Pest detection techniques are helpful in reducing the frequency and scale of pest outbreaks;however,their application in the actual agricultural production process is still challenging owing to the problems of intersp...Pest detection techniques are helpful in reducing the frequency and scale of pest outbreaks;however,their application in the actual agricultural production process is still challenging owing to the problems of interspecies similarity,multi-scale,and background complexity of pests.To address these problems,this study proposes an FD-YOLO pest target detection model.The FD-YOLO model uses a Fully Connected Feature Pyramid Network(FC-FPN)instead of a PANet in the neck,which can adaptively fuse multi-scale information so that the model can retain small-scale target features in the deep layer,enhance large-scale target features in the shallow layer,and enhance the multiplexing of effective features.A dual self-attention module(DSA)is then embedded in the C3 module of the neck,which captures the dependencies between the information in both spatial and channel dimensions,effectively enhancing global features.We selected 16 types of pests that widely damage field crops in the IP102 pest dataset,which were used as our dataset after data supplementation and enhancement.The experimental results showed that FD-YOLO’s mAP@0.5 improved by 6.8%compared to YOLOv5,reaching 82.6%and 19.1%–5%better than other state-of-the-art models.This method provides an effective new approach for detecting similar or multiscale pests in field crops.展开更多
The root system actively reacts to mechanical stimuli in its environment,transmitting mechanical signals to optimize the utilization of environmental resources.While the mechanical impedance created by the growth medi...The root system actively reacts to mechanical stimuli in its environment,transmitting mechanical signals to optimize the utilization of environmental resources.While the mechanical impedance created by the growth medium serves as the primary source of stimulation for the roots,extensive research has focused on the roots'response to static mechanical stimulation.However,the impact of dynamic mechanical stimulation on root phenotype remains underexplored.In this study,we utilized a low acyl gellan gum/polyacrylamide(GG/PAM)double network elastic hydrogel as the growth medium for rapeseed.We constructed a mechanical device to investigate the effects of reciprocating extrusion stimulation on the growth of the rapeseed root system.After three weeks of mechanical stimulation,the root system exhibited a significant increase in lateral roots.This branching enhanced the roots'anchoring and penetration into the hydrogel,thereby improving the root system's adaptability to its environment.Our findings offer valuable data and insights into the effects of reciprocating mechanical stimulation on root growth,providing a new way for engineering root phenotype.展开更多
With the advancement of Vehicle-to-Everything(V2X)technology,efficient resource allocation in dynamic vehicular networks has become a critical challenge for achieving optimal performance.Existing methods suffer from h...With the advancement of Vehicle-to-Everything(V2X)technology,efficient resource allocation in dynamic vehicular networks has become a critical challenge for achieving optimal performance.Existing methods suffer from high computational complexity and decision latency under high-density traffic and heterogeneous network conditions.To address these challenges,this study presents an innovative framework that combines Graph Neural Networks(GNNs)with a Double Deep Q-Network(DDQN),utilizing dynamic graph structures and reinforcement learning.An adaptive neighbor sampling mechanism is introduced to dynamically select the most relevant neighbors based on interference levels and network topology,thereby improving decision accuracy and efficiency.Meanwhile,the framework models communication links as nodes and interference relationships as edges,effectively capturing the direct impact of interference on resource allocation while reducing computational complexity and preserving critical interaction information.Employing an aggregation mechanism based on the Graph Attention Network(GAT),it dynamically adjusts the neighbor sampling scope and performs attention-weighted aggregation based on node importance,ensuring more efficient and adaptive resource management.This design ensures reliable Vehicle-to-Vehicle(V2V)communication while maintaining high Vehicle-to-Infrastructure(V2I)throughput.The framework retains the global feature learning capabilities of GNNs and supports distributed network deployment,allowing vehicles to extract low-dimensional graph embeddings from local observations for real-time resource decisions.Experimental results demonstrate that the proposed method significantly reduces computational overhead,mitigates latency,and improves resource utilization efficiency in vehicular networks under complex traffic scenarios.This research not only provides a novel solution to resource allocation challenges in V2X networks but also advances the application of DDQN in intelligent transportation systems,offering substantial theoretical significance and practical value.展开更多
