Threshold friction velocity influenced by soil particle size within the Columbia Plateau, northwestern United States

Wind erosion is a geomorphic process in arid and semi-arid areas and has substantial implications for regional climate and desertification.In the Columbia Plateau of northwestern United States,the emissions from fine particles of loessial soils often contribute to the exceedance of inhalable particulate matter(PM)with an aerodynamic diameter of 10μm or less(PM10)according to the air quality standards.However,little is known about the threshold friction velocity(TFV)for particles of different sizes that comprise these soils.In this study,soil samples of two representative soil types(Warden sandy loam and Ritzville silt loam)collected from the Columbia Plateau were sieved to seven particle size fractions,and an experiment was then conducted to determine the relationship between TFV and particle size fraction.The results revealed that soil particle size significantly affected the initiation of soil movement and TFV;TFV ranged 0.304-0.844 and 0.249-0.739 m/s for different particle size fractions of Ritzville silt loam and Warden sandy loam,respectively.PM10 and total suspended particulates(TSP)emissions from a bed of 63-90μm soil particles were markedly higher for Warden sandy loam than for Ritzville silt loam.Together with the lower TFV of Warden sandy loam,dust emissions from fine particles(<100μm in diameter)of Warden sandy loam thus may be a main contributor to dust in the region's atmosphere,since the PM10 emissions from the soil erosion surfaces and its ensuing suspension within the atmosphere constitute an essential process of soil erosion in the Columbia Plateau.Developing and implementing strategic land management practices on sandy loam soils is therefore necessary to control dust emissions in the Columbia Plateau.

用Velocity Verlet积分器改进HMC抽样方法

Hamilton Monte Carlo (HMC)方法是一种常用的快速抽样方法.在对哈密顿方程进行抽样时,HMC方法使用Leapfrog积分器,这可能造成方程的位置及动量的迭代值在时间上不同步,其产生的误差会降低抽样效率及抽样结果的稳定性.为此,本文提出了IHMC(Improved HMC)方法,该方法用Velocity Verlet积分器替代Leapfrog积分器,每次迭代时都计算两变量在同一时刻的值.为验证方法的效果,本文进行了两个实验,一个是将该方法应用于非对称随机波动率模型(RASV模型)的参数估计,另一个是将方法应用于方差伽马分布的抽样,结果显示:IHMC方法比HMC方法的效率更高、结果更稳定.

ST-LSTM-SA:A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

The scarcity of in-situ ocean observations poses a challenge for real-time information acquisition in the ocean.Among the crucial hydroacoustic environmental parameters,ocean sound velocity exhibits significant spatial and temporal variability and it is highly relevant to oceanic research.In this study,we propose a new data-driven approach,leveraging deep learning techniques,for the prediction of sound velocity fields(SVFs).Our novel spatiotemporal prediction model,STLSTM-SA,combines Spatiotemporal Long Short-Term Memory(ST-LSTM) with a self-attention mechanism to enable accurate and real-time prediction of SVFs.To circumvent the limited amount of observational data,we employ transfer learning by first training the model using reanalysis datasets,followed by fine-tuning it using in-situ analysis data to obtain the final prediction model.By utilizing the historical 12-month SVFs as input,our model predicts the SVFs for the subsequent three months.We compare the performance of five models:Artificial Neural Networks(ANN),Long ShortTerm Memory(LSTM),Convolutional LSTM(ConvLSTM),ST-LSTM,and our proposed ST-LSTM-SA model in a test experiment spanning 2019 to 2022.Our results demonstrate that the ST-LSTM-SA model significantly improves the prediction accuracy and stability of sound velocity in both temporal and spatial dimensions.The ST-LSTM-SA model not only accurately predicts the ocean sound velocity field(SVF),but also provides valuable insights for spatiotemporal prediction of other oceanic environmental variables.

