Volumetric lattice Boltzmann method for pore-scale mass diffusionadvection process in geopolymer porous structures

Porous materials present significant advantages for absorbing radioactive isotopes in nuclear waste streams.To improve absorption efficiency in nuclear waste treatment,a thorough understanding of the diffusion-advection process within porous structures is essential for material design.In this study,we present advancements in the volumetric lattice Boltzmann method(VLBM)for modeling and simulating pore-scale diffusion-advection of radioactive isotopes within geopolymer porous structures.These structures are created using the phase field method(PFM)to precisely control pore architectures.In our VLBM approach,we introduce a concentration field of an isotope seamlessly coupled with the velocity field and solve it by the time evolution of its particle population function.To address the computational intensity inherent in the coupled lattice Boltzmann equations for velocity and concentration fields,we implement graphics processing unit(GPU)parallelization.Validation of the developed model involves examining the flow and diffusion fields in porous structures.Remarkably,good agreement is observed for both the velocity field from VLBM and multiphysics object-oriented simulation environment(MOOSE),and the concentration field from VLBM and the finite difference method(FDM).Furthermore,we investigate the effects of background flow,species diffusivity,and porosity on the diffusion-advection behavior by varying the background flow velocity,diffusion coefficient,and pore volume fraction,respectively.Notably,all three parameters exert an influence on the diffusion-advection process.Increased background flow and diffusivity markedly accelerate the process due to increased advection intensity and enhanced diffusion capability,respectively.Conversely,increasing the porosity has a less significant effect,causing a slight slowdown of the diffusion-advection process due to the expanded pore volume.This comprehensive parametric study provides valuable insights into the kinetics of isotope uptake in porous structures,facilitating the development of porous materials for nuclear waste treatment applications.

A High Order Accurate Bound-Preserving Compact Finite Difference Scheme for Two-Dimensional Incompressible Flow

For solving two-dimensional incompressible flow in the vorticity form by the fourth-order compact finite difference scheme and explicit strong stability preserving temporal discretizations,we show that the simple bound-preserving limiter in Li et al.(SIAM J Numer Anal 56:3308–3345,2018)can enforce the strict bounds of the vorticity,if the velocity field satisfies a discrete divergence free constraint.For reducing oscillations,a modified TVB limiter adapted from Cockburn and Shu(SIAM J Numer Anal 31:607–627,1994)is constructed without affecting the bound-preserving property.This bound-preserving finite difference method can be used for any passive convection equation with a divergence free velocity field.

亚共晶合金晶粒尺寸与相图变量相关双参数模型的检验

提出用于描述晶粒尺寸与工艺条件和相图变量相关联的简单双参数数学模型,然而,这些模型还没有通过良好的实验数据进行充分检验。采用精选的亚共晶合金实验数据检验这些模型,并提出实验数据的选择标准。采用这些双参数模型拟合被选择的实验数据,检查曲线的拟合质量和适用性,从而确定与实验数据吻合更好的数学模型。基于数据分析,探讨溶质元素细化晶粒尺寸的机理。结果表明,晶粒尺寸与合金凝固间隔之间存在明确的依赖关系,这种关系可采用P变量加以描述。晶粒尺寸对凝固间隔的这种明显依赖表明,在充型和凝固过程存在对流的铸锭和铸件中,与枝晶破碎有关的机理是控制溶质元素细化晶粒的主要运行机制。

Revolutionizing plasmonic platform via magnetic field-assisted confined ultrafast laser deposition of high-density,uniform,and ultrafine nanoparticle arrays

