Tribological Performance of Different Concentrations of Al_(2)O_(3)Nanofluids on Minimum Quantity Lubrication Milling

Nanofluid minimum quantity lubrication(NMQL)is a green processing technology.Cottonseed oil is suitable as base oil because of excellent lubrication performance,low freezing temperature,and high yield.Al_(2)O_(3)nanoparticles improve not only the heat transfer capacity but also the lubrication performance.The physical and chemical proper-ties of nanofluid change when Al_(2)O_(3)nanoparticles are added.However,the effects of the concentration of nanofluid on lubrication performance remain unknown.Furthermore,the mechanisms of interaction between Al_(2)O_(3)nanoparti-cles and cottonseed oil are unclear.In this research,nanofluid is prepared by adding different mass concentrations of Al_(2)O_(3)nanoparticles(0,0.2%,0.5%,1%,1.5%,and 2%wt)to cottonseed oil during minimum quantity lubrication(MQL)milling 45 steel.The tribological properties of nanofluid with different concentrations at the tool/workpiece interface are studied through macro-evaluation parameters(milling force,specific energy)and micro-evaluation parameters(surface roughness,micro morphology,contact angle).The result show that the specific energy is at the minimum(114 J/mm^(3)),and the roughness value is the lowest(1.63μm)when the concentration is 0.5 wt%.The surfaces of the chip and workpiece are the smoothest,and the contact angle is the lowest,indicating that the tribological proper-ties are the best under 0.5 wt%.This research investigates the intercoupling mechanisms of Al_(2)O_(3)nanoparticles and cottonseed base oil,and acquires the optimal Al_(2)O_(3)nanofluid concentration to receive satisfactory tribological properties.

Multidimensional defects tailoring local electron and Mg^(2+) diffusion channels for boosting magnesium storage performance of WO_(3)/MoO_(2)

Defect engineering presents great promise in addressing lower specific capacity,sluggish diffusion kinetics and poor cycling life issues in energy storage devices.Herein,multidimensional(0D/2D/3D) structural defects are constructed in WO_(3)/MoO_(2) simultaneously via competing for and sharing with O atoms during simple hydrothermal process.OD and 2D defects tailor local electron,activating more sites and generating built-in electric fields to yield ion reservoir,meanwhile,3D defect owning lower anisotropic property tailors Mg^(2+) diffusion channels to fully exploit Mg^(2+) adsorbed sites induced by OD and 2D defects,enhance the kinetics and maintain structural stability.Benefitted from synergistic effect of 0D/2D/3D structural defects,the designed WO_(3)/MoO_(2) shows the higher specific capacity(112.8 mA h g^(-1) at 50 mA g^(-1) with average attenuation rate per cycle of 0.068%),superior rate capability and excellent cycling stability(specific capacity retention of 80% after 1500 cycles at 1000 mA g^(-1)).This strategy provides design ideas of introducing multidimensional structural defects for tailoring local electron and microstructure to improve energy storage property.

Research on Multi-Blockchain Electronic Archives Sharing Model

The purpose of introducing blockchain into electronic archives sharing and utilization is to break the information barrier between electronic archives sharing departments by relying on technologies such as smart contract and asymmetric encryption.Aiming at the problem of dynamic permission management in common access control methods,a new access control method based on smart contract under blockchain is proposed,which improves the intelligence level under blockchain technology.Firstly,the Internet attribute access control model based on smart contract is established.For the dynamic access of heterogeneous devices,the management contract,permission judgment contract and access control contract are designed;Secondly,the access object credit evaluation algorithm based on particle swarm optimization radial basis function(PSO-RBF)neural network is used to dynamically generate the access node credit threshold combined with the access policy,so as to realize the intelligent access right management method.Finally,combined with the abovemodels and algorithms,the workflow of electronic archives sharing and utilization model of multi blockchain is constructed.The experimental results show that the timeconsuming of the process increases linearly with the number of continuous access to electronic archives blocks,and the secure access control of sharing and utilization is feasible,secure and effective.