The generation of high-quality,realistic face generation has emerged as a key field of research in computer vision.This paper proposes a robust approach that combines a Super-Resolution Generative Adversarial Network(...The generation of high-quality,realistic face generation has emerged as a key field of research in computer vision.This paper proposes a robust approach that combines a Super-Resolution Generative Adversarial Network(SRGAN)with a Pyramid Attention Module(PAM)to enhance the quality of deep face generation.The SRGAN framework is designed to improve the resolution of generated images,addressing common challenges such as blurriness and a lack of intricate details.The Pyramid Attention Module further complements the process by focusing on multi-scale feature extraction,enabling the network to capture finer details and complex facial features more effectively.The proposed method was trained and evaluated over 100 epochs on the CelebA dataset,demonstrating consistent improvements in image quality and a marked decrease in generator and discriminator losses,reflecting the model’s capacity to learn and synthesize high-quality images effectively,given adequate computational resources.Experimental outcome demonstrates that the SRGAN model with PAM module has outperformed,yielding an aggregate discriminator loss of 0.055 for real,0.043 for fake,and a generator loss of 10.58 after training for 100 epochs.The model has yielded an structural similarity index measure of 0.923,that has outperformed the other models that are considered in the current study for analysis.展开更多
Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum sca...Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.展开更多
Peristaltic transport of non-Newtonian nanofluids with double diffusion is essential to biological engineering,microfluidics,and manufacturing processes.The authors tackle the key problem of Sisko nanofluids under dou...Peristaltic transport of non-Newtonian nanofluids with double diffusion is essential to biological engineering,microfluidics,and manufacturing processes.The authors tackle the key problem of Sisko nanofluids under double diffusion convection with thermal radiations and electroosmotic effects.Thestudy proposes a solution approach by using Morlet-Wavelet Neural Networks that can effectively solve this complex problem by their superior ability in the capture of nonlinear dynamics.These convergence analyses were calculated across fifty independent runs.Theil’s Inequality Coefficient and theMean Squared Error values range from 10^(-7) to 10^(-5) and 10^(-7) to 10^(-10),respectively.These values showed the proposed method is scientifically reliable and fast converging.Studies reveal that the intensity of the magnetic field causes a reduction in the flow velocity profile in the center of the channel.It is also evaluated that thermal radiations enhance the energy of the system,which promotes thermally induced diffusion and particle flow.The physical applications of this work pertain to improving fluid flow and heat transfer in engineering structures like converters or cooling devices or magnetic fluids in electronics,energy,and biomedical applications,where optimal control of fluid behavior is of paramount importance.展开更多
The purpose is to study modules of double crossproducts D (X, A) of Skew-Hopf pairs ( X, A). A sufficient and necessary condition for M to be D ( X, A)-mod is shown. Relations between D ( X, A)-mod and quantam Yang-Ba...The purpose is to study modules of double crossproducts D (X, A) of Skew-Hopf pairs ( X, A). A sufficient and necessary condition for M to be D ( X, A)-mod is shown. Relations between D ( X, A)-mod and quantam Yang-Baxter A-mod or X-mod are revealed.展开更多
Developing a low-cost and well-recyclable adsorbent with high adsorption capacity is greatly desirable in dye wastewater treatment. Here, we demonstrate a kind of novel tough and reusable hydrogel beads with quite hig...Developing a low-cost and well-recyclable adsorbent with high adsorption capacity is greatly desirable in dye wastewater treatment. Here, we demonstrate a kind of novel tough and reusable hydrogel beads with quite high capacity of dye adsorption via incorporating mussel-bioinspired poly（L-DOPA） （PDOPA） into alginate/poly（acrylamide） double network （DN） hydrogels. The synthesized PDOPA nanoaggregates were introduced into the DN hydrogels by simple one-pot mixing with the monomers prior to polymerization. The fabricated hydrogel beads exhibited high mechanical strength and good elastic recovery due to the interpenetrating Ca2＋-alginate and poly（acrylamide） networks. It was shown that the beads exhibited relatively high dye adsorption capacity compared to other adsorbents reported in literature, and the introduction of PDOPA with an appropriate amount raised the adsorption capacity. It is believed that the addition of PDOPA and the matrix of double network architecture contributed synergistically to the high adsorption capacity of hydrogel beads. Moreover, the desorption of dyes could be easily realized via rinsing in acidic water and ethanol solution. The hydrogel beads remained the high adsorption capacity even after 5 times of adsorption and desorption cycles. This tough and stable hydrogel with high adsorption capacity may have potential in treatment of dye wastewater released by textile dyeing industry.展开更多
Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into t...Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into the conventional tough DN hydro-gel system.We synthesize the PEG-PDAC/P(AAm-co-AAc)DN hydrogels,of which the first network is a well-defined PEG(polyethylene glycol)network loaded with PDAC(poly(acryloyloxyethyltrimethyl ammonium chloride))strands,while the second network is formed by copolymerizing AAm(acrylamide)with AAc(acrylic acid)and cross-linker MBAA(N;N′-methylenebisacrylamide).The PEG-PDAC/P(AAm-co-AAc)DN gels exhibits high mechanical strength.The fracture stress and toughness of the DN gels reach up to 0.9 MPa and 3.8 MJ/m^3,respectively.Compared with the conventional double network hydrogels with neutral polymers as the soft and ductile second network,the PEG-PDAC/P(AAm-co-AAc)DN hydrogels use P(AAm-co-AAc),a weak polyelectrolyte,as the second network.The AAc units serve as the coordination points with Fe^3+ions and physically crosslink the second network,which realizes the shape memory property activated by the reducing ability of ascorbic acid.Our results indicate that the high mechanical strength and shape memory properties,probably the two most important characters related to the potential application of the hydrogels,can be introduced simultaneously into the DN hydrogels if the functional monomer has been integrated into the network of DN hydrogels smartly.展开更多
Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine.In this paper,a newly double network(DN)hydrogel was prepared based on...Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine.In this paper,a newly double network(DN)hydrogel was prepared based on zwitterionic material sulfobetaine methacrylate(SBMA)and natural polysaccharide,sodium alginate(SA).The PSBMA network is covalently crosslinked while the SA network is ionically crosslinked by Ca^(2+).The hybrid crosslinked double network structure endows the DN hydrogel with excellent mechanical properties(E=0.19±0.01 MPa,σ=0.73±0.03 MPa),fast self-recovery ability as well as excellent fatigue resistance.Moreover,the results show that the PSBMA/SA-Ca^(2+)DN hydrogel is biocompatible and resists the absorption of non-specific proteins and adhesion of microorganisms,such as cells and algae,exhibiting outstanding antifouling properties.These unique characteristics of PSBMA/SA-Ca^(2+)DN hydrogel make it a promising candidate for biomedical application,such as artificial connective tissues,implantable devices,and underwater equipment.展开更多
Recently, the phase compensation technique has allowed the ultrasound to propagate through the skull and focus into the brain. However, the temperature evolution during treatment is hard to control to achieve effectiv...Recently, the phase compensation technique has allowed the ultrasound to propagate through the skull and focus into the brain. However, the temperature evolution during treatment is hard to control to achieve effective treatment and avoid over-high temperature. Proposed in this paper is a method to modulate the temperature distribution in the focal region. It superimposes two signals which focus on two preset different targets with a certain distance. Then the temperature distribution is modulated by changing triggering time delay and amplitudes of the two signals. The simulation model is established based on an 82-element transducer and computed tomography （CT） data of a volunteer＇s head. A finite- difference time-domain （FDTD） method is used to calculate the temperature distributions. The results show that when the distances between the two targets respectively are 7.5-12.5 mm on the acoustic axis and 2.0-3.0 mm in the direction perpendicular to the acoustic axis, a focal region with a uniform temperature distribution （64-65 ℃） can be created. Moreover, the volume of the focal region formed by one irradiation can be adjusted （26.8-266.7 mm3） along with the uniform temperature distribution. This method may ensure the safety and efficacy of HIFU brain tumor therapy.展开更多
Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operat...Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operation of high-speed trains.For this reason,a rail internal defect detection method based on an enhanced network structure and module design using ultrasonic images is proposed in this paper.First,a data augmentation method was used to extend the existing image dataset to obtain appropriate image samples.Second,an enhanced network structure was designed to make full use of the high-level and low-level feature information in the image,which improved the accuracy of defect detection.Subsequently,to optimize the detection performance of the proposed model,the Mish activation function was used to design the block module of the feature extraction network.Finally,the pro-posed rail defect detection model was trained.The experimental results showed that the precision rate and F1score of the proposed method were as high as 98%,while the model’s recall rate reached 99%.Specifically,good detec-tion results were achieved for different types of defects,which provides a reference for the engineering application of internal defect detection.Experimental results verified the effectiveness of the proposed method.展开更多
