become the second most common cancer threatening men’s health, and prostate-specific antigen (PSA), as the main screening indicator for prostate cancer, has the defects of low specificity and insufficient diagnostic efficacy. As a novel inflammatory index based on neutrophil, lymphocyte and platelet counts, the systemic immune-inflammation index (SII) has recently become a more powerful biomarker for predicting the occurrence and progression of various malignancies. SII reflects the systemic inflammatory response of prostate cancer patients in a more balanced manner, and has higher predictive value than neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). High SII values are often associated with cancer progression and poor prognosis. This article reviews the research progress of SII in prostate cancer, in order to provide guidance for clinical practice.

Integrated in-memory sensor and computing of artificial vision system based on reversible bonding transition-induced nitrogen-doped carbon quantum dots (N-CQDs)

Carbon quantum dots (CQDs) have been used in memristors due to their attractive optical and electronic properties, which are considered candidates for brain-inspired computing devices. In this work, the performance of CQDs-based memristors is improved by utilizing nitrogen-doping. In contrast, nitrogen-doped CQDs (N-CQDs)-based optoelectronic memristors can be driven with smaller programming voltages (−0.6 to 0.7 V) and exhibit lower powers (78 nW/0.29 µW). The physical mechanism can be attributed to the reversible transition between C–N and C=N with lower binding energy induced by the electric field and the generation of photogenerated carriers by ultraviolet light irradiation, which adjusts the conductivity of the initial N-CQDs to implement resistance switching. Importantly, the convolutional image processing based on various cross kernels is efficiently demonstrated by stable multi-level storage properties. An N-CQDs-based optoelectronic reservoir computing implements impressively high accuracy in both no noise and various noise modes when recognizing the Modified National Institute of Standards and Technology (MNIST) dataset. It illustrates that N-CQDs-based memristors provide a novel strategy for developing artificial vision system with integrated in-memory sensor and computing.

Tackling application limitations of high-safetyγ-butyrolactone electrolytes:Exploring mechanisms and proposing solutions

Developing wide-temperature and high-safety lithium-ion batteries(LIBs)presents significant challenges attributed to the absence of suitable solvents possessing broad liquid range and non-flammability properties.γ-Butyrolactone(GBL)has emerged as a promising solvent;however,its incompatibility with graphite anode has hindered its application.This limitation necessitates a comprehensive investigation into the underlying mechanisms and potential solutions.In this study,we achieve a molecular-level understanding of the perplexing interphase formation process by employing in-situ spectroelectrochemical techniques and density function calculations.Our findings reveal that,even at high salt concentrations,GBL consistently occupies the primary Li^(+)solvation sheath,leading to extensive GBL decomposition and the formation of a high-impedance and inorganic-poor solid-electrolyte interphase(SEI)layer.Contrary to manipulating solvation structures,our research demonstrates that the utilization of filmforming additives with higher reduction potential facilitates the pre-establishment of a robust SEI film on the graphite anode.This approach effectively inhibits GBL decomposition and significantly enhances the battery's lifespan.This study provides the first reported intrinsic understanding of the unique GBLgraphite incompatibility and offers valuable insights for the development of wide-temperature and high-safety LIBs.

Image Inpainting Technique Incorporating Edge Prior and Attention Mechanism

Recently,deep learning-based image inpainting methods have made great strides in reconstructing damaged regions.However,these methods often struggle to produce satisfactory results when dealing with missing images with large holes,leading to distortions in the structure and blurring of textures.To address these problems,we combine the advantages of transformers and convolutions to propose an image inpainting method that incorporates edge priors and attention mechanisms.The proposed method aims to improve the results of inpainting large holes in images by enhancing the accuracy of structure restoration and the ability to recover texture details.This method divides the inpainting task into two phases:edge prediction and image inpainting.Specifically,in the edge prediction phase,a transformer architecture is designed to combine axial attention with standard self-attention.This design enhances the extraction capability of global structural features and location awareness.It also balances the complexity of self-attention operations,resulting in accurate prediction of the edge structure in the defective region.In the image inpainting phase,a multi-scale fusion attention module is introduced.This module makes full use of multi-level distant features and enhances local pixel continuity,thereby significantly improving the quality of image inpainting.To evaluate the performance of our method.comparative experiments are conducted on several datasets,including CelebA,Places2,and Facade.Quantitative experiments show that our method outperforms the other mainstream methods.Specifically,it improves Peak Signal-to-Noise Ratio(PSNR)and Structure Similarity Index Measure(SSIM)by 1.141~3.234 db and 0.083~0.235,respectively.Moreover,it reduces Learning Perceptual Image Patch Similarity(LPIPS)and Mean Absolute Error(MAE)by 0.0347~0.1753 and 0.0104~0.0402,respectively.Qualitative experiments reveal that our method excels at reconstructing images with complete structural information and clear texture details.Furthermore,our model exhibits impressive performance in terms of the number of parameters,memory cost,and testing time.

