The complex current systems of the Southern Ocean play a critical role in shaping the heterogeneity and distinctiveness of Antarctic habitats.Nonetheless,how Antarctic water masses influence ciliates,one of the most c...The complex current systems of the Southern Ocean play a critical role in shaping the heterogeneity and distinctiveness of Antarctic habitats.Nonetheless,how Antarctic water masses influence ciliates,one of the most common groups of protozoa in polar regions,remains largely unknown.The present study investigated how the ciliate communities are affected by com-plex Southern Ocean currents by analyzing the diversity distributions,community assembly mechanisms,and co-occurrence networks of ciliates across three distinct water masses in the Scotia Sea.The findings reveal that the hydrography of the Scotia Sea significantly affects the spatial patterns of planktonic ciliates,primarily through the combination of temperature,salinity,and depth.In contract to surface waters(Antarctic Surface Water and Antarctic Circumpolar Current),ciliates inhab-iting deep waters(Circumpolar Deep Water)exhibit stronger and more direct correlations with the environment parameters,alongside greater network stability.Community assembly in surface and deep-water masses is governed by stochastic and deterministic processes,respectively.Compared to other Antarctic regions documented in previous studies,the Scotia Sea demonstrated the lowest alpha diversity indices for ciliates while harboring the highest number of endemic species.A detailed re-evaluation of Antarctic ciliate community structure in the Antarctic from prior research offers valuable insights into how dynamic ocean currents shape the ecological dynamics of ciliate communities,thus providing a broader understanding of the environmental changes impacting polar marine ecosystems.展开更多
Drone-based small object detection is of great significance in practical applications such as military actions, disaster rescue, transportation, etc. However, the severe scale differences in objects captured by drones...Drone-based small object detection is of great significance in practical applications such as military actions, disaster rescue, transportation, etc. However, the severe scale differences in objects captured by drones and lack of detail information for small-scale objects make drone-based small object detection a formidable challenge. To address these issues, we first develop a mathematical model to explore how changing receptive fields impacts the polynomial fitting results. Subsequently, based on the obtained conclusions, we propose a simple but effective Hybrid Receptive Field Network (HRFNet), whose modules include Hybrid Feature Augmentation (HFA), Hybrid Feature Pyramid (HFP) and Dual Scale Head (DSH). Specifically, HFA employs parallel dilated convolution kernels of different sizes to extend shallow features with different receptive fields, committed to improving the multi-scale adaptability of the network;HFP enhances the perception of small objects by capturing contextual information across layers, while DSH reconstructs the original prediction head utilizing a set of high-resolution features and ultrahigh-resolution features. In addition, in order to train HRFNet, the corresponding dual-scale loss function is designed. Finally, comprehensive evaluation results on public benchmarks such as VisDrone-DET and TinyPerson demonstrate the robustness of the proposed method. Most impressively, the proposed HRFNet achieves a mAP of 51.0 on VisDrone-DET with 29.3 M parameters, which outperforms the extant state-of-the-art detectors. HRFNet also performs excellently in complex scenarios captured by drones, achieving the best performance on the CS-Drone dataset we built.展开更多
Objective:This study investigated trends in the study of phytochemical treatment of post-traumatic stress disorder(PTSD).Methods:The Web of Science database(2007-2022)was searched using the search terms“phytochemical...Objective:This study investigated trends in the study of phytochemical treatment of post-traumatic stress disorder(PTSD).Methods:The Web of Science database(2007-2022)was searched using the search terms“phytochemicals”and“PTSD,”and relevant literature was compiled.Network clustering co-occurrence analysis and qualitative narrative review were conducted.Results:Three hundred and one articles were included in the analysis of published research,which has surged since 2015 with nearly half of all relevant articles coming from North America.The category is dominated by neuroscience and neurology,with two journals,Addictive Behaviors and Drug and Alcohol Dependence,publishing the greatest number of papers on these topics.Most studies focused on psychedelic intervention for PTSD.Three timelines show an“ebb and flow”phenomenon between“substance use/marijuana abuse”and“psychedelic medicine/medicinal cannabis.”Other phytochemicals account for a small proportion of the research and focus on topics like neurosteroid turnover,serotonin levels,and brain-derived neurotrophic factor expression.Conclusion:Research on phytochemicals and PTSD is unevenly distributed across countries/regions,disciplines,and journals.Since 2015,the research paradigm shifted to constitute the mainstream of psychedelic research thus far,leading to the exploration of botanical active ingredients and molecular mechanisms.Other studies focus on anti-oxidative stress and anti-inflammation.展开更多
Land use influences soil biota community composition and diversity,and then belowground ecosystem processes and functions.To characterize the effect of land use on soil biota,soil nematode communities in crop land,for...Land use influences soil biota community composition and diversity,and then belowground ecosystem processes and functions.To characterize the effect of land use on soil biota,soil nematode communities in crop land,forest land and fallow land were investigated in six regions of northern China.Generic richness,diversity,abundance and biomass of soil nematodes was the lowest in crop land.The richness and diversity of soil nematodes were 28.8and 15.1%higher in fallow land than in crop land,respectively.No significant differences in soil nematode indices were found between forest land and fallow land,but their network keystone genera composition was different.Among the keystone genera,50%of forest land genera were omnivores-predators and 36%of fallow land genera were bacterivores.The proportion of fungivores in forest land was 20.8%lower than in fallow land.The network complexity and the stability were lower in crop land than forest land and fallow land.Soil pH,NH_(4)^(+)-N and NO_(3)^(–)-N were the major factors influencing the soil nematode community in crop land while soil organic carbon and moisture were the major factors in forest land.Soil nematode communities in crop land influenced by artificial management practices were more dependent on the soil environment than communities in forest land and fallow land.Land use induced soil environment variation and altered network relationships by influencing trophic group proportions among keystone nematode genera.展开更多
