Effect of auricular acupoint sticking and pressing on postoperative pain of patients with mixed hemorrhoids:A Meta-analysis

Objective:To systematically evaluate the application effect of auricular acupuncture in postoperative analgesia in patients with mixed hemorrhoids.Methods:We searched Chinese Biomedical Literature Database,CNKI,WanFang,PubMed,Embase,and The Cochrane Library to collect randomized controlled trials about auricular acupuncture on Postoperative patients with mixed hemorrhoids.According to the inclusion criteria and exclusion criteria screening literature.RevMan 5.3 software was used for meta-analysis.Results:A total of 20 articles and 21 studies were included,including 1999 patients after mixed hemorrhoids.The control group was treated with routine nursing analgesia.The experimental group was treated with auricular acupressure beans based on the control group.The meta-analysis showed that the pain relief rate of the experimental group was better than that of the control group[OR=2.84,95%CI(2.12,3.80),P<0.05].Subgroup analysis showed that the application of auricular acupressure after milligan morgan was superior to the control group in the analgesic effect[OR=3.68,95%CI(2.62,5.18),P<0.05],but it is not yet possible to apply auricular acupoint pressing to relieve pain after Stapler hemorrhoidectomy(P>0.05).The pain scores of 24 hours and 48 hours after operation in the experimental group were lower than those of the control group,indicating that auricular acupoint sticking can relieve the pain after operation.The improvement of the postoperative anal margin edema was better in the experimental group than in the control group,24 h[SMD=-1.99,95%CI(-2.84,-1.14),P<0.05],48 h[SMD=-1.92,95%CI(-2.72,-1.11),P<0.05].The adverse reactions were lower than the control group.Conclusion:The application of ear acupoint pressure pea after external exfoliation of mixed hemorrhoids can improve the analgesic effect and reduce the symptoms of postoperative anal edge edema,and the price is low,the operation is convenient,and the side effects are few.It is recommended to be popularized in clinical practice.

Data-based flatness prediction and optimization in tandem cold rolling

In cold rolling process,the flatness actuator efficiency is the basis of the flatness control system.The precision of flatness is determined by the setpoints of flatness actuators.In the presence of modeling uncertainties and unmodeled nonlinearities in rolling process,it is difficult to obtain efficiency factors and setpoints of flatness actuators accurately.Based on the production data,a method to obtain the flatness actuator efficiency by using partial least square(PLS)combined with orthogonal signal correction(OSC)was adopted.Compared with the experiential method and principal component analysis method,the OSC-PLS method shows superior performance in obtaining the flatness actuator efficiency factors at the last stand.Furthermore,kernel partial least square combined with artificial neural network(KPLS-ANN)was proposed to predict the flatness values and optimize the setpoints of flatness actuators.Compared with KPLS or ANN,KPLS-ANN shows the best predictive ability.The root mean square error,mean absolute error and mean absolute percentage error are 0.51 IU,0.34 IU and 0.09,respectively.After the setpoints of flatness actuators are optimized,KPLS-ANN shows better optimization ability.The result in an average flatness standard deviation is 2.22 IU,while the unoptimized value is 4.10 IU.

A leakage-resilient certificateless public key encryption scheme with CCA2 security

In recent years,much attention has been focused on designing provably secure cryptographic primitives in the presence of key leakage.Many constructions of leakage-resilient cryptographic primitives have been proposed.However,for any polynomial time adversary,most existing leakage-resilient cryptographic primitives cannot ensure that their outputs are random,and any polynomial time adversary can obtain a certain amount of leakage on the secret key from the corresponding output of a cryptographic primitive.In this study,to achieve better performance,a new construction of a chosen ciphertext attack 2(CCA2)secure,leakage-resilient,and certificateless public-key encryption scheme is proposed,whose security is proved based on the hardness of the classic decisional Diffie-Hellman assumption.According to our analysis,our method can tolerate leakage attacks on the private key.This method also achieves better performance because polynomial time adversaries cannot achieve leakage on the private key from the corresponding ciphertext,and a key leakage ratio of 1/2 can be achieved.Because of these good features,our method may be significant in practical applications.

Putative zeatin O-glucosyltransferase OscZOG1 regulates root and shoot development and formation of agronomic traits in rice

As a ubiquitous reaction, glucosylation controls the bioactivity of cytokinins in plant growth and development. Here we show that genetic manipulation of zeatin-O- glucosylation regulates the formation of important agronomic traits in rice by manipulating the expression of OscZOG1 gene, encoding a putative zeatin O-glucosyltransferase. We found that OscZOG~ was preferentially expressed in shoot and root meristematic tissues and nascent organs. The growth of lateral roots was stimulated in the overexpression lines, but inhibited in RNA interference lines. In shoots, knockdown of OscZOG1 expression by RNA interference significantly im- proved tillering, panicle branching, grain number per panicle and seed size, which are important agronomic traits for grain yield. In contrast, constitutive expression of OscZOG1 leads to negative effects on the formation of the grain-yielding traits with a marked increase in the accumulation levels of cis-zeatin O-glucoside （cZOG） in the transgenic rice plants. In this study,our findings demonstrate the feasibility of improving the critical yield-determinant agronomic traits, including tiller number, panicle branches, total grain number per panicle and grain weight by downregulating the expression level of OscZOG1. Our results suggest that modulating the levels of cytokinin glucosylation can function as a fine-tuning switch in regulating the formation of agronomic traits in rice.

A quality requirements model and verification approach for system of systems based on description logic

System of systems engineering(So SE) involves the complex procedure of translating capability needs into the high-level requirements for system of systems(So S) and evaluating how the SoS quality requirements meet their capability needs. One of the key issues is to model the So S requirements and automate the verification procedure. To solve the problem of modeling and verification, meta-models are proposed to refine both functional and non-functional characteristics of the So S requirements. A domain-specific modeling language is defined by extending Unified Modeling Language(UML) class and association with fuzzy constructs to model the vague and uncertain concepts of the SoS quality requirements. The efficiency evaluation function of the cloud model is introduced to evaluate the efficiency of the SoS quality requirements. Then a concise algorithm transforms the fuzzy UML models into the description logic(DL) ontology so that the verification can be automated with a DL reasoner. This method implements modeling and verification of high-level So S quality requirements. A crisp case is used to facilitate and demonstrate the correctness and feasibility of this method.

Roll gap prediction in acceleration and deceleration process of cold rolling based on a data-driven method

Severe fluctuation of the effective roll gap in the acceleration and deceleration section of the cold rolling process is a significant factor causing thickness deviation.However,the conventional roll gap compensation method and control strategy do not meet the stringent strip quality requirements.The roll gap model in the acceleration and deceleration process is studied to increase the thickness control precision.In order to improve model accuracy,a roll gap prediction method based on data-driven is proposed.Given the complexities of the cold rolling process,the extreme gradient boosting(XGBoost)method is used to predict the roll gap model as the rolling speed changes.Meanwhile,support vector regression and neural network-based methods are taken to evaluate and compare the prediction performances.Based on the field data,the simulation experiments are carried out.It demonstrated that the prediction performance of the proposed method outperformed the other two methods.The values of root mean square error,determination coefficient value,mean absolute percentage error and mean absolute error obtained from the XGBoost model were equal to 0.000346,0.952,7.02,and 0.00028,respectively.In addition,the proposed method analyzed the contribution rates of the rolling affecting parameters on the roll gap.The data showed that in the controllable rolling parameters,the rolling speed is the most impacting factor that disturbs the roll gap model in the acceleration and deceleration process,which can provide a useful direction for actual roll gap adjustment.