Analysis of Human Interactive Accounting Management Information Systems Based on Artificial Intelligence

BACKGROUND: With the gradual improvement of market economy, people' s consumption level is constantly improving, and the quality requirements are getting higher and higher. OBJECTIVES: In order to study the management accounting information analysis platform based on Artificial Intelligence (AI) and realize the goal of accounting computerization, the application of AI in expert system is applied to the field of accounting information analysis. METHODS: The combination of subsystems is applied to the construction of AI accounting information Web system, and the feasibility analysis of its theory and technology is carried out. RESULTS: The results show that its effect is obvious: accelerating the flow of all information and promoting the change of enterprise management mode. Moreover, compared with the traditional system algorithm, the accuracy of the system model is improved by 6% and the time delay is reduced by 9ms, which makes the overall management level of the enterprise further improved, the scope of enterprise competition further expanded, the cost of enterprise saved

Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity

Agent-based modeling is a simulation method in which autonomous agents interact with their environment and one another, given a predefined set of rules. It is an integral method for modeling and simulating complex systems, such as socio-economic problems. Since agent-based models are not described by simple and concise mathematical equations, the code that generates them is typically complicated, large, and slow. Here we present Agents.jl, a Julia-based software that provides an ABM analysis platform with minimal code complexity. We compare our software with some of the most popular ABM software in other programming languages. We find that Agents.jl is not only the most performant but also the least complicated software, providing the same (and sometimes more) features as the competitors with less input required from the user. Agents.jl also integrates excellently with the entire Julia ecosystem, including interactive applications, differential equations, parameter optimization, and so on. This removes any “extensions library” requirement from Agents.jl, which is paramount in many other tools.

Astragalin Ameliorates Cognitive Dysfunction Through Inhibiting PI3K/Akt-MTOR-Mediated Autophagic Flow in Hippocampal Neurons of APP/PS1 Mice

Astragalin (AST), a natural small molecule flavonoid, can exert anti-oxidant, anti-inflammatory and anti-cancer impacts by regulating autophagy. However, the potential mechanism of the neuroprotective effect of AST on neurological disorders such as Alzheimer’s disease (AD) is still not clear. In the present study, we firstly screened AST for the treatment of AD from the ingredients of Chinese medicines such as Acori tataninowii Rhizoma, Eucommiae Cortex, Paeoniae Radix Alba through the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) database. And then we found that AST could improve the cognitive abilities of APP/PS1 mice by Step-down passive avoidance (SDA) and Morris Water Maze (MWM) Test. Further, we identified that AST diminished Aβ plaques deposition in the brains of APP/PS1 mice and Aβ as well as Aβ42 levels in the serum of APP/PS1 mice. Next, microtubule-associated protein 1 light chain 3B (LC3B), p62, Beclin-1, ATG5, ATG12, LAMP-1 were observed to be co-expressed with NeuN in the hippocampus of APP/PS1 mice by immunofluorescent multiplex staining, while AST was able to activate autophagy and maintain autophagic flow in hippocampal neurons of APP/PS1 mice by western blot (WB) analysis. Finally, AST reduced the expressions of p-PI3K, p-Akt, p-mTOR by WB analysis. Taken together, we confirmed that AST may play key neuroprotective effects on APP/PS1 mice by inhibiting the PI3K/Akt-mTOR signaling pathway to activate autophagy and keep autophagic flow smooth.

Design of feasibility analysis platform for college physical education based on mobile social network

In order to promote the development of sports distance network education, a college sports teaching feasibility analysis platform based on mobile social network is designed. The key technologies such as Ajax, database and XML, Java Web containers applied to mobile social networks provide a technical basis for the platform design of this paper. Design the feasibility analysis platform framework using MVC mode, three platform functional modules were designed. Among it, the member function module is responsible for the registration and modification of the platform personal information of members; The feasibility analysis interactive discussion module is based on the cloud database storage and analysis platform user discussion records; The feasibility evaluation module of mobile social network is based on mobile social network, builds the hierarchical model of feasibility analysis and completes the design of feasibility analysis of distance teaching in universities. Experimental performance tested the platform, with an average response time of 2.3 ms and an analysis time of 18 ms. The feasibility analysis results of the platform have high reliability and effectiveness to meet the practical application requirements.