Classifying the texture of granules in 2D images has aroused manifold research atten-tion for its technical challenges in image processing areas.This letter presents an aggregate texture identification approach by joi...Classifying the texture of granules in 2D images has aroused manifold research atten-tion for its technical challenges in image processing areas.This letter presents an aggregate texture identification approach by jointly using Gray Level Co-occurrence Probability(GLCP) and BP neural network techniques.First, up to 8 GLCP-associated texture feature parameters are defined and computed, and these consequent parameters next serve as the inputs feeding to the BP neural network to calculate the similarity to any of given aggregate texture type.A finite number of aggregate images of 3 kinds, with each containing specific type of mineral particles, are put to the identification test, experimentally proving the feasibility and robustness of the proposed method.展开更多
Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based ...Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based rendering （IBR）. Color correction between views is necessary to use multi-view systems in IBR to make audiences feel comfortable when views are switched or when a free viewpoint video is displayed. Color correction usually involves two steps： the first is to adjust camera parameters such as gain, brightness, and aperture before capture, and the second is to modify captured videos through image processing. This paper deals with the latter, which does not need a color pattern board. The proposed method uses scale invariant feature transform （SIFT） to detect correspondences, treats RGB channels independently, calculates lookup tables with an energy-minimization approach, and corrects captured video with these tables. The experimental results reveal that this approach works well.展开更多
Inversion tillage with straw amendment is widely applied in northeastern China, and it can substantially increase the storage of carbon and improve multiple subsoil functions. Soil microorganisms are believed to be th...Inversion tillage with straw amendment is widely applied in northeastern China, and it can substantially increase the storage of carbon and improve multiple subsoil functions. Soil microorganisms are believed to be the key to this process,but research into their role in subsoil amelioration is limited. Therefore, a field experiment was conducted in 2018 in a region in northeastern China with Hapli-Udic Cambisol using four treatments: conventional tillage(CT, tillage to a depth of 15 cm with no straw incorporation), straw incorporation with conventional tillage(SCT, tillage to a depth of 15 cm),inversion tillage(IT, tillage to a depth of 35 cm) and straw incorporation with inversion tillage(SIT, tillage to a depth of 35 cm). The soils were managed by inversion to a depth of 15 or 35 cm every year after harvest. The results indicated that SIT improved soil multi-nutrient cycling variables and increased the availability of key nutrients such as soil organic carbon, total nitrogen, available nitrogen, available phosphorus and available potassium in both the topsoil and subsoil.In contrast to CT and SCT, SIT created a looser microbial network structure but with highly centralized clusters by reducing the topological properties of average connectivity and node number, and by increasing the average path length and the modularity. A Random Forest analysis found that the average path length and the clustering coefficient were the main determinants of soil multi-nutrient cycling. These findings suggested that SIT can be an effective option for improving soil multi-nutrient cycling and the structure of microbial networks, and they provide crucial information about the microbial strategies that drive the decomposition of straw in Hapli-Udic Cambisol.展开更多
Interactions between dissolved organic matter(DOM)and bacteria are central in the biogeochemical cycles of aquatic ecosystems;however,the relative importance of biodegradable dissolved organic carbon(BDOC)compared wit...Interactions between dissolved organic matter(DOM)and bacteria are central in the biogeochemical cycles of aquatic ecosystems;however,the relative importance of biodegradable dissolved organic carbon(BDOC)compared with other environmental variables in structuring the bacterial communities needs further investigation.Here,we investigated bacterial communities,chromophoric DOM(CDOM)characteristics and physico-chemical parameters as well as examined BDOC via bioassay incubations in large eutrophic Lake Taihu,China,to explore the importance of BDOC for shaping bacterial community structures and co-occurrence patterns.We found that the proportion of BDOC(%BDOC)correlated significantly and positively with the DOC concentration and the index of the contribution of recent produced autochthonous CDOM(BIX).%BDOC,further correlated positively with the relative abundance of the tryptophan-like component and negatively with CDOM aromaticity,indicating that autochthonous production of protein-like CDOM was an important source of BDOC.The richness of the bacterial communities correlated negatively with%BDOC,indicating an enhanced number of species in the refractory DOC environments.%BDOC was identified as a significant stronger factor than DOC in shaping bacterial community composition and the co-occurrence network,suggesting that substrate biodegradability is more significant than DOC quantity determining the bacterial communities in a eutrophic lake.Environmental factors explained a larger proportion of the variation in the conditionally rare and abundant subcommunity than for the abundant and the rare bacterial subcommunities.Our findings emphasize the importance of considering bacteria with different abundance patterns and DOC biodegradability when studying the interactions between DOM and bacteria in eutrophic lakes.展开更多