Quantitatively characterizing sandy soil structure altered by MICP using multi-level thresholding segmentation algorithm

The influences of biological,chemical,and flow processes on soil structure through microbially induced carbonate precipitation(MICP)are not yet fully understood.In this study,we use a multi-level thresholding segmentation algorithm,genetic algorithm(GA)enhanced Kapur entropy(KE)(GAE-KE),to accomplish quantitative characterization of sandy soil structure altered by MICP cementation.A sandy soil sample was treated using MICP method and scanned by the synchrotron radiation(SR)micro-CT with a resolution of 6.5 mm.After validation,tri-level thresholding segmentation using GAE-KE successfully separated the precipitated calcium carbonate crystals from sand particles and pores.The spatial distributions of porosity,pore structure parameters,and flow characteristics were calculated for quantitative characterization.The results offer pore-scale insights into the MICP treatment effect,and the quantitative understanding confirms the feasibility of the GAE-KE multi-level thresholding segmentation algorithm.

In vivo label-free measurement of blood flow velocity symmetry based on dual line scanning third-harmonic generation microscopy excited at the 1700 nm window

Measurement of bloodflow velocity is key to understanding physiology and pathology in vivo.While most measurements are performed at the middle of the blood vessel,little research has been done on characterizing the instantaneous bloodflow velocity distribution.This is mainly due to the lack of measurement technology with high spatial and temporal resolution.Here,we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation(THG)imaging technology.Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of bloodflow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo.Our results clearly show that the instantaneous bloodflow velocity is not symmetric under general conditions.

Flood Velocity Prediction Using Deep Learning Approach

Floods are one of the most serious natural disasters that can cause huge societal and economic losses.Extensive research has been conducted on topics like flood monitoring,prediction,and loss estimation.In these research fields,flood velocity plays a crucial role and is an important factor that influences the reliability of the outcomes.Traditional methods rely on physical models for flood simulation and prediction and could generate accurate results but often take a long time.Deep learning technology has recently shown significant potential in the same field,especially in terms of efficiency,helping to overcome the time-consuming associated with traditional methods.This study explores the potential of deep learning models in predicting flood velocity.More specifically,we use a Multi-Layer Perceptron(MLP)model,a specific type of Artificial Neural Networks(ANNs),to predict the velocity in the test area of the Lundesokna River in Norway with diverse terrain conditions.Geographic data and flood velocity simulated based on the physical hydraulic model are used in the study for the pre-training,optimization,and testing of the MLP model.Our experiment indicates that the MLP model has the potential to predict flood velocity in diverse terrain conditions of the river with acceptable accuracy against simulated velocity results but with a significant decrease in training time and testing time.Meanwhile,we discuss the limitations for the improvement in future work.

Origin of tradeoff between movement velocity and attachment duration of kinesin motor on a microtubule

Kinesin-1 motor protein is a homodimer containing two identical motor domains connected by a common long coiledcoil stalk via two flexible neck linkers. The motor can step on a microtubule with a velocity of about 1 μm·s-1and an attachment duration of about 1 s under physiological conditions. The available experimental data indicate a tradeoff between velocity and attachment duration under various experimental conditions, such as variation of the solution temperature,variation of the strain between the two motor domains, and so on. However, the underlying mechanism of the tradeoff is unknown. Here, the mechanism is explained by a theoretical study of the dynamics of the motor under various experimental conditions, reproducing quantitatively the available experimental data and providing additional predictions. How the various experimental conditions lead to different decreasing rates of attachment duration versus velocity is also explained.

Ultrafast Response and Threshold Adjustable Intelligent Thermoelectric Systems for Next‑Generation Self‑Powered Remote IoT Fire Warning

Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelligent self-powered remote IoT fire warning system,by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films.The flexible films,prepared by a convenient solution mixing,display p-type characteristic with excellent high-temperature stability,flame retardancy and TE(power factor of 239.7±15.8μW m^(-1) K^(-2))performances.The comprehensive morphology and structural analyses shed light on the underlying mechanisms.And the assembled TE devices(TEDs)exhibit fast fire warning with adjustable warning threshold voltages(1–10 mV).Excitingly,an ultrafast fire warning response time of~0.1 s at 1 mV threshold voltage is achieved,rivaling many state-of-the-art systems.Furthermore,TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure.Finally,a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier,analogto-digital converter and Bluetooth module.By combining TE characteristics,high-temperature stability and flame retardancy with wireless IoT signal transmission,TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.

