Robust watermarking requires finding invariant features under multiple attacks to ensure correct extraction.Deep learning has extremely powerful in extracting features,and watermarking algorithms based on deep learnin...Robust watermarking requires finding invariant features under multiple attacks to ensure correct extraction.Deep learning has extremely powerful in extracting features,and watermarking algorithms based on deep learning have attracted widespread attention.Most existing methods use 3×3 small kernel convolution to extract image features and embed the watermarking.However,the effective perception fields for small kernel convolution are extremely confined,so the pixels that each watermarking can affect are restricted,thus limiting the performance of the watermarking.To address these problems,we propose a watermarking network based on large kernel convolution and adaptive weight assignment for loss functions.It uses large-kernel depth-wise convolution to extract features for learning large-scale image information and subsequently projects the watermarking into a highdimensional space by 1×1 convolution to achieve adaptability in the channel dimension.Subsequently,the modification of the embedded watermarking on the cover image is extended to more pixels.Because the magnitude and convergence rates of each loss function are different,an adaptive loss weight assignment strategy is proposed to make theweights participate in the network training together and adjust theweight dynamically.Further,a high-frequency wavelet loss is proposed,by which the watermarking is restricted to only the low-frequency wavelet sub-bands,thereby enhancing the robustness of watermarking against image compression.The experimental results show that the peak signal-to-noise ratio(PSNR)of the encoded image reaches 40.12,the structural similarity(SSIM)reaches 0.9721,and the watermarking has good robustness against various types of noise.展开更多
Fall behavior is closely related to high mortality in the elderly,so fall detection becomes an important and urgent research area.However,the existing fall detection methods are difficult to be applied in daily life d...Fall behavior is closely related to high mortality in the elderly,so fall detection becomes an important and urgent research area.However,the existing fall detection methods are difficult to be applied in daily life due to a large amount of calculation and poor detection accuracy.To solve the above problems,this paper proposes a dense spatial-temporal graph convolutional network based on lightweight OpenPose.Lightweight OpenPose uses MobileNet as a feature extraction network,and the prediction layer uses bottleneck-asymmetric structure,thus reducing the amount of the network.The bottleneck-asymmetrical structure compresses the number of input channels of feature maps by 1×1 convolution and replaces the 7×7 convolution structure with the asymmetric structure of 1×7 convolution,7×1 convolution,and 7×7 convolution in parallel.The spatial-temporal graph convolutional network divides the multi-layer convolution into dense blocks,and the convolutional layers in each dense block are connected,thus improving the feature transitivity,enhancing the network’s ability to extract features,thus improving the detection accuracy.Two representative datasets,Multiple Cameras Fall dataset(MCF),and Nanyang Technological University Red Green Blue+Depth Action Recognition dataset(NTU RGB+D),are selected for our experiments,among which NTU RGB+D has two evaluation benchmarks.The results show that the proposed model is superior to the current fall detection models.The accuracy of this network on the MCF dataset is 96.3%,and the accuracies on the two evaluation benchmarks of the NTU RGB+D dataset are 85.6%and 93.5%,respectively.展开更多
石墨作为锂离子电池的商业阳极材料,由于其高丰度、低成本和低电位的优势,在K离子电池中也显示出了的巨大潜力。然而,K离子半径(0.138 nm)大于Li离子半径(0.076 nm),会造成的明显结构损伤导致明显的容量衰减和不稳定的循环寿命。在这里...石墨作为锂离子电池的商业阳极材料,由于其高丰度、低成本和低电位的优势,在K离子电池中也显示出了的巨大潜力。然而,K离子半径(0.138 nm)大于Li离子半径(0.076 nm),会造成的明显结构损伤导致明显的容量衰减和不稳定的循环寿命。在这里,我们用简单有效的微波方法通过石墨烯涂层设计了石墨阳极的稳定界面。微波还原可以在10 s内有效地去除氧化石墨烯的氧基,这一点得到了X射线光电子能谱(XPS)的证实。石墨烯涂层不仅可以缓冲石墨的体积膨胀以抑制结构崩溃,还可以加速电子传输以提高倍率性能。石墨烯涂层负极(GCG)在3000次循环后表现出262 m Ah·g^(-1)的超级循环稳定性。与石墨相比GCG的倍率性能也更加优异(500 m A·g^(-1)的电流密度下容量为161.2 m Ah·g^(-1))。相反,在相同的电流密度下,石墨的容量在150次循环后衰减到小于150m Ah·g^(-1)。进一步的电化学阻抗(EIS)和恒电流间歇滴定(GITT)测试表明,与石墨相比,GCG表现出更快的电导率和离子扩散。循环后的拉曼光谱、扫描电镜(SEM)和透射电镜(TEM)图像验证了石墨烯作为缓冲界面有利于电极结构的完整性和固体电解质膜(SEI)的稳定性。这项工作为钾离子电池的大规模应用提供了新的希望。展开更多
As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crud...As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.展开更多
The function of exogenous alanine(Ala)in regulating biomass accumulation,lipid production,photosynthesis,and respiration in Chlorella pyrenoidosa was studied.Result shows that the supplementation of Ala increased C.py...The function of exogenous alanine(Ala)in regulating biomass accumulation,lipid production,photosynthesis,and respiration in Chlorella pyrenoidosa was studied.Result shows that the supplementation of Ala increased C.pyrenoidosa biomass and lipid production in an 8-d batch culture.The concentration of 10 mmol/L of Ala was optimum and increased the microalgal cell biomass and lipid content by 39.3%and 21.4%,respectively,compared with that in the control(0-mmol/L Ala).Ala supplementation reduced photosynthetic activity while boosting respiratory activity and pyruvate levels,indicating that C.pyrenoidosa used exogenous Ala for biomass accumulation through the respiratory metabolic process.The accelerated respiratory metabolism due to Ala supplementation elevated the substrate pool and improved the lipogenic gene expression,promoting lipid production at last.This study provided a novel method for increasing biomass accumulation and lipid production and elucidated the role of Ala in regulating lipid production.展开更多
