Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

Optimization Techniques for GPU-Based Parallel Programming Models in High-Performance

This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.

Expansion Performance and Microstructure of High-performance Concrete using Differently Scaled MgO Agents and Mineral Powder

To investigate the assumptions proposed in this paper,the evolution law governing the strength and expansion performance of MgO and nano-MgO micro-expansive concrete in the environment of mineral powder was firstly observed in this study.Secondly,SEM,XRD,and TG-DSC microscopic tests were conducted to reveal the effects of the active mineral-powder admixture on the hydration degree and expansion performance of MgO and nano-MgO in HPC.Our experimental results successfully verified our hypothesis,which indicated that the expansion performance of macro-MgO and nano-MgO was indeed depressed by the addition of active mineral power admixtures,even though the mechanical property of concrete composites was effectively improved.Furthermore,the hydration test also demonstrated the negative interference on the mineral powders,which was induced by the expansion agents.It is found the amounts of hydrates tend to decrease because the mineral powder ratio reaches and exceeds 40%.Moreover,it is also concluded the effect of expansion agents is governed by the alkalinity cement paste,especially for the nano-MgO.In other words,the expansion performance of nano-MgO will vary more obviously with the hydration process,than MgO.The results of this study provide that effective experimental and theoretical data support the hydration-inhibition mechanism of magnesium expansive agents.

SQL Server性能优化的技术分析

随着客户端/服务器技术和多层架构的进步,系统效率问题日益引发广泛讨论。由于缺乏数据库管理系统(DBMS)提供的优化方法和工具,以及基于微软技术的数据库管理员和应用程序开发人员的知识,无法对设计和服务执行系统进行优化。文章回顾了提高SQL Server实例性能时需要考虑的目标,并阐述了用于优化查询的技术。

Exploring High-Performance Architecture for Data Center Networks

As a critical infrastructure of cloud computing,data center networks(DCNs)directly determine the service performance of data centers,which provide computing services for various applications such as big data processing and artificial intelligence.However,current architectures of data center networks suffer from a long routing path and a low fault tolerance between source and destination servers,which is hard to satisfy the requirements of high-performance data center networks.Based on dual-port servers and Clos network structure,this paper proposed a novel architecture RClos to construct high-performance data center networks.Logically,the proposed architecture is constructed by inserting a dual-port server into each pair of adjacent switches in the fabric of switches,where switches are connected in the form of a ring Clos structure.We describe the structural properties of RClos in terms of network scale,bisection bandwidth,and network diameter.RClos architecture inherits characteristics of its embedded Clos network,which can accommodate a large number of servers with a small average path length.The proposed architecture embraces a high fault tolerance,which adapts to the construction of various data center networks.For example,the average path length between servers is 3.44,and the standardized bisection bandwidth is 0.8 in RClos(32,5).The result of numerical experiments shows that RClos enjoys a small average path length and a high network fault tolerance,which is essential in the construction of high-performance data center networks.

Python Server Page Performance Analysis and Modeling

Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.

FedAdaSS: Federated Learning with Adaptive Parameter Server Selection Based on Elastic Cloud Resources

The rapid expansion of artificial intelligence(AI)applications has raised significant concerns about user privacy,prompting the development of privacy-preserving machine learning(ML)paradigms such as federated learning(FL).FL enables the distributed training of ML models,keeping data on local devices and thus addressing the privacy concerns of users.However,challenges arise from the heterogeneous nature of mobile client devices,partial engagement of training,and non-independent identically distributed(non-IID)data distribution,leading to performance degradation and optimization objective bias in FL training.With the development of 5G/6G networks and the integration of cloud computing edge computing resources,globally distributed cloud computing resources can be effectively utilized to optimize the FL process.Through the specific parameters of the server through the selection mechanism,it does not increase the monetary cost and reduces the network latency overhead,but also balances the objectives of communication optimization and low engagement mitigation that cannot be achieved simultaneously in a single-server framework of existing works.In this paper,we propose the FedAdaSS algorithm,an adaptive parameter server selection mechanism designed to optimize the training efficiency in each round of FL training by selecting the most appropriate server as the parameter server.Our approach leverages the flexibility of cloud resource computing power,and allows organizers to strategically select servers for data broadcasting and aggregation,thus improving training performance while maintaining cost efficiency.The FedAdaSS algorithm estimates the utility of client systems and servers and incorporates an adaptive random reshuffling strategy that selects the optimal server in each round of the training process.Theoretical analysis confirms the convergence of FedAdaSS under strong convexity and L-smooth assumptions,and comparative experiments within the FLSim framework demonstrate a reduction in training round-to-accuracy by 12%–20%compared to the Federated Averaging(FedAvg)with random reshuffling method under unique server.Furthermore,FedAdaSS effectively mitigates performance loss caused by low client engagement,reducing the loss indicator by 50%.