Probing the Galactic Halo with RR Lyrae Stars.VI.The Radial Velocity Curve Templates of RRc Stars

We present radial velocity(RV)curve templates of RR Lyrae first-overtone(RRc)stars constructed with the Mg I b triplet and Hαlines using time-domain Medium-Resolution Survey spectra of seven RRc stars from Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)Data Release 9.Additionally,we derive the relation between the stellar RV curve amplitudes and g-band light curve amplitudes from Zwicky Transient Facility(ZTF)public survey.For those RRc stars without ZTF g-band light curves,we provide the conversions from the light curve amplitudes in ZTF r-and i-bands,Gaia G-band,and V-band from the All-Sky Automated Survey for Supernovae to those in ZTF g-band.We validate our RV curve templates using the RRc star SV Scl and find the uncertainties of systemic RV are less than 2.11 km s~(-1)and 6.08 km s~(-1)based on the Mg I b triplet and Hαlines,respectively.We calculate the systemic RVs of 30 RRc stars using the RV curve templates constructed with the Mg I b triplet and Hαlines and find the systemic RVs are comparable with each other.This RV curve template will be particularly useful for obtaining the systemic RV of RRc using the LAMOST spectroscopy.

Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical field.It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which is essential in smart healthcare.However,Personal Health Records(PHRs)are normally kept in public cloud servers controlled by IoMT service providers,so privacy and security incidents may be frequent.Fortunately,Searchable Encryption(SE),which can be used to execute queries on encrypted data,can address the issue above.Nevertheless,most existing SE schemes cannot solve the vector dominance threshold problem.In response to this,we present a SE scheme called Vector Dominance with Threshold Searchable Encryption(VDTSE)in this study.We use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’corresponding bits excluding wildcards is not less than a threshold t.Then,we solve the problem using the proposed technique modified in Hidden Vector Encryption(HVE).This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes.A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.

Chalcogenide Ovonic Threshold Switching Selector

Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.

Fractal model of spontaneous imbibition in low-permeability reservoirs coupled with heterogeneity of pore seepage channels and threshold pressure

Spontaneous imbibition(SI)is an important mechanism for enhancing oil recovery in low-permeability reservoirs.Due to the strong heterogeneity,and the non-Darcy flow,the construction of SI model for lowpermeability reservoirs is extremely challenging.Commonly,traditional SI models based on single or averaged capillary tortuosity ignore the influence of heterogeneity of pore seepage channels and the threshold pressure(TP)on imbibition.Therefore,in this work,based on capillary model and fractal theory,a mathematical model of characterizing SI considering heterogeneity of pore seepage channels is established.On this basis,the threshold pressure was introduced to determine the pore radius at which the wetted phase can displace oil.The proposed new SI model was verified by imbibition experimental data.The study shows that for weakly heterogeneous cores with permeability of 0-1 m D,the traditional SI model can characterize the imbibition process relatively accurately,and the new imbibition model can increase the coefficient of determination by 1.05 times.However,traditional model has serious deviations in predicting the imbibition recovery for cores with permeability of 10-50 m D.The new SI model coupling with heterogeneity of pore seepage channels and threshold pressure effectively solves this problem,and the determination coefficient is increased from 0.344 to 0.922,which is increased by2.68 times.For low-permeability reservoirs,the production of the oil in transitional pores(0.01-0.1μm)and mesopores(0.1-1μm)significantly affects the imbibition recovery,as the research shows that when the heterogeneity of pore seepage channels is ignored,the oil recovery in transitional pores and mesopores decreases by 7.54%and 4.26%,respectively.Sensitivity analysis shows that increasing interfacial tension,decreasing contact angle,oil-water viscosity ratio and threshold pressure will increase imbibition recovery.In addition,there are critical values for the influence of these factors on the imbibition recovery,which provides theoretical support for surfactant optimization.

