High-performance solid thermal interface materials(TIMs)are crucial for addressing overheating issues in high-power electronics,especially in extreme temperature environments.However,solid TIMs often suffer from poor ...High-performance solid thermal interface materials(TIMs)are crucial for addressing overheating issues in high-power electronics,especially in extreme temperature environments.However,solid TIMs often suffer from poor topographical conformability to mating surfaces,limited deformability,large thickness,and low out-of-plane thermal conductivity,leading to high thermal resistance.Here,we fabricated a highly compressible 3D interconnected graphene lamellae network with abundant micro-bulges on its surface(SBGLN).The micro-bulges enable good topographical conformability to various solid substrates under pressure,and meanwhile,the lamellae can reconstruct the networks by deformation to enhance the out-of-plane thermal conductivity.Thus,the SBGLN achieves an ultra-low total thermal resistance of 0.081 cm^(2)K W^(−1)with a minimal bonding line thickness of 23μm,which are much better than those of previ-ously reported solid TIMs and state-of-the-art commercial TIMs.Moreover,it exhibits a negligible change in thermal resistance when subjected to heat shock at 160℃ for 80 h,in contrast to the 284%increase observed in thermal grease.These combined excellent properties,along with the ease of scaling up,establish the SBGLN as a highly reliable and high-performance solid TIMs for the thermal management of high-power electronics.展开更多
Wastewater treatment plants(WWTPs) are deemed reservoirs of antibiotic resistance genes(ARGs). Bacterial phylogeny can shape the resistome in activated sludge. However, the co-occurrence and interaction of ARGs abunda...Wastewater treatment plants(WWTPs) are deemed reservoirs of antibiotic resistance genes(ARGs). Bacterial phylogeny can shape the resistome in activated sludge. However, the co-occurrence and interaction of ARGs abundance and bacterial communities in different WWTPs located at continental scales are still not comprehensively understood. Here, we applied quantitative PCR and Miseq sequence approaches to unveil the changing profiles of ARGs(sul1, sul2, tet W, tet Q, tet X), int I1 gene, and bacterial communities in 18 geographically distributed WWTPs. The results showed that the average relative abundance of sul1 and sul2 genes were 2.08 × 10^(-1) and 1.32 × 10^(-1) copies/16 S rRNA copies, respectively. The abundance of tet W gene was positively correlated with the Shannon diversity index(H′), while both studied sul genes had significant positive relationship with the int I1 gene. The highest average relative abundances of sul1, sul2, tet X, and int I1 genes were found in south region and oxidation ditch system. Network analysis found that 16 bacterial genera co-occurred with tet W gene. Co-occurrence patterns were revealed distinct community interactions between aerobic/anoxic/aerobic and oxidation ditch systems. The redundancy analysis model plot of the bacterial community composition clearly demonstrated that the sludge samples were significant differences among those from the different geographical areas,and the shifts in bacterial community composition were correlated with ARGs. Together,these findings from the present study will highlight the potential risks of ARGs and bacterial populations carrying these ARGs, and enable the development of suitable technique to control the dissemination of ARGs from WWTPs into aquatic environments.展开更多
The end value of the dynamic resistance curve of stainless steel was proved to have strong correlation with nugget size by experiments, so it was an important factor for estimation of weld quality. BP neural network w...The end value of the dynamic resistance curve of stainless steel was proved to have strong correlation with nugget size by experiments, so it was an important factor for estimation of weld quality. BP neural network was employed to estimate the weld quality, The end value of the dynamic resistance curve, welding current and welding time were selected as the input variables while the nugget diameter, which is closely related to weld quality, was selected as the output variable. Testing results shows that such network has fine fault tolerance and real-time quality estimation is possible.展开更多
Magnesium(Mg) and its alloys have been intensively studied to develop the next generation of bone implants recently, but their clinical application is restricted by rapid degradation and unsatisfied osteogenic effect ...Magnesium(Mg) and its alloys have been intensively studied to develop the next generation of bone implants recently, but their clinical application is restricted by rapid degradation and unsatisfied osteogenic effect in vivo. A bioactive chemical conversion Mg-phenolic networks complex coating(e EGCG) was stepwise incorporated by epigallocatechin-3-gallate(EGCG) and exogenous Mg^(2+)on Mg-2Zn magnesium alloy. Simplex EGCG induced chemical conversion coating(c EGCG) was set as compare group. The in vitro corrosion behavior of Mg-2Zn alloy, c EGCG and e EGCG was evaluated in SBF using electrochemical(PDP, EIS) and immersion test. The cytocompatibility was investigated with rat bone marrow mesenchymal stem cells(r BMSCs). Furthermore, the in vivo tests using a rabbit model involved micro computed tomography(Micro-CT) analysis, histological observation, and interface analysis. The results showed that the e EGCG is Mgphenolic multilayer coating incorporated Mg-phenolic networks, which is rougher, more compact and much thicker than c EGCG. The e EGCG highly improved the corrosion resistance of Mg-2Zn alloy, combined with its lower average hemolytic ratios, continuous high scavenging effect ability and relatively moderate contact angle features, resulting in a stable and suitable biological environment, obviously promoted r BMSCs adhesion and proliferation. More importantly, Micro-CT, histological and interface elements distribution evaluations all revealed that the e EGCG effectively inhibited degradation and enhanced bone tissue formation of Mg alloy implants. This study puts forward a promising bioactive chemical conversion coating with Mg-phenolic networks for the application of biodegradable orthopedic implants.展开更多
