FPGA-based position reconstruction method for neutron beam flux spatial distribution measurement in BNCT

A new measurement method for the spatial distribution of neutron beam flux in boron neutron capture therapy(BNCT)is being developed based on the two-dimensional Micromegas detector.To address the issue of long processing times in traditional offline position reconstruction methods,this paper proposes a field programmable gate array based online position reconstruction method utilizing the micro-time projection chamber principle.This method encapsulates key technical aspects:a self-adaptive serial link technique built upon the dynamical adjustment of the delay chain length,fast sorting,a coordinate-matching technique based on the mapping between signal timestamps and random access memory(RAM)addresses,and a precise start point-merging technique utilizing a circular combined RAM.The performance test of the selfadaptive serial link shows that the bit error rate of the link is better than 10-12 at a confidence level of 99%,ensuring reliable data transmission.The experiment utilizing the readout electronics and Micromegas detector shows a spatial resolution of approximately 1.4 mm,surpassing the current method’s resolution level of 5 mm.The beam experiment confirms that the readout electronics system can obtain the flux spatial distribution of neutron beams online,thus validating the feasibility of the position reconstruction method.The online position reconstruction method avoids traditional methods,such as bubble sorting and traversal searching,simplifies the design of the logic firmware,and reduces the time complexity from O(n2)to O(n).This study contributes to the advancement in measuring neutron beam flux for BNCT.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Synergetic optimization operation method for distribution network based on SOP and PV

The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices that can flexibly control active and reactive power flows.With the exception of active power output,photovoltaic(PV)devices can provide reactive power compensation through an inverter.Thus,a synergetic optimization operation method for SOP and PV in a distribution network is proposed.A synergetic optimization model was developed.The voltage deviation,network loss,and ratio of photovoltaic abandonment were selected as the objective functions.The PV model was improved by considering the three reactive power output modes of the PV inverter.Both the load fluctuation and loss of the SOP were considered.Three multi-objective optimization algorithms were used,and a compromise optimal solution was calculated.Case studies were conducted using an IEEE 33-node system.The simulation results indicated that the SOP and PVs complemented each other in terms of active power transmission and reactive power compensation.Synergetic optimization improves power control capability and flexibility,providing better power quality and PV consumption rate.

Integrative biogeography: Validating hypotheses of species distribution

DEAR EDITOR,Biogeography is a scientific field dedicated to the investigation of the origins and distribution patterns of organisms,as well as predicting future alterations in their geographical distributions(Cox&Moore,2005).However,the majority of conclusions drawn within the field of biogeography are hypothetical.Rigorous testing of these biogeographic hypotheses remains a considerable challenge.This paper presents the concept of“integrative biogeography”,which emphasizes the experimental testing of biogeographic hypotheses through studies on geological history,as well as biotic and abiotic factors(Figure 1).

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.

Influence of Topography on the Distribution and Structure of Woody Plants in the Senegalese Sahel (Sandy Ferlo)

This study describes the floristic composition and structure of a woody stand in the Senegalese Sahel, paying particular attention to the edaphic factors of its floristic composition. A stratified inventory considering the different relief units was adopted. Woody vegetation was surveyed using a dendrometric approach. The results obtained show that the flora is dominated by a few species adapted to drought, such as Balanites aegyptiaca (L.) Del., Calotropis procera Ait. and Boscia senegalensis (Pers.). The distribution of this flora and the structure of the ligneous plants are linked to the topography. In the lowlands, the flora is more diversified and the ligneous plants reach their optimum level of development compared with the higher relief areas. In the lowlands, there are a few woody species which, in the past, were indicative of better climatic conditions. These are Anogeissus leiocarpus (DC.), Commiphora africana (A. Rich.), Feretia apodanthera Del., Loeseneriella africana (A. Smith), Mitragyna inermis (Willd.) and Sclerocarya birrea (A. Rich). It is important that their reintroduction into reforestation projects takes account of their edaphic preference.

