The complex aerodynamic interaction between tandem tilt-wing and multi-rotor directly affects the wing surface flow and rotor thrust,making it a critical factor during the tilt transition process of this configuration...The complex aerodynamic interaction between tandem tilt-wing and multi-rotor directly affects the wing surface flow and rotor thrust,making it a critical factor during the tilt transition process of this configuration of rotorcraft.The aerodynamic interaction of tandem tilt-wing and multi-rotor is investigated based on the CFD method.The aerodynamic effect of multi tilt-rotor is simulated as virtual disk modeling by adding source terms to the Navier-Stokes equations,effectively reducing the calculation time while maintaining the accuracy of aerodynamic interaction calculations.Aerodynamic forces and flow field characteristics of the tandem tilt-wing and multi-rotor under different tilt angles are compared between cases with and without aerodynamic interaction.Furthermore,the differences in aerodynamic forces between dynamic tilt transition and fixed-angle conditions were compared.The results show that the aerodynamic interaction of multi-rotor obviously increases the lift of front tilt-wing at different tilt angles,the wing lift under interaction is increased by more than 40%compared with isolated wing at tilt angle of 15°for the computation in this paper,which is related to the increase of wing flow velocity and the suppression of flow separation caused by multi-rotor;the wing blocking effect will increase rotor thrust,especially near the tilt angles of 30°and 45°;the increases of rear wing lift and rear rotor thrust under aerodynamic interaction are not significant because of suppression by the front wing’s downwash;the unsteady effects during dynamic tilting have a relatively minor impact on aerodynamic interaction,with the aerodynamic forces on the rotors and wings during the dynamic tilting process showing little difference from those under corresponding fixed tilt angles.展开更多
Background:The golden Syrian hamster is a valuable animal model for studying carcinogenesis,metabolic disorders,cardiovascular diseases,and viral infections due to its biological and pathological similarities to human...Background:The golden Syrian hamster is a valuable animal model for studying carcinogenesis,metabolic disorders,cardiovascular diseases,and viral infections due to its biological and pathological similarities to humans.However,the development of genetically engineered hamsters has lagged behind that of mice and rats,largely because of an embryonic development block at the two-cell stage in vitro.Although CRISPR/Cas9-mediated gene knockout has been achieved in hamsters,precise DNA fragment insertion or conditional knockout(cKO)models have not previously been reported,likely due to technical limitations in embryo manipulation and insufficient efficiency of homology-directed repair(HDR).Methods:In this study,we generated conditional alleles of the ApoF gene in golden Syrian hamsters.A two-cut strategy was applied using Cas9 protein,two sgRNAs,and a single donor plasmid containing exon 2 flanked by loxP sites and two~0.8 kb homology arms.A mixture of Cas9 protein,sgRNAs,and the donor plasmid was microinjected into the pronuclei of one-cell stage hamster embryos.Results:The efficiency of CRISPR/Cas9-mediated loxP knock-in reached up to 27%,and the genetically modified floxed alleles were successfully transmitted through the germline.The functionality of the inserted loxP sites was validated by in vivo Cremediated recombination following local administration of AAV vectors,including AAV-cTnT-Cre in the heart and AAV-CMV-Cre in the brain.Conclusions:To our knowledge,this work represents the first successful establishment of a conditional knockout model in the golden Syrian hamster,providing a valuable tool for mechanistic studies of gene function and disease modeling.展开更多
The plant pathogenic fungus Sclerotinia sclerotiorum is the causative agent of Sclerotinia stem rot(SSR)disease in most dicotyledons.Among the various proteins involved in drug efflux or substance transport,ATP-bindin...The plant pathogenic fungus Sclerotinia sclerotiorum is the causative agent of Sclerotinia stem rot(SSR)disease in most dicotyledons.Among the various proteins involved in drug efflux or substance transport,ATP-binding cassette(ABC)transporters constitute a superfamily of membrane-bound proteins that may play a crucial role in the survival of S.sclerotiorum.However,the expression patterns and functions of ABC transporter genes in S.sclerotiorum remain largely uncharacterized.This study characterized a highly expressed S.sclerotiorum