In this study,acrylic acid was used as a neutralizer to prepare bio-based WPU with an interpenetrating polymer network structure by thermally induced free radical emulsion polymerization.The effects of the content of ...In this study,acrylic acid was used as a neutralizer to prepare bio-based WPU with an interpenetrating polymer network structure by thermally induced free radical emulsion polymerization.The effects of the content of acrylic acid on the properties of the resulting waterborne polyurethane-poly(acrylic acid)(WPU-PAA)dispersion and the films were systematically investigated.The results showed that the cross-linking density of the interpenetrating network polymers was increased and the interlocking structure of the soft and hard phase dislocations in the molecular segments of the double networks was tailored with increasing the content of acrylic acid,leading to enhancement of the mechanical properties and water resistance of WPU-PAA films.Notably,with the increase in content of acrylic acid,the tensile strength,Young’s modulus,and toughness of the WPU-PAA-110 film increased by 3 times,and 8 times,and 2.4 times compared with WPU-PAA-80,respectively.The WPU-PAA-100 film showed the best water resistance,and the water absorption rate at 96 h was only 3.27%.This work provided a new design scheme for constructing bio-based WPU materials with excellent properties.展开更多
The accumulation of undesirable deposits on the heat exchange surface represents a critical issue in industrial heat exchangers.Taking experimental measurements of the fouling is relatively difficult and,often,this me...The accumulation of undesirable deposits on the heat exchange surface represents a critical issue in industrial heat exchangers.Taking experimental measurements of the fouling is relatively difficult and,often,this method does not lead to precise results.To overcome these problems,in the present study,a new approach based on an Artificial Neural Network(ANN)is used to predict the fouling resistance as a function of specific measurable variables in the phosphoric acid concentration process.These include:the phosphoric acid inlet and outlet temperatures,the steam temperature,the phosphoric acid density,the phosphoric acid volume flow rate circulating in the loop.Some statistical accuracy indices are employed simultaneously to justify the interrelation between these independent variables and the fouling resistance and to select the best training algorithm allowing the determination of the optimal number of hidden neurons.In particular,the BFGS quasi-Newton back-propagation approach is found to be the most performing of the considered training algorithms.Furthermore,the best topology ANN for the shell and tube heat exchanger is obtained with a network consisting of one hidden layer with 13 neurons using a tangent sigmoid transfer function for the hidden and output layers.This model predicts the experimental values of the fouling resistance with AARD%=0.065,MSE=2.168×10^(−11),RMSE=4.656×10^(−6)and r^(2)=0.994.展开更多
Background:The purpose of the study was to investigatethe active ingredients and potential biochemicalmechanisms of Simiao Wan(SMW)in obesity-associated insulin resistance.Methods:An integrated network pharmacology me...Background:The purpose of the study was to investigatethe active ingredients and potential biochemicalmechanisms of Simiao Wan(SMW)in obesity-associated insulin resistance.Methods:An integrated network pharmacology method to screen the active compoundsand candidate targets,construct the protein-protein-interaction network,and ingredients-targets-pathways network was constructed for topological analysis to identify core targets and main ingredients.To find the possible signaling pathways,enrichment analysis was performed.Further,a model of insulin resistance in HL-7702 cells was established to verify the impact of SMW and the regulatory processes.Results:An overall of 63 active components and 151 candidate targets were obtained,in which flavonoids were the main ingredients.Enrichment analysis indicated that the PI3K-Akt signaling pathway was the potential pathway regulated by SMW in obesity-associated insulin resistance treatment.The result showed that SMW could significantly ameliorate insulin sensitivity,increase glucose synthesis and glucose utilization and reduce intracellular lipids accumulation in hepatocytes.Also,SMW inhibited diacylglycerols accumulation-induced PKCεactivity and decreased its translocation to the membrane.Conclusion:SMW ameliorated obesity-associated insulin resistance through PKCε/IRS-1/PI3K/Akt signaling axis in hepatocytes,providing a new strategy for metabolic disease treatment.展开更多
Pyrus pyrifolia,commonly known as sand pear,is a key economic fruit tree in temperate regions that possesses highly diverse germplasm resources for pear quality improvement.However,research on the relationship between...Pyrus pyrifolia,commonly known as sand pear,is a key economic fruit tree in temperate regions that possesses highly diverse germplasm resources for pear quality improvement.However,research on the relationship between resistance and fruit quality traits in the breeding of fruit species like pear is limited.Pan-transcriptomes effectively capture genetic information from coding regions and reflect variations in gene expression between individuals.Here,we constructed a pan-transcriptome based on 506 samples from different tissues of sand pear,and explored the intrinsic relationships among phenotypes and the selection for disease resistance during improvement based on expression presence/absence variations(eP AVs).The pan-transcriptome in this study contains 156,744 transcripts,among which the novel transcripts showed significant enrichment in the defense response.Interestingly,disease resistance genes are highly expressed in landraces of pear but have been selected against during the improvement of this perennial tree species.We found that the genetically diverse landraces can be divided into two subgroups and inferred that they have undergone different dispersal processes.Through co-expression network analysis,we confirmed that the formation of stone cells in pears,the synthesis of fruit anthocyanins,and the ability to resist stress are interrelated.They are jointly regulated by several modules,and the expression of regulatory genes has significant correlations with these three processes.Moreover,we identified candidate genes such as HKL1 that may affect sugar content and are missing from the reference genome.This study provides insights into the associations between complex fruit traits,while providing a database resource for pear disease resistance and fruit quality breeding.展开更多
