Electrochemical nitrogen reduction reaction(ENRR)is emerging as a favorable option to the power-intensive Haber-Bosch process for ammonia synthesis.However,obstacles such as poor selectivity,low production rates,and c...Electrochemical nitrogen reduction reaction(ENRR)is emerging as a favorable option to the power-intensive Haber-Bosch process for ammonia synthesis.However,obstacles such as poor selectivity,low production rates,and competition against the hydrogen evolution reaction hinder its practical implementation.To address these,the design of highly active catalysts is critical.Single-atom catalysts(SACs)have shown great potential because of their maximized atom utilization,but their limited stability and low metal loading restrict their performances.On the other hand,dual-atom catalysts(DACs)are atomic catalysts with two metal atoms nearby and offer enhanced electrocatalytic performances by aligning with the N≡N bond to enhance N2 reduction efficiency,potentially overcoming the limitations of SAC.This review discusses recent advances in SACs and more importantly DACs for ENRR,highlighting their advantages,limitations,and the need for advanced characterization techniques to better understand catalyst behavior.The review concludes by underscoring the importance of research to optimize these catalysts for efficient and sustainable nitrogen fixation.展开更多
A facile method to fabricate tough and highly stretchable polyacrylamide （PAM） nanocomposite physical hydrogel （NCP gel） was proposed. The hydrogels are dually crosslinked single network with the PAM grafted vinyl...A facile method to fabricate tough and highly stretchable polyacrylamide （PAM） nanocomposite physical hydrogel （NCP gel） was proposed. The hydrogels are dually crosslinked single network with the PAM grafted vinyl hybrid silica nanoparticles （VSNPs） as the analogous covalent crosslinking points and the reversible hydrogen bonds among the PAM chains as the physical crosslinking points. In order to further elucidate the toughening mechanism of the PAM NCP gel, especially to understand the role of the dual crosslinking points, the PAM hybrid hydrogels （H gels） and a series of poly（acrylamide-co-dimethylacrylamide） （P（AM-co-DMAA）） NCP gels were designed and fabricated. Their mechanical properties were compared with those of the PAM NCP gels. The PAM H gels are prepared by simply mixing the PAM chains with bare silica nanoparticles （SNPs）. Relative to the poor mechanical properties of the PAM H gel, the PAM NCP gel is remarkably tough and stretchable and also generates large number of micro-cracks to stop notch propagation, indicating the important role of PAM grafted VSNPs in toughening the NCP gel. In the P（AM-co-DMAA） NCP gels, the P（AM-co- DMAA） chains are grafted on VSNPs and the polydimethylacrylamide （PDMAA） only forms very weak hydrogen bonds between themselves. It is found that mechanical properties of the PAM NCP gel, such as the tensile strength and the elongation at break, are enhanced significantly, but those of the P（AM-co-DMAA） NCP gels decreased rapidly with decreasing AM content. This result reveals the role of the hydrogen bonds among the grafted polymer chains as the physical crosslinking points in toughening the NCP gel.展开更多
The single event effects(SEEs)evaluations caused by atmospheric neutrons were conducted on three different convolutional neural network(CNN)models(Yolov3,MNIST,and ResNet50)in the atmospheric neutron irradiation spect...The single event effects(SEEs)evaluations caused by atmospheric neutrons were conducted on three different convolutional neural network(CNN)models(Yolov3,MNIST,and ResNet50)in the atmospheric neutron irradiation spectrometer(ANIS)at the China Spallation Neutron Source(CSNS).The Yolov3 and MNIST models were implemented on the XILINX28-nm system-on-chip(So C).Meanwhile,the Yolov3 and ResNet50 models were deployed on the XILINX 16-nm Fin FET Ultra Scale+MPSoC.The atmospheric neutron SEEs on the tested CNN systems were comprehensively evaluated from six aspects,including chip type,network architecture,deployment methods,inference time,datasets,and the position of the anchor boxes.The various types of SEE soft errors,SEE cross-sections,and their distribution were analyzed to explore the radiation sensitivities and rules of 28-nm and 16-nm SoC.The current research can provide the technology support of radiation-resistant design of CNN system for developing and applying high-reliability,long-lifespan domestic artificial intelligence chips.展开更多
BACKGROUND Peripheral artery disease(PAD)affects millions globally,with a 5.6%prevalence in 2015 impacting 236 million adults,rising above 10%in those over 60 due to factors like diabetes and smoking.Post-revasculariz...BACKGROUND Peripheral artery disease(PAD)affects millions globally,with a 5.6%prevalence in 2015 impacting 236 million adults,rising above 10%in those over 60 due to factors like diabetes and smoking.Post-revascularization,single antiplatelet therapy(SAPT)is standard,but dual antiplatelet therapy(DAPT)may improve outcomes,though duration and bleeding risks are unclear.The 2024 American College of Cardiology/American Heart Association guidelines endorse short-term DAPT,yet evidence gaps remain in comparative efficacy and safety.We hypothesized that DAPT reduces cardiovascular events and reinterventions vs SAPT without significantly elevating bleeding in PAD patients’post-lower extremity revascularization.AIM To evaluate the efficacy and safety of DAPT vs SAPT in PAD patients’post-revascularization.METHODS This systematic review and meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines,searching PubMed,EMBASE,and ScienceDirect up to July 2025.Included were randomized controlled trials(RCTs)and cohort studies from various global settings(e.g.,hospitals,tertiary care)comparing DAPT(aspirin plus P2Y12 inhibitor for>1 month)to SAPT in symptomatic PAD patients undergoing endovascular or surgical revascularization(n up to 28244 participants selected via eligibility criteria).Data were pooled using random-effects models for risk ratio(RR)with 95%CI;heterogeneity was assessed via the I²statistic.Quality appraisal used Risk of Bias in Non-randomized Studies of Interventions for cohorts and Risk of Bias 2.0 for RCTs;certainty was evaluated via Grading of Recommendations Assessment,Development and Evaluation(GRADE).RESULTS Twelve studies(3 RCTs,9 cohorts,conducted 2010–2025 with follow-ups of 6 months to 5 years)were included.DAPT showed no significant difference but a trend toward reduced all-cause mortality(RR:0.52,95%CI:0.27–1.01,P=0.05,DAPT of 298/9545 events vs SAPT of 165/566 events)or stroke(RR:0.72,95%CI:0.30–1.72,P=0.46,DAPT of 16/3729 events vs SAPT of 41/7673 events)vs SAPT.DAPT significantly reduced cardiac mortality(RR:0.46,95%CI:0.27–0.80,P=0.006,DAPT of 78/2903 events vs SAPT of 171/1465 events,risk difference:-5.4%),myocardial infarction(RR:0.82,95%CI:0.71–0.94,P=0.004,DAPT of 233/7704 events vs SAPT of 262/9130 events,risk difference:-1.8%),and major reintervention(RR:0.58,95%CI:0.35–0.98,P=0.04,DAPT of 803/205 events vs SAPT of 1197/4 events,risk difference:-42%).Bleeding showed no difference(RR:1.12,95%CI:0.42–3.03,P=0.82,DAPT of 195/2775 events vs SAPT of 202/8234 events).Heterogeneity was high(I^(2)=59%–97%).Quality revealed moderate to serious bias in cohorts and some concerns in RCTs;GRADE certainty moderate for cardiac mortality,myocardial infarction,reintervention,low for others due to inconsistency and imprecision.CONCLUSION DAPT reduces cardiac mortality,myocardial infarction,and major reintervention risks compared to SAPT in PAD post-revascularization without apparent bleeding increase,though limited by heterogeneity and low certainty for some outcomes.展开更多