A highly sensitive double artificial neural network （DANN） analysis with flow-injection chemiluminescence （FI-CL） has been developed to simultaneously determine the trace amounts of the gold and platinum in simula...A highly sensitive double artificial neural network （DANN） analysis with flow-injection chemiluminescence （FI-CL） has been developed to simultaneously determine the trace amounts of the gold and platinum in simulated mixed samples, without the boring process.展开更多
High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading del...High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.展开更多
Conductive hydrogels have shown great prospects as wearable flexible sensors.Nevertheless,it is still a challenge to construct hydrogel-based sensor with great mechanical strength and high strain sensitivity.Herein,an...Conductive hydrogels have shown great prospects as wearable flexible sensors.Nevertheless,it is still a challenge to construct hydrogel-based sensor with great mechanical strength and high strain sensitivity.Herein,an ion-conducting hydrogel was fabricated by introducing gelatin-dialdehydeβ-cyclodextrin(Gel-DACD)into polyvinyl alcohol-borax(PVA-borax)hydrogel network.Natural Gel-DACD network acted as mechanical deformation force through non-covalent cross-linking to endow the polyvinyl alcoholborax/gelatin-dialdehydeβ-cyclodextrin hydrogel(PGBCDH)with excellent mechanical stress(1.35 MPa),stretchability(400%),toughness(1.84 MJ/m3)and great fatigue resistance(200%strain for 100 cycles).Surprisingly,PGBCDH displayed good conductivity of 0.31 S/m after adding DACD to hydrogel network.As sensor,it showed rapid response(168 ms),high strain sensitivity(gage factor(GF)=8.57 in the strain range of 200%-250%)and reliable sensing stability(100%strain for 200 cycles).Importantly,PGBCDHbased sensor can accurately monitor complex body movements(knee,elbow,wrist and finger joints)and large-scale subtle movements(speech,swallow,breath and facial expressions).Thus,PGBCDH shows great potential for human monitoring with high precision.展开更多
A shape-memory double network hydrogel consists of two polymer networks:a chemically crosslinked primary network that is responsible for the permanent shape and a physically crosslinked secondary network that is used ...A shape-memory double network hydrogel consists of two polymer networks:a chemically crosslinked primary network that is responsible for the permanent shape and a physically crosslinked secondary network that is used to fix the temporary shapes.The formation/melting transition of the secondary network serves as an effective mechanism for the double network hydrogel’s shape-memory effect.When the crosslinks in the secondary network are dissociated by applying an external stimulus,only the primary network is left to support the load.When the secondary network is re-formed by removing the stimulus,both the primary and secondary networks support the load.In the past,models have been developed for the constitutive behaviors of double network hydrogels,but the model of shape-memory double network hydrogels is still lacking.This work aims to build a constitutive model for the polyacrylamide-gelatin double network shape-memory hydrogel developed in our previous work.The model is first calibrated by experimental data of the double network shape-memory hydrogel under uniaxial loading and then employed to predict the shape-fixing performance of the hydrogel.The model is also implemented into a three-dimension finite element code and utilized to simulate the shape-memory behavior of the double network hydrogel with inhomogeneous deformations related to applications.展开更多
A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores...A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.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
To overcome hole-injection limitation of p^＋-n emitter junction in 4H-SiC light triggered thyristor, a novel high- voltage 4H-SiC light triggered thyristor with double-deck thin n-base structure is proposed and demon...To overcome hole-injection limitation of p^＋-n emitter junction in 4H-SiC light triggered thyristor, a novel high- voltage 4H-SiC light triggered thyristor with double-deck thin n-base structure is proposed and demonstrated by two- dimensional numerical simulations. In this new structure, the conventional thin n-base is split to double-deck. The hole- injection of p^＋-n emitter junction is modulated by modulating the doping concentration and thickness of upper-deck thin n- base. With double-deck thin n-base, the current gain coefficient of the top pnp transistor in 4H-SiC light triggered thyristor is enhanced. As a result, the triggering light intensity and the turn-on delay time of 4H-SiC light triggered thyristor are both reduced. The simulation results show that the proposed 10-kV 4H-SiC light triggered thyristor is able to be triggered on by 500-mW/cm^2 ultraviolet light pulse. Meanwhile, the turn-on delay time of the proposed thyristor is reduced to 337 ns.展开更多
基金funded by Liaoning Provincial Department of Education Project,Award number JYTMS20230418.
