Extended wet sieving method for determination of complete particle size distribution of general soils

The traditional standard wet sieving method uses steel sieves with aperture?0.063 mm and can only determine the particle size distribution(PSD)of gravel and sand in general soil.This paper extends the traditional method and presents an extended wet sieving method.The extended method uses both the steel sieves and the nylon filter cloth sieves.The apertures of the cloth sieves are smaller than 0.063 mm and equal 0.048 mm,0.038 mm,0.014 mm,0.012 mm,0.0063 mm,0.004 mm,0.003 mm,0.002 mm,and 0.001 mm,respectively.The extended method uses five steps to separate the general soil into many material sub-groups of gravel,sand,silt and clay with known particle size ranges.The complete PSD of the general soil is then calculated from the dry masses of the individual material sub-groups.The extended method is demonstrated with a general soil of completely decomposed granite(CDG)in Hong Kong,China.The silt and clay materials with different particle size ranges are further examined,checked and verified using stereomicroscopic observation,physical and chemical property tests.The results further confirm the correctness of the extended wet sieving method.

Optical Modeling of Sea Salt Aerosols Using in situ Measured Size Distributions and the Impact of Larger Size Particles

Sea salt aerosols play a critical role in regulating the global climate through their interactions with solar radiation.The size distribution of these particles is crucial in determining their bulk optical properties.In this study,we analyzed in situ measured size distributions of sea salt aerosols from four field campaigns and used multi-mode lognormal size distributions to fit the data.We employed super-spheroids and coated super-spheroids to account for the particles’non-sphericity,inhomogeneity,and hysteresis effect during the deliquescence and crystallization processes.To compute the singlescattering properties of sea salt aerosols,we used the state-of-the-art invariant imbedding T-matrix method,which allows us to obtain accurate optical properties for sea salt aerosols with a maximum volume-equivalent diameter of 12μm at a wavelength of 532 nm.Our results demonstrated that the particle models developed in this study were successful in replicating both the measured depolarization and lidar ratios at various relative humidity(RH)levels.Importantly,we observed that large-size particles with diameters larger than 4μm had a substantial impact on the optical properties of sea salt aerosols,which has not been accounted for in previous studies.Specifically,excluding particles with diameters larger than 4μm led to underestimating the scattering and backscattering coefficients by 27%−38%and 43%−60%,respectively,for the ACE-Asia field campaign.Additionally,the depolarization ratios were underestimated by 0.15 within the 50%−70%RH range.These findings emphasize the necessity of considering large particle sizes for optical modeling of sea salt aerosols.

Particle size spatial distribution in landslide dams

The particle composition and spatial distribution of landslide-induced dam bodies are critical geotechnical parameters for studying the hazards of dam-break floods.However,current research often neglects the influence of the initial particle composition and spatial distribution of the landslide on the particle composition and spatial distribution of the landslide dam.This study investigated the impact of initial particle size distribution,volume,and sliding length on the energy and velocity changes of characteristic particles during the sliding process and the spatial distribution of particle sizes in the landslide dam body.Numerical simulations and physical models were employed to examine the effects of sequential gradient arrangements(where particle sizes decrease from top to bottom)and four other different initial particle arrangements on the energy and velocity changes of particles and the spatial distribution of particle sizes in the dam body.The study reveals the characteristics of translational and rotational energy of different particles and the laws of mechanical energy conversion,obtaining the spatial distribution patterns of particle sizes in landslide-induced dams.The results show that under the sequential gradient arrangement,the energy dissipation of the landslide movement is lower,with larger particles mainly distributed at the distal end and smaller particles at the proximal end of the landslide dam.In contrast,under the reverse gradient arrangement,the energy dissipation of the landslide movement is higher,and the distribution pattern of the dam particles is opposite to that of the sequential gradient arrangement.For the other arrangement modes,the spatial distribution of dam particles falls between the aforementioned two.There is a positive correlation between particle size and translational kinetic energy within the particle flow during the landslide process,and rotational motion increases energy dissipation.Under constant slope conditions,sliding length does not affect the movement pattern of the particle flow or the spatial distribution of particles in the dam body.The findings of this study provide a scientific basis for the accurate simulation and prediction of dam-break flood processes.