In this paper a scheme for quantum secure direct communication （QSDC） network is proposed with a sequence of polarized single photons. The single photons are prepared originally in the same state （0） by the server...In this paper a scheme for quantum secure direct communication （QSDC） network is proposed with a sequence of polarized single photons. The single photons are prepared originally in the same state （0） by the servers on the network, which will reduce the difficulty for the legitimate users to check eavesdropping largely. The users code the information on the single photons with two unitary operations which do not change their measuring bases. Some decoy photons, which are produced by operating the sample photons with a Hadamard, are used for preventing a potentially dishonest server from eavesdropping the quantum lines freely. This scheme is an economical one as it is the easiest way for QSDC network communication securely.展开更多
Sulfide-based all-solid-state lithium batteries suffer from electrochemo-mechanical damage to Ni-rich oxide-based cathode active materials(CAMs),primarily caused by severe volume changes,results in significant stress ...Sulfide-based all-solid-state lithium batteries suffer from electrochemo-mechanical damage to Ni-rich oxide-based cathode active materials(CAMs),primarily caused by severe volume changes,results in significant stress and strain,causes micro-cracks and interfacial contact loss at potentials>4.3 V(vs.Li/Li^(+)).Quantifying micro-cracks and voids in CAMs can reveal the degradation mechanisms of Ni-rich oxidebased cathodes during electrochemical cycling.Nonetheless,the origin of electrochemical-mechanical damage remains unclear.Herein,We have developed a multifunctional PEG-based soft buffer layer(SBL)on the surface of carbon black(CB).This layer functions as a percolation network in the single crystal LiNi_(0.83)Co_(0.07)Mn_(0.1)O_(2)and Li_(6)PS_(5)Cl composite cathode layer,ensuring superior ionic conductivity,reducing void formation and particle cracking,and promoting uniform utilization of the cathode active material in all-solid-state lithium batteries(ASSLBs).High-angle annular dark-field STEM combined with nanoscale X-ray holo-tomography and plasma-focused ion beam scanning electron microscopy confirmed that the PEG-based SBL mitigated strain induced by reaction heterogeneity in the cathode.This strain produces lattice stretches,distortions,and curved transition metal oxide layers near the surface,contributing to structural degradation at elevated voltages.Consequently,ASSLBs with a LiNi_(0.83)Co_(0.07)Mn_(0.1)O_(2)cathode containing LCCB-10(CB/PEG mass ratio:100/10)demonstrate a high areal capacity(2.53 mAh g^(-1)/0.32 mA g^(-1))and remarkable rate capability(0.58 mAh g^(-1)at 1.4 mA g^(-1)),with88%capacity retention over 1000 cycles.展开更多
Since the oil production of single well in water flooding reservoir varies greatly and is hard to predict, an oil production prediction method of single well based on temporal convolutional network(TCN) is proposed an...Since the oil production of single well in water flooding reservoir varies greatly and is hard to predict, an oil production prediction method of single well based on temporal convolutional network(TCN) is proposed and verified. This method is started from data processing, the correspondence between water injectors and oil producers is determined according to the influence radius of the water injectors, the influence degree of a water injector on an oil producer in the month concerned is added as a model feature, and a Random Forest(RF) model is built to fill the dynamic data of water flooding. The single well history is divided into 4 stages according to its water cut, that is, low water cut, middle water cut, high water cut and extra-high water cut stages. In each stage, a TCN based prediction model is established, hyperparameters of the model are optimized by the Sparrow Search Algorithm(SSA). Finally, the models of the 4 stages are integrated into one whole-life model of the well for production prediction. The application of this method in Daqing Oilfield, NE China shows that:(1) Compared with conventional data processing methods, the data obtained by this processing method are more close to the actual production, and the data set obtained is more authentic and complete.(2) The TCN model has higher prediction accuracy than other 11 models such as Long Short Term Memory(LSTM).(3) Compared with the conventional full-life-cycle models, the model of integrated stages can significantly reduce the error of production prediction.展开更多
Study of gene expression has been arguably the most active research field in functional genomics.Over the last two decades,various high-throughput technologies,from gene expression microarray to RNA-seq,have been wide...Study of gene expression has been arguably the most active research field in functional genomics.Over the last two decades,various high-throughput technologies,from gene expression microarray to RNA-seq,have been widely applied to the wholegenome profiling of gene expression.The commonality of these experiments is that they measure the gene expression levels of"bulk"sample,which pools a large number(often in the scale of millions)of cells,and thus the measurements reflect the average expression展开更多
Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial expressions.Numerous deep neural networks(DNNs)with convolutional structures have been pr...Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial expressions.Numerous deep neural networks(DNNs)with convolutional structures have been proposed.However,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small datasets.Still,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective features.To address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-XgBoost)is introduced for ME Recognition.The proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical Flow TV-L1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective features.The outputs are then fused,concatenated,and classified using the XgBoost algorithm.This comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of XgBoost.The proposed method is evaluated on three publicly available ME databases named Chinese Academy of Sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent models.The accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the F1-score are 75.47%,68.91%,and 63.84%,respectively.The proposed method has the advantage of operational efficiency and less computational time.展开更多
The interactions between the moving dislocation within matrix channel and the interfacial misfit dislocation networks on the two-phase interfaces in Ni-based single crystal superalloys are studied carefully via atomic...The interactions between the moving dislocation within matrix channel and the interfacial misfit dislocation networks on the two-phase interfaces in Ni-based single crystal superalloys are studied carefully via atomic modeling, with special focus on the factors influ- encing the critical bowing stress of moving dislocations in the matrix channel. The results show that the moving matrix dislocation type and its position with respect to the interfacial misfit dislocation segments have considerable influences on the interactions. If the moving matrix dislocation is pure screw, it reacts with the interracial misfit dislocation segments toward dislocation linear energy reduction, which decreases the critical bowing stress of screw dislocation due to dislocation linear energy release during the dislocation reactions. If the moving matrix dislocation is of 60^-mixed type, it is obstructed by the interaction between the mixed matrix dislocations and the misfit interfacial dislocation segments. As a result, the critical bowing stress increases significantly because extra interactive energy needs to be overcome. These two different effects on the critical bowing stress become in- creasingly significant when the moving matrix dislocation is very close to the interracial misfit dislocation segments. In addition, the matrix channel width also has a significant influence on the critical bowing stress, i.e. the narrower the matrix channel is, the higher the critical bowing stress is. The classical Orowan formula is modified to predict these effects on the critical bowing stress of moving matrix dislocation, which is in good agreement with the computational results.展开更多
