The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated....The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.展开更多
The generic classification of the family Orthophlebiidae is revised systematically in the present paper. Genera Orthophlebia and Protophlebia are remained in the family Orthophlebiidae while genus Mesophlebia is disas...The generic classification of the family Orthophlebiidae is revised systematically in the present paper. Genera Orthophlebia and Protophlebia are remained in the family Orthophlebiidae while genus Mesophlebia is disassembled, in which the species are ascribed to Orthophlebia if Rs1 at least with 3 branches, and to Protophlebia if Rs1 only with 2 branches. Three subgenera are erected in Orthophlebia and Protophlebia respectively according to the relationship between stems of Rs and MA, i.e. Rs forking earlier or later than MA, or at the same level as MA.展开更多
AIM To evaluate the role of small bowel capsule endoscopy(SBCE)on the reclassification of colonic inflammatory bowel disease type unclassified(IBDU).METHODS We performed a multicenter,retrospective study including pat...AIM To evaluate the role of small bowel capsule endoscopy(SBCE)on the reclassification of colonic inflammatory bowel disease type unclassified(IBDU).METHODS We performed a multicenter,retrospective study including patients with IBDU undergoing SBCE,between 2002 and 2014.SBCE studies were reviewed and the inflammatory activity was evaluated by determining the Lewis score(LS).Inflammatory activity was considered significant and consistent with Crohn's disease(CD)when the LS≥135.The definitive diagnosis during follow-up(minimum 12 mo following SBCE)was based on the combination of clinical,analytical,imaging,endoscopic and histological elements.RESULTS Thirty-six patients were included,21 females(58%)with mean age at diagnosis of 33±13(15-64)years.The mean follow-up time after the SBCE was 52±41(12-156)mo.The SBCE revealed findings consistent with significant inflammatory activity in the small bowel(LS≥135)in 9 patients(25%);in all of them the diagnosis of CD was confirmed during follow-up.In 27 patients(75%),the SBCE revealed no significant inflammatory activity(LS<135);among these patients,the diagnosis of Ulcerative Colitis(UC)was established in 16 cases(59.3%),CD in 1 case(3.7%)and 10 patients(37%)maintained a diagnosis of IBDU during follow-up.A LS≥135 at SBCE had a sensitivity=90%,specificity=100%,positive predictive value=100%and negative predictive value=94%for the diagnosis of CD.CONCLUSION SBCE proved to be fundamental in the reclassification of patients with IBDU.Absence of significant inflammatory activity in the small intestine allowed exclusion of CD in 94%of cases.展开更多
This review revises the reclassification of the mem-branoproliferative glomerulonephritis （MPGN） after the consensus conference that by 2015 reclassified all the glomerulonephritis basing on etiology and patho-genes...This review revises the reclassification of the mem-branoproliferative glomerulonephritis （MPGN） after the consensus conference that by 2015 reclassified all the glomerulonephritis basing on etiology and patho-genesis, instead of the histomorphological aspects. After reclassification, two types of MPGN are to date recognized： The immunocomplexes mediated MPGN and the complement mediated MPGN. The latter type is more extensively described in the review either because several of these entities are completely new or because the improved knowledge of the complement cascade allowed for new diagnostic and therapeutic approaches. Overall the complement mediated MPGN are related to acquired or genetic cause. The presence of circulating auto antibodies is the principal acquired cause. Genetic wide association studies and family studies allowed to recognize genetic mutations of different types as causes of the complement dysregulation. The complement cascade is a complex phenomenon and activating factors and regulating factors should be distinguished. Genetic mutations causing abnormalities either in activating or in regulating factors have been described. The diagnosis of the complement mediated MPGN requires a complete study of all these different complement factors. As a consequence, new therapeutic approaches are becoming available. Indeed, in addition to a nonspecifc treatment and to the immunosuppression that has the aim to block the auto antibodies production, the specific inhibition of complement activation is relatively new and may act either blocking the C5 convertase or the C3 convertase. The drugs acting on C3 convertase are still in different phases of clinical development and might represent drugs for the future. Overall the authors consider that one of the principal problems in fnding new types of drugs are both the rarity of the disease and the consequent poor interest in the marketing and the lack of large international cooperative studies.展开更多
