Heterogeneously-catalyzed aerobic oxidation of furfural to furancarboxylic acid with CuO-Promoted MnO_(2)

A cost-effective and sustainable noble-metal free catalyst system based on ubiquitously available Mn-Cu bimetallic oxides was served as efficient catalysts for furfural selective oxidation to furancarboxylic acid(FA). Interestingly, Mn_(2)Cu_(1)O_(x)exhibited an excellent furfural conversion of 99% with quantitative selectivity toward FA. Especially, we demonstrate the significant weakening of the Mn-O bonds with the incorporation of CuO into the Mn-Cu oxides, resulting in an improved OLreactivity of Mn_(2)Cu_(1)O_(x), which brings about a higher catalytic activity for furfural oxidation. More importantly, Mn_(2)Cu_(1)O_(x)could exhibit YFA>90% over 5 cycles of reusability test. Through this study, the relationship between the morphology, surface chemistry, and catalytic activity of Mn-Cu bimetallic oxides are elucidated, providing a simple and environmentally friendly catalytic strategy and scientific basis for the development of Mn-Cu bimetallic oxides bioderived molecular aerobic oxidation materials.

Research on Fault Repair Method of All-Optical Network Based on SDN

All-optical network,as a new backbone network,is featured with high speed and large capacity transmission.It may be out of order due to various faults while providing high-performance transmission service,thus more effective fault repairing methods are required.A routing and wavelength assignment method based on SDN is designed and analyzed from the perspective of service function chaining in this paper.A multi-objective integer linear programming model based on impairment-aware and scheduling time is constructed by combining the unified control of control plane with the resource allocation mode of service function virtualization.Meanwhile,an improved Firefly Algorithm is adopted to solve the model for obtaining a better scheduling scheme,so as to the resources are allocated on-demand in a more flexible and efficient way,which effectively improved the self-recovery capability of the network.In the simulation experiments,Through the comparison between the method proposed and methods based on centralization and distribution,method proposed in the paper is superior to the compared ones in the indexes of survivability,blocking probability,link recovery time,and presents a better scheduling performance,makes the system has stronger ability of self-healing in the face of failure.

A Cooperative Abnormal Behavior Detection Framework Based on Big Data Analytics

As cyber attacks increase in volume and complexity,it becomes more and more difficult for existing analytical tools to detect previously unseen malware.This paper proposes a cooperative framework to leverage the robustness of big data analytics and the power of ensemble learning techniques to detect the abnormal behavior.In addition to this proposal,we implement a large scale network abnormal traffic behavior detection system performed by the framework.The proposed model detects the abnormal behavior from large scale network traffic data using a combination of a balanced decomposition algorithm and an ensemble SVM.First,the collected dataset is divided into k subsets based on the similarity between patterns using a parallel map reduce k-means algorithm.Then,patterns are randomly selected from each cluster and balanced training sub datasets are formed.Next,the subsets are fed into the mappers to build an SVM model.The construction of the ensemble is achieved in the reduce phase.The proposed structure closely delivers a high accuracy as the number of iterations increases.Experimental results show a promising gain in detection rate and false alarm compared with other existing models.

An Availability Evaluation Method of Web Services Using Improved Grey Correlation Analysis with Entropy Difference and Weight

Web services is one of the basic network services, whose availability evaluation is of great significance to the promotion of users’ experience. This paper focuses on the problem of availability evaluation of Web services and proposes a method for availability evaluation of Web services using improved grey correlation analysis with entropy difference and weight (EWGCA).This method is based on grey correlation analysis, and use entropy difference to illustrate the changes of availability, set weight to quantize availability requirements of different operations or transactions in services. Through simulation experiment in high load scenarios for Web services, the experiment result shows that our method can realize hierarchical description and overall evaluation for availability of Web services accurately in the case of smaller test sample volumes or uncertain data even in the field of big data.

