Research on Clothing Image Database Retrieval Algorithm Based on Wavelet Transform

Aiming at the problems of low image data retrieval accuracy and slow retrieval speed in the existing image database retrieval algorithms, this paper designs a clothing image database retrieval algorithm based on wavelet transform. Firstly, it represents the color consistency vector of clothing image, reflects the composition and distribution of image color through color histogram, quantifies the visual features of clothing image, aggregates them into a fixed size representation vector, and uses the Fair Value (FV) model to complete the collection of clothing image data. Then, the size of the clothing image is adjusted by using the size transformation technology, and the clothing pattern is divided into four moments with the same size. On this basis, the clothing image is discretized with the help of Hu invariant moment to complete the preprocessing of clothing image data. Finally, the generating function of wavelet transform is determined, and a cluster of functions is obtained through translation and expansion. The wavelet filter is decomposed into basic modules, and then, the wavelet transform is studied step by step. The clothing image data are regarded as a signal, split, predicted, and updated and input into the wavelet model, and the retrieval research of clothing image database is completed. The experimental results show that the design of the retrieval algorithm is reasonable, the retrieval data accuracy is high, and the retrieval speed is fast.

Research on Fast Face Retrieval Optimization Algorithm Based on Fuzzy Clustering

Aiming at the problem of long retrieval time for massive face image databases under a given threshold, a fast retrieval algorithm for massive face images based on fuzzy clustering is proposed. The algorithm builds a deep convolutional neural network model. The model can be used to extract features from face photos to obtain a high-dimensional vector to represent the high-level semantic features of face photos. On this basis, the fuzzy clustering algorithm is used to perform fuzzy clustering on the feature vectors of the face database to construct a retrieval pedigree map. When the threshold is passed in for database retrieval of the target face photos, the pedigree map can be quickly retrieved. Experiments on the LFW face dataset and self-collected face dataset show that the model is better than the commonly used K-means model in face recognition accuracy, clustering effect, and retrieval speed and has certain commercial value.

Plectranthus ecklonii Benth: A Comprehensive Review Into its Phytochemistry and Exerted Biological Activities

Ethnopharmacological Relevance:Plectranthus genus (Lamiaceae family) contain several species with acknowledged ethnopharmacological uses, such as, for gastrointestinal and respiratory-related problems, due to their anti-inflammatory, antibacterial and antifungal properties. The bioactivity of isolated medicinal compounds from this genus justifies the increased interest in recent times for species of Plectranthus, placing them in the spotlight for natural product drug development.Aim of the study: To the best of our knowledge, this is the first review on the biological activities of Plectranthus ecklonii Benth. As such, the aim of this review was three-fold: 1) to summarize the chemical compounds isolated from P. ecklonii; 2) to collate the biological activities and mechanisms of action of these compounds from in vitro studies; and 3) to evaluate the documented uses and potential applications of this species, in order to postulate on the direction of pharmaceutical uses of this species.Materials and methods: An extensive database retrieval was performed using the electronic databases Web of Science, PubMed, Google Scholar and ScienceDirect. The search criteria consisted of the keywords “Plectranthus ecklonii”, “Plectranthus ecklonii + review”, “Plectranthus ecklonii + diterpenes” or “Plectranthus ecklonii + abietanes”, “ecklonii + parviflorone D”, searched individually and as combinations. Eligibility criteria were set out and titles in English, Portuguese and Spanish were reviewed, with all references included dating from 1970 to 2021. A total of 169 papers were selected and included. Chemical structures were drawn using ChemDraw 20.0, CID numbers were searched in PubChem and the PRISMA diagram was created using PowerPoint 2012.Results: To date, a total of 28 compounds have been isolated from P. ecklonii, including diterpenes, triterpenes, flavonoids, and hydroxycinnamic acids. Most focused on the antimicrobial action of its constituents, although compounds have demonstrated other bioactivities, namely antioxidant, anti-inflammatory and antitumor. The most recent studies emphasize the diterpenoids, particularly parviflorone D, with the help of nanotechnology.Conclusions: The widespread ethnobotanical and traditional uses of P. ecklonii can be scientifically justified by a range of biological activities, demonstrated by isolated secondary metabolites. These bioactivities showcase the potential of this species in the development of economically important active pharmaceutical ingredients, particularly in anticancer therapy.

Analysis of allergen components and identification of bioactivity of HSP70 in pollen of Populus deltoides

Background Allergies caused by pollen from Populus deltoides are common, but the allergic components are still unclear. Methods The total proteins in pollen of P. deltoides were analyzed by proteomics, and the potential allergens were identified via the WHO/IUIS database and the allergenOnline database retrieval. One target protein was screened by bioinformatics and expressed in Escherichia coli. The biological activity of the expressed product was verified by animal experiments. Results The total of 3929 proteins in pollen of P. deltoides were identified, and 46 potential allergens belonging to 10 protein families were recognized by database retrieval. B9N9W6 protein of Hsp70 family was screened by bioinformatics analysis and expressed successfully. ELISA showed that B9N9W6 can stimulate the immune system to produce specific IgE and promote the generation of IL-4. Flow cytometry showed that B9N9W6 can significantly stimulate the proliferation of CD4+ T cells and promote the polarization of Th2 cells. The pathological sections of mice lung tissues indicated that alveolar destruction was more severe in the B9N9W6 group than that of extract group, and there were more inflammatory cells infiltration, mucus exudation and bleeding. Conclusion B9N9W6 is an important antigenic substance in the pollen of P. deltoides. Due to the conserved structure of Hsp70 family, more attention should be paid to the possibility of sensitization when Hsp70 from any pathogenic species is administered.