ABC transporter gene during inoculation on host plants,Ss BMR1.Silencing Ss BMR1 resulted in a significant reduction in hyphal growth,infection cushion development,sclerotia formation,and virulence.Moreover,host-induced gene silencing(HIGS)of Ss BMR1 significantly enhanced plant resistance.Transcriptome and metabolomics analyses suggested that Ss BMR1 is involved in antioxidant and toxin transport,thereby influencing fungal defense and cell rescue mechanisms.In comparison to the wild-type strain,Ss BMR1 gene-silenced transformants exhibited a diminished response to extracellar oxidative stress and a decreased exporting of antioxidant glutathione.Tolerance assays further demonstrated the crucial role of Ss BMR1 in conferring resistance to the plant antifungal substances,camalexin and brassinin,as well as certain fungicides.Furthermore,Ss BMR1 gene-silenced transformants showed enhanced repression on virulence when sprayed with camalexin and brassinin on the leaves.Thus,Ss BMR1 likely contributes to virulence by facilitating the export of antioxidant and providing resistance against antifungal agents.The findings of this study provide valuable insights that could contribute to the development of novel management techniques for SSR.展开更多
In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→...In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.展开更多
Cloud data sharing is an important issue in modern times.To maintain the privacy and confidentiality of data stored in the cloud,encryption is an inevitable process before uploading the data.However,the centralized ma...Cloud data sharing is an important issue in modern times.To maintain the privacy and confidentiality of data stored in the cloud,encryption is an inevitable process before uploading the data.However,the centralized management and transmission latency of the cloud makes it difficult to support real-time processing and distributed access structures.As a result,fog computing and the Internet of Things(IoT)have emerged as crucial applications.Fog-assisted proxy re-encryption is a commonly adopted technique for sharing cloud ciphertexts.It allows a semitrusted proxy to transforma data owner’s ciphertext into another re-encrypted ciphertext intended for a data requester,without compromising any information about the original ciphertext.Yet,the user revocation and cloud ciphertext renewal problems still lack effective and secure mechanisms.Motivated by it,we propose a revocable conditional proxy re-encryption scheme offering ciphertext evolution(R-CPRE-CE).In particular,a periodically updated time key is used to revoke the user’s access privileges while an access condition prevents a malicious proxy from reencrypting unauthorized ciphertext.We also demonstrate that our scheme is provably secure under the notion of indistinguishability against adaptively chosen identity and chosen ciphertext attacks in the random oracle model.Performance analysis shows that our scheme reduces the computation time for a complete data access cycle from an initial query to the final decryption by approximately 47.05%compared to related schemes.展开更多
The carbonylation of amines offers a promising route for synthesizing N-substituted carbamates with high atom economy.However,conventional catalysts exhibit limited catalytic efficiency,and the underlying proton trans...The carbonylation of amines offers a promising route for synthesizing N-substituted carbamates with high atom economy.However,conventional catalysts exhibit limited catalytic efficiency,and the underlying proton transfer mechanism remains elusive.Herein,we reported a metal-free,room-temperature strategy utilizing 1,5,7-triazabicyclo[4.4.0]dec-5-ene(TBD)as a dual hydrogen bond catalyst to synergistically activate propylamine(PA)and dimethyl carbonate(DMC).This green catalytic system achieves a 10-fold acceleration in reaction rate compared to other hydrogen bonding catalysts under mild conditions.This is enabled by dual hydrogen bonding of TBD with PA and DMC,which facilitates rapid proton transfer and stabilizes tetrahedral intermediates.Theoretical calculations confirm that the dual hydrogen bond system significantly lowers activation energy compared to single hydrogen bond analogs.Furthermore,it was revealed that the hydrogen bonding network within the product is the primary factor responsible for the sluggish reaction rate.This study demonstrates the effectiveness of a dual hydrogen bond system in accelerating the carbonylation of amines and provides a green route to access carbamates.展开更多