In this letter, we present a novel integrated feature that incorporates traditional parameters, and adopt a parallel cascading fashion network Haze Net for enhancing image quality. Our unified feature is a complete in...In this letter, we present a novel integrated feature that incorporates traditional parameters, and adopt a parallel cascading fashion network Haze Net for enhancing image quality. Our unified feature is a complete integration, and its role is to directly describe the effects of haze. In Haze Net, we design two separate structures including backbone and auxiliary networks to extract feature map. Backbone network is responsible for extracting high-level feature map, and low-level feature learned by the auxiliary network can be interpreted as fine-grained feature. After cascading two features with different accuracy, final performance can be effectively improved. Extensive experimental results on both synthetic datasets and real-world images prove the superiority of the proposed method, and demonstrate more favorable performance compared with the existing state-of-art methods.展开更多
With the explosive growth of computational resources and data generation,deep machine learning has been successfully employed in various applications.One important and emerging scientific application of deep learning ...With the explosive growth of computational resources and data generation,deep machine learning has been successfully employed in various applications.One important and emerging scientific application of deep learning involves solving differential equations.Here,physics-informed neural networks(PINNs)are developed to solve the differential equations associated with a specific scientific problem.As such,algorithms for solving the differential equations by embedding their initial and boundary conditions in the cost function of the artificial neural networks using algorithmic differentiation must also be developed.In this study,various PINNs are adopted to estimate the stresses in the tablets and the interphase of a single lap joint.The proposed model is represented by two fourth-order non-homogeneous coupled partial differential equations,with the axial stresses in the upper and lower tablets adopted as the dependent variables.The axial stresses are a function of the tablet length,which presents the independent variable.Therefore,the axial stresses in the tablets are estimated by solving the coupled partial differential equations when subjected to the boundary conditions,whereas the remaining stress components are expressed in terms of axial stresses.The results obtained using the developed methodology are validated using the results obtained via MAPLE software.展开更多
Dual three-phase permanent-magnet synchronous machines(DTP-PMSM)connected with a single neutral point provide a loop for zero-sequence current(ZSC).This paper proposes a novel space vector pulse width modulation(SVPWM...Dual three-phase permanent-magnet synchronous machines(DTP-PMSM)connected with a single neutral point provide a loop for zero-sequence current(ZSC).This paper proposes a novel space vector pulse width modulation(SVPWM)strategy to suppress the ZSC.Five vectors are selected as basic voltage vectors in one switching period.The fundamental and harmonic planes and the zero-sequence plane are taken into consideration to synthesis the reference voltage vector.To suppress the ZSC,a non-zero zero-sequence voltage(ZSV)is generated to compensate the third harmonic back-EMF.Rather than triangular carrier modulation,the sawtooth carrier modulation strategy is used to generate asymmetric PWM signals.The modulation range is investigated to explore the variation of modulation range caused by considering the zero-sequence plane.With the proposed method,the ZSC can be considerably reduced.The simulated and experimental results are presented to validate the effectiveness of the proposed modulation strategy.展开更多
Nitrogen reduction reaction (NRR) is a clean mode of energy conversion and the development of highly efficient NRR electrocatalysts under ambient conditions for industrial application is still a big challenge. Metal-n...Nitrogen reduction reaction (NRR) is a clean mode of energy conversion and the development of highly efficient NRR electrocatalysts under ambient conditions for industrial application is still a big challenge. Metal-nitrogen-carbon (M-N-C) has emerged as a class of single atom catalyst due to the unique geometric structure, high catalytic activity, and clear selectivity. Herein, we designed a series of dual metal single atom catalysts containing adjacent M-N-C dual active centers (MN_(4)/M'N_(4)-C) as NRR electrocatalysts to uncover the structure-activity relationship. By evaluating structural stability, catalytic activity, and selectivity using density functional theory (DFT) calculations, 5 catalysts, such as CrN_(4)/M'N_(4)-C (M’ = Cr, Mn, Fe, Cu and Zn), were determined to exhibit the best NRR catalytic performance with the limiting potential ranging from -0.64 V to -0.62 V. The CrN_(4) center acted as the main catalytic site and the adjacent M'N_(4) center could enhance the NRR catalytic activity by modulation effect based on the analysis of the electronic properties including the charge density difference, partial density of states (PDOS), and Bader charge variation. This study offers useful insights on understanding the structure-activity relationship of dual metal single atom catalysts for electrochemical NRR.展开更多
The development of redox bifunctional electrocatalysts with high performance,low cost,and long lifetimes is essential for achieving clean energy goals.This study proposed an atom capture strategy for anchoring dual si...The development of redox bifunctional electrocatalysts with high performance,low cost,and long lifetimes is essential for achieving clean energy goals.This study proposed an atom capture strategy for anchoring dual single atoms(DSAs)in a zinc-zeolitic imidazolate framework(Zn-ZIF),followed by calcination under an N_(2) atmosphere to synthesize ruthenium-platinum DSAs supported on a nitrogendoped carbon substrate(RuPt DSAs-NC).Theoretical calculations showed that the degree of Ru 5dxz-~*O 2p_x orbital hybridization was high when^(*)O was adsorbed at the Ru site,indicating enhanced covalent hybridization of metal sites and oxygen ligands,which benefited the adsorption of intermediate species.The presence of the RuPtN_6 active center optimized the absorption-desorption behavior of intermediates,improving the electrocatalytic performance of the oxygen reduction reaction(ORR)and the oxygen evolution reaction(DER),RuPt DSAs-NC exhibited a 0.87 V high half-wave potential and a 268 mV low overpotential at 10 mA cm^(-2)in an alkaline environment.Furthermore,rechargeable zinc-air batteries(ZABs)achieved a peak power density of 171 MW cm^(-2).The RuPt DSAs-NC demonstrated long-term cycling for up to 500 h with superior round-trip efficiency.This study provided an effective structural design strategy to construct DSAs active sites for enhanced electrocata lytic performance.展开更多
