Microscopic defects formation and dynamic mechanical response analysis of Q345 steel plate subjected to explosive load

As the basic protective element, steel plate had attracted world-wide attention because of frequent threats of explosive loads. This paper reports the relationships between microscopic defects of Q345 steel plate under the explosive load and its macroscopic dynamics simulation. Firstly, the defect characteristics of the steel plate were investigated by stereoscopic microscope(SM) and scanning electron microscope(SEM). At the macroscopic level, the defect was the formation of cave which was concentrated in the range of 0-3.0 cm from the explosion center, while at the microscopic level, the cavity and void formation were the typical damage characteristics. It also explains that the difference in defect morphology at different positions was the combining results of high temperature and high pressure. Secondly, the variation rules of mechanical properties of steel plate under explosive load were studied. The Arbitrary Lagrange-Euler(ALE) algorithm and multi-material fluid-structure coupling method were used to simulate the explosion process of steel plate. The accuracy of the method was verified by comparing the deformation of the simulation results with the experimental results, the pressure and stress at different positions on the surface of the steel plate were obtained. The simulation results indicated that the critical pressure causing the plate defects may be approximately 2.01 GPa. On this basis, it was found that the variation rules of surface pressure and microscopic defect area of the Q345 steel plate were strikingly similar, and the corresponding mathematical relationship between them was established. Compared with Monomolecular growth fitting models(MGFM) and Logistic fitting models(LFM), the relationship can be better expressed by cubic polynomial fitting model(CPFM). This paper illustrated that the explosive defect characteristics of metal plate at the microscopic level can be explored by analyzing its macroscopic dynamic mechanical response.

Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics

Background:Traumatic brain injury can be caused by head impacts,but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo,and the characteristics of different types of impacts are not well studied.We investigated the spectral characteristics of different head impact types with kinematics classification.Methods:Data were analyzed from 3262 head impacts from lab reconstruction,American football,mixed martial arts,and publicly available car crash data.A random forest classifier with spectral densities of linear acceleration and angular velocity was built to classify head impact types(e.g.,football,car crash,mixed martial arts).To test the classifier robustness,another 271 lab-reconstructed impacts were obtained from 5 other instrumented mouthguards.Finally,with the classifier,type-specific,nearest-neighbor regression models were built for brain strain.Results:The classifier reached a median accuracy of 96% over 1000 random partitions of training and test sets.The most important features in the classification included both low-and high-frequency features,both linear acceleration features and angular velocity features.Different head impact types had different distributions of spectral densities in low-and high-frequency ranges(e.g.,the spectral densities of mixed martial arts impacts were higher in the high-frequency range than in the low-frequency range).The type-specific regression showed a generally higher R2value than baseline models without classification.Conclusion:The machine-learning-based classifier enables a better understanding of the impact kinematics spectral density in different sports,and it can be applied to evaluate the quality of impact-simulation systems and on-field data augmentation.

A digital microfluidic single-cell manipulation systemoptimized by extending-depth-of-field device

Microfuidic systems have been widely utilized in high-throughput biology analysis,but thedificulties in iquid manipulation and cell cultivation limit its application.This work has developed a new digital microfluidic(DMF)system for on-demand droplet control.By adopting anextending-depth-of-field(EDoF)phase modulator to the optical system,the entire depth of themicrofluidic channel can be covered in one image without any refocusing process,ensuring that 95%of the particles in the droplet are captured within three shots together with shaking pro-cesses.With this system,suspension droplets are generated and droplets containing only oneyeast cll can be recognized,then each single cell is cultured in the array of the chip.Byobservingtheir growth in cell numbers and the green fluorescence protein(GFP)production via fluorescence imaging,the single cell with the highest production can be identified.The results haveproved the heterogeneity of yeast cells,and showed that the combined system can be applied forrapid single-cell sorting,cultivation,and analysis.

Evolvement behavior of microstructure and H_2O adsorption of lignite pyrolysis

The effect of pyrolysis on the microstructure and moisture adsorption of lignite was investigated with low field nuclear magnetic resonance spectroscopy. Changes in oxygen-containing groups were analyzed by Fourier transform infrared spectroscopy （FTIR）, and H20 adsorption mechanism on the surface of lignite pyrolysis was inferred. Two major changes in the pore structure of lignite char were observed as temperature increased in 105-200 ℃ and 500-700 ℃. Pyrolysis temperature is a significant factor in removing carboxyl and phenolic hydroxyl from lignite. Variation of ether bond content can be divided into three stages; the content initially increased, then decreased, and finally increased. The equilibrium adsorption ratio, content of oxygen-containing groups, and variation of pore volume below 700° were closely correlated with each other. The amount of adsorbed water on char pyrolyzed at 700 ℃ increased. Moreover, the adsorption capacity of the lignite decreased, and the adsorption state changed.

How does a woodpecker work? An impact dynamics approach

To understand how a woodpecker is able accelerate its head to such a high velocity in a short amount of time,a multi-rigid-segment model of a woodpecker＇s body is established in this study.Based on the skeletal specimen of the woodpecker and several videos of woodpeckers pecking,the parameters of a three-degree-of-freedom system are determined.The high velocity of the head is found to be the result of a whipping effect,which could be affected by muscle torque and tendon stiffness.The mechanism of whipping is analyzed by comparing the response of a hinged rod to that of a rigid rod.Depending on the parameters,the dynamic behavior of a hinged rod is classified into three response modes.Of these,a high free-end velocity could be achieved in mode II.The model is then generalized to a multihinge condition,and the free-end velocity is found to increase with hinge number,which explains the high free-end velocity resulting from whipping.Furthermore,the effects of some other factors,such as damping and mass distribution,on the velocity are also discussed.