A Design of an SMTP Email Server

This study developed a mail server program using Socket API and Python.The program uses the Hypertext Transfer Protocol(HTTP)to receive emails from browser clients and forward them to actual email service providers via the Simple Mail Transfer Protocol(SMTP).As a web server,it handles Transmission Control Protocol(TCP)connection requests from browsers,receives HTTP commands and email data,and temporarily stores the emails in a file.Simultaneously,as an SMTP client,the program establishes a TCP connection with the actual mail server,sends SMTP commands,and transmits the previously saved emails.In addition,we also analyzed security issues and the efficiency and availability of this server,providing insights into the design of SMTP mail servers.

Excel+SQL Server在实验成绩信息管理中的应用研究

深入探讨了如何利用Excel和SQL Server集成化地管理和分析大学物理实验成绩信息。通过建立数据库、导入导出数据、数据查询与分析及使用Excel的数据透视表和图表功能,可以高效地管理实验成绩数据,进而深入分析学生的学习情况和教学效果。

Measurement and analysis of defects in high-performance concrete with three-dimensional micro-computer tomography

In order to investigate the effects of two mineral admixtures （i. e., fly ash and ground slag）on initial defects existing in concrete microstructures, a high-resolution X-ray micro-CT（ micro-focus computer tomography）is employed to quantitatively analyze the initial defects in four series of highperformance concrete （HPC）specimens with additions of different mineral admixtures. The nigh-resolution 3D images of microstructures and filtered defects are reconstructed by micro- CT software. The size distribution and volume fractions of initial defects are analyzed based on 3D and 2D micro-CT images. The analysis results are verified by experimental results of watersuction tests. The results show that the additions of mineral admixtures in concrete as cementitious materials greatly change the geometrical properties of the microstructures and the spatial features of defects by physical-chemistry actions of these mineral admixtures. This is the major cause of the differences between the mechanical behaviors of HPC with and without mineral admixtures when the water-to-binder ratio and the size distribution of aggregates are constant.

Preliminary Studies on High-performance Liquid Chro-matography Chemiluminescence Determination of theSaturated Fatty Acids(C_(16) C_(18))in Human Serum

The peroxyoxalate chemiluminescence(CL)detection of fatty acids in human se- rum combined with high-performance liquid chromatography (HPLC)is described.Some fatty acids in serum were extracted with a 1 :1(v/v)mixture of chloroform-n-heptane.2-(4-Hydrazinocarbonyl- phenyl)-4,5-diphenylimidazole (HCPI) was used as a fluorescent labelling reagent of the fatty acids. The labelling reaction was carried out at 30℃ for 1 h at pH 6.5 and the resulting reaction mixture was sudjected to HPLC. The labelled fatty acid C_(17)(P-C_(17))was used as the internal standard. The la- belled fatty acids C_(16) and C_(18) were separated within 18 min on an ODS-8OTM column (150 mm× 6 mm ID,5μm,Tosoh Japan).The calibrlation curves of fatty acids from the spiked control serum were Y_1=-0.003 7 + 0.0028X_1,r=0.994 for FA C_( 16) and Y_2=0.00 1 2 + 0.00098X_2,r=0.999 for FA C_( 18),respectively.The average recoveries of facids from the spiked contrl serum were 107.2%(n=8,RSD=4.3%)for FA C_(16) and 97.35%(n=8, RSD=4.0%)for FA C_(18),respectively.The lower detection limits of fatty acids after reaction were 12μmol per 20μl injection for FA C_(16) and 18 μmol per 20μl injection for FA C_(18),respectively(signal to noise ratio, S/N=2).The HPLC/CL method was applied to the determination of FA C_(16) and FA C_(18) in normal human serum and the results showed that the concentrations of fatty acids in normal human serum were 0.134 ± 0.009 μ mol/ml serum(n=5) for FA C_(16) and 0.052±0.028 μmol/ml serum(n=5)for FA C_(18),respectively.