Neural stem cell-derived exosomes promote mitochondrial biogenesis and restore abnormal protein distribution in a mouse model of Alzheimer's disease

Mitochondrial dysfunction is a hallmark of Alzheimer’s disease.We previously showed that neural stem cell-derived extracellular vesicles improved mitochondrial function in the cortex of AP P/PS1 mice.Because Alzheimer’s disease affects the entire brain,further research is needed to elucidate alterations in mitochondrial metabolism in the brain as a whole.Here,we investigated the expression of several important mitochondrial biogenesis-related cytokines in multiple brain regions after treatment with neural stem cell-derived exosomes and used a combination of whole brain clearing,immunostaining,and lightsheet imaging to clarify their spatial distribution.Additionally,to clarify whether the sirtuin 1(SIRT1)-related pathway plays a regulatory role in neural stem cell-de rived exosomes interfering with mitochondrial functional changes,we generated a novel nervous system-SIRT1 conditional knoc kout AP P/PS1mouse model.Our findings demonstrate that neural stem cell-de rived exosomes significantly increase SIRT1 levels,enhance the production of mitochondrial biogenesis-related fa ctors,and inhibit astrocyte activation,but do not suppress amyloid-βproduction.Thus,neural stem cell-derived exosomes may be a useful therapeutic strategy for Alzheimer’s disease that activates the SIRT1-PGC1αsignaling pathway and increases NRF1 and COXIV synthesis to improve mitochondrial biogenesis.In addition,we showed that the spatial distribution of mitochondrial biogenesis-related factors is disrupted in Alzheimer’s disease,and that neural stem cell-derived exosome treatment can reverse this effect,indicating that neural stem cell-derived exosomes promote mitochondrial biogenesis.

Boosting Adversarial Training with Learnable Distribution

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural networks.Adversarial training is one of the most potent methods to defend against adversarial attacks.However,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial training.This paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture model.The distribution centroid is built to classify samples and constrain the distribution of the sample features.The natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the model.The proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial training.This algorithm gradually increases the accuracy and robustness of the model by scaling perturbation.Finally,the proposed method outputs the predicted labels and the distance between the sample and the distribution centroid.The distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model defense.The effectiveness of the proposed method is demonstrated through comprehensive experiments.

Approximating the Radial Distribution Function of the Electron in a Hydrogen Atom by a Normal Distribution Suggests That Magnetic Confinement Fusion Would Be Less Energy Efficient than Inertial Confinement Fusion

Since the position of the electron in a hydrogen atom cannot be determined, the region in which it resides is said to be determined stochastically and forms an electron cloud. The probability density function of the single electron in 1s orbit is expressed as φ2, a function of distance from the nucleus. However, the probability of existence of the electron is expressed as a radial distribution function at an arbitrary distance from the nucleus, so it is estimated as the probability of the entire spherical shape of that radius. In this study, it has been found that the electron existence probability approximates the radial distribution function by assuming that the probability of existence of the electron being in the vicinity of the nucleus follows a normal distribution for arbitrary x-, y-, and z-axis directions. This implies that the probability of existence of the electron, which has been known only from the distance information, would follow a normal distribution independently in the three directions. When the electrons’ motion is extremely restricted in a certain direction by the magnetic field of both tokamak and helical fusion reactors, the probability of existence of the electron increases with proximity to the nucleus, and as a result, it is less likely to be liberated from the nucleus. Therefore, more and more energy is required to free the nucleus from the electron in order to generate plasma.

An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Security analysis of satellite-to-ground reference-frame-independent quantum key distribution with beam wandering

The reference-frame-independent(RFI)quantum key distribution(QKD)is suitable for satellite-based links by removing the active alignment on the reference frames.However,how the beam wandering influences the performance of RFI-QKD remains a pending issue in satellite-to-ground links.In this paper,based on the mathematical model for characterizing beam wandering,we present the security analysis for satellite-to-ground RFI-QKD and analytically derive formulas for calculating the secret key rate with beam wandering.Our simulation results show that the performance of RFI-QKD is better than the Bennett–Brassard 1984(BB84)QKD with beam wandering in asymptotic case.Furthermore,the degree of influences of beam wandering is specifically presented for satellite-to-ground RFI-QKD when statistical fluctuations are taken into account.Our work can provide theoretical support for the realization of RFI-QKD using satellite-to-ground links and have implications for the construction of large-scale satellite-based quantum networks.

