Amino-functionalized UiO-66-doped mixed matrix membranes with high permeation performance and fouling resistance

For the reduction of bovine serum proteins from wastewater,a novel mixed matrix membrane was prepared by functionalizing the substrate material polyaryletherketone(PAEK),followed by carboxyl groups(C-SPAEKS),and then adding amino-functionalized UiO-66-NH_(2)(Am-UiO-66-NH_(2)).Aminofunctionalization of UiO-66 was accomplished by melamine,followed by an amidation reaction to immobilize Am-UiO-66-NH_(2),which was immobilized on the surface of the membrane as well as in the pore channels,which enhanced the hydrophilicity of the membrane surface while increasing the negative potential of the membrane surface.This nanoparticle-loaded ultrafiltration membrane has good permeation performance,with a pure water flux of up to 482.3 L·m^(-2)·h^(-1) for C-SPAEKS/AmUiO-66-NH_(2) and a retention rate of up to 98.7%for bovine serum albumin(BSA)-contaminated solutions.Meanwhile,after several hydrophilic modifications,the flux recovery of BSA contaminants by this series of membranes increased from 56.2%to 80.55%of pure membranes.The results of ultra-filtration flux time tests performed at room temperature showed that the series of ultrafiltration membranes remained relatively stable over a test time of 300 min.Thus,the newly developed mixed matrix membrane showed potential for high efficiency and stability in wastewater treatment containing bovine serum proteins.

Amine-functionalized metal organic framework@graphene oxide as filler in PAEK-containing carboxyl group membrane for ultrafiltration with ultra-high permeability and strong fouling resistance

Achieving high fouling resistance and permeability using membrane separation technology in water treatment processes remains a challenge.In this work,a novel mixed-matrix membrane(MMM)(poly(arylene ether ketone)[PAEK]-containing carboxyl groups[PAEK-COOH]/UiO-66-NH_(2)@graphene oxide[GO])with superb fouling resistance and high permeability was prepared by the nonsolvent-induced phase separation method,by in-situ growth of UiO-66-NH_(2) on the GO layer,and by preparing hydrophilic PAEK-COOH.On the basis of the structure and performance analysis of the MMM,the maximum water flux reached 591.25 L·m^(-2)·h^(-1) for PAEK-COOH/UiO-66-NH_(2)@GO,whereas the retention rate for bovine serum albumin increased from 85.40%to 94.87%.As the loading gradually increased,the hydrophilicity of the MMMs increased,significantly enhancing their fouling resistance.The strongest anti-fouling ability observed was 94.74%,which was 2.02 times greater than that of the pure membrane.At the same time,the MMMs contained internal amide and hydrogen bonds during the preparation process,forming a cross-linked structure,which further enhanced the mechanical strength and chemical stability.In summary,the MMMs with high retention rate,strong permeability,and anti-fouling ability were successfully prepared.

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

Molecular Mechanism of Zhizi Ganjiang Decoction in Regulating Liver Cirrhosis Based on BATMAN-TCM Platform

