Discrete Littlewood-Paley-Stein Theory And Wolff Potentials On Homogeneous Spaces And Multi-Parameter Hardy Spaces

This dissertation consists of two parts: In part I, We establish a new atomic decomposition of the multi-parameter Hardy spaces of homogeneous type and obtain the associated $H^p-L^p$ and $H^p-H^p$ boundedness criterions for singular integral operators. On the other hand, we compare the Wolff and Riesz potentials on spaces of homogenous type, followed by a Hardy-Littlewood-Sobolev type inequality. Then we drive integrability estimates of positive solutions to the Lane-Emden type integral systems on spaces of homogeneous type. In part II, We establish a $(p,2)$-atomic decomposition of the Hardy space associated with different homogeneities for $

Acanthopagrus latus migration patterns and habitat use in Wanshan Islands, Pearl River Estuary, determined using otolith microchemical analysis

IntroductionThe waters surrounding the Wanshan Islands are important traditional fishing grounds in China, with rich habitat types. Acanthopagrus latus is an economically important species in this area; however, the distribution of its spawning grounds and habitat use patterns remain unknown.MethodsThus 100 otolith samples of A. latus were collected from three geographic areas (MW: Qi’ao Island Mangrove Water Habitat; OW: Yamen Estuary Oyster Farm Water Habitat; RW: Dong’ao-Guishan Island Reef Water Habitat), and the concentrations of Sr and Ca along the shortest axis of the vertical otolith annual or lunar rings were measured to span the entire life cycle of A. latus, with the core and edge areas corresponding to environmental characteristics at birth and capture, respectively.Results and discussionAnalysis of covariance (ANCOVA) revealed that the ratios of Sr/Ca in otolith edges of RW samples are significantly higher than those of OW and MW samples; however, both the values of Sr/Ca ratio in otolith cores collected from OW and MW are comparable with those of RW samples. Cluster analysis and non-metric multidimensional scaling (nMDS) indicated that at the juvenile stage, RW and MW individuals in the two main clusters belonged to the same cluster. There was no significant difference between the cores of the RW samples and the edges of the MW and OW samples. Therefore, the spawning area of A. latus in the Wanshan Islands is thought to have originated from low to medium-salinity waters with mangroves and oyster farm habitats in the Pearl River Estuary. A. latus from RW was found to have three distinct habitat-use patterns: 1) Marine Resident (7.2% of sampled fish) fish that remain in marine habitats for life; 2) Marine Migrant (16.4% of sampled fish) juveniles inhabit low to moderate salinity habitats and migrate to marine habitats as they grow; 3) Estuarine Visitor (76.4% of sampled fish) repeated migration between low to moderate salinity and marine habitats. This suggests widespread migration between estuarine and marine habitats throughout the ontogeny. The plasticity of this habitat use and the protection of spawning grounds should be considered in future fisheries management because A. Latus in this area has been the victim of the overexploitation of resources

Boundedness of para-product operators on spaces of homogeneous type

summary:We obtain the boundedness of Calderón-Zygmund singular integral operators $T$ of non-convolution type on Hardy spaces $H^p(\mathcal X)$ for $1/{(1+\epsilon )}<p\le 1$, where ${\mathcal X}$ is a space of homogeneous type in the sense of Coifman and Weiss (1971), and $\epsilon$ is the regularity exponent of the kernel of the singular integral operator $T$. Our approach relies on the discrete Littlewood-Paley-Stein theory and discrete Calderón's identity. The crucial feature of our proof is to avoid atomic decomposition and molecular theory in contrast to what was used in the literature

User Preference Mining in Digital Community Based on CLV Preference Mining Model

[Purpose/Significance] Digital communities have become a way for enterprises to manage users efficiently. The existing research on digital community rarely considers the importance of user behavior information and user's customer life cycle value to the mining of user preferences in digital community. This research aims to give full play to the digital community's characteristics such as intuitive, convenient, interesting, and interactive properties so that the research results can benefit every user in their use of the digital community and every enterprise in their user management. [Method/Process] Aiming at the user groups in digital community, this paper proposes a preference mining model ClV-Preference mining (CLV-PM) based on Customer Lifetime Value (CLV). First, in order to reflect the real preferences of users, the three indicators of the RFM model are used to quantify user behavior information, and the group characteristics of users are mined through K-mean ++ algorithm to generate user value category labels. Second, in order to consider the timeliness and difference of users and enhance the model's cognition of preferences, this paper uses the entropy weight method to solve the indicator weights of each activity, obtains user CLV to construct user-project scoring matrix, and uses the collaborative filtering algorithm to predict user preferences. Finally, based on the user value category, user historical preference and user forecast preference, the user preference profile of target users in digital community is generated, and feasible suggestions are put forward for the operation and maintenance of target users according to the user preference profile. [Results/Conclusions] The user dataset of the "Wechat community" management platform can be divided into four user value categories: important value users, low value users, returned users and important retention users. Target users 16254 are important value users, and the operation strategy of "retention and maintenance" is adopted. The historical preferences are happy hop, sec-kill and other activities; the prediction preference is flying chess battle, guessing code map and other activities; the target user preference sketch provides the basis for the operation and maintenance of users in the digital community. In terms of data source, the CLV-PM model proposed in this paper directly reflects user preferences based on user behavior information and reduces the problem of score distortion. To provide a new perspective for the research of user behavior in digital community, the construction of user-project scoring matrix based on user CLV fully considers the user value of digital community and provides a new direction for the extension and application of CLV. However, due to limited research space, this paper did not conduct model evaluation research on the proposed model, which can be further discussed in subsequent studies

Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites

With the rapid growth of networking, cyber–physical–social systems (CPSSs) provide vast amounts of information. Aimed at the huge and complex data provided by networking, obtaining valuable information to meet precise search needs when capturing user intention has become a major challenge, especially in personalized websites. General search engines face difficulties in addressing the challenges brought by this exploding amount of information. In this paper, we use real-time location and relevant feedback technology to design and implement an efficient, configurable, and intelligent retrieval framework for personalized websites in CPSSs. To improve the retrieval results, this paper also proposes a strategy of implicit relevant feedback based on click-through data analysis, which can obtain the relationship between the user query conditions and retrieval results. Finally, this paper designs a personalized PageRank algorithm including modified parameters to improve the ranking quality of the retrieval results using the relevant feedback from other users in the interest group. Experiments illustrate that the proposed accurate and intelligent retrieval framework improves the user experience

Distribution Pattern of Coral Reef Fishes in China

Coral reefs are known as “tropical rain forests” in the ocean. Fish diversity is extremely high, accounting for one-third of marine fishes. To better protect and manage coral reef fishes, this study systematically compiled documents and databases published in China. We counted 2855 species of coral reef fishes in China, which belong to 3 classes, 41 orders, 252 families, and 1017 genera. Among these, Perciformes was the dominant order, accounting for 57.31% of the total species. Gobiidae (7.43%), Labridae (5.36%), Pomacentridae (4.52%), and Serranidae (4.38%) were the main families, while other families accounted for less than 4%. Furthermore, 5.56% of coral reef fish species have entered the IUCN Red List. The present study found that coral reef fishes can be divided into nearshore and offshore. This was mainly because the nearshore coral reef fishes were more affected by human disturbance and runoff from the mainland, whereas offshore coral reef fishes were in areas with high salinity and temperature far from the mainland, where human disturbance was less. Coral reef fish species’ diversity had a significant positive correlation with coral species diversity (p < 0.05), mainly because corals provide habitat and shelter. This study is the first systematic compilation and analysis of coral reef fishes in China and provides a basic reference for global protection management and biological geographical analysis

Distribution Pattern of Coral Reef Fishes in China

Coral reefs are known as &ldquo;tropical rain forests&rdquo; in the ocean. Fish diversity is extremely high, accounting for one-third of marine fishes. To better protect and manage coral reef fishes, this study systematically compiled documents and databases published in China. We counted 2855 species of coral reef fishes in China, which belong to 3 classes, 41 orders, 252 families, and 1017 genera. Among these, Perciformes was the dominant order, accounting for 57.31% of the total species. Gobiidae (7.43%), Labridae (5.36%), Pomacentridae (4.52%), and Serranidae (4.38%) were the main families, while other families accounted for less than 4%. Furthermore, 5.56% of coral reef fish species have entered the IUCN Red List. The present study found that coral reef fishes can be divided into nearshore and offshore. This was mainly because the nearshore coral reef fishes were more affected by human disturbance and runoff from the mainland, whereas offshore coral reef fishes were in areas with high salinity and temperature far from the mainland, where human disturbance was less. Coral reef fish species&rsquo; diversity had a significant positive correlation with coral species diversity (p &lt; 0.05), mainly because corals provide habitat and shelter. This study is the first systematic compilation and analysis of coral reef fishes in China and provides a basic reference for global protection management and biological geographical analysis

SAR Image Despeckling With Residual-In-Residual Dense Generative Adversarial Network

Deep convolutional neural networks have delivered remarkable aptitude in performing Synthetic Aperture Radar (SAR) image speckle removal tasks. Such approaches are nevertheless constrained in balancing speckle removal and preservation of spatial information, particularly with respect to strong speckle noise. In this paper, a novel residual-in-residual dense generative adversarial network is proposed to effectively suppress SAR image speckle while retaining rich spatial information. A despeckling sub-network composed of residual-in-residual dense blocks with an encoder-decoder structure is devised to learn end-to-end mapping of noisy images onto noise-free images, where the combination of residual-in-residual structure and dense connection significantly enhances the feature representation capability. In addition, a discriminator sub-network with a fully convolutional structure is introduced, and the adversarial learning strategy is adopted to continuously refine the quality of despeckled results. Systematic experimental results on simulated and real SAR images demonstrate that the novel approach offers superior performance in both quantitative and visual evaluation as compared to state-of-the-art methods.</p

Development Path of Marine Ranching in South China Sea Based on SWOT Analysis

As a modern fishery model to repair the marine ecosystem and realize the proliferation of fishery resources, marine ranching is an important link in promoting the green development of marine economy, promoting the transformation and upgrading of traditional fisheries and building a community of shared future for the sea. However, there are many factors restricting the high-quality development of modern marine ranching in the actual construction. Rational planning of marine ranching and giving full play to its ecological, social and economic benefits are crucial to the sustainable development of marine ranching. This paper summarizes the current situation of the construction, technical development and policy management of marine ranching in the South China Sea, and comprehensively analyzes the development of marine ranching in the South China Sea by using SWOT analysis method, explains the advantages, disadvantages, opportunities and challenges of marine ranching in the South China Sea, and puts forward the path for the development of marine ranching industry in the South China Sea based on the experience and development trend of marine ranching construction at home and abroad, It is expected to provide reference for the high-quality development of marine ranching in China