Particle residence time distribution and axial dispersion coefficient in a pressurized circulating fluidized bed by using multiphase particle-in-cell simulation

The particle residence time distribution(RTD)and axial dispersion coefficient are key parameters for the design and operation of a pressurized circulating fluidized bed(PCFB).In this study,the effects of pressure(0.1-0.6 MPa),fluidizing gas velocity(2-7 m·s^(-1)),and solid circulation rate(10-90 kg·m^(-2)·s^(-1))on particle RTD and axial dispersion coefficient in a PCFB are numerically investigated based on the multiphase particle-in-cell(MP-PIC)method.The details of the gas-solid flow behaviors of PCFB are revealed.Based on the gas-solid flow pattern,the particles tend to move more orderly under elevated pressures.With an increase in either fluidizing gas velocity or solid circulation rate,the mean residence time of particles decreases while the axial dispersion coefficient increases.With an increase in pressure,the core-annulus flow is strengthened,which leads to a wider shape of the particle RTD curve and a larger mean particle residence time.The back-mixing of particles increases with increasing pressure,resulting in an increase in the axial dispersion coefficient.

Simulation of fixed-bed adsorption process considering particle size distribution

The distribution of adsorbent particle sizes typically has a significant impact on adsorption performance.Most fixed-bed adsorption studies adopt the assumption of average particle size to simplify the adsorption model,but this does not eliminate the deviation between experiments and simulations caused by particle size distribution in practice.In this study,the population balance equation(PBE)and fixed-bed adsorption kinetics model were combined to simulate the adsorption process in a fixed-bed reactor,modeling the distribution of adsorbate uptake over time on adsorbent particles of different sizes.We integrated and optimized the PBE and fixed-bed mass transfer model in the algorithm,and the resulting combined model adopts a variable time step size,which can achieve a balance between computational efficiency and error while ensuring computational convergence.By slicing the model in the spatial dimension,multiple sets of PBE can be calculated in parallel,improving computational efficiency.The adsorption process of single-component and multi-component CO_(2)/CH_(4)/N_(2)on 4A zeolite without binder was simulated,and the influence of adsorbent particle size distribution was analyzed.Simulation results show that the assumption of average adsorbent particle size,which was commonly made in published work,will underestimate the time required for adsorbates to break through the fixed bed compared with the assumption of uniform adsorbent particle size.This model helps to consider the impact of adsorbent particle size distribution on the adsorption process,thereby improving the prediction accuracy of adsorbent performance.

Optimal Configuration of Fault Location Measurement Points in DC Distribution Networks Based on Improved Particle Swarm Optimization Algorithm

The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.

Efficient and Stable Perovskite Solar Cells and Modules Enabled by Tailoring Additive Distribution According to the Film Growth Dynamics

Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.

Differential distribution of PINK1 and Parkin in the primate brain implies distinct roles

The vast majority of in vitro studies have demonstrated that PINK1 phosphorylates Parkin to work together in mitophagy to protect against neuronal degeneration.However,it remains largely unclear how PINK1 and Parkin are expressed in mammalian brains.This has been difficult to address because of the intrinsically low levels of PINK1 and undetectable levels of phosphorylated Parkin in small animals.Understanding this issue is critical for elucidating the in vivo roles of PINK1 and Parkin.Recently,we showed that the PINK1 kinase is selectively expressed as a truncated form(PINK1–55)in the primate brain.In the present study,we used multiple antibodies,including our recently developed monoclonal anti-PINK1,to validate the selective expression of PINK1 in the primate brain.We found that PINK1 was stably expressed in the monkey brain at postnatal and adulthood stages,which is consistent with the findings that depleting PINK1 can cause neuronal loss in developing and adult monkey brains.PINK1 was enriched in the membrane-bound fractionations,whereas Parkin was soluble with a distinguishable distribution.Immunofluorescent double staining experiments showed that PINK1 and Parkin did not colocalize under physiological conditions in cultured monkey astrocytes,though they did colocalize on mitochondria when the cells were exposed to mitochondrial stress.These findings suggest that PINK1 and Parkin may have distinct roles beyond their well-known function in mitophagy during mitochondrial damage.