Denitrifying bacteria in epiphytic biofilms play a crucial role in nitrogen cycle in aquatic habitats.However,little is known about the connection between algae and denitrifying bacteria and their assembly processes i...Denitrifying bacteria in epiphytic biofilms play a crucial role in nitrogen cycle in aquatic habitats.However,little is known about the connection between algae and denitrifying bacteria and their assembly processes in epiphytic biofilms.Epiphytic biofilms were collected from submerged macrophytes(Patamogeton lucens and Najas marina L.)in the Caohai Lake,Guizhou,SW China,from July to November 2020 to:(1)investigate the impact of abiotic and biotic variables on denitrifying bacterial communities;(2)investigate the temporal variation of the algae-denitrifying bacteria co-occurrence networks;and(3)determine the contribution of deterministic and stochastic processes to the formation of denitrifying bacterial communities.Abiotic and biotic factors influenced the variation in the denitrifying bacterial community,as shown in the Mantel test.The co-occurrence network analysis unveiled intricate interactions among algae to denitrifying bacteria.Denitrifying bacterial community co-occurrence network complexity(larger average degrees representing stronger network complexity)increased continuously from July to September and decreased in October before increasing in November.The co-occurrence network complexity of the algae and nirS-encoding denitrifying bacteria tended to increase from July to November.The co-occurrence network complexity of the algal and denitrifying bacterial communities was modified by ammonia nitrogen(NH_(4)^(+)-N)and total phosphorus(TP),pH,and water temperature(WT),according to the ordinary least-squares(OLS)model.The modified stochasticity ratio(MST)results reveal that deterministic selection dominated the assembly of denitrifying bacterial communities.The influence of environmental variables to denitrifying bacterial communities,as well as characteristics of algal-bacterial co-occurrence networks and the assembly process of denitrifying bacterial communities,were discovered in epiphytic biofilms in this study.The findings could aid in the appropriate understanding and use of epiphytic biofilms denitrification function,as well as the enhancement of water quality.展开更多
Nitrogen(N)deep placement has been found to reduce N leaching and increase N use efficiency in paddy fields.However,relatively little is known how bacterial consortia,especially abundant and rare taxa,respond to N dee...Nitrogen(N)deep placement has been found to reduce N leaching and increase N use efficiency in paddy fields.However,relatively little is known how bacterial consortia,especially abundant and rare taxa,respond to N deep placement,which is critical for understanding the biodiversity and function of agricultural ecosystem.In this study,lllumina sequencing and ecological models were conducted to examine the diversity patterns and underlying assembly mechanisms of abundant and rare taxa in rice rhizosphere soil under different N fertilization regimes at four rice growth stages in paddy fields.The results showed that abundant and rare bacteria had distinct distribution patterns in rhizosphere samples.Abundant bacteria showed ubiquitous distribution;while rare taxa exhibited uneven distribution across all samples.Stochastic processes dominated community assembly of both abundant and rare bacteria,with dispersal limitation playing a more vital role in abundant bacteria,and undominated processes playing a more important role in rare bacteria.The N deep placement was associated with a greater influence of dispersal limitation than the broadcast N fertilizer(BN)and no N fertilizer(NN)treatments in abundant and rare taxa of rhizosphere soil;while greater contributions from homogenizing dispersal were observed for BN and NN in rare taxa.Network analysis indicated that abundant taxa with closer relationships were usually more likely to occupy the central position of the network than rare taxa.Nevertheless,most of the keystone species were rare taxa and might have played essential roles in maintaining the network stability.Overall,these findings highlighted that the ecological mechanisms and co-occurrence patterns of abundant and rare bacteria in rhizosphere soil under N deep placement.展开更多
Climate change and human activity have led to the degradation of desert wetlands.Free-living diazotrophs are vital for soil nitrogen input.However,a comprehensive understanding of how soil free-living diazotrophic com...Climate change and human activity have led to the degradation of desert wetlands.Free-living diazotrophs are vital for soil nitrogen input.However,a comprehensive understanding of how soil free-living diazotrophic communities and their co-occurrence patterns respond to desert wetland degradation is lacking.Here,quantitative polymerase chain reaction(qPCR),amplicon sequencing targeting nitrogenase gene(nifH),and network analysis were used to investigate the abundance,diversity,community composition,and co-occurrence patterns of soil free-living diazotrophs along the wetland degradation gradient,i.e.,non-degraded(ND),lightly degraded(LD),moderately degraded(MD),and severely degraded(SD),in the southeastern Mu Us Desert,northern China.The abundance and Shannon,Simpson,Chao 1,and ACE indexes decreased(P<0.05)by 14.6%,20.7%,2.1%,46.5%,and 45.0%,respectively,in SD wetland,whereas no significant difference(P>0.05)was observed between ND and LD wetlands.The relative abundance of Proteobacteria generally decreased(by 53.5%–19.7%)across the different degradation levels,while the relative abundance of Cyanobacteria increased(by 6.2%–40.1%)from ND to MD levels.The abundance,diversity,and community composition of diazotrophs were most strongly related to soil organic carbon,followed by total nitrogen,moisture,and pH.The least number of network nodes and edges and the lowest density were observed for MD and SD wetlands,indicating that the complexity of free-living diazotrophic networks was reduced by continued degeneration.Overall,severe desert wetland degradation affected the abundance,diversity,and network complexity of soil free-living diazotrophs more negatively than light degradation.This degradation promoted the growth of autotrophic diazotrophs and inhibited the growth of heterotrophic diazotrophs.These changes were mostly related to the loss of soil organic carbon.展开更多
Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their...Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.展开更多
