数字出版供应链下区块链投资与版权保护策略

区块链技术的可追溯性、安全性以及不可篡改性可以解决数字内容产品的盗版问题。以此为背景,构建由出版商、销售平台以及消费者构成的数字出版供应链,探讨在传统版权保护和区块链下的版权保护两种版权保护模式中的出版商最优定价和平台最优版权保护强度的决策问题,并比较了供应链绩效。研究发现,区块链下的版权保护模式中平台实施严格的版权保护强度,进而提高正版产品的吸引力,需求上升弥补了传统版权保护下出版商通过降价提高需求造成的利润损失。但是,平台只有在区块链投资成本较低时才愿意投资区块链,无法实现供应链的收益最大化。针对这一问题,通过设计契约提高了平台投资区块链的动机。最后,研究了平台投资区块链对购买正版产品消费者的消费者剩余以及社会福利,发现投资区块链可以提高社会福利,但在一定程度上会损害正版产品的消费者剩余。

Studies on Ecological Monitoring of Plant Community and Plant Diversity in Shenzhen, Southern China

From Jan. 2013 to Nov. 2018, we carried out the investigation on vegetation studies in the ecological monitoring programs, Shenzhen and totally researched 170 plant communities of mountain areas etc., few areas of street regions and parks etc., for communities’ structural characteristics and plant diversity. We comparatively analyzed natural forests, semi-natural forest and artificial forest composition and structural characters and family, genus and species diversity level and the main affected factors. We also researched and analyzed these communities’ structural characteristics and pant diversity, comparatively analyzed natural forests, semi-natural forest and artificial forest composition and structural characters and family, genus and species diversity level, the main affected factors;researched and analyzed the relationship between plant community structure characteristics with the absorbing ability to PM2.5 pollutants. The result showed that the structure and plant diversity of natural forest were obviously better than artificial disturbed forest or artificial forest, the semi-natural forest was the middle level of the forests, In the indices of height, DBH, coverage and crow width etc. of tree layer, natural forests and semi-natural forests were obvious higher than that of artificial disturbed forest or artificial forest;in some forests of artificial disturbed forest or artificial forest, though their richness indices of family and genus were a slightly higher, but this contribution was majorly due to herb layer plants, and some shrub layer plants. Analyzing three kinds of communities, the number of tree layer species of natural forest was the largest, and their every α-diversity index value was the highest;these characteristics values of semi-natural forest were second, artificial disturbed forests or artificial forests were the lowest;in shrub layer, and herb layer, few α-diversity indices of artificial disturbed forest or artificial forest were a slightly higher than that of some natural forests, but the integral values of the diversity indices of natural forest and semi-natural forest were obviously higher than the former. The research showed that in the artificial disturbed forest or artificial forest, because there have some little scale clearing areas, so some pioneer plant species could enter the community and formed a temporarily increase of species diversity, however, these species major were some shrub and herb plants;but tree layer possessed obviously more, even surpassed several ten times biomass than shrub and herb layers. Therefore, the respects of maintain ecosystem stability and other ecological efficient have major and dominated position and so on;and then this community can be natural recovery and succession, those forementioned new entire plants shall withdraw from the community and are replaced by the original plants of the community;but this process has already caused the ecological efficient loss and ecosystem unstable. Above research results are better evidence and theory reference to the argument problems on that are natural forest and natural restoration forest biodiversity higher? or is artificial forest biodiversity higher? and or is more artificial disturbed forest higher? Our researches showed that used random investigation method set quadrats, and combined typical investigation method, the structural indices in the all layer of community and all diversity indices of tree, shrub and herb layers and the integral values were similar, same or usually these indices in the community which set 600 m2, 800 m2 total quatrat area were higher (α-diversity) than that of more than 3000 m2, 4000 m2 or 7000 m2, even more than 17,000 m2 total quadrat area of communities. These lots of researches further proved that according to minimum area method for vegetation survey, in subtropical region, using random investigation method combined with typical investigation set 400 m2 or 400 m2 - 500 m2 total quad

