Tomato detection method using domain adaptive learning for dense planting environments

This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.

Advances in Research of Collection and Detection Methods of Microplastics in Environment

As a new type of environmental pollutants,microplastics have gradually attracted people's attention.A large number of plastics discharged into the environment by human beings are constantly aging and breaking,and finally become microplastics.Microplastics can adsorb pollutants in the environment,and their components have certain toxicity,which can cause different degrees of harm to organisms.Due to the structural characteristics of microplastic particles,such as small particle size,large specific surface area,and their distribution in different environmental media,it is very difficult to accurately detect microplastics.Reliable collection and detection methods are the key to the study of environmental behavior of microplastics.In this study,the collection and detection methods of microplastics in the environment were reviewed,and the development direction of microplastics detection technology in the future was prospected.This study has a certain reference value for the related research and the prevention and treatment of micro-plastic pollution.

Comparison of fish communities using environmental DNA metabarcoding and capture methods in a plateau Erhai Lake,China

Environmental DNA(eDNA)has been used as an important tool for fish diversity analysis,which can greatly solve the problems in traditional survey methodology.However,little work has been done on the actual monitoring accuracy of eDNA.In this study,we analyzed the current status of fish resources in Erhai Lake in Yunnan,SW China,by dividing the lake into three sectors according to habitat differences,and compared the results of eDNA and traditional capture methods to investigate the shortcomings of the current analysis of eDNA results.A total of 27 fish species were detected by eDNA and traditional capture methods,including 20 and 19 fish species,respectively,and additional differences in fish composition between the two methods.The alpha diversity showed higher fish abundance and lower fish diversity by eDNA method compared to the traditional capture method,demonstrating that eDNA was not superior for use in fish diversity analysis.Fish community similarity analysis showed that community differences were generally significant for eDNA(P<0.05).RDA analysis indicated that environmental factors did not significantly affect fish communities monitored by the eDNA method.However,water temperature,aquatic plants,and water depth had significant(P<0.05)effects on fish communities in the traditional capture method,suggesting that eDNA results are insensitive to the effects of environmental factors.Our results illustrate the effectiveness of eDNA in fish identification and the issues in quantification compared to traditional capture methods.Therefore,combining eDNA with traditional methods is a more effective method for analyzing eDNA metabarcoding,following which the protocols of both quantitative methods can be designed to explore the regularity of eDNA quantification.

Online learning method for predicting air environmental information used in agricultural robots

Air environmental information plays an important role during plant growth and reproduction, prompt and accurate prediction of atmospheric environmental data is helpful for agricultural robots to make a timely decision. For efficiency, an online learning method for predicting air environmental information was presented in this work. This method combines the advantages of convolutional neural network (CNN) and experience replay technique: CNN is used to extract features from raw data and predict atmospheric environmental information, experience replay technique can store environmental data over some time and update the hyperparameters of CNN. To validate the effects of this method, this online method was compared with three different predictive methods (including random forest, multi-layer perceptron, and support vector regression) using a public dataset (Jena). According to results, a suitable sample sequence size (e.g., 16) has a smaller number of training sessions and stable results, a larger replay memory size (e.g., 200) can provide enough samples to capture useful features, and 6 d of historical information is the best setting for training predictor. Compared with traditional methods, the method proposed in this study is the only method applied for various conditions.

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.

Multiscale Finite Element Method for Coupling Analysis of Heterogeneous Magneto-Electro-Elastic Structures in Thermal Environment

Magneto-electro-elastic (MEE) materials, a new type of composite intelligent materials, exhibit excellent multifield coupling effects. Due to the heterogeneity of the materials, it is challenging to use the traditional finite element method (FEM) for mechanical analysis. Additionally, the MEE materials are often in a complex service environment, especially under the influence of the thermal field with thermoelectric and thermomagnetic effects, which affect its mechanical properties. Therefore, this paper proposes the efficient multiscale computational method for the multifield coupling problem of heterogeneous MEE structures under the thermal environment. The method constructs a multi-physics field with numerical base functions (the displacement, electric potential, and magnetic potential multiscale base functions). It equates a single cell of heterogeneous MEE materials to a macroscopic unit and supplements the macroscopic model with a microscopic model. This allows the problem to be solved directly on a macroscopic scale. Finally, the numerical simulation results demonstrate that compared with the traditional FEM, the multiscale finite element method (MsFEM) can achieve the purpose of ensuring accuracy and reducing the degree of freedom, and significantly improving the calculation efficiency.