The efficient separation of chalcopyrite(CuFeS2)and galena(PbS)is essential for optimal resource utilization.However,find-ing a selective depressant that is environmentally friendly and cost effective remains a challe...The efficient separation of chalcopyrite(CuFeS2)and galena(PbS)is essential for optimal resource utilization.However,find-ing a selective depressant that is environmentally friendly and cost effective remains a challenge.Through various techniques,such as mi-croflotation tests,Fourier transform infrared spectroscopy,scanning electron microscopy(SEM)observation,X-ray photoelectron spec-troscopy(XPS),and Raman spectroscopy measurements,this study explored the use of ferric ions(Fe^(3+))as a selective depressant for ga-lena.The results of flotation tests revealed the impressive selective inhibition capabilities of Fe^(3+)when used alone.Surface analysis showed that Fe^(3+)significantly reduced the adsorption of isopropyl ethyl thionocarbamate(IPETC)on the galena surface while having a minimal impact on chalcopyrite.Further analysis using SEM,XPS,and Raman spectra revealed that Fe^(3+)can oxidize lead sulfide to form compact lead sulfate nanoparticles on the galena surface,effectively depressing IPETC adsorption and increasing surface hydrophilicity.These findings provide a promising solution for the efficient and environmentally responsible separation of chalcopyrite and galena.展开更多
Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)...Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)has not received enough attention in the existing literature.Based on the provincial panel data from 2013 to 2020 in China,this paper examines the effect of AEC on AWI,comprising three dimensions:digitalization(DIGITAL),agrifood e-commerce infrastructure and supporting services(AECI),and agri-food e-commerce economy(AECE).First,AWI and AEC are measured using an entropy-based combination of indicators.The results indicate that for China as a whole,AWI has remained practically unchanged,whereas AEC exhibits a significant rising trend.Second,the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI,whereas AECI negatively affects AWI.Third,threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity,which manifests as a first increase and then a drop in the inhibition degree.These results suggest that with the introduction of e-commerce for agricultural product circulation,digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress.Furthermore,the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.展开更多
Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns...Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns are recognized as ideal sites for pure hydrogen storage.Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues.In this article,the software CiteSpace is used to analyze and filter hot topics in published research.Based on a detailed classification and analysis,a“four‐factor”model for the site selection of salt cavern hydrogen storage is proposed,encompassing the dynamic demands of hydrogen energy,geological,hydrological,and ground factors of salt mines.Subsequently,20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted,which provided a preliminary site selection system for salt cavern hydrogen storage.Ultimately,the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City,Henan Province,thereby confirming its rationality and effectiveness.This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.展开更多
The key to preventing the COVID-19 is to diagnose patients quickly and accurately.Studies have shown that using Convolutional Neural Networks(CNN)to analyze chest Computed Tomography(CT)images is helpful for timely CO...The key to preventing the COVID-19 is to diagnose patients quickly and accurately.Studies have shown that using Convolutional Neural Networks(CNN)to analyze chest Computed Tomography(CT)images is helpful for timely COVID-19 diagnosis.However,personal privacy issues,public chest CT data sets are relatively few,which has limited CNN’s application to COVID-19 diagnosis.Also,many CNNs have complex structures and massive parameters.Even if equipped with the dedicated Graphics Processing Unit(GPU)for acceleration,it still takes a long time,which is not conductive to widespread application.To solve above problems,this paper proposes a lightweight CNN classification model based on transfer learning.Use the lightweight CNN MobileNetV2 as the backbone of the model to solve the shortage of hardware resources and computing power.In order to alleviate the problem of model overfitting caused by insufficient data set,transfer learning is used to train the model.The study first exploits the weight parameters trained on the ImageNet database to initialize the MobileNetV2 network,and then retrain the model based on the CT image data set provided by Kaggle.Experimental results on a computer equipped only with the Central Processing Unit(CPU)show that it consumes only 1.06 s on average to diagnose a chest CT image.Compared to other lightweight models,the proposed model has a higher classification accuracy and reliability while having a lightweight architecture and few parameters,which can be easily applied to computers without GPU acceleration.Code:github.com/ZhouJie-520/paper-codes.展开更多
DNA barcoding has been widely used for herb identification in recent decades,enabling safety and innovation in the field of herbal medicine.In this article,we summarize recent progress in DNA bar-coding for herbal med...DNA barcoding has been widely used for herb identification in recent decades,enabling safety and innovation in the field of herbal medicine.In this article,we summarize recent progress in DNA bar-coding for herbal medicine to provide ideas for the further development and application of this tech-nology.Most importantly,the standard DNA barcode has been extended in two ways.First,while conventional DNA barcodes have been widely promoted for their versatility in the identification of fresh or well-preserved samples,super-barcodes based on plastid genomes have rapidly developed and have shown advantages in species identification at low taxonomic levels.Second,mini-barcodes are attractive because they perform better in cases of degraded DNA from herbal materials.In addition,some mo-lecular techniques,such as high-throughput sequencing and isothermal amplification,are combined with DNA barcodes for species identification,which has expanded the applications of herb identification based on DNA barcoding and brought about the post-DNA-barcoding era.Furthermore,standard and high-species coverage DNA barcode reference libraries have been constructed to provide reference se-quences for species identification,which increases the accuracy and credibility of species discrimination based on DNA barcodes.In summary,DNA barcoding should play a key role in the quality control of traditional herbal medicine and in the international herb trade.展开更多