With the continuous advancement of communication and unmanned aerial vehicle(UAV)technologies,the collaborative operations of diverse platforms,including UAVs and ground vehicles,have been significantly promoted.Howev...With the continuous advancement of communication and unmanned aerial vehicle(UAV)technologies,the collaborative operations of diverse platforms,including UAVs and ground vehicles,have been significantly promoted.However,battlefield uncertainties,such as equipment failures and enemy attacks,can impact these collaborative operations'stability and communication efficiency.To this end,we design a highly destruction-resistant air-ground cooperative resilient networking platform that aims to enhance the robustness of network communications by integrating ground vehicle information for UAV network deployment.It then incorporates the concept of virtual guiding force,enabling the UAV swarm to adaptively configure its network layout based on ground vehicle information,thereby improving network destruction resistance.Simulation results demonstrate that the UAV swarm involved in the proposed platform exhibits balanced flight energy consumption and excellent performance in network destruction resistance.展开更多
BACKGROUND Abnormal iron metabolism plays a critical role in paclitaxel(PTX)resistance in esophageal cancer cells.Qige San(QG)is a traditional Chinese herbal formula that is reported to improve short-term therapeutic ...BACKGROUND Abnormal iron metabolism plays a critical role in paclitaxel(PTX)resistance in esophageal cancer cells.Qige San(QG)is a traditional Chinese herbal formula that is reported to improve short-term therapeutic effects of esophageal cancer.AIM To investigate the effects and regulatory mechanisms involved in QG-targeted PTX-resistant esophageal cancer cells.METHODS Cell viability was assessed using the Cell Counting Kit-8 assay.Ferroptosis was evaluated by analyzing lipid reactive oxygen species accumulation and the Fe2+concentration in PTX-resistant esophageal cancer cells.Expression of ferroptosis regulators was measured by western blot.Network pharmacology analysis was employed to identify potential targets of QG in PTX-resistant esophageal cancer cells.RESULTS Treatment with QG significantly suppressed the viability,proliferation,and migration of PTX-resistant esophageal cancer cells and simultaneously induced ferroptosis.The network pharmacology analysis identified the phosphoinositide 3-kinase(PI3K)/protein kinase B signaling pathway as the potential target of QG in PTX-resistant esophageal cancer cells.Activation of the PI3K pathway notably reversed the ferroptosis of PTX-resistant esophageal cancer cells that was induced by QG.CONCLUSION QG could repress the resistance of esophageal cancer cells to PTX via targeting the PI3K signaling pathway.展开更多
In mine ventilation network calculation, the total ventilatiou perameters, such as total specific resistance and total natural veutilatiou pressure of an overall mine ventilation system, play an important role on sele...In mine ventilation network calculation, the total ventilatiou perameters, such as total specific resistance and total natural veutilatiou pressure of an overall mine ventilation system, play an important role on selecting main fan and regulating its operating point. This paper explains the critical effect of network’ s total parameter calculation on the above two aspects and presents a new method, the junction pressure composing method(JPC method), which can be applied to calculate the total resistance.of an overall, complex and multi-fan ventilation network. Based on the total ressistance and airflow rate of main fan, total specific resistance of a natwork is easily calculated. This method gets rid of those shortcomings in the route airflow working mathod(RAW method), greatly improves computing speed and adaptability, and can calculate the total parameters of a mine ventilation network rapidly and conveniently. This method is proved to be correct and reliable by example tests.展开更多
Defensin,an essential component of plant development,is indispensable in pathogen resistance.However,the molecular function of defensins under pathological conditions of Cytospora canker has not been characterized in ...Defensin,an essential component of plant development,is indispensable in pathogen resistance.However,the molecular function of defensins under pathological conditions of Cytospora canker has not been characterized in apple plants.The present study exhibits a detailed overview of the phylogeny and structure of 29 defensins(MdDEF)in apple.Expression analysis revealed that MdDEF genes were spatiotemporally diverse across apple tissues.Five MdDEF genes were found to be significantly up-regulated following a challenge with Cytospora mali.The transgenic overexpression of five defensin genes in apple calli enhanced resistance to C.mali.Among them,MdDEF30 was strongly induced and conferred the highest resistance level in vivo.Meanwhile,antifungal activity assays in vitro demonstrated that a recombinant protein produced from MdDEF30could inhibit the growth of C.mali.Notably,MdDEF30 promoted the accumulation of reactive oxygen species(ROS)and activated defense-related genes such as PR4,PR10,CML13,and MPK3.Co-expression regulatory network analysis showed that MdWRKY75 may regulate the expression of MdDEF30.Further yeast onehybrid(Y1H),luciferase,and chromatin Immunoprecipitation quantitative polymerase chain reaction(ChIPqPCR)assays verified that MdWRKY75 could directly bind to the promoter of MdDEF30.Importantly,pathogen inoculation assays confirmed that MdWRKY75 positively regulates resistance by transcriptionally activating MdDEF30.Overall,these results demonstrated that MdDEF30 promotes resistance to C.mali in apple plants and that MdWRKY75 regulates MdDEF30 expression during the induction of resistance,thereby clarifying biochemical mechanisms of resistance to C.mali in apple trees.展开更多
Overview of the DNA damage response(DDR)in tumor cells.DDR is a highly coordinated signaling network that repairs DNA damage caused by intrinsic cellular processes and extrinsic insults,thereby preventing genome insta...Overview of the DNA damage response(DDR)in tumor cells.DDR is a highly coordinated signaling network that repairs DNA damage caused by intrinsic cellular processes and extrinsic insults,thereby preventing genome instability.Depending on the type of damage,distinct DNA damage repair and DNA damage tolerance(DDT)pathways are involved and coordinately regulated.展开更多
