Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
Some homological properties of R-modules were investigated by matrices over aring R. Given two cardinal numbers α, β and an α x β row-finite matrix A, it was proved thatExt_R^1(R^((α))/R^((β))A, M) = 0 if and on...Some homological properties of R-modules were investigated by matrices over aring R. Given two cardinal numbers α, β and an α x β row-finite matrix A, it was proved thatExt_R^1(R^((α))/R^((β))A, M) = 0 if and only if M_α/r_(M_α)(R^((β))A) ≈ Hom_R(R^((β))A,M) ifand only if r_(M_β)l_(R^((β)))(A) = AM_α. Thus, the notion of (m,n)-injectivity was extended.Moreover, ( α, β) -flatness was characterized via annihilators of matrices, factorizations ofhomomorphisms as well as homological groups so that (m, n)-flat modules, f-projective modules andn-projective modules were consolidated under the notion of (α, β)-flat modules. Furthermore, acharacterization of left R-ML modules and some equivalent conditions for R^((β)) to be left R-MLwere presented. Consequently, the notions of coherent rings, (m, n)-coherent rings and π-coherentrings were consolidated under that of (α, β)-coherent rings.展开更多
Let R be a commutative noetherian local ring. In this paper, we study Gorenstein projective, injective and flat modules with respect to a semidualizing R-module C, and we give some connections between C-Gorenstein hom...Let R be a commutative noetherian local ring. In this paper, we study Gorenstein projective, injective and flat modules with respect to a semidualizing R-module C, and we give some connections between C-Gorenstein homological dimensions and the Auslander categories of R.展开更多
In this article, we define almost prime submodules as a new generalization of prime and weakly prime submodules of unitary modules over a commutative ring with identity. We study some basic properties of almost prime ...In this article, we define almost prime submodules as a new generalization of prime and weakly prime submodules of unitary modules over a commutative ring with identity. We study some basic properties of almost prime submodules and give some characterizations of them, especially for （finitely generated faithful） multiplication modules.展开更多
The aim of this paper is to study the conditions by which a P-prime sub-module can be expressed as a finite intersection or union of P-prime submodules. Also corresponding to dimension and rank of modules, some equiva...The aim of this paper is to study the conditions by which a P-prime sub-module can be expressed as a finite intersection or union of P-prime submodules. Also corresponding to dimension and rank of modules, some equivalent conditions for a ring to be a Dedekind domain are given.展开更多
Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address ...Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address this challenge,a mushroom recognition method was proposed based on an erase module integrated into the EL-DenseNet model.EL-DenseNet,an extension of DenseNet,incorporated an erase attention module designed to enhance sensitivity to visible features.The erase module helped eliminate complex backgrounds and irrelevant information,allowing the mushroom body to be preserved and increasing recognition accuracy in cluttered environments.Considering the difficulty in distinguishing similar mushroom species,label smoothing regularization was employed to mitigate mislabeling errors that commonly arose from human observers.This strategy converted hard labels into soft labels during training,reducing the model’s overreliance on noisy labels and improving its generalization ability.Experimental results showed that the proposed EL-DenseNet,when combined with transfer learning,achieved a recognition accuracy of 96.7%for mushrooms in occluded and complex backgrounds.Compared with the original DenseNet and other classic models,this approach demonstrated superior accuracy and robustness,providing a promising solution for intelligent mushroom recognition.展开更多
In this article, we introduce and study the concept of n-Gorenstein injective （resp., n-Gorenstein flat） modules as a nontrivial generalization of Gorenstein injective （resp., Gorenstein flat） modules. We invest...In this article, we introduce and study the concept of n-Gorenstein injective （resp., n-Gorenstein flat） modules as a nontrivial generalization of Gorenstein injective （resp., Gorenstein flat） modules. We investigate the properties of these modules in various ways. For example, we show that the class of n-Gorenstein injective （resp., n -Gorenstein flat） modules is closed under direct sums and direct products for n ≥ 2. To this end, we first introduce and study the notions of n-injective modules and n-flat modules.展开更多
The definition of principally pseudo injectivity motivates us to generalize tae notion of injectivity, noted SP pseudo injectivity. The aim of this paper is to investigate characterizations and properties of SP pseudo...The definition of principally pseudo injectivity motivates us to generalize tae notion of injectivity, noted SP pseudo injectivity. The aim of this paper is to investigate characterizations and properties of SP pseudo injective modules. Various results are devel- oped, many extending known results. As applications, we give some characterizations on Noetherian rings, QI rings, quasi-Frobenius rings.展开更多
Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differe...Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differences between single types of modification modules,neglecting the impact of steric-hindrance effect caused by chemical structure.Herein,single-tailed modification module with low-steric-hindrance effect and two-tailed modification module with high-steric-hindrance effect were selected to construct paclitaxel prodrugs(P-LA_(C18)and P-BAC18),and the in-depth insights of the sterichindrance effect on prodrug nanoassemblies were explored.Notably,the size stability of the two-tailed prodrugs was enhanced due to improved intermolecular interactions and steric hindrance.Single-tailed prodrug nanoassemblies were more susceptible to attack by redox agents,showing faster drug release and stronger antitumor efficacy,but with poorer safety.In contrast,two-tailed prodrug nanoassemblies exhibited significant advantages in terms of pharmacokinetics,tumor accumulation and safety due to the good size stability,thus ensuring equivalent antitumor efficacy at tolerance dose.These findings highlighted the critical role of steric-hindrance effect of the modification module in regulating the structureactivity relationship of prodrug nanoassemblies and proposed new perspectives into the precise design of self-assembled prodrugs for high-performance cancer therapeutics.展开更多
With the rapid development of the new energy automotive industry,the enhancement of lithium battery performance and production efficiency has become critical.This article explores the application of artificial intelli...With the rapid development of the new energy automotive industry,the enhancement of lithium battery performance and production efficiency has become critical.This article explores the application of artificial intelligence technology in the lithium battery module PACK line,analyzing how it optimizes the production process and improves production efficiency,and predicts future development trends.The PACK line is an important link in battery manufacturing,involving complex processes such as cell sorting,welding,assembly and testing.The application of AI technology in image recognition,data analysis and predictive maintenance provides new solutions for the intelligent upgrading of the PACK line.This article describes the process of the PACK line in detail,analyzes the challenges under current technological levels,and reviews the application cases of AI technology in the manufacturing industry.The study aims to provide theoretical and practical guidance for the intelligent development of lithium battery module PACK lines,discussing the integration of AI technology,its actual performance,technical challenges,and solutions.It is expected that AI technology will play a greater role in the PACK line,and future research will focus on improving the adaptability of models,developing efficient algorithms,and further integrating into the production line.展开更多
Monocot root systems comprise a large number of lateral roots to allow them to survive and colonize land.Auxin signaling pathways centered on Aux/IAA play a crucial role in lateral root development.However,in non-mode...Monocot root systems comprise a large number of lateral roots to allow them to survive and colonize land.Auxin signaling pathways centered on Aux/IAA play a crucial role in lateral root development.However,in non-model monocot plants,the effects of Aux/IAA on lateral root initiation and number remain largely unknown.The present study transformed PheIAA17,a member of the Aux/IAA family of Moso bamboo,into rice and found that it significantly drove plants to produce lateral roots and improved the rooting rate.Quantitative experiments showed that PheIAA17 overexpression significantly affected the expression of ARF family members.Phylogenetic and promoter analyses indicate that PheARF3-2 belongs to class B ARF,and the promoter region contains auxin response elements.The results of yeast one-hybrid and dual-luciferase reporter assays confirmed that PheIAA17 bound specific fragments of the PheARF3-2 promoter to repress its transcriptional activity.Y2H and BiFC assay have shown that PheIAA17 and PheIAA30-3 could physically interact in vitro and in vivo.Taken together,this study reports a new molecular module centered on PheIAA17,which directs plants to alter root morphology through an increase in lateral roots.展开更多