Organic depressants have low selectivity in separating molybdenite and talc because their metal sites lack activity for organics chemisorption.In this study,surface modification by copper sulfate was used to induce th...Organic depressants have low selectivity in separating molybdenite and talc because their metal sites lack activity for organics chemisorption.In this study,surface modification by copper sulfate was used to induce the differential adsorption of pectin onto molybdenite and talc surfaces for enhanced flotation separation.Contact-angle experiments,scanning electron microscopy,adsorption measurements,timeof-flight secondary-ion mass spectrometry,and X-ray photoelectron spectroscopy analyses were conducted to reveal the interaction mechanism.Results illustrated that molybdenite and talc could not be separated using pectin alone,while molybdenite was selectively depressed after surface modification by copper sulfate and this effect was strengthened under alkaline conditions.Metal sites(Mg,Si and Mo)of talc and molybdenite themselves were unable to react with pectin,whereas Cu+would deposit and further function as active site for pectin chemisorption after surface modification.However,the quantity of deposited Cu sites dropped on talc surface and increased on molybdenite surface with increased pH,and the Mo atoms of molybdenite crystal were activated to take part in pectin chemisorption.Therefore,more pectin was adhered on molybdenite surface,which imparted molybdenite stronger wettability.Herein,surface-modification through metal ions can enable the differential adsorption of organic depressants and enhance the flotation separation of minerals.展开更多
3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective.When existing methods reconstruct the mesh surface of complex objects,the surface details are difficult ...3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective.When existing methods reconstruct the mesh surface of complex objects,the surface details are difficult to predict and the reconstruction visual effect is poor because the mesh representation is not easily integrated into the deep learning framework;the 3D topology is easily limited by predefined templates and inflexible,and unnecessary mesh self-intersections and connections will be generated when reconstructing complex topology,thus destroying the surface details;the training of the reconstruction network is limited by the large amount of information attached to the mesh vertices,and the training time of the reconstructed network is too long.In this paper,we propose a method for fast mesh reconstruction from single view based on Graph Convolutional Network(GCN)and topology modification.We use GCN to ensure the generation of high-quality mesh surfaces and use topology modification to improve the flexibility of the topology.Meanwhile,a feature fusion method is proposed to make full use of the features of each stage of the image hierarchically.We use 3D open dataset ShapeNet to train our network and add a new weight parameter to speed up the training process.Extensive experiments demonstrate that our method can not only reconstruct object meshes on complex topological surfaces,but also has better qualitative and quantitative results.展开更多
Is Cannabis a boon or bane?Cannabis sativa has long been a versatile crop for fiber extraction(industrial hemp),traditional Chinese medicine(hemp seeds),and recreational drugs(marijuana).Cannabis faced global prohibit...Is Cannabis a boon or bane?Cannabis sativa has long been a versatile crop for fiber extraction(industrial hemp),traditional Chinese medicine(hemp seeds),and recreational drugs(marijuana).Cannabis faced global prohibition in the twentieth century because of the psychoactive properties of △^(9)-tetrahydrocannabinol;however,recently,the perspective has changed with the recognition of additional therapeutic values,particularly the pharmacological potential of cannabidiol.A comprehensive understanding of the underlying mechanism of cannabinoid biosynthesis is necessary to cultivate and promote globally the medicinal application of Cannabis resources.Here,we comprehensively review the historical usage of Cannabis,biosynthesis of trichome-specific cannabinoids,regulatory network of trichome development,and synthetic biology of cannabinoids.This review provides valuable insights into the efficient biosynthesis and green production of cannabinoids,and the development and utilization of novel Cannabis varieties.展开更多
Due to the high charge transfer efficiency compared to that of non-porous materials,porous electrodes with larger surface area and thinner solid pore walls have been widely applied in the lithium-ion battery field.Sin...Due to the high charge transfer efficiency compared to that of non-porous materials,porous electrodes with larger surface area and thinner solid pore walls have been widely applied in the lithium-ion battery field.Since the capacity and charge-discharge efficiency of batteries are closely related to the microstructure of porous materials,a conceptually simple and computationally efficient cellular automata(CA)framework is proposed to reconstruct the porous electrode structure and simulate the reactiondiffusion process under the irregular solid-liquid boundary in this work.This framework is consisted of an electrode generating model and a reaction-diffusion model.Electrode structures with specific geometric properties,i.e.,porosity,surface area,size distribution,and eccentricity distribution can be constructed by the electrode generating model.The reaction-diffusion model is exemplified by solving the Fick's diffusion problem and simulating the cyclic voltammetry(CV)process.The discharging process in the lithium-ion battery are simulated through combining the above two CA models,and the simulation results are consistent with the well-known pseudo-two-dimensional(P2D)model.In addition,a set of electrodes with different microstructures are constructed and their reaction efficiencies are evaluated.The results indicate that there is an optimum combination of porosity and particle size for discharge efficiency.This framework is a promising one for studying the effect of electrode microstructure on battery performance due to its fully synchronous computation way,easy handled boundary conditions,and free of convergence concerns.展开更多