Analysis of Allergen Components and Identification of Bioactivity of HSP70 in Pollen of Populus Deltoides

Background: Allergies caused by pollen from Populus deltoides are common, but the allergic components are still unclear. Methods: The total proteins in pollen of P. deltoides were analyzed by proteomics, and the potential allergens were identified via the WHO/IUIS database and the allergenOnline database retrieval. The target protein was screened by bioinformatics and expressed in Escherichia coli. The biological activity of the expressed product was verified by animal experiments. Results: 3929 total proteins in pollen of P. deltoides were identified, and 49 potential allergens belonging to 10 protein families were recognized by database retrieval. B9N9W6 protein of Hsp 70 family was screened by bioinformatics analysis and expressed successfully. ELISA showed that B9N9W6 can stimulate the immune system to produce specific IgE and promote the generation of IL-4. Flow cytometry showed that B9N9W6 can significantly stimulate the proliferation of CD4+ T cells and promote the polarization of Th2 cells. The pathological sections of mice lung tissues indicated that alveolar destruction was more severe in the B9N9W6 group than that of extract group, and there were more inflammatory cells infiltration, mucus exudation and bleeding. Conclusion: B9N9W6 is an important antigenic substance in the pollen of P. deltoides. Due to the conserved structure of Hsp 70 family, more attention should be paid to the possibility of sensitization when HSP 70 from any pathogenic species is administered.

A Heterogeneous Geospatial Data Retrieval Method Using Knowledge Graph

Information resources have increased rapidly in the big data era. Geospatial data plays an indispensable role in spatially informed analyses, while data in different areas are relatively isolated. Therefore, it is inadequate to use relational data in handling many semantic intricacies and retrieving geospatial data. In light of this, a heterogeneous retrieval method based on knowledge graph is proposed in this paper. There are three advantages of this method: (1) the semantic knowledge of geospatial data is considered; (2) more information required by users could be obtained; (3) data retrieval speed can be improved. Firstly, implicit semantic knowledge is studied and applied to construct a knowledge graph, integrating semantics in multi-source heterogeneous geospatial data. Then, the query expansion rules and the mappings between knowledge and database are designed to construct retrieval statements and obtain related spatial entities. Finally, the effectiveness and efficiency are verified through comparative analysis and practices. The experiment indicates that the method could automatically construct database retrieval statements and retrieve more relevant data. Additionally, users could reduce the dependence on data storage mode and database Structured Query Language syntax. This paper would facilitate the sharing and outreach of geospatial knowledge for various spatial studies.

Research on Improving Teaching Qualities by Using Metadata to Recognize Plants

Metadata plays a vital role in the development and implementation of the National Digital Archives Program (NDAP). We’re now developing an online database for teaching plant recognition, providing students and other users with an access to recognizing all plants possible. While digitalizing the above-mentioned database, this study focuses on “subject and community oriented” metadata kernel set. By using the exact searching and result revealing interface over the same data as well as cross-database retrieval, we aim at uttering convenience and user-friendliness. In view of the ever-increasing data and the need for future integration, we’ve tried to analyze the content and features of possible plants, made comparisons over various metadata standards, constructed a user-friendly database system and designed the plant-related metadata in the dedication of research references at home and abroad. The assistant learning mechanism of this interactive digital archive includes two vital aspects. They are, respectively, student-learning circulation and database-learning circulation, which are worth developing into further application on teaching. Learners of all levels are able to use the system freely and spontaneously. For the exchange of the digital archives, this study constructs a Chinese metadata format and integrates XML technique in the hope of helping students retrieve their data precisely, acquire an integrated concept of plants and learn to appreciate and cherish all plants in their campus.

Global Research Status and Development of COVID-19 in 2020: A Bibliometric Analysis

Background: The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is currently widespread in the world. This study aimed to access the characteristics of the publications involving COVID-19 by using a bibliometric analysis.Methods: COVID-19 publications published between 1 January 2020 and 31 July 2020 was searched from the Web of Science database on 1 August 2020.The database retrieval was done on the same day. Analysis parameters mainly include publication month, research institutions, authors, journals, countries and cooperation networks among them.Results: A total of 14186 COVID-19 associated articles were retrieved from the Web of Science database, and the quantity of articles increased rapidly month by month. The authors of the top ten manuscripts per number of citations and the most productive institution were both from China. The total publication number of China was as high as 3,029，second only to the United States. Moreover, China ranks first in the number of total citations of articles and the average article citations. The United States has the highest number of total publications and ranks second only to China in terms of the influence of individual articles. Authors, institutions and Countries established a network of close cooperation for research on COVID-19.Conclusion: There was a growing number of articles on COVID-19 around the world, China and the United States are the two most influential countries.