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.

Energy dissipation mechanism and ballistic characteristic optimization in foam sandwich panels against spherical projectile impact

This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels(FSP)under high-velocity impact using the explicit non-linear finite element method.Based on the geometric topology of the FSP system,three FSP configurations with the same areal density are derived,namely multi-layer,gradient core and asymmetric face sheet,and three key structural parameters are identified:core thickness(t_(c)),face sheet thickness(t_(f))and overlap face/core number(n_(o)).The ballistic performance of the FSP system is comprehensively evaluated in terms of the ballistic limit velocity(BLV),deformation modes,energy dissipation mechanism,and specific penetration energy(SPE).The results show that the FSP system exhibits a significant configuration dependence,whose ballistic performance ranking is:asymmetric face sheet>gradient core>multi-layer.The mass distribution of the top and bottom face sheets plays a critical role in the ballistic resistance of the FSP system.Both BLV and SPE increase with tf,while the raising tcor noleads to an increase in BLV but a decrease in SPE.Further,a face-core synchronous enhancement mechanism is discovered by the energy dissipation analysis,based on which the ballistic optimization procedure is also conducted and a design chart is established.This study shed light on the anti-penetration mechanism of the FSP system and might provide a theoretical basis for its engineering application.

Health diagnosis of ultrahigh arch dam performance using heterogeneous spatial panel vector model

Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

Mechanical Behavior of Panels Reinforced with Orthogonal Plant Fabrics: Experimental and Numerical Assessment

The construction sector is one of the main sources of pollution,due to high energy consumption and the toxic substances generated during the processing and use of traditional materials.The production of cement,steel,and other conventional materials impacts both ecosystems and human health,increasing the demand for ecological and biodegradable alternatives.In this paper,we analyze the properties of panels made from a combination of plant fibers and castor oil resin,analyzing the viability of their use as construction material.For the research,orthogonal fabrics made with waste plant fibers supplied by a company that deals with the manufacture of furniture and craft products were used.These fabrics were made with strips of plant fibers of the Calamus rotang,Bambusa vulgaris,Heteropsis flexuosa,and Salix viminalis species.To improve their compatibility with the castor oil resin,a cold argon plasma treatment was applied.The effect of the treatment on the properties of the fibers and the panels was analyzed.The density,water absorption capacity,and swelling percentage were evaluated.Tensile,compression,static bending,and linear buckling tests were carried out.The study found that panels made with treated fiber fabrics exhibited a reduction of approximately 10%in absorption capacity and up to 35%in swelling percentage values.Panels made with Bambusa vulgaris fabrics exhibited the highest strength and stiffness values.Numerical models were constructed using commercial finite element software.When comparing the numerical results with the experimental ones,differences of less than 15%were seen,demonstrating that the models allow adequately predicting the analyzed properties.On comparing the values obtained with the characteristic values of oriented strand board,the results suggest that panels made with unconventional materials could replace commercial panels traditionally made with wood-based fibers and particles and other composite materials in several applications in the construction industry.

How R&D investment promotes green technology innovation in the context of digitalization?-An empirical analysis based on provincial panel data

Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.

Advancements in Photovoltaic Panel Fault Detection Techniques

This paper examines the progression and advancements in fault detection techniques for photovoltaic (PV) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of PV technology grows, the need for effective fault detection strategies becomes increasingly paramount to maximize energy output and minimize operational downtimes of solar power systems. These approaches include the use of machine learning and deep learning methodologies to be able to detect the identified faults in PV technology. Here, we delve into how machine learning models, specifically kernel-based extreme learning machines and support vector machines, trained on current-voltage characteristic (I-V curve) data, provide information on fault identification. We explore deep learning approaches by taking models like EfficientNet-B0, which looks at infrared images of solar panels to detect subtle defects not visible to the human eye. We highlight the utilization of advanced image processing techniques and algorithms to exploit aerial imagery data, from Unmanned Aerial Vehicles (UAVs), for inspecting large solar installations. Some other techniques like DeepLabV3 , Feature Pyramid Networks (FPN), and U-Net will be detailed as such tools enable effective segmentation and anomaly detection in aerial panel images. Finally, we discuss implications of these technologies on labor costs, fault detection precision, and sustainability of PV installations.