文摘Pest detection techniques are helpful in reducing the frequency and scale of pest outbreaks;however,their application in the actual agricultural production process is still challenging owing to the problems of interspecies similarity,multi-scale,and background complexity of pests.To address these problems,this study proposes an FD-YOLO pest target detection model.The FD-YOLO model uses a Fully Connected Feature Pyramid Network(FC-FPN)instead of a PANet in the neck,which can adaptively fuse multi-scale information so that the model can retain small-scale target features in the deep layer,enhance large-scale target features in the shallow layer,and enhance the multiplexing of effective features.A dual self-attention module(DSA)is then embedded in the C3 module of the neck,which captures the dependencies between the information in both spatial and channel dimensions,effectively enhancing global features.We selected 16 types of pests that widely damage field crops in the IP102 pest dataset,which were used as our dataset after data supplementation and enhancement.The experimental results showed that FD-YOLO’s mAP@0.5 improved by 6.8%compared to YOLOv5,reaching 82.6%and 19.1%–5%better than other state-of-the-art models.This method provides an effective new approach for detecting similar or multiscale pests in field crops.
基金supporting from Shanghai Pujiang Program(23PJ1400400)DHU startup grant,the Fundamental Research Funds for the Central Universities,DHU Distinguished Young Professor Program.
文摘The root system actively reacts to mechanical stimuli in its environment,transmitting mechanical signals to optimize the utilization of environmental resources.While the mechanical impedance created by the growth medium serves as the primary source of stimulation for the roots,extensive research has focused on the roots'response to static mechanical stimulation.However,the impact of dynamic mechanical stimulation on root phenotype remains underexplored.In this study,we utilized a low acyl gellan gum/polyacrylamide(GG/PAM)double network elastic hydrogel as the growth medium for rapeseed.We constructed a mechanical device to investigate the effects of reciprocating extrusion stimulation on the growth of the rapeseed root system.After three weeks of mechanical stimulation,the root system exhibited a significant increase in lateral roots.This branching enhanced the roots'anchoring and penetration into the hydrogel,thereby improving the root system's adaptability to its environment.Our findings offer valuable data and insights into the effects of reciprocating mechanical stimulation on root growth,providing a new way for engineering root phenotype.
基金Project ZR2023MF111 supported by Shandong Provincial Natural Science Foundation。
文摘With the advancement of Vehicle-to-Everything(V2X)technology,efficient resource allocation in dynamic vehicular networks has become a critical challenge for achieving optimal performance.Existing methods suffer from high computational complexity and decision latency under high-density traffic and heterogeneous network conditions.To address these challenges,this study presents an innovative framework that combines Graph Neural Networks(GNNs)with a Double Deep Q-Network(DDQN),utilizing dynamic graph structures and reinforcement learning.An adaptive neighbor sampling mechanism is introduced to dynamically select the most relevant neighbors based on interference levels and network topology,thereby improving decision accuracy and efficiency.Meanwhile,the framework models communication links as nodes and interference relationships as edges,effectively capturing the direct impact of interference on resource allocation while reducing computational complexity and preserving critical interaction information.Employing an aggregation mechanism based on the Graph Attention Network(GAT),it dynamically adjusts the neighbor sampling scope and performs attention-weighted aggregation based on node importance,ensuring more efficient and adaptive resource management.This design ensures reliable Vehicle-to-Vehicle(V2V)communication while maintaining high Vehicle-to-Infrastructure(V2I)throughput.The framework retains the global feature learning capabilities of GNNs and supports distributed network deployment,allowing vehicles to extract low-dimensional graph embeddings from local observations for real-time resource decisions.Experimental results demonstrate that the proposed method significantly reduces computational overhead,mitigates latency,and improves resource utilization efficiency in vehicular networks under complex traffic scenarios.This research not only provides a novel solution to resource allocation challenges in V2X networks but also advances the application of DDQN in intelligent transportation systems,offering substantial theoretical significance and practical value.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(*MSIT)(No.2018R1A5A7059549).
文摘The generation of high-quality,realistic face generation has emerged as a key field of research in computer vision.This paper proposes a robust approach that combines a Super-Resolution Generative Adversarial Network(SRGAN)with a Pyramid Attention Module(PAM)to enhance the quality of deep face generation.The SRGAN framework is designed to improve the resolution of generated images,addressing common challenges such as blurriness and a lack of intricate details.The Pyramid Attention Module further complements the process by focusing on multi-scale feature extraction,enabling the network to capture finer details and complex facial features more effectively.The proposed method was trained and evaluated over 100 epochs on the CelebA dataset,demonstrating consistent improvements in image quality and a marked decrease in generator and discriminator losses,reflecting the model’s capacity to learn and synthesize high-quality images effectively,given adequate computational resources.Experimental outcome demonstrates that the SRGAN model with PAM module has outperformed,yielding an aggregate discriminator loss of 0.055 for real,0.043 for fake,and a generator loss of 10.58 after training for 100 epochs.The model has yielded an structural similarity index measure of 0.923,that has outperformed the other models that are considered in the current study for analysis.