Although Chinese Ditransitive Construction(CDC) and English Ditransitive Construction(EDC) respectively belong to two completely different languages, there do exist many similarities between them. One of the similarit...Although Chinese Ditransitive Construction(CDC) and English Ditransitive Construction(EDC) respectively belong to two completely different languages, there do exist many similarities between them. One of the similarities is the diversified classifications of the verbs that enter into them because different scholars, though under different theoretical frameworks, classified the DC verbs on the basis of the lexical meanings of the verbs, which is a boundless category. It is not difficult to find that all the constituents of DC and the construction as a whole interact with each other after the comparison of the similarities between CDC and EDC; the lexical meanings of the verbs that enter into DC do not exist in isolation but interact with the construction sense. Therefore, it may be the best choice to reclassify the DC verbs on the basis of the interaction between the lexical meaning of the verbs and the construction sense.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could ra...As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.展开更多
Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective metho...Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
目的 根据听力损失程度对全聋型突发性聋患者临床再分型,分析全聋型突发性聋患者的临床特征及预后。方法 选取解放军总医院第六医学中心耳鼻咽喉头颈外科医学部耳鼻咽喉内科住院治疗的全聋型突发性聋患者共计928例,依据治疗前患者的纯...目的 根据听力损失程度对全聋型突发性聋患者临床再分型,分析全聋型突发性聋患者的临床特征及预后。方法 选取解放军总医院第六医学中心耳鼻咽喉头颈外科医学部耳鼻咽喉内科住院治疗的全聋型突发性聋患者共计928例,依据治疗前患者的纯音听阈将患者分为1组(80~<95 dB HL)、2组(95~<110 dB HL)和3组(≥110 dB HL),运用非参数秩检验、分层卡方、多因素logistic回归和趋势性检验等方法比较3组全聋型突发性聋患者的临床特征与疗效。结果 (1)临床特征方面:3组全聋型患者的发病到治疗时间(P=0.002)、眩晕发生率(P<0.001)、糖尿病发生率(P=0.012)以及年龄(P=0.014)、发病侧别(P=0.019)均存在差异;而性别(P=0.469)、伴发耳鸣(P=0.099)、耳闷(P=0.098)、高血压(P=0.906)及诱因(P=0.102)无明显差异。(2)听力转归方面:3组全聋型患者在听力治疗的总有效率方面存在差异(P<0.001)。在发病14 d内(P<0.001)和14~40 d(P=0.041)接受治疗的3组全聋型突发性聋患者听力转归存在差异,发病40~180 d(P=0.110)接受治疗的全聋型突发性聋患者的疗效无明显差异。3组全聋型突发性聋患者在低频(P=0.003)、中频(P=0.002)和高频(P=0.013)的听力转归均存在差异。(3)言语识别率方面:言语识别数据完整的294例全聋型突发性聋患者治疗30 d的言语识别率有效率约为36.7%,180 d内的言语识别率有效率约为39.1%。3组患者在治疗后30 d和治疗后180 d的言语识别率疗效存在明显差异(P<0.001)。(4)听力转归影响因素:共计4个因素与患者预后相关,分别为病程(OR=0.95)、年龄(OR=0.99)、听力损失≥110 dB HL(OR=0.67,以80~95 dB HL的患者为参照)和性别(OR=1.40,男性为参照)。结论 不同程度的全聋型突发性聋患者在临床特征、听力转归和言语识别率的治疗有效率方面均存在差异,对全聋型突发性聋患者进行再分型研究有助于提高突发性聋分型诊治的有效率。展开更多
An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning secur...An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning security tags to subjects and objects is greatly simplified.The interoperation among different departments is implemented through assigning multiple security tags to one post, and the more departments are closed on the organization tree,the more secret objects can be exchanged by the staff of the departments.The access control matrices of the department,post and staff are defined.By using the three access control matrices,a multi granularity and flexible discretionary access control policy is implemented.The outstanding merit of the BLP model is inherited,and the new model can guarantee that all the information flow is under control.Finally,our study shows that compared to the BLP model,the proposed model is more flexible.展开更多
Salient object detection(SOD)models struggle to simultaneously preserve global structure,maintain sharp object boundaries,and sustain computational efficiency in complex scenes.In this study,we propose SPSALNet,a task...Salient object detection(SOD)models struggle to simultaneously preserve global structure,maintain sharp object boundaries,and sustain computational efficiency in complex scenes.In this study,we propose SPSALNet,a task-driven two-stage(macro–micro)architecture that restructures the SOD process around superpixel representations.In the proposed approach,a“split-and-enhance”principle,introduced to our knowledge for the first time in the SOD literature,hierarchically classifies superpixels and then applies targeted refinement only to ambiguous or error-prone regions.At