With the increasing oil demand, the construction of oil energy reserves in China needs to be further strengthened. However, given that there has been no research on the main influencing factors of crude oil temperatur...With the increasing oil demand, the construction of oil energy reserves in China needs to be further strengthened. However, given that there has been no research on the main influencing factors of crude oil temperature drop in storage tanks under actual dynamically changing environments, this paper considers the influence of dynamic thermal environment and internal crude oil physical properties on the fluctuating changes in crude oil temperature. A theoretical model of the unsteady-state temperature drop heat transfer process is developed from a three-dimensional perspective. According to the temperature drop variation law of crude oil storage tank under the coupling effect of various heat transfer modes such as external forced convection, thermal radiation, and internal natural convection, the external dynamic thermal environment influence zone, the internal crude oil physical property influence zone, and the intermediate transition zone of the tank are proposed. And the multiple non-linear regression method is used to quantitatively characterize the influence of external ambient temperature, solar radiation, wind speed, internal crude oil density, viscosity, and specific heat capacity on the temperature drop of crude oil in each influencing zone. The results of this paper not only quantitatively explain the main influencing factors of the oil temperature drop in the top, wall, and bottom regions of the tank, but also provide a theoretical reference for oil security reserves under a dynamic thermal environment.展开更多
Chalcopyrite is the main Cu-containing mineral and cannot be separated well from pyrite using traditional xanthate collectors with large amounts of lime depressant, resulting in difficulties of the tailing treatment a...Chalcopyrite is the main Cu-containing mineral and cannot be separated well from pyrite using traditional xanthate collectors with large amounts of lime depressant, resulting in difficulties of the tailing treatment and associated precious metals recovery. Therefore, in this study, the green and odourless ethylenediamine tetramethylenephosphonic acid(EDTMPA) was introduced as a novel chalcopyrite collector. Flotation results from the binary mineral mixture and real ore demonstrated that EDTMPA could realize the selective separation of chalcopyrite from pyrite relative to ethyl xanthate(EX) without any depressants within the wide p H range of 6.0–11.0, and might replace the traditional high-alkaline lime process. Electrochemical and Fourier transform infrared spectra measurements indicated that the difference in adsorption performance of EDTMPA on chalcopyrite and pyrite was larger than that of EX, suggesting a better selectivity for EDTMPA. Density functional theory calculations demonstrated that there were stronger chemical bonds between P—O groups of EDTMPA and the Fe/Cu atoms on chalcopyrite in the form of a stable six-membered ring. Crystal chemistry calculations further revealed that the activity of metal atoms of chalcopyrite was higher than that of pyrite. Therefore, these basic theoretical results and practical application provide a guidance for the industrial application of EDTMPA in chalcopyrite flotation.展开更多
Background Sharply increased beef consumption is propelling the genetic improvement projects of beef cattle in China.Three-dimensional genome structure is confirmed to be an important layer of transcription regulation...Background Sharply increased beef consumption is propelling the genetic improvement projects of beef cattle in China.Three-dimensional genome structure is confirmed to be an important layer of transcription regulation.Although genome-wide interaction data of several livestock species have already been produced,the genome structure states and its regulatory rules in cattle muscle are still limited.Results Here we present the first 3D genome data in Longissimus dorsi muscle of fetal and adult cattle(Bos taurus).We showed that compartments,topologically associating domains(TADs),and loop undergo re-organization and the structure dynamics were consistent with transcriptomic divergence during muscle development.Furthermore,we annotated cis-regulatory elements in cattle genome during myogenesis and demonstrated the enrichments of promoter and enhancer in selection sweeps.We further validated the regulatory function of one HMGA2 intronic enhancer near a strong sweep region on primary bovine myoblast proliferation.Conclusions Our data provide key insights of the regulatory function of high order chromatin structure and cattle myogenic biology,which will benefit the progress of genetic improvement of beef cattle.展开更多
基金supported,in part,by the National Nature Science Foundation of China under grant numbers 62272236in part,by the Natural Science Foundation of Jiangsu Province under grant numbers BK20201136,BK20191401in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)fund.
文摘Robust watermarking requires finding invariant features under multiple attacks to ensure correct extraction.Deep learning has extremely powerful in extracting features,and watermarking algorithms based on deep learning have attracted widespread attention.Most existing methods use 3×3 small kernel convolution to extract image features and embed the watermarking.However,the effective perception fields for small kernel convolution are extremely confined,so the pixels that each watermarking can affect are restricted,thus limiting the performance of the watermarking.To address these problems,we propose a watermarking network based on large kernel convolution and adaptive weight assignment for loss functions.It uses large-kernel depth-wise convolution to extract features for learning large-scale image information and subsequently projects the watermarking into a highdimensional space by 1×1 convolution to achieve adaptability in the channel dimension.Subsequently,the modification of the embedded watermarking on the cover image is extended to more pixels.Because the magnitude and convergence rates of each loss function are different,an adaptive loss weight assignment strategy is proposed to make theweights participate in the network training together and adjust theweight dynamically.Further,a high-frequency wavelet loss is proposed,by which the watermarking is restricted to only the low-frequency wavelet sub-bands,thereby enhancing the robustness of watermarking against image compression.The experimental results show that the peak signal-to-noise ratio(PSNR)of the encoded image reaches 40.12,the structural similarity(SSIM)reaches 0.9721,and the watermarking has good robustness against various types of noise.