The dynamic characteristics of the track system can directly affect its service performance and failure process.To explore the load characteristics and dynamic response of the track system under the dynamic loads from...The dynamic characteristics of the track system can directly affect its service performance and failure process.To explore the load characteristics and dynamic response of the track system under the dynamic loads from the rack vehicle in traction conditions,a systematic test of the track subsystem was carried out on a large-slope test line.In the test,the bending stress of the rack teeth,the wheel-rail forces,and the acceleration of crucial components in the track system were measured.Subsequently,a detailed analysis was conducted on the tested signals of the rack railway track system in the time domain and the time-frequency domains.The test results indicate that the traction force significantly affects the rack tooth bending stress and the wheel-rail forces.The vibrations of the track system under the traction conditions are mainly caused by the impacts generated from the gear-rack engagement,which are then transferred to the sleepers,the rails,and the ballast beds.Furthermore,both the maximum stress on the racks and the wheel-rail forces measured on the rails remain below their allowable values.This experimental study evaluates the load characteristics and reveals the vibration characteristics of the rack railway track system under the vehicle’s ultimate load,which is very important for the load-strengthening design of the key components such as racks and the vibration and noise reduction of the track system.展开更多
In this paper,we study the asymptotic behavior of the micropolar fluid flow through a thin domain,assuming zero Dirichlet boundary condition on the top boundary,which is rapidly oscillating,and non-standard boundary c...In this paper,we study the asymptotic behavior of the micropolar fluid flow through a thin domain,assuming zero Dirichlet boundary condition on the top boundary,which is rapidly oscillating,and non-standard boundary conditions on the flat bottom.Assuming“Reynolds roughness regime”,in which the thickness of the domain is very small compared to the wavelength of the roughness(i.e.a very slight roughness),we rigorously derive a generalized Reynolds equation for pressure,clearly showing the roughness-induced effects.Moreover,we give expressions for the average velocity and microrotation.展开更多
The main purpose of using geothermal energy piles(GEPs)is to enable the exploitation of geothermal energy for meeting the heating/cooling demands of buildings efficiently.However,the installation process of convention...The main purpose of using geothermal energy piles(GEPs)is to enable the exploitation of geothermal energy for meeting the heating/cooling demands of buildings efficiently.However,the installation process of conventional GEPs is inconvenient compared with that of traditional foundation piles.The pre-bored grouted planted geothermal energy pile(PGP GEP)is an innovative technology to simplify the installation process.Most investigations of in-situ experiments for conventional GEPs have focused on summer conditions.An in-situ test for a PGP GEP was conducted to analyze the temperature changes and thermo-mechanical characteristics under winter conditions.The results show that the average temperature of the pile decreased by 5.1℃,and the pile exhibited a general trend of high temperatures at both ends and low temperatures in the middle.In mechanics,strong pile end restraints resulted in smaller observed axial strain and higher axial thermal-induced force in the pile ends than at the middle of the pile.展开更多
To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervis...To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.展开更多
Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of...Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.展开更多
Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC rec...Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.展开更多
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of...Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.展开更多
文摘目的探讨基于ABC-X模型的护理干预在轻度认知障碍(mild cognitive impairment,MCI)患者中的应用价值。方法选取100例MCI患者,采用随机数表法将其分为观察组和对照组,各50例。观察组使用基于ABC-X模型的护理干预,对照组使用常规护理干预。比较两组患者干预前和干预4周后的焦虑自评量表(self-rating anxiety scale,SAS)、抑郁自评量表(self-rating depression scale,SDS)、蒙特利尔认知评估(Montreal cognitive assessment,Mo CA)量表、36条简明健康状况调查表(36-item short form health survey,SF-36)评分。结果两组患者在护理干预前SAS、SDS得分、MoCA量表总分、SF-36平均分比较,差异均无统计学意义(均P>0.05)。在干预4周后,观察组患者SAS、SDS得分均显著低于对照组(均P<0.01);Mo CA量表总分、SF-36平均分均显著高于对照组(均P<0.01)。结论在MCI患者中应用基于ABC-X模型的护理干预,能有效缓解其负面情绪,改善认知功能,进而提升其生活质量,因此具备良好的推广应用价值。
基金supported by the National Key Laboratory of Helicopter Aeromechanics Fund(No.2024-CXPT-GF-JJ-093-05).