the macro stage,the image is partitioned into content-adaptive superpixel regions,and each superpixel is represented by a high-dimensional region-level feature vector.These representations define a regional decomposition problem in which superpixels are assigned to three classes:background,object interior,and transition regions.Superpixel tokens interact with a global feature vector from a deep network backbone through a cross-attention module and are projected into an enriched embedding space that jointly encodes local topology and global context.At the micro stage,the model employs a U-Net-based refinement process that allocates computational resources only to ambiguous transition regions.The image and distance–similarity maps derived from superpixels are processed through a dual-encoder pathway.Subsequently,channel-aware fusion blocks adaptively combine information from these two sources,producing sharper and more stable object boundaries.Experimental results show that SPSALNet achieves high accuracy with lower computational cost compared to recent competing methods.On the PASCAL-S and DUT-OMRON datasets,SPSALNet exhibits a clear performance advantage across all key metrics,and it ranks first on accuracy-oriented measures on HKU-IS.On the challenging DUT-OMRON benchmark,SPSALNet reaches a MAE of 0.034.Across all datasets,it preserves object boundaries and regional structure in a stable and competitive manner.展开更多
Inspections of power transmission lines(PTLs)conducted using unmanned aerial vehicles(UAVs)are complicated by the fine structure of the lines and complex backgrounds,making accurate and efficient segmentation challeng...Inspections of power transmission lines(PTLs)conducted using unmanned aerial vehicles(UAVs)are complicated by the fine structure of the lines and complex backgrounds,making accurate and efficient segmentation challenging.This study presents the Wavelet-Guided Transformer U-Net(WGT-UNet)model,a new hybrid net-work that combines Convolutional Neural Networks(CNNs),Discrete Wavelet Transform(DWT),and Transformer architectures.The model’s primary contribution is based on spatial and channel attention mechanisms derived from wavelet subbands to guide the Transformer’s self-attention structure.Thus,low and high frequency components are separated at each stage using DWT,suppressing structural noise and making linear objects more prominent.The developed design is supported by multi-component hybrid cost functions that simultaneously solve class imbalance,edge sharpness,structural integrity,and spatial regularity issues.Furthermore,high segmentation success has been achieved in producing sharp boundaries and continuous line structures with the DWT-guided attention mechanism.Experiments conducted on the TTPLA dataset reveal that the version using the ConvNeXt backbone outperforms the current state-of-the-art approaches with an F1-Score of 79.33%and an Intersection over Union(IoU)value of 68.38%.The models and visual outputs of the developed method and all compared models can be accessed at https://github.com/burhanbarakli/WGT-UNET.展开更多
为明确蔓荆子的基原演变过程及分类学变迁,同时为其药材质量控制与临床合理应用提供科学依据,系统梳理历代本草文献记载,并结合现代分子系统学证据开展考证。结果表明,南北朝以前蔓荆子与牡荆子存在混用情况;唐代《新修本草》首次将单...为明确蔓荆子的基原演变过程及分类学变迁,同时为其药材质量控制与临床合理应用提供科学依据,系统梳理历代本草文献记载,并结合现代分子系统学证据开展考证。结果表明,南北朝以前蔓荆子与牡荆子存在混用情况;唐代《新修本草》首次将单叶蔓荆(Vitex trifolia L. var. simplicifolia Cham.)确立为蔓荆子基原;明代《本草纲目》进一步明确蔓荆(Vitex trifolia L.)为另一基原,且APG IV系统将牡荆属归入唇形科的修订结论,得到bootstrap支持率> 85%的分子数据及相关化学特征的双重佐证。理清了蔓荆子的历史沿革、形态特征、产地及功效的演变脉络,明确了其基原与分类学变迁规律,为其资源开发与合理利用提供了理论支撑。展开更多
This study explores the motivations,perceived benefits,and challenges associated with the adoption of clearcutfree forestry by early adopters among non-industrial private forest(NIPF)owners in southern-central Sweden....This study explores the motivations,perceived benefits,and challenges associated with the adoption of clearcutfree forestry by early adopters among non-industrial private forest(NIPF)owners in southern-central Sweden.Clearcut-free forestry,characterized by continuous tree cover and an emphasis on biodiversity,structural diversity,and ecosystem services(ES),is increasingly seen as a sustainable alternative to conventional intensive management based on short rotations and clear-cutting practices.Based on qualitative interviews with 22 NIPF owners who have adopted this approach,the study provides insights into how these early adopters perceive the value of clearcut-free forestry.Reported motivations include environmental concerns,such