The remarkable capabilities of 2D plasmonic surfaces in controlling optical waves havegarnered significant attention.However,the challenge of large-scale manufacturing of uniform,well-aligned,and tunable plasmonic surfaces has hindered their industrialization.To address this,we present a groundbreaking tunable plasmonic platform design achieved throughmagnetic field(MF)assisted ultrafast laser direct deposition in air.Through precise control of metal nanoparticles(NPs),with cobalt(Co)serving as the model material,employing an MF,and fine-tuning ultrafast laser parameters,we have effectively converted coarse and non-uniform NPs into densely packed,uniform,and ultrafine NPs(~3 nm).This revolutionary advancement results in the creation of customizable plasmonic‘hot spots,’which play a pivotal role insurface-enhanced Raman spectroscopy(SERS)sensors.The profound impact of this designable plasmonic platform lies in its close association with plasmonic resonance and energyenhancement.When the plasmonic nanostructures resonate with incident light,they generate intense local electromagnetic fields,thus vastly increasing the Raman scattering signal.This enhancement leads to an outstanding 2–18 fold boost in SERS performance and unparalleled sensing sensitivity down to 10^(-10)M.Notably,the plasmonic platform also demonstratesrobustness,retaining its sensing capability even after undergoing 50 cycles of rinsing andre-loading of chemicals.Moreover,this work adheres to green manufacturing standards,making it an efficient and environmentally friendly method for customizing plasmonic‘hot spots’inSERS devices.Our study not only achieves the formation of high-density,uniform,and ultrafine NP arrays on a tunable plasmonic platform but also showcases the profound relation betweenplasmonic resonance and energy enhancement.The outstanding results observed in SERS sensors further emphasize the immense potential of this technology for energy-relatedapplications,including photocatalysis,photovoltaics,and clean water,propelling us closer to a sustainable and cleaner future.

Electronic properties of 2D materials and their junctions

With an extensive range of distinctive features at nano meter-scale thicknesses,two-dimensional(2D)materials drawn the attention of the scientific community.Despite tremendous advancements in exploratory research on 2D materials,knowledge of 2D electrical transport and carrier dynamics still in its infancy.Thus,here we highlighted the electrical characteristics of 2D materials with electronic band structure,electronic transport,dielectric constant,carriers mobility.The atomic thinness of 2D materials makes substantially scaled field-effect transistors(FETs)with reduced short-channel effects conceivable,even though strong carrier mobility required for high performance,low-voltage device operations.We also discussed here about factors affecting 2D materials which easily enhanced the activity of those materials for various applications.Presently,Those 2D materials used in state-of-the-art electrical and optoelectronic devices because of the extensive nature of their electronic band structure.2D materials offer unprecedented freedom for the design of novel p-n junction device topologies in contrast to conventional bulk semiconductors.We also,describe the numerous 2D p-n junctions,such as homo junction and hetero junction including mixed dimensional junctions.Finally,we talked about the problems and potential for the future.

Impact of initial fluctuations and nuclear deformations in isobar collisions

Relativistic isobar^(96)_(44)Ru+^(96)_(44)Ru and^(96)_(40)Zr+^(96)_(40)Zrcollisions have revealed intricate differences in their nuclear size and shape,inspiring unconventional studies of nuclear structure using relativistic heavy ion collisions.In this study,we investigate the relative differences in the mean multiplicityR_(<Nch>)and the secondR_(ε2)and third-order eccentricityR_(ε3)between isobar collisions using initial state Glauber models.It is found that initial fluctuations and nuclear deformations have negligible effects on R_(<Nch>)in most central collisions,while both are important for the R_(ε2)and R_(ε3),the degree of which is sensitive to the underlying nucleonic or sub-nucleonic degree of freedom.These features,compared to real data,may probe the particle production mechanism and the physics underlying nuclear structure.

Unraveling links between aging,circadian rhythm and cancer:Insights from evidence-based analysis

Aging and circadian rhythms have been connected for decades,but their molecular interaction has remained unknown,especially for cancers.In this situation,we summarized the current research actuality and problems in this field using the bibliometric analysis.Publications in the PubMed and Web of Science databases were retrieved.Overall,there is a rising trend in the publication volume regarding aging and circadian rhythms in the field of cancer.Researchers from USA,Germany,Italy,China and England have greater studies than others.Top three publication institutions are University of California System,UDICE-French Research Universities and University of Texas System.Current research hotspots include oxidative stress,breast cancer,melatonin,cell cycle,calorie restriction,prostate cancer and NF-κB.In conclusion,results generated by bibliometric analysis indicate that many approaches involve in the complex interactions between aging and circadian rhythm in cancer.These established and emerging research directions guide our exploration of the regulatory mechanisms of aging and circadian rhythms in cancer and provide a reference for developing new research avenues.