[Objectives]To explore the molecular mechanism of Zhizi Ganjiang Decoction in the treatment of liver cirrhosis based on the network pharmacology.[Methods]The BATMAN-TCM server was used to predict the potential targets of Zhizi Ganjiang Decoction,and the GeneCards database searched for targets related to liver cirrhosis;Cytoscape 3.5.1 software was used to construct compound-cirrhosis target interaction network and protein interaction network;then gene ontology(GO)enrichment analysis,Reactome pathway enrichment analysis,and KEGG-based biological pathway enrichment analysis were performed.[Results]The compound-disease-target network of Zhizi Ganjiang Decoction was constructed.The PPI network of Zhizi Ganjiang Decoction targets constructed based on String contained 130 nodes and 689 interaction relationships.The key nodes mainly involved nuclear hormone receptor-like domain superfamily and ligand binding domain,serpentine type 7TM GPCR chemoreceptor and chemoreceptor Srx,rhodopsin family transmembrane receptors,zinc finger NHR/GATA type nuclear hormone receptors and ligand binding domains,PI3-kinase family p85 binding domain,phosphoinositide(PI)3-kinase catalytic domain and other categories.GO enrichment analysis pathway related entries mainly involved steroid hormone receptor activity,nuclear receptor activity,transcription factor activity,direct ligands regulation sequence-specific DNA binding,G protein-coupled amine receptor activity,steroid binding,catecholamine binding,neurotransmitter receptor activity,adrenergic receptor activity,ammonium ion binding,and oxidoreductase activity,etc.KEGG channel analysis mainly involved neuroactive ligand-receptor interaction,aldosterone regulates sodium reabsorption,regulates lipolysis in adipocytes,regulates inflammatory mediators of TRP channels,tyrosine metabolism,calcium signaling pathway,cAMP signaling pathway,and nonalcoholic fatty liver diseases.[Conclusions]The research results suggest that Zhizi Ganjiang Decoction regulates the process of liver cirrhosis mainly through aldosterone regulation of sodium reabsorption,regulation of lipolysis in adipocytes,regulation of inflammatory mediators of TRP channels,calcium signaling pathways,and nonalcoholic fatty liver diseases.This reflects the multi-target and holistic action characteristics of the Chinese herbal compounds,and is expected to provide new ideas for further research on the molecular mechanism of Zhizi Ganjiang Decoction.

An efficient and universal protoplast-based transient gene expression system for genome editing in Brassica crops

Protoplast-based transient gene expression system has been widely used in plant genome editing because of its simple operation and less time-consuming.In order to establish a universal protoplast-based transient transfection system for verifying activities of genome editing vectors containing targets in Brassica,we systematically optimized factors affecting protoplast isolation and transient gene expression.We established an efficient protoplast-based transient gene expression system(PTGE)in Chinese cabbage,achieving high protoplast yield of 4.9×10^(5)·g^(-1)FW,viability over 95%,and transfection efficiency of 76%.We showed for the first time that pretreatment of protoplasts with a hypotonic MMG could significantly enhance the transfection efficiency.Furthermore,protoplasts incubated at 37℃ for 6 min improved the transfection efficiency to 86%.We also demonstrated that PTGE worked well(more than 50%transfection efficiency)in multiple Brassica species including cabbage,Pak Choi,Chinese kale,and turnip.Finally,PTGE was used for validating the activities of CRISPR/Cas9 vectors containing targets in Chinese cabbage,cabbage,and pak choi,demonstrating the broad applicability of the established PTGE for genome editing in Brassica crops.

Study on the mechanism of Euphorbia fischeriana Steud.- Jujubae Fructus in the treatment of hepatocirrhosis based on network pharmacology

The active components,targets,and pathways of Euphorbia fischeriana Steud.-Jujubae Fructus in treating hepatocirrhosis and the mechanism of action were explored by means of network pharmacology.Firstly,the active components and related targets of Jujubae Fructus were screened by TCMSP database and standardized by Uniprot database.The compounds of Euphorbia fischeriana Steud.were obtained by searching the literature and finally screened by PubChem database,Swiss ADME,and SwissTargetPrediction.Hepatocirrhosis targets were obtained through Genecards database,PPI network analysis was conducted on common targets of Euphorbia fischeriana Steud.-Jujubae Fructus and hepatocirrhosis by using String database,GO enrichment analysis and KEGG pathway enrichment analysis was conducted through Metascape database by using intersection targets of Euphorbia fischeriana Steud.-Jujubae Fructus and hepatocirrhosis,and the results were drawn by using Weishengxin online drawing platform.Then,the network of drug-compound-target-pathway was constructed by the software of Cytoscape3.8.0.Finally,the above results were verified by molecular docking.47 active compounds from Euphorbia fischeriana Steud.-Jujubae Fructus were screened out,which had 38 common targets,162 intersection targets,and 340 signal pathways with hepatocirrhosis,mainly involving hepatitis C,JAK-STAT signal pathway and AGE-RAGE signal pathway.Targets,such as MAPK1,AKT1,TNF,JUN,IL6 and PTGS2,play important roles in the treatment.The findings suggested that the main active ingredients of Euphorbia fischeriana Steud.-Jujubae Fructus in treating hepatocirrhosis are quercetin,scopolamine,physcion,7-deoxyrangduin,17-Hydroxyjolkinolide A,etc.Molecular docking results showed that the main active components and core targets might have a good binding capacity.This study preliminarily explored the potential mechanism of Euphorbia fischeriana Steud.-Jujubae Fructus in treating hepatocirrhosis and provided a theoretical basis for the clinical application of Euphorbia fischeriana Steud.-Jujubae Fructus.