as biodiversity conservation and climate resilience,as well as strong socio-cultural values linked to family traditions,aesthetic preferences,and community wellbeing.In this study,we use the multi-level perspective(MLP)framework to conceptualize NIPF owners who have adopted clearcut-free forestry as niche actors and analyze their potential contribution to the emergence of an alternative forest management regime.The findings highlight that early adopters associate multiple benefits with clearcut-free forestry,encompassing enhanced ecosystem services such as carbon sequestration,water regulation,habitat preservation,and socio-cultural enrichment through recreation and relational values.However,the interviewees identify several interrelated challenges,including knowledge gaps,lack of clear definitions and standardized practices,limited advisory services,underdeveloped value chains for high-quality timber,and market barriers,which hinder more widespread adoption.Within the multi-level perspective,owner perceptions linking clearcut-free management with improved forest multifunctionality serve as a key driver of niche-level experimentation.This suggests an alignment between these owners and evolving societal demands for more inclusive,sustainable,and diversified forest use.Policy recommendations include targeted investments in knowledge co-production,infrastructure,market incentives,and certification schemes to support the economic viability and broader adoption of clearcut-free forestry.展开更多
An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation tran...An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation translation and scaling are the intrinsic properties of the MIAFs.For each contour point the multi-level included angles are obtained based on the paired line segments derived from unequal-arc-length partitions of contour.And a Fourier descriptor derived from multi-level included angle functions MIAFD is presented for efficient shape retrieval.The proposed descriptor is evaluated with the standard performance evaluation method on three shape image databases the MPEG-7 database the Kimia-99 database and the Swedish leaf database. The experimental results of shape retrieval indicate that the MIAFD outperforms the existing Fourier descriptors and has low computational complexity.And the comparison of the MIAFD with other shape description methods also shows that the proposed descriptor has the highest precision at the same recall value which verifies its effectiveness.展开更多
The multi-level ditch system developed in the Sanjiang Plain,Northeast China has sped up water drainage process hence transferred more pollutants from farmlands into the rivers of this region.Understanding the seasona...The multi-level ditch system developed in the Sanjiang Plain,Northeast China has sped up water drainage process hence transferred more pollutants from farmlands into the rivers of this region.Understanding the seasonal dynamics of nitrogen (N) and phosphorus (P) transportation in the ditch system and the role of different ditch size is thus crucial for water pollution control of the rivers in the Sanjiang Plain.In this study,an investigation was conducted in the Nongjiang watershed of the Sanjiang Plain to study the nutrient variation and the correlation between water and sediments in the ditch system in terms of ditch level.Water and sediments samples were collected in each ditch level in growing season at regular intervals (once per month),and TN,NO 3--N,NH 4+-N,TP,and PO 4 3--P were analyzed.The results show that nutrient contents in water were higher in June and July,especially in July,the contents of TN and TP were 3.21mg/L and 0.84mg/L in field ditch,4.04mg/L and 1.06mg/L in lateral ditch,2.46mg/L and 0.70mg/L in branch ditch,1.92mg/L and 0.63mg/L in main ditch,respectively.In August and September,the nutrient contents in the water were relatively lower.The peak value of nutrient in ditch water had been moving from the field ditch to the main ditch over time,showing a remarkable impact of ditch system on river water environment.The nutrient transfer in ditch sediments could only be found in rainfall season.Nutrient contents in ditch sediment had effect on that in ditch water,but nutrients in ditch water and sediments had different origination.Ditch management in terms of the key fac-tors is hence very important for protecting river water environment.展开更多
基金supported by the National Natural Science Foundation of China(No.52090041).