Observer-Based Adaptive Robust Precision Motion Control of a Multi-Joint Hydraulic Manipulator

Hydraulic manipulators are usually applied in heavy-load and harsh operation tasks.However,when faced with a complex operation,the traditional proportional-integral-derivative(PID)control may not meet requirements for high control performance.Model-based full-state-feedback control is an effective alternative,but the states of a hydraulic manipulator are not always available and reliable in practical applications,particularly the joint angular velocity measurement.Considering that it is not suitable to obtain the velocity signal directly from differentiating of position measurement,the low-pass filtering is commonly used,but it will definitely restrict the closed-loop bandwidth of the whole system.To avoid this problem and realize better control performance,this paper proposes a novel observerbased adaptive robust controller(obARC)for a multi-joint hydraulic manipulator subjected to both parametric uncertainties and the lack of accurate velocity measurement.Specifically,a nonlinear adaptive observer is first designed to handle the lack of velocity measurement with the consideration of parametric uncertainties.Then,the adaptive robust control is developed to compensate for the dynamic uncertainties,and the close-loop system robust stability is theoretically proved under the observation and control errors.Finally,comparative experiments are carried out to show that the designed controller can achieve a performance improvement over the traditional methods,specifically yielding better control accuracy owing to the closed-loop bandwidth breakthrough,which is limited by low-pass filtering in fullstate-feedback control.

Stomatal dynamics are regulated by leaf hydraulic traits and guard cell anatomy in nine true mangrove species

Stomatal regulation is critical for mangroves to survive in the hyper-saline intertidal zone where water stress is severe and water availability is highly fluctuant.However,very little is known about the stomatal sensitivity to vapour pressure deficit(VPD)in mangroves,and its co-ordination with stomatal morphology and leaf hydraulic traits.We measured the stomatal response to a step increase in VPD in situ,stomatal anatomy,leaf hydraulic vulnerability and pressure-volume traits in nine true mangrove species of five families and collected the data of genome size.We aimed to answer two questions:(1)Does stomatal morphology influence stomatal dynamics in response to a high VPD in mangroves?with a consideration of possible influence of genome size on stomatal morphology;and(2)do leaf hydraulic traits influence stomatal sensitivity to VPD in mangroves?We found that the stomata of mangrove plants were highly sensitive to a step rise in VPD and the stomatal responses were directly affected by stomatal anatomy and hydraulic traits.Smaller,denser stomata was correlated with faster stomatal closure at high VPD across the species of Rhizophoraceae,and stomata size negatively and vein density positively correlated with genome size.Less negative leaf osmotic pressure at the full turgor(πo)was related to higher operating steady-state stomatal conductance(gs);and a higher leaf capacitance(Cleaf)and more embolism resistant leaf xylem were associated with slower stomatal responses to an increase in VPD.In addition,stomatal responsiveness to VPD was indirectly affected by leaf morphological traits,which were affected by site salinity and consequently leaf water status.Our results demonstrate that mangroves display a unique relationship between genome size,stomatal size and vein packing,and that stomatal responsiveness to VPD is regulated by leaf hydraulic traits and stomatal morphology.Our work provides a quantitative framework to better understand of stomatal regulation in mangroves in an environment with high salinity and dynamic water availability.

Analysis and Review of Downregulated Actin Cytoskeletal Proteins in Non-Small Cell Lung Cancer