Compartmentalized regulation of organelle integrity in neurodegenerative diseases:lessons from the Drosophila motor neuron

Neurons are highly polarized,morphologically asymmetric,and functionally compartmentalized cells that contain long axons extending from the cell body.For this reason,their maintenance relies on spatiotemporal regulation of organelle distribution between the somatodendritic and axonal domains.Although some organelles,such as mitochondria and smooth endoplasmic reticulum,are widely distributed throughout the neuron,others are segregated to either the somatodendritic or axonal compartment.For example,Golgi outposts and acidified lysosomes are predominantly present in the somatodendritic domain and rarely distributed along the axon,whereas newly formed autophagosomes and synaptic vesicles are mainly distributed in the distal axon(Britt et al.,2016).

Effects of aggregate size distribution and carbon nanotubes on the mechanical properties of cemented gangue backfill samples under true triaxial compression

The mechanical behavior of cemented gangue backfill materials(CGBMs)is closely related to particle size distribution(PSD)of aggregates and properties of cementitious materials.Consequently,the true triaxial compression tests,CT scanning,SEM,and EDS tests were conducted on cemented gangue backfill samples(CGBSs)with various carbon nanotube concentrations(P_(CNT))that satisfied fractal theory for the PSD of aggregates.The mechanical properties,energy dissipations,and failure mechanisms of the CGBSs under true triaxial compression were systematically analyzed.The results indicate that appropriate carbon nanotubes(CNTs)effectively enhance the mechanical properties and energy dissipations of CGBSs through micropore filling and microcrack bridging,and the optimal effect appears at P_(CNT)of 0.08wt%.Taking PSD fractal dimension(D)of 2.500 as an example,compared to that of CGBS without CNT,the peak strength(σ_(p)),axial peak strain(ε_(1,p)),elastic strain energy(Ue),and dissipated energy(U_(d))increased by 12.76%,29.60%,19.05%,and90.39%,respectively.However,excessive CNTs can reduce the mechanical properties of CGBSs due to CNT agglomeration,manifesting a decrease inρ_(p),ε_(1,p),and the volumetric strain increment(Δε_(v))when P_(CNT)increases from 0.08wt%to 0.12wt%.Moreover,the addition of CNTs improved the integrity of CGBS after macroscopic failure,and crack extension in CGBSs appeared in two modes:detour and pass through the aggregates.Theσ_(p)and U_(d)firstly increase and then decrease with increasing D,and porosity shows the opposite trend.Theε_(1,p)andΔε_(v)are negatively correlated with D,and CGBS with D=2.150 has the maximum deformation parameters(ε_(1,p)=0.05079,Δε_(v)=0.01990)due to the frictional slip effect caused by coarse aggregates.With increasing D,the failure modes of CGBSs are sequentially manifested as oblique shear failure,"Y-shaped"shear failure,and conjugate shear failure.

Pretreatment red blood cell distribution width as a predictive marker for postoperative complications after laparoscopic pancreatoduodenectomy

BACKGROUND Red blood cell distribution width(RDW)is associated with the development and progression of various diseases.AIM To explore the association between pretreatment RDW and short-term outcomes after laparoscopic pancreatoduodenectomy(LPD).METHODS A total of 804 consecutive patients who underwent LPD at our hospital between March 2017 and November 2021 were retrospectively analyzed.Correlations between pretreatment RDW and clinicopathological characteristics and short-term outcomes were investigated.RESULTS Patients with higher pretreatment RDW were older,had higher Eastern Cooperative Oncology Group scores and were associated with poorer short-term outcomes than those with normal RDW.High pretreatment RDW was an independent risk factor for postoperative complications(POCs)(hazard ratio=2.973,95%confidence interval:2.032-4.350,P<0.001)and severe POCs of grade IIIa or higher(hazard ratio=3.138,95%confidence interval:2.042-4.824,P<0.001)based on the Clavien-Dino classification system.Subgroup analysis showed that high pretreatment RDW was an independent risk factor for Clavien-Dino classi-fication grade IIIb or higher POCs,a comprehensive complication index score≥26.2,severe postoperative pancreatic fistula,severe bile leakage and severe hemorrhage.High pretreatment RDW was positively associated with the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio and was negatively associated with albumin and the prognostic nutritional index.CONCLUSION Pretreatment RDW was a special parameter for patients who underwent LPD.It was associated with malnutrition,severe inflammatory status and poorer short-term outcomes.RDW could be a surrogate marker for nutritional and inflammatory status in identifying patients who were at high risk of developing POCs after LPD.

