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.

Unmanned Ship Identification Based on Improved YOLOv8s Algorithm

Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm(R_YOLO).The algorithm incorporates the Efficient Multi-Scale Attention mechanism(EMA),the efficient Reparameterized Generalized-feature extraction module(CSPStage),the small target detection header,the Repulsion Loss function,and the context aggregation block(CABlock),which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference.The algorithm is validated in detail on two vessel datasets.The comprehensive experimental results demonstrate that,in the infrared dataset,the YOLOv8s algorithm exhibits improvements in various performance metrics.Specifically,compared to the baseline algorithm,there is a 3.1%increase in mean average precision at a threshold of 0.5(mAP(0.5)),a 5.4%increase in recall rate,and a 2.2%increase in mAP(0.5:0.95).Simultaneously,while less than 5 times parameters,the mAP(0.5)and frames per second(FPS)exhibit an increase of 1.7%and more than 3 times,respectively,compared to the CAA_YOLO algorithm.Finally,the evaluation indexes on the visible light data set have shown an average improvement of 4.5%.

Efficient Ship:A Hybrid Deep Learning Framework for Ship Detection in the River

Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore waters.Current deep learning researches on optical image-based ship detection mainly focus on improving one-stage detectors for real-time ship detection but sacrifices the accuracy of detection.To solve this problem,we present a hybrid ship detection framework which is named EfficientShip in this paper.The core parts of the EfficientShip are DLA-backboned object location(DBOL)and CascadeRCNN-guided object classification(CROC).The DBOL is responsible for finding potential ship objects,and the CROC is used to categorize the potential ship objects.We also design a pixel-spatial-level data augmentation(PSDA)to reduce the risk of detection model overfitting.We compare the proposed EfficientShip with state-of-the-art(SOTA)literature on a ship detection dataset called Seaships.Experiments show our ship detection framework achieves a result of 99.63%(mAP)at 45 fps,which is much better than 8 SOTA approaches on detection accuracy and can also meet the requirements of real-time application scenarios.

Fine-Grained Ship Recognition Based on Visible and Near-Infrared Multimodal Remote Sensing Images: Dataset,Methodology and Evaluation

Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technol-ogy.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.

A Time-Domain Numerical Simulation for Free Motion Responses of Two Ships Advancing in Head Waves

The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.

Improved Scatter Search Algorithm for Multi-skilled Personnel Scheduling of Ship Block Painting

This paper focuses on the optimization method for multi-skilled painting personnel scheduling.The budget working time analysis is carried out considering the influence of operating area,difficulty of spraying area,multi-skilled workers,and worker’s efficiency,then a mathematical model is established to minimize the completion time. The constraints of task priority,paint preparation,pump management,and neighbor avoidance in the ship block painting production are considered. Based on this model,an improved scatter search(ISS)algorithm is designed,and the hybrid approximate dynamic programming(ADP)algorithm is used to improve search efficiency. In addition,the two solution combination methods of path-relinking and task sequence combination are used to enhance the search breadth and depth. The numerical experimental results show that ISS has a significant advantage in solving efficiency compared with the solver in small scale instances;Compared with the scatter search algorithm and genetic algorithm,ISS can stably improve the solution quality. Verified by the production example,ISS effectively shortens the total completion time of the production,which is suitable for scheduling problems in the actual painting production of the shipyard.

Sending The King Ship, A Tradition Connecting Two Peoples

“The sky is dark,and it is about to rain,”goes a lyric from China’s coastal Minnan(southern Fujian)region.“The king ship is leaving the bay,papa is going out to sea,and mama is sending the ship off.May it bring us wealth,food,and the gods’protection.”The 600-year-old custom is called Ong Chun,Wangchuan,Wangkang,or“Sending the King Ship.”

Ship recognition based on HRRP via multi-scale sparse preserving method

In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.

欧盟AUTOSHIP项目

欧洲水域自主航运倡议项目(Autonomous Shipping Initiative for European Waters,AUTOSHIP项目)由意大利Ciaotech S.r.l.公司牵头,联合康士伯等其他欧洲国家合作伙伴共同完成。该项目通过在不同环境下运营的两艘不同类型船舶上安装和测试自主航行设施,加速新一代自主航行船舶发展,并为欧盟实现船舶自主航行制定商业化路线图。

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.