The co-occurrence of bacteria and microeukaryote species is a ubiquitous ecological phenomenon,but there is limited cross-domain research in aquatic environments.We conducted a network statistical analysis and visuali...The co-occurrence of bacteria and microeukaryote species is a ubiquitous ecological phenomenon,but there is limited cross-domain research in aquatic environments.We conducted a network statistical analysis and visualization of microbial cross-domain co-occurrence patterns based on DNA sampling of a typical subtropical bay during four seasons,using high-throughput sequencing of both 18S rRNA and 16S rRNA genes.First,we found obvious relationships between network stability and network complexity indices.For example,increased cooperation and modularity were found to weaken the stability of cross-domain networks.Secondly,we found that bacterial operational taxonomic units(OTUs)were the most important contributors to network complexity and stability as they occupied more nodes,constituted more keystone OTUs,built more connections,more importantly,ignoring bacteria led to greater variation in network robustness.Gammaproteobacteria,Alphaproteobacteria,Bacteroidetes,and Actinobacteria were the most ecologically important groups.Finally,we found that the environmental drivers most associated with cross-domain networks varied across seasons(in detail,the network in January was primarily constrained by temperature and salinity,the network in April was primarily constrained by depth and temperature,the network in July was mainly affected by depth,temperature,and salinity,depth was the most important factor affecting the network in October)and that environmental influence was stronger on bacteria than on microeukaryotes.展开更多
The Western Subarctic Gyre(WSG)is one of the two gyre-systems in the subarctic North Pacific known for high nutrient and low-chlorophyll waters.However,the bacterioplankton in marine water of this area,either in terms...The Western Subarctic Gyre(WSG)is one of the two gyre-systems in the subarctic North Pacific known for high nutrient and low-chlorophyll waters.However,the bacterioplankton in marine water of this area,either in terms of the taxonomic composition or functional structure,remains relatively unexplored.A total of 22 sampling sites from two water layers(surface water,SW and 50-m layer water,FW)were collected in this area.The physiochemical parameters of waters,Synechococcus,and bacterial density,as well as the bacterioplankton community composition and distribution pattern,were analyzed.The nutrient concentrations of DIN,DIP,and DSi,Chl-a concentration,and the average abundance of heterobacteria in FW were higher than those in SW.However,temperature and the average abundance of Synechococcus and pico-eukaryotes were higher in SW.A total of 3269 OTUs were assigned,and 2123OTUs were commonly shared;moreover,similar alpha diversity patterns were observed in both SW and FW.The bacterioplankton community showed significantly obvious correlation with salinity,DIP,DIN,and Chl a in both SW and FW.Proteobacteria,Cyanobacteria,Bacteroidota,Actinobacteriota,and Firmicutes were the main phyla while Synechococcus_CC9902,Psychrobacter,and Sulfitobacter were the dominant genera in each sampling site.Most correlations that happened between the OTUs in the cooccurrence network were positive and inter-module.Higher edges and graph density were found in SW,indicating that more correlations occurred,and the community was more complex in SW.This study provided novel knowledge on the bacterioplankton community structure and the correlation characteristics in WSG.展开更多
In this paper we deal with Twitter and the presence of the keyword “Macedonia” in tweets over a period of time. We searched for the same term in three different languages, i.e. “Μακεδονíα”, “Macedoni...In this paper we deal with Twitter and the presence of the keyword “Macedonia” in tweets over a period of time. We searched for the same term in three different languages, i.e. “Μακεδονíα”, “Macedonia” and “Македонска - Македониjа”, since we are primarily interested in views from Greece and FYROM without excluding views from other regions. We use methods from Social Network Analysis (SNA) in order to create networks of users, calculate some main network metrics, measure user importance and investigate the presence of possible fragmentations—communities among them. We furthermore proceed to a form of content analysis, using pairs of words within tweets, in order to obtain main ideas, trends and public views that circulated over the network.展开更多
Background In this study, we propose view interpolation networks to reproduce changes in the brightness of an object′s surface depending on the viewing direction, which is important for reproducing the material appea...Background In this study, we propose view interpolation networks to reproduce changes in the brightness of an object′s surface depending on the viewing direction, which is important for reproducing the material appearance of a real object. Method We used an original and modified version of U-Net for image transformation. The networks were trained to generate images from the intermediate viewpoints of four cameras placed at the corners of a square. We conducted an experiment using with three different combinations of methods and training data formats. Result We determined that inputting the coordinates of the viewpoints together with the four camera images and using images from random viewpoints as the training data produces the best results.展开更多
Side scan sonar imaging is one of the advanced methods for seabed study.In order to be utilized in other projects,such as ocean engineering,the image needs to be classified according to the distributions of different ...Side scan sonar imaging is one of the advanced methods for seabed study.In order to be utilized in other projects,such as ocean engineering,the image needs to be classified according to the distributions of different classes of seabed materials.In this paper,seabed image is classified according to BP neural network,and.Genetic Algorithm is adopted in train network in this paper.The feature vectors are average intensity,six statistics of texture and two dimensions of fractal.It considers not only the spatial correlation between different pixels,but also the terrain coarseness.The texture is denoted by the statistics of the co-occurrence matrix.Double Blanket algorithm is used to calculate dimension.Because a uniform fractal may not be sufficient to describe a seafloor,two dimensions are calculated respectively by the upper blanket and the lower blanket.However,in sonar image,fractal has directivity,i.e.there are different dimensions in different direction.Dimensions are different in acrosstrack and alongtrack,so the average of four directions is used to solve this problem.Finally,the real data verify the algorithm.In this paper,one hidden layer including six nodes is adopted.The BP network is rapidly and accurately convergent through GA.Correct classification rate is 92.5%in the result.展开更多
基金supported by the Science and Technology Innovation Project of Laoshan Laboratory(LSKJ202203205)National Natural Science Foundation of China(NFSC)(Nos.42276156,42206147,32100404)Natural Science Foundation of Shandong Province of China(No.ZR2021QC045).