基于ArcGIS Server的网络农田地理信息系统设计

该文为提高农田信息管理智能化水平,应用ArcGIS Server应用平台,完成对网络农田地理信息系统的设计。首先,设计和搭建系统架构和系统运行环境。其次,分别设计用户登录、信息表达、查询统计、专题图制作和空间分析等模块,保证系统功能设计效果。最后,从应用层、服务层、数据层3个方面,完成对系统设计和实现。结果表明,在ArcGIS Server应用平台的应用背景下,该文所设计的网络农田地理信息系统具有操作简单、安全可靠等特点,可以实时共享和发布农田空间信息,完全符合预期设计标准和要求。希望通过这次研究,为相关人员提供有效的借鉴和参考。

Simultaneous determination of five nucleosides and nucleobases in Panax notoginseng using high-performance liquid chromatography

Aim To quantitatively determine five nucleosides and nucleobases, including cytidine, uridine, guanosine, adenosine and uracil in different parts of Panax notoginseng. Methods Separation was performed on a Zorbax SB-Aq column using a gradient elution with mobile phase of 8 mmol^L-1 ammonium acetate aqueous solution （A） and methanol （B）. The assay was carried out at a flow rate of 1 mL·min^-1 at 25 ℃ with the diode-array detection at 260 nm. Results Cytidine, uridine, guanosine, adenosine and uracil had good linearity in the ranges of 1.79 - 57.40 μg·mL^-1 （r^2 = 1.0000）, 3.30 - 105.60 μg·mL^-1 （r^2 = 1.0000）, 3.09 - 98.80 μg·mL^ -1（r^2 = 0.9999）, 2.77 - 88.60 μg·mL^-1 （r^2 = 1.0000） and 0.38 - 12.30 μg·mL ^-1 （r^2 = 1.0000） with average recoveries of 93.9%, 96.5%, 92.7%, 93.2% and 98.8%, respectively. The content of cytidine, uridine, guanosine, adenosine and uracil in different parts of P. notogingeng were significantly different. Conclusion This is the first report on quantitative determination of nucleosides and nucleobases in P notoginseng.

High-Performance Liquid Chromatographical Analysis of Ginsenosides in Panax ginseng,P.quinquef(?)lium and P.notoginseng

The compositions and contents of ginsenbsides in Panax ginseng,P.quinquefolium and P.notoginseng were determined and compared by reversed-phase High-Performance Liquid Chro- matography(HPLC).The method was performed on an Alltech Adsorbosphere HS C_(18) column,using 5×10^(-3)M NaH_2PO_4-H_3PO_4 buffer solution(pH 3.0)and acetonitrile-water(50:50)as gradient eluents. The baseline separation of ginsenosides Rb_1,Rb_2,Rb_1,Rc,Rd,Rf,Ro,and Re+Rg_1 was obtained in one analytical run.The ginsenosides are directly detected at 203 nm.The detection limit is 40μg at a signal to noise ratio of 3:1.The improved sample preparation and clean-up prior to injection with SEP-PAK C_(18)cartridge strongly reduced the front peaks caused by the impurities in the methanolic extracts of samples to afford a smooth baseline and clear background.The HPLC patterns of methanolic extracts mainly including the ginsenosides were found capable of serving as chemical fingerprints to differentiate the three species from each other.It was also found that there are no significant diffe- rences of the HPLC patterns between the wild Panax ginseng and the cultivated,the white and the red ginsengs,Chinese and Korean red ginsengs,and the tap roots of Panax ginseng collected in four consecutive months,only certain differences in contents of ginsenosides do exist.The contents of the nine major ginsenosides present in the rhizome,tap root and rootlet as well as the leaf of Panax quinquefolium were also determined and compared.

Recent developments and applications on high-performance cast magnesium rare-earth alloys

During the past decades,with the increasing demands in lightweight structural materials,Mg alloys with low density and high performance have been extensively investigated and partly applied in some industries.Especially when rare earth(RE)elements are added as major alloying elements to Mg alloys,the alloy strength and creep resistance are greatly improved,which have promoted several series of Mg-RE alloys.This paper reviews the progress and developments of high-performance Mg-RE alloys in recent years with emphasis on cast alloys.The main contents include the alloy design,melt purification,grain refinement,castability,novel liquid casting and semisolid forming approaches,and the industrial applications or trials made of Mg-RE alloys.The review will provide insights for future developments of new alloys,techniques and applications of Mg alloys.