A study of the soil water potential threshold values to trigger irrigation of ‘Shimizu Hakuto’ peach at pivotal fruit developmental stages

Water management is an important practice that affects fruit size and quality.Effective implementation of irrigation scheduling requires knowledge of the appropriate indicators and thresholds,which are established manly based on the effects of water deficits on final fruit quality.Few studies have focused on the real-time effects of water status on fruit and shoot growth.To establish soil water potential (ψ_(soil)) thresholds to trigger irrigation of peach at pivotal fruit developmental stages,photogrammetry,^(13)C labelling,and other techniques were used in this study to investigate real-time changes in stem diameter,fruit projected area,net leaf photosynthetic rate (P_(n)),and allocation of photoassimilates to fruit under soil water potential conditions ranging from saturation to stress in 6-year-old Shimizu hakuto’peach.Stem growth,fruit growth,and P_n exhibited gradually decreasing sensitivity to water deficits during fruit developmental stages I,II,and III.Stem diameter growth was significantly inhibited whenψ_(soil)dropped to-8.5,-7.6,and-5.4 k Pa,respectively.Fruit growth rate was low,reaching zero when theψ_(soil)was-9.0 to-23.1,-14.9 to-21.4,and-16.5 to-23.3 k Pa,respectively,and P_ndecreased significantly when theψ_(soil)reached-24.2,-22.7,and-20.4 kPa,respectively.In addition,more photoassimilates were allocated to fruit under moderateψ_(soil)conditions (-10.1 to-17.0 k Pa) than under otherψ_(soil)values.Our results revealed threeψ_(soil)thresholds,-10.0,-15.0,and-15.0 kPa,suitable for triggering irrigation during stages I,II,and III,respectively.These thresholds can be helpful for controlling excessive tree vigor,maintaining rapid fruit growth and leaf photosynthesis,and promoting the allocation of more photoassimilates to fruit.

Determining rock crack stress thresholds using ultrasonic through-transmission measurements

The crack initiation stress threshold is widely used in excavation industries as rock spalling strength when designing deep underground structures to avoid unwanted brittle failures.While various strain-based methods have been developed for the estimation of this critical design parameter,such methods are destructive and often requires subjective interpretations of the stress–strain curves,particularly in rocks with pre-existing microcracks or high porosity.This study explore the applicability of non-destructive ultrasonic through-transmission methods for determining rock damage levels by assessing the changes in transmitted signal characteristics during loading.The change in velocity,amplitude,dominant frequency,and root-mean-square voltage are investigated with four different rock types including marble,sandstone,granite,and basalt under various stress levels.Results suggest the rate of signal variations can be reliably used to estimate crack closure and crack initiation stress levels across the tested rocks before failure.Comparison of the results between the conventional techniques and the new proposed methods based on ultrasonic monitoring are further discussed.

Automatic velocity picking based on optimal key points tracking algorithm

Picking velocities from semblances manually is laborious and necessitates experience. Although various methods for automatic velocity picking have been developed, there remains a challenge in efficiently incorporating information from nearby gathers to ensure picked velocity aligns with seismic horizons while also improving picking accuracy. The conventional method of velocity picking from a semblance volume is computationally demanding, highlighting a need for a more efficient strategy. In this study, we introduce a novel method for automatic velocity picking based on multi-object tracking. This dynamic tracking process across different semblance panels can integrate information from nearby gathers effectively while maintaining computational efficiency. First, we employ accelerated density clustering on the velocity spectrum to discern cluster centers without the requirement for prior knowledge regarding the number of clusters. These cluster centers embody the maximum likelihood velocities of the main subsurface structures. Second, our proposed method tracks key points within the semblance volume. Kalman filter is adopted to adjust the tracking process, followed by interpolation on these tracked points to construct the final velocity model. Our synthetic data example demonstrates that our proposed algorithm can effectively rectify the picking errors of the clustering algorithm. We further compare the performances of the clustering method(CM), the proposed tracking method(TM), and the variational method(VM) on a field dataset from the Gulf of Mexico. The results attest that our method offers superior accuracy than CM, achieves comparable accuracy with VM, and benefits from a reduced computational cost.

Epidemic threshold influenced by non-pharmaceutical interventions in residential university environments

The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.