An error back propagation （BP） neural network prediction model was established for the shunt current compensation in series resistance spot welding. The input variables for the neural network consist of the resistiv...An error back propagation （BP） neural network prediction model was established for the shunt current compensation in series resistance spot welding. The input variables for the neural network consist of the resistivity of the material, the thickness of workpiece and the spot spacing, and the shunt rate is outputted. A simplified calculation for the shunt rate was presented based on the feature of the constant-current resistance spot welding and the variation of the resistance in resistance spot welding process, and then the data generated by simplified calculation were used to train and adjust the neural network model. The neural network model proposed was used to predict the shunt rate in the spot welding of 20# mlid steel （in Chinese classification） （in 2. 0 mm thickness） and 10# mild steel （in 1.5 mm and 1.0 mm thickness）. The maximum relative prediction errors are, respectively, 2. 83%, 1.77% and 3.67%. Shunt current compensation experiments were peoCormed based on the neural network prediction model proposed to check the diameter difference of nuggets. Experimental results show that maximum nugget diameter deviation is less than 4% for both 10# and 20# mlid steels with spot spacing of 30 mm and 50 mm.展开更多
A numerical study on the multi-parameter control method based on nonlinear auto-regressive with exogenous input neural network （NARX） is presented here. Welding current was set as the input parameter; electrode disp...A numerical study on the multi-parameter control method based on nonlinear auto-regressive with exogenous input neural network （NARX） is presented here. Welding current was set as the input parameter; electrode displacement and dynamic resistance were set us the output parameters. The NARX model using these parameters was set up to simulate the multi-parameter resistance spot welding process. By comparing actual experimental data and NARX model output data, it was validated that the results from the model reflect the relationship between input parameter and output parameters correctly under the influence of many affecting factors.展开更多
The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL ...The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL for fungal disease resistance(FDR)in maize.However,different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies.The meta-QTL(MQTL)analysis is the meta-analysis of multiple QTL experiments,which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits.In the present study,128(33.59%)out of 381 reported QTL(from 82 studies)for FDR could be projected on the maize genome through MQTL analysis.It revealed 38 MQTL for FDR(12 diseases)on all chromosomes except chromosome 10.Five MQTL namely 1_4,2_4,3_2,3_4,and 5_4 were linked with multiple FDR.Total of 1910 candidate genes were identified for all the MQTL regions,with protein kinase gene families,TFs,pathogenesis-related,and disease-responsive proteins directly or indirectly associated with FDR.The comparison of physical positions of marker-traits association(MTAs)from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases.The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies.The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network,which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.展开更多
Natural stones used as floor and wall coverings are exposed to many different abrasive forces,so it is essential to choose suitable materials for wear resistance in terms of the life of the structure.The abrasion resi...Natural stones used as floor and wall coverings are exposed to many different abrasive forces,so it is essential to choose suitable materials for wear resistance in terms of the life of the structure.The abrasion resistance of natural stones can be determined in the laboratory by applying the B?hme abrasion resistance(BAR)test.However,the direct analysis of BAR in the laboratory has disadvantages such as wasting time and energy,experimental errors,and health impacts.To eliminate these disadvantages,the estimation of BAR using artificial neural networks(ANN)was proposed.Different natural stone samples were collected from Türkiye,and uniaxial compressive strength(UCS),flexural strength(FS),water absorption rate(WA),unit volume weight(UW),effective porosity(n),and BAR tests were carried out.The outputs of these tests were gathered and a data set,consisting of a total of 105 data,was randomly divided into two groups:testing and training.In the current study,the success of three different training algorithms of Levenberg-Marquardt(LM),Bayesian regularization(BR),and scaled conjugate gradient(SCG)were compared for BAR prediction of natural stones.Statistical criteria such as coefficient of determination(R~2),mean square error(MSE),mean square error(RMSE),and mean absolute percentage error(MAPE),which are widely used and adopted in the literature,were used to determine predictive validity.The findings of the study indicated that ANN is a valid method for estimating the BAR value.Also,the LM algorithm(R~2=0.9999,MSE=0.0001,RMSE=0.0110,and MAPE=0.0487)in training and the BR algorithm(R~2=0.9896,MSE=0.0589,RMSE=0.2427,and MAPE=1.2327)in testing showed the best prediction performance.It has been observed that the proposed method is quite practical to implement.Using the artificial neural networks method will provide an advantage in similar laborintensive experimental studies.展开更多
In view of the application importance of resistance network in modern science and technology, this paper presents the basic structure of a three terminals ladder shaped resistance network, for which, to study in- dept...In view of the application importance of resistance network in modern science and technology, this paper presents the basic structure of a three terminals ladder shaped resistance network, for which, to study in- depth the equivalent resistance, carry out network analysis by applying virtual current method and construct a model of two elements three orders differential equation. Based on different marginal conditions, two general adaptive rules for the three-terminal ladder shaped inlet resistance, as well as two ultimate rules for the equiva- lent resistance of three-terminal infinite ladder shaped were given.展开更多
Conventional artificial neural networks used to solve electrical resistivity imaging （ERI） inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian ne...Conventional artificial neural networks used to solve electrical resistivity imaging （ERI） inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network （PBNN） nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter αk, which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.展开更多
基金financially supported by the Guangdong Basic and Applied Basic Research Foundation(No.2020B0301030002)the National Key R&D Program of China(Nos.2022YFA1205301 and 2022YFA1205300)+1 种基金the National Natural Science Foundation of China(Nos.52188101 and 52273240)the LiaoNing Revitalization Talents Program(No.XLYC2201003).