Recently, the exponential rise in communication system demands has motivated global academia-industry to develop efficient communication technologies to fulfill energy efficiency and Quality of Service (QoS) demands. ...Recently, the exponential rise in communication system demands has motivated global academia-industry to develop efficient communication technologies to fulfill energy efficiency and Quality of Service (QoS) demands. Wireless Sensor Network (WSN) being one of the most efficient technologies possesses immense potential to serve major communication purposes including civil, defense and industrial purposes etc. The inclusion of sensor-mobility with WSN has broadened application horizon. The effectiveness of WSNs can be characterized by its ability to perform efficient data gathering and transmission to the base station for decision process. Clustering based routing scheme has been one of the dominating techniques for WSN systems;however key issues like, cluster formation, selection of the number of clusters and cluster heads, and data transmission decision from sensors to the mobile sink have always been an open research area. In this paper, a robust and energy efficient single mobile sink based WSN data gathering protocol is proposed. Unlike existing approaches, an enhanced centralized clustering model is developed on the basis of expectation-maximization (EEM) concept. Further, it is strengthened by using an optimal cluster count estimation technique that ensures that the number of clusters in the network region doesn’t introduce unwanted energy exhaustion. Meanwhile, the relative distance between sensor node and cluster head as well as mobile sink is used to make transmission (path) decision. Results exhibit that the proposed EEM based clustering with optimal cluster selection and optimal dynamic transmission decision enables higher throughput, fast data gathering, minima delay and energy consumption, and higher展开更多
In this paper,we propose hierarchical attention dual network(DNet)for fine-grained image classification.The DNet can randomly select pairs of inputs from the dataset and compare the differences between them through hi...In this paper,we propose hierarchical attention dual network(DNet)for fine-grained image classification.The DNet can randomly select pairs of inputs from the dataset and compare the differences between them through hierarchical attention feature learning,which are used simultaneously to remove noise and retain salient features.In the loss function,it considers the losses of difference in paired images according to the intra-variance and inter-variance.In addition,we also collect the disaster scene dataset from remote sensing images and apply the proposed method to disaster scene classification,which contains complex scenes and multiple types of disasters.Compared to other methods,experimental results show that the DNet with hierarchical attention is robust to different datasets and performs better.展开更多
Single image super-resolution(SISR)is a fundamentally challenging problem because a low-resolution(LR)image can correspond to a set of high-resolution(HR)images,while most are not expected.Recently,SISR can be achieve...Single image super-resolution(SISR)is a fundamentally challenging problem because a low-resolution(LR)image can correspond to a set of high-resolution(HR)images,while most are not expected.Recently,SISR can be achieved by a deep learning-based method.By constructing a very deep super-resolution convolutional neural network(VDSRCNN),the LR images can be improved to HR images.This study mainly achieves two objectives:image super-resolution(ISR)and deblurring the image from VDSRCNN.Firstly,by analyzing ISR,we modify different training parameters to test the performance of VDSRCNN.Secondly,we add the motion blurred images to the training set to optimize the performance of VDSRCNN.Finally,we use image quality indexes to evaluate the difference between the images from classical methods and VDSRCNN.The results indicate that the VDSRCNN performs better in generating HR images from LR images using the optimized VDSRCNN in a proper method.展开更多
In the present research,enzyme encapsulated hydrogels（single gels and double network gels）and enzyme immobilized magnetic beads,which allow high-throughput screening,were fabricated and evaluated in terms of the pre...In the present research,enzyme encapsulated hydrogels（single gels and double network gels）and enzyme immobilized magnetic beads,which allow high-throughput screening,were fabricated and evaluated in terms of the preservation,precision, and repeatability of enzyme activity.The fabricated gels and magnetic beads were analyzed in a 96-well microassay plate.Trypsin was successfully encapsulated in both types of gels and immobilized to the magnetic beads.However,pepsin,either encapsulated in the gels or immobilized to the magnetic beads,could not react with its substrates.The adaptability to various enzymes （e.g.,trypsin,β-glucuronidase,and CYP1A1）in the single gels and magnetic beads was superior to that in double network gels.However,the soak out of the enzymes was observed in the single gels.The double network gels could encapsulate trypsin,whereas the fabrication of the other enzymes（e.g.β-glucuronidase,CYP1A1,and pepsin）failed because of the inactivation of the enzymes by acryl amide and ammonium peroxodisulfate,which are the components of the gel formulation. The enzyme reaction in the magnetic beads exhibited the highest efficiency among the three fabrication methods.Furthermore, the stability of the enzymes immobilized to the magnetic beads was better than that fabricated by the other methods,and the activities of trypsin andβ-glucuronidase did not decline for up to one week.In addition,in the magnetic beads,the activities of trypsin andβ-glucuronidase can be well repeated.Hence,although the adaptability of the double network gels to various enzymes is currently limited,the efficiency of the enzyme encapsulation can be improved by optimizing the formulation of acryl amide gels.展开更多
Highly transparent,durable,and flexible liquid-repellent coatings are urgently needed in the realm of transparent materials,such as car windows,optical lenses,solar panels,and flexible screen materials.However,it has ...Highly transparent,durable,and flexible liquid-repellent coatings are urgently needed in the realm of transparent materials,such as car windows,optical lenses,solar panels,and flexible screen materials.However,it has been difficult to strike a balance between the robustness and flexibility of coatings constructed by a single cross-linked network design.To overcome the conundrum,this innovative approach effectively combines two distinct cross-linked networks with unique functions,thus overcoming the challenge.Through a tightly interwoven structure comprised of added crosslinking sites,the coating achieves improved liquid repellency(WCA>100°,OSA<10°),increased durability(withstands 2,000 cycles of cotton wear),enhanced flexibility(endures 5,000 cycles of bending with a bending radius of 1 mm),and maintains high transparency(over 98%in the range of 410 nm to 760 nm).Additionally,the coating with remarkable adhesion can be applied to multiple substrates,enabling large-scale preparation and easy cycling coating,thus expanding its potential applications.The architecture of this fluoride-free dual cross-linked network not only advances liquid-repellent surfaces but also provides valuable insights for the development of eco-friendly materials in the future.展开更多
基金supported by the National Research Foundation of Korea(2022R1C1C2005786,RS-2023-00256106,RS-2023-00207831,RS-2024-00346153).
