The damage to model concrete gravity dams subjected to water explosions

Over the past century,the safety of dams has gradually attracted attention from all parties.Research on the dynamic response and damage evolution of dams under extreme loads is the basis of dam safety issues.In recent decades,scholars have studied the responses of dams under earthquake loads,but there is still much room for improvement in experimental and theoretical research on small probability loads such as explosions.In this paper,a 50-m-high concrete gravity dam is used as a prototype dam,and a water explosion model test of a 2.5-m-high concrete gravity dam is designed.The water pressure and the acceleration response of the dam body in the test are analysed.The pressure characteristics and dynamic response of the dam body are assessed.Taking the dam damage test as an example,a numerical model of concrete gravity dam damage is established,and the damage evolution of the dam body is analysed.By combining experiments and numerical simulations,the damage characteristics of the dam body under the action of different charge water explosions are clarified.The integrity of the dam body is well maintained under the action of a small-quantity water explosion,and the dynamic response of the dam body is mainly caused by the shock wave.Both the shock wave and the bubble pulsation cause the dam body to accelerate,and the peak acceleration of the dam body under the action of the bubble pulsation is only one percent of the peak acceleration of the dam body under the action of the shock wave.When subjected to explosions in large quantities of water,the dam body is seriously damaged.Under the action of a shock wave,the dam body produces a secondary acceleration response,which is generated by an internal interaction after the dam body is damaged.The damage evolution process of the dam body under the action of a large-scale water explosion is analysed,and it is found that the shock wave pressure of the water explosion causes local damage to the dam body facing the explosion.After the peak value of the shock wave,the impulse continues to act on the dam body,causing cumulative damage and damage inside the dam body.

ams关注传感、照明和可视化的CMOS图像传感器

工业图像传感器市场是具有巨大潜力的市场。在过去10 年中,质量检查应用中的图像传感器已从CCD 过渡到CMOS。未来10 年,工业4.0 将推动更多新应用。智能嵌入式2D和3D 解决方案将支持新的颠覆性应用。ams 致力于通过提供必要的光学解决方案,为传感,照明和可视化趋势提供领先的解决方案。

AMS-C磁谱仪试运行及调试

AMS实验是由丁肇中教授所领导的国际空间站上第一个大型物理实验，目的是寻找反物质组成的宇宙、寻找暗物质的来源和测量宇宙线的来源。AMS-C系统是AMS-01磁谱仪的地面版本，主要由硅微条探测器、飞行时间探测器和永久磁铁组成。在安装调试期间，静电感应、高压放电、电源高频脉冲、电源谐波噪声和强电磁干扰等严重影响了AMS—C系统的电子设备。通过采用良好地线、屏蔽和电源分布准则等措施，有效抑制了尖峰、浪涌等干扰，还进一步使用隔离变压器和滤波器来提高系统抗干扰能力。

Speed and surface steepness affect internal tibial loading during running

Background:Internal tibial loading is influenced by modifiable factors with implications for the risk of stress injury.Runners encounter varied surface steepness(gradients)when running outdoors and may adapt their speed according to the gradient.This study aimed to quantify tibial bending moments and stress at the anterior and posterior peripheries when running at different speeds on surfaces of different gradients.Methods:Twenty recreational runners ran on a treadmill at 3 different speeds(2.5 m/s,3.0 m/s,and 3.5 m/s)and gradients(level:0%;uphill:+5%,+10%,and+15%;downhill:-5%,-10%,and-15%).Force and marker data were collected synchronously throughout.Bending moments were estimated at the distal third centroid of the tibia about the medial-lateral axis by ensuring static equilibrium at each 1%of stance.Stress was derived from bending moments at the anterior and posterior peripheries by modeling the tibia as a hollow ellipse.Two-way repeated-measures analysis of variance were conducted using both functional and discrete statistical analyses.Results:There were significant main effects for running speed and gradient on peak bending moments and peak anterior and posterior stress.Higher running speeds resulted in greater tibial loading.Running uphill at+10%and+15%resulted in greater tibial loading than level running.Running downhill at-10%and-15%resulted in reduced tibial loading compared to level running.There was no difference between+5%or-5%and level running.Conclusion:Running at faster speeds and uphill on gradients≥+10%increased internal tibial loading,whereas slower running and downhill running on gradients≥-10%reduced internal loading.Adapting running speed according to the gradient could be a protective mechanism,providing runners with a strategy to minimize the risk of tibial stress injuries.