文摘The complex aerodynamic interaction between tandem tilt-wing and multi-rotor directly affects the wing surface flow and rotor thrust,making it a critical factor during the tilt transition process of this configuration of rotorcraft.The aerodynamic interaction of tandem tilt-wing and multi-rotor is investigated based on the CFD method.The aerodynamic effect of multi tilt-rotor is simulated as virtual disk modeling by adding source terms to the Navier-Stokes equations,effectively reducing the calculation time while maintaining the accuracy of aerodynamic interaction calculations.Aerodynamic forces and flow field characteristics of the tandem tilt-wing and multi-rotor under different tilt angles are compared between cases with and without aerodynamic interaction.Furthermore,the differences in aerodynamic forces between dynamic tilt transition and fixed-angle conditions were compared.The results show that the aerodynamic interaction of multi-rotor obviously increases the lift of front tilt-wing at different tilt angles,the wing lift under interaction is increased by more than 40%compared with isolated wing at tilt angle of 15°for the computation in this paper,which is related to the increase of wing flow velocity and the suppression of flow separation caused by multi-rotor;the wing blocking effect will increase rotor thrust,especially near the tilt angles of 30°and 45°;the increases of rear wing lift and rear rotor thrust under aerodynamic interaction are not significant because of suppression by the front wing’s downwash;the unsteady effects during dynamic tilting have a relatively minor impact on aerodynamic interaction,with the aerodynamic forces on the rotors and wings during the dynamic tilting process showing little difference from those under corresponding fixed tilt angles.
基金State Key Laboratory Special Fund,Grant/Award Number:2060204Open Research Project in State Key Laboratory of Vascular Homeostasis and Remodeling,Grant/Award Number:Peking University,202411+3 种基金The Non-profit Central Research Institute Fund of the Chinese Academy of Medical Sciences,Grant/Award Number:2023-PT180-01Haihe Laboratory of Cell Ecosystem Innovation Fund,Grant/Award Number:HH24KYZX0007CAMS Innovation Fund for Medical Sciences,Grant/Award Number:2021-I2M-1-024,2022-I2M-1-020 and 2023-I2M-2-001the National Key Research and Development Program of China from the Ministry of Science and Technology,Grant/Award Number:2021YFF0702802。
文摘Background:The golden Syrian hamster is a valuable animal model for studying carcinogenesis,metabolic disorders,cardiovascular diseases,and viral infections due to its biological and pathological similarities to humans.However,the development of genetically engineered hamsters has lagged behind that of mice and rats,largely because of an embryonic development block at the two-cell stage in vitro.Although CRISPR/Cas9-mediated gene knockout has been achieved in hamsters,precise DNA fragment insertion or conditional knockout(cKO)models have not previously been reported,likely due to technical limitations in embryo manipulation and insufficient efficiency of homology-directed repair(HDR).Methods:In this study,we generated conditional alleles of the ApoF gene in golden Syrian hamsters.A two-cut strategy was applied using Cas9 protein,two sgRNAs,and a single donor plasmid containing exon 2 flanked by loxP sites and two~0.8 kb homology arms.A mixture of Cas9 protein,sgRNAs,and the donor plasmid was microinjected into the pronuclei of one-cell stage hamster embryos.Results:The efficiency of CRISPR/Cas9-mediated loxP knock-in reached up to 27%,and the genetically modified floxed alleles were successfully transmitted through the germline.The functionality of the inserted loxP sites was validated by in vivo Cremediated recombination following local administration of AAV vectors,including AAV-cTnT-Cre in the heart and AAV-CMV-Cre in the brain.Conclusions:To our knowledge,this work represents the first successful establishment of a conditional knockout model in the golden Syrian hamster,providing a valuable tool for mechanistic studies of gene function and disease modeling.