文摘Electrochemical nitrogen reduction reaction(ENRR)is emerging as a favorable option to the power-intensive Haber-Bosch process for ammonia synthesis.However,obstacles such as poor selectivity,low production rates,and competition against the hydrogen evolution reaction hinder its practical implementation.To address these,the design of highly active catalysts is critical.Single-atom catalysts(SACs)have shown great potential because of their maximized atom utilization,but their limited stability and low metal loading restrict their performances.On the other hand,dual-atom catalysts(DACs)are atomic catalysts with two metal atoms nearby and offer enhanced electrocatalytic performances by aligning with the N≡N bond to enhance N2 reduction efficiency,potentially overcoming the limitations of SAC.This review discusses recent advances in SACs and more importantly DACs for ENRR,highlighting their advantages,limitations,and the need for advanced characterization techniques to better understand catalyst behavior.The review concludes by underscoring the importance of research to optimize these catalysts for efficient and sustainable nitrogen fixation.
基金financially supported by the National Natural Science Foundation of China(Nos.21474058 and 51633003)State Key Laboratory for Modification of Chemical Fibers and Polymer Materials,Donghua University(No.LK1404)+1 种基金Tsinghua University Scientific Research Project(No.2014Z22069)State Key Laboratory of Organic-Inorganic Composites,Beijing University of Chemical Technology(No.OIC-201601006)
文摘A facile method to fabricate tough and highly stretchable polyacrylamide （PAM） nanocomposite physical hydrogel （NCP gel） was proposed. The hydrogels are dually crosslinked single network with the PAM grafted vinyl hybrid silica nanoparticles （VSNPs） as the analogous covalent crosslinking points and the reversible hydrogen bonds among the PAM chains as the physical crosslinking points. In order to further elucidate the toughening mechanism of the PAM NCP gel, especially to understand the role of the dual crosslinking points, the PAM hybrid hydrogels （H gels） and a series of poly（acrylamide-co-dimethylacrylamide） （P（AM-co-DMAA）） NCP gels were designed and fabricated. Their mechanical properties were compared with those of the PAM NCP gels. The PAM H gels are prepared by simply mixing the PAM chains with bare silica nanoparticles （SNPs）. Relative to the poor mechanical properties of the PAM H gel, the PAM NCP gel is remarkably tough and stretchable and also generates large number of micro-cracks to stop notch propagation, indicating the important role of PAM grafted VSNPs in toughening the NCP gel. In the P（AM-co-DMAA） NCP gels, the P（AM-co- DMAA） chains are grafted on VSNPs and the polydimethylacrylamide （PDMAA） only forms very weak hydrogen bonds between themselves. It is found that mechanical properties of the PAM NCP gel, such as the tensile strength and the elongation at break, are enhanced significantly, but those of the P（AM-co-DMAA） NCP gels decreased rapidly with decreasing AM content. This result reveals the role of the hydrogen bonds among the grafted polymer chains as the physical crosslinking points in toughening the NCP gel.
基金Project supported by the National Natural Science Foundation of China(Grant No.12305303)the Natural Science Foundation of Hunan Province of China(Grant Nos.2023JJ40520,2024JJ2044,and 2021JJ40444)+3 种基金the Science and Technology Innovation Program of Hunan Province,China(Grant No.2020RC3054)the Postgraduate Scientific Research Innovation Project of Hunan Province,China(Grant No.CX20240831)the Natural Science Basic Research Plan in the Shaanxi Province of China(Grant No.2023-JC-QN0015)the Doctoral Research Fund of University of South China(Grant No.200XQD033)。
文摘The single event effects(SEEs)evaluations caused by atmospheric neutrons were conducted on three different convolutional neural network(CNN)models(Yolov3,MNIST,and ResNet50)in the atmospheric neutron irradiation spectrometer(ANIS)at the China Spallation Neutron Source(CSNS).The Yolov3 and MNIST models were implemented on the XILINX28-nm system-on-chip(So C).Meanwhile,the Yolov3 and ResNet50 models were deployed on the XILINX 16-nm Fin FET Ultra Scale+MPSoC.The atmospheric neutron SEEs on the tested CNN systems were comprehensively evaluated from six aspects,including chip type,network architecture,deployment methods,inference time,datasets,and the position of the anchor boxes.The various types of SEE soft errors,SEE cross-sections,and their distribution were analyzed to explore the radiation sensitivities and rules of 28-nm and 16-nm SoC.The current research can provide the technology support of radiation-resistant design of CNN system for developing and applying high-reliability,long-lifespan domestic artificial intelligence chips.
文摘BACKGROUND Peripheral artery disease(PAD)affects millions globally,with a 5.6%prevalence in 2015 impacting 236 million adults,rising above 10%in those over 60 due to factors like diabetes and smoking.Post-revascularization,single antiplatelet therapy(SAPT)is standard,but dual antiplatelet therapy(DAPT)may improve outcomes,though duration and bleeding risks are unclear.The 2024 American College of Cardiology/American Heart Association guidelines endorse short-term DAPT,yet evidence gaps remain in comparative efficacy and safety.We hypothesized that DAPT reduces cardiovascular events and reinterventions vs SAPT without significantly elevating bleeding in PAD patients’post-lower extremity revascularization.AIM To evaluate the efficacy and safety of DAPT vs SAPT in PAD patients’post-revascularization.METHODS This systematic review and meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines,searching PubMed,EMBASE,and ScienceDirect up to July 2025.Included were randomized controlled trials(RCTs)and cohort studies from various global settings(e.g.,hospitals,tertiary care)comparing DAPT(aspirin plus P2Y12 inhibitor for>1 month)to SAPT in symptomatic PAD patients undergoing endovascular or surgical revascularization(n up to 28244 participants selected via eligibility criteria).Data were pooled using random-effects models for risk ratio(RR)with 95%CI;heterogeneity was assessed via the I²statistic.Quality appraisal used Risk of Bias in Non-randomized Studies of Interventions for cohorts and Risk of Bias 2.0 for RCTs;certainty was evaluated via Grading of Recommendations Assessment,Development and Evaluation(GRADE).RESULTS Twelve studies(3 RCTs,9 cohorts,conducted 2010–2025 with follow-ups of 6 months to 5 years)were included.DAPT showed no significant difference but a trend toward reduced all-cause mortality(RR:0.52,95%CI:0.27–1.01,P=0.05,DAPT of 298/9545 events vs SAPT of 165/566 events)or stroke(RR:0.72,95%CI:0.30–1.72,P=0.46,DAPT of 16/3729 events vs SAPT of 41/7673 events)vs SAPT.DAPT significantly reduced cardiac mortality(RR:0.46,95%CI:0.27–0.80,P=0.006,DAPT of 78/2903 events vs SAPT of 171/1465 events,risk difference:-5.4%),myocardial infarction(RR:0.82,95%CI:0.71–0.94,P=0.004,DAPT of 233/7704 events vs SAPT of 262/9130 events,risk difference:-1.8%),and major reintervention(RR:0.58,95%CI:0.35–0.98,P=0.04,DAPT of 803/205 events vs SAPT of 1197/4 events,risk difference:-42%).Bleeding showed no difference(RR:1.12,95%CI:0.42–3.03,P=0.82,DAPT of 195/2775 events vs SAPT of 202/8234 events).Heterogeneity was high(I^(2)=59%–97%).Quality revealed moderate to serious bias in cohorts and some concerns in RCTs;GRADE certainty moderate for cardiac mortality,myocardial infarction,reintervention,low for others due to inconsistency and imprecision.CONCLUSION DAPT reduces cardiac mortality,myocardial infarction,and major reintervention risks compared to SAPT in PAD post-revascularization without apparent bleeding increase,though limited by heterogeneity and low certainty for some outcomes.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 10604008 and 10435020） and the Beijing Education Committee （Grant No XK100270454）.