Actin, a highly conserved protein, plays a dominant role in Non-small cell lung cancer (NSCLC). Late diagnosis and the aggressive nature of NSCLC pose a significant threat. Studying the clinic pathological properties of NSCLC proteins is a potential alternative for developing treatment strategies. Towards this, 35 downregulated actin cytoskeletal proteins on NSCLC prognosis and treatment were studied by examining their protein-protein interactions, gene ontology enrichment terms, and signaling pathways. Using PubMed, various proteins in NSCLC were identified. The protein-protein interactions and functional associations of these proteins were examined using the STRING database. The focal adhesion signaling pathway was selected from all available KEGG and Wiki pathways because of its role in regulating gene expression, facilitating cell movement and reproduction, and significantly impacting NSCLC. The protein-protein interaction network of the 35 downregulated actin cytoskeleton proteins revealed that ACTG1, ACTR2, ACTR3, ANXA2, ARPC4, FLNA, TLN1, CALD1, MYL6, MYH9, MYH10, TPM1, TPM3, TPM4, PFN1, IQGAP1, MSN, and ZXY exhibited the highest number of interactions. Whereas HSPB1, CTNNA1, KRT17, KRT7, FLNB, SEPT2, and TUBA1B displayed medium interactions, while UTRN, TUBA1B, and DUSP23 had relatively fewer interactions. It was discovered that focal adhesions are critical in connecting membrane receptors with the actin cytoskeleton. In addition, protein kinases, phosphatases, and adapter proteins were identified as key signaling molecules in this process, greatly influencing cell shape, motility, and gene expression. Our analysis shows that the focal adhesion pathway plays a crucial role in NSCLC and is essential for developing effective treatment strategies and improving patient outcomes.

Quantifying the Impact of In-Cab Alerts on Truck Speed Reductions in Ohio

In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driver response was evaluated by measuring the statistical trends of vehicle speeds after the in-cab alerts were received. Vehicle speeds pre and post in-cab alert were collected over a 47 day period in the fall of 2023 for trucks traveling on interstate roadways in Ohio. Results show that approximately 22% of drivers receiving Dangerous Slowdown alerts had reduced their speeds by at least 5 mph 30 seconds after receiving such an alert. Segmenting this analysis by speed found that of vehicles traveling at or above 70 mph at the time of alerting, 26% reduced speeds by at least 5 mph. These speed reductions suggest drivers taking actional measures after receiving alerts. Future studies will involve further analysis on the impact of the types of alerts shown, roadway characteristics and overall traffic conditions on truck speeds passing through work zones.

Application of Connected Truck Data to Evaluate Spatiotemporal Impact of Rest Area Closures on Ramp Parking

Ensuring adequate access to truck parking is critical to the safe and efficient movement of freight traffic. There are strict federal guidelines for commercial truck driver rest periods. Rest areas and private truck stops are the only places for the trucks to stop legally and safely. In locations without sufficient parking areas, trucks often park on interstate ramps, which create safety risks for other interstate motorists. Historically, agencies have employed costly and time intensive manual counting methods, camera surveillance, and driver surveys to assess truck parking. Connected truck data, available in near real-time, offers an efficient alternative to practitioners to assess truck parking patterns and identify areas where there may be insufficient safe parking spaces. This paper presents a case study of interstate I-70 in east central Indiana and documents the observed spatiotemporal impacts of a rest area closure on truck parking on nearby interstate ramps. Results showed that there was a 28% increase in parking on ramps during the rest area closure. Analysis also found that ramps closest to the rest area were most impacted by the closure, seeing a rise in truck parking sessions as high as 2.7 times. Parking duration on the ramps during rest area closure also increased drastically. Although it was expected that this would result in increased parking by trucks on adjacent ramps, this before, during, after scenario provided an ideal scenario to evaluate the robustness of these techniques to assess changing parking characteristics of long-haul commercial trucks. The data analytics and visualization tools presented in this study are scalable nationwide and will aid stakeholders in informed data-driven decision making when allocating resources towards improving the nations commercial vehicle parking infrastructure.

FEA-Based Fatigue Life Assessment of Cycloidal Displacement Cam and Flat-Faced Follower Mechanism

Cam-followers provide reliable and controlled motions in various mechanical systems. Due to the highly fluctuating load between the cam and follower in operation, the cam-follower may be subjected to a high risk of contact fatigue failure. This paper assesses the fatigue life of a cycloidal displacement cam and a flat-faced follower under the defined loads and constraints. Computer-aided design (CAD) model of the cam-follower is developed in CATIA software and imported to ANSYS software for finite element analysis (FEA) of fatigue life. MATLAB programming is developed for determining the appropriate spring constant and pre-load force to always keep the cam and follower in contact. The fatigue life of the cam-follower has been estimated under the specified operating conditions. The analysis method can be applied to investigate the fatigue life of cams with other profiles, including the modified trapezoidal functions, polynomial functions, etc.