Composite Panels from the Combination of Rice Husk and Wood Chips with a Natural Resin Based on Tannins Reinforced with Sugar Cane Molasses Intended for Building Insulation: Physico-Mechanical and Thermal Properties

The objective of this work is to develop new biosourced insulating composites from rice husks and wood chips that can be used in the building sector. It appears from the properties of the precursors that rice chips and husks are materials which can have good thermal conductivity and therefore the combination of these precursors could make it possible to obtain panels with good insulating properties. With regard to environmental and climatic constraints, the composite panels formulated at various rates were tested and the physico-mechanical and thermal properties showed that it was essential to add a crosslinker in order to increase certain solicitation. an incorporation rate of 12% to 30% made it possible to obtain panels with low thermal conductivity, a low surface water absorption capacity and which gives the composite good thermal insulation and will find many applications in the construction and real estate sector. Finally, new solutions to improve the fire reaction of the insulation panels are tested which allows to identify suitable solutions for the developed composites. In view of the flame tests, the panels obtained are good and can effectively combat fire safety in public buildings.

A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.

Comprehensive Examination of Solar Panel Design: A Focus on Thermal Dynamics

In the 21st century, the deployment of ground-based Solar Photovoltaic (PV) Modules has seen exponential growth, driven by increasing demands for green, clean, and renewable energy sources. However, their usage is constrained by certain limitations. Notably, the efficiency of solar PV modules on the ground peaks at a maximum of 25%, and there are concerns regarding their long-term reliability, with an expected lifespan of approximately 25 years without failures. This study focuses on analyzing the thermal efficiency of PV Modules. We have investigated the temperature profile of PV Modules under varying environmental conditions, such as air velocity and ambient temperature, utilizing Computational Fluid Dynamics (CFD). This analysis is crucial as the efficiency of PV Modules is significantly impacted by changes in the temperature differential relative to the environment. Furthermore, the study highlights the effect of airflow over solar panels on their temperature. It is found that a decrease in the temperature of the PV Module increases Open Circuit Voltage, underlining the importance of thermal management in optimizing solar panel performance.

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.

血清外泌体microRNAs单一及组合panel对结直肠癌的诊断价值

目的 检测血清外泌体miR-15b、miR-16、miR-21和miR-31在结直肠癌患者中的表达水平,并评估其对结直肠癌的诊断价值。方法 选取2018年3月至2022年5月本院收治的123例直肠癌患者(结直肠癌组)及117例大肠腺瘤患者作为研究对象(结直肠癌组),并纳入150例健康对照者作为对照(健康对照组)。提取血清外泌体中miR-15b、miR-16、miR-21和miR-31,qRT-PCR比较4种miRNA在各组中表达水平差异。受试者工作特征(ROC)曲线评价4种miRNA单一及组合panel对结直肠癌的诊断价值。结果 结直肠癌组血清miR-15b、miR-16、miR-21和miR-31水平高于健康对照组(P <0.05),且miR-15b、miR-21和miR-31水平高于结直肠腺瘤组(P <0.05)。Ⅲ-Ⅳ期、伴淋巴结浸润、低分化程度结直肠癌组患者血清miR-15b、miR-21和miR-31水平分别高于Ⅰ-Ⅱ期、不伴淋巴结浸润、中-高分化程度患者,miR-15b、miR-21和miR-31水平与临床TNM分期、伴淋巴结浸润呈正相关,与分化程度呈负相关。4种miRNA中诊断价值最高的指标是miR-15b,其敏感度和特异度分别为81.33%和91.80%(P <0.05);且miR-15b、miR-21和miR-31的组合panel具有更好的诊断价值,其敏感度和特异度分别为95.06%和94.44%(P <0.05)。结论 miR-15b、miR-16、miR-21和miR-31在结直肠癌患者外周血血清中异常表达,miR-15b、miR-21和miR-31水平与结直肠癌的发病及进展密切相关,且miR-15b、miR-21和miR-31组合panel具有作为结直肠癌的新型诊断模型的潜力。

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.