An Energy Efficient Random Walk Based Expanding Ring Search Method for Wireless Networks

Wireless networks generate large amount of data. It is important to design energy efficient data search method since power of wireless nodes is finite. Expanding Ring Search (ERS) is a data search technique exploring for targets progressively, which is widely used to locate destinations or information in wireless networks. The existing studies on improving the energy efficiency of ERS cannot work without positioning systems. In this paper, we combine the technique of random walk with ERS, and propose a random walk based expanding ring search method (RWERS) for large-scale wireless networks. RWERS can work without using positioning systems, and improve the energy efficiency of ERS by preventing each node from transmitting the same request more than once using the technique of random walk. We compare RWERS with the optimal ERS strategy and CERS in networks with various shapes of terrains. The simulation results show that RWERS decreases the energy cost by 50% without decreasing in success rate compared with ERS, and has twice the success rate of CERS when the network is sparse. RWERS can be applied to various shapes of terrains better compared with CERS.

A Distributed Strategy for Defensing Objective Function Attack in Large-scale Cognitive Networks

Most of existed strategies for defending OFA (Objective Function Attack)are centralized, only suitable for small-scale networks and stressed on the computation complexity and traffic load are usually neglected. In this paper, we pay more attentions on the OFA problem in large-scale cognitive networks, where the big data generated from the network must be considered and the traditional methods could be of helplessness. In this paper, we first analyze the interactive processes between attacker and defender in detail, and then a defense strategy for OFA based on differential game is proposed, abbreviated as DSDG. Secondly, the game saddle point and optimal defense strategy have proved to be existed simultaneously. Simulation results show that the proposed DSDG has a less influence on network performance and a lower rate of packet loss.More importantly, it can cope with the large range

IMB-0523 Inhibits Enterovirus 71 Replication by Activating Signal Transducer and Activator of Transcription 3 Signaling to Upregulate Interferon-Stimulated Genes Expression

Background Hand,foot,and mouth disease caused by enterovirus 71(EV71)infection is prevalent in the Asia-Pacific region in recent years.Currently,no drug is available for the prevention and treatment of EV71 infection.IMB-0523,a N-phenylbenzamide derivative,inhibits hepatitis B virus replication by upregulating the expression of APOBEC3G.In the present study,the effect of IMB-0523 on EV71 replication and related mechanism were investigated.Methods The cytotoxicity of IMB-0523 was determined by cell counting kit.Quantitative real-time polymerase chain reaction and Western blot assay were used to detect the effect of IMB-0523 on EV71 replication and related mechanism.Cytopathic effect assay was used to investigate the effect of IMB-0523 on different EV71 strains,coxsackievirus A16,and coxsackieviruses of group B.Results The results showed that IMB-0523 could dose-dependently inhibit EV71 replication.Preliminary mechanism studies showed that IMB-0523 could activate STAT3 signaling to upregulate the expression of interferon-stimulated genes to play an antiviral role.In addition,IMB-0523 inhibited the replication of different EV71 strains,coxsackievirus A16,and coxsackieviruses of group B.Conclusions IMB-0523 inhibits EV71 replication by activating the STAT3 signaling pathway to upregulate interferon-stimulated gene expression.IMB-0523 has broad-spectrum antiviral potential and may be used as a lead compound for the development of broad spectrum antiviral drugs.

Recent Progress on Functional Genomics Research of Enterovirus 71

Enterovirus 71(EV71) is one of the main pathogens that causes hand-foot-and-mouth disease(HFMD). HFMD caused by EV71 infection is mostly self-limited; however, some infections can cause severe neurological diseases, such as aseptic meningitis, brain stem encephalitis, and even death. There are still no effective clinical drugs used for the prevention and treatment of HFMD. Studying EV71 protein function is essential for elucidating the EV71 replication process and developing anti-EV71 drugs and vaccines. In this review, we summarized the recent progress in the studies of EV71 noncoding regions(50 UTR and 30 UTR) and all structural and nonstructural proteins, especially the key motifs involving in viral infection, replication, and immune regulation. This review will promote our understanding of EV71 virus replication and pathogenesis, and will facilitate the development of novel drugs or vaccines to treat EV71.