Species composition and distribution of common Crassostrea and Saccostrea oysters along the coast of Hainan Island

Oyster cultivation is a pivotal economic industry in Hainan Island,South China,where a high oyster species diversity is shown.However,the specific distribution and biodiversity of oyster resources in the island have remained unclear.To elucidate the diversity of oyster species and their distribution there,307 oyster samples were collected from 29 sites in the intertidal zone around the island,and were identified using both morphological and molecular approaches.A minimum of 12 oyster species were identified in taxonomy,including Crassostrea species(C.gigas angulata,C.sikamea,C.iredalei,C.dianbaiensis,C.talonata,C.ariakensis,and C.hongkongensis),and Saccostrea species(S.malabonensis,S.mordax,S.echinata,S.circumsuta,and S.mordoides).The results revealed a remarkable diversity of oyster species along the coast of the island.Particularly noteworthy are that S.malabonensis and S.mordax constituted 36%and 22%of the collected specimens,respectively.This study provided a comprehensive overview on current state of oyster biodiversity in Hainan,serving as a valuable reference for conservation and research on species distribution and resource dynamics in oyster populations.

Heterogeneous population distribution enhances resistance to wheat lodging by optimizing the light environment

Lodging is still the key factor that limits continuous increases in wheat yields today,because the mechanical strength of culms is reduced due to low-light stress in populations under high-yield cultivation.The mechanical properties of the culm are mainly determined by lignin,which is affected by the light environment.However,little is known about whether the light environment can be sufficiently improved by changing the population distribution to inhibit culm lodging.Therefore,in this study,we used the wheat cultivar“Xinong 979”to establish a low-density homogeneous distribution treatment(LD),high-density homogeneous distribution treatment(HD),and high-density heterogeneous distribution treatment(HD-h)to study the regulatory effects and mechanism responsible for differences in the lodging resistance of wheat culms under different population distributions.Compared with LD,HD significantly reduced the light transmittance in the middle and basal layers of the canopy,the net photosynthetic rate in the middle and lower leaves of plants,the accumulation of lignin in the culm,and the breaking resistance of the culm,and thus the lodging index values increased significantly,with lodging rates of 67.5%in 2020–2021 and 59.3%in 2021–2022.Under HD-h,the light transmittance and other indicators in the middle and basal canopy layers were significantly higher than those under HD,and the lodging index decreased to the point that no lodging occurred.Compared with LD,the activities of phenylalanine ammonia-Lyase(PAL),4-coumarate:coenzyme A ligase(4CL),catechol-O-methyltransferase(COMT),and cinnamyl-alcohol dehydrogenase(CAD)in the lignin synthesis pathway were significantly reduced in the culms under HD during the critical period for culm formation,and the relative expression levels of TaPAL,Ta4CL,TaCOMT,and TaCAD were significantly downregulated.However,the activities of lignin synthesis-related enzymes and their gene expression levels were significantly increased under HD-h compared with HD.A partial least squares path modeling analysis found significant positive effects between the canopy light environment,the photosynthetic capacity of the middle and lower leaves of plants,lignin synthesis and accumulation,and lodging resistance in the culms.Thus,under conventional high-density planting,the risk of wheat lodging was significantly higher.Accordingly,the canopy light environment can be optimized by changing the heterogeneity of the population distribution to improve the photosynthetic capacity of the middle and lower leaves of plants,promote lignin accumulation in the culm,and enhance lodging resistance in wheat.These findings provide a basis for understanding the mechanism responsible for the lower mechanical strength of the culm under high-yield wheat cultivation,and a theoretical basis and for developing technical measures to enhance lodging resistance.

Effects of heating temperature and atmosphere on element distribution and microstructure in high-Mn/Al austenitic low-density steel

The elemental distribution and microstructure near the surface of high-Mn/Al austenitic low-density steel were investigated after isothermal holding at temperatures of 900-1200℃ in different atmospheres,including air,N_(2),and N_(2)+CO_(2).No ferrite was formed near the surface of the experimental steel during isothermal holding at 900 and 1000℃ in air,while ferrite was formed near the steel sur-face at holding temperatures of 1100 and 1200℃.The ferrite fraction was larger at 1200℃ because more C and Mn diffused to the sur-face,exuded from the steel,and then reacted with N and O to form oxidation products.The thickness of the compound scale increased owing to the higher diffusion rate at higher temperatures.In addition,after isothermal holding at 1100℃ in N_(2),the Al content near the surface slightly decreased,while the C and Mn contents did not change.Therefore,no ferrite was formed near the surface.However,the near-surface C and Al contents decreased after holding at 1100℃in the N_(2)+CO_(2)mixed atmosphere,resulting in the formation of a small amount of ferrite.The compound scale was thickest in N_(2),followed by the N_(2)+CO_(2)mixed atmosphere,and thinnest in air.Overall,the element loss and ferrite fraction were largest after holding in air at the same temperature.The differences in element loss and ferrite frac-tion between in N_(2) and N_(2)+CO_(2)atmospheres were small,but the compound scale formed in N_(2) was significantly thicker.According to these results,N_(2)+CO_(2)is the ideal heating atmosphere for the industrial production of high-Mn/Al austenitic low-density steel.