Notum protects against myocardial infarction-induced heart dysfunction by alleviating cardiac fibrosis

Background and Objective:Cardiac fibrosis is a pathological reparative process that follows myocardial infarctionand is associated with compromised cardiac systolic and reduced cardiac compliance.The Wnt signaling pathway is closely implicated in organ fibrosis,and Notum,a highly conserved secreted inhibitor,modulates Wnt signaling.The objective of this study was to explore the role and mechanism of Notum in cardiac fibrosis.Methods:A mouse model of cardiac remodeling was established through left coronary artery ligation surgery,with the addition of Notum injection following myocardial infarction surgery.The protective effect of Notum on myocardial infarction was assessed by evaluating cardiac function,including survival rate,echocardiographic assessment,and cardiac contraction analyses.Inflammatory cell necrosis and infiltration were confirmed through H&E and Masson staining.The expression of fibrosis-related genes andβ-catenin pathway markers was detected using Western blot quantificational RT-PCR(qRT-PCR).Additionally,EdU,wound healing,and immunofluorescence staining analyses were performed to detect the effect of Notum's in transforming growth factor beta-1(TGF-β1)induced myofibroblast transformation.Results:The administration of Notum treatment resulted in enhanced survival rates,improved cardiac function,and decreased necrosis and infiltration of inflammatory cells in mice subjected to left coronary artery ligation.Furthermore,Notum effectively impeded the senescence of cardiac fibroblasts and hindered their pathological transformation into cardiac fibroblasts.Additionally,it significantly reduced collagen production and attenuated the activation of the Wnt/β-catenin pathway.Our preliminary investigations successfully demonstrated the therapeutic potential of Notum in both fibroblasts in vitro and in a mouse model of myocardial infarction-induced cardiac fibrosis in vivo.Conclusion:Notum inhibition of the Wnt/β-catenin signaling pathway and cardiac fibroblast senescence ultimately hampers the onset of cardiac fibrosis.Our findings suggest that Notum could represent a new therapeutic strategy for the treatment of cardiac fibrosis.

Viscosity reduction of tapioca starch by incorporating with molasses hydrocolloids

As a low cost non-staple food resource,the high-viscosity paste and poor gel-forming ability of tapioca starch limit its industrial application.Herein,molasses hydrocolloids that is a by-product of the sugar refining process was applied as a blending modifier to reduce the viscosity of tapioca starch paste.The test results of paste and rheological properties show that molasses hydrocolloids exhibited a good physical viscosity-reducing effect on tapioca starch paste.The irregular network structure and high K^(+)/Ca^(2+)ion contents of molasses hydrocolloids exerted wrapping,adhesion,barrier,and hydration effects on starch,leading to the reduction of viscosity.The scanning electron microscope images and textural analysis demonstrated that this strategy also improve the structure of tapioca starch gel and enhanced its puncture strength by 75.46%.This work shows the great potential of molasses hydrocolloids as a lowcost and desirable material for the viscosity reduction of tapioca starch.

Multi-Scale Feature Extraction for Joint Classification of Hyperspectral and LiDAR Data

With the development of sensors,the application of multi-source remote sensing data has been widely concerned.Since hyperspectral image(HSI)contains rich spectral information while light detection and ranging(LiDAR)data contains elevation information,joint use of them for ground object classification can yield positive results,especially by building deep networks.Fortu-nately,multi-scale deep networks allow to expand the receptive fields of convolution without causing the computational and training problems associated with simply adding more network layers.In this work,a multi-scale feature fusion network is proposed for the joint classification of HSI and LiDAR data.First,we design a multi-scale spatial feature extraction module with cross-channel connections,by which spatial information of HSI data and elevation information of LiDAR data are extracted and fused.In addition,a multi-scale spectral feature extraction module is employed to extract the multi-scale spectral features of HSI data.Finally,joint multi-scale features are obtained by weighting and concatenation operations and then fed into the classifier.To verify the effective-ness of the proposed network,experiments are carried out on the MUUFL Gulfport and Trento datasets.The experimental results demonstrate that the classification performance of the proposed method is superior to that of other state-of-the-art methods.