基金supported,in part,by the National Nature Science Foundation of China under Grant Numbers 62272236,62376128in part,by the Natural Science Foundation of Jiangsu Province under Grant Numbers BK20201136,BK20191401.
文摘Fall behavior is closely related to high mortality in the elderly,so fall detection becomes an important and urgent research area.However,the existing fall detection methods are difficult to be applied in daily life due to a large amount of calculation and poor detection accuracy.To solve the above problems,this paper proposes a dense spatial-temporal graph convolutional network based on lightweight OpenPose.Lightweight OpenPose uses MobileNet as a feature extraction network,and the prediction layer uses bottleneck-asymmetric structure,thus reducing the amount of the network.The bottleneck-asymmetrical structure compresses the number of input channels of feature maps by 1×1 convolution and replaces the 7×7 convolution structure with the asymmetric structure of 1×7 convolution,7×1 convolution,and 7×7 convolution in parallel.The spatial-temporal graph convolutional network divides the multi-layer convolution into dense blocks,and the convolutional layers in each dense block are connected,thus improving the feature transitivity,enhancing the network’s ability to extract features,thus improving the detection accuracy.Two representative datasets,Multiple Cameras Fall dataset(MCF),and Nanyang Technological University Red Green Blue+Depth Action Recognition dataset(NTU RGB+D),are selected for our experiments,among which NTU RGB+D has two evaluation benchmarks.The results show that the proposed model is superior to the current fall detection models.The accuracy of this network on the MCF dataset is 96.3%,and the accuracies on the two evaluation benchmarks of the NTU RGB+D dataset are 85.6%and 93.5%,respectively.
文摘石墨作为锂离子电池的商业阳极材料,由于其高丰度、低成本和低电位的优势,在K离子电池中也显示出了的巨大潜力。然而,K离子半径(0.138 nm)大于Li离子半径(0.076 nm),会造成的明显结构损伤导致明显的容量衰减和不稳定的循环寿命。在这里,我们用简单有效的微波方法通过石墨烯涂层设计了石墨阳极的稳定界面。微波还原可以在10 s内有效地去除氧化石墨烯的氧基,这一点得到了X射线光电子能谱(XPS)的证实。石墨烯涂层不仅可以缓冲石墨的体积膨胀以抑制结构崩溃,还可以加速电子传输以提高倍率性能。石墨烯涂层负极(GCG)在3000次循环后表现出262 m Ah·g^(-1)的超级循环稳定性。与石墨相比GCG的倍率性能也更加优异(500 m A·g^(-1)的电流密度下容量为161.2 m Ah·g^(-1))。相反,在相同的电流密度下,石墨的容量在150次循环后衰减到小于150m Ah·g^(-1)。进一步的电化学阻抗(EIS)和恒电流间歇滴定(GITT)测试表明,与石墨相比,GCG表现出更快的电导率和离子扩散。循环后的拉曼光谱、扫描电镜(SEM)和透射电镜(TEM)图像验证了石墨烯作为缓冲界面有利于电极结构的完整性和固体电解质膜(SEI)的稳定性。这项工作为钾离子电池的大规模应用提供了新的希望。
基金This work was financially supported by the National Natural Science Foundation of China(52074089 and 52104064)Natural Science Foundation of Heilongjiang Province of China(LH2019E019).
文摘As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.
基金Supported by the National Natural Science Foundation of China(Nos.32002411,42276189)the Innovation and Entrepreneurship Project for College Students of Hohai University(No.2022102941027)the Jiangsu Innovation Center for Marine Bioresources(No.822153216)。
文摘The function of exogenous alanine(Ala)in regulating biomass accumulation,lipid production,photosynthesis,and respiration in Chlorella pyrenoidosa was studied.Result shows that the supplementation of Ala increased C.pyrenoidosa biomass and lipid production in an 8-d batch culture.The concentration of 10 mmol/L of Ala was optimum and increased the microalgal cell biomass and lipid content by 39.3%and 21.4%,respectively,compared with that in the control(0-mmol/L Ala).Ala supplementation reduced photosynthetic activity while boosting respiratory activity and pyruvate levels,indicating that C.pyrenoidosa used exogenous Ala for biomass accumulation through the respiratory metabolic process.The accelerated respiratory metabolism due to Ala supplementation elevated the substrate pool and improved the lipogenic gene expression,promoting lipid production at last.This study provided a novel method for increasing biomass accumulation and lipid production and elucidated the role of Ala in regulating lipid production.
基金the National Natural Science Foundation of China(Nos.52204298 and 52004335)the National Key R&D Program of China(Nos.2022YFC2904502 and 2022YFC2904501)+1 种基金the Major Science and Technology Projects in Yunnan Province(No.202202AB080012)the Science Research Initiation Fund of Central South University(No.202044019).