文摘In this paper a scheme for quantum secure direct communication （QSDC） network is proposed with a sequence of polarized single photons. The single photons are prepared originally in the same state （0） by the servers on the network, which will reduce the difficulty for the legitimate users to check eavesdropping largely. The users code the information on the single photons with two unitary operations which do not change their measuring bases. Some decoy photons, which are produced by operating the sample photons with a Hadamard, are used for preventing a potentially dishonest server from eavesdropping the quantum lines freely. This scheme is an economical one as it is the easiest way for QSDC network communication securely.
基金supported by the Hainan Province Science and Technology Special Fund(ZDYF2021SHFZ232,ZDYF2023GXJS022)the Hainan Province Postdoctoral Science Foundation(300333)the National Natural Science Foundation of China(21203008,21975025,12274025,22372008)。
文摘Sulfide-based all-solid-state lithium batteries suffer from electrochemo-mechanical damage to Ni-rich oxide-based cathode active materials(CAMs),primarily caused by severe volume changes,results in significant stress and strain,causes micro-cracks and interfacial contact loss at potentials>4.3 V(vs.Li/Li^(+)).Quantifying micro-cracks and voids in CAMs can reveal the degradation mechanisms of Ni-rich oxidebased cathodes during electrochemical cycling.Nonetheless,the origin of electrochemical-mechanical damage remains unclear.Herein,We have developed a multifunctional PEG-based soft buffer layer(SBL)on the surface of carbon black(CB).This layer functions as a percolation network in the single crystal LiNi_(0.83)Co_(0.07)Mn_(0.1)O_(2)and Li_(6)PS_(5)Cl composite cathode layer,ensuring superior ionic conductivity,reducing void formation and particle cracking,and promoting uniform utilization of the cathode active material in all-solid-state lithium batteries(ASSLBs).High-angle annular dark-field STEM combined with nanoscale X-ray holo-tomography and plasma-focused ion beam scanning electron microscopy confirmed that the PEG-based SBL mitigated strain induced by reaction heterogeneity in the cathode.This strain produces lattice stretches,distortions,and curved transition metal oxide layers near the surface,contributing to structural degradation at elevated voltages.Consequently,ASSLBs with a LiNi_(0.83)Co_(0.07)Mn_(0.1)O_(2)cathode containing LCCB-10(CB/PEG mass ratio:100/10)demonstrate a high areal capacity(2.53 mAh g^(-1)/0.32 mA g^(-1))and remarkable rate capability(0.58 mAh g^(-1)at 1.4 mA g^(-1)),with88%capacity retention over 1000 cycles.
基金Major Unified Construction Project of Petro China(2019-40210-000020-02)。
文摘Since the oil production of single well in water flooding reservoir varies greatly and is hard to predict, an oil production prediction method of single well based on temporal convolutional network(TCN) is proposed and verified. This method is started from data processing, the correspondence between water injectors and oil producers is determined according to the influence radius of the water injectors, the influence degree of a water injector on an oil producer in the month concerned is added as a model feature, and a Random Forest(RF) model is built to fill the dynamic data of water flooding. The single well history is divided into 4 stages according to its water cut, that is, low water cut, middle water cut, high water cut and extra-high water cut stages. In each stage, a TCN based prediction model is established, hyperparameters of the model are optimized by the Sparrow Search Algorithm(SSA). Finally, the models of the 4 stages are integrated into one whole-life model of the well for production prediction. The application of this method in Daqing Oilfield, NE China shows that:(1) Compared with conventional data processing methods, the data obtained by this processing method are more close to the actual production, and the data set obtained is more authentic and complete.(2) The TCN model has higher prediction accuracy than other 11 models such as Long Short Term Memory(LSTM).(3) Compared with the conventional full-life-cycle models, the model of integrated stages can significantly reduce the error of production prediction.
基金partially supported by NIH grants (2U19AI090023,5P30AI50409,and R01GM122083)
文摘Study of gene expression has been arguably the most active research field in functional genomics.Over the last two decades,various high-throughput technologies,from gene expression microarray to RNA-seq,have been widely applied to the wholegenome profiling of gene expression.The commonality of these experiments is that they measure the gene expression levels of"bulk"sample,which pools a large number(often in the scale of millions)of cells,and thus the measurements reflect the average expression
基金supported by the Key Research and Development Program of Jiangsu Province under Grant BE2022059-3,CTBC Bank through the Industry-Academia Cooperation Project,as well as by the Ministry of Science and Technology of Taiwan through Grants MOST-108-2218-E-002-055,MOST-109-2223-E-009-002-MY3,MOST-109-2218-E-009-025,and MOST431109-2218-E-002-015.
文摘Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial expressions.Numerous deep neural networks(DNNs)with convolutional structures have been proposed.However,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small datasets.Still,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective features.To address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-XgBoost)is introduced for ME Recognition.The proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical Flow TV-L1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective features.The outputs are then fused,concatenated,and classified using the XgBoost algorithm.This comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of XgBoost.The proposed method is evaluated on three publicly available ME databases named Chinese Academy of Sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent models.The accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the F1-score are 75.47%,68.91%,and 63.84%,respectively.The proposed method has the advantage of operational efficiency and less computational time.