基金received financial support from the Natural Science Foundation of Chongqing,China(CSTB2023NSCQMSX0355)the Fundamental Research Funds for the Central Universities,China(SWU120075)the National Natural Science Foundation of China(32372077)。
文摘The plant pathogenic fungus Sclerotinia sclerotiorum is the causative agent of Sclerotinia stem rot(SSR)disease in most dicotyledons.Among the various proteins involved in drug efflux or substance transport,ATP-binding cassette(ABC)transporters constitute a superfamily of membrane-bound proteins that may play a crucial role in the survival of S.sclerotiorum.However,the expression patterns and functions of ABC transporter genes in S.sclerotiorum remain largely uncharacterized.This study characterized a highly expressed S.sclerotiorum ABC transporter gene during inoculation on host plants,Ss BMR1.Silencing Ss BMR1 resulted in a significant reduction in hyphal growth,infection cushion development,sclerotia formation,and virulence.Moreover,host-induced gene silencing(HIGS)of Ss BMR1 significantly enhanced plant resistance.Transcriptome and metabolomics analyses suggested that Ss BMR1 is involved in antioxidant and toxin transport,thereby influencing fungal defense and cell rescue mechanisms.In comparison to the wild-type strain,Ss BMR1 gene-silenced transformants exhibited a diminished response to extracellar oxidative stress and a decreased exporting of antioxidant glutathione.Tolerance assays further demonstrated the crucial role of Ss BMR1 in conferring resistance to the plant antifungal substances,camalexin and brassinin,as well as certain fungicides.Furthermore,Ss BMR1 gene-silenced transformants showed enhanced repression on virulence when sprayed with camalexin and brassinin on the leaves.Thus,Ss BMR1 likely contributes to virulence by facilitating the export of antioxidant and providing resistance against antifungal agents.The findings of this study provide valuable insights that could contribute to the development of novel management techniques for SSR.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12361040,12061064)the National Science Foundation of Gansu Province(Grant No.22JR5RA264)State Scholarship Fund(Grant No.20230862021).
文摘In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.
基金supported in part by the National Science and Technology Council of Republic of China under the contract numbers NSTC 114-2221-E-019-055-MY2NSTC 114-2221-E-019-069.
文摘Cloud data sharing is an important issue in modern times.To maintain the privacy and confidentiality of data stored in the cloud,encryption is an inevitable process before uploading the data.However,the centralized management and transmission latency of the cloud makes it difficult to support real-time processing and distributed access structures.As a result,fog computing and the Internet of Things(IoT)have emerged as crucial applications.Fog-assisted proxy re-encryption is a commonly adopted technique for sharing cloud ciphertexts.It allows a semitrusted proxy to transforma data owner’s ciphertext into another re-encrypted ciphertext intended for a data requester,without compromising any information about the original ciphertext.Yet,the user revocation and cloud ciphertext renewal problems still lack effective and secure mechanisms.Motivated by it,we propose a revocable conditional proxy re-encryption scheme offering ciphertext evolution(R-CPRE-CE).In particular,a periodically updated time key is used to revoke the user’s access privileges while an access condition prevents a malicious proxy from reencrypting unauthorized ciphertext.We also demonstrate that our scheme is provably secure under the notion of indistinguishability against adaptively chosen identity and chosen ciphertext attacks in the random oracle model.Performance analysis shows that our scheme reduces the computation time for a complete data access cycle from an initial query to the final decryption by approximately 47.05%compared to related schemes.
基金financially supported by the National Key R&D Program of China(2023YFC3905400)the Clean Combustion and Low-carbon Utilization of Coal,Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No.XDA 29000000.