Novel Low-Carbon Optimal Operation Method for Flexible Distribution Network Based on Carbon Emission Flow

With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FDN),the calculation of carbon flow distribution in FDN is more difficult.To this end,this study constructs a model for low-carbon optimal operations within the FDN on the basis of enhanced carbon emission flow(CEF).First,the carbon emission characteristics of FDNs are scrutinized and an improved method for calculating carbon flow within these networks is proposed.Subsequently,a model for optimizing low-carbon operations within FDNs is formulated based on the refined CEF,which merges the specificities of DG and intelligent SOP.Finally,this model is scrutinized using an upgraded IEEE 33-node distribution system,a comparative analysis of the cases reveals that when DG and SOP are operated in a coordinated manner in the FDN,with the cost of electricity generation was reduced by 40.63 percent and the cost of carbon emissions by 10.18 percent.The findings indicate that the judicious optimization of areas exhibiting higher carbon flow rates can effectively enhance the economic efficiency of DN operations and curtail the carbon emissions of the overall network.

Numerical Simulation of Flow and Temperature Distribution in a Bottom-Blown Copper Bath

Smelting with oxygen bottom blowing is one of the main methods used in the frame of copper pyrometallurgy.With this approach,feed materials and oxygen-enriched air are introduced in reversed order to enhance multiphaseflow within the furnace.Understanding the flow structure and temperature distribution in this setup is crucial foroptimizing production.In this study,gas-liquid interactions,and temperature profiles under varying air-injectionconditions are examined by means of numerical simulation for a 3.2 m×20 m furnace.The results indicate that thehigh-velocity regions are essentially distributed near the lance within the reaction region and the flue gas outlet,while low-velocity regions are located close to the furnace walls on both side of the reaction region.Dead regionsappear in the sedimentation region,with gas velocities surpassing those of the molten phase.As the injection rateincreases from 0.50 to 0.80 Nm3/s,the stabilization time of the average liquid surface velocity decreases from 2.6 sto 1.9 s,exhibiting a similar trend to the gas holdup.During stabilization,the average liquid surface velocity risesfrom 0.505 to 0.702 m/s.The average turbulent kinetic energy(TKE)of the fluid in the molten bath increases from0.095 to 0.162 m^(2)/s^(2).The proportion of the area distribution with TKE greater than 0.10 m^(2)/s^(2) and the gas holdupat steady state both rise with an increase in the injection quantity.The maximum splashing height of the melt growsfrom approximately 0.756 to 1.154 m,with the affected area expanding from 14.239 to 20.498 m^(2).Under differentworking conditions with varying injection quantities,the average temperature changes in melt zone and flue gaszone of the furnace are small.The temperature in the melt and in the flue-gas zone spans the interval 1200℃–1257℃,and 1073℃–1121℃,respectively.The temperature distribution of the melt and flue gas reveals a patterncharacterized by elevated temperatures in the reaction zone,gradually transitioning to lower temperatures in thesedimentation region.

Data driven prediction of fragment velocity distribution under explosive loading conditions

This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.

A Case Study on Garbage Code Redistribution Methods for Heart Failure at City Level by Two Approaches

Cause of death surveillance data is most important for developing effective health policies,whose quality is crucially affected by the accuracy of the underlying cause of death(UCOD)provided in death certificates.The World Health Organization(WHO)has clearly defined a UCOD as“the disease or injury which initiated the train of morbid events leading directly to death,or the circumstance of the accident or violence which produced the fatal injuries”[1].