文摘High-performance solid thermal interface materials(TIMs)are crucial for addressing overheating issues in high-power electronics,especially in extreme temperature environments.However,solid TIMs often suffer from poor topographical conformability to mating surfaces,limited deformability,large thickness,and low out-of-plane thermal conductivity,leading to high thermal resistance.Here,we fabricated a highly compressible 3D interconnected graphene lamellae network with abundant micro-bulges on its surface(SBGLN).The micro-bulges enable good topographical conformability to various solid substrates under pressure,and meanwhile,the lamellae can reconstruct the networks by deformation to enhance the out-of-plane thermal conductivity.Thus,the SBGLN achieves an ultra-low total thermal resistance of 0.081 cm^(2)K W^(−1)with a minimal bonding line thickness of 23μm,which are much better than those of previ-ously reported solid TIMs and state-of-the-art commercial TIMs.Moreover,it exhibits a negligible change in thermal resistance when subjected to heat shock at 160℃ for 80 h,in contrast to the 284%increase observed in thermal grease.These combined excellent properties,along with the ease of scaling up,establish the SBGLN as a highly reliable and high-performance solid TIMs for the thermal management of high-power electronics.
基金supported by the International Science and Technology Cooperation Program(No.2018KW-011)the National Key Research and Development Program of China(No.2016YFC0400706)+1 种基金the grant from "Young Outstanding Talents" in Universities of Shaanxi Provincesupport from the "Yanta Outstanding Youth Scholar" project from Xi'an University of Architecture and Technology(XAUAT)
文摘Wastewater treatment plants(WWTPs) are deemed reservoirs of antibiotic resistance genes(ARGs). Bacterial phylogeny can shape the resistome in activated sludge. However, the co-occurrence and interaction of ARGs abundance and bacterial communities in different WWTPs located at continental scales are still not comprehensively understood. Here, we applied quantitative PCR and Miseq sequence approaches to unveil the changing profiles of ARGs(sul1, sul2, tet W, tet Q, tet X), int I1 gene, and bacterial communities in 18 geographically distributed WWTPs. The results showed that the average relative abundance of sul1 and sul2 genes were 2.08 × 10^(-1) and 1.32 × 10^(-1) copies/16 S rRNA copies, respectively. The abundance of tet W gene was positively correlated with the Shannon diversity index(H′), while both studied sul genes had significant positive relationship with the int I1 gene. The highest average relative abundances of sul1, sul2, tet X, and int I1 genes were found in south region and oxidation ditch system. Network analysis found that 16 bacterial genera co-occurred with tet W gene. Co-occurrence patterns were revealed distinct community interactions between aerobic/anoxic/aerobic and oxidation ditch systems. The redundancy analysis model plot of the bacterial community composition clearly demonstrated that the sludge samples were significant differences among those from the different geographical areas,and the shifts in bacterial community composition were correlated with ARGs. Together,these findings from the present study will highlight the potential risks of ARGs and bacterial populations carrying these ARGs, and enable the development of suitable technique to control the dissemination of ARGs from WWTPs into aquatic environments.
文摘The end value of the dynamic resistance curve of stainless steel was proved to have strong correlation with nugget size by experiments, so it was an important factor for estimation of weld quality. BP neural network was employed to estimate the weld quality, The end value of the dynamic resistance curve, welding current and welding time were selected as the input variables while the nugget diameter, which is closely related to weld quality, was selected as the output variable. Testing results shows that such network has fine fault tolerance and real-time quality estimation is possible.
基金supported by the Key Research and Development Program of Shaanxi Province (2019ZDLSF03-06) and (2020ZDLGY13-05)the National Key Research and Development Program of China (2020YFC1107202)。
文摘Magnesium(Mg) and its alloys have been intensively studied to develop the next generation of bone implants recently, but their clinical application is restricted by rapid degradation and unsatisfied osteogenic effect in vivo. A bioactive chemical conversion Mg-phenolic networks complex coating(e EGCG) was stepwise incorporated by epigallocatechin-3-gallate(EGCG) and exogenous Mg^(2+)on Mg-2Zn magnesium alloy. Simplex EGCG induced chemical conversion coating(c EGCG) was set as compare group. The in vitro corrosion behavior of Mg-2Zn alloy, c EGCG and e EGCG was evaluated in SBF using electrochemical(PDP, EIS) and immersion test. The cytocompatibility was investigated with rat bone marrow mesenchymal stem cells(r BMSCs). Furthermore, the in vivo tests using a rabbit model involved micro computed tomography(Micro-CT) analysis, histological observation, and interface analysis. The results showed that the e EGCG is Mgphenolic multilayer coating incorporated Mg-phenolic networks, which is rougher, more compact and much thicker than c EGCG. The e EGCG highly improved the corrosion resistance of Mg-2Zn alloy, combined with its lower average hemolytic ratios, continuous high scavenging effect ability and relatively moderate contact angle features, resulting in a stable and suitable biological environment, obviously promoted r BMSCs adhesion and proliferation. More importantly, Micro-CT, histological and interface elements distribution evaluations all revealed that the e EGCG effectively inhibited degradation and enhanced bone tissue formation of Mg alloy implants. This study puts forward a promising bioactive chemical conversion coating with Mg-phenolic networks for the application of biodegradable orthopedic implants.