面向资金约束供应商的供应链内部融资--股权还是债权?

通过制造商向供应商提供投资或借款,可以减少由于供应商资金不足无法正常组织生产引起的制造商及供应链利润的损失,分析了股权和债权两种融资模式下制造商的最优融资与供应商的最优生产决策,并比较了供应链绩效.结论表明:供应商一定会接受债权融资,但只有在一定条件下才会接受股权融资;在股权融资模式下,要将资金约束供应商的生产恢复到无资金约束下的最优水平,需要供应商的初始资金低于一定的临界值且制造商分享供应商的利润份额超过一定的临界值;在债权融资模式下,要将资金约束供应商的生产恢复到无资金约束下的最优水平,则需要供应商的初始资金超过一定的临界值;从制造商和供应链整体的视角,在供应商自有资金少时实行股权融资模式,并且增加制造商分享的利润份额,而在供应商自有资金多时实行债权融资模式是最优策略.最后通过算例对结论进行了验证.

竞争环境下新创企业的供应链管理模式选择——应急采购VS饥饿营销

考虑需求不确定下,新创企业和在位企业两条异质供应链竞争对供需匹配策略的影响,运用Bertrand模型比较新创企业供应链实施应急采购和饥饿营销两种策略下的均衡价格和均衡销量,以及供应链的期望利润随市场基本需求和产品替代系数的变化情况。研究发现,当实现的需求不确定性小时,饥饿营销策略下需求响应时间不会影响新创企业供应链的均衡价格和均衡销量;而当实现的需求不确定性大时,实施饥饿营销策略的新创企业供应链里零售商的最优定价会高于应急采购策略的均衡价格,而最终的销量会低于应急采购策略的均衡销量。即使应急采购的额外成本为零,新创企业供应链的期望利润在实施了饥饿营销策略之后,也会比应急采购策略下的期望利润大,并且期望利润的增加率随市场基本需求单调递增,随产品替代系数单调递减。这也意味着新创企业供应链可以有效实施饥饿营销策略。

基于SICAS模型的图书直播营销探究

数字经济时代,直播带货模式在很多行业都受到普遍关注,出版企业也开始探索直播售书这一营销模式。图书直播营销打破了时空限制,通过提供“一站式”购书服务为受众创造了合适的消费场景。本文首先阐释了SICAS模型应用于图书直播营销的价值,然后分析了图书直播营销现状并指出存在的问题,最后基于SICAS模型,从品牌营销、内容营销、关系营销、整合营销、社群营销五个方面提出有针对性的解决策略。

Semantic Constraint Based Unsupervised Domain Adaptation for Cardiac Segmentation

The segmentation of unlabeled medical images is troublesome due to the high cost of annotation, and unsupervised domain adaptation is one solution to this. In this paper, an improved unsupervised domain adaptation method was proposed. The proposed method considered both global alignment and category-wise alignment. First, we aligned the appearance of two domains by image transformation. Second, we aligned the output maps of two domains in a global way. Then, we decomposed the semantic prediction map by category, aligning the prediction maps in a category-wise manner. Finally, we evaluated the proposed method on the 2017 Multi-Modality Whole Heart Segmentation Challenge dataset, and obtained 82.1 on the dice similarity coefficient and 4.6 on the average symmetric surface distance, demonstrating the effectiveness of the combination of global alignment and category-wise alignment.

WADE-Net: Weighted Aggregation with Density Estimation for Point Cloud Place Recognition

Point cloud based place recognition plays an important role in mobile robotics. In this paper, we propose a weighted aggregation method from structure information adaptively for point cloud place recognition. Firstly, to preserve the prior distributions and local geometric structures, we fuse learned hidden features with handcrafted features in the beginning. Secondly, we further extract and aggregate adaptively weighted features concerning density and relative spatial information from these fused features, named Weighted Aggregation with Density Estimation (WADE) module. Then, we conduct the WADE block iteratively to group the latent manifold structures. Finally, comparison results on two public datasets Oxford Robotcar and KITTI show that the proposed approach exceeds the comparison approaches on recall rate averagely 7% - 8%.