文摘The carbonylation of amines offers a promising route for synthesizing N-substituted carbamates with high atom economy.However,conventional catalysts exhibit limited catalytic efficiency,and the underlying proton transfer mechanism remains elusive.Herein,we reported a metal-free,room-temperature strategy utilizing 1,5,7-triazabicyclo[4.4.0]dec-5-ene(TBD)as a dual hydrogen bond catalyst to synergistically activate propylamine(PA)and dimethyl carbonate(DMC).This green catalytic system achieves a 10-fold acceleration in reaction rate compared to other hydrogen bonding catalysts under mild conditions.This is enabled by dual hydrogen bonding of TBD with PA and DMC,which facilitates rapid proton transfer and stabilizes tetrahedral intermediates.Theoretical calculations confirm that the dual hydrogen bond system significantly lowers activation energy compared to single hydrogen bond analogs.Furthermore,it was revealed that the hydrogen bonding network within the product is the primary factor responsible for the sluggish reaction rate.This study demonstrates the effectiveness of a dual hydrogen bond system in accelerating the carbonylation of amines and provides a green route to access carbamates.
基金supported by the National Natural Science Foundation of China(No.52388102)the Sichuan Science and Technology Program(No.2024NSFTD0011)the Fundamental Research Funds for the State Key Laboratory of Rail Transit Vehicle System of Southwest Jiaotong University(No.2023TPL-T11).
文摘The dynamic characteristics of the track system can directly affect its service performance and failure process.To explore the load characteristics and dynamic response of the track system under the dynamic loads from the rack vehicle in traction conditions,a systematic test of the track subsystem was carried out on a large-slope test line.In the test,the bending stress of the rack teeth,the wheel-rail forces,and the acceleration of crucial components in the track system were measured.Subsequently,a detailed analysis was conducted on the tested signals of the rack railway track system in the time domain and the time-frequency domains.The test results indicate that the traction force significantly affects the rack tooth bending stress and the wheel-rail forces.The vibrations of the track system under the traction conditions are mainly caused by the impacts generated from the gear-rack engagement,which are then transferred to the sleepers,the rails,and the ballast beds.Furthermore,both the maximum stress on the racks and the wheel-rail forces measured on the rails remain below their allowable values.This experimental study evaluates the load characteristics and reveals the vibration characteristics of the rack railway track system under the vehicle’s ultimate load,which is very important for the load-strengthening design of the key components such as racks and the vibration and noise reduction of the track system.
文摘In this paper,we study the asymptotic behavior of the micropolar fluid flow through a thin domain,assuming zero Dirichlet boundary condition on the top boundary,which is rapidly oscillating,and non-standard boundary conditions on the flat bottom.Assuming“Reynolds roughness regime”,in which the thickness of the domain is very small compared to the wavelength of the roughness(i.e.a very slight roughness),we rigorously derive a generalized Reynolds equation for pressure,clearly showing the roughness-induced effects.Moreover,we give expressions for the average velocity and microrotation.
文摘The main purpose of using geothermal energy piles(GEPs)is to enable the exploitation of geothermal energy for meeting the heating/cooling demands of buildings efficiently.However,the installation process of conventional GEPs is inconvenient compared with that of traditional foundation piles.The pre-bored grouted planted geothermal energy pile(PGP GEP)is an innovative technology to simplify the installation process.Most investigations of in-situ experiments for conventional GEPs have focused on summer conditions.An in-situ test for a PGP GEP was conducted to analyze the temperature changes and thermo-mechanical characteristics under winter conditions.The results show that the average temperature of the pile decreased by 5.1℃,and the pile exhibited a general trend of high temperatures at both ends and low temperatures in the middle.In mechanics,strong pile end restraints resulted in smaller observed axial strain and higher axial thermal-induced force in the pile ends than at the middle of the pile.
基金supported by the National Natural Science Foundation of China Funded Project(Project Name:Research on Robust Adaptive Allocation Mechanism of Human Machine Co-Driving System Based on NMS Features,Project Approval Number:52172381).
文摘To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.
基金supported by the Chung-Ang University Research Grants in 2023.Alsothe work is supported by the ELLIIT Excellence Center at Linköping–Lund in Information Technology in Sweden.
文摘Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.
基金supported by the National Natural Science Foundation of China(Grant Nos.42077242 and 42171407)the Graduate Innovation Fund of Jilin University.
文摘Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.
基金supported by Supported by the Scientific Research Foundation for High-Level Talents of Zhoukou Normal University(ZKNUC2024018).
文摘Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.