文摘The complex current systems of the Southern Ocean play a critical role in shaping the heterogeneity and distinctiveness of Antarctic habitats.Nonetheless,how Antarctic water masses influence ciliates,one of the most common groups of protozoa in polar regions,remains largely unknown.The present study investigated how the ciliate communities are affected by com-plex Southern Ocean currents by analyzing the diversity distributions,community assembly mechanisms,and co-occurrence networks of ciliates across three distinct water masses in the Scotia Sea.The findings reveal that the hydrography of the Scotia Sea significantly affects the spatial patterns of planktonic ciliates,primarily through the combination of temperature,salinity,and depth.In contract to surface waters(Antarctic Surface Water and Antarctic Circumpolar Current),ciliates inhab-iting deep waters(Circumpolar Deep Water)exhibit stronger and more direct correlations with the environment parameters,alongside greater network stability.Community assembly in surface and deep-water masses is governed by stochastic and deterministic processes,respectively.Compared to other Antarctic regions documented in previous studies,the Scotia Sea demonstrated the lowest alpha diversity indices for ciliates while harboring the highest number of endemic species.A detailed re-evaluation of Antarctic ciliate community structure in the Antarctic from prior research offers valuable insights into how dynamic ocean currents shape the ecological dynamics of ciliate communities,thus providing a broader understanding of the environmental changes impacting polar marine ecosystems.
基金supported by the National Natural Science Foundation of China(Nos.62276204 and 62203343)the Fundamental Research Funds for the Central Universities(No.YJSJ24011)+1 种基金the Natural Science Basic Research Program of Shanxi,China(Nos.2022JM-340 and 2023-JC-QN-0710)the China Postdoctoral Science Foundation(Nos.2020T130494 and 2018M633470).
文摘Drone-based small object detection is of great significance in practical applications such as military actions, disaster rescue, transportation, etc. However, the severe scale differences in objects captured by drones and lack of detail information for small-scale objects make drone-based small object detection a formidable challenge. To address these issues, we first develop a mathematical model to explore how changing receptive fields impacts the polynomial fitting results. Subsequently, based on the obtained conclusions, we propose a simple but effective Hybrid Receptive Field Network (HRFNet), whose modules include Hybrid Feature Augmentation (HFA), Hybrid Feature Pyramid (HFP) and Dual Scale Head (DSH). Specifically, HFA employs parallel dilated convolution kernels of different sizes to extend shallow features with different receptive fields, committed to improving the multi-scale adaptability of the network;HFP enhances the perception of small objects by capturing contextual information across layers, while DSH reconstructs the original prediction head utilizing a set of high-resolution features and ultrahigh-resolution features. In addition, in order to train HRFNet, the corresponding dual-scale loss function is designed. Finally, comprehensive evaluation results on public benchmarks such as VisDrone-DET and TinyPerson demonstrate the robustness of the proposed method. Most impressively, the proposed HRFNet achieves a mAP of 51.0 on VisDrone-DET with 29.3 M parameters, which outperforms the extant state-of-the-art detectors. HRFNet also performs excellently in complex scenarios captured by drones, achieving the best performance on the CS-Drone dataset we built.
基金the National Natural Science Foundation of China(No.81573150)Military Key Discipline Construction Projects of China(No.HL21JD1206).
文摘Objective:This study investigated trends in the study of phytochemical treatment of post-traumatic stress disorder(PTSD).Methods:The Web of Science database(2007-2022)was searched using the search terms“phytochemicals”and“PTSD,”and relevant literature was compiled.Network clustering co-occurrence analysis and qualitative narrative review were conducted.Results:Three hundred and one articles were included in the analysis of published research,which has surged since 2015 with nearly half of all relevant articles coming from North America.The category is dominated by neuroscience and neurology,with two journals,Addictive Behaviors and Drug and Alcohol Dependence,publishing the greatest number of papers on these topics.Most studies focused on psychedelic intervention for PTSD.Three timelines show an“ebb and flow”phenomenon between“substance use/marijuana abuse”and“psychedelic medicine/medicinal cannabis.”Other phytochemicals account for a small proportion of the research and focus on topics like neurosteroid turnover,serotonin levels,and brain-derived neurotrophic factor expression.Conclusion:Research on phytochemicals and PTSD is unevenly distributed across countries/regions,disciplines,and journals.Since 2015,the research paradigm shifted to constitute the mainstream of psychedelic research thus far,leading to the exploration of botanical active ingredients and molecular mechanisms.Other studies focus on anti-oxidative stress and anti-inflammation.
基金supported by the National Natural Science Foundation of China(U22A20501)the National Key Research and Development Plan of China(2022YFD1500601)+4 种基金the National Science and Technology Fundamental Resources Investigation Program of China(2018FY100304)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA28090200)the Liaoning Province Applied Basic Research Plan Program,China(2022JH2/101300184)the Shenyang Science and Technology Plan Program,China(21-109-305)the Liaoning Outstanding Innovation Team,China(XLYC2008015)。
文摘Land use influences soil biota community composition and diversity,and then belowground ecosystem processes and functions.To characterize the effect of land use on soil biota,soil nematode communities in crop land,forest land and fallow land were investigated in six regions of northern China.Generic richness,diversity,abundance and biomass of soil nematodes was the lowest in crop land.The richness and diversity of soil nematodes were 28.8and 15.1%higher in fallow land than in crop land,respectively.No significant differences in soil nematode indices were found between forest land and fallow land,but their network keystone genera composition was different.Among the keystone genera,50%of forest land genera were omnivores-predators and 36%of fallow land genera were bacterivores.The proportion of fungivores in forest land was 20.8%lower than in fallow land.The network complexity and the stability were lower in crop land than forest land and fallow land.Soil pH,NH_(4)^(+)-N and NO_(3)^(–)-N were the major factors influencing the soil nematode community in crop land while soil organic carbon and moisture were the major factors in forest land.Soil nematode communities in crop land influenced by artificial management practices were more dependent on the soil environment than communities in forest land and fallow land.Land use induced soil environment variation and altered network relationships by influencing trophic group proportions among keystone nematode genera.