Effects of thinning on the understory light environment of different stands and the photosynthetic performance and growth of the reforestation species Phoebe bournei

Light levels determine regeneration in stands and a key concern is how to regulate the light environment of different stand types to the requirements of the understory.In this study,we selected three stands typical in south China(a Cryptomeria japonica plantation,a Quercus acutissima plantation,and a mixed stand of both)and three thinning intensities to determine the best understory light environ-ment for 3-year-old Phoebe bournei seedlings.The canopy structure,understory light environment,and photosynthe-sis and growth indicators were assessed following thin-ning.Thinning improved canopy structure and understory light availability of each stand;species composition was the reason for differences in the understory light environ-ment.Under the same thinning intensity,the mixed stand had the greatest light radiation and most balanced spectral composition.P.bournei photosynthesis and growth were closely related to the light environment;all three stands required heavy thinning to create an effective and sustained understory light environment.In a suitable understory light environment,the efficiency of light interception,absorption,and use by seedlings was enhanced,resulting in a higher carbon assimilation the main limiting factor was stomatal conductance.As a shade-avoidance signal,red/far-red radia-tion is a critical factor driving changes in photosynthesis and growth of P.bournei seedlings,and a reduction increased light absorption and use capacity and height:diameter ratios.The growth advantage transformed from diameter to height,enabling seedlings to access more light.Our findings suggest that the regeneration of shade-tolerant species such as P.bournei could be enhanced if a targeted approach to thinning based on stand type was adopted.

Corrosion behavior of HVOF Inconel 625 coating in the simulated marine environment

High velocity oxygen fuel(HVOF)spraying process is commonly used to produce superalloy coatings.Inconel 625 coating was prepared on Q235B low carbon steel by HVOF.A series of experiments were conducted to examine the surface and corrosion resistance properties of Inconel 625 HVOF coating.In this paper,potentiodynamic polarization tests and electrochemical impedance spectroscopy(EIS)tests were carried out to evaluate the corrosion resistance of Inconel 625 coating under simulated marine environment.The experiment-al results showed that Inconel 625 coating revealed low porosity and desired coating thickness.Shift in the corrosion potential(E_(corr))to-wards the noble direction combined with much low corrosion current density(i_(corr))indicating a significant improvement of HVOF Inconel 625 coating compared with the substrate.

Design and Sizing of an Ecological Wastewater Treatment System in a School Environment: A Case Study of Ndiebene Gandiol 1 School

The primary objective of this study was to design and size a sustainable sanitation solution for the Ndiebene Gandiol 1 school located in the eponymous commune in northern Senegal. Field investigations led to the collection of wastewater samples. Their analysis revealed specific pollutant loads, including loads of BOD5 3.6966 kgO2/day and COD of 12.8775 kgO2/day, which were central to the design phase. Following a rigorous assessment of the existing sanitation infrastructure, constructed wetland (CWs) emerged as the most appropriate ecological solution. This system, valued for its ability to effectively remove contaminants, was tailored to the specific needs of the site. Consequently, the final design of the filter extends over 217.16 m2, divided into two cells of 108.58 m2 each, with dimensions of 12.77 m in length and 8.5 m in width. The depth of the filtering medium is approximately 0.60 m, meeting the standards while ensuring maximized purification. Typha, an indigenous and prolific plant known for its purification abilities, was selected as the filtering agent. Concurrently, non-crushed gravel was chosen for its proven filtration capacity. This study is the result of a combination of scientific rigor and design expertise. It provides a holistic view of sanitation for Ndiebene Gandiol. The technical specifications and dimensions of the constructed wetland filter embody an approach that marries indepth analysis and practical application, all aimed at delivering an effective and long-lasting solution to the local sanitation challenges. By integrating precise scientific data with sanitation design expertise, this study delivers a holistic solution for Ndiebene Gandiol. The detailed dimensions and specifications of the constructed wetland filter reflect a methodology that combines meticulous analysis with practical adaptation, aiming to provide an effective and sustainable response to the challenges of rural and school sanitation in the northern region of Senegal.

