An adaptive multilevel indexing method for disaster service discovery

With the globe facing various scales of natural disasters then and there, disaster recovery is one among the hottest research areas and the rescue and recovery services can be highly benefitted with the advancements of information and communications technology (ICT). Enhanced rescue effect can be achieved through the dynamic networking of people, systems and procedures. A seamless integration of these elements along with the service-oriented systems can satisfy the mission objectives with the maximum effect. In disaster management systems, services from multiple sources are usually integrated and composed into a usable format in order to effectively drive the decision-making process. Therefore, a novel service indexing method is required to effectively discover desirable services from the large-scale disaster service repositories, comprising a huge number of services. With this in mind, this paper presents a novel multilevel indexing algorithm based on the equivalence theory in order to achieve effective service discovery in large-scale disaster service repositories. The performance and efficiency of the proposed model have been evaluated by both theoretical analysis and practical experiments. The experimental results proved that the proposed algorithm is more efficient for service discovery and composition than existing inverted index methods

GAOM: Genetic Algorithm Based Ontology Matching

In this paper a genetic algorithm-based optimization procedure for ontology matching problem is presented as a feature-matching process. First, from a global view, we model the problem of ontology matching as an optimization problem of a mapping between two compared ontologies, and every ontology has its associated feature sets. Second, as a powerful heuristic search strategy, genetic algorithm is employed for the ontology matching problem. Given a certain mapping as optimizing object for GA, fitness function is defined as a global similarity measure function between two ontologies based on feature sets. Finally, a set of experiments are conducted to analysis and evaluate the performance of GA in solving ontology matching problem

CFBenchmark: Chinese Financial Assistant Benchmark for Large Language Model

Large language models (LLMs) have demonstrated great potential in the financial domain. Thus, it becomes important to assess the performance of LLMs in the financial tasks. In this work, we introduce CFBenchmark, to evaluate the performance of LLMs for Chinese financial assistant. The basic version of CFBenchmark is designed to evaluate the basic ability in Chinese financial text processing from three aspects~(\emph{i.e.} recognition, classification, and generation) including eight tasks, and includes financial texts ranging in length from 50 to over 1,800 characters. We conduct experiments on several LLMs available in the literature with CFBenchmark-Basic, and the experimental results indicate that while some LLMs show outstanding performance in specific tasks, overall, there is still significant room for improvement in basic tasks of financial text processing with existing models. In the future, we plan to explore the advanced version of CFBenchmark, aiming to further explore the extensive capabilities of language models in more profound dimensions as a financial assistant in Chinese. Our codes are released at https://github.com/TongjiFinLab/CFBenchmark.Comment: 12 pages, 4 figure

CFGPT: Chinese Financial Assistant with Large Language Model

Large language models (LLMs) have demonstrated great potential in natural language processing tasks within the financial domain. In this work, we present a Chinese Financial Generative Pre-trained Transformer framework, named CFGPT, which includes a dataset~(CFData) for pre-training and supervised fine-tuning, a financial LLM~(CFLLM) to adeptly manage financial texts, and a deployment framework~(CFAPP) designed to navigate real-world financial applications. The CFData comprising both a pre-training dataset and a supervised fine-tuning dataset, where the pre-training dataset collates Chinese financial data and analytics, alongside a smaller subset of general-purpose text with 584M documents and 141B tokens in total, and the supervised fine-tuning dataset is tailored for six distinct financial tasks, embodying various facets of financial analysis and decision-making with 1.5M instruction pairs and 1.5B tokens in total. The CFLLM, which is based on InternLM-7B to balance the model capability and size, is trained on CFData in two stage, continued pre-training and supervised fine-tuning. The CFAPP is centered on large language models (LLMs) and augmented with additional modules to ensure multifaceted functionality in real-world application. Our codes are released at https://github.com/TongjiFinLab/CFGPT.Comment: 12 pages, 5 figure

Intercropping changed the soil microbial community composition but no significant effect on alpha diversity

IntroductionEnhancing the planning of the forest-agricultural composite model and increasing the efficiency with which forest land is utilized could benefit from a thorough understanding of the impacts of intercropping between forests and agriculture on soil physicochemical properties and microbial communities.MethodsPopulus cathayana × candansis cv. Xinlin No.1 and Glycine max intercrop soils, along with their corresponding monocrops, were used in this study’s llumina high-throughput sequencing analysis to determine the composition and diversity of soil bacterial and fungal communities.ResultsThe findings indicated that intercropping considerably raised the soil’s total phosphorus content and significantly lowered the soil’s carbon nitrogen ratio when compared to poplar single cropping. Furthermore, the total carbon and nitrogen content of soil was increased and the soil pH was decreased. The sequencing results showed that intercropping had no significant effect on soil alpha diversity. Intercropping could increase the composition of fungal community and decrease the composition of bacterial community in poplar soil. At the phylum level, intercropping significantly increased the relative abundance of four dominant phyla, i.e., Patescibacteria, Proteobacteria, Patescibacteria and Deinococcus-Thermus. And the relative abundances of only two dominant phyla were significantly increased. It was found that soil total phosphorus and available phosphorus content had the strongest correlation with soil bacterial community diversity, and soil pH had the strongest correlation with soil fungal community diversity.DiscussionThe results of this study were similar to those of previous studies. This study can serve as a theoretical foundation for the development of a poplar and black bean-based forest-agricultural complex management system in the future

