Study on Daily Accounting Profit Feasibility of Banking Based on Data Center

By the end of 2013, Chinese large-scaled commercial banks have basically completed the construction of IT banking system, in order to provide technical guarantee of deepening business operation and operation management reform. This indicates that our national banking industry information technology has been in a new level. This paper, based on the operation principle of commercial bank safety, liquidity and profitability, makes research on improving commercial banking profit data timeliness, accuracy, integrity and realizing daily accounting profit. According to survey, the four big banks have proposed the prospect of 2013 full scope implementing daily accounting profit. Thus, this paper, based on the profit accounting status of four big banks of data center, analyzes the feasibility of daily accounting profit and puts forward the relevant solutions.

Isolated traumatic orbital floor fracture:An analysis of the National Trauma Data Bank

Objectives:To date,no study provides a comprehensive analysis of traumatic orbital floor fractures across the United States.We aimed to characterize patient demographics,injury-related variables,and operative management in this population.Method:The National Trauma Data Bank was queried for open or closed orbital floor fractures from 2008 to 2016.Clinical data were extracted.Results:Overall,148,592 orbital floor fractures were identified,with 142,577(95.9%)closed-and 6158(4.1%)open-type fractures.A total of 106,243(71.5%)patients were male and the median patient age was 41 years.The majority of patients(79.2%)had abbreviated injury scale scores of≤2,indicating minor/moderate injury.Fracture mechanism of injury(MOI)differed by gender,with the most frequent being unarmed fights in men(34.3%)and falls in women(14.0%).There were 29,600 patients(19.9%)with isolated orbital floor(I-OF)fractures.The MOI most strongly associated with operative intervention of with I-OF fractures were penetrating injuries caused by a firearm(odds ratio[OR]:2.91;95%confidence interval[CI]:1.62–5.20)and cuttings/piercings(OR:2.17;95%CI:1.29–3.65).Conclusion:This large epidemiological study reveals that orbital floor fractures tend to present with minor or moderate injuries and are more likely to require operative intervention in setting of firearm or cut/pierce injuries.

Identification of distant co-evolving residues in antigen 85C from Mycobacterium tuberculosis using statistical coupling analysis of the esterase family proteins

A fundamental goal in cellular signaling is to understand allosteric communication, the process by which sig-nals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Statistical coupling analysis （SCA） is a statistical technique that uses evolutionary data of a protein family to measure correlation between distant functional sites and suggests allosteric communication. In proteins, very distant and small interactions between collections of amino acids provide the communication which can be important for signaling process. In this paper, we present the SCA of protein alignment of the esterase family （pfam ID： PF00756） containing the sequence of antigen 85C secreted by Mycobacterium tuberculosis to identify a subset of interacting residues. Clustering analysis of the pairwise correlation highlighted seven important residue positions in the esterase family alignments. These resi-dues were then mapped on the crystal structure of antigen 85C （PDB ID： 1DQZ）. The mapping revealed corre-lation between 3 distant residues （Asp38, Leu123 and Met125） and suggests allosteric communication between them. This information can be used for a new drug against this fatal disease.

Computational Analyses of Docosahexaenoic Acid (DHA, C22:6, n-3) with Alzheimer’s Disease-Causing Amyloid Peptide Aβ1-42 Reassures Its Therapeutic Utility

The accumulation of amyloid β peptide1-42 (Aβ1-42) masses in the brains of Alzheimer’s Disease (AD) patients is associated with neuronal loss and memory deficits. We have previously reported that oral administration of docosahexaenoic acid (DHA, C22:6, n-3) significantly decreases Aβ burden in the brains of AD model rats and that direct in vitro incubation of DHA with Aβ1-42 curbs the progression of amyloid fibrillation. In the present in silico study, we investigated whether DHA computationally binds with amyloid peptides. The NMR solution structures of Aβ1-42 were downloaded from the Protein Data Bank (PDB IDs: 1Z0Q and 2BEG). The binding of DHA to Aβ peptides was assessed by molecular docking using both a flexible and rigid docking system. Thioflavin T (ThT) was used as positive control. The chemical structures of ThT and DHA were modeled and converted to the PDB format using PRODRUG. Drug-like properties of DHA were evaluated by ADME (Absorption, Distribution, Metabolism, and Excretion). DHA was found to successfully dock with Aβ1-42. Computational analyses of the binding of DHA to Aβ1-42, as evaluated by docking studies, further corroborated the inhibitory effect of DHA on in vitro Aβ1-42 fibrillogenesis and might explain the in vivo reduction of amyloid burden observed in the brains of DHA-administered AD model rats demonstrated in our previous study. These computational data suggest the potential utility of DHA as a preventive medication in Aβ-induced neurodegenerative diseases, including AD.

Blockchain application in healthcare service mode based on Health Data Bank

Blockchain is commonly considered a potentialdisruptive technology. Moreover, the healthcareindustry has experienced rapid growth in the adoption ofhealth information technology, such as electronic healthrecords and electronic medical records. To guarantee dataprivacy and data security as well as to harness the value ofhealth data, the concept of Health Data Bank (HDB) isproposed. In this study, HDB is defined as an integratedhealth data service institution, which bears no “ownership”of health data and operates health data under the principalagentmodel. This study first comprehensively reviews themain characters of blockchain and identifies the blockchain-based healthcare industry projects and startups in theareas of health insurance, pharmacy, and medical treatment.Then, we analyze the fundamental principles ofHDB and point out four challenges faced by HDB’ssustainable development: (1) privacy protection andinteroperability of health data;(2) data rights;(3) healthdata supervision;(4) and willingness to share health data.We also analyze the important benefits of blockchainadoption in HDB. Furthermore, three application scenariosincluding distributed storage of health data, smart-contractbasedhealthcare service mode, and consensus-algorithmbasedincentive policy are proposed to shed light on HDBbasedhealthcare service mode. In the end, this study offersinsights into potential research directions and challenges.

Bank transaction data modeling by optimized hybrid machine learning merged with ARIMA

The bank transactions are needed to be modeled to predict the future transactions of the banks based on the previous transactions.In order to achieve efficient modeling of bank data transactions,Deep Belief Network(DBN)and Neural network(NN)classifiers are used in this paper.Initially,the bank transaction data such as transaction count and amount are subjected to feature extraction to extract the statistical features.Now,the extracted data are modeled using the combination of DBN and NN models,where the average modeled output from both the network is considered as the final result.The above procedure is utilized for the two prediction models such as transaction count and transaction amount.Moreover,the transaction count from prediction model 1 is subjected to the Auto-Regressive Integrated Moving Average(ARIMA)model to compute the relationship between the transition count and transition amount.Here,as the main contribution,the number of hidden neurons in both DBN and NN are optimized or tuned accurately using the hybridized optimization models with Lion Algorithm(LA),and Artificial Bee Colony(ABC)named L-ABC model.The average of entire transactional amounts,i.e.the modeled outputs are matched with the actual data to validate the performance of the implemented model.