基金Funded by Ningbo Natural Science Foundation (No.2006A610016)
文摘Classifying the texture of granules in 2D images has aroused manifold research atten-tion for its technical challenges in image processing areas.This letter presents an aggregate texture identification approach by jointly using Gray Level Co-occurrence Probability(GLCP) and BP neural network techniques.First, up to 8 GLCP-associated texture feature parameters are defined and computed, and these consequent parameters next serve as the inputs feeding to the BP neural network to calculate the similarity to any of given aggregate texture type.A finite number of aggregate images of 3 kinds, with each containing specific type of mineral particles, are put to the identification test, experimentally proving the feasibility and robustness of the proposed method.
文摘Systems using numerous cameras are emerging in many fields due to their ease of production and reduced cost, and one of the fields where they are expected to be used more actively in the near future is in image-based rendering （IBR）. Color correction between views is necessary to use multi-view systems in IBR to make audiences feel comfortable when views are switched or when a free viewpoint video is displayed. Color correction usually involves two steps： the first is to adjust camera parameters such as gain, brightness, and aperture before capture, and the second is to modify captured videos through image processing. This paper deals with the latter, which does not need a color pattern board. The proposed method uses scale invariant feature transform （SIFT） to detect correspondences, treats RGB channels independently, calculates lookup tables with an energy-minimization approach, and corrects captured video with these tables. The experimental results reveal that this approach works well.
基金funded by the National Key Research and Development Program of China (2022YFD1500100)the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA28070100)+1 种基金the National Natural Science Foundation of China (41807085)the earmarked fund for China Agriculture Research System (CARS04)。
文摘Inversion tillage with straw amendment is widely applied in northeastern China, and it can substantially increase the storage of carbon and improve multiple subsoil functions. Soil microorganisms are believed to be the key to this process,but research into their role in subsoil amelioration is limited. Therefore, a field experiment was conducted in 2018 in a region in northeastern China with Hapli-Udic Cambisol using four treatments: conventional tillage(CT, tillage to a depth of 15 cm with no straw incorporation), straw incorporation with conventional tillage(SCT, tillage to a depth of 15 cm),inversion tillage(IT, tillage to a depth of 35 cm) and straw incorporation with inversion tillage(SIT, tillage to a depth of 35 cm). The soils were managed by inversion to a depth of 15 or 35 cm every year after harvest. The results indicated that SIT improved soil multi-nutrient cycling variables and increased the availability of key nutrients such as soil organic carbon, total nitrogen, available nitrogen, available phosphorus and available potassium in both the topsoil and subsoil.In contrast to CT and SCT, SIT created a looser microbial network structure but with highly centralized clusters by reducing the topological properties of average connectivity and node number, and by increasing the average path length and the modularity. A Random Forest analysis found that the average path length and the clustering coefficient were the main determinants of soil multi-nutrient cycling. These findings suggested that SIT can be an effective option for improving soil multi-nutrient cycling and the structure of microbial networks, and they provide crucial information about the microbial strategies that drive the decomposition of straw in Hapli-Udic Cambisol.
基金supported by the National Natural Science Foundation of China (Nos.41930760, 41807362, and 41977322)the Provincial Natural Science Foundation of Jiangsu in China (No.BK20181104)+2 种基金the Key Research Program of Frontier Sciences, Chinese Academy of Sciences (No.QYZDB-SSWDQC016)supported by WATEC (Centre for Water Technology, AU)the TüBITAK outstanding scientists program 2232 (project 118C250)。
文摘Interactions between dissolved organic matter(DOM)and bacteria are central in the biogeochemical cycles of aquatic ecosystems;however,the relative importance of biodegradable dissolved organic carbon(BDOC)compared with other environmental variables in structuring the bacterial communities needs further investigation.Here,we investigated bacterial communities,chromophoric DOM(CDOM)characteristics and physico-chemical parameters as well as examined BDOC via bioassay incubations in large eutrophic Lake Taihu,China,to explore the importance of BDOC for shaping bacterial community structures and co-occurrence patterns.We found that the proportion of BDOC(%BDOC)correlated significantly and positively with the DOC concentration and the index of the contribution of recent produced autochthonous CDOM(BIX).%BDOC,further correlated positively with the relative abundance of the tryptophan-like component and negatively with CDOM aromaticity,indicating that autochthonous production of protein-like CDOM was an important source of BDOC.The richness of the bacterial communities correlated negatively with%BDOC,indicating an enhanced number of species in the refractory DOC environments.%BDOC was identified as a significant stronger factor than DOC in shaping bacterial community composition and the co-occurrence network,suggesting that substrate biodegradability is more significant than DOC quantity determining the bacterial communities in a eutrophic lake.Environmental factors explained a larger proportion of the variation in the conditionally rare and abundant subcommunity than for the abundant and the rare bacterial subcommunities.Our findings emphasize the importance of considering bacteria with different abundance patterns and DOC biodegradability when studying the interactions between DOM and bacteria in eutrophic lakes.