A Distributed Photovoltaics Ordering Grid-Connected Method for Analyzing Voltage Impact in Radial Distribution Networks

In recent years,distributed photovoltaics(DPV)has ushered in a good development situation due to the advantages of pollution-free power generation,full utilization of the ground or roof of the installation site,and balancing a large number of loads nearby.However,under the background of a large-scale DPV grid-connected to the county distribution network,an effective analysis method is needed to analyze its impact on the voltage of the distribution network in the early development stage of DPV.Therefore,a DPV orderly grid-connected method based on photovoltaics grid-connected order degree(PGOD)is proposed.This method aims to orderly analyze the change of voltage in the distribution network when large-scale DPV will be connected.Firstly,based on the voltagemagnitude sensitivity(VMS)index of the photovoltaics permitted grid-connected node and the acceptance of grid-connected node(AoGCN)index of other nodes in the network,thePGODindex is constructed to determine the photovoltaics permitted grid-connected node of the current photovoltaics grid-connected state network.Secondly,a photovoltaics orderly grid-connected model with a continuous updating state is constructed to obtain an orderly DPV grid-connected order.The simulation results illustrate that the photovoltaics grid-connected order determined by this method based on PGOD can effectively analyze the voltage impact of large-scale photovoltaics grid-connected,and explore the internal factors and characteristics of the impact.

Salinity fronts shape spatial patterns in zooplankton distribution in Hangzhou Bay

Ocean fronts play important roles in nutrient transport and in the shaping ecological patterns.Frontal zones in small bays are typically small in scale,have a complex structure,and they are spatially and temporally variable,but there are limited data on how biological communities respond to this variation.Hangzhou Bay,a mediumsized estuary in China,is an ideal place in which to study the response of plankton to small-scale ocean fronts,because three water masses(Qiantang River Diluted Water,Changjiang River Diluted Water,and the East China Sea current) converge here and form dynamic salinity fronts throughout the year.We investigate zooplankton communities,and temperature,salinity and chlorophyll a(Chl a) in Hangzhou Bay in June(wet perio d) and December(dry period) of 2022 and examine the dominant environmental factors that affect zooplankton community spatial variability.We then match the spatial distributions of zooplankton communities with those of salinity fronts.S alinity is the most important explanatory variable to affect zooplankton community spatial variability during both wet and dry periods,in that it contributes>60% of the variability in community structure.Furthermore,the spatial distributions of zooplankton match well with salinity fronts.During December,with weaker Qiantang River Diluted Water and a stronger secondary Changjiang River Plume,zooplankton communities occur in moderate salinity(MS,salinity range 15.6±2.2) and high salinity(HS,22.4±1.7) regions,and their ecological boundaries closely match the Qiantang River Diluted Water front.In June,different zooplankton communities occur in low salinity(LS,3.9±1.0),MS(11.7±3.6) and HS(21.3±1.9) regions.Although the LS region occurs abnormally in the central bay rather than its apex because of the anomalous influence of rising and falling tides during the sampling perio d,the ecological boundaries still match salinity interfaces.Low-salinity or brackish-water zooplankter taxa are relatively more abundant in LS or MS regions,and the biomass and abundance of zooplankton is higher in the MS region.

Effect of distribution of fines on evolution of cooperation in spatial public goods game

In the realm of public goods game,punishment,as a potent tool,stands out for fostering cooperation.While it effectively addresses the first-order free-rider problem,the associated costs can be substantial.Punishers incur expenses in imposing sanctions,while defectors face fines.Unfortunately,these monetary elements seemingly vanish into thin air,representing a loss to the system itself.However,by virtue of the redistribution of fines to cooperators and punishers,not only can we mitigate this loss,but the rewards for these cooperative individuals can be enhanced.Based upon this premise,this paper introduces a fine distribution mechanism to the traditional pool punishment model.Under identical parameter settings,by conducting a comparative experiment with the conventional punishment model,the paper aims to investigate the impact of fine distribution on the evolution of cooperation in spatial public goods game.The experimental results clearly demonstrate that,in instances where the punishment cost is prohibitively high,the cooperative strategies of the traditional pool punishment model may completely collapse.However,the model enriched with fine distribution manages to sustain a considerable number of cooperative strategies,thus highlighting its effectiveness in promoting and preserving cooperation,even in the face of substantial punishment cost.