The simulation of ultrasonic beams with a Gaussian beam equivalent point source model

Point Sources and Gaussian beams are used frequently as fundamental building blocks for developing ultrasonic beam models. Both these models have different weaknesses that limit their effectiveness. Here, we will show that one can develop a Gaussian Beam Equivalent Point Source （GBEPS） model that removes those weaknesses and combines the accuracy and versatility of the point source models with much of the speed and well-behaved nature of Gaussian beam models. We will demonstrate the efficiency and versatility of this new GBEPS model in simulating the beams generated from ultrasonic phased arrays, using as few as one Gaussian beam per element of the array. A single element GBEPS model will be shown to be as accurate as a point source model even when substantial beam focusing or steering is present in the array or where the array beam is transmitted through an interface. At the same time the GBEPS model will be shown to be several orders of magnitude faster than the point source model.

Physics-data coupling-driven method to predict the penetration depth into concrete targets

The projectile penetration process into concrete target is a nonlinear complex problem.With the increase ofexperiment data,the data-driven paradigm has exhibited a new feasible method to solve such complex prob-lem.However,due to poor quality of experimental data,the traditional machine learning(ML)methods,whichare driven only by experimental data,have poor generalization capabilities and limited prediction accuracy.Therefore,this study intends to exhibit a ML method fusing the prior knowledge with experiment data.The newML method can constrain the fitting to experimental data,improve the generalization ability and the predic-tion accuracy.Experimental results show that integrating domain prior knowledge can effectively improve theperformance of the prediction model for penetration depth into concrete targets.

Highlights in recent wireless power IC research

Wireless power transfer(WPT)has been a popular topic in power integrated circuit(IC)designs in the past decade.As slogan"cutting the last wire"presented in ISSCC’15[1],WPT is poised to take over many wired power deliveries applica-tions today,just like what happened to wireless communica-tion nowadays.Over the years,WPT has become more mature and more wirelessly charged or powered products have become available on the market.This mini review intends to summarize recent breakthroughs in WPT inte-grated circuits(IC)research.

The metabolic profiling of Chinese yam fermented by Saccharomyces boulardii and the biological activities of its ethanol extract in vitro

Chinese yam(Dioscorea opposita Thunb.),as one of the medicinal and edible homologous plants,is rich in various nutrients and functional factors.In this study,Chinese yam fermented by Saccharomyces boulardii was performed to investigate its bioactive components and metabolic profile.And then,the main bioactive components and biological activities of fermented Chinese yam ethanol extract(FCYE)were evaluated.Results showed that there were 49 up-regulated metabolites and 52 down-regulated metabolites in fermented Chinese yam compared to unfermented Chinese yam.Besides,corresponding metabolic pathways analysis initially revealed that the distribution of bioactive substances was concentrated on alcoholsoluble small molecular substances.Ulteriorly,the total polyphenol content and the total flavonoid content in FCYE were significantly increased,and the corresponding antioxidant and immunomodulatory activities in vitro were also significantly enhanced.Our study provided a new reference for the comprehensive utilization of Chinese yam and laid a theoretical foundation for the development and application of natural probiotic-fermented products.

Anderson Acceleration of Gradient Methods with Energy for Optimization Problems

Anderson acceleration(AA)is an extrapolation technique designed to speed up fixed-point iterations.For optimization problems,we propose a novel algorithm by combining the AA with the energy adaptive gradient method(AEGD)[arXiv:2010.05109].The feasibility of our algorithm is ensured in light of the convergence theory for AEGD,though it is not a fixed-point iteration.We provide rigorous convergence rates of AA for gradient descent(GD)by an acceleration factor of the gain at each implementation of AA-GD.Our experimental results show that the proposed AA-AEGD algorithm requires little tuning of hyperparameters and exhibits superior fast convergence.

Abomasal infusion of branched-chain amino acids or branched-chain keto-acids alter lactation performance and liver triglycerides in fresh cows