Customer Churn Prediction Framework of Inclusive Finance Based on Blockchain Smart Contract

In view of the fact that the prediction effect of influential financial customer churn in the Internet of Things environment is difficult to achieve the expectation,at the smart contract level of the blockchain,a customer churn prediction framework based on situational awareness and integrating customer attributes,the impact of project hotspots on customer interests,and customer satisfaction with the project has been built.This framework introduces the background factors in the financial customer environment,and further discusses the relationship between customers,the background of customers and the characteristics of pre-lost customers.The improved Singular Value Decomposition(SVD)algorithm and the time decay function are used to optimize the search and analysis of the characteristics of pre-lost customers,and the key index combination is screened to obtain the data of potential lost customers.The framework will change with time according to the customer’s interest,adding the time factor to the customer churn prediction,and improving the dimensionality reduction and prediction generalization ability in feature selection.Logistic regression,naive Bayes and decision tree are used to establish a prediction model in the experiment,and it is compared with the financial customer churn prediction framework under situational awareness.The prediction results of the framework are evaluated from four aspects:accuracy,accuracy,recall rate and F-measure.The experimental results show that the context-aware customer churn prediction framework can be effectively applied to predict customer churn trends,so as to obtain potential customer data with high churn probability,and then these data can be transmitted to the company’s customer service department in time,so as to improve customer churn rate and customer loyalty through accurate service.

Practical Progress of SBAR Communication Model-Related Teaching in Clinical Teaching

This paper elaborates the core and essence of situation,background,assessment,recommendation(SBAR)communication model,clarify the application status of SBAR communication model in the clinical teaching of nursing students,and describe its effectiveness and limitations,so as to provide reference for improving clinical nursing teaching ability.

The Latest Research Progress in the Application of MEWS Scoring System in Clinical Nursing

This paper summarizes the background of the formation of the Modified Early Warning System(MEWS)evaluation system,its current status of clinical teaching applications in different fields of hospitals,and its significance on the medical and nursing career,aiming to provide specific theoretical basis for medical staff and lay a foundation for continuing to carry out related work on MEWS.

Plant distribution and pharmacological activity of flavonoids

Flavonoids are natural organic compounds that are widely found in nature, their structural types are complex, and they mainly include flavonoids, flavonols, dihydroflavonols, isoflavones, dihydroisoflavones, chalcones, orange ketones, flavanoids, anthocyanidins, and biflavonoids. This review covers the plant distribution and pharmacological activities of flavonoids. Flavonoids are mainly distributed in angiosperms and gymnosperms, and they are abundant in plants such as Rutaceae, Labiatae, Zingiberaceae, Scrophulariaceae, and Leguminosae. Because of their wide distribution and variety, researchers have found that flavonoids have diverse biological activities, mainly focusing on anti-inflammatory, antibacterial and antitumor activities. Mechanistically, the anti-inflammatory effects are mainly related to the NF-κB and MAPK (mitogen-activated protein kinase) signaling pathway and then the inhibition of the production of inflammatory cytokines and mediators. The antibacterial activity is mainly manifested as inhibitory effects on many strains, including Escherichia coli, Cryptococcus neoformans, and Pseudomonas aeruginosa, via destroying the stability of the microbial membrane, inhibiting the invasion of virulent bacteria into host cells, promoting the apoptosis of bacteria, inhibiting bacterial fatty acid synthesis, etc. The antitumor activity of flavonoids is related to their inhibition of cell proliferation and induction of apoptosis via the mitochondria-mediated, endoplasmic reticulum-mediated, and death factor and its receptor-mediated signal transduction pathways. Understanding the plant distribution and pharmacological activity of flavonoids not only reveals the importance of identifying such valuable flavonoids in another genus or family but also provides a basis for fully exploiting the therapeutic potential of flavonoids.

Research on Hybrid Model of Garlic Short-term Price Forecasting based on Big Data

Garlic prices fluctuate dramatically in recent years and it is very difficult to predict garlic prices.The autoregressive integrated moving average(ARIMA)model is currently the most important method for predicting garlic prices.However,the ARIMA model can only predict the linear part of the garlic prices,and cannot predict its nonlinear part.Therefore,it is urgent to adopt a method to analyze the nonlinear characteristics of garlic prices.After comparing the advantages and disadvantages of several major prediction models which used to forecast nonlinear time series,using support vector machine(SVM)model to predict the nonlinear part of garlic prices and establish ARIMA-SVM hybrid forecast model to predict garlic prices.The monthly average price data of garlic in 2010-2017 was used to test the effect of ARIMA model,SVM model and ARIMA-SVM model.The experimental results show that:(1)Garlic price is affected by many factors but the most is the supply and demand relationship;(2)The SVM model has a good effect in dealing with the nonlinear relationship of garlic prices;(3)The ARIMA-SVM hybrid model is better than the single ARIMA model and SVM model on the accuracy of garlic price prediction,it can be used as an effective method to predict the short-term price of garlic.