文摘The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.
基金the Beijing Natural Science Foundation (5052013)the Program of the Excellent Young Scientists of the Ministry of Land Resources(2005)
文摘The generic classification of the family Orthophlebiidae is revised systematically in the present paper. Genera Orthophlebia and Protophlebia are remained in the family Orthophlebiidae while genus Mesophlebia is disassembled, in which the species are ascribed to Orthophlebia if Rs1 at least with 3 branches, and to Protophlebia if Rs1 only with 2 branches. Three subgenera are erected in Orthophlebia and Protophlebia respectively according to the relationship between stems of Rs and MA, i.e. Rs forking earlier or later than MA, or at the same level as MA.
文摘AIM To evaluate the role of small bowel capsule endoscopy(SBCE)on the reclassification of colonic inflammatory bowel disease type unclassified(IBDU).METHODS We performed a multicenter,retrospective study including patients with IBDU undergoing SBCE,between 2002 and 2014.SBCE studies were reviewed and the inflammatory activity was evaluated by determining the Lewis score(LS).Inflammatory activity was considered significant and consistent with Crohn's disease(CD)when the LS≥135.The definitive diagnosis during follow-up(minimum 12 mo following SBCE)was based on the combination of clinical,analytical,imaging,endoscopic and histological elements.RESULTS Thirty-six patients were included,21 females(58%)with mean age at diagnosis of 33±13(15-64)years.The mean follow-up time after the SBCE was 52±41(12-156)mo.The SBCE revealed findings consistent with significant inflammatory activity in the small bowel(LS≥135)in 9 patients(25%);in all of them the diagnosis of CD was confirmed during follow-up.In 27 patients(75%),the SBCE revealed no significant inflammatory activity(LS<135);among these patients,the diagnosis of Ulcerative Colitis(UC)was established in 16 cases(59.3%),CD in 1 case(3.7%)and 10 patients(37%)maintained a diagnosis of IBDU during follow-up.A LS≥135 at SBCE had a sensitivity=90%,specificity=100%,positive predictive value=100%and negative predictive value=94%for the diagnosis of CD.CONCLUSION SBCE proved to be fundamental in the reclassification of patients with IBDU.Absence of significant inflammatory activity in the small intestine allowed exclusion of CD in 94%of cases.
文摘This review revises the reclassification of the mem-branoproliferative glomerulonephritis （MPGN） after the consensus conference that by 2015 reclassified all the glomerulonephritis basing on etiology and patho-genesis, instead of the histomorphological aspects. After reclassification, two types of MPGN are to date recognized： The immunocomplexes mediated MPGN and the complement mediated MPGN. The latter type is more extensively described in the review either because several of these entities are completely new or because the improved knowledge of the complement cascade allowed for new diagnostic and therapeutic approaches. Overall the complement mediated MPGN are related to acquired or genetic cause. The presence of circulating auto antibodies is the principal acquired cause. Genetic wide association studies and family studies allowed to recognize genetic mutations of different types as causes of the complement dysregulation. The complement cascade is a complex phenomenon and activating factors and regulating factors should be distinguished. Genetic mutations causing abnormalities either in activating or in regulating factors have been described. The diagnosis of the complement mediated MPGN requires a complete study of all these different complement factors. As a consequence, new therapeutic approaches are becoming available. Indeed, in addition to a nonspecifc treatment and to the immunosuppression that has the aim to block the auto antibodies production, the specific inhibition of complement activation is relatively new and may act either blocking the C5 convertase or the C3 convertase. The drugs acting on C3 convertase are still in different phases of clinical development and might represent drugs for the future. Overall the authors consider that one of the principal problems in fnding new types of drugs are both the rarity of the disease and the consequent poor interest in the marketing and the lack of large international cooperative studies.