Comparison of Semi-Quantitative Scoring and Artificial Intelligence Aided Digital Image Analysis of Chromogenic Immunohistochemistry

Semi-quantitative scoring is a method that is widely used to estimate the quantity of proteins on chromogen-labelled immunohistochemical (IHC) tissue sections. However, it suffers from several disadvantages, including its lack of objectivity and the fact that it is a time-consuming process. Our aim was to test a recently established artificial intelligence (AI)-aided digital image analysis platform, Pathronus, and to compare it to conventional scoring by five observers on chromogenic IHC-stained slides belonging to three experimental groups. Because Pathronus operates on grayscale 0-255 values, we transformed the data to a seven-point scale for use by pathologists and scientists. The accuracy of these methods was evaluated by comparing statistical significance among groups with quantitative fluorescent IHC reference data on subsequent tissue sections. The pairwise inter-rater reliability of the scoring and converted Pathronus data varied from poor to moderate with Cohen’s kappa, and overall agreement was poor within every experimental group using Fleiss’ kappa. Only the original and converted that were obtained from Pathronus original were able to reproduce the statistical significance among the groups that were determined by the reference method. In this study, we present an AI-aided software that can identify cells of interest, differentiate among organelles, protein specific chromogenic labelling, and nuclear counterstaining after an initial training period, providing a feasible and more accurate alternative to semi-quantitative scoring.

Bibliometric Analysis of the Scientific Literature on Rheumatoid Arthritis-Associated Interstitial Lung Disease

Background. In recent years, the number of studies on rheumatoid arthritis-related interstitial lung disease (RA-ILD) has been increasing, which has led to many publications on this topic. Our purpose is to identify research trends in RA-ILD and analyze the most-cited RA-ILD-related high-quality scientific publications. Methods. All publications on RA-ILD in the Core Collection database of Web of Science were searched. The publication year, country, institution, total citations, and journal were extracted and analyzed. We used VOSviewer software or an online bibliometric analysis platform for cooccurrence analysis of the keywords, institutions, and countries involved. The 100 most frequently cited RA-ILD publications were analyzed. Results. In total, 596 publications related to RA-ILD were obtained. Over time, the frequency of RA-ILD publications has increased. Globally, the United States provides the most publications on RA-ILD ( n = 195 ). The institution with the highest publication output was the Mayo Clinic ( n = 43 ). The journal “Annals of the Rheumatic Diseases” published most with 93 articles and received 338 citations. A clinical description was the most common research topic in RA-ILD-related publications. Conclusions. In recent years, there has been an increasing number of studies on RA-ILD, and related publications have increased rapidly. This study is the first bibliometric study of RA-ILD-related publications. It can be used as a guide for clinicians and can help researchers choose research directions of interest in this field.

Association between rs20456 and rs6930913 of Kinesin-Like Family 6 and Hypertension in a Chinese Cohort

This study aimed to investigate the relationship between kinesin-like family 6 (KIF6) polymorphisms and hypertension in a northeast Chinese cohort. In this study, two single nucleotide polymorphisms of KIF6 (rs20456 and rs6930913) and their haplotype were analyzed in 382 hypertension patients and 378 controls with SHEsis analysis platform, and the gene-environmental interactions were evaluated with logistic regression analysis. After adjusting for confounding factors, significantly lower risk of hypertension was observed in participants with genotype TC (0.416 (CI 0.299–0.578), p < 0.001 ) and CC (0.577 (0.389–0.857), p = 0.007 ) of rs20456 compared with TT. For rs6930913, allele T (0.522 (0.386–0.704), p < 0.001 ), genotype TT (0.325 (0.205–0.515), p < 0.001 ), and genotype CT (0.513 (0.379–0.693), p < 0.001 ) were significantly associated with lower risk of hypertension than allele C and CC genotype, respectively. Gene-environment analyses confirmed the significant influence on hypertension by the interactions between genotypes distribution in rs20456 (CT: p = 0.036 , TT: p = 0.022 ) and smoking status. No interactions were found between smoking and rs6930913, except those with dominant or recessive genetic models (both P s = 0.006 ). There were no interactions between KIF6 and overweight (all P s > 0.05 ). Haplotype analyses showed that CC ( p = 0.005 ) and TC ( p = 0.001 ) of rs20456 and rs6930913 were significantly associated with a statistically increased risk of hypertension. The false-positive report probability (FPRP) analysis was used to verify significant findings. In conclusions, KIF6 might affect the susceptibility of hypertension. The allele C (rs20456) and allele T (rs690913) were inclined to protect individuals from hypertension both in genotype and haplotype analyses.