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Intervention of Nitrogen Evolution on Species Diversity of Broad-leaved Forest Plants in Xianweng Mountain

IOP Conference Series: Earth and Environmental science 2020年第3期446卷

作者： Wenbo Chang Yanbin Sun Penglin Shen Qingsong Chen Tianlin Miao Lan Li College of Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

Nitrogen evolution is one of the important factors driving biodiversity change. It is generally believed that the species diversity structure will be changed, and under the conditions of exogenous nitrogen addition, grasses and deciduous shrubs have a competitive advantage over hybrid grasses and evergreen shrubs. For the competition between plants in the same life type, the interaction between different life-type plants is not involved. Therefore, from the changes in forest ecosystem structure and nitrogen elements, the response of different life-type plants to nitrogen evolution can be further explored. The lower plant species of the deciduous broad-leaved forest-Mongolian carp are studied, and different gradients of nitrogen (0, 40, 80, 120 kg Nha−1yr−1) are added to the four gradients of extraneous nitrogen effects of nitrogen evolution on forest biodiversity in the north temperate zone. The results of five-year continuous nitrogen addition experiments showed that nitrogen addition significantly reduced the species richness and diversity of understory plants, and changed the species composition of the community. Nitrogen addition increased the species richness of shrub plants and diversity, reduced the richness of herbaceous plants, and reduced the important value of grasses and increased the important value of hybrid grasses. The study showed that long-term nitrogen addition significantly changed the species composition of understory plants, and the response of different life-type plants to nitrogen addition was also different.

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Mathematical model-based study of Scottish herring and mackerel migration

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IOP Conference Series: Earth and Environmental science 2021年第1期687卷

作者： Zhenzhen Yang Jiaxin Yue Yadan Yu Yuehua Zhang Lan Li Faculty of Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

The global sea temperature continues to rise and reaches a new high in 2019. This phenomenon will force the migration of Scottish herring and mackerel to higher latitudes and severely inhibit the development of small-scale Scottish fishing companies. This paper establishes a grey prediction model, a regression analysis prediction model and a fuzzy comprehensive evaluation model to explore the migration locations of herring and mackerel in the next 50 years, and to formulate appropriate business strategies for small-scale Scottish fishing companies. The model results show that in the next 50 years, herring and mackerel will migrate to Greenland and Norwegian waters, and will migrate out of the fishing range of small fishing companies from 2046 to 2053. Therefore, reducing labour costs is the most appropriate business strategy.

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Application of Kronecker convolutions in deep learning technique for automated detection of kidney stones with coronal CT images

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Information sciences 2023年 640卷

作者： Patro, Kiran Kumar Allam, Jaya Prakash Neelapu, Bala Chakravarthy Tadeusiewicz, Ryszard Acharya, U Rajendra Hammad, Mohamed Yildirim, Ozal Plawiak, Pawel Department of Electronics and Communication Engineering Aditya Institute of Technology and Management AP Tekkali532201 India Department of Electronics and Communication Engineering National Institute of Technology Rourkela Odisha Rourkela769008 India Department of Biotechnology and Medical Engineering National Institute of Technology Rourkela Odisha Rourkela769008 India AGH University of Science and Technology Department of Biocybernetics and Biomedical Engineering Krakow Poland School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia EIAS Data Science Lab College of Computer and Information Sciences Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology Faculty of Computers and Information Menoufia University Shibin El Kom32511 Egypt Department of Software Engineering Firat University Elazig Turkey Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 Krakow31-155 Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland

Kidney stone disease is a serious public health concern that is getting worse with changes in diet, obesity, medical conditions, certain supplements etc. A kidney stone also called a renal calculus, is a hard buildup of urine minerals that form in the kidneys. Computed tomography (CT) is one of the imaging models used to identify kidney stones by clinical experts. Due to the low resolution of these images, sometimes detecting kidney stones is tedious with the naked eye, which may lead to false alarms. In this work, a computer-based diagnosis system with a deep learning technique has been developed as a practical solution to aid clinicians in their diagnosis. The traditional convolutional neural network (CNN)-based deep learning technology can detect stones in the kidney. Still, it suffers from the performance and standard implementation of the convolution operations in convolution layers. A Kronecker product-based convolution technique is incorporated in the proposed deep learning architecture to reduce the redundancy in feature maps without convolution overlapping. Our proposed method helps to make the network more effective by extracting abstract and in-depth features from the input images. The publicly available GitHub kidney stone CT scans are utilized to develop the proposed architecture. Our automated model detected kidney stones with an accuracy of 98.56% utilizing CT images. Our system is more effective than the most recent and cutting-edge techniques developed for identifying kidney stones of any size, including the smallest ones. © 2023 The Author(s)

关键词： Convolution

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NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation

arXiv

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arXiv 2024年

作者： Lou, Zhenye Xu, Qing Jiang, Zekun He, Xiangjian Chen, Zhen Wang, Yi Li, Chenxin He, Maggie M. Duan, Wenting Sichuan University Pittsburgh Institute Sichuan University Chengdu China School of Computer Science University of Nottingham Ningbo China Zhejiang Ningbo China West China Biomedical Big Data Center West China Hospital Sichuan University Chengdu China Hong Kong Institute of Science & Innovation Chinese Academy of Sciences Hong Kong School of Software Dalian University of Technology Dalian116600 China Department of Electronic Engineering The Chinese University of Hong Kong 999077 Hong Kong Department of Cardiology Gold Coast University Hospital QLD Australia School of Computer Science University of Lincoln LincolnLN6 7TS United Kingdom

Domain-generalized nuclei segmentation refers to the generalizability of models to unseen domains based on knowledge learned from source domains and is challenged by various image conditions, cell types, and stain strategies. Recently, the Segment Anything Model (SAM) has made great success in universal image segmentation by interactive prompt modes (e.g., point and box). Despite its strengths, the original SAM presents limited adaptation to medical images. Moreover, SAM requires providing manual bounding box prompts for each object to produce satisfactory segmentation masks, so it is laborious in nuclei segmentation scenarios. To address these limitations, we propose a domain-generalizable framework for nuclei image segmentation, abbreviated to NuSegDG. Specifically, we first devise a Heterogeneous Space Adapter (HS-Adapter) to learn multi-dimensional feature representations of different nuclei domains by injecting a small number of trainable parameters into the image encoder of SAM. To alleviate the labor-intensive requirement of manual prompts, we introduce a Gaussian-Kernel Prompt Encoder (GKP-Encoder) to generate density maps driven by a single point, which guides segmentation predictions by mixing position prompts and semantic prompts. Furthermore, we present a Two-Stage Mask Decoder (TSM-Decoder) to effectively convert semantic masks to instance maps without the manual demand for morphological shape refinement. Based on our experimental evaluations, the proposed NuSegDG demonstrates state-of-the-art performance in nuclei instance segmentation, exhibiting superior domain generalization capabilities. The source code is available at https://***/xq141839/NuSegDG. © 2024, CC BY.

关键词： Decoding

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Impact of Garden Plant Resources Allocation on Ecological Landscape in Cold Cities

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IOP Conference Series: Earth and Environmental science 2020年第3期446卷

作者： Tianqi Yang Ye Gu Yanbin Sun Changbao Wang Haitao Cheng Shengju Li Lan Li College of Science College of Life Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

This paper analyzes the distribution of plant resources in the test plots, and aims to optimize the allocation of plants and improve the follow-up construction plan for the cold land ecological park. We provide basis and reference for plant species selection and diversification in the construction of cold land urban Greenland plant landscape, and further improve the urban environment. Taking Jiamusi City as an example, the plant species, ecological distribution and utilization of plant resources in Jiamusi City Park were investigated and investigated by sample method and field investigation method. The data were analyzed by the analytic hierarchy process, and the ornamental value of the regional plants was analyzed. According to the survey, there are 41 species of plants in the park in Jiamusi City, belonging to 15 families and 35 genera. Their use involves three aspects, such as edible medicinal, and has high application value. As a typical cold city, Jiamusi proposes to consider the concept of ecological balance and sustainable development while considering the ornamental nature of plant resources, to play a role in supporting the image of the city.