区块链技术对供应链金融信用风险的影响--基于PSM-DID方法的实证分析

区块链技术作为一项极具颠覆性的新兴技术,为供应链金融风险控制提供了创新性解决方案。基于2017—2020年供应链金融上市公司面板数据,运用倾向得分匹配-双重差分法(PSM-DID)实证分析区块链技术的应用对供应链金融信用风险的影响。研究发现,区块链技术能够显著降低供应链金融信用风险。因此,各企业可积极引入区块链技术,利用区块链的技术优势解决信用风险难题。

Intraoperative ultrasonography in hepatobiliary surgery

Objective: To assess the value of intraoperative ultra- sonography in hepatobiliary surgery. Methods: Aloka-650 and Aloka-500 with a 3.5 MHz probe were used in preoperative uitrasonography and those with 5 MHz or 7.5 MHz probes in intraopera- tive ultrasonography. All patients with carcinoma were confirmed pathologically. Results: In 44 patients with liver cancer (76 tumors), the diagnostic rate of intraoperative ultra- sonography was 97% (74/76), which was markedly higher than 84% (64/76) of preoperative ultra- sonography (P<0.05). The diagnostic rate (92%; 22/24) of intraoperative ultrasonography for tumors ≤2 cm in diameter was markedly higher than that (54%; 13/24) of preoperative ultrasonography (P< 0.01). The diagnostic rate (94%; 16/17) of intra- operative ultrasonography for tumor embulus of the vein was also markedly higher than that (53%; 9/ 17) of preoperative ultrasonography (P<0.01). The diagnostic rates of intraoperative and preoperative ultrasonography for cholelithiasis were 99% (108/ 109) and 97% (106/109) respectively (P>0.05). Yet the diagnostic rate (100%; 12/12) of intraopera- tive ultrasonography for gallbladder carcinoma was markedly higher than that (66.7%; 8/12) of pre- operative ultrasonography (P<0.05). The diagnos- tic rates of intraoperative ultrasonography for chole- docholith and biliary tract cancer were all 100%, markedly higher than those (83%; 20/24 and 75%; 12/16) of preoperative ultrasonography (P<0.05). Conclusions: Intraoperative ultrasonography can raise the detective rate of the liver occupying lesions comparing with that of preoperative untrasonogra- phy. It is of valuable in selecting operative scheme and locating small lesions.

Graph-Based Dimensionality Reduction for Hyperspectral Imagery: A Review

Hyperspectral image(HSI)contains a wealth of spectral information,which makes fine classification of ground objects possible.In the meanwhile,overly redundant information in HSI brings many challenges.Specifically,the lack of training samples and the high computational cost are the inevitable obstacles in the design of classifier.In order to solve these problems,dimensionality reduction is usually adopted.Recently,graph-based dimensionality reduction has become a hot topic.In this paper,the graph-based methods for HSI dimensionality reduction are summarized from the following aspects.1)The traditional graph-based methods employ Euclidean distance to explore the local information of samples in spectral feature space.2)The dimensionality-reduction methods based on sparse or collaborative representation regard the sparse or collaborative coefficients as graph weights to effectively reduce reconstruction errors and represent most important information of HSI in the dictionary.3)Improved methods based on sparse or collaborative graph have made great progress by considering global low-rank information,local intra-class information and spatial information.In order to compare typical techniques,three real HSI datasets were used to carry out relevant experiments,and then the experimental results were analysed and discussed.Finally,the future development of this research field is prospected.