文摘Although Chinese Ditransitive Construction(CDC) and English Ditransitive Construction(EDC) respectively belong to two completely different languages, there do exist many similarities between them. One of the similarities is the diversified classifications of the verbs that enter into them because different scholars, though under different theoretical frameworks, classified the DC verbs on the basis of the lexical meanings of the verbs, which is a boundless category. It is not difficult to find that all the constituents of DC and the construction as a whole interact with each other after the comparison of the similarities between CDC and EDC; the lexical meanings of the verbs that enter into DC do not exist in isolation but interact with the construction sense. Therefore, it may be the best choice to reclassify the DC verbs on the basis of the interaction between the lexical meaning of the verbs and the construction sense.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
基金co-supported by the National Key Research and Development Program of China(No.2022YFF0503100)the Youth Innovation Project of Pandeng Program of National Space Science Center,Chinese Academy of Sciences(No.E3PD40012S).
文摘As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.
基金supported by the Fund of Key Laboratory of Biomedical Engineering of Hainan Province(No.BME20240001)the STI2030-Major Projects(No.2021ZD0200104)the National Natural Science Foundations of China under Grant 61771437.
文摘Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
文摘目的 根据听力损失程度对全聋型突发性聋患者临床再分型,分析全聋型突发性聋患者的临床特征及预后。方法 选取解放军总医院第六医学中心耳鼻咽喉头颈外科医学部耳鼻咽喉内科住院治疗的全聋型突发性聋患者共计928例,依据治疗前患者的纯音听阈将患者分为1组(80~<95 dB HL)、2组(95~<110 dB HL)和3组(≥110 dB HL),运用非参数秩检验、分层卡方、多因素logistic回归和趋势性检验等方法比较3组全聋型突发性聋患者的临床特征与疗效。结果 (1)临床特征方面:3组全聋型患者的发病到治疗时间(P=0.002)、眩晕发生率(P<0.001)、糖尿病发生率(P=0.012)以及年龄(P=0.014)、发病侧别(P=0.019)均存在差异;而性别(P=0.469)、伴发耳鸣(P=0.099)、耳闷(P=0.098)、高血压(P=0.906)及诱因(P=0.102)无明显差异。(2)听力转归方面:3组全聋型患者在听力治疗的总有效率方面存在差异(P<0.001)。在发病14 d内(P<0.001)和14~40 d(P=0.041)接受治疗的3组全聋型突发性聋患者听力转归存在差异,发病40~180 d(P=0.110)接受治疗的全聋型突发性聋患者的疗效无明显差异。3组全聋型突发性聋患者在低频(P=0.003)、中频(P=0.002)和高频(P=0.013)的听力转归均存在差异。(3)言语识别率方面:言语识别数据完整的294例全聋型突发性聋患者治疗30 d的言语识别率有效率约为36.7%,180 d内的言语识别率有效率约为39.1%。3组患者在治疗后30 d和治疗后180 d的言语识别率疗效存在明显差异(P<0.001)。(4)听力转归影响因素:共计4个因素与患者预后相关,分别为病程(OR=0.95)、年龄(OR=0.99)、听力损失≥110 dB HL(OR=0.67,以80~95 dB HL的患者为参照)和性别(OR=1.40,男性为参照)。结论 不同程度的全聋型突发性聋患者在临床特征、听力转归和言语识别率的治疗有效率方面均存在差异,对全聋型突发性聋患者进行再分型研究有助于提高突发性聋分型诊治的有效率。
基金The National Natural Science Foundation of China(No.60403027,60773191,70771043)the National High Technology Research and Development Program of China(863 Program)(No.2007AA01Z403)
文摘An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning security tags to subjects and objects is greatly simplified.The interoperation among different departments is implemented through assigning multiple security tags to one post, and the more departments are closed on the organization tree,the more secret objects can be exchanged by the staff of the departments.The access control matrices of the department,post and staff are defined.By using the three access control matrices,a multi granularity and flexible discretionary access control policy is implemented.The outstanding merit of the BLP model is inherited,and the new model can guarantee that all the information flow is under control.Finally,our study shows that compared to the BLP model,the proposed model is more flexible.