基于变形力监测数据的残余应力场推断和表征方法

残余应力是材料的基本属性之一,与零件的几何形状、尺寸稳定性和疲劳寿命直接相关。针对具有高精度要求的大型零件,其残余应力场的准确测量和预测一直是一个挑战。目前的残余应力场测量技术可以分为基于应变的破坏性方法和基于射线、声波等物理量的非破坏性方法,但均受限于测量效率和精度,且难以得到工件的整体残余应力场。针对以上问题,本文提出了一种基于加工过程中的变形力监测数据推断工件整体残余应力场的新方法。本方法通过能够反映去除材料后不平衡残余应力场整体效应的变形力推断零件的残余应力场。利用虚功原理建立了变形力与残余应力场之间的力学关系,并引入正则化方法求解整体残余应力场。理论验证和实际实验测试结果均表明,该方法对于大型结构件的残余应力场测量具有可靠的精度和灵活性。在数字化和智能制造的趋势下,该方法的基本原理为利用加工监测数据预测和补偿由残余应力引起的零件加工变形提供了重要参考。

A New Dynamics Analysis Model for Five-Axis Machining of Curved Surface Based on Dimension Reduction and Mapping

The equipment used in various fields contains an increasing number of parts with curved surfaces of increasing size.Five-axis computer numerical control(CNC)milling is the main parts machining method,while dynamics analysis has always been a research hotspot.The cutting conditions determined by the cutter axis,tool path,and workpiece geometry are complex and changeable,which has made dynamics research a major challenge.For this reason,this paper introduces the innovative idea of applying dimension reduction and mapping to the five-axis machining of curved surfaces,and proposes an efficient dynamics analysis model.To simplify the research object,the cutter position points along the tool path were discretized into inclined plane five-axis machining.The cutter dip angle and feed deflection angle were used to define the spatial position relationship in five-axis machining.These were then taken as the new base variables to construct an abstract two-dimensional space and establish the mapping relationship between the cutter position point and space point sets to further simplify the dimensions of the research object.Based on the in-cut cutting edge solved by the space limitation method,the dynamics of the inclined plane five-axis machining unit were studied,and the results were uniformly stored in the abstract space to produce a database.Finally,the prediction of the milling force and vibration state along the tool path became a data extraction process that significantly improved efficiency.Two experiments were also conducted which proved the accuracy and efficiency of the proposed dynamics analysis model.This study has great potential for the online synchronization of intelligent machining of large surfaces.

Experiment Combined with Picture Archiving and Communication System in the Practical Teaching of Medical Imaging

Objective:To explore the application effect of virtual simulation experiment combined with picture archiving and communication system(PACS)in medical imaging practical teaching.Methods:97 students from the medical imaging class of 2022 were divided into two groups;the control group(n=48)was taught by the traditional teaching method,whereas the research group was taught by virtual simulation experiment combined with PACS(n=49).The teaching achievements and teaching effects of the two groups were compared to define the advantages of the two teaching modes.Results:Initially,there were no significant differences in the basic theory,image analysis,report writing,and differential diagnosis scores between the two groups of students(P>0.05);however,after 16 weeks of teaching,the scores of the research group were better than those of the control group(P<0.05);the pass rate of students in the study group(93.88%)was higher than that in the control group(81.25%);the scores of students in the research group in terms of clinical inquiry skills,X-ray/computed tomography/magnetic resonance imaging(X-ray/CT/MRI)operation skills,and doctor-patient communication skills were significantly higher than those in the control group(P<0.05).Conclusion:In medical imaging practical teaching,the application of virtual simulation experiment combined with PACS can effectively address several problems in the traditional teaching mode,including the single teaching method,the single teaching content,and the lack of innovation,and,at the same time,improve students’basic theoretical knowledge,X-ray/CT/MRI operation skills,consultation skills,and doctor-patient communication skills,thereby effectively improving the teaching quality and learning effect.