基金by the Research and Development Program in Key Areas of Guangdong Province(Grant No.2020B0202010008)Guangdong Province Science&Technology Program(2018B030306016)+1 种基金Guangdong Provincial Innovation Team for General Key Technologies in Modern Agricultural Industry(2019KJ133)Key Projects of Basic Research and Applied Basic Research of the Higher Education Institutions of Guangdong Province(2018KZDXM014).
文摘In this study,acrylic acid was used as a neutralizer to prepare bio-based WPU with an interpenetrating polymer network structure by thermally induced free radical emulsion polymerization.The effects of the content of acrylic acid on the properties of the resulting waterborne polyurethane-poly(acrylic acid)(WPU-PAA)dispersion and the films were systematically investigated.The results showed that the cross-linking density of the interpenetrating network polymers was increased and the interlocking structure of the soft and hard phase dislocations in the molecular segments of the double networks was tailored with increasing the content of acrylic acid,leading to enhancement of the mechanical properties and water resistance of WPU-PAA films.Notably,with the increase in content of acrylic acid,the tensile strength,Young’s modulus,and toughness of the WPU-PAA-110 film increased by 3 times,and 8 times,and 2.4 times compared with WPU-PAA-80,respectively.The WPU-PAA-100 film showed the best water resistance,and the water absorption rate at 96 h was only 3.27%.This work provided a new design scheme for constructing bio-based WPU materials with excellent properties.
文摘The accumulation of undesirable deposits on the heat exchange surface represents a critical issue in industrial heat exchangers.Taking experimental measurements of the fouling is relatively difficult and,often,this method does not lead to precise results.To overcome these problems,in the present study,a new approach based on an Artificial Neural Network(ANN)is used to predict the fouling resistance as a function of specific measurable variables in the phosphoric acid concentration process.These include:the phosphoric acid inlet and outlet temperatures,the steam temperature,the phosphoric acid density,the phosphoric acid volume flow rate circulating in the loop.Some statistical accuracy indices are employed simultaneously to justify the interrelation between these independent variables and the fouling resistance and to select the best training algorithm allowing the determination of the optimal number of hidden neurons.In particular,the BFGS quasi-Newton back-propagation approach is found to be the most performing of the considered training algorithms.Furthermore,the best topology ANN for the shell and tube heat exchanger is obtained with a network consisting of one hidden layer with 13 neurons using a tangent sigmoid transfer function for the hidden and output layers.This model predicts the experimental values of the fouling resistance with AARD%=0.065,MSE=2.168×10^(−11),RMSE=4.656×10^(−6)and r^(2)=0.994.
基金supported by the National Natural Science Foundation of China(81903871)Natural Science Foundation of Jiangsu Province(BK20190565)+1 种基金Fundamental Research Funds for the Central Universities(2632021ZD16)Zhenjiang City 2022 Science and Technology Innovation Fund(SH2022084).
文摘Background:The purpose of the study was to investigatethe active ingredients and potential biochemicalmechanisms of Simiao Wan(SMW)in obesity-associated insulin resistance.Methods:An integrated network pharmacology method to screen the active compoundsand candidate targets,construct the protein-protein-interaction network,and ingredients-targets-pathways network was constructed for topological analysis to identify core targets and main ingredients.To find the possible signaling pathways,enrichment analysis was performed.Further,a model of insulin resistance in HL-7702 cells was established to verify the impact of SMW and the regulatory processes.Results:An overall of 63 active components and 151 candidate targets were obtained,in which flavonoids were the main ingredients.Enrichment analysis indicated that the PI3K-Akt signaling pathway was the potential pathway regulated by SMW in obesity-associated insulin resistance treatment.The result showed that SMW could significantly ameliorate insulin sensitivity,increase glucose synthesis and glucose utilization and reduce intracellular lipids accumulation in hepatocytes.Also,SMW inhibited diacylglycerols accumulation-induced PKCεactivity and decreased its translocation to the membrane.Conclusion:SMW ameliorated obesity-associated insulin resistance through PKCε/IRS-1/PI3K/Akt signaling axis in hepatocytes,providing a new strategy for metabolic disease treatment.
基金supported by the National Science Foundation of China(32230097)the National Key Research and Development Program of China(2022YFD1200503)+2 种基金the earmarked fund for China Agriculture Research System(CARS-28)the earmarked fund for Jiangsu Agricultural Industry Technology System(JATS[2023]412)the Natural Science Foundation of Jiangsu Province for Young Scholar,China(BK20221010)。
文摘Pyrus pyrifolia,commonly known as sand pear,is a key economic fruit tree in temperate regions that possesses highly diverse germplasm resources for pear quality improvement.However,research on the relationship between resistance and fruit quality traits in the breeding of fruit species like pear is limited.Pan-transcriptomes effectively capture genetic information from coding regions and reflect variations in gene expression between individuals.Here,we constructed a pan-transcriptome based on 506 samples from different tissues of sand pear,and explored the intrinsic relationships among phenotypes and the selection for disease resistance during improvement based on expression presence/absence variations(eP AVs).The pan-transcriptome in this study contains 156,744 transcripts,among which the novel transcripts showed significant enrichment in the defense response.Interestingly,disease resistance genes are highly expressed in landraces of pear but have been selected against during the improvement of this perennial tree species.We found that the genetically diverse landraces can be divided into two subgroups and inferred that they have undergone different dispersal processes.Through co-expression network analysis,we confirmed that the formation of stone cells in pears,the synthesis of fruit anthocyanins,and the ability to resist stress are interrelated.They are jointly regulated by several modules,and the expression of regulatory genes has significant correlations with these three processes.Moreover,we identified candidate genes such as HKL1 that may affect sugar content and are missing from the reference genome.This study provides insights into the associations between complex fruit traits,while providing a database resource for pear disease resistance and fruit quality breeding.