文摘The efficient separation of chalcopyrite(CuFeS2)and galena(PbS)is essential for optimal resource utilization.However,find-ing a selective depressant that is environmentally friendly and cost effective remains a challenge.Through various techniques,such as mi-croflotation tests,Fourier transform infrared spectroscopy,scanning electron microscopy(SEM)observation,X-ray photoelectron spec-troscopy(XPS),and Raman spectroscopy measurements,this study explored the use of ferric ions(Fe^(3+))as a selective depressant for ga-lena.The results of flotation tests revealed the impressive selective inhibition capabilities of Fe^(3+)when used alone.Surface analysis showed that Fe^(3+)significantly reduced the adsorption of isopropyl ethyl thionocarbamate(IPETC)on the galena surface while having a minimal impact on chalcopyrite.Further analysis using SEM,XPS,and Raman spectra revealed that Fe^(3+)can oxidize lead sulfide to form compact lead sulfate nanoparticles on the galena surface,effectively depressing IPETC adsorption and increasing surface hydrophilicity.These findings provide a promising solution for the efficient and environmentally responsible separation of chalcopyrite and galena.
基金supported by the Leading Talent Support Program for Agricultural Talents of the Chinese Academy of Agricultural Sciences(TCS2022020)the General program of National Natural Science Foundation of China(1573263)。
文摘Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market.However,the interaction between agri-food e-commerce(AEC)and the traditional agri-food wholesale industry(AWI)has not received enough attention in the existing literature.Based on the provincial panel data from 2013 to 2020 in China,this paper examines the effect of AEC on AWI,comprising three dimensions:digitalization(DIGITAL),agrifood e-commerce infrastructure and supporting services(AECI),and agri-food e-commerce economy(AECE).First,AWI and AEC are measured using an entropy-based combination of indicators.The results indicate that for China as a whole,AWI has remained practically unchanged,whereas AEC exhibits a significant rising trend.Second,the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI,whereas AECI negatively affects AWI.Third,threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity,which manifests as a first increase and then a drop in the inhibition degree.These results suggest that with the introduction of e-commerce for agricultural product circulation,digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress.Furthermore,the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.
基金supported by the Henan Institute for Chinese Development Strategy of Engineering&Technology(Grant No.2022HENZDA02)the Since&Technology Department of Sichuan Province Project(Grant No.2021YFH0010)the High‐End Foreign Experts Program of the Yunnan Revitalization Talents Support Plan of Yunnan Province.
文摘Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns are recognized as ideal sites for pure hydrogen storage.Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues.In this article,the software CiteSpace is used to analyze and filter hot topics in published research.Based on a detailed classification and analysis,a“four‐factor”model for the site selection of salt cavern hydrogen storage is proposed,encompassing the dynamic demands of hydrogen energy,geological,hydrological,and ground factors of salt mines.Subsequently,20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted,which provided a preliminary site selection system for salt cavern hydrogen storage.Ultimately,the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City,Henan Province,thereby confirming its rationality and effectiveness.This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.
基金This work was supported,in part,by the Natural Science Foundation of Jiangsu Province under Grant Numbers BK20201136,BK20191401in part,by the National Nature Science Foundation of China under Grant Numbers 61502240,61502096,61304205,61773219in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘The key to preventing the COVID-19 is to diagnose patients quickly and accurately.Studies have shown that using Convolutional Neural Networks(CNN)to analyze chest Computed Tomography(CT)images is helpful for timely COVID-19 diagnosis.However,personal privacy issues,public chest CT data sets are relatively few,which has limited CNN’s application to COVID-19 diagnosis.Also,many CNNs have complex structures and massive parameters.Even if equipped with the dedicated Graphics Processing Unit(GPU)for acceleration,it still takes a long time,which is not conductive to widespread application.To solve above problems,this paper proposes a lightweight CNN classification model based on transfer learning.Use the lightweight CNN MobileNetV2 as the backbone of the model to solve the shortage of hardware resources and computing power.In order to alleviate the problem of model overfitting caused by insufficient data set,transfer learning is used to train the model.The study first exploits the weight parameters trained on the ImageNet database to initialize the MobileNetV2 network,and then retrain the model based on the CT image data set provided by Kaggle.Experimental results on a computer equipped only with the Central Processing Unit(CPU)show that it consumes only 1.06 s on average to diagnose a chest CT image.Compared to other lightweight models,the proposed model has a higher classification accuracy and reliability while having a lightweight architecture and few parameters,which can be easily applied to computers without GPU acceleration.Code:github.com/ZhouJie-520/paper-codes.
基金supported by the National Key R&D Program of China(Nos.2022YFC2904501,2019YFC1907803)the National Natural Science Foundation of China(No.52004335)+1 种基金the Open Sharing Fund for Large-scale Instruments and Equipment of Central South University,China(No.CSUZC202132)the Key Laboratory of Hunan Province for Clean and Efficient Utilization of Strategic Calcium-containing Mineral Resources,China(No.2018TP1002)。
基金supported by the National Key Research and Development Program of China(No.2020YFC1909202)the Postdoctoral Foundation of China(Nos.BX20200389,2020M672513)the National Natural Science Foundation of China(No.52004343)。
基金funded by the National Natural Science Foundation of China(Grant No.:U1812403-1)the China Academy of Chinese Medical Sciences Innovation Fund(Grant No.:CI2021A03910).