文摘Salient object detection(SOD)models struggle to simultaneously preserve global structure,maintain sharp object boundaries,and sustain computational efficiency in complex scenes.In this study,we propose SPSALNet,a task-driven two-stage(macro–micro)architecture that restructures the SOD process around superpixel representations.In the proposed approach,a“split-and-enhance”principle,introduced to our knowledge for the first time in the SOD literature,hierarchically classifies superpixels and then applies targeted refinement only to ambiguous or error-prone regions.At the macro stage,the image is partitioned into content-adaptive superpixel regions,and each superpixel is represented by a high-dimensional region-level feature vector.These representations define a regional decomposition problem in which superpixels are assigned to three classes:background,object interior,and transition regions.Superpixel tokens interact with a global feature vector from a deep network backbone through a cross-attention module and are projected into an enriched embedding space that jointly encodes local topology and global context.At the micro stage,the model employs a U-Net-based refinement process that allocates computational resources only to ambiguous transition regions.The image and distance–similarity maps derived from superpixels are processed through a dual-encoder pathway.Subsequently,channel-aware fusion blocks adaptively combine information from these two sources,producing sharper and more stable object boundaries.Experimental results show that SPSALNet achieves high accuracy with lower computational cost compared to recent competing methods.On the PASCAL-S and DUT-OMRON datasets,SPSALNet exhibits a clear performance advantage across all key metrics,and it ranks first on accuracy-oriented measures on HKU-IS.On the challenging DUT-OMRON benchmark,SPSALNet reaches a MAE of 0.034.Across all datasets,it preserves object boundaries and regional structure in a stable and competitive manner.
文摘Inspections of power transmission lines(PTLs)conducted using unmanned aerial vehicles(UAVs)are complicated by the fine structure of the lines and complex backgrounds,making accurate and efficient segmentation challenging.This study presents the Wavelet-Guided Transformer U-Net(WGT-UNet)model,a new hybrid net-work that combines Convolutional Neural Networks(CNNs),Discrete Wavelet Transform(DWT),and Transformer architectures.The model’s primary contribution is based on spatial and channel attention mechanisms derived from wavelet subbands to guide the Transformer’s self-attention structure.Thus,low and high frequency components are separated at each stage using DWT,suppressing structural noise and making linear objects more prominent.The developed design is supported by multi-component hybrid cost functions that simultaneously solve class imbalance,edge sharpness,structural integrity,and spatial regularity issues.Furthermore,high segmentation success has been achieved in producing sharp boundaries and continuous line structures with the DWT-guided attention mechanism.Experiments conducted on the TTPLA dataset reveal that the version using the ConvNeXt backbone outperforms the current state-of-the-art approaches with an F1-Score of 79.33%and an Intersection over Union(IoU)value of 68.38%.The models and visual outputs of the developed method and all compared models can be accessed at https://github.com/burhanbarakli/WGT-UNET.