基金supported in part by the National Natural Science Foundation of China under Grant 62425110 and Grant U22A2002in part by the National Key Research and Development Program of China under Grant 2020YFA0711301+2 种基金in part by the Leading Project of Minzu University of China under Grant 2023QNYL23in part by the Key Research and Development Project of Nantong(Special Project for Prospective Technology Innovation)under Grant GZ2024002in part by the Suzhou Science and Technology Project,and in part by the FAW Jiefang Automotive Co.,Ltd.
文摘Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.
文摘Peristaltic transport of non-Newtonian nanofluids with double diffusion is essential to biological engineering,microfluidics,and manufacturing processes.The authors tackle the key problem of Sisko nanofluids under double diffusion convection with thermal radiations and electroosmotic effects.Thestudy proposes a solution approach by using Morlet-Wavelet Neural Networks that can effectively solve this complex problem by their superior ability in the capture of nonlinear dynamics.These convergence analyses were calculated across fifty independent runs.Theil’s Inequality Coefficient and theMean Squared Error values range from 10^(-7) to 10^(-5) and 10^(-7) to 10^(-10),respectively.These values showed the proposed method is scientifically reliable and fast converging.Studies reveal that the intensity of the magnetic field causes a reduction in the flow velocity profile in the center of the channel.It is also evaluated that thermal radiations enhance the energy of the system,which promotes thermally induced diffusion and particle flow.The physical applications of this work pertain to improving fluid flow and heat transfer in engineering structures like converters or cooling devices or magnetic fluids in electronics,energy,and biomedical applications,where optimal control of fluid behavior is of paramount importance.
文摘The purpose is to study modules of double crossproducts D (X, A) of Skew-Hopf pairs ( X, A). A sufficient and necessary condition for M to be D ( X, A)-mod is shown. Relations between D ( X, A)-mod and quantam Yang-Baxter A-mod or X-mod are revealed.
基金supported by the National Natural Science Foundation of China(Nos.51573159 and 51273176)the Fundamental Research Funds for the Central Universities(No.2016QNA4032)
文摘Developing a low-cost and well-recyclable adsorbent with high adsorption capacity is greatly desirable in dye wastewater treatment. Here, we demonstrate a kind of novel tough and reusable hydrogel beads with quite high capacity of dye adsorption via incorporating mussel-bioinspired poly（L-DOPA） （PDOPA） into alginate/poly（acrylamide） double network （DN） hydrogels. The synthesized PDOPA nanoaggregates were introduced into the DN hydrogels by simple one-pot mixing with the monomers prior to polymerization. The fabricated hydrogel beads exhibited high mechanical strength and good elastic recovery due to the interpenetrating Ca2＋-alginate and poly（acrylamide） networks. It was shown that the beads exhibited relatively high dye adsorption capacity compared to other adsorbents reported in literature, and the introduction of PDOPA with an appropriate amount raised the adsorption capacity. It is believed that the addition of PDOPA and the matrix of double network architecture contributed synergistically to the high adsorption capacity of hydrogel beads. Moreover, the desorption of dyes could be easily realized via rinsing in acidic water and ethanol solution. The hydrogel beads remained the high adsorption capacity even after 5 times of adsorption and desorption cycles. This tough and stable hydrogel with high adsorption capacity may have potential in treatment of dye wastewater released by textile dyeing industry.