Sedimentary environment and organic matter accumulation of Wufeng-Longmaxi shales,southwest Yangtze Plate,China:Insights from geochemical and petrological evidence

Upper Ordovician-Lower Silurian Wufeng-Longmaxi Formation is the most developed strata of shale gas in southern China.Due to the complex sedimentary environment adjacent to the Kangdian Uplift,the favorable area for organic-rich shale development is still undetermined.The authors,therefore,focus on the mechanism of accumulation of organic matter and the characterization of the sedimentary environment of the Wufeng-Longmaxi Shales to have a more complete understanding and new discovering of organic matter enrichment and favorable area in the marginal region around Sichuan Basin.Multiple methods were applied in this study,including thin section identification,scanning electron microscopy(SEM)observations and X-ray diffraction(XRD),and elemental analysis on outcrop samples.Five lithofacies have been defined according to the mineralogical and petrological analyses,including mudstone,bioclastic limestone,silty shale,dolomitic shale,and carbonaceous siliceous shale.The paleo-environments have been reconstructed and the organic enrichment mechanism has been identified as a reduced environment and high productivity.The Wufeng period is generally a suboxic environment and the early Longmaxi period is a reducing environment based on geochemical characterization.High dolomite content in the study area is accompanied by high TOC,which may potentially indicate the restricted anoxic environment formed by biological flourishing in shallower water.And for the area close to the Kangdian Uplift,the shale gas generation capability is comparatively favorable.The geochemical parameters implied that new favorable areas for shale gas exploration could be targeted,and more shale gas resources in the mountain-basin transitional zone might be identified in the future.

Synthesis and nitrogen content regulation of diamond in a high-pressure hydrogen-rich environment

The regulating nitrogen content of diamond in a hydrogen-rich high-temperature and high-pressure(HPHT) growth environment was systematically investigated in this work by developing three growth systems,namely, "FeNi+Ti", "FeNi+G_(3)N_(6)H_(6)",and "FeNi+Ti+C_(3)N_(6)H_(6)".Optical microscopy,infrared spectroscopy,and photoluminescence(PL)spectroscopy measurements were conducted to analyze the spectroscopic characteristics of diamonds grown in these three systems.From our analysis,it was demonstrated that the presence of hydrogen in the sp^(3) hybrid C-H does not directly affect the color of the diamond and facilitates the increase of the nitrogen-vacancy(NV) center concentration in a highnitrogen-content diamond.In addition,titanium plays an important role in nitrogen removal,while its impact on hydrogen doping within the diamond lattice is insignificant.Most importantly,by regulating the ratio of nitrogen impurities that coexist in the nitrogen and hydrogen HPHT environment,the production of hydrogenous Ⅱa-type diamond,hydrogenous Ib-type diamond,and hydrogenous high-nitrogen-type diamonds was achieved with a nitrogen content of less than 1 ppm to 1600 ppm.

Predict the evolution of mechanical property of Al-Li alloys in a marine environment

The ocean is one of the essential fields of national defense in the future,and more and more attention is paid to the lightweight research of Marine equipment and materials.This study it is to develop a Machine learning(ML)-based prediction method to study the evolution of the mechanical properties of Al-Li alloys in the marine environment.We obtained the mechanical properties of Al-Li alloy samples under uniaxial tensile deformation at different exposure times through Marine exposure experiments.We obtained the strain evolution by digital image correlation(DIC).The strain field images are voxelized using 2D-Convolutional Neural Networks(CNN)autoencoders as input data for Long Short-Term Memory(LSTM)neural networks.Then,the output data of LSTM neural networks combined with corrosion features were input into the Back Propagation(BP)neural network to predict the mechanical properties of Al-Li alloys.The main conclusions are as follows:1.The variation law of mechanical properties of2297-T8 in the Marine atmosphere is revealed.With the increase in outdoor exposure test time,the tensile elastic model of 2297-T8 changes slowly,within 10%,and the tensile yield stress changes significantly,with a maximum attenuation of 23.6%.2.The prediction model can predict the strain evolution and mechanical response simultaneously with an error of less than 5%.3.This study shows that a CNN/LSTM system based on machine learning can be built to capture the corrosion characteristics of Marine exposure experiments.The results show that the relationship between corrosion characteristics and mechanical response can be predicted without considering the microstructure evolution of metal materials.