Meta-analysis on Treatment of Chronic Hepatitis B with Telbivudine and Entecavir

Objective To evaluate the therapeutic effects of telbivudine and entecavir on patients with chronic hepatitis B by meta-analysis method. Methods Databases including the Cochrane Library, PubMed, EMBASE and HighWire were searched from January 2008 to October 2012. Randomized controlled trials on treatment of chronic hepatitis B with telbivudine and entecavir were included. According to the Cochrane systematic reviews, the methodological quality of the included studies was evaluated and effective data was extracted from these studies and analyzed. Results Six studies were included eventually. The telbivudine group included 417 cases and the entecavir group included 396 cases. For 12-week antiviral treatment of chronic hepatitis B, the rate of undetectable HBV DNA was 39.1% with telbivudine and 38.6% with entecavir [OR = 1.04, 95% CI(0.62, 1.73), P > 0.05]; for treatment of HBeAg(+) hepatitis B, the HBeAg clearance rate was 23.8% with telbivudine and 3.8% with entecavir [OR= 8.07, 95% CI(2.69, 24.21), P < 0.05], and the HBeAg seroconversion rate was 6.7% with telbivudine and 3.8% with entecavir [OR = 4.95, 95% CI(1.60, 15.31), P < 0.05]; the ALT normalization rate was 54.3% with telbivudine and 58.5% with entecavir [OR = 0.84, 95% CI(0.49, 1.45), P > 0.05]; and for early-stage treatment, the incidence of adverse events was 17.2% with telbivudine and 22.0% with entecavir [OR = 0.66, 95% CI(0.33, 1.32), P > 0.05]. For 1-year antiviral treatment of chronic hepatitis B, the rate of undetectable HBV DNA was 79.4% with telbivudine and 89.7% with entecavir [OR = 0.46, 95% CI(0.28, 0.74), P < 0.05]; for treatment of HBeAg(+) hepatitis B, the HBeAg clearance rate was 28.9% with telbivudine and 15.6% with entecavir [OR = 2.21, 95% CI(1.06, 4.58), P < 0.05], and the HBeAg seroconversion rate was 31.2% with telbivudine and 18.5% with entecavir [OR = 2.31, 95% CI(1.23, 4.31), P < 0.05]; the ALT normalization rate was 85.8% with telbivudine and 84.9% with entecavir [OR = 0.90, 95% CI(0.29, 2.84), P > 0.05]; and the resistance rate was 6.0% with telbivudine and 0.76% with entecavir [OR = 5.71, 95% CI(1.67, 19.47), P < 0.05]. Conclusions For 1-year treatment of chronic hepatitis B, the difference in ALT normalization between telbivudine and entecavir was not statistically significant; and telbivudine was superior over entecavir in terms of HBeAg undetectable and HBeAg seroconversion; entecavir was superior over telbivudine in terms of HBV DNA undetectable and resistance; and both drugs had similar rates of adverse events in early-stage treatment and no severe adverse event was noted. Both telbivudine and entecavir are effective antiviral drugs against hepatitis B.

Coronary artery aneurysm combined with myocardial bridge:A case report

BACKGROUND Coronary artery aneurysm combined with myocardial bridge is a very rare clinical situation.The prognosis of this clinical situation is not yet clear.CASE SUMMARY A coronary artery aneurysm and myocardial bridge in the same segment of the coronary artery were found in a 54-year-old female patient who underwent coronary angiography and intravascular ultrasound examination.Through conservative treatment,the patient was discharged from the hospital smoothly,and she was in good condition during 5 mo of follow-up.CONCLUSION Coronary artery aneurysm combined with myocardial bridge seems to have a good prognosis,but due to the rarity of this clinical situation,further research and follow-up are needed.

Local Preserving Graphs Using Intra-Class Competitive Representation for Dimensionality Reduction of Hyperspectral Image

As a key technique in hyperspectral image pre-processing,dimensionality reduction has received a lot of attention.However,most of the graph-based dimensionality reduction methods only consider a single structure in the data and ignore the interfusion of multiple structures.In this paper,we propose two methods for combining intra-class competition for locally preserved graphs by constructing a new dictionary containing neighbourhood information.These two methods explore local information into the collaborative graph through competing constraints,thus effectively improving the overcrowded distribution of intra-class coefficients in the collaborative graph and enhancing the discriminative power of the algorithm.By classifying four benchmark hyperspectral data,the proposed methods are proved to be superior to several advanced algorithms,even under small-sample-size conditions.