Network Security Situation Awareness Framework based on Threat Intelligence

Network security situation awareness is an important foundation for network security management,which presents the target system security status by analyzing existing or potential cyber threats in the target system.In network offense and defense,the network security state of the target system will be affected by both offensive and defensive strategies.According to this feature,this paper proposes a network security situation awareness method using stochastic game in cloud computing environment,uses the utility of both sides of the game to quantify the network security situation value.This method analyzes the nodes based on the network security state of the target virtual machine and uses the virtual machine introspection mechanism to obtain the impact of network attacks on the target virtual machine,then dynamically evaluates the network security situation of the cloud environment based on the game process of both attack and defense.In attack prediction,cyber threat intelligence is used as an important basis for potential threat analysis.Cyber threat intelligence that is applicable to the current security state is screened through the system hierarchy fuzzy optimization method,and the potential threat of the target system is analyzed using the cyber threat intelligence obtained through screening.If there is no applicable cyber threat intelligence,using the Nash equilibrium to make predictions for the attack behavior.The experimental results show that the network security situation awareness method proposed in this paper can accurately reflect the changes in the network security situation and make predictions on the attack behavior.

Invariance of Painlev property for some reduced (1+1)-dimensional equations

We study the Painlevé property of the （1＋1）-dimensional equations arising from the symmetry reduction for the （2＋1）- dimensional ones. Firstly, we derive the similarity reduction of the （2＋1）-dimensional potential Calogero-Bogoyavlenskii- Schiff （CBS） equation and Konopelchenko-Dubrovsky （KD） equations with the optimal system of the admitted one-dimensional subalgebras. Secondly, by analyzing the reduced CBS, KD, and Burgers equations with Painlevé test, re-spectively, we find both the Painlevé integrability, and the number and location of resonance points are invariant, if the similarity variables include all of the independent variables.

Annual advances of Chinese minority traditional medicine in 2019

Traditional medicine systems practiced by various ethnic minorities represent an important part of traditional Chinese medicine.The past 12 months have witnessed extensive research pertaining to different Chinese minority traditional medicine(CMTM).The annual CMTM review evaluates research published during 2019 in different CMTM including Tibetan medicine,Uyghur medicine,Mongolian medicine,Korean medicine and Zhuang medicine.Research in the field of Tibetan medicine focused on pharmacology,pharmacy,plant sciences,medicinal chemistry and integrated complementary medicine and the top three countries were China,USA and India.Research in Uyghur medicine mainly pertained to chemistry,pharmacology,pharmacy,and food science technology and the publications were mainly from China.Research in Mongolian medicine mainly pertained to pharmacology,pharmacy,analytical chemistry,biochemistry,molecular biology and experimental research;the publications were mainly from China and Mongolia.In short,research related to traditional medicine of various ethnic minorities was mainly conducted in China and the neighboring countries.The research focus for each minority medicine is essentially on the effects and mechanisms of action of the active ingredients of the ethnodrugs and the special prescriptions or therapies.The generated evidence will facilitate further developments in this field.

Research on the Relationship Between Garlic and Young GarlicShoot Based on Big Data

In view of the problems such as frequent fluctuation of garlic price, lack ofefficient forecasting means and difficulty in realizing the steady development of garlicindustry, combined with the current situation of garlic industry and the collected datainformation. Taking Big Data platform of garlic industry chain as the core, using themethods of correlation analysis, smoothness test, co-integration test, and Grangercausality test, this paper analyzes the correlation, dynamic, and causality between garlicprice and young garlic shoot price. According to the current situation of garlic industry,the garlic industry service based on Big Data is put forward. It is concluded that there is apositive correlation between garlic price and young garlic shoot price, and there is a longtermstable dynamic equilibrium relationship between young garlic shoot price and garlicprice fluctuation, and young garlic shoot price can affect garlic price. Finally, it isproposed to strengthen the infrastructure construction of garlic Big Data, increase thetechnological innovation and application of garlic Big Data technology, and promote thesafety and security ability of the whole industry to promote the development of garlicindustry.