Experiences of Fatigue at Sea—A Comparative Study in European and Chinese Shipping Industry

Fatigue has negative impacts on the general working population as well as on seafarers. In order to study seafarers’ fatigue, a questionnaire-base survey was conducted to gain information about potential risk factors for fatigue and construct indexes indicating fatigue. The study applies T-test to compare strata of seafarers to analyse work and sleep patterns in global seafaring. Qualitative analysis are also employed to explore the impacts of fatigue on seafarer’s occupational health and safety.

Highly enhanced visible-light photocatalytic hydrogen evolution on g-C_3N_4 decorated with vopc through π-π interaction

Photocatalytic H2 evolution reactions on pristine graphitic carbon nitrides(g-C3N4),as a promising approach for converting solar energy to fuel,are attractive for tackling global energy concerns but still suffer from low efficiencies.In this article,we report a tractable approach to modifying g-C3N4 with vanadyl phthalocyanine(VOPc/CN)for efficient visible-light-driven hydrogen production.A non-covalent VOPc/CN hybrid photocatalyst formed viaπ-πstacking interactions between the two components,as confirmed by analysis of UV-vis absorption spectra.The VOPc/CN hybrid photocatalyst shows excellent visible-light-driven photocatalytic performance and good stability.Under optimal conditions,the corresponding H2 evolution rate is nearly 6 times higher than that of pure g-C3N4.The role of VOPc in promoting hydrogen evolution activity was to extend the visible light absorption range and prevent the recombination of photoexcited electron-hole pairs effectively.It is expected that this facile modification method could be a new inspiration for the rational design and exploration of g-C3N4-based hybrid systems with strong light absorption and high-efficiency carrier separation.

锂-空气电池的实用化之路:规避二氧化碳负面效应

与其他的锂电池体系相比,锂-空气电池具有最高的理论比能量,被认为有潜力成为终极能量转换和储存装置。目前的锂-空气电池常常使用气体钢瓶提供纯氧气,而非空气中的氧气,这种电池设计极大降低了锂-空气电池的能量密度和实用性。然而,当空气作为锂-空气电池的氧气供给源时,二氧化碳作为杂质会引起严重的副反应,从而降低锂-空气电池的性能。要解决二氧化碳引起的副反应,理解其反应机制至关重要。本文综述了锂-空气电池中有关二氧化碳诱发的化学/电化学反应的研究进展;总结了可缓解二氧化碳负面效应的有效策略。此外,对二氧化碳选透膜材料和分离技术用于锂-空气电池进行了展望。

Influence of Axial Loads to Propagation Characteristics of the Elastic Wave in a Non-Uniform Shaft

The vibration propagates through the shaft in the form of elastic waves. The propagation characteristics of the elastic waves are a ected by the axial loads. The influence of the axial loads to the propagation characteristics of the elastic waves is studied in this paper. Firstly, the transfer matrix of the elastic waves for the non-uniform shaft with axial loads is deduced by combining the transfer matrix without axial load and the additional equation caused by the axial load. And then, a numerical method is used to study the influence of the axial load, non-uniformity and the rotating speed to the propagation characteristics of the elastic waves. It’s found that a new Stop Band will appear due to the axial force, and the central frequency of which will decrease as the increase of the force, while the band width of which remains the same. The central frequency of the new Stop Band will also increase as the increase of the cross-section area ratio;however, the rotating speed of the shaft doesn’t a ect the propagation characteristics of the elastic waves obviously. Finally, an experimental rig is built up for further study, even though there are some small local errors, the results of experiments match well with the numerical ones, which indicates the validation of the theoretical results. The result can help to study the influence of the axial load to the dynamics of a non-uniform shaft and help to reveal the vibration propagating mechanism in such a shaft.