Prevalence and ecological factors affecting the distribution of plant-parasitic nematodes in Prunus groves in Spain

A wide survey was conducted to study plant-parasitic nematodes(PPNs)associated with Prunus groves in Spain.This research aimed to determine the prevalence and distribution of PPNs in Prunus groves,as well as the influence of explanatory variables describing soil,climate and agricultural management in structuring the variation of PPNs community composition.A total of 218 sampling sites were surveyed and 84 PPN species belonging to 32 genera were identified based of an integrative taxonomic approach.PPN species considered as potential limiting factors in Prunus production,such as Meloidogyne arenaria,M.incognita,M.javanica,Pratylenchus penetrans and P.vulnus,were identified in this survey.Seven soil physico-chemical(C,Mg,N,Na,OM,P,pH and clay,loamy sand and sandy loam texture classes),four climate(Bio04,Bio05,Bio13 and Bio14)and four agricultural management variables(grove-use history less than 10 years,irrigation,apricot seedling rootstock,and Montclar rootstock)were identified as the most influential variables driving spatial patterns of PPNs communities.In particular,younger plantations showed higher values for species richness and diversity indices than groves cultivated for more than 20 years with Prunus spp.Our study increases the knowledge of the distribution and prevalence of PPNs associated with Prunus rhizosphere,as well as on the influence of explanatory variables driving the spatial structure PPNs communities,which has important implications for the successful design of sustainable management strategies in the future in this agricultural system.

Tuning mechanical behaviors of highly entangled hydrogels with the random distribution of mobile entanglements

Highly entangled hydrogels exhibit excellent mechanical properties,including high toughness,high stretchability,and low hysteresis.By considering the evolution of randomly distributed entanglements within the polymer network upon mechanical stretches,we develop a constitutive theory to describe the large stretch behaviors of these hydrogels.In the theory,we utilize a representative volume element(RVE)in the shape of a cube,within which there exists an averaged chain segment along each edge and a mobile entanglement at each corner.By employing an explicit method,we decouple the elasticity of the hydrogels from the sliding motion of their entanglements,and derive the stress-stretch relations for these hydrogels.The present theoretical analysis is in agreement with experiment,and highlights the significant influence of the entanglement distribution within the hydrogels on their elasticity.We also implement the present developed constitutive theory into a commercial finite element software,and the subsequent simulations demonstrate that the exact distribution of entanglements strongly affects the mechanical behaviors of the structures of these hydrogels.Overall,the present theory provides valuable insights into the deformation mechanism of highly entangled hydrogels,and can aid in the design of these hydrogels with enhanced performance.

The Uptake and Distribution Evidence of Nano-and Microplastics in vivo after a Single High Dose of Oral Exposure

Objective Tissue uptake and distribution of nano-/microplastics was studied at a single high dose by gavage in vivo.Methods Fluorescent microspheres(100 nm,3μm,and 10μm)were given once at a dose of 200 mg/(kg∙body weight).The fluorescence intensity(FI)in observed organs was measured using the IVIS Spectrum at 0.5,1,2,and 4 h after administration.Histopathology was performed to corroborate these findings.Results In the 100 nm group,the FI of the stomach and small intestine were highest at 0.5 h,and the FI of the large intestine,excrement,lung,kidney,liver,and skeletal muscles were highest at 4 h compared with the control group(P<0.05).In the 3μm group,the FI only increased in the lung at 2 h(P<0.05).In the 10μm group,the FI increased in the large intestine and excrement at 2 h,and in the kidney at 4 h(P<0.05).The presence of nano-/microplastics in tissues was further verified by histopathology.The peak time of nanoplastic absorption in blood was confirmed.Conclusion Nanoplastics translocated rapidly to observed organs/tissues through blood circulation;however,only small amounts of MPs could penetrate the organs.