Determination of Natural Logarithm of Diffusion Coefficient and Activation Energy of Thin Layer Drying Process of Ginger Rhizome Slices

This study is an extension of the previous work done with ARS-680 Environmental Chamber. Drying is a complex operation that demands much energy and time. Drying is essentially important for preservation of ginger rhizome. Drying of ginger was modeled, and then the effective diffusion coefficient and activation energy were determined. For this purpose, the experiments were done at six levels of varied temperatures: 10°C, 20°C, 30°C, 40°C, 50°C and 60°C. The values of effective diffusion coefficients obtained in this work for the variously treated ginger rhizomes closely agreed with the average effective diffusion coefficients of other notable authors who determined the drying kinetics and convective heat transfer coefficients of ginger slices.

Functionally graded structure of a nitride-strengthened Mg_(2)Si-based hybrid composite

The ex-situ incorporation of the secondary SiC reinforcement,along with the in-situ incorporation of the tertiary and quaternary Mg_(3)N_(2) and Si_(3)N_(4) phases,in the primary matrix of Mg_(2)Si is employed in order to provide ultimate wear resistance based on the laser-irradiation-induced inclusion of N_(2) gas during laser powder bed fusion.This is substantialized based on both the thermal diffusion-and chemical reactionbased metallurgy of the Mg_(2)Si–SiC/nitride hybrid composite.This study also proposes a functional platform for systematically modulating a functionally graded structure and modeling build-direction-dependent architectonics during additive manufacturing.This strategy enables the development of a compositional gradient from the center to the edge of each melt pool of the Mg_(2)Si–SiC/nitride hybrid composite.Consequently,the coefficient of friction of the hybrid composite exhibits a 309.3%decrease to–1.67 compared to–0.54 for the conventional nonreinforced Mg_(2)Si structure,while the tensile strength exhibits a 171.3%increase to 831.5 MPa compared to 485.3 MPa for the conventional structure.This outstanding mechanical behavior is due to the(1)the complementary and synergistic reinforcement effects of the SiC and nitride compounds,each of which possesses an intrinsically high hardness,and(2)the strong adhesion of these compounds to the Mg_(2)Si matrix despite their small sizes and low concentrations.

人工智能算法偏见与健康不公平的成因与对策分析

随着信息技术的发展,人工智能为疾病诊疗带来重要价值。然而,人工智能中存在算法偏见现象,可导致医疗卫生资源分配不均等问题,严重损害患者的健康公平。算法偏见是人为偏见的技术化体现,其形成与人工智能开发过程密切相关,主要源于数据收集、训练优化和输出应用3个方面。医护工作者作为患者健康的直接参与者,应采取相应措施以预防算法偏见,避免其引发健康公平问题。医护工作者需保障健康数据真实无偏见、优化人工智能的公平性和加强其输出应用的透明度,同时需思考如何处理临床实践中算法偏见引发的不公平现象,全面保障患者健康公平。本研究就健康领域中算法偏见的形成原因和应对策略展开综述,以期提高医护工作者识别和处理算法偏见的意识与能力,为保障信息化时代中的患者健康公平提供参考。

Thermally insulating and fire-retardant bio-mimic structural composites with a negative Poisson's ratio for battery protection

Battery safety has attracted considerable attention worldwide due to the rapid development of wearable electronics and the steady increase in the production and use of electric vehicles.As battery failures are often associated with mechanical-thermal coupled behaviors,protective shielding materials with excellent mechanical robustness and flame-retardant properties are highly desired to mitigate thermal runaway.However,most of the thermal insulating materials are not strong enough to protect batteries from mechanical abuse,which is one of the most critical scenarios with catastrophic consequences.Here,inspired by wood,we have developed an effective approach to engineer a hierarchical nanocomposite via self-assembly of calcium silicate hydrate and polyvinyl alcohol polymer chains(referred as CSH wood).The versatile protective material CSH wood demonstrates an unprecedented combination of light weight(0.018 g cm-3),high stiffness(204 MPa in the axial direction),negative Poisson's ratio(-0.15),remarkable toughness(6.67×105 J m-3),superior thermal insulation(0.0204 W m-1 K-1 in the radial direction),and excellent fire retardancy(UL94-V0).When applied as a protective cover or a protective layer within battery packages,the tough CSH wood can resist high-impact load and block heat diffusion to block or delay the spread of fire,therefore significantly reducing the risk of property damage or bodily injuries caused by battery explosions.This work provides new pathways for fabricating advanced thermal insulating materials with large scalability and demonstrates great potential for the protection of electronic devices.