An Initial Residual Stress Inference Method by Incorporating Monitoring Data and Mechanism Model

Initial residual stress is the main reason causing machining deformation of the workpiece,which has been deemed as one of the most important aspects of machining quality issues.The inference of the distribution of initial residual stress inside the blank has significant meaning for machining deformation control.Due to the principle error of existing residual stress detection methods,there are still challenges in practical applications.Aiming at the detection problem of the initial residual stress field,an initial residual stress inference method by incorporating monitoring data and mechanism model is proposed in this paper.Monitoring data during machining process is used to represent the macroscopic characterization of the unbalanced residual stress,and the finite element numerical model is used as the mechanism model so as to solve the problem that the analytic mechanism model is difficult to establish;the policy gradient approach is introduced to solve the gradient descent problem of the combination of learning model and mechanism model.Finally,the initial residual stress field is obtained through iterative calculation based on the fusing method of monitoring data and mechanism model.Verification results show that the proposed inference method of initial residual stress field can accurately and effectively reflect the machining deformation in the actual machining process.

Feedback Between Influent Condition Heterogeneity and Diversity of Bacterial Community in Bioreactor at Low Substrate Concentration

In order to investigate the effect of influent condition heterogeneity on diversity of the bacterial community,the degree of microbial resolution and effluent quality,biological treatment of micro-polluted source water is proposed. Scanning Electron Microscopy( SEM) analysis reflects that influent conditions change the morphologies of biofilm. Denaturing Gradient Gel Electrophoresis( DGGE) analysis shows differences of H values are due to succession of functional bacterial communities. Microbial resolution values and species identifications reveal organic carbon is the main cause of community differentiation and bacterial migration.

Luminescent characteristics of Tm^(3+)/Tb^(3+)/Eu^(3+) tri-doped Na_(5)Y_(9)F_(32) single crystals for white emission with high thermal stability

By using an improved Bridgman method,0.3 mol%Tm^(3+)/0.6 mol%Tb^(3+)/y mol%Eu^(3+)(y=0,0.4,0.6,0.8)doped Na_(5)Y_(9)F_(32)single crystals were prepared.The x-ray diffraction,excitation spectra,emission spectra and fluorescence decay curves were used to explore the crystal structure and optical performance of the obtained samples.When excited by 362 nm light,the cool white emission was realized by Na_(5)Y_(9)F_(32)single crystal triply-doped with 0.3 mol%Tm^(3+)/0.6 mol%Tb^(3+)/0.8 mol%Eu^(3+),in which the Commission Internationale de l’Eclairage(CIE)chromaticity coordinate was(0.2995,0.3298)and the correlated color temperature(CCT)was 6586 K.The integrated normalized emission intensity of the tridoped single crystal at 448 K could keep 62%of that at 298 K.The internal quantum yield(QY)was calculated to be~15.16%by integrating spheres.These results suggested that the single crystals tri-doped with Tm^(3+),Tb^(3+)and Eu^(3+)ions have a promising potential application for white light-emitting diodes(w-LEDs).

Reinforcement learning method for machining deformation control based on meta-invariant feature space

Precise control of machining deformation is crucial for improving the manufacturing quality of structural aerospace components.In the machining process,different batches of blanks have different residual stress distributions,which pose a significant challenge to machining deformation control.In this study,a reinforcement learning method for machining deformation control based on a meta-invariant feature space was developed.The proposed method uses a reinforcement-learning model to dynamically control the machining process by monitoring the deformation force.Moreover,combined with a meta-invariant feature space,the proposed method learns the internal relationship of the deformation control approaches under different stress distributions to achieve the machining deformation control of different batches of blanks.Finally,the experimental results show that the proposed method achieves better deformation control than the two existing benchmarking methods.

Analysis of Air Pollutants in Xiong’an New Area Based on MATLAB Grey Model

The purpose of this paper is to study the air pollutants in Xiong’an New Area based on MATLAB grey model [1]. From 2011 to 2016, the results of sulfur dioxide (SO2), nitrogen dioxide (NO2) and inhalable particulate matter (PM1O) detected at monitoring points in the three counties of Xiong’an were analyzed. According to the national environmental air quality standard [2], the air quality in Xiong’an New Area was reasonably evaluated based on grey model in MATLAB. Judging from the weight of pollution factors in the model, sulfur dioxide (SO2) is the controlling factor of air quality in Xiong’an New Area, and the weight of nitrogen dioxide (NO2) gradually increases. The main sources of the three pollutants were obtained by comprehensive data analysis, and a grey model was established according to the mass concentration of the main air pollutants, and the grey forecasting model was tested. The experimental results show that the model can be effectively applied to the forecasting of ambient air quality. On this basis, the present situation of atmospheric environmental quality in Xiong’an New Area and suggestions for improvement are obtained.