Background Dairy cows are at high risk of fatty liver disease in early lactation,but current preventative measures are not always effective.Cows with fatty liver have lower circulating branched-chain amino acid(BCAA)concentra-tions whereas cows with high circulating BCAA levels have low liver triglyceride(TG).Our objective was to determine the impact of BCAA and their corresponding ketoacids(branched-chain ketoacids,BCKA)on production performance and liver TG accumulation in Holstein cows in the first 3 weeks postpartum.Methods Thirty-six multiparous Holstein cows were used in a randomized block design experiment.Cows were abomasally infused for the first 21 d postpartum with solutions of 1)saline(CON,n=12);2)BCA(67 g valine,50 g leu-cine,and 34 g isoleucine,n=12);and 3)BCK(77 g 2-ketovaline calcium salt,57 g 2-ketoleucine calcium salt,and 39 g 2-ketoisoleucine calcium salt,n=12).All cows received the same diet.Treatment effects were determined using PROC GLIMMIX in SAS.Results No differences were detected for body weight,body condition score,or dry matter intake averaged over the first 21 d postpartum.Cows receiving BCK had significantly lower liver TG concentrations compared to CON(6.60%vs.4.77%,standard error of the mean(SEM)0.49)during the first 3 weeks of lactation.Infusion of BCA increased milk yield(39.5 vs.35.3 kg/d,SEM 1.8),milk fat yield(2.10 vs.1.69 kg/d,SEM 0.08),and lactose yield(2.11 vs.1.67 kg/d,SEM 0.07)compared with CON.Compared to CON,cows receiving BCA had lower plasma glucose(55.0 vs.59.2 mg/dL,SEM 0.86)but higherβ-hydroxybutyrate(9.17 vs.6.00 mg/dL,SEM 0.80).Conclusions Overall,BCAA supplementation in this study improved milk production,whereas BCKA supplementa-tion reduced TG accumulation in the liver of fresh cows.

基于注意力机制与自适应特征融合的群养猪身份识别

针对群养猪攻击过程中身体形变和重叠影响猪身份识别精度的问题,开发一种基于注意力机制和自适应特征融合的深度学习方法以提高猪身份识别精度。录制猪栏中8只猪每天8小时共3天的视频,并筛选含攻击的16830帧作为数据集。首先,采用ResNet50提取猪的卷积神经网络(CNN)特征;然后,采用特征金字塔网络(FPN)在ResNet50中选择3层不同尺度的特征,以优化这些特征的定位和语义信息;接着,采用自注意力机制提高这些特征的区分度,并采用自适应空间特征融合(ASFF)以融合不同尺度的特征;最后,利用卷积和Sigmoid函数相结合的检测器对猪身份进行识别。使用该方法后,猪身份识别的均值平均精度(mAP)达到95.59%,速度达到37.6 f/s。结果表明,该方法能够在攻击场景下有效识别猪身份,有助于将攻击识别从群体级细化为个体级。

Population genomic analysis reveals key genetic variations and the driving force for embryonic callus induction capability in maize

Genetic transformation has been an effective technology for improving the agronomic traits of maize.However,it is highly reliant on the use of embryonic callus(EC)and shows a serious genotype dependence.In this study,we performed genomic sequencing for 80 core maize germplasms and constructed a high-density genomic variation map using our newly developed pipeline(MQ2Gpipe).Based on the induction rate of EC(REC),these inbred lines were categorized into three subpopulations.The low-REC germplasms displayed more abundant genetic diversity than the high-REC germplasms.By integrating a genome-wide selective signature screen and region-based association analysis,we revealed 95.23 Mb of selective regions and 43 REC-associated variants.These variants had phenotypic variance explained values ranging between 21.46 and 49.46%.In total,103 candidate genes were identified within the linkage disequilibrium regions of these REC-associated loci.These genes mainly participate in regulation of the cell cycle,regulation of cytokinesis,and other functions,among which MYB15 and EMB2745 were located within the previously reported QTL for EC induction.Numerous leaf area-associated variants with large effects were closely linked to several REC-related loci,implying a potential synergistic selection of REC and leaf size during modern maize breeding.

Experimental and numerical study on protective effect of RC blast wall against air shock wave

Prototype experiments were carried out on the explosion-proof performance of the RC blast wall.The mass of TNT detonated in the experiments is 5 kg and 20 kg respectively.The shock wave overpressure was tested in different regions.The above experiments were numerically simulated,and the simulated shock wave overpressure waveforms were compared with that tested and given by CONWEP program.The results show that the numerically simulated waveform is slightly different from the test waveform,but similar to CONWEP waveform.Through dimensional analysis and numerical simulation under different working conditions,the equation for the attenuation rate of the diffraction overpressure behind the blast wall was obtained.According to the corresponding standards,the degree of casualties and the damage degree of the brick concrete building at a certain distance behind the wall can be determined when parameters are set.The above results can provide a reference for the design and construction of the reinforced concrete blast wall.