Mechanical microenvironments as key cellular regulator in the liver

Tissue stiffness, shear stress, and interstitial pressure make up major factors of liver mechanical microenvironment, which play the key regulatory role to control cell behaviors in the liver and progress of liver diseases. In this review, we focus on the characteristics of liver mechanical microenvironments and summarize cellular responses to mechanobiological changes during liver pathogenesis, especially in hepatic fibrosis and cirrhosis. A better understanding of the indispensable contributions of mechanical cues to liver homeostasis and pathogenesis is significant to identify new therapeutic targets for liver diseases such as hepatic fibrosis or cirrhosis.

Preparation and water sorption properties of novel SiO_(2)-LiBr microcapsules for water-retaining pavement

Novel SiO_(2)-LiBr microcapsules for water-retaining pavement were prepared and firstly characterized by scanning electron microscope(SEM),particle size analysis,and Fourier transform infrared spectroscopy(FT-IR).The water vapor sorption and desorption of the formulated microcapsules was then experimentally studied using dynamic vapor sorption(DVS),with the results fitted to three kinds of adsorption kinetics models.In addition,the specific surface area(SSA)was also calculated based on BET theory;and the thermal performance was investigated by laser flash analysis(LFA).Experimental results show a change of 103%in mass of the microcapsule sample under 90%relative humidity(RH)at 30℃after water vapor sorption.The fitting of results indicates that the adsorption process is mainly governed by the intra-particle diffusion mechanism,followed by the pseudo-first-order adsorption process.In comparison with most conventional pavement materials,it is found that the SSA of the formulated microcapsules is much larger while the thermal conductivity is lower.The unique properties of the formulated SiO_(2)-LiBr microcapsules have significant potential to take the edge off the urban heat island effect and reduce rutting when applied to water-retaining pavement materials.

Signaling Pathways and Molecular Mechanisms of Oxidative Stress in Skeletal Muscle

Oxidative stress is a major factor affecting animal health and production performance. This paper briefly introduced the signaling pathways(i.e. NF-κB signaling pathway, MAPK, AP-1 and PGC-1α) of oxidative stress and the main genes regulating the signals of oxidative stress in skeletal muscle, providing a theoretical basis for reducing oxidative stress damage.

Clinical Observation and Network Pharmacology Study on Analgesic Effect of Qianghuo Chushi Decoction on Fasciitis

[Objectives]To observe the clinical analgesic effect of Qianghuo Chushi Decoction(QHCSD)on patients with fasciitis,and explore its possible molecular mechanism based on network pharmacology.[Methods]120 enrolled patients were randomly divided into experimental group and control group,and were separately treated with QHCSD formula granules and Diclofenac Sodium Enteric-coated Tablets for 4 weeks.The patient’s pain visual analogue scale(VAS)was used as the curative effect indicator.The molecular action mechanism of QHCSD was predicted based on network pharmacology,the active components of QHCSD were screened using TCMSP database,potential targets were predicted by PharmMapper server,compound-target network and protein interaction network were constructed,and GO-based enrichment analysis and KEGG-based biological pathway enrichment analysis were performed.[Results]After treatment,the pain scores in each group were significantly lower than those before treatment(P<0.01),the score of the experimental group was significantly lower than that of the control group(P<0.01),and the total effective rate of the experimental group was 83.33%,which was significantly higher than that of the control group(78.33%,P<0.05).Based on 108 active components in QHCSD,a compound-target network was constructed.The PPI network contained 155 nodes and 527 interaction relationships,and key nodes included FOS,ESR1,NCOA1,RELA,EGFR,MAPK8,IL-6,etc.The GO pathway mainly involved steroid hormone and its receptor activity,RNA polymerase II transcriptional regulator binding,nuclear receptor activity,protein heterodimerization activity and other pathways.KEGG metabolic pathways included PI3 K-Akt signaling pathway,Kaposi’s sarcoma-associated herpesvirus(KSHV)infection and other pathways.[Conclusions]QHCSD has a significant analgesic effect on fasciitis,and the PI3 K-Akt signaling pathway may be the key pathway for its analgesic effect.