Repurposing carrimycin as an antiviral agent against human coronaviruses,including the currently pandemic SARS-CoV-2

COVID-19 pandemic caused by SARS-CoV-2 infection severely threatens global health and economic development.No effective antiviral drug is currently available to treat COVID-19 and any other human coronavirus infections.We report herein that a macrolide antibiotic,carrimycin,potently inhibited the cytopathic effects(CPE)and reduced the levels of viral protein and RNA in multiple cell types infected by human coronavirus 229 E,OC43,and SARS-CoV-2.Time-of-addition and pseudotype virus infection studies indicated that carrimycin inhibited one or multiple post-entry replication events of human coronavirus infection.In support of this notion,metabolic labelling studies showed that carrimycin significantly inhibited the synthesis of viral RNA.Our studies thus strongly suggest that carrimycin is an antiviral agent against a broad-spectrum of human coronaviruses and its therapeutic efficacy to COVID-19 is currently under clinical investigation.

Chinese herbal medicine compound Yi-Zhi-Hao pellet inhibits replication of influenza virus infection through activation of heme oxygenase-1

As a leading cause of respiratory disease, influenza A virus(IAV) presents a pandemic threat in annual seasonal outbreaks. Given the limitation of existing anti-influenza therapies, there remains to be a requirement for new drugs. Compound Yi-Zhi-Hao pellet(CYZH) is a famous traditional Chinese medicine(TCM) used in the clinic, whose formula has been recorded in Complication of National Standard for Traditional Chinese Medicine to treat common cold. In this study, we found that CYZH exhibited a broad-spectrum anti-influenza activity and inhibited the expression of viral RNA and proteins in vitro. Mechanistically, CYZH had no inhibitory activities against viral protein hemagglutinin and IAV RNA-dependent RNA polymerase. Instead, it induced activation of erythroid 2-related factor 2(Nrf2) and nuclear factor kappa B(NF-κB), which subsequently upregulated heme oxygenase-1(HO-1) expression.Also, CYZH protected cells from oxidative damage induced by reactive oxygen series. In conclusions,CYZH inhibits IAV replication in vitro, at least partly by activating expression of the Nrf2/HO-1 pathway.

Hybrid Semantic Service Matchmaking Method Based on a Random Forest

Semantic Service Matchmaking(SSM)can be leveraged for mining the most suitable service to accommodate a diversity of user demands.However,existing research on SSM mostly involves logical or non-logical matching,leading to unavoidable false-positive and false-negative problems.Combining different types of SSM methods is an effective way to improve this situation,but the adaptive combination of different service matching methods is still a difficult issue.To conquer this difficulty,a hybrid SSM method,which is based on a random forest and combines the advantages of existing SSM methods,is proposed in this paper.The result of each SSM method is treated as a multi-dimensional feature vector input for the random forest,converting the service matching into a two classification problem.Therefore,our method avoids the flaws found in manual threshold setting.Experimental results show that the proposed method achieves an outstanding performance.

An effective method for service components selection based on micro-canonical annealing considering dependability assurance

Distributed virtualization changes the pattern of building software systems. However, it brings some problems on dependability assurance owing to the complex social relationships and interactions between service components. The best way to solve the problems in a distributed virtualized environment is dependable service components selection. Dependable service components selection can be modeled as finding a dependable service path, which is a multiconstrained optimal path problem. In this paper, a service components selection method that searches for the dependable service path in a distributed virtualized environment is proposed from the perspective of dependability assurance. The concept of Quality of Dependability is introduced to describe and constrain software system dependability during dynamic composition. Then, we model the dependable service components selection as a multiconstrained optimal path problem, and apply the Adaptive Bonus-Penalty Microcanonical Annealing algorithm to find the optimal dependable service path. The experimental results show that the proposed algorithm has high search success rate and quick converges.