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Effects of atrazine on the black community land function and role of microbial ecology

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IOP Conference Series: Earth and Environmental science 2020年第3期446卷

作者： Yaosheng Zhang Long Tian Ruixi Ma Yanxiang Wei Jiali Yang YanBin Sun Lan Li College of Science College of Life Science Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

By measuring the concentration of atrazine stress and different culture days, the abundance of key genes in soil nitrogen transformation was studied by means of real-time PCR with the increase of atrazine stress time. The abundance of soil nitrogen-fixing function gene (nif-H) increased significantly with the increase of time in the middle and late culture period (15-30 d), indicating that the abundance of soil nitrogen-fixing function gene was promoted; soil ammonia oxidation. The abundance of functional gene (amo A) was reduced at the low concentration of atrazine (0 mg/kg, 20 mg/kg), and then decreased with increasing stress time, while at high concentration of atrazine. Under the treatment of (100mg/kg), with the increase of time, the abundance of soil ammonia oxidation function increased first and then decreased, indicating that the abundance of soil ammonia oxidation function gene was affected in the process of culture. II Based on high-throughput sequencing technology, the results of soil nitrogen fixation and ammonia oxidation community diversity showed that the functional gene diversity of soil samples was affected by the concentration of atrazine and stress time. According to the analysis of soil diversity index, nitrogen-fixing functional genes of soil samples treated with atrazine at 0 mg/kg, 20 mg/kg and 100 mg/kg were tested at the late stage (30 d). The diversity index of (nif-H) was higher than the mid-test (15 d). At the beginning of the experiment (0 d), the ammonia functional gene (amo A) diversity index of soil samples treated with atrazine concentrations of 0 mg/kg, 20 mg/kg and 100 mg/kg was higher than that in the middle of the experiment (15d), studies have shown that the nitrogen and ammonia oxidation functional gene diversity is affected under different concentrations of atrazine stress time. The distribution of the nitrogen-fixing gene (nif-H) and the ammonia-oxidizing functional gene (amo A) in the horizontal sample community structure sh

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COSINE:a software development model integrating collective intelligence, service and ecosystem

COSINE:a software development model integrating collective i...

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IEEE World Congress on Services (SERVICES)

作者： Hongbing Wang Tianjing Hong Jian Cao Haijun Zhang Changhai Nie Bo Cheng Yangfan He Li Kuang Dunwei Gong Wuhui Chen Yuliang Shi Deyi Huang School of Computer Science and Engineering and Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China Shanghai Jiaotong University Shanghai China College of Computer Science and Technology Harbin Institute of Technology Shenzhen China Nanjing University Nanjing China Wuhan University Wuhan China Research Institute of Network Technology Beijing University of Posts and Telecommunications Beijing China Software College Central South University Changsha China College of information and control engineering China University of mining and technology Xuzhou China College of data science and computer science Zhongshan University Guangzhou China Shandong University Jinan China Landry Company Shenzhen China

ISBN: (数字)9781728182032

ISBN: (纸本)9781728182049

With the development of the internet technology, a large amount of softwares have emerged to meet users' increasing needs. At the mean time, software systems have been faced with a problem that they must adapt to the dynamic network environment. It is obvious that a variety of software development models have been proposed in the past few decades. However, the majority of these methods are gradually unadaptable to new circumstances. In this paper, we proposed a new software development model integrating collective intelligence, service and ecosystem. On the one hand, we have introduced the model in detail. On the other hand, We took a practical example to demonstrate the effectiveness of the proposed model.