Three-dimensional macroscopic absorbents: From synergistic effects to advanced multifunctionalities

The accelerated arriving of 5G era has brought a new round of intelligent transformation which will completely emancipate smart terminal devices.While the subsequent deleterious effect of electromagnetic wave on electronic devices is increasingly serious,driving the growth of next-generation electromagnetic wave absorbents.As a tactful combination of components and structures,three-dimensional(3D)macroscopic absorbents with fascinating synergy afford exceptional electromagnetic wave absorption,and tremendous efforts have been devoted to this investigation.However,in terms of macroscopic absorbents and their synergistic effect,few reviews are proposed to comb the latest achievements and detailed synergy.This review article focuses on the synergistic effect of macro-architectured absorbents mainly including structure-induced synergy,structure-components synergy,and multiple-components induced synergy.And then the potential construction principles and strategies of macroscopic absorbents are combed.Significantly,the key information for structures and components manipulation including nano-micro design and components regulation is further dissected by critically selected cutting-edge 3D macroscopic absorbents.Moreover,a brief summary of multifunctional electromagnetic wave absorbents(EWAs)-based macroscopic structures is presented.Finally,the development prospects and challenges of these materials are discussed.

The resistance switching performance of the memristor improved effectively by inserting carbon quantum dots(CQDs)for digital information processing

As an emerging information device that adapts to development of the big data era,memristor has attracted much attention due to its advantage in processing massive data.However,the nucleation and growth of conductive filaments often exhibit randomness and instability,which undoubtedly leads to a wide and discrete range of switching parameters,damaging the electrical performance of device.In this work,a strategy of inserting carbon quantum dots(CQDs)into graphene oxide(GO)resistance layer is utilized to improve the stability of the switching parameters and the reliability of the device is improved.Compared with GO-based devices,GO/CQDs/GO-based devices exhibit a more stable resistance switching curve,low power,lower and more concentrated threshold voltage parameters with lower variation coefficient,faster switching speed,and more stable retention and endurance.The cause-inducing performance improvement may be attributed to the local electric field generated by CQDs in resistance switching that effectively guides the formation and rupture of conductive filaments,which optimizes the effective migration distance of Ag^(+),thereby improving the uniformity of resistance switching.Additionally,a convolutional neural network model is constructed to identify the CIFAR-10 data set,showing the high recognition accuracy of online and offline learning.The cross-kernel structure is used to further implement convolutional image processing through multiplication and accumulation operations.This work provides a solution to improve the performance of memristors,which can contribute to developing digital information processing.

主动防御的双结构网络

网络空间安全攸关人类福祉与国家利益,但当前网络空间安全存在重大挑战:互联网体系结构具有优越的互联互通性和开放性,但也导致其安全问题无法彻底解决,处处设防却处处难防;传统安全防御机制依赖安全威胁的先验信息,难以应对不断演化的安全威胁.为了应对上述挑战,本文提出了一种新型网络空间安全防御理论体系:构建与互联网主结构平行的"动态、异构、冗余"的基于播存思想的次结构网络,辅助现有互联网体系结构而形成双结构网络;提出不依赖安全威胁先验信息的数据与知识联合驱动的新型主动防御机理;提出双网透明接入与前置主动防御技术等关键支撑技术.为改变我国网络空间安全领域受制于人、被动防御的现状,本文试图从演进式改变网络体系结构角度提出完备解决方案.

基于高铁酸盐的水污染控制技术研究进展

高铁酸盐(FeO4^2-, Fe(Ⅵ))是一种同时具有氧化、吸附、絮凝、杀菌、消毒等多种功能的绿色水处理剂,因独特的环境友好特性而受到人们越来越多的关注.本文主要介绍了Fe(Ⅵ)的氧化特性及机理,综述了近年来基于Fe(Ⅵ)的水处理技术研究进展,包括Fe(Ⅵ)氧化新兴有机污染物及强化方面的研究、Fe(Ⅵ)杀菌消毒作用及其氧化过程中消毒副产物生成情况、Fe(Ⅵ)氧化和自分解产生的新生态铁氧化物的特性及其去除重(类)金属的机理,并对未来的研究方向和发展趋势进行了展望.