Determination of seven active components in Salvia miltiorrhiza herb by matrix solid phase dispersion combined with ion liquid extraction followed by high performance liquid chromatography

A low cost,rapid and sensitive preparation method of silica gel supported ionic liquid(SGSIL)combined with matrix solid phase dispersion(MSPD)followed by high performance liquid chromatography(HPLC)with ultraviolet detection(UV)is proposed,and it was applied to determine the seven active compounds in Salvia Miltiorrhiza herb.SGSIL and ionic liquid[BMIM]BF4 were used as the adsorbent and the green elution reagent in the MSPD procedure.Several extraction conditions including type of filler and elution solvent,the volume of elution solvent,material liquid ratio were optimized.Under the optimum conditions,the SGSIL-MSPD-HPLC method showed a low limit of detection(LOD,S/N=3)of 0.0122-0.8788μg/mL for standard solution,limit of quantification(LOQ,S/N=10)of 0.0406-2.9292μg/mL for standard solution,wide linear range from 1.56 to 2000μg/mL for all compounds for standard solution,correlation coefficients(r)of more than 0.9990,acceptable reproducibility(relative standard deviations,RSDs<3.54%),and precision of RSDs<3.36%for intra-day,RSDs<3.50%for inter-day.The satisfactory recoveries ranged from 96.4 to 102.5,with RSDs less than 3.45%.The developed SGSIL-MSPD method is easier and more suitable for the determination of the seven active compounds in Salvia Miltiorrhiza herb than the traditional ultrasonic extraction.It was an effective and efficient method for the extraction and quantification of the seven active compounds in traditional Chinese herbal samples.

A Secure and Effective Energy-Aware Fixed-Point Quantization Scheme for Asynchronous Federated Learning

Asynchronous federated learning(AsynFL)can effectivelymitigate the impact of heterogeneity of edge nodes on joint training while satisfying participant user privacy protection and data security.However,the frequent exchange of massive data can lead to excess communication overhead between edge and central nodes regardless of whether the federated learning(FL)algorithm uses synchronous or asynchronous aggregation.Therefore,there is an urgent need for a method that can simultaneously take into account device heterogeneity and edge node energy consumption reduction.This paper proposes a novel Fixed-point Asynchronous Federated Learning(FixedAsynFL)algorithm,which could mitigate the resource consumption caused by frequent data communication while alleviating the effect of device heterogeneity.FixedAsynFL uses fixed-point quantization to compress the local and global models in AsynFL.In order to balance energy consumption and learning accuracy,this paper proposed a quantization scale selection mechanism.This paper examines the mathematical relationship between the quantization scale and energy consumption of the computation/communication process in the FixedAsynFL.Based on considering the upper bound of quantization noise,this paper optimizes the quantization scale by minimizing communication and computation consumption.This paper performs pertinent experiments on the MNIST dataset with several edge nodes of different computing efficiency.The results show that the FixedAsynFL algorithm with an 8-bit quantization can significantly reduce the communication data size by 81.3%and save the computation energy in the training phase by 74.9%without significant loss of accuracy.According to the experimental results,we can see that the proposed AsynFixedFL algorithm can effectively solve the problem of device heterogeneity and energy consumption limitation of edge nodes.