文摘为明确蔓荆子的基原演变过程及分类学变迁,同时为其药材质量控制与临床合理应用提供科学依据,系统梳理历代本草文献记载,并结合现代分子系统学证据开展考证。结果表明,南北朝以前蔓荆子与牡荆子存在混用情况;唐代《新修本草》首次将单叶蔓荆(Vitex trifolia L. var. simplicifolia Cham.)确立为蔓荆子基原;明代《本草纲目》进一步明确蔓荆(Vitex trifolia L.)为另一基原,且APG IV系统将牡荆属归入唇形科的修订结论,得到bootstrap支持率> 85%的分子数据及相关化学特征的双重佐证。理清了蔓荆子的历史沿革、形态特征、产地及功效的演变脉络,明确了其基原与分类学变迁规律,为其资源开发与合理利用提供了理论支撑。
基金financed by a grant from Mistra[DIA 2019/28]and from Formas via the National Research Programme on Climate(2021–00416)FORMAS,Grant Nos.2022-02146 and 2021–01067Swedish Environmental Protection Agency Research Grant No.2021–00040。
文摘This study explores the motivations,perceived benefits,and challenges associated with the adoption of clearcutfree forestry by early adopters among non-industrial private forest(NIPF)owners in southern-central Sweden.Clearcut-free forestry,characterized by continuous tree cover and an emphasis on biodiversity,structural diversity,and ecosystem services(ES),is increasingly seen as a sustainable alternative to conventional intensive management based on short rotations and clear-cutting practices.Based on qualitative interviews with 22 NIPF owners who have adopted this approach,the study provides insights into how these early adopters perceive the value of clearcut-free forestry.Reported motivations include environmental concerns,such as biodiversity conservation and climate resilience,as well as strong socio-cultural values linked to family traditions,aesthetic preferences,and community wellbeing.In this study,we use the multi-level perspective(MLP)framework to conceptualize NIPF owners who have adopted clearcut-free forestry as niche actors and analyze their potential contribution to the emergence of an alternative forest management regime.The findings highlight that early adopters associate multiple benefits with clearcut-free forestry,encompassing enhanced ecosystem services such as carbon sequestration,water regulation,habitat preservation,and socio-cultural enrichment through recreation and relational values.However,the interviewees identify several interrelated challenges,including knowledge gaps,lack of clear definitions and standardized practices,limited advisory services,underdeveloped value chains for high-quality timber,and market barriers,which hinder more widespread adoption.Within the multi-level perspective,owner perceptions linking clearcut-free management with improved forest multifunctionality serve as a key driver of niche-level experimentation.This suggests an alignment between these owners and evolving societal demands for more inclusive,sustainable,and diversified forest use.Policy recommendations include targeted investments in knowledge co-production,infrastructure,market incentives,and certification schemes to support the economic viability and broader adoption of clearcut-free forestry.
基金The National Natural Science Foundation of China(No.61170116,61375010,60973064)
文摘An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation translation and scaling are the intrinsic properties of the MIAFs.For each contour point the multi-level included angles are obtained based on the paired line segments derived from unequal-arc-length partitions of contour.And a Fourier descriptor derived from multi-level included angle functions MIAFD is presented for efficient shape retrieval.The proposed descriptor is evaluated with the standard performance evaluation method on three shape image databases the MPEG-7 database the Kimia-99 database and the Swedish leaf database. The experimental results of shape retrieval indicate that the MIAFD outperforms the existing Fourier descriptors and has low computational complexity.And the comparison of the MIAFD with other shape description methods also shows that the proposed descriptor has the highest precision at the same recall value which verifies its effectiveness.
基金Under the auspices of Major State Basic Research Development Program of China (No.2007CB407307)National Key Technology Research and Development Program of China (No.2006BAC15B01)National Natural Science Foundation of China (No. 40671182)
文摘The multi-level ditch system developed in the Sanjiang Plain,Northeast China has sped up water drainage process hence transferred more pollutants from farmlands into the rivers of this region.Understanding the seasonal dynamics of nitrogen (N) and phosphorus (P) transportation in the ditch system and the role of different ditch size is thus crucial for water pollution control of the rivers in the Sanjiang Plain.In this study,an investigation was conducted in the Nongjiang watershed of the Sanjiang Plain to study the nutrient variation and the correlation between water and sediments in the ditch system in terms of ditch level.Water and sediments samples were collected in each ditch level in growing season at regular intervals (once per month),and TN,NO 3--N,NH 4+-N,TP,and PO 4 3--P were analyzed.The results show that nutrient contents in water were higher in June and July,especially in July,the contents of TN and TP were 3.21mg/L and 0.84mg/L in field ditch,4.04mg/L and 1.06mg/L in lateral ditch,2.46mg/L and 0.70mg/L in branch ditch,1.92mg/L and 0.63mg/L in main ditch,respectively.In August and September,the nutrient contents in the water were relatively lower.The peak value of nutrient in ditch water had been moving from the field ditch to the main ditch over time,showing a remarkable impact of ditch system on river water environment.The nutrient transfer in ditch sediments could only be found in rainfall season.Nutrient contents in ditch sediment had effect on that in ditch water,but nutrients in ditch water and sediments had different origination.Ditch management in terms of the key fac-tors is hence very important for protecting river water environment.
