Application of Textiles With Plant Textures in Soft Decoration of Home Furnishing

Textiles with plant textures have been widely applied in soft decoration of home furnishing and decoration means are diversified. This paper discusses the design foothold of textiles with plant textures in soft decoration of home furnishing, elaborates their different varieties in soft decoration and the basic principles of application, analyzes the concrete application methods of textiles with plant textures in different soft decoration styles, and predicts their development tendency in soft decoration of home furnishing, thus offering theoretical basis and method reference for the application of textiles with plant textures in soft decoration of modern home furnishing.

Permanence and Stability of an Age-Structured Prey-Predator System with Delays

An age-structured prey-predator model with delays is proposed and analyzed. Mathematical analyses of the model equations with regard to boundedness of solutions, permanence, and stability are analyzed. By using the persistence theory for infinite-dimensional systems, the sufficient conditions for the permanence of the system are obtained. By constructing suitable Lyapunov functions and using an iterative technique, sufficient conditions are also obtained for the global asymptotic stability of the positive equilibrium of the model

Screening and cloning of differentially expressed genes in Dendrobium nobile induced by orchid mycorrhizal fungus promoting the growth

Appropriate mycorrhizal fungi could effectively promote plant growth and development. Our previous research results showed that the growth of Dendrobium nobile was obviously promoted under inoculating one orchid mycorrhizal fungi, Epulorhiza sp. AR-18. To understand the growth-promoting molecular mechanisms, differential displayed real time polymerase chain reaction (DDRT-PCR), reverse Northern blot and Southern blot were used to isolate and identify genes whose transcription were altered in cultured D. nobile plants that were treated with Epulorhiza sp. AR-18. Amplified by 8 primer combinations from one anchor primers and 8 random primers, a total of 14 complementary DNA (cDNA) fragments including 12 differentially expressed cDNA bands were isolated. Reverse northern blot analysis showed that only 2 genes were differentially displayed cDNA bands. One band was an especially expressed fragment, expressed in the treated group but not in the control; while another was a differentially expressed fragment, weak in the treated and strength in the control. Southern blot analysis demonstrated that the two gene fragments were from the plant and not from the fungus. Sequence analysis and database searches revealed no significant homology to any known sequences. The results suggested that the usefulness of messenger RAN (mRNA) differential display technique for the detection of differentially expressed genes in D. nobile whose growth could be promoted by mycorrhizal fungi.Keywords: Dendrobium nobile, differential displayed real time polymerase chain reaction (DDRT-PCR), orchid mycorrhizal fungus, Epulorhiza sp., reverse northern blo

TCMGIS-II based prediction of medicinal plant distribution for conservation planning: a case study of Rheum tanguticum

<p>Abstract</p> <p>Background</p> <p>Many medicinal plants are increasingly endangered due to overexploitation and habitat destruction. To provide reliable references for conservation planning and regional management, this study focuses on large-scale distribution prediction of <it>Rheum tanguticum </it>Maxim. ex Balf (<it>Dahuang</it>).</p> <p>Methods</p> <p>Native habitats were determined by specimen examination. An improved version of GIS-based program for the distribution prediction of traditional Chinese medicine (TCMGIS-II) was employed to integrate national geographic, climate and soil type databases of China. Grid-based distance analysis of climate factors was based on the Mikowski distance and the analysis of soil types was based on grade division. The database of resource survey was employed to assess the reliability of prediction result.</p> <p>Results</p> <p>A total of 660 counties of 17 provinces in China, covering a land area of 3.63 × 10⁶km², shared similar ecological factors with those of native habitats appropriate for <it>R. tanguticum </it>growth.</p> <p>Conclusion</p> <p>TCMGIS-II modeling found the potential habitats of target medicinal plants for their conservation planning. This technology is useful in conservation planning and regional management of medicinal plant resources.</p

Identification of closely related species in Aspergillus through Analysis of Whole-Genome

The challenge of discriminating closely related species persists, notably within clinical diagnostic laboratories for invasive aspergillosis (IA)-related species and food contamination microorganisms with toxin-producing potential. We employed Analysis of the whole-GEnome (AGE) to address the challenges of closely related species within the genus Aspergillus and developed a rapid detection method. First, reliable whole genome data for 77 Aspergillus species were downloaded from the database, and through bioinformatic analysis, specific targets for each species were identified. Subsequently, sequencing was employed to validate these specific targets. Additionally, we developed an on-site detection method targeting a specific target using a genome editing system. Our results indicate that AGE has successfully achieved reliable identification of all IA-related species (Aspergillus fumigatus, Aspergillus niger, Aspergillus nidulans, Aspergillus flavus, and Aspergillus terreus) and three well-known species (A. flavus, Aspergillus parasiticus, and Aspergillus oryzae) within the Aspergillus section. Flavi and AGE have provided species-level-specific targets for 77 species within the genus Aspergillus. Based on these reference targets, the sequencing results targeting specific targets substantiate the efficacy of distinguishing the focal species from its closely related species. Notably, the amalgamation of room-temperature amplification and genome editing techniques demonstrates the capacity for rapid and accurate identification of genomic DNA samples at a concentration as low as 0.1 ng/μl within a concise 30-min timeframe. Importantly, this methodology circumvents the reliance on large specialized instrumentation by presenting a singular tube operational modality and allowing for visualized result assessment. These advancements aptly meet the exigencies of on-site detection requirements for the specified species, facilitating prompt diagnosis and food quality monitoring. Moreover, as an identification method based on species-specific genomic sequences, AGE shows promising potential as an effective tool for epidemiological research and species classification