关键词： Adaptation models Biological system modeling Ecosystems Collective intelligence software systems

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Retraction notice to “Intelligent Edge Computing Based on Machine Learning for Smart City” [Future Generation Computer Systems 115 (2020) 90–99]

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Future Generation Computer Systems 2024年 158卷 569-569页

作者： Zhihan Lv Dongliang Chen Ranran Lou Qingjun Wang School of Data Science and Software Engineering Qingdao University Qingdao China Shenyang Aerospace University Shenyang 110136 China Nanjing University of Aeronautics and Astronautics Nanjing China

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DAMBLO: Improving Arrhythmia Classification with Plug-and-Play Dual Attention-Based Multiscale Feature Learning Block

SSRN

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SSRN 2023年

作者： Zhuang, Tianming Qin, Zhiguang You, Li Deng, Erqiang Ding, Yi Cao, Mingsheng Guo, Yingkun Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu610054 China Department of Molecular Genetics Erasmus University Medical Center Rotterdam Netherlands Department of Radiology Key Laboratory of Obstetric and Gynecologic and Pediatric Diseases and Birth Defects Ministry of Education West China Second University Hospital Sichuan University Sichuan Chengdu610072 China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China

The electrocardiogram diagnosis played an important role in early arrhythmia prevention and cardiovascular disease detection. How to analysis and detect the electrocardiogram automatically becomes a challenging task in clinical practice. Convolutional neural network based approaches have been widely applied in the field of automatic arrhythmia detection and analysis. However, the existing methods fails to preserve the abundant and essential latent representatives from multiple dimensions. To address these problems, a dual spatial-channel aggregation module is proposed, which expects to concentrate on the prominent target information along spatial and channel dimension of electrocardiogram signals. Moreover, a multi-scale enhancement module with channel-wise gating mechanism is also proposed to enlarge the receptive resolution and further to improve the learning ability of long-range dependencies from the global information. Furthermore, these two proposed modules are integrated as a "plug-and-play" block that can be easily adopted as a drop-in replacement for any 3×3 convolution layers in convolutional neural networ based architectures. In order to evaluate the effectiveness and generalization of the proposed block, it is plugged in a series of convolutional neural network based frameworks and are evaluated on two benchmark datasets, MIT-BIH and PTB. The extensive experimental results show that the proposed "plug-and-play" block can significantly improve the arrhythmia classification performance. Moreover, compared to other state-of-the-art methods, the framework plugged with the proposed block can achieve a competitive classification performance, proving the feasibility and advancement of the proposed dual attention-based multiscale feature learning block. © 2023, The Authors. All rights reserved.

关键词： Electrocardiograms

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The Characteristics and Geographical Features of Plant Populations in the Forest Region of Wanda Mountains

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IOP Conference Series: Earth and Environmental science 2021年第1期687卷

作者： Jialin Li Jiao Yang XueWei Sun Jincheng Luo Hongbin Qiu Lan Li School of Public Health Jiamusi University Jiamusi City Heilongjiang Province 154007 China School of Data Science and Software Engineering Wuzhou University Wuzhou City Guangxi Province 543000 China

The study of species diversity and fauna characteristics in the Wandashan area is of great significance for the protection and utilization of plant resources in the future. The relevant characteristics and characteristics of species diversity in the Wandashan area are analyzed. The various species diversity indices of the Dashan area are calculated, reflecting the species richness, dominance, uniformity and the information volume and community complexity of the Wandashan area. Through Matlab, the location of each plot in the Wandashan area and the species diversity index of Joe, Irrigation, Grass and all species are represented in the form of graphs, reflecting the different species diversity indices in other areas of the mountainous region. Changes combining the results of the field survey with the existing literature, the floristic analysis is carried out to obtain the characteristics of the flora of the mountainous area, and reflec the information about the species diversity of the mountainous area. Through the similarity coefficient comparison and analysis of plant distribution, the relationship between the flora of Wandashan, Changbai Mountain and Xiaoxing'anling was determined. The results of flora analysis show that the flora of the Wandashan area belongs to the North Temperate Zone and has a general connection with other floras in the world. The flora of Northeast China mainly includes Xiaoxing'anling area, Wandashan area and Changbai Mountain. By comparing the similarity coefficients at the three levels of families, genera and species, it can be seen that the similarity coefficient between Xiaoxing'anling and Wandashan is higher than that between Changbai Mountain and Wandashan.

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