基金supported by the National Natural Science Foundation of China (No.51273189)the National Science and Technology Major Project of the Ministry of Science and Technology of China (No.2016ZX05016),the National Science and Technology Major Project of the Ministry of Science and Technology of China (No.2016ZX05046)
文摘Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into the conventional tough DN hydro-gel system.We synthesize the PEG-PDAC/P(AAm-co-AAc)DN hydrogels,of which the first network is a well-defined PEG(polyethylene glycol)network loaded with PDAC(poly(acryloyloxyethyltrimethyl ammonium chloride))strands,while the second network is formed by copolymerizing AAm(acrylamide)with AAc(acrylic acid)and cross-linker MBAA(N;N′-methylenebisacrylamide).The PEG-PDAC/P(AAm-co-AAc)DN gels exhibits high mechanical strength.The fracture stress and toughness of the DN gels reach up to 0.9 MPa and 3.8 MJ/m^3,respectively.Compared with the conventional double network hydrogels with neutral polymers as the soft and ductile second network,the PEG-PDAC/P(AAm-co-AAc)DN hydrogels use P(AAm-co-AAc),a weak polyelectrolyte,as the second network.The AAc units serve as the coordination points with Fe^3+ions and physically crosslink the second network,which realizes the shape memory property activated by the reducing ability of ascorbic acid.Our results indicate that the high mechanical strength and shape memory properties,probably the two most important characters related to the potential application of the hydrogels,can be introduced simultaneously into the DN hydrogels if the functional monomer has been integrated into the network of DN hydrogels smartly.
基金financially supported by the National Natural Science Foundation of China(Nos.52073256,21404091 and 21404089)the Zhejiang Provincial Natural Science Foundation of China(No.LBY21E030001)。
文摘Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine.In this paper,a newly double network(DN)hydrogel was prepared based on zwitterionic material sulfobetaine methacrylate(SBMA)and natural polysaccharide,sodium alginate(SA).The PSBMA network is covalently crosslinked while the SA network is ionically crosslinked by Ca^(2+).The hybrid crosslinked double network structure endows the DN hydrogel with excellent mechanical properties(E=0.19±0.01 MPa,σ=0.73±0.03 MPa),fast self-recovery ability as well as excellent fatigue resistance.Moreover,the results show that the PSBMA/SA-Ca^(2+)DN hydrogel is biocompatible and resists the absorption of non-specific proteins and adhesion of microorganisms,such as cells and algae,exhibiting outstanding antifouling properties.These unique characteristics of PSBMA/SA-Ca^(2+)DN hydrogel make it a promising candidate for biomedical application,such as artificial connective tissues,implantable devices,and underwater equipment.
基金Project supported by the National Natural Science Foundation of China(Grant No.81272495)the Natural Science Foundation of Tianjin,China(Grant No.16JC2DJC32200)
文摘Recently, the phase compensation technique has allowed the ultrasound to propagate through the skull and focus into the brain. However, the temperature evolution during treatment is hard to control to achieve effective treatment and avoid over-high temperature. Proposed in this paper is a method to modulate the temperature distribution in the focal region. It superimposes two signals which focus on two preset different targets with a certain distance. Then the temperature distribution is modulated by changing triggering time delay and amplitudes of the two signals. The simulation model is established based on an 82-element transducer and computed tomography （CT） data of a volunteer＇s head. A finite- difference time-domain （FDTD） method is used to calculate the temperature distributions. The results show that when the distances between the two targets respectively are 7.5-12.5 mm on the acoustic axis and 2.0-3.0 mm in the direction perpendicular to the acoustic axis, a focal region with a uniform temperature distribution （64-65 ℃） can be created. Moreover, the volume of the focal region formed by one irradiation can be adjusted （26.8-266.7 mm3） along with the uniform temperature distribution. This method may ensure the safety and efficacy of HIFU brain tumor therapy.
基金Supported by National Natural Science Foundation of China(Grant No.61573233)Guangdong Provincial Natural Science Foundation of China(Grant No.2021A1515010661)Guangdong Provincial Special Projects in Key Fields of Colleges and Universities of China(Grant No.2020ZDZX2005).
文摘Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operation of high-speed trains.For this reason,a rail internal defect detection method based on an enhanced network structure and module design using ultrasonic images is proposed in this paper.First,a data augmentation method was used to extend the existing image dataset to obtain appropriate image samples.Second,an enhanced network structure was designed to make full use of the high-level and low-level feature information in the image,which improved the accuracy of defect detection.Subsequently,to optimize the detection performance of the proposed model,the Mish activation function was used to design the block module of the feature extraction network.Finally,the pro-posed rail defect detection model was trained.The experimental results showed that the precision rate and F1score of the proposed method were as high as 98%,while the model’s recall rate reached 99%.Specifically,good detec-tion results were achieved for different types of defects,which provides a reference for the engineering application of internal defect detection.Experimental results verified the effectiveness of the proposed method.