Forest-Fire Recognition by Sparse and Collaborative Subspace Clustering

Traditional forest-fire recognition based on the characteristics of smoke, temperature and light fails to accurately detect and respond to early fires. By analyzing the characteristics of flame, the methods based on aerial image recognition have been widely used, such as RGB-based and HIS-based methods. However, these methods are susceptible to background factors causing interference and false detection. To alleviate these problems, we investigate two subspace clustering methods based on sparse and collaborative representation, respectively, to detect and locate forest fires. Firstly, subspace clustering segments flame from the whole image. Afterwards, sparse or collaborative representation is employed to represent most of the flame information in a dictionary with l1-regularization or l2-regularization term, which results in fewer reconstruction errors. Experimental results show that the proposed SSC and CSC substantially outperform the state-of-the art methods.

The Application of the Concept of"Nearly Natural"Plant Community in the Optimization of Coastal Ecological Space

The overexploitation of the natural environment caused by urbanization makes more and more natural and semi-natural plant communities gradually lack,which causes a lot of irreversible damage to the environment.Therefore,it is very important to carry out ecological environment construction in all fields of urban construction.In this paper,based on theory and method of plant landscape construction under the concept of"nearly natural"plant community,through the investigation and analysis on plant species,distribution,and structural characteristics of plant community in Baguang District of Shenzhen,regional native plant species are summarized,and structural characteristics of original zonal plant community are simulated.The research aims to provide a reference basis for creating a coastal plant landscape with subtropical marine climate for Baguang and even Lingnan,constructing near natural ecological park according to local conditions,forming the pattern well-coordinated with the local natural ecosystem,and carrying out protection of the regional ecological environment.

3D Distinct Element Back Analysis Based on Rock Structure Modelling of SfM Point Clouds:The Case of the 2019 Pinglu Rockfall of Kaili,China

This paper introduces the use of point cloud processing for extracting 3D rock structure and the 3DEC-related reconstruction of slope failure,based on a case study of the 2019 Pinglu rockfall.The basic processing procedure involves:(1)computing the point normal for HSV-rendering of point cloud;(2)automatically clustering the discontinuity sets;(3)extracting the set-based point clouds;(4)estimating of set-based mean orientation,spacing,and persistence;(5)identifying the block-forming arrays of discontinuity sets for the assessment of stability.The effectiveness of our rock structure processing has been proved by 3D distinct element back analysis.The results show that Sf M modelling and rock structure computing provides enormous cost,time and safety incentives in standard engineering practice.

Associations of sleeping patterns and isotemporal substitution of other behavior with the prevalence of CKD in Chinese adults

Studies have found a U-shaped relationship between sleep duration and chronic kidney disease(CKD)risk,but limited research evaluated the association of reallocating excessive sleep to other behavior with CKD.We included 104538 participants from the nationwide cohort of the Risk Evaluation of Cancers in Chinese Diabetic Individuals:A Longitudinal Study,with self-reported time of daily-life behavior.Using isotemporal substitution models,we found that substituting 1 h of sleeping with sitting,walking,or moderate-to-vigorous physical activity was associated with a lower CKD prevalence.Leisure-time physical activity displacement was associated with a greater prevalence reduction than occupational physical activity in working population.In stratified analysis,a lower CKD prevalence related to substitution toward physical activity was found in long sleepers.More pronounced correlations were observed in long sleepers with diabetes than in those with prediabetes,and they benefited from other behavior substitutions toward a more active way.The U-shaped association between sleep duration and CKD prevalence implied the potential effects of insufficient and excessive sleep on the kidneys,in which the pernicious link with oversleep could be reversed by time reallocation to physical activity.The divergence in the predicted effect on CKD following time reallocation to behavior of different domains and intensities and in subpopulations with diverse metabolic statuses underlined the importance of optimizing sleeping patterns and adjusting integral behavioral composition.