Analysis of Whole-Genome facilitates rapid and precise identification of fungal species

Fungal identification is a cornerstone of fungal research, yet traditional molecular methods struggle with rapid and accurate onsite identification, especially for closely related species. To tackle this challenge, we introduce a universal identification method called Analysis of whole GEnome (AGE). AGE includes two key steps: bioinformatics analysis and experimental practice. Bioinformatics analysis screens candidate target sequences named Targets within the genome of the fungal species and determines specific Targets by comparing them with the genomes of other species. Then, experimental practice using sequencing or non-sequencing technologies would confirm the results of bioinformatics analysis. Accordingly, AGE obtained more than 1,000,000 qualified Targets for each of the 13 fungal species within the phyla Ascomycota and Basidiomycota. Next, the sequencing and genome editing system validated the ultra-specific performance of the specific Targets; especially noteworthy is the first-time demonstration of the identification potential of sequences from unannotated genomic regions. Furthermore, by combining rapid isothermal amplification and phosphorothioate-modified primers with the option of an instrument-free visual fluorescence method, AGE can achieve qualitative species identification within 30 min using a single-tube test. More importantly, AGE holds significant potential for identifying closely related species and differentiating traditional Chinese medicines from their adulterants, especially in the precise detection of contaminants. In summary, AGE opens the door for the development of whole-genome-based fungal species identification while also providing guidance for its application in plant and animal kingdoms

Hyper-Relational Knowledge Graph Neural Network for Next POI

With the advancement of mobile technology, Point of Interest (POI) recommendation systems in Location-based Social Networks (LBSN) have brought numerous benefits to both users and companies. Many existing works employ Knowledge Graph (KG) to alleviate the data sparsity issue in LBSN. These approaches primarily focus on modeling the pair-wise relations in LBSN to enrich the semantics and thereby relieve the data sparsity issue. However, existing approaches seldom consider the hyper-relations in LBSN, such as the mobility relation (a 3-ary relation: user-POI-time). This makes the model hard to exploit the semantics accurately. In addition, prior works overlook the rich structural information inherent in KG, which consists of higher-order relations and can further alleviate the impact of data sparsity.To this end, we propose a Hyper-Relational Knowledge Graph Neural Network (HKGNN) model. In HKGNN, a Hyper-Relational Knowledge Graph (HKG) that models the LBSN data is constructed to maintain and exploit the rich semantics of hyper-relations. Then we proposed a Hypergraph Neural Network to utilize the structural information of HKG in a cohesive way. In addition, a self-attention network is used to leverage sequential information and make personalized recommendations. Furthermore, side information, essential in reducing data sparsity by providing background knowledge of POIs, is not fully utilized in current methods. In light of this, we extended the current dataset with available side information to further lessen the impact of data sparsity. Results of experiments on four real-world LBSN datasets demonstrate the effectiveness of our approach compared to existing state-of-the-art methods

Generation and analysis of expressed sequence tags from a cDNA library of the fruiting body of Ganoderma lucidum

<p>Abstract</p> <p>Background</p> <p>Little genomic or trancriptomic information on <it>Ganoderma lucidum </it>(<it>Lingzhi</it>) is known. This study aims to discover the transcripts involved in secondary metabolite biosynthesis and developmental regulation of <it>G. lucidum </it>using an expressed sequence tag (EST) library.</p> <p>Methods</p> <p>A cDNA library was constructed from the <it>G</it>. <it>lucidum </it>fruiting body. Its high-quality ESTs were assembled into unique sequences with contigs and singletons. The unique sequences were annotated according to sequence similarities to genes or proteins available in public databases. The detection of simple sequence repeats (SSRs) was preformed by online analysis.</p> <p>Results</p> <p>A total of 1,023 clones were randomly selected from the <it>G</it>. <it>lucidum </it>library and sequenced, yielding 879 high-quality ESTs. These ESTs showed similarities to a diverse range of genes. The sequences encoding squalene epoxidase (SE) and farnesyl-diphosphate synthase (FPS) were identified in this EST collection. Several candidate genes, such as <it>hydrophobin</it>, <it>MOB2</it>, <it>profilin </it>and <it>PHO84 </it>were detected for the first time in <it>G</it>. <it>lucidum</it>. Thirteen (13) potential SSR-motif microsatellite loci were also identified.</p> <p>Conclusion</p> <p>The present study demonstrates a successful application of EST analysis in the discovery of transcripts involved in the secondary metabolite biosynthesis and the developmental regulation of <it>G. lucidum</it>.</p

Crypto-ransomware Detection through Quantitative API-based Behavioral Profiling

With crypto-ransomware's unprecedented scope of impact and evolving level of sophistication, there is an urgent need to pinpoint the security gap and improve the effectiveness of defenses by identifying new detection approaches. Based on our characterization results on dynamic API behaviors of ransomware, we present a new API profiling-based detection mechanism. Our method involves two operations, namely consistency analysis and refinement. We evaluate it against a set of real-world ransomware and also benign samples. We are able to detect all ransomware executions in consistency analysis and reduce the false positive case in refinement. We also conduct in-depth case studies on the most informative API for detection with context