文摘A highly sensitive double artificial neural network （DANN） analysis with flow-injection chemiluminescence （FI-CL） has been developed to simultaneously determine the trace amounts of the gold and platinum in simulated mixed samples, without the boring process.
基金supported by the National Natural Science Foundation of China (U1834211, 61925302, 62103033)the Open Research Fund of the State Key Laboratory for Management and Control of Complex Systems (20210104)。
文摘High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.
基金supported by National Key R&D Program of China(Nos.2019YFC1905500 and 2021ZD0201604)National Natural Science Foundation of China(Nos.U20A20261,31870948,31971250 and 21922409)Seed Foundation of Tianjin University(No.2022XYY-0009)。
文摘Conductive hydrogels have shown great prospects as wearable flexible sensors.Nevertheless,it is still a challenge to construct hydrogel-based sensor with great mechanical strength and high strain sensitivity.Herein,an ion-conducting hydrogel was fabricated by introducing gelatin-dialdehydeβ-cyclodextrin(Gel-DACD)into polyvinyl alcohol-borax(PVA-borax)hydrogel network.Natural Gel-DACD network acted as mechanical deformation force through non-covalent cross-linking to endow the polyvinyl alcoholborax/gelatin-dialdehydeβ-cyclodextrin hydrogel(PGBCDH)with excellent mechanical stress(1.35 MPa),stretchability(400%),toughness(1.84 MJ/m3)and great fatigue resistance(200%strain for 100 cycles).Surprisingly,PGBCDH displayed good conductivity of 0.31 S/m after adding DACD to hydrogel network.As sensor,it showed rapid response(168 ms),high strain sensitivity(gage factor(GF)=8.57 in the strain range of 200%-250%)and reliable sensing stability(100%strain for 200 cycles).Importantly,PGBCDHbased sensor can accurately monitor complex body movements(knee,elbow,wrist and finger joints)and large-scale subtle movements(speech,swallow,breath and facial expressions).Thus,PGBCDH shows great potential for human monitoring with high precision.
基金supported by the Air Force Office of Scientific Research under Award(Grant FA9550-19-1-0395)the National Science Foundation(Grant 1935154)。
文摘A shape-memory double network hydrogel consists of two polymer networks:a chemically crosslinked primary network that is responsible for the permanent shape and a physically crosslinked secondary network that is used to fix the temporary shapes.The formation/melting transition of the secondary network serves as an effective mechanism for the double network hydrogel’s shape-memory effect.When the crosslinks in the secondary network are dissociated by applying an external stimulus,only the primary network is left to support the load.When the secondary network is re-formed by removing the stimulus,both the primary and secondary networks support the load.In the past,models have been developed for the constitutive behaviors of double network hydrogels,but the model of shape-memory double network hydrogels is still lacking.This work aims to build a constitutive model for the polyacrylamide-gelatin double network shape-memory hydrogel developed in our previous work.The model is first calibrated by experimental data of the double network shape-memory hydrogel under uniaxial loading and then employed to predict the shape-fixing performance of the hydrogel.The model is also implemented into a three-dimension finite element code and utilized to simulate the shape-memory behavior of the double network hydrogel with inhomogeneous deformations related to applications.
基金financially supported by the National Natural Science Foundation of China(Nos.52120105007 and 52374062)the Innovation Fund Project for Graduate Students of China University of Petroleum(East China)supported by“the Fundamental Research Funds for the Central Universities”(23CX04047A)。
文摘A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.
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supported by the National Natural Science Foundation of China(Grant No.51677149)
文摘To overcome hole-injection limitation of p^＋-n emitter junction in 4H-SiC light triggered thyristor, a novel high- voltage 4H-SiC light triggered thyristor with double-deck thin n-base structure is proposed and demonstrated by two- dimensional numerical simulations. In this new structure, the conventional thin n-base is split to double-deck. The hole- injection of p^＋-n emitter junction is modulated by modulating the doping concentration and thickness of upper-deck thin n- base. With double-deck thin n-base, the current gain coefficient of the top pnp transistor in 4H-SiC light triggered thyristor is enhanced. As a result, the triggering light intensity and the turn-on delay time of 4H-SiC light triggered thyristor are both reduced. The simulation results show that the proposed 10-kV 4H-SiC light triggered thyristor is able to be triggered on by 500-mW/cm^2 ultraviolet light pulse. Meanwhile, the turn-on delay time of the proposed thyristor is reduced to 337 ns.