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.METHODS:Plasma samples from ESCC patients(n=51)and healthy control adults(n=60)were analyzed by high-performance liquid chromatography(HPLC).The ESCC patients included moderate/poorly-differentiation(n=24),lymph node metastasis(n=17)and clinical stage>Ib2(n=36).Partial least squares discriminant analysis was performed to demonstrate that the PFAA metabolic patterns enabled discrimination between ESCC patients and controls,and the Student t test was applied to assess significant differences in PFAA concentrations between the two groups.RESULTS:There were significant differences in the PFAA profiles between controls and ESCC patients.Compared with healthy controls,the levels of Asp,Glu,Gly,His,Thr,Tau,Ala,Met,Ile,Leu,and Phe were decreased in ESCC patients,but Cys was increased.There exists a strong correlation between PFAA profiles and clinicopathological characteristics in ESCC patients.The levels of many PFAAs(i.e.,Glu,Asp,Ser,Gly,Tau,Ala,Tyr,Val,Ile,and Leu)were related to pathological grading,lymph node metastasis,and ESCC clinical stage.Very good discrimination between ESCC patients and control subjects was achieved by multivariate modeling of plasma profiles.CONCLUSION:HPLC-based plasma profiling analysis was shown to be an effective approach to differentiate between ESCC patients and controls.PFAA profiles may have potential value for screening or diagnosing ESCC.

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.

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.

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.

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.

Determination of gouty arthritis' biomarkers in human urine using reversed-phase high-performance liquid chromatography

Creatinine, uric acid, hypoxanthine and xanthine are important diagnostic biomarkers in human urine for gouty arthritis or renal disease diacrisis. A simple method for simultaneous determination of these biomarkers in urine based on reversed-phase high-performance liquid chromatography （RP-HPLC） with ultraviolet （UV） detector was proposed. After pretreatment by dilution, centrifugation and filtration, the biomarkers in urine samples were separated by ODS-BP column by elution with methanol/50 mM NaH2PO4 buffer solution at pH 5.26 （5：95）. Good linearity between peak areas and concentrations of standards was obtained for the biomarkers with correlation coefficients in the range of 0.9957-0.9993. The proposed analytical method has satisfactory repeatability （the recovery of data in a range of creatinine, uric acid, hypoxanthine and xanthine was 93.49-97.90%, 95.38-96.45%, 112.46-115.78%and 90.82-97.13%with standard deviation of o5%, respectively） and the limits of detection （LODs, S/N Z 3） for creatinine, uric acid, hypoxanthine, and xanthine were 0.010, 0.025, 0.050 and 0.025 mg/L, respectively. The established method was proved to be simple, accurate, sensitive and reliable for the quantitation of gouty arthritis＇ biomarkers in human urine samples. The ratio of creatinine to uric acid was found to be a possible factor for assessment of gouty arthritis.

SYNTHESIS AND PROPERTIES OF NOVEL POLY(IMINO KETONE)S AS HIGH-PERFORMANCE POLYMERS

Di(4-bromophenyl)ketone and various aromatic diamines as the monomers,a series of novel poly(imino ketone)s (PIKs)have been synthesized via palladium-catalyzed aryl amination,which is Hartwig-Buchwald polycondensation reaction.The structures of PIKs are characterized by means of elemental analysis,FT-IR,~1H-NMR and UV-Vis spectroscopy. The results show a good agreement with the proposed structure.The general properties of PIKs are studied by DSC,TG and wide-angle X-ray diffraction,the solubility behavior is...

Influence of shrinkage-reducing admixture on drying shrinkage and mechanical properties of high-performance concrete

High-performance concrete （HPC） has specific performance advantages over conventional concrete in strength and durability. HPC mixtures are usually produced with water/binder mass ratios （mW/mB） in the range of 0.2-0.4, so volume changes of concrete as a result of drying, chemical reactions, and temperature change cannot be avoided. For these reasons, shrinkage and cracking are frequent phenomena. It is necessary to add some types of admixture for reduction of shrinkage and cracking of HPC. This study used a shrinkage-reducing admixture （SRA） for that purpose. Concrete was prepared with two different mW/mB （0.22 and 0.40） and four different mass fractions of SRA to binder （w（SRA） = 0%, 1%, 2%, and 4%）. The mineral admixtures used for concrete mixes were： 25% fly ash （FA） and 25% slag by mass of binder for the mixture with mW/mB = 0.40, and 15% silica fume （SF） and 25% FA for the mixture with mW/mB = 0.22. Tests were conducted on 24 prismatic specimens, and shrinkage strains were measured through 120 days of drying. Compressive strength, splitting strength, and static modulus of elasticity were also determined. The results show that the SRA effectively reduces some mechanical properties of HPC. The reductions in compressive strength, splitting tensile strength, and elastic modulus of the concrete were 7%-24%, 9%-19%, and 5%-12%, respectively, after 90 days, compared to concrete mixtures without SRA. SRA can also help reduce drying shrinkage of concrete. The shrinkage strains of HPC with SRA were only as high as 41% of the average free shrinkage of concrete without SRA after 120 days of drying.