文摘DNA barcoding has been widely used for herb identification in recent decades,enabling safety and innovation in the field of herbal medicine.In this article,we summarize recent progress in DNA bar-coding for herbal medicine to provide ideas for the further development and application of this tech-nology.Most importantly,the standard DNA barcode has been extended in two ways.First,while conventional DNA barcodes have been widely promoted for their versatility in the identification of fresh or well-preserved samples,super-barcodes based on plastid genomes have rapidly developed and have shown advantages in species identification at low taxonomic levels.Second,mini-barcodes are attractive because they perform better in cases of degraded DNA from herbal materials.In addition,some mo-lecular techniques,such as high-throughput sequencing and isothermal amplification,are combined with DNA barcodes for species identification,which has expanded the applications of herb identification based on DNA barcoding and brought about the post-DNA-barcoding era.Furthermore,standard and high-species coverage DNA barcode reference libraries have been constructed to provide reference se-quences for species identification,which increases the accuracy and credibility of species discrimination based on DNA barcodes.In summary,DNA barcoding should play a key role in the quality control of traditional herbal medicine and in the international herb trade.
基金The authors would like to acknowledge the support from the National Natural Science Foundation of China(No.52174272)the Joint Funds of the National Natural Science Foundation of China(No.U1704252)+1 种基金the Fundamental Research Funds for the Central Universities of Central South University(Nos.2021zzts0306 and 2021zzts0896)the Hunan Provincial Natural Science Foundation of China(No.2020JJ5736).
文摘Organic depressants have low selectivity in separating molybdenite and talc because their metal sites lack activity for organics chemisorption.In this study,surface modification by copper sulfate was used to induce the differential adsorption of pectin onto molybdenite and talc surfaces for enhanced flotation separation.Contact-angle experiments,scanning electron microscopy,adsorption measurements,timeof-flight secondary-ion mass spectrometry,and X-ray photoelectron spectroscopy analyses were conducted to reveal the interaction mechanism.Results illustrated that molybdenite and talc could not be separated using pectin alone,while molybdenite was selectively depressed after surface modification by copper sulfate and this effect was strengthened under alkaline conditions.Metal sites(Mg,Si and Mo)of talc and molybdenite themselves were unable to react with pectin,whereas Cu+would deposit and further function as active site for pectin chemisorption after surface modification.However,the quantity of deposited Cu sites dropped on talc surface and increased on molybdenite surface with increased pH,and the Mo atoms of molybdenite crystal were activated to take part in pectin chemisorption.Therefore,more pectin was adhered on molybdenite surface,which imparted molybdenite stronger wettability.Herein,surface-modification through metal ions can enable the differential adsorption of organic depressants and enhance the flotation separation of minerals.
基金This work was supported,in part,by the Natural Science Foundation of Jiangsu Province under Grant Numbers BK20201136,BK20191401in part,by the National Nature Science Foundation of China under Grant Numbers 61502240,61502096,61304205,61773219in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective.When existing methods reconstruct the mesh surface of complex objects,the surface details are difficult to predict and the reconstruction visual effect is poor because the mesh representation is not easily integrated into the deep learning framework;the 3D topology is easily limited by predefined templates and inflexible,and unnecessary mesh self-intersections and connections will be generated when reconstructing complex topology,thus destroying the surface details;the training of the reconstruction network is limited by the large amount of information attached to the mesh vertices,and the training time of the reconstructed network is too long.In this paper,we propose a method for fast mesh reconstruction from single view based on Graph Convolutional Network(GCN)and topology modification.We use GCN to ensure the generation of high-quality mesh surfaces and use topology modification to improve the flexibility of the topology.Meanwhile,a feature fusion method is proposed to make full use of the features of each stage of the image hierarchically.We use 3D open dataset ShapeNet to train our network and add a new weight parameter to speed up the training process.Extensive experiments demonstrate that our method can not only reconstruct object meshes on complex topological surfaces,but also has better qualitative and quantitative results.
基金supported by the National Natural Science Foundation of China(82204579)the Fundamental Research Funds for the Central Universities(2572022DX06)+1 种基金the Scientific and Technological Innovation Project of China Academy of Chinese Medical Science(CI2021A04113)Heilongjiang Touyan Innovation Team Program(Tree Genetics and Breeding Innovation Team).
文摘Is Cannabis a boon or bane?Cannabis sativa has long been a versatile crop for fiber extraction(industrial hemp),traditional Chinese medicine(hemp seeds),and recreational drugs(marijuana).Cannabis faced global prohibition in the twentieth century because of the psychoactive properties of △^(9)-tetrahydrocannabinol;however,recently,the perspective has changed with the recognition of additional therapeutic values,particularly the pharmacological potential of cannabidiol.A comprehensive understanding of the underlying mechanism of cannabinoid biosynthesis is necessary to cultivate and promote globally the medicinal application of Cannabis resources.Here,we comprehensively review the historical usage of Cannabis,biosynthesis of trichome-specific cannabinoids,regulatory network of trichome development,and synthetic biology of cannabinoids.This review provides valuable insights into the efficient biosynthesis and green production of cannabinoids,and the development and utilization of novel Cannabis varieties.