Hybrid reconstruction framework for model-based multispectral bioluminescence tomography based on Alpha-divergence

Bioluminescence tomography(BLT)is a promising imaging modality that can provide noninvasive three-dimensional visualization information on tumor distribution.In BLT reconstruction,the widely used methods based on regularization or greedy strategy face problems such as over-sparsity,over-smoothing,spatial discontinuity,poor robustness,and poor multi-target resolution.To deal with these problems,combining the advantages of the greedy strategies as well as regularization methods,we propose a hybrid reconstruction framework for model-based multispectral BLT using the support set of a greedy strategy as a feasible region and the Alpha-divergence to combine the weighted solutions obtained by L1-norm and L2-norm regularization methods.In numerical simulations with digital mouse and in vivo experiments,the results show that the proposed framework has better localization accuracy,spatial resolution,and multi-target resolution.

Monitoring Thosea sinensis Walker in Tea Plantations Based on UAV Multi- Spectral Image

Thosea sinensis Walker(TSW)rapidly spreads and severely damages the tea plants.Therefore,finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research community.Such methods also enable us to calculate the precise application of pesticides and prevent the subsequent spread of the pests.In this work,based on the unmanned aerial vehicle(UAV)platform,five band images of multispectral red-edge camera were obtained and used for monitoring the TSW in tea plantations.By combining the minimum redundancy maximum relevance(mRMR)with the selected spectral features,a comprehensive spectral selection strategy was proposed.Then,based on the selected spectral features,three classic machine learning algorithms,including random forest(RF),support vector machine(SVM),and k-nearest neighbors(KNN)were used to construct the pest monitoring model and were evaluated and compared.The results showed that the strategy proposed in this work obtained ideal monitoring accuracy by only using the combination of a few optimized features(2 or 4).In order to differentiate the healthy and TSW-damaged areas(2-class model),the monitoring accuracies of all the three models were computed,which were above 96%.The RF model used the least number of features,including only SAVI and Bandred.In order to further discriminate the pest incidence levels(3-class model),the monitoring accuracies of all the three models were computed,which were above 80%,among which the RF algorithm based on SAVI,Band_(red),VARI__(green),and Band_(red_edge) features achieve the highest accuracy(OAA of 87%,and Kappa of 0.79).Considering the computational cost and model accuracy,this work recommends the RF model based on a few optimal feature combinations to monitor and distinguish the severity of TSW in tea plantations.According to the UAV remote sensing mapping results,the TSW infestation exhibited an aggregated distribution pattern.The spatial information of occurrence and severity can offer effective guidance for precise control of the pest.In addition,the relevant methods provide a reference for monitoring other leaf-eating pests,effectively improving the management level of plant protection in tea plantations,and guaranting the yield and quality of tea plantations.

Development of Tourism Resources of Baimai Spring Park in Jinan City and Its Path Optimization

Tourism is gradually becoming one of the pillar industries of China s economy. Tourism resources are the premise and foundation of tourism development. It is of great significance to study the exploitation of tourism resources to promote the development of tourism. Jinan is famous for water, and Baimai Spring Park is a collection of springs in one place, with rich tourism resources. Coupled with the local government s attention to tourism, Baimai Spring Park, as a representative, has accumulated a rich tourism market foundation. With the support of policies, unique spring ecological and cultural resources and increasingly perfect location conditions, the high-quality development of tourism resources in Baimai Spring Park is particularly urgent. In this study, the present situation and problems of development of tourism resources in Baimai Spring Park were analyzed by questionnaire survey method, and corresponding optimization suggestions were put forward.

A Fairness Resource Allocation Algorithm for Coverage and Capacity Optimization in Wireless Self-Organized Network

To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SON). In this paper, a novel CCO scheme is proposed to maximize utility function of the integrated coverage and capacity. It starts with the analysis on the throughput proportional fairness(PF) algorithm and then proposes the novel Coverage and Capacity Proportional Fairness(CCPF) allocation algorithm along with a proof of the algorithms convergence. This proposed algorithm is applied in a coverage capacity optimization scheme which can guarantee the reasonable network capacity by the coverage range accommodation. Next, we simulate the proposed CCO scheme based on telecom operators' real network data and compare with three typical resource allocation algorithms: round robin(RR), proportional fairness(PF) and max C/I. In comparison of the PF algorithm, the numerical results show that our algorithm increases the average throughput by 1.54 and 1.96 times with constructed theoretical data and derived real network data respectively.