Genome-Wide Identification of NAC Transcription Factor Family in Juglans mandshurica and Their Expression Analysis during the Fruit Development and Ripening

The NAC (NAM, ATAF and CUC) gene family plays a crucial role in the transcriptional regulation of various biological processes and has been identified and characterized in multiple plant species. However, genome-wide identification of this gene family has not been implemented in Juglans mandshurica, and specific functions of these genes in the development of fruits remain unknown. In this study, we performed genome-wide identification and functional analysis of the NAC gene family during fruit development and identified a total of 114 JmNAC genes in the J. mandshurica genome. Chromosomal location analysis revealed that JmNAC genes were unevenly distributed in 16 chromosomes; the highest numbers were found in chromosomes 2 and 4. Furthermore, according to the homologues of JmNAC genes in Arabidopsis thaliana, a phylogenetic tree was constructed, and the results demonstrated 114 JmNAC genes, which were divided into eight subgroups. Four JmNAC gene pairs were identified as the result of tandem duplicates. Tissue-specific analysis of JmNAC genes during different developmental stages revealed that 39 and 25 JmNAC genes exhibited upregulation during the mature stage in walnut exocarp and embryos, indicating that they may serve key functions in fruit development. Furthermore, 12 upregulated JmNAC genes were common in fruit ripening stage in walnut exocarp and embryos, which demonstrated that these genes were positively correlated with fruit development in J. mandshurica. This study provides new insights into the regulatory functions of JmNAC genes during fruit development in J. mandshurica, thereby improving the understanding of characteristics and evolution of the JmNAC gene family

Endophytic Communities of Transgenic Poplar Were Determined by the Environment and Niche Rather Than by Transgenic Events

Microbial communities associated with plants represent key determinants of plant health, survival, and growth. However, a good understanding of the structural composition of the bacterial and fungal microbiome present in different plant tissues and growing environments, especially in transgenic woody plants, is required. In the present study, we hypothesized that environmental conditions, ecological niches, and transgenic events could influence the community structure of plant-associated microorganisms (bacterial and fungal endophytes). We sampled the root and stem endospheres of field-grown transgenic and non-transgenic poplar trees (Populus alba × P. berolinensis) and applied 16S rRNA and internal transcribed spacer amplicon Illumina MiSeq sequencing to determine the bacterial and fungal communities associated with the different plant habitats and tissues. We found that actinobacteria, proteobacteria, bacteroidetes, and firmicutes were the dominant endophytic bacteria, and the fungal community was dominated by dothideomycetes, agaricomycetes, leotiomycetes, and sordariomycetes. In conclusion, transgenic events did not affect the endophytic bacterial and fungal diversity of poplar trees. The bacterial and fungal community structure depends on the pH and the soil organic matter content. Each plant tissue represents a unique ecological niche for the microbial communities. Finally, we identified the indicator operational taxonomic units (OTUs) and core microbiome associated with the different plant tissues of Populus and different environmental conditions. The results provide a basis for further study of host-microbial interactions with the identified abundant OTUs of Populus

Differences in phyllosphere microbiomes among different Populus spp. in the same habitat

IntroductionThe above-ground parts of terrestrial plants are collectively known as the phyllosphere. The surface of the leaf blade is a unique and extensive habitat for microbial communities. Phyllosphere bacteria are the second most closely associated microbial group with plants after fungi and viruses, and are the most abundant, occupying a dominant position in the phyllosphere microbial community. Host species are a major factor influencing the community diversity and structure of phyllosphere microorganisms.MethodsIn this study, six Populus spp. were selected for study under the same site conditions and their phyllosphere bacterial community DNA fragments were paired-end sequenced using 16S ribosomal RNA (rRNA) gene amplicon sequencing. Based on the distribution of the amplicon sequence variants (ASVs), we assessed the alpha-diversity level of each sample and further measured the differences in species abundance composition among the samples, and predicted the metabolic function of the community based on the gene sequencing results.ResultsThe results revealed that different Populus spp. under the same stand conditions resulted in different phyllosphere bacterial communities. The bacterial community structure was mainly affected by the carbon and soluble sugar content of the leaves, and the leaf nitrogen, phosphorus and carbon/nitrogen were the main factors affecting the relative abundance of phyllosphere bacteria.DiscussionPrevious studies have shown that a large proportion of the variation in the composition of phyllosphere microbial communities was explained by the hosts themselves. In contrast, leaf-borne nutrients were an available resource for bacteria living on the leaf surface, thus influencing the community structure of phyllosphere bacteria. These were similar to the conclusions obtained in this study. This study provides theoretical support for the study of the composition and structure of phyllosphere bacterial communities in woody plants and the factors influencing them