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.

Contract Mechanism of Water Environment Regulation for Small and Medium Sized Enterprises Based on Optimal Control Theory

The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.

Depositional Environment and Origin of Inertinite-rich Coal in the Ordos Basin

Inertinite-rich coal is widely distributed in the Ordos Basin,represented by the No.2 coal seam of the Middle Jurassic Yan'an Formation.This paper combined coal petrology and geochemistry to analyze the origin of inertinite,changes in the coal-forming environment and control characteristics of wildfire.Research has shown that there are two forms of inertinite sources in the study area.Alongside typical fusinization,wildfire events also play a substantial role in inertinite formation.There are significant fluctuations in the coal-forming environment of samples at different depths.Coal samples were formed in dry forest swamp with low water levels and strong oxidation,which have a high inertinite content,and the samples formed in wet forest swamp and limnic showed low inertinite content.Conversely,the inertinite content of different origins does not fully correspond to the depositional environment characterized by dryness and oxidation.Nonpyrogenic inertinites were significantly influenced by climatic conditions,while pyrofusinite was not entirely controlled by climatic conditions but rather directly impacted by wildfire events.The high oxygen level was the main factor causing widespread wildfire events.Overall,the combination of wildfire activity and oxidation generates a high content of inertinite in the Middle Jurassic coal of the Ordos Basin.

Current status and prospects of research on safety situation awareness of high speed railway operation environment

Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.

Sedimentary Environment and Mineralization of the Black Shale Polymetallic Layer in the Early Cambrian,SW China:Constraints from in situ LA-ICP-MS Analysis of Pyrite

A polymetallic layer is usually developed at the bottom of the early Cambrian black shale in Guizhou Province.The mineral that makes up the polymetallic layer is related to the sedimentary facies.To analyze the differentiation mechanism between polymetallic deposits(Ni-Mo and V),the Zhijin Gezhongwu profile located in the outer shelf and the Sansui Haishan V deposit located in the lower slope are selected to study the in situ sulfur isotopes and trace elements of pyrite.The results show that δ^(34)S values of pyrite vary widely from−7.8‰to 28‰in the Gezhongwu profile,while the δ^(34)S values are relatively uniform(from 27.8‰to 38.4‰)in the Haishan profile.The isotopic S composition is consistent with the transition that occurs in the sedimentary phase from the shelf to the deep sea on the transgressive Yangtze platform;this indicates that the δ^(34)SO_(4)^(2−)values in seawater must be differently distributed in depositional environments.The sulfur in the Ni-Mo layer is produced after the mixing of seawater and hydrothermal fluid,while the V layer mainly originates from seawater.Overall,the Ni-Mo and V deposits have been differentiated primarily on the basis of the combined effect of continental weathering and hydrothermal fluid.

Fast and accurate detection of kiwifruits in the natural environment using improved YOLOv4