基金supported by the financial support from NSFC (Grant 11472113 and Grant 11272130)
文摘The interactions between the moving dislocation within matrix channel and the interfacial misfit dislocation networks on the two-phase interfaces in Ni-based single crystal superalloys are studied carefully via atomic modeling, with special focus on the factors influ- encing the critical bowing stress of moving dislocations in the matrix channel. The results show that the moving matrix dislocation type and its position with respect to the interfacial misfit dislocation segments have considerable influences on the interactions. If the moving matrix dislocation is pure screw, it reacts with the interracial misfit dislocation segments toward dislocation linear energy reduction, which decreases the critical bowing stress of screw dislocation due to dislocation linear energy release during the dislocation reactions. If the moving matrix dislocation is of 60^-mixed type, it is obstructed by the interaction between the mixed matrix dislocations and the misfit interfacial dislocation segments. As a result, the critical bowing stress increases significantly because extra interactive energy needs to be overcome. These two different effects on the critical bowing stress become in- creasingly significant when the moving matrix dislocation is very close to the interracial misfit dislocation segments. In addition, the matrix channel width also has a significant influence on the critical bowing stress, i.e. the narrower the matrix channel is, the higher the critical bowing stress is. The classical Orowan formula is modified to predict these effects on the critical bowing stress of moving matrix dislocation, which is in good agreement with the computational results.
基金supported by the National Natural Science Foundation of China (No.61561030)the Gansu Provincial F inance Department (No.214138)。
文摘In this letter, we present a novel integrated feature that incorporates traditional parameters, and adopt a parallel cascading fashion network Haze Net for enhancing image quality. Our unified feature is a complete integration, and its role is to directly describe the effects of haze. In Haze Net, we design two separate structures including backbone and auxiliary networks to extract feature map. Backbone network is responsible for extracting high-level feature map, and low-level feature learned by the auxiliary network can be interpreted as fine-grained feature. After cascading two features with different accuracy, final performance can be effectively improved. Extensive experimental results on both synthetic datasets and real-world images prove the superiority of the proposed method, and demonstrate more favorable performance compared with the existing state-of-art methods.
基金Project supported by the Science and Engineering Research Board(SERB),Department of Science and Technology(DST),India(No.SRG/2019/001581)。
文摘With the explosive growth of computational resources and data generation,deep machine learning has been successfully employed in various applications.One important and emerging scientific application of deep learning involves solving differential equations.Here,physics-informed neural networks(PINNs)are developed to solve the differential equations associated with a specific scientific problem.As such,algorithms for solving the differential equations by embedding their initial and boundary conditions in the cost function of the artificial neural networks using algorithmic differentiation must also be developed.In this study,various PINNs are adopted to estimate the stresses in the tablets and the interphase of a single lap joint.The proposed model is represented by two fourth-order non-homogeneous coupled partial differential equations,with the axial stresses in the upper and lower tablets adopted as the dependent variables.The axial stresses are a function of the tablet length,which presents the independent variable.Therefore,the axial stresses in the tablets are estimated by solving the coupled partial differential equations when subjected to the boundary conditions,whereas the remaining stress components are expressed in terms of axial stresses.The results obtained using the developed methodology are validated using the results obtained via MAPLE software.
基金supported in part by the National Natural Science Foundation of China under Grant 51977099。
文摘Dual three-phase permanent-magnet synchronous machines(DTP-PMSM)connected with a single neutral point provide a loop for zero-sequence current(ZSC).This paper proposes a novel space vector pulse width modulation(SVPWM)strategy to suppress the ZSC.Five vectors are selected as basic voltage vectors in one switching period.The fundamental and harmonic planes and the zero-sequence plane are taken into consideration to synthesis the reference voltage vector.To suppress the ZSC,a non-zero zero-sequence voltage(ZSV)is generated to compensate the third harmonic back-EMF.Rather than triangular carrier modulation,the sawtooth carrier modulation strategy is used to generate asymmetric PWM signals.The modulation range is investigated to explore the variation of modulation range caused by considering the zero-sequence plane.With the proposed method,the ZSC can be considerably reduced.The simulated and experimental results are presented to validate the effectiveness of the proposed modulation strategy.
基金supported by the open project of State Key Laboratory of Advanced Welding and Joining,Harbin Institute of Technology (No. AWJ-19M07)the National Natural Science Foundation of China (No. U2067216)。
文摘Nitrogen reduction reaction (NRR) is a clean mode of energy conversion and the development of highly efficient NRR electrocatalysts under ambient conditions for industrial application is still a big challenge. Metal-nitrogen-carbon (M-N-C) has emerged as a class of single atom catalyst due to the unique geometric structure, high catalytic activity, and clear selectivity. Herein, we designed a series of dual metal single atom catalysts containing adjacent M-N-C dual active centers (MN_(4)/M'N_(4)-C) as NRR electrocatalysts to uncover the structure-activity relationship. By evaluating structural stability, catalytic activity, and selectivity using density functional theory (DFT) calculations, 5 catalysts, such as CrN_(4)/M'N_(4)-C (M’ = Cr, Mn, Fe, Cu and Zn), were determined to exhibit the best NRR catalytic performance with the limiting potential ranging from -0.64 V to -0.62 V. The CrN_(4) center acted as the main catalytic site and the adjacent M'N_(4) center could enhance the NRR catalytic activity by modulation effect based on the analysis of the electronic properties including the charge density difference, partial density of states (PDOS), and Bader charge variation. This study offers useful insights on understanding the structure-activity relationship of dual metal single atom catalysts for electrochemical NRR.
基金supported by the National Natural Science Foundation of China (No.22309023,22179014)the project of Natural Science Foundation of Chongqing (Grant No.CSTB2022NSCQMSX0270)+3 种基金the China Postdoctoral Science Foundation (No.2022M720593)the youth project of science and technology research program of Chongqing Municipal Education Commission of China (Grant No.KJQN202201127)the Scientific Research Foundation of Chongqing University of Technology (2022ZDZ011,2022PYZ026)the special funding for research projects of Chongqing Human Resources and Social Security Bureau (Grant No.2022CQBSHTB1023)。
文摘The development of redox bifunctional electrocatalysts with high performance,low cost,and long lifetimes is essential for achieving clean energy goals.This study proposed an atom capture strategy for anchoring dual single atoms(DSAs)in a zinc-zeolitic imidazolate framework(Zn-ZIF),followed by calcination under an N_(2) atmosphere to synthesize ruthenium-platinum DSAs supported on a nitrogendoped carbon substrate(RuPt DSAs-NC).Theoretical calculations showed that the degree of Ru 5dxz-~*O 2p_x orbital hybridization was high when^(*)O was adsorbed at the Ru site,indicating enhanced covalent hybridization of metal sites and oxygen ligands,which benefited the adsorption of intermediate species.The presence of the RuPtN_6 active center optimized the absorption-desorption behavior of intermediates,improving the electrocatalytic performance of the oxygen reduction reaction(ORR)and the oxygen evolution reaction(DER),RuPt DSAs-NC exhibited a 0.87 V high half-wave potential and a 268 mV low overpotential at 10 mA cm^(-2)in an alkaline environment.Furthermore,rechargeable zinc-air batteries(ZABs)achieved a peak power density of 171 MW cm^(-2).The RuPt DSAs-NC demonstrated long-term cycling for up to 500 h with superior round-trip efficiency.This study provided an effective structural design strategy to construct DSAs active sites for enhanced electrocata lytic performance.