基金the National Natural Science Foundation of China(21878012)。
文摘Due to the high charge transfer efficiency compared to that of non-porous materials,porous electrodes with larger surface area and thinner solid pore walls have been widely applied in the lithium-ion battery field.Since the capacity and charge-discharge efficiency of batteries are closely related to the microstructure of porous materials,a conceptually simple and computationally efficient cellular automata(CA)framework is proposed to reconstruct the porous electrode structure and simulate the reactiondiffusion process under the irregular solid-liquid boundary in this work.This framework is consisted of an electrode generating model and a reaction-diffusion model.Electrode structures with specific geometric properties,i.e.,porosity,surface area,size distribution,and eccentricity distribution can be constructed by the electrode generating model.The reaction-diffusion model is exemplified by solving the Fick's diffusion problem and simulating the cyclic voltammetry(CV)process.The discharging process in the lithium-ion battery are simulated through combining the above two CA models,and the simulation results are consistent with the well-known pseudo-two-dimensional(P2D)model.In addition,a set of electrodes with different microstructures are constructed and their reaction efficiencies are evaluated.The results indicate that there is an optimum combination of porosity and particle size for discharge efficiency.This framework is a promising one for studying the effect of electrode microstructure on battery performance due to its fully synchronous computation way,easy handled boundary conditions,and free of convergence concerns.
基金supported by the National Natural Science Foundation of China(52104064)(52074089)the China Postdoctoral Science Foundation(2020M681074)+3 种基金Heilongjiang Provincial Natural Science Foundation of China(YQ2023E006)University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(UNPYSCT-2020152)Postdoctoral Science Foundation of Heilongjiang Province in China(LBH-TZ2106)(LBH-Z20122)Northeast Petroleum University Talents Introduction Fund(2019KQ18).
文摘With the increasing oil demand, the construction of oil energy reserves in China needs to be further strengthened. However, given that there has been no research on the main influencing factors of crude oil temperature drop in storage tanks under actual dynamically changing environments, this paper considers the influence of dynamic thermal environment and internal crude oil physical properties on the fluctuating changes in crude oil temperature. A theoretical model of the unsteady-state temperature drop heat transfer process is developed from a three-dimensional perspective. According to the temperature drop variation law of crude oil storage tank under the coupling effect of various heat transfer modes such as external forced convection, thermal radiation, and internal natural convection, the external dynamic thermal environment influence zone, the internal crude oil physical property influence zone, and the intermediate transition zone of the tank are proposed. And the multiple non-linear regression method is used to quantitatively characterize the influence of external ambient temperature, solar radiation, wind speed, internal crude oil density, viscosity, and specific heat capacity on the temperature drop of crude oil in each influencing zone. The results of this paper not only quantitatively explain the main influencing factors of the oil temperature drop in the top, wall, and bottom regions of the tank, but also provide a theoretical reference for oil security reserves under a dynamic thermal environment.
基金financial supports from the Key Program for International S&T Cooperation Projects of China (No. 2021YFE0106800)the National Natural Science Foundation of China (No. U2067201)+3 种基金the Leading Talents of S & T Innovation of Hunan Province, China (No. 2021RC4002)the Science Fund for Distinguished Young Scholars of Hunan Province, China (No. 2020JJ2044)the Key Research and Development Program of Hunan Province, China (No. 2021SK2043)the National 111 Project, China (No. B14034)。
文摘Chalcopyrite is the main Cu-containing mineral and cannot be separated well from pyrite using traditional xanthate collectors with large amounts of lime depressant, resulting in difficulties of the tailing treatment and associated precious metals recovery. Therefore, in this study, the green and odourless ethylenediamine tetramethylenephosphonic acid(EDTMPA) was introduced as a novel chalcopyrite collector. Flotation results from the binary mineral mixture and real ore demonstrated that EDTMPA could realize the selective separation of chalcopyrite from pyrite relative to ethyl xanthate(EX) without any depressants within the wide p H range of 6.0–11.0, and might replace the traditional high-alkaline lime process. Electrochemical and Fourier transform infrared spectra measurements indicated that the difference in adsorption performance of EDTMPA on chalcopyrite and pyrite was larger than that of EX, suggesting a better selectivity for EDTMPA. Density functional theory calculations demonstrated that there were stronger chemical bonds between P—O groups of EDTMPA and the Fe/Cu atoms on chalcopyrite in the form of a stable six-membered ring. Crystal chemistry calculations further revealed that the activity of metal atoms of chalcopyrite was higher than that of pyrite. Therefore, these basic theoretical results and practical application provide a guidance for the industrial application of EDTMPA in chalcopyrite flotation.
基金supported by the National Natural Science Foundation of China[Grant No.31972558]the Agricultural Improved Seed Project of Shandong Province[Grant No.2020LZGC014-03]。
文摘Background Sharply increased beef consumption is propelling the genetic improvement projects of beef cattle in China.Three-dimensional genome structure is confirmed to be an important layer of transcription regulation.Although genome-wide interaction data of several livestock species have already been produced,the genome structure states and its regulatory rules in cattle muscle are still limited.Results Here we present the first 3D genome data in Longissimus dorsi muscle of fetal and adult cattle(Bos taurus).We showed that compartments,topologically associating domains(TADs),and loop undergo re-organization and the structure dynamics were consistent with transcriptomic divergence during muscle development.Furthermore,we annotated cis-regulatory elements in cattle genome during myogenesis and demonstrated the enrichments of promoter and enhancer in selection sweeps.We further validated the regulatory function of one HMGA2 intronic enhancer near a strong sweep region on primary bovine myoblast proliferation.Conclusions Our data provide key insights of the regulatory function of high order chromatin structure and cattle myogenic biology,which will benefit the progress of genetic improvement of beef cattle.