Experimental investigation of engineered geopolymer composite for structural strengthening against blast loads

The recent increase in blast/bombing incidents all over the world has pushed the development of effective strengthening approaches to enhance the blast resistance of existing civil infrastructures.Engineered geopolymer composite(EGC)is a promising material featured by eco-friendly,fast-setting and strain-hardening characteristics for emergent strengthening and construction.However,the fiber optimization for preparing EGC and its protective effect on structural elements under blast scenarios are uncertain.In this study,laboratory tests were firstly conducted to evaluate the effects of fiber types on the properties of EGC in terms of workability,dry shrinkage,and mechanical properties in compression,tension and flexure.The experimental results showed that EGC containing PE fiber exhibited suitable workability,acceptable dry shrinkage and superior mechanical properties compared with other types of fibers.After that,a series of field tests were carried out to evaluate the effectiveness of EGC retrofitting layer on the enhancement of blast performance of typical elements.The tests include autoclaved aerated concrete(AAC)masonry walls subjected to vented gas explosion,reinforced AAC panels subjected to TNT explosion and plain concrete slabs subjected to contact explosion.It was found that EGC could effectively enhance the blast resistance of structural elements in different scenarios.For AAC masonry walls and panels,with the existence of EGC,the integrity of specimens could be maintained,and their deflections and damage were significantly reduced.For plain concrete slabs,the EGC overlay could reduce the diameter and depth of the crater and spallation of specimens.

Efficiency of Botanical and Chemical Pesticides on the Control of Field Insect Pests under Cowpea Production

The pulse cowpea [Vigna unguiculata (L.) Walp] holds a significant agricultural position in Uganda, ranking fourth among legume crops, following common beans, groundnuts, and soybeans. Known for its versatility, cowpeas are consumable at various developmental stages, from early seedling to maturity. However, the crop faces persistent pest challenges at each stage, leading to substantial yield losses. In Uganda, chemical insecticides are the primary pest control means, but their increased and excessive use raises environmental, health, and economic concerns. This has prompted a quest for alternative and sustainable solutions, prompting an exploration of botanical insecticides. This study, conducted at Makerere University Agricultural Research Institute (MUARIK), aimed to evaluate the effectiveness of three selected botanical insecticides versus four established chemical insecticides for managing cowpea insect pests under field conditions. The treatments included: Carbofuran, Cypermethrin 10% EC, Dimethoate, Pestwin, Pyrethrum ewc , Pyrethrum 5ew, Profenofos 40% Cypermethrin 4% EC mix, and Untreated, arranged in a randomized complete block design with three replications. The significant pests studied were aphids, thrips, pod-sucking bugs, and legume pod borer. Results indicated substantial impacts of the treatments on pest infestation, with Profenofos 40% Cypermethrin 4% EC being the most effective against most pests. The plant parameter, plant height, was significantly affected by treatments in 2016B, while the number of pods was impacted in 2017A. Pestwin, a botanical insecticide blend (containing Azadirachtin indica, Pongamia pinnata, and Ricinus communis extracts) demonstrated superior efficacy against cowpea aphids. Moreover, it positively influenced plant height, number of pods, and pod biomass, surpassing many chemical insecticides. Pestwin’s environmental friendliness positions it as a potential contributor to reducing environmental pollution, making it a promising candidate for inclusion in IPM programs. Overall, the study underscores the importance of exploring botanical alternatives to chemical insecticides for sustainable pest management in cowpea cultivation.

Exploring the genetic control of sweat gland characteristics in beef cattle for enhanced heat tolerance

Background Thermal stress in subtropical regions is a major limiting factor in beef cattle production systems with around$369 million being lost annually due to reduced performance.Heat stress causes numerous physiological and behavioral disturbances including reduced feed intake and decreased production levels.Cattle utilize various physiological mechanisms such as sweating to regulate internal heat.Variation in these traits can help identify genetic variants that control sweat gland properties and subsequently allow for genetic selection of cattle with greater thermotolerance.Methods This study used 2,401 Brangus cattle from two commercial ranches in Florida.Precise phenotypes that contribute to an animal's ability to manage heat stress were calculated from skin biopsies and included sweat gland area,sweat gland depth,and sweat gland length.All animals were genotyped with the Bovine GGP F250K,and BLUPF90 software was used to estimate genetic parameters and for Genome Wide Association Study.Results Sweat gland phenotypes heritability ranged from 0.17 to 0.42 indicating a moderate amount of the phenotypic variation is due to genetics,allowing producers the ability to select for favorable sweat gland properties.A weighted single-step GWAS using sliding 10 kb windows identified multiple quantitative trait loci(QTLs)explaining a significant amount of genetic variation.QTLs located on BTA7 and BTA12 explained over 1.0%of genetic variance and overlap the ADGRV1 and CCDC168 genes,respectively.The variants identified in this study are implicated in processes related to immune function and cellular proliferation which could be relevant to heat management.Breed of Origin Alleles(BOA)were predicted using local ancestry in admixed populations(LAMP-LD),allowing for identification of markers'origin from either Brahman or Angus ancestry.A BOA GWAS was performed to identify regions inherited from particular ancestral breeds that might have a significant impact on sweat gland phenotypes.Conclusions The results of the BOA GWAS indicate that both Brahman and Angus alleles contribute positively to sweat gland traits,as evidenced by favorable marker effects observed from both genetic backgrounds.Understanding and utilizing genetic traits that confer better heat tolerance is a proactive approach to managing the impacts of climate change on livestock farming.