Novel damage constitutive models and new quantitative identification method for stress thresholds of rocks under uniaxial compression

Four key stress thresholds exist in the compression process of rocks,i.e.,crack closure stress(σ_(cc)),crack initiation stress(σ_(ci)),crack damage stress(σ_(cd))and compressive strength(σ_(c)).The quantitative identifications of the first three stress thresholds are of great significance for characterizing the microcrack growth and damage evolution of rocks under compression.In this paper,a new method based on damage constitutive model is proposed to quantitatively measure the stress thresholds of rocks.Firstly,two different damage constitutive models were constructed based on acoustic emission(AE)counts and Weibull distribution function considering the compaction stages of the rock and the bearing capacity of the damage element.Then,the accumulative AE counts method(ACLM),AE count rate method(CRM)and constitutive model method(CMM)were introduced to determine the stress thresholds of rocks.Finally,the stress thresholds of 9 different rocks were identified by ACLM,CRM,and CMM.The results show that the theoretical stress−strain curves obtained from the two damage constitutive models are in good agreement with that of the experimental data,and the differences between the two damage constitutive models mainly come from the evolutionary differences of the damage variables.The results of the stress thresholds identified by the CMM are in good agreement with those identified by the AE methods,i.e.,ACLM and CRM.Therefore,the proposed CMM can be used to determine the stress thresholds of rocks.

Velocity equation for grenades while impacting on dry sand media

This paper deals with the collision of sphere shape grenades with sand media.The central issue of the article is the establishing of an empirical velocity equation of the grenade while impacting on sand that is used to solve motion equations of the mechanical mechanism inside the impact grenade fuze.The paper focuses on impact velocities that are lower than 5 m s^(-1).An experiment was conducted to study the velocity of the grenade while impacting on dry sand.A high-speed camera video was used to capture the grenade positions.The grenade velocity in the impact process was generated from these video data.Some types of fitting curves are used to regress the velocity equation of the grenade while interacting with the sand media and the best-fitting model is chosen.The result shows the regression curve has a high correlation with the experiment data for grenade velocities below 5 m s^(-1).The received regression equation is useful for analyzing the working ability of the inertial mechanism inside the impact grenade or analyzing and choosing the appropriate parameters of each part in the inertial mechanism to meet the required characteristics of the mechanism.

Swimming velocity of spherical squirmers in a square tube at finite fluid inertia

The three-dimensional lattice Boltzmann method(LBM)is used to simulate the motion of a spherical squirmer in a square tube,and the steady motion velocity of a squirmer with different Reynolds numbers(Re,ranging from 0.1 to 2)and swimming types is investigated and analyzed to better understand the swimming characteristics of microorganisms in different environments.First,as the Reynolds number increases,the effect of the inertial forces becomes significant,disrupting the squirmer's ability to maintain its theoretical velocity.Specifically,as the Reynolds number increases,the structure of the flow field around the squirmer changes,affecting its velocity of motion.Notably,the swimming velocity of the squirmer exhibits a quadratic relationship with the type of swimming and the Reynolds number.Second,the narrow tube exerts a significant inhibitory effect on the squirmer motion.In addition,although chirality does not directly affect the swimming velocity of the squirmer,it can indirectly affect the velocity by changing its motion mode.

CT Thresholds for Spinal Bone Mineral Attenuation to Prioritize Eligible Older Women for Osteoporosis Screening

Introduction: Computed tomography (CT) measurements of bone mineral attenuation may be a useful means to identify older women who should be prioritized for bone mineral density screening. Methods: We compared bone mineral attenuation as measured in the L1 vertebra of CT studies to the results of dual-energy x-ray absorptiometry (DEXA) studies to determine what CT attenuation thresholds might yield a reasonable combination of sensitivity and specificity for the detection of osteoporosis. The study was limited to women between the ages of 65 and 75 years who had a DEXA study and a CT that included the L1 or adjacent vertebra performed within 3 years of the DEXA study. Results: There were 1226 women in this study, of whom 452 (38%) had osteoporosis based on a T-score ≤ −2.5 by DEXA. There were 830 CT studies performed with contrast and 396 studies which were performed without contrast. There was a statistically significant difference in the mean HU of those studies performed without contrast compared to those with contrast (unenhanced mean 103 HU versus 125 HU, p < 0.001). Different CT attenuation thresholds provided the most appropriate combination of sensitivity and specificity for the detection of osteoporosis when comparing CT studies performed without or with IV contrast and when all the CT data were used in aggregate. Conclusion: Different thresholds appear necessary when using the mean CT vertebral attenuation to identify older women for preferential referral for DEXA studies.