基金Supported by the National Natural Science Foundation of China(No.41867056)the Guizhou Provincial Key Technology R&D Program(Nos.2021470,2023216)。
文摘Denitrifying bacteria in epiphytic biofilms play a crucial role in nitrogen cycle in aquatic habitats.However,little is known about the connection between algae and denitrifying bacteria and their assembly processes in epiphytic biofilms.Epiphytic biofilms were collected from submerged macrophytes(Patamogeton lucens and Najas marina L.)in the Caohai Lake,Guizhou,SW China,from July to November 2020 to:(1)investigate the impact of abiotic and biotic variables on denitrifying bacterial communities;(2)investigate the temporal variation of the algae-denitrifying bacteria co-occurrence networks;and(3)determine the contribution of deterministic and stochastic processes to the formation of denitrifying bacterial communities.Abiotic and biotic factors influenced the variation in the denitrifying bacterial community,as shown in the Mantel test.The co-occurrence network analysis unveiled intricate interactions among algae to denitrifying bacteria.Denitrifying bacterial community co-occurrence network complexity(larger average degrees representing stronger network complexity)increased continuously from July to September and decreased in October before increasing in November.The co-occurrence network complexity of the algae and nirS-encoding denitrifying bacteria tended to increase from July to November.The co-occurrence network complexity of the algal and denitrifying bacterial communities was modified by ammonia nitrogen(NH_(4)^(+)-N)and total phosphorus(TP),pH,and water temperature(WT),according to the ordinary least-squares(OLS)model.The modified stochasticity ratio(MST)results reveal that deterministic selection dominated the assembly of denitrifying bacterial communities.The influence of environmental variables to denitrifying bacterial communities,as well as characteristics of algal-bacterial co-occurrence networks and the assembly process of denitrifying bacterial communities,were discovered in epiphytic biofilms in this study.The findings could aid in the appropriate understanding and use of epiphytic biofilms denitrification function,as well as the enhancement of water quality.
基金the National Key Research and Development Program of China(2016YFD0200309 and 2018YFD0301104-01).
文摘Nitrogen(N)deep placement has been found to reduce N leaching and increase N use efficiency in paddy fields.However,relatively little is known how bacterial consortia,especially abundant and rare taxa,respond to N deep placement,which is critical for understanding the biodiversity and function of agricultural ecosystem.In this study,lllumina sequencing and ecological models were conducted to examine the diversity patterns and underlying assembly mechanisms of abundant and rare taxa in rice rhizosphere soil under different N fertilization regimes at four rice growth stages in paddy fields.The results showed that abundant and rare bacteria had distinct distribution patterns in rhizosphere samples.Abundant bacteria showed ubiquitous distribution;while rare taxa exhibited uneven distribution across all samples.Stochastic processes dominated community assembly of both abundant and rare bacteria,with dispersal limitation playing a more vital role in abundant bacteria,and undominated processes playing a more important role in rare bacteria.The N deep placement was associated with a greater influence of dispersal limitation than the broadcast N fertilizer(BN)and no N fertilizer(NN)treatments in abundant and rare taxa of rhizosphere soil;while greater contributions from homogenizing dispersal were observed for BN and NN in rare taxa.Network analysis indicated that abundant taxa with closer relationships were usually more likely to occupy the central position of the network than rare taxa.Nevertheless,most of the keystone species were rare taxa and might have played essential roles in maintaining the network stability.Overall,these findings highlighted that the ecological mechanisms and co-occurrence patterns of abundant and rare bacteria in rhizosphere soil under N deep placement.
基金supported by the National Natural Science Foundation of China(No.41471437)the National Key R&D Program of China(Nos.2016YFA0600801,2017YFC0504504)the West Light Foundation of the Chinese Academy of Sciences(No.XAB2016A04).
文摘Climate change and human activity have led to the degradation of desert wetlands.Free-living diazotrophs are vital for soil nitrogen input.However,a comprehensive understanding of how soil free-living diazotrophic communities and their co-occurrence patterns respond to desert wetland degradation is lacking.Here,quantitative polymerase chain reaction(qPCR),amplicon sequencing targeting nitrogenase gene(nifH),and network analysis were used to investigate the abundance,diversity,community composition,and co-occurrence patterns of soil free-living diazotrophs along the wetland degradation gradient,i.e.,non-degraded(ND),lightly degraded(LD),moderately degraded(MD),and severely degraded(SD),in the southeastern Mu Us Desert,northern China.The abundance and Shannon,Simpson,Chao 1,and ACE indexes decreased(P<0.05)by 14.6%,20.7%,2.1%,46.5%,and 45.0%,respectively,in SD wetland,whereas no significant difference(P>0.05)was observed between ND and LD wetlands.The relative abundance of Proteobacteria generally decreased(by 53.5%–19.7%)across the different degradation levels,while the relative abundance of Cyanobacteria increased(by 6.2%–40.1%)from ND to MD levels.The abundance,diversity,and community composition of diazotrophs were most strongly related to soil organic carbon,followed by total nitrogen,moisture,and pH.The least number of network nodes and edges and the lowest density were observed for MD and SD wetlands,indicating that the complexity of free-living diazotrophic networks was reduced by continued degeneration.Overall,severe desert wetland degradation affected the abundance,diversity,and network complexity of soil free-living diazotrophs more negatively than light degradation.This degradation promoted the growth of autotrophic diazotrophs and inhibited the growth of heterotrophic diazotrophs.These changes were mostly related to the loss of soil organic carbon.