Some Eigenvalue Properties of Third-order Boundary Value Problems with Distributional Potentials

Several eigenvalue properties of the third-order boundary value problems with distributional potentials are investigated.Firstly,we prove that the operators associated with the problems are self-adjoint and the corresponding eigenvalues are real.Next,the continuity and differential properties of the eigenvalues of the problems are given,especially we find the differential expressions for the boundary conditions,the coefficient functions and the endpoints.Finally,we show a brief application to a kind of transmission boundary value problems of the problems studied here.

The Effects of Misgurnus anguillicaudatus Bioturbation on the Vertical Distribution of Sediment Particles in Paddy Fied

[Objective] The purpose of this study was to investigate the role of breeding Misgurnus anguillicaudatus in paddy field in vertical distribution of sediment particles. [Method] Using chemically stable glass beads as tracers, the effects of Misgurnus anguillicaudatus bioturbation on the vertical distribution of sediment particles in paddy field were investigated, and the bioturbation role of benthic fish in the coupling process of benthic-pelagic interface was discussed. [Result] After ten days of Misgurnus anguillicaudatus bioturbation, 43.2% of the glass beads on the surface were transferred downwardly with the maximum distance of 7.5 cm, and the vertical transportation rate of sediment particles was 7.676×10-4g-1·cm-2·d-1. At a depth of 6 cm, 39.7% and 9.9% of the glass beads were respectively transferred upwards and downwards, to the maximum distanc of 4.5 cm and 5.1 cm, respectively; and the vertical transportation rates of sediment particles were 7.597×10-4g-1·cm-2·d-1 and 1.894×10-4g-1·cm-2·d-1, respectively. [Conclusion] Misgurnus anguillicaudatus bioturbation could promote the circulation and transformation of nutrients at water/soil interface through affecting the vertical distribution of sediment particles.

Analysis on the Distribution Characteristics of Atmospheric Aerosol Particles in Hebei Area in the Cloudy Day Condition

By using the probe data of two sorties airplane in the middle and southern parts of Hebei Province in 2007 spring,the characteristics of atmospheric aerosol particles concentration and size distribution in the area in the cloudy day situation were analyzed.The results showed that the overall trend of aerosol particles concentration in the weather systems which included the south branch trough and North China low vortex was the decrease as the height increased.However,if the cirrostratus was in the high altitude,it increased as the height increased.In the bottom of inversion layer,there existed the obvious accumulation of aerosol and cloud droplet.Affected by the complex weather systems,the aerosol particle size distribution presented the multi-peak type for the disturbance of updraft or turbulence.

Measuring particle size distribution and total number in the activation chamber of desulfurization system by PIV

Application of particle image velocity (PIV) techniques for measuringparticle size distribution and total number in an activation chamber of desulfurization system isintroduced. Watersheld algorithm is used to choose the suitable initial gray level threshold whichis used to change the gray level images taken by PIV to black and white ones, then every particle inan image is isolated totally. For every isolating particle, its contour is tracked by the edgeenhancement filter function and kept by Freeman s chain code. Based on a set of particle s chincode, its size and size distribution are calculated and sorted. Finally, the experimental data ofcalcium particles and water drops, separately injected into the activation chamber, and the erroranalysis of data are given out.

Distribution algorithm of entangled particles for wireless quantum communication mesh networks

With ensured network connectivity in quantum channels, the issue of distributing entangled particles in wireless quantum communication mesh networks can be equivalently regarded as a problem of quantum backbone nodes selection in order to save cost and reduce complexity. A minimum spanning tree（ MST）-based quantum distribution algorithm（ QDMST） is presented to construct the mesh backbone network. First, the articulation points are found,and for each connected block uncovered by the articulation points, the general centers are solved. Then, both articulation points and general centers are classified as backbone nodes and an M ST is formed. The quantum path between every two neighbor nodes on the MST is calculated. The nodes on these paths are also classified as backbone nodes. Simulation results validate the advantages of QDMST in the average backbone nodes number and average quantum channel distance compared to the existing random selection algorithm under multiple network scenarios.