Superconvergence of Direct Discontinuous Galerkin Methods:Eigen-structure Analysis Based on Fourier Approach

This paper investigates superconvergence properties of the direct discontinuous Galerkin(DDG)method with interface corrections and the symmetric DDG method for diffusion equations.We apply the Fourier analysis technique to symbolically compute eigenvalues and eigenvectors of the amplification matrices for both DDG methods with different coefficient settings in the numerical fluxes.Based on the eigen-structure analysis,we carry out error estimates of the DDG solutions,which can be decomposed into three parts:(i)dissipation errors of the physically relevant eigenvalue,which grow linearly with the time and are of order 2k for P^(k)(k=2,3)approximations;(ii)projection error from a special projection of the exact solution,which is decreasing over the time and is related to the eigenvector corresponding to the physically relevant eigenvalue;(iii)dissipative errors of non-physically relevant eigenvalues,which decay exponentially with respect to the spatial mesh sizeΔx.We observe that the errors are sensitive to the choice of the numerical flux coefficient for even degree P^(2)approximations,but are not for odd degree P^(3)approximations.Numerical experiments are provided to verify the theoretical results.

Evaluation of the Impact of Driver Behavior on Back of Queues Events in Work Zones Using the SHRP2 Naturalistic Driving Study Data

The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE and 209 “normal” events which were used as controls. The traces included representing 209 unique drivers. A Mixed-Effects Logistic Regression model was developed with probability of a SCE as the response variable and driver and work zone characteristics as predictor variables. The final model indicated glances over 1 second away from the driving task and following closely increased risk of an SCE by 3.8 times and 2.9 times, respectively. Average speed was negatively correlated to crash risk. This is counterintuitive since in most cases, it is expected that higher speeds are related to back of queue crashes. However, most queues form under congested conditions. As a result, vehicles encountering a back of queue would be more likely to be traveling at lower speeds.

Artificial Intelligence-Based Sentiment Analysis of Dynamic Message Signs that Report Fatality Numbers Using Connected Vehicle Data

This study presents results from sentiment analysis of Dynamic message sign (DMS) message content, focusing on messages that include numbers of road fatalities. As a traffic management tool, DMS plays a role in influencing driver behavior and assisting transportation agencies in achieving safe and efficient traffic movement. However, the psychological and behavioral effects of displaying fatality numbers on DMS remain poorly understood;hence, it is important to know the potential impacts of displaying such messages. The Iowa Department of Transportation displays the number of fatalities on a first screen, followed by a supplemental message hoping to promote safe driving;an example is “19 TRAFFIC DEATHS THIS YEAR IF YOU HAVE A SUPER BOWL DON’T DRIVE HIGH.” We employ natural language processing to decode the sentiment and undertone of the supplementary message and investigate how they influence driving speeds. According to the results of a mixed effect model, drivers reduced speeds marginally upon encountering DMS fatality text with a positive sentiment with a neutral undertone. This category had the largest associated amount of speed reduction, while messages with negative sentiment with a negative undertone had the second largest amount of speed reduction, greater than other combinations, including positive sentiment with a positive undertone.

Investigation of Projectile Impact Behaviors of Graphene Aerogel Using Molecular Dynamics Simulations

Graphene aerogel(GA),as a novel solid material,has shown great potential in engineering applications due to its unique mechanical properties.In this study,the mechanical performance of GA under high-velocity projectile impacts is thoroughly investigated using full-atomic molecular dynamics(MD)simulations.The study results show that the porous structure and density are key factors determining the mechanical response of GA under impact loading.Specifically,the impact-induced penetration of the projectile leads to the collapse of the pore structure,causing stretching and subsequent rupture of covalent bonds in graphene sheets.Moreover,the effects of temperature on the mechanical performance of GA have been proven to be minimal,thereby highlighting the mechanical stability of GA over a wide range of temperatures.Finally,the energy absorption density(EAD)and energy absorption efficiency(EAE)metrics are adopted to assess the energy absorption capacity of GA during projectile penetration.The research findings of this work demonstrate the significant potential of GA for energy absorption applications.