MMLUP: Multi-Source & Multi-Task Learning for User Profiles in Social Network

With the rapid development of the mobile Internet,users generate massive data in different forms in social network every day,and different characteristics of users are reflected by these social media data.How to integrate multiple heterogeneous information and establish user profiles from multiple perspectives plays an important role in providing personalized services,marketing,and recommendation systems.In this paper,we propose Multi-source&Multi-task Learning for User Profiles in Social Network which integrates multiple social data sources and contains a multi-task learning framework to simultaneously predict various attributes of a user.Firstly,we design their own feature extraction models for multiple heterogeneous data sources.Secondly,we design a shared layer to fuse multiple heterogeneous data sources as general shared representation for multi-task learning.Thirdly,we design each task’s own unique presentation layer for discriminant output of specific-task.Finally,we design a weighted loss function to improve the learning efficiency and prediction accuracy of each task.Our experimental results on more than 5000 Sina Weibo users demonstrate that our approach outperforms state-of-the-art baselines for inferring gender,age and region of social media users.

Characterization of Turbot(Scophthalmus maximus) Skin and the Extracted Acid-Soluble Collagen

The biochemical composition of the turbot skin was investigated. The moisture level of the skin was found to be 51.4%. Based on dry matter content, there were relatively high protein(82.1%) and lipid(13.1%) concentrations in the turbot skin. Mineral element analysis revealed that the turbot skin had high Ca content(2069.0 mg kg^-1), and the concentrations of toxic heavy metals Hg and Pb were less than 0.005 mg kg^-1, which indicates that the turbot skin is a safe resource for collagen production. The sodium dodecyl sulfate-polyacrylamide gel electrophoresis(SDS-PAGE) analysis showed that acid-soluble collagen(ASC) extracted from the turbot skin was type-I collagen. The imino acid content of the ASC was 241.6 per 1000 amino acids, which suggests a relatively high denaturation temperature. The Fourier transform infrared(FTIR) spectra of ASC reflected a highly stable structure, and the measured denaturation temperature of ASC was 29.5℃, which is higher than those from many temperate fishes. ASC was the most soluble at pH 4.0, and when the pH values were below or above 4.0, the solubility decreased rapidly. The ASC exhibited a relatively high solubility when NaCl concentration was lower than 2%. These results show that turbo skin can be employed as a source for producing collagen with high quality.

Annual advances of Chinese minority traditional medicine in 2020

Chinese minority traditional medicine is a traditional medicine formed during the long-term medical practice of various ethnic groups and is the crystallization of the wisdom of the people in all ethnic groups in China.The unique meaning carried by Chinese minority traditional medicine makes it an inseparable and important part of traditional Chinese medicine.The rich clinical experience and theoretical studies with different Chinese minority traditional medicine provide new ideas and new methods for Chinese medicine development.The pieces of literature published in 2020 on the traditional application analyzed the phytochemical composition,pharmacological effects,and mechanisms of the different ethnic groups including Tibetan,Mongolian,Zhuang,Dai,and Uyghur medicines,among others.This study found that some projects were stalled or delayed due to the coronavirus disease 2019 outbreak in 2020 compared with 2019,resulting in a decrease in the number of articles in certain fields.However,studied on Chinese minority traditional medicine have shown an overall upward trend this year with the Tibetan,Mongolian,and Dai medicines as the top three.In addition,the Chinese minority traditional medicine application under the coronavirus disease 2019 epidemic situation background was also summarized.Consequently,this study found that among the Chinese minority traditional medicine-related publications in 2020,publications using Chinese minority traditional medicine to treat coronavirus disease 2019 account for a certain percentage.Thus,this article systematically reviews and summarizes the related research of Chinese minority traditional medicine published in 2020 and provides references for future Chinese minority traditional medicine development.