基金supported by the Researchers Supporting Project of King Saud University,Riyadh,Saudi Arabia,under Project RSPD2025R681。
文摘With the continuous advancement of communication and unmanned aerial vehicle(UAV)technologies,the collaborative operations of diverse platforms,including UAVs and ground vehicles,have been significantly promoted.However,battlefield uncertainties,such as equipment failures and enemy attacks,can impact these collaborative operations'stability and communication efficiency.To this end,we design a highly destruction-resistant air-ground cooperative resilient networking platform that aims to enhance the robustness of network communications by integrating ground vehicle information for UAV network deployment.It then incorporates the concept of virtual guiding force,enabling the UAV swarm to adaptively configure its network layout based on ground vehicle information,thereby improving network destruction resistance.Simulation results demonstrate that the UAV swarm involved in the proposed platform exhibits balanced flight energy consumption and excellent performance in network destruction resistance.
基金Supported by Zhejiang Traditional Chinese Medicine Administration,No.2024ZL944.
文摘BACKGROUND Abnormal iron metabolism plays a critical role in paclitaxel(PTX)resistance in esophageal cancer cells.Qige San(QG)is a traditional Chinese herbal formula that is reported to improve short-term therapeutic effects of esophageal cancer.AIM To investigate the effects and regulatory mechanisms involved in QG-targeted PTX-resistant esophageal cancer cells.METHODS Cell viability was assessed using the Cell Counting Kit-8 assay.Ferroptosis was evaluated by analyzing lipid reactive oxygen species accumulation and the Fe2+concentration in PTX-resistant esophageal cancer cells.Expression of ferroptosis regulators was measured by western blot.Network pharmacology analysis was employed to identify potential targets of QG in PTX-resistant esophageal cancer cells.RESULTS Treatment with QG significantly suppressed the viability,proliferation,and migration of PTX-resistant esophageal cancer cells and simultaneously induced ferroptosis.The network pharmacology analysis identified the phosphoinositide 3-kinase(PI3K)/protein kinase B signaling pathway as the potential target of QG in PTX-resistant esophageal cancer cells.Activation of the PI3K pathway notably reversed the ferroptosis of PTX-resistant esophageal cancer cells that was induced by QG.CONCLUSION QG could repress the resistance of esophageal cancer cells to PTX via targeting the PI3K signaling pathway.
文摘In mine ventilation network calculation, the total ventilatiou perameters, such as total specific resistance and total natural veutilatiou pressure of an overall mine ventilation system, play an important role on selecting main fan and regulating its operating point. This paper explains the critical effect of network’ s total parameter calculation on the above two aspects and presents a new method, the junction pressure composing method(JPC method), which can be applied to calculate the total resistance.of an overall, complex and multi-fan ventilation network. Based on the total ressistance and airflow rate of main fan, total specific resistance of a natwork is easily calculated. This method gets rid of those shortcomings in the route airflow working mathod(RAW method), greatly improves computing speed and adaptability, and can calculate the total parameters of a mine ventilation network rapidly and conveniently. This method is proved to be correct and reliable by example tests.
基金funded by the National Key R&D Program of China(2023YFD1401401)the China Agriculture Research System(CARS27)。
文摘Defensin,an essential component of plant development,is indispensable in pathogen resistance.However,the molecular function of defensins under pathological conditions of Cytospora canker has not been characterized in apple plants.The present study exhibits a detailed overview of the phylogeny and structure of 29 defensins(MdDEF)in apple.Expression analysis revealed that MdDEF genes were spatiotemporally diverse across apple tissues.Five MdDEF genes were found to be significantly up-regulated following a challenge with Cytospora mali.The transgenic overexpression of five defensin genes in apple calli enhanced resistance to C.mali.Among them,MdDEF30 was strongly induced and conferred the highest resistance level in vivo.Meanwhile,antifungal activity assays in vitro demonstrated that a recombinant protein produced from MdDEF30could inhibit the growth of C.mali.Notably,MdDEF30 promoted the accumulation of reactive oxygen species(ROS)and activated defense-related genes such as PR4,PR10,CML13,and MPK3.Co-expression regulatory network analysis showed that MdWRKY75 may regulate the expression of MdDEF30.Further yeast onehybrid(Y1H),luciferase,and chromatin Immunoprecipitation quantitative polymerase chain reaction(ChIPqPCR)assays verified that MdWRKY75 could directly bind to the promoter of MdDEF30.Importantly,pathogen inoculation assays confirmed that MdWRKY75 positively regulates resistance by transcriptionally activating MdDEF30.Overall,these results demonstrated that MdDEF30 promotes resistance to C.mali in apple plants and that MdWRKY75 regulates MdDEF30 expression during the induction of resistance,thereby clarifying biochemical mechanisms of resistance to C.mali in apple trees.
基金the National Natural Science Foundation of China(Grant No.82330090 and Grant No.82341006 to C.G.)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA0460403 to C.G.)the Natural Science Foundation of Shanxi Province(Grant No.202203021211155 to X.M.).
文摘Overview of the DNA damage response(DDR)in tumor cells.DDR is a highly coordinated signaling network that repairs DNA damage caused by intrinsic cellular processes and extrinsic insults,thereby preventing genome instability.Depending on the type of damage,distinct DNA damage repair and DNA damage tolerance(DDT)pathways are involved and coordinately regulated.