Effects of Different Broth Enrichment upon Phage Magnetoelastic Biosensor for Fast Detecting Low <i>Salmonella</i>Counts on Problematic Produce

According to the FDA Bacteriological Analytical Manual (BAM) for Salmonella identification in produce, two pre-enrichment steps with 48 hours of incubation are the golden procedures. Lactose broth is recommended for the first pre-enrichment step medium for leafy greens, and the universal pre-enrichment (UP) broth is for tomatoes. However, the suggested broths were evaluated to have the maximum performance using the culture-dependent methods, and may not be applied to other methods, such as biosensor detection platform. A wireless bacteriophage magnetoelastic (ME) biosensor has been recently developed for real-time or rapid detection of food-borne pathogens in various foods. This affinity-based biosensor utilizes a phage oligonucleotide as the probe to capture target bacteria. In this study, the efficiencies of different pre-enrichment media for early detection of low Salmonella on spinach leaves and tomatoes use ME biosensors to shorten detection time. Four broths of modified peptone water, Lennox broth (LB), lactose broth, and UP broth were selected in this study. Various pre-enrichment times for ME biosensor detection were investigated. After spiking 4 cfu/g Salmonella on the tomatoes surfaces, the phage biosensor was able to detect Salmonella within 5 hours of pre-enrichment comparing to 24 hours in the FDA procedures. For Salmonella spiked spinach leaves, the same medium showed Salmonella positive within 7 hours. This study demonstrated that LB broth is the best medium to shorten pre-enrichment time to pass Salmonella number detection thresholds for ME biosensor detection in spinach and tomatoes when comparing to FDA procedures.

Factors Affecting Ion Thruster’s Performance

In this project,we investigated how ion thrusters produce propulsion and how the design of ion thrusters affects the performance of the thruster.In the experiment,we build a high voltage power supply(0-50 kV)and foil rings to produce ion wind.When considering the design of the thruster,we focus on three variables:the volume of the space,where ions are produced and the electric field intensity.Thus,to investigate the first variable we made foil rings with different radius and change the distance between the ring and positive cathode.To determine the propulsion produced we use a speed sensor to determine the magnitude of the wind produced.

High Magnetic Property and Toxicity of Particulate Matter Generated during Welding and Cutting Processes

Magnetic particulate matter(PM)has raised increasing concern due to its abundant presence in ambient air and negative health impact.However,there is still a lack of comprehensive understanding of their emission sources and toxicities.We here report the observation of high magnetic property and toxicity of PM generated during typical welding and cutting processes.Magnetite,formed during high-temperature operation with less oxygen pressure,was revealed to be the major magnetic contributor.The averaged saturation magnetization and magnetic susceptibility values of fine PM(PM_(2.5))from welding processes are 1.4−4.2 times greater than those of PM emitted from other unintended emission sources,including iron and steel plants and brake wear,while they are 2.0−5.7 times greater for the cutting processes.Furthermore,PM_(2.5)from welding and cutting processes are nearly 3.5−4.5 times more neurovirulent and 2.1−7.0 times more likely to induce oxidative stress than those from other magnetic sources in the nerve cells lines.Moreover,all of these magnetic PM_(2.5)exhibit greater negative health effects than typical atmospheric PM_(2.5)collected in Shanghai urban regions.These new findings suggest that appropriate occupational protection measures should be implemented for the welding and cutting process to reduce adverse health impacts.

Ribosome biogenesis in disease:new players and therapeutic targets

The ribosome is a multi-unit complex that translates mRNA into protein.Ribosome biogenesis is the process that generates ribosomes and plays an essential role in cell proliferation,differentiation,apoptosis,development,and transformation.The mTORC1,Myc,and noncoding RNA signaling pathways are the primary mediators that work jointly with RNA polymerases and ribosome proteins to control ribosome biogenesis and protein synthesis.Activation of mTORC1 is required for normal fetal growth and development and tissue regeneration after birth.Myc is implicated in cancer development by enhancing RNA Pol II activity,leading to uncontrolled cancer cell growth.The deregulation of noncoding RNAs such as microRNAs,long noncoding RNAs,and circular RNAs is involved in developing blood,neurodegenerative diseases,and atherosclerosis.We review the similarities and differences between eukaryotic and bacterial ribosomes and the molecular mechanism of ribosome-targeting antibiotics and bacterial resistance.We also review the most recent findings of ribosome dysfunction in COVID-19 and other conditions and discuss the consequences of ribosome frameshifting,ribosome-stalling,and ribosome-collision.We summarize the role of ribosome biogenesis in the development of various diseases.Furthermore,we review the current clinical trials,prospective vaccines for COVID-19,and therapies targeting ribosome biogenesis in cancer,cardiovascular disease,aging,and neurodegenerative disease.

Elliptical model for surface topography prediction in five-axis flank milling

In five-axis flank milling operations,the intersecting surfaces of different cutting edges create roughness on the milled surfaces that cannot be ignored in situations with strict requirements,especially in aeronautical manufacturing.To focus on motion problems in milling operations,this paper presents a new model that utilizes elliptical paths as cutting edge trajectories on 3D surface topography machined by peripheral milling.First,the cutter parallel axis offset and location angle are considered,which change the location of the ellipse center and intersection point of the cutting edges.Then,through the proposed model,the predicted surface topography is obtained,and the factors that affect the development tendency of roughness are analyzed.Next,the effects of the cutter location position(CLP)geometric parameters,cutter parallel axis offset and curvature on the roughness are evaluated by a numerical simulation.Finally,machining tests are carried out to validate the model predictions,and the results show that the surface topography predictions correspond well with the experimental results.