Synthesis and antiviral activity of a series of novel N-phenylbenzamide and N-phenylacetophenone compounds as anti-HCV and anti-EV71 agents

A series of novel N-phenylbenzamide and N-phenylacetophenone compounds were synthesized and evaluated for their antiviral activity against HCV and EV71(strain SZ-98).The biological results showed that three compounds(23,25 and 41) exhibited considerable anti-HCV activity(IC50? 0.57–7.12 μmol/L) and several compounds(23,28,29,30,31 and 42) displayed potent activity against EV71 with the IC50 values lower than 5.00 μmol/L.The potency of compound 23(IC50? 0.57 μmol/L) was superior to that of reported compounds IMB-1f(IC50? 1.90 μmol/L) and IMB-1g(IC50? 1.00 μmol/L) as anti-HCV agents,and compound29 possessed the highest anti-EV71 activity,comparable to the comparator drug pirodavir.The efficacy in vivo and antiviral mechanism of these compounds warrant further investigations.

Synthesis and antiviral activities of a novel class of thioflavone and flavonoid analogues

A novel class of thioflavone and flavonoid derivatives has been prepared and their antiviral activities against enterovirus 71(EV71)and the coxsackievirus B3(CVB3)and B6(CVB6)were evaluated.Compounds 7d and 9b showed potent antiviral activities against EV71 with ICso values of 8.27 and 5.48μM,respectively.Compound 7f,which has been synthesized for the first time in this work,showed the highest level of inhibitory activity against both CVB3 and CVB6 with an ICso value of 0.62 and 0.87μM.Compounds 4b,7a,9c and 9e also showed strong inhibitory activities against both the CVB3 and CV B6 at low concentrations(IC_(50)=1.42-7.15μM),whereas compounds 4d,7c,7e and 7g showed strong activity against CVB6(IC_(50)=2.91-3.77μM)together with low levels of activity against CVB3.Compound 7d exhibited stronger inhibitory activity against CVB3(IC_(50)=6.44μM)thaln CVB6(IC_(50)>8.29μM).The thioflavone derivatives 7a,7c,7d,7e,7f and 7g,represent a new class of lead compounds for the development of novel antiviral agents.

The antiviral effect of jiadifenoic acids C against coxsackievirus B3

Coxsackievirus B type 3(CVB3)is one of the major causative pathogens associated with viral meningitis and myocarditis,which are widespread in the human population and especially prevalent in neonates and children.These infections can result in dilated cardiomyopathy(DCM)and other severe clinical complications.There are no vaccines or drugs approved for the prevention or therapy of CVB3-induced diseases.During screening for anti-CVB3 candidates in our previous studies,we found that jiadifenoic acids C exhibited strong antiviral activities against CVB3 as well as other strains of Coxsackie B viruses(CVBs).The present studies were carried out to evaluate the antiviral activities of jiadifenoic acids C.Results showed that jiadifenoic acids C could reduce CVB3 RNA and proteins synthesis in a dose-dependent manner.Jiadifenoic acids C also had a similar antiviral effect on the pleconaril-resistant variant of CVB3.We further examined the impact of jiadifenoic acids C on the synthesis of viral structural and non-structural proteins,finding that jiadifenoic acids C could reduce VP1 and 3D protein production.A time-course study with Vero cells showed that jiadifenoic acids C displayed significant antiviral activities at 0–6 h after CVB3 inoculation,indicating that jiadifenoic acids C functioned at an early step of CVB3 replication.However,jiadifenoic acids C had no prophylactic effect against CVB3.Taken together,we show that jiadifenoic acids C exhibit strong antiviral activities against all strains of CVB,including the pleconaril-resistant variant.Our study could provide a significant lead for anti-CVB3 drug development.