文摘Recently, the exponential rise in communication system demands has motivated global academia-industry to develop efficient communication technologies to fulfill energy efficiency and Quality of Service (QoS) demands. Wireless Sensor Network (WSN) being one of the most efficient technologies possesses immense potential to serve major communication purposes including civil, defense and industrial purposes etc. The inclusion of sensor-mobility with WSN has broadened application horizon. The effectiveness of WSNs can be characterized by its ability to perform efficient data gathering and transmission to the base station for decision process. Clustering based routing scheme has been one of the dominating techniques for WSN systems;however key issues like, cluster formation, selection of the number of clusters and cluster heads, and data transmission decision from sensors to the mobile sink have always been an open research area. In this paper, a robust and energy efficient single mobile sink based WSN data gathering protocol is proposed. Unlike existing approaches, an enhanced centralized clustering model is developed on the basis of expectation-maximization (EEM) concept. Further, it is strengthened by using an optimal cluster count estimation technique that ensures that the number of clusters in the network region doesn’t introduce unwanted energy exhaustion. Meanwhile, the relative distance between sensor node and cluster head as well as mobile sink is used to make transmission (path) decision. Results exhibit that the proposed EEM based clustering with optimal cluster selection and optimal dynamic transmission decision enables higher throughput, fast data gathering, minima delay and energy consumption, and higher
基金Supported by the National Natural Science Foundation of China(61601176)。
文摘In this paper,we propose hierarchical attention dual network(DNet)for fine-grained image classification.The DNet can randomly select pairs of inputs from the dataset and compare the differences between them through hierarchical attention feature learning,which are used simultaneously to remove noise and retain salient features.In the loss function,it considers the losses of difference in paired images according to the intra-variance and inter-variance.In addition,we also collect the disaster scene dataset from remote sensing images and apply the proposed method to disaster scene classification,which contains complex scenes and multiple types of disasters.Compared to other methods,experimental results show that the DNet with hierarchical attention is robust to different datasets and performs better.
文摘Single image super-resolution(SISR)is a fundamentally challenging problem because a low-resolution(LR)image can correspond to a set of high-resolution(HR)images,while most are not expected.Recently,SISR can be achieved by a deep learning-based method.By constructing a very deep super-resolution convolutional neural network(VDSRCNN),the LR images can be improved to HR images.This study mainly achieves two objectives:image super-resolution(ISR)and deblurring the image from VDSRCNN.Firstly,by analyzing ISR,we modify different training parameters to test the performance of VDSRCNN.Secondly,we add the motion blurred images to the training set to optimize the performance of VDSRCNN.Finally,we use image quality indexes to evaluate the difference between the images from classical methods and VDSRCNN.The results indicate that the VDSRCNN performs better in generating HR images from LR images using the optimized VDSRCNN in a proper method.
基金The Global COE Program from the Ministry of Education,Science,Sports,and Culture of Japan.
文摘In the present research,enzyme encapsulated hydrogels（single gels and double network gels）and enzyme immobilized magnetic beads,which allow high-throughput screening,were fabricated and evaluated in terms of the preservation,precision, and repeatability of enzyme activity.The fabricated gels and magnetic beads were analyzed in a 96-well microassay plate.Trypsin was successfully encapsulated in both types of gels and immobilized to the magnetic beads.However,pepsin,either encapsulated in the gels or immobilized to the magnetic beads,could not react with its substrates.The adaptability to various enzymes （e.g.,trypsin,β-glucuronidase,and CYP1A1）in the single gels and magnetic beads was superior to that in double network gels.However,the soak out of the enzymes was observed in the single gels.The double network gels could encapsulate trypsin,whereas the fabrication of the other enzymes（e.g.β-glucuronidase,CYP1A1,and pepsin）failed because of the inactivation of the enzymes by acryl amide and ammonium peroxodisulfate,which are the components of the gel formulation. The enzyme reaction in the magnetic beads exhibited the highest efficiency among the three fabrication methods.Furthermore, the stability of the enzymes immobilized to the magnetic beads was better than that fabricated by the other methods,and the activities of trypsin andβ-glucuronidase did not decline for up to one week.In addition,in the magnetic beads,the activities of trypsin andβ-glucuronidase can be well repeated.Hence,although the adaptability of the double network gels to various enzymes is currently limited,the efficiency of the enzyme encapsulation can be improved by optimizing the formulation of acryl amide gels.
基金financially supported by the National Natu-ral Science Foundation of China(Nos.22375047,22378068,and 22075046)the Natural Science Foundation of Fujian Province(No.2022J01568)+2 种基金the National Key Research and Development Program of China(Nos.2022YFB3804905 and 2022YFB3804900)China Postdoctoral Science Foundation(No.2023M743437)start-up funding from Wenzhou Institute,University of Chinese Academy of Sciences(No.WIUCASQD2019002).
文摘Highly transparent,durable,and flexible liquid-repellent coatings are urgently needed in the realm of transparent materials,such as car windows,optical lenses,solar panels,and flexible screen materials.However,it has been difficult to strike a balance between the robustness and flexibility of coatings constructed by a single cross-linked network design.To overcome the conundrum,this innovative approach effectively combines two distinct cross-linked networks with unique functions,thus overcoming the challenge.Through a tightly interwoven structure comprised of added crosslinking sites,the coating achieves improved liquid repellency(WCA>100°,OSA<10°),increased durability(withstands 2,000 cycles of cotton wear),enhanced flexibility(endures 5,000 cycles of bending with a bending radius of 1 mm),and maintains high transparency(over 98%in the range of 410 nm to 760 nm).Additionally,the coating with remarkable adhesion can be applied to multiple substrates,enabling large-scale preparation and easy cycling coating,thus expanding its potential applications.The architecture of this fluoride-free dual cross-linked network not only advances liquid-repellent surfaces but also provides valuable insights for the development of eco-friendly materials in the future.