Real-time detection of kiwifruits in natural environments is essential for automated kiwifruit harvesting. In this study, a lightweight convolutional neural network called the YOLOv4-GS algorithm was proposed for kiwifruit detection. The backbone network CSPDarknet-53 of YOLOv4 was replaced with GhostNet to improve accuracy and reduce network computation. To improve the detection accuracy of small targets, the upsampling of feature map fusion was performed for network layers 151 and 154, and the spatial pyramid pooling network was removed to reduce redundant computation. A total of 2766 kiwifruit images from different environments were used as the dataset for training and testing. The experiment results showed that the F1-score, average accuracy, and Intersection over Union (IoU) of YOLOv4-GS were 98.00%, 99.22%, and 88.92%, respectively. The average time taken to detect a 416×416 kiwifruit image was 11.95 ms, and the model’s weight was 28.8 MB. The average detection time of GhostNet was 31.44 ms less than that of CSPDarknet-53. In addition, the model weight of GhostNet was 227.2 MB less than that of CSPDarknet-53. YOLOv4-GS improved the detection accuracy by 8.39% over Faster R-CNN and 8.36% over SSD-300. The detection speed of YOLOv4-GS was 11.3 times and 2.6 times higher than Faster R-CNN and SSD-300, respectively. In the indoor picking experiment and the orchard picking experiment, the average speed of the YOLOv4-GS processing video was 28.4 fps. The recognition accuracy was above 90%. The average time spent for recognition and positioning was 6.09 s, accounting for about 29.03% of the total picking time. The overall results showed that the YOLOv4-GS proposed in this study can be applied for kiwifruit detection in natural environments because it improves the detection speed without compromising detection accuracy.

Grain size and surface micro-texture characteristics and their paleoenvironmental significance of Holocene sediment in southern margin of the Gurbantunggut Desert,China

The southern margin of the Gurbantunggut Desert,China,is characterized by alternating layers of aeolian and alluvial deposits.Investigating the characteristics of arenaceous sediment in this area is of significant importance for understanding the interactive processes of wind and water forces,as well as the provenance of sediment.However,there are relatively few investigations on the characteristics of such sediment at present.In this study,we researched three aeolian-alluvial interactive stratigraphic profiles and different types of surface sediment on the desert-oasis transitional zone of southern margin of the Gurbantunggut Desert.Based on the optically stimulated luminescence(OSL)dating of aeolian sand and analyses of quartz sand grain size and surface micro-texture,we explored the aeolian-alluvial environmental change at southern margin of the desert in Holocene,as well as the provenance of sediment.The results indicated that the grain size characteristics of different types of sediment in the stratigraphic profiles were similar to those of modern dune sand,interdune sand,muddy desert surface soil,and riverbed sand.Their frequency curves were unimodal or bimodal,and cumulative probability curves were two-segment or three-segment,mainly composed of suspension load and saltation load.The quartz sand in the sediment at southern margin of the desert had undergone alternating transformation of various exogenic forces,with short transportation distance and time,and sedimentary environment was relatively humid.In Holocene,southern margin of the desert primarily featured braided river deposits,and during intermittent period of river activity,there were also aeolian deposits such as sand sheet deposits,stabilized dune deposits,and mobile dune deposits.The provenance for Holocene alluvial deposits at southern margin of the desert remains relatively constant,with the debris of the Tianshan Mountains being the primary provenance.Aeolian sand is mainly near-source recharge,which is formed by in situ deposition of fluvial or lacustrine materials in southern margin of the desert transported by wind erosion,and its provenance was still the weathered debris of the Tianshan Mountains.In addition,the sand in interior of the desert may be transported by northwest wind in desert-scale,thus affecting the development of dunes in southern margin of the desert.The results of this study provide a reference for understanding the composition and provenance changes of desert sand in the context of global climate change.

The chemical environment and structural ordering in liquid Mg-Y-Zn system:An ab-initio molecular dynamics investigation of melt for the formation mechanism of LPSO structure

In an effort to clarify the formation mechanism of LPSO structure in Mg-Y-Zn alloy,the chemical environment and structural ordering in liquid Mg-rich Mg-Y-Zn system are investigated with the aid of ab-initio molecular dynamics simulation.In liquid Mg-rich Mg-Y alloys,the strong Mg-Y interaction is determined,which promotes the formation of fivefold symmetric local structure.For Mg-Zn alloys,the weak Mg-Zn interaction results in the fivefold symmetry weakening in the liquid structure.Due to the coexistence of Y and Zn,the strong attractive interaction is introduced in liquid Mg-Y-Zn ternary alloy,and contributes to the clustering of Mg,Y,Zn launched from Zn.What is more,the distribution of local structures becomes closer to that in pure Mg compared with that in binary Mg-Y and Mg-Zn alloys.These results should relate to the origins of the Y/Zn segregation zone and close-packed stacking mode in LPSO structure,which provides a new insight into the formation mechanism of LPSO structure at atomic level.