基金Acknowledgements The authors would like to thank for the financial support from the National Natural Science Foundation of China through document 51275418. The authors would also like to acknowledge professor Yang Siqian for providing discussion of the results for this study.
文摘An error back propagation （BP） neural network prediction model was established for the shunt current compensation in series resistance spot welding. The input variables for the neural network consist of the resistivity of the material, the thickness of workpiece and the spot spacing, and the shunt rate is outputted. A simplified calculation for the shunt rate was presented based on the feature of the constant-current resistance spot welding and the variation of the resistance in resistance spot welding process, and then the data generated by simplified calculation were used to train and adjust the neural network model. The neural network model proposed was used to predict the shunt rate in the spot welding of 20# mlid steel （in Chinese classification） （in 2. 0 mm thickness） and 10# mild steel （in 1.5 mm and 1.0 mm thickness）. The maximum relative prediction errors are, respectively, 2. 83%, 1.77% and 3.67%. Shunt current compensation experiments were peoCormed based on the neural network prediction model proposed to check the diameter difference of nuggets. Experimental results show that maximum nugget diameter deviation is less than 4% for both 10# and 20# mlid steels with spot spacing of 30 mm and 50 mm.
文摘A numerical study on the multi-parameter control method based on nonlinear auto-regressive with exogenous input neural network （NARX） is presented here. Welding current was set as the input parameter; electrode displacement and dynamic resistance were set us the output parameters. The NARX model using these parameters was set up to simulate the multi-parameter resistance spot welding process. By comparing actual experimental data and NARX model output data, it was validated that the results from the model reflect the relationship between input parameter and output parameters correctly under the influence of many affecting factors.
基金supported by Indian Council of Agricultural Research(ICAR),New Delhi for assistance.
文摘The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL for fungal disease resistance(FDR)in maize.However,different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies.The meta-QTL(MQTL)analysis is the meta-analysis of multiple QTL experiments,which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits.In the present study,128(33.59%)out of 381 reported QTL(from 82 studies)for FDR could be projected on the maize genome through MQTL analysis.It revealed 38 MQTL for FDR(12 diseases)on all chromosomes except chromosome 10.Five MQTL namely 1_4,2_4,3_2,3_4,and 5_4 were linked with multiple FDR.Total of 1910 candidate genes were identified for all the MQTL regions,with protein kinase gene families,TFs,pathogenesis-related,and disease-responsive proteins directly or indirectly associated with FDR.The comparison of physical positions of marker-traits association(MTAs)from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases.The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies.The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network,which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.
文摘Natural stones used as floor and wall coverings are exposed to many different abrasive forces,so it is essential to choose suitable materials for wear resistance in terms of the life of the structure.The abrasion resistance of natural stones can be determined in the laboratory by applying the B?hme abrasion resistance(BAR)test.However,the direct analysis of BAR in the laboratory has disadvantages such as wasting time and energy,experimental errors,and health impacts.To eliminate these disadvantages,the estimation of BAR using artificial neural networks(ANN)was proposed.Different natural stone samples were collected from Türkiye,and uniaxial compressive strength(UCS),flexural strength(FS),water absorption rate(WA),unit volume weight(UW),effective porosity(n),and BAR tests were carried out.The outputs of these tests were gathered and a data set,consisting of a total of 105 data,was randomly divided into two groups:testing and training.In the current study,the success of three different training algorithms of Levenberg-Marquardt(LM),Bayesian regularization(BR),and scaled conjugate gradient(SCG)were compared for BAR prediction of natural stones.Statistical criteria such as coefficient of determination(R~2),mean square error(MSE),mean square error(RMSE),and mean absolute percentage error(MAPE),which are widely used and adopted in the literature,were used to determine predictive validity.The findings of the study indicated that ANN is a valid method for estimating the BAR value.Also,the LM algorithm(R~2=0.9999,MSE=0.0001,RMSE=0.0110,and MAPE=0.0487)in training and the BR algorithm(R~2=0.9896,MSE=0.0589,RMSE=0.2427,and MAPE=1.2327)in testing showed the best prediction performance.It has been observed that the proposed method is quite practical to implement.Using the artificial neural networks method will provide an advantage in similar laborintensive experimental studies.
基金a project financed by Natural Science Fund of Education Department of Jiangsu Province (02KJB140008)
文摘In view of the application importance of resistance network in modern science and technology, this paper presents the basic structure of a three terminals ladder shaped resistance network, for which, to study in- depth the equivalent resistance, carry out network analysis by applying virtual current method and construct a model of two elements three orders differential equation. Based on different marginal conditions, two general adaptive rules for the three-terminal ladder shaped inlet resistance, as well as two ultimate rules for the equiva- lent resistance of three-terminal infinite ladder shaped were given.
基金supported by the National Natural Science Foundation of China(Grant No.41374118)the Research Fund for the Higher Education Doctoral Program of China(Grant No.20120162110015)+3 种基金the China Postdoctoral Science Foundation(Grant No.2015M580700)the Hunan Provincial Natural Science Foundation,the China(Grant No.2016JJ3086)the Hunan Provincial Science and Technology Program,China(Grant No.2015JC3067)the Scientific Research Fund of Hunan Provincial Education Department,China(Grant No.15B138)
文摘Conventional artificial neural networks used to solve electrical resistivity imaging （ERI） inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network （PBNN） nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter αk, which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.