Development and Application of Big Data Platform for Garlic Industry Chain

In order to effectively solve the problems which affect the stable and healthy development of garlic industry,such as the uncertainty of the planting scale and production data,the influence factors of price fluctuation is difficult to be accurately analyzed,the difficult to predict the trend of price change,the uncertainty of the market concentration,and the difficulty of the short-term price prediction etc.the big data platform of the garlic industry chain has been developed.Combined with a variety of data acquisition technology,the information collection of influencing factors for garlic industry chain is realized.Based on the construction of the big data technology platform,the real-time synchronous acquisition,efficient storage and analysis of the planting,market,storage,processing,export and logistics information in five provinces and seven counties are realized.The application of the big data platform for garlic industry chain has realized the accurate acquisition of garlic planting area,the price and trend of market circulation and the information of export information,analyzed the fluctuation regulation of garlic price,and also realized the short-term precision prediction of garlic price.

Analysis of Hongdao Clam Industrial Structure Based on Industry Chain

The vertical and transverse structures of Hongdao clam industry are described and analyzed objectively based on the perspective of industry chain. On the basis of field investigation,the key nodes of Hongdao clam industry chain,including nursery,breeding,processing,transportation and sale,are analyzed. It can be concluded that the development of clam industry chain is unbalanced,especially the deep-processing capacity is not strong,and the development of supporting industy lags behind. The horizontal industry chain of clam needs to be further improved. The corresponding suggestions are put forward: strengthening research on new nursery technology in later period,further extending the horizontal industry chain of clam,mining the depth of clam-related leisure industry,and upgrading service level of leisure travel.

Research hotspots and trends in Chinese minority traditional medicine during 2021:a visual bibliometrics analysis

Background:Chinese minority traditional medicine(CMTM)is an important component of Chinese traditional culture and medicine that has contributed to the health and prosperity of Chinese people of all ethnic groups.Although this type of medicine has attracted interest,its developmental trends and research status remain unclear.Therefore,we used literature metrology to evaluate the publications on CMTM during 2021 and explore hotspots and frontier areas.Methods:Reports associated with CMTM published between January 1,2021,and December 31,2021,were downloaded from the Web of Science database.The authors,institutions,countries,journals,keywords,and other standard bibliometric indicators were analyzed and visualized using CiteSpace,and research hotspots and trends were identified.Results:We retrieved 152 CMTM-related publications,among which Tibetan medicine attracted the most interest.Journals covering alternative and complementary medicine topics were the most prevalent sources of reports about CMTM,particularly the Journal of Ethnopharmacology.Most research in this field was conducted in China and frequently published by traditional Chinese medicine colleges and universities.One author,Yi Zhang,has extensively investigated Tibetan and Korean medicine.The keyword co-occurrence network revealed that investigations into ethnic groups mainly focused on the pharmacological activities and phytochemical components of ethnic medicines.The keywords of gut microbiota and autophagy in some publications reflect the direction of future CMTM investigations.Conclusion:Our findings showed the current status and trends in CMTM investigations.This information will help identify new research directions and hotspots in this field.

Effects of nonlinear strength parameters on stability of 3D soil slopes

Actual slope stability problems have three-dimensional(3D) characteristics and the soils of slopes have curved failure envelopes. This incorporates a power-law nonlinear failure criterion into the kinematic approach of limit analysis to conduct the evaluation of the stability of 3D slopes. A tangential technique is adopted to simplify the nonlinear failure criterion in the form of equivalent Mohr-Coulomb strength parameters. A class of 3D admissible rotational failure mechanisms is selected for soil slopes including three types of failure mechanisms: face failure, base failure, and toe failure. The upper-bound solutions and corresponding critical slip surfaces can be obtained by an efficient optimization method. The results indicate that the nonlinear parameters have significant influences on the assessment of slope stability, especially on the type of failure mechanism. The effects of nonlinear parameters appear to be pronounced for gentle slopes constrained to a narrow width. Compared with the solutions derived from plane-strain analysis, the 3D solutions are more sensitive to the values of nonlinear parameters.

测度空间上的Lévy-Prohorov距离（英文）

Under the premise of infinitely many pure strategies, by defining the new LP* metric, striking an equivalence of topology and weak* topology, we prove that the existence of the essential component.