O/N/S trifunctional doping on graphite felts:A novel strategy toward performance boosting of cerium-based redox flow batteries

The cerium-based redox flow battery(RFB)is regarded as a compelling gridscale energy storage technology to revolutionize the utilization of renewable energy by storing the energy in liquid electrolytes.However,its widespread implementation is impeded by the cerium redox reactions that exhibit slow kinetics on commercial graphite felt(GF)electrodes.Surface functionalization may be an available activation strategy to achieve a significant boost in the electrochemical performance of GFs.However,conventional chemical and/or electrochemical routes for the surface functionalization of GFs suffer from the issues of complication,and the deterioration of the resulting modified electrode surface over long-term cycle processes leads to catalytic activity decline.Here,we develop a facile and general strategy for introducing the functional groups to the electrode through the addition of L-cysteine into electrolytes.The-COOH,-NH_(2),and-SH groups in L-cysteine can induce oxygen/nitrogen/sulfur trifunctional doping on GF surfaces with lower deterioration rates,which enables the activated GFs to demonstrate a promising electrocatalytic activity toward cerium redox reactions and excellent durability when used as a cerium-based RFB electrode.This study proposes a rational strategy to overcome the intrinsic limitations of existing modification techniques for GFs and provides a potential pathway toward high-performance RFBs.

A Self-Organizing RBF Neural Network Based on Distance Concentration Immune Algorithm

Radial basis function neural network(RBFNN) is an effective algorithm in nonlinear system identification. How to properly adjust the structure and parameters of RBFNN is quite challenging. To solve this problem, a distance concentration immune algorithm(DCIA) is proposed to self-organize the structure and parameters of the RBFNN in this paper. First, the distance concentration algorithm, which increases the diversity of antibodies, is used to find the global optimal solution. Secondly,the information processing strength(IPS) algorithm is used to avoid the instability that is caused by the hidden layer with neurons split or deleted randomly. However, to improve the forecasting accuracy and reduce the computation time, a sample with the most frequent occurrence of maximum error is proposed to regulate the parameters of the new neuron. In addition, the convergence proof of a self-organizing RBF neural network based on distance concentration immune algorithm(DCIA-SORBFNN) is applied to guarantee the feasibility of algorithm. Finally, several nonlinear functions are used to validate the effectiveness of the algorithm. Experimental results show that the proposed DCIASORBFNN has achieved better nonlinear approximation ability than that of the art relevant competitors.

One-step synthesis of carbon-supported copper nanoparticles from biomass for N-arylation of pyrazole

Carbon-supported copper catalyst was prepared for the first time in one-step with copper nitrate and corn stalk through calcination under different temperatures. Uniformly dispersed nanoparticles were obtained and were identified to be Cu（0） and Cu（Ⅰ） in XRD patterns. Excellent catalytic activity and selectivity were achieved in the N-arylation of pyrazole under ligand and protection gas free conditions. About90.4% of product yield was achieved with only 0.5 mol% of copper catalyst（Cu-C-300）, which was considerably more efficient than previous reports. XPS results suggested that the N-arylation of pyrazole activity was closely related to the surface Cu（Ⅰ） species.

Distributed Energy Saving Mechanism Based on CoMP in LTE-A System

To reduce the energy consumption of the LTE-A system,a distributed energy-saving mechanism based on Co MP(Co MPDESM) is proposed to solve the inadequate coverage problem under the dormant cells.First,the network is divided into clusters based on the equivalent cell principle.Then,we transfer global optimization into a group of subproblems.Second,a joint processing-based cooperative cell selection model is constructed to determine cooperative cells and dormant cells.Third,the compensative cells with a determined threshold are selected to control users' access.Finally,a simulation is implemented in Matlab.Results show that the energy-saving rate can reach 36.4% and that the mechanism meets the network coverage requirement.Thus,joint processing can be effectively applied in an energy saving mechanism and used to improve the network performance of edge users without increasing transmission power.