High-Performance and Multifunctional Cement-Based Composite Material

Concrete is a continuously evolving material, and even the definition of high-performance concrete has changed over time. In this paper, high-performance characteristics of concrete material are considered to be those that support the desirable durability, resilience, and sustainability of civil infrastructure that directly impact our quality of life. It is proposed that high-performance material characteristics include tensile ductility, autogenous crack-width control, and material “greenness.” Furthermore, smart functionalities should be aimed at enhancing infrastructure durability, resilience, and sustainability by responding to changes in the surrounding environment of the structure in order to perform desirable functions, thus causing the material to behave in a manner more akin to certain biological materials. Based on recent advances in engineered cementitious composites (ECCs), this paper suggests that concrete embodying such high-performance characteristics and smart multifunctionalities can be designed, and holds the potential to fulfill the expected civil infrastructure needs of the 21st century. Highlights of relevant properties of ECCs are provided, and directions for necessary future research are indicated.

Plasma free amino acid profiling of esophageal cancer using high-performance liquid chromatography spectroscopy

AIM: To perform plasma free amino acid (PFAA) profiling of esophageal squamous cell carcinoma (ESCC) patients at different pathological stages and healthy subjects.

Advancements in the preparation of high-performance liquid chromatographic organic polymer monoliths for the separation of small-molecule drugs

The various advantages of organic polymer monoliths, including relatively simple preparation processes,abundant monomer availability, and a wide application range of pH, have attracted the attention of chromatographers. Organic polymer monoliths prepared by traditional methods only have macropores and mesopores, and micropores of less than 50 nm are not commonly available. These typical monoliths are suitable for the separation of biological macromolecules such as proteins and nucleic acids, but their ability to separate small molecular compounds is poor. In recent years, researchers have successfully modified polymer monoliths to achieve uniform compact pore structures. In particular, microporous materials with pores of 50 nm or less that can provide a large enough surface area are the key to the separation of small molecules. In this review, preparation methods of polymer monoliths for high-performance liquid chromatography, including ultra-high cross-linking technology, post-surface modification, and the addition of nanomaterials, are discussed. Modified monolithic columns have been used successfully to separate small molecules with obvious improvements in column efficiency.

High-performance self-assembly MnCo2O4 nanosheets for asymmetric supercapacitors

In this study,MnCo2O4 nanosheets were proposed to be utilized as an electrode material for supercapacitors.A two-step hydrothermal method with post-annealing treatment was employed in preparation of the nanostructures.MnCo2O4 electrode delivered a high specific capacitance of 2000 F g^-1 at 0.5 A g^-1,remarkable high-rate capability of 1150 F g^-1 at 20 A g^-1,and an excellent cycling stability of 92.3%at 5 A g^-1 after 5000 cycles.It is found that a three-electrode supercapacitor based on MnCo2O4 exhibits a promising electrochemical performance,better than the other similar materials,benefited from the synergistic effects of MnCo2O4 nanosheets.In fact,the self-assembly of nanosheets structure with high specific surface area and mesoporous structure can potentially enhance the electrochemical performance of supercapacitors.

INFLUENCE OF MINERAL ADMIXTURES ON MECHANICAL PROPERTIES OF HIGH-PERFORMANCE CONCRETE

The improvements of the mechanical properties, including bulk density of fresh mixtures, elastic modulus, and compressive strengths of four high-performance concrete mixtures, made with the addition of fly ash, refined ground blast - furnace microslag (microslag) and silica fume are studied. The concrete mixtures were determined based on the dispersion testing results. The study indicates that the elastic modulus at 28 and 91 days, and compressive strengths of the concretes are improved a lot when fly ash and microslag by 25 percent by weight of cement are added into the mixtures individually. The improvement is especially evident when silica fume by 5 percent and fly ash by 25 percent by weight of cement are added together into the mixture, while the fresh concrete mixture keeps a good workability. Through the analysis of chemically combined water ratios of the four mixtures at various hydration ages, it is found that the addition of all these mineral mixtures are beneficial to the hydration process, especially, at later stages, which might be one of the reasons for the improvement of mechanical properties. (Author abstract) 4 Refs.