Pan-genome and transcriptome analyses provide insights into genomic variation and differential gene expression profiles related to disease resistance and fatty acid biosynthesis in eastern black walnut (Juglans nigra)

Walnut(Juglans)species are used as nut crops worldwide.Eastern black walnut(EBW,Juglans nigra),a diploid,horticultural important woody species is native to much of eastern North America.Although it is highly valued for its wood and nut,there are few resources for understanding EBW genetics.Here,we present a high-quality genome assembly of J.nigra based on Illumina,Pacbio,and HiC technologies.The genome size was 540.8 Mb,with a scaffold N50 size of 35.1 Mb,and 99.0%of the assembly was anchored to 16 chromosomes.Using this genome as a reference,the resequencing of 74 accessions revealed the effective population size of J.nigra declined during the glacial maximum.A single whole-genome duplication event was identified in the J.nigra genome.Large syntenic blocks among J.nigra,Juglans regia,and Juglans microcarpa predominated,but inversions of more than 600 kb were identified.By comparing the EBW genome with those of J.regia and J.microcarpa,we detected InDel sizes of 34.9 Mb in J.regia and 18.3 Mb in J.microcarpa,respectively.Transcriptomic analysis of differentially expressed genes identified five presumed NBS-LRR(NUCLEOTIDE BINDING SITELEUCINE-RICH REPEAT)genes were upregulated during the development of walnut husks and shells compared to developing embryos.We also identified candidate genes with essential roles in seed oil synthesis,including FAD(FATTY ACID DESATURASE)and OLE(OLEOSIN).Our work advances the understanding of fatty acid bioaccumulation and disease resistance in nut crops,and also provides an essential resource for conducting genomics-enabled breeding in walnut.

Multi-objective optimization in highway pavement maintenance and rehabilitation project selection and scheduling:A state-of-the-art review

The motivation for cost-effective management of highway pavements is evidenced not only by the massive expenditures associated with these activities at a national level but also by the consequences of poor pavement condition on road users.This paper presents a state-of-the-art review of multi-objective optimization(MOO)problems that have been formulated and solution techniques that have been used in selecting and scheduling highway pavement rehabilitation and maintenance activities.First,the paper presents a taxonomy and hierarchy for these activities,the role of funding sources,and levels of jurisdiction.The paper then describes how three different decision mechanisms have been used in past research and practice for project selection and scheduling(historical practices,expert opinion,and explicit mathematical optimization)and identifies the pros and cons of each mechanism.The paper then focuses on the optimization mechanism and presents the types of optimization problems,formulations,and objectives that have been used in the literature.Next,the paper examines various solution algorithms and discusses issues related to their implementation.Finally,the paper identifies some barriers to implementing multi-objective optimization in selecting and scheduling highway pavement rehabilitation and maintenance activities,and makes recommendations to overcome some of these barriers.

Towards rapid and automated vulnerability classification of concrete buildings

With the overwhelming number of older reinforced concrete buildings that need to be assessed for seismic vulnerability in a city,local governments face the question of how to assess their building inventory.By leveraging engineering drawings that are stored in a digital format,a well-established method for classification reinforced concrete buildings with respect to seismic vulnerability,and machine learning techniques,we have developed a technique to automatically extract quantitative information from the drawings to classify vulnerability.Using this technique,stakeholders will be able to rapidly classify buildings according to their seismic vulnerability and have access to information they need to prioritize a large building inventory.The approach has the potential to have significant impact on our ability to rapidly make decisions related to retrofit and improvements in our communities.In the Los Angeles County alone it is estimated that several thousand buildings of this type exist.The Hassan index is adopted here as the method for automation due to its simple application during the classification of the vulnerable reinforced concrete buildings.This paper will present the technique used for automating information extraction to compute the Hassan index for a large building inventory.