基金the National Natural Science Foundation of China Grant 71673131 for financial support
文摘Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.
基金Supported by the National Natural Science Foundation of China(Nos.42141003,42176147)the National Key Research and Development Program of China(No.2022YFF0802204)the Natural Science Foundation of Fujian Province of China(No.2021J01025)。
文摘The co-occurrence of bacteria and microeukaryote species is a ubiquitous ecological phenomenon,but there is limited cross-domain research in aquatic environments.We conducted a network statistical analysis and visualization of microbial cross-domain co-occurrence patterns based on DNA sampling of a typical subtropical bay during four seasons,using high-throughput sequencing of both 18S rRNA and 16S rRNA genes.First,we found obvious relationships between network stability and network complexity indices.For example,increased cooperation and modularity were found to weaken the stability of cross-domain networks.Secondly,we found that bacterial operational taxonomic units(OTUs)were the most important contributors to network complexity and stability as they occupied more nodes,constituted more keystone OTUs,built more connections,more importantly,ignoring bacteria led to greater variation in network robustness.Gammaproteobacteria,Alphaproteobacteria,Bacteroidetes,and Actinobacteria were the most ecologically important groups.Finally,we found that the environmental drivers most associated with cross-domain networks varied across seasons(in detail,the network in January was primarily constrained by temperature and salinity,the network in April was primarily constrained by depth and temperature,the network in July was mainly affected by depth,temperature,and salinity,depth was the most important factor affecting the network in October)and that environmental influence was stronger on bacteria than on microeukaryotes.
基金Supported by the National Key Research and Development Program of China(No.2019YFD0901401)the Natural Science Foundation of Shandong Province(No.ZR202102280248)+1 种基金the National Natural Science Foundation of China(No.81900630)the Outstanding Youth Project of Yunnan Provincial Department of Science and Technology(No.2019F1019)。
文摘The Western Subarctic Gyre(WSG)is one of the two gyre-systems in the subarctic North Pacific known for high nutrient and low-chlorophyll waters.However,the bacterioplankton in marine water of this area,either in terms of the taxonomic composition or functional structure,remains relatively unexplored.A total of 22 sampling sites from two water layers(surface water,SW and 50-m layer water,FW)were collected in this area.The physiochemical parameters of waters,Synechococcus,and bacterial density,as well as the bacterioplankton community composition and distribution pattern,were analyzed.The nutrient concentrations of DIN,DIP,and DSi,Chl-a concentration,and the average abundance of heterobacteria in FW were higher than those in SW.However,temperature and the average abundance of Synechococcus and pico-eukaryotes were higher in SW.A total of 3269 OTUs were assigned,and 2123OTUs were commonly shared;moreover,similar alpha diversity patterns were observed in both SW and FW.The bacterioplankton community showed significantly obvious correlation with salinity,DIP,DIN,and Chl a in both SW and FW.Proteobacteria,Cyanobacteria,Bacteroidota,Actinobacteriota,and Firmicutes were the main phyla while Synechococcus_CC9902,Psychrobacter,and Sulfitobacter were the dominant genera in each sampling site.Most correlations that happened between the OTUs in the cooccurrence network were positive and inter-module.Higher edges and graph density were found in SW,indicating that more correlations occurred,and the community was more complex in SW.This study provided novel knowledge on the bacterioplankton community structure and the correlation characteristics in WSG.
文摘In this paper we deal with Twitter and the presence of the keyword “Macedonia” in tweets over a period of time. We searched for the same term in three different languages, i.e. “Μακεδονíα”, “Macedonia” and “Македонска - Македониjа”, since we are primarily interested in views from Greece and FYROM without excluding views from other regions. We use methods from Social Network Analysis (SNA) in order to create networks of users, calculate some main network metrics, measure user importance and investigate the presence of possible fragmentations—communities among them. We furthermore proceed to a form of content analysis, using pairs of words within tweets, in order to obtain main ideas, trends and public views that circulated over the network.
文摘Background In this study, we propose view interpolation networks to reproduce changes in the brightness of an object′s surface depending on the viewing direction, which is important for reproducing the material appearance of a real object. Method We used an original and modified version of U-Net for image transformation. The networks were trained to generate images from the intermediate viewpoints of four cameras placed at the corners of a square. We conducted an experiment using with three different combinations of methods and training data formats. Result We determined that inputting the coordinates of the viewpoints together with the four camera images and using images from random viewpoints as the training data produces the best results.
文摘Side scan sonar imaging is one of the advanced methods for seabed study.In order to be utilized in other projects,such as ocean engineering,the image needs to be classified according to the distributions of different classes of seabed materials.In this paper,seabed image is classified according to BP neural network,and.Genetic Algorithm is adopted in train network in this paper.The feature vectors are average intensity,six statistics of texture and two dimensions of fractal.It considers not only the spatial correlation between different pixels,but also the terrain coarseness.The texture is denoted by the statistics of the co-occurrence matrix.Double Blanket algorithm is used to calculate dimension.Because a uniform fractal may not be sufficient to describe a seafloor,two dimensions are calculated respectively by the upper blanket and the lower blanket.However,in sonar image,fractal has directivity,i.e.there are different dimensions in different direction.Dimensions are different in acrosstrack and alongtrack,so the average of four directions is used to solve this problem.Finally,the real data verify the algorithm.In this paper,one hidden layer including six nodes is adopted.The BP network is rapidly and accurately convergent through GA.Correct classification rate is 92.5%in the result.