Modules enable students to engage with content at their own pace,fostering autonomy and deeper understanding.The modular approach ensures clarity in presenting objectives,instructions,and concepts,while having illustr...Modules enable students to engage with content at their own pace,fostering autonomy and deeper understanding.The modular approach ensures clarity in presenting objectives,instructions,and concepts,while having illustrations,activities,and assessments could enhance comprehension and retention.This paper was a developmental study on STS module for college students using the ADDIE Model(Analysis,Design,Development,Implementation,and Evaluation).Sampled 673 first-year students from Northwest Samar State University participated in the study,with 299 participating in a test try-out and 374 in the students’performance evaluation.Three expert evaluators with backgrounds in science,English,and psychology,each with over four years of experience,assessed the modules to ensure alignment with the study’s constructivist learning goals and instructional integrity.The findings revealed that both students and experts had rated the instructional module positively,indicating its effectiveness in facilitating learning and completing lessons.Key aspects such as the style of illustrations and written expressions,the usefulness of learning activities,and the guidance provided by illustrations and captions were especially well-received.The module was praised for its clear objectives,understandable instructions,and engaging tasks like trivia and puzzles.Expert evaluations highlighted relevance,simplicity,and balanced emphasis on topics in the module content.Furthermore,students in test group demonstrated significant improvement in performance,with post-test scores notably higher than pre-test scores,confirming the module’s effectiveness in enhancing learning outcomes.Consequently,this paper provides an opportunity to integrate science learning with initiatives aimed at promoting environmental preservation and driving social change.展开更多
Transcription factors(TFs)play key roles in the regulatory network of leaf senescence.However,many nodes in this network remain unclear.To elucidate the mechanism of leaf senescence mediated by a rice TF,WRKY10,the ex...Transcription factors(TFs)play key roles in the regulatory network of leaf senescence.However,many nodes in this network remain unclear.To elucidate the mechanism of leaf senescence mediated by a rice TF,WRKY10,the expression of multiple senescence-related genes and physiological phenotypes were monitored in WRKY10-and VQ MOTIF-CONTAINING PROTEIN8(VQ8)-overexpressing plants and the wrky10 and vq8 mutants.Our results showed that WRKY10 positively regulates abscisic acid(ABA)-and dark-induced senescence(DIS)by directly regulating the expression of multiple senescence-related genes.The VQ8 protein,a repressor of WRKY10,negatively regulates WRKY10-mediated DIS.The WRKY10-VQ8 module fine-tunes the progression of DIS.ABA,methyl jasmonate,and H_(2)O_(2) accelerate WRKY10-mediated DIS,whereas ammonium nitrate and dithiothreitol delay WRKY10-mediated DIS.Further analysis revealed that WRKY10 and VQ8 interact with ABA RESPONSIVE ELEMENT BINDING FACTOR1(ABF1)or ABF2.VQ8 represses the transcriptional activity of ABF1 and ABF2.Overexpression of ABF1 or ABF2 accelerates ABA-and dark-induced senescence and H_(2)O_(2) accumulation in N.benthamiana leaves,and WRKY10 and VQ8 can inhibit either ABF1-or ABF2-induced cell necrosis.Taken together,WRKY10 integrates multiple senescence signals to establish an orderly progression of leaf senescence.The VQ8 protein acts as a brake on WRKY10-induced senescence and ABF1/2-induced cell death,preventing uncontrolled cell death.展开更多
Current research focuses on the performance degradation of photovoltaic(PV)modules,examining both crystalline silicon(p-Si and m-Si)and thin-film technologies,including a-Si/μc-Si,HIT,CdTe and CIGS.These modules were...Current research focuses on the performance degradation of photovoltaic(PV)modules,examining both crystalline silicon(p-Si and m-Si)and thin-film technologies,including a-Si/μc-Si,HIT,CdTe and CIGS.These modules were operated outdoors in two distinct climatic zones in the United States(US)over a period of three years.The degradation analysis includes the study of various quantities,such as the decrease in peak power,the reduction in current and voltage,and the variation in the fill factor.The annual degradation rate(DR)of PV modules is obtained by a linear fit of the effective maximum power evolution over time.The results indicate that m-Si and p-Si modules experienced a slight decrease in performance,with DRs of−0.83%and−1.07%,respectively.Subsequently,the HIT module exhibited a DR of−1.75%,while CdTe and CIGS modules demonstrated DRs of−2.03%and−2.45%,respectively.The a-Si/μc-Si module showed the highest DR at−3.26%.Using the Single Diode Model(SDM),we monitored the temporal evolution of physical parameters as well as changes in the shape of the I-V and P-V curves over time.We found that the key points of the I-V curve degrade over time,as do the I-V and P-V characteristics between two days approximately 30 months apart.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
Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant attention.Compared with traditional encryption and blockchain technologies,PLA provides a more computationally effi...Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant attention.Compared with traditional encryption and blockchain technologies,PLA provides a more computationally efficient alternative to exploiting the properties of the wireless medium itself.Some existing PLA solutions rely on static mechanisms,which are insufficient to address the authentication challenges in fifth generation(5G)and beyond wireless networks.Additionally,with the massive increase in mobile device access,the communication security of the IoT is vulnerable to spoofing attacks.To overcome the above challenges,this paper proposes a lightweight deep convolutional neural network(CNN)equipped with squeeze and excitation module(SE module)in dynamic wireless environments,namely SE-ConvNet.To be more specific,a convolution factorization is developed to reduce the complexity of PLA models based on deep learning.Moreover,an SE module is designed in the deep CNN to enhance useful features andmaximize authentication accuracy.Compared with the existing solutions,the proposed SE-ConvNet enabled PLA scheme performs excellently in mobile and time-varying wireless environments while maintaining lower computational complexity.展开更多
This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in ...This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance.The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules.This enables accurate determination of the optimal timing for postfailure corrective maintenance.To optimize the maintenance strategy,the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate.The model considers multiple cost factors,including inspection costs,preventive maintenance costs,restorative maintenance costs,and penalty costs associated with delayed fault detection.Through this optimization framework,the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions.Comparative analysis demonstrates that the twostage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models.When evaluated against traditional maintenance approaches,including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies,the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components.The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization,leading to enhanced power generation performance.These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance.展开更多
The intelligent vehicle corner module system,which integrates four-wheel independent drive,independent steering,independent braking and active suspension,can accurately and efficiently perform vehicle driving tasks an...The intelligent vehicle corner module system,which integrates four-wheel independent drive,independent steering,independent braking and active suspension,can accurately and efficiently perform vehicle driving tasks and is the best carrier of intelligent vehicles.Nevertheless,too many angle/torque control inputs make control difficult and non-real-time.In this paper,a hierarchical real-time motion control framework for corner module configuration intelligent electric vehicles is proposed.In the trajectory planning module,an improved driving risk field is designed to describe the surrounding environment’s driving risk.Combined with the kinematic vehicle-road model,model predictive control(MPC)method,spline curve method,the local reference trajectory of safety,comfort and smoothness is planned in real time.The optimal steering angle is determined using MPC method in path tracking module.In the motion control module,a feedforward-feedback controller assigns the optimal steering angle to the front/rear axles,and an angle allocation controller distributes the target angles of the front/rear axles to four steered wheels.Finally,the PreScan-Simulink-CarSim joint simulation environment is established for conducting the human-in-the-loop emergency obstacle avoidance experiment.It took only 0.005 s for the hierarchical motion control system to determine its average solution time.This proves the effectiveness of the hierarchical motion control system.展开更多
The secondary cell wall(SCW)is essential for plant growth and development in vascular plants,and its biosynthesis is mainly controlled by a complex hierarchical regulatory network involving multiple transcription fact...The secondary cell wall(SCW)is essential for plant growth and development in vascular plants,and its biosynthesis is mainly controlled by a complex hierarchical regulatory network involving multiple transcription factors(TFs)at the transcription level.However,TFs that specifically regulate secondary xylem have not been widely reported.In this study,we described a poplar KNOTTED1-like homeobox(KNOX)TF PtoKNAT3a1,which was mainly expressed in the expanding xylem cells of stems.PtoKNAT3a1 overexpression caused fiber SCW thickening and increased all measured SCW compositions by upregulating the expression of SCW-biosynthetic genes and-associated TFs,but had no effect on the vessels of SCW.The opposite phenotype was observed in the PtoKNAT3a1-knockout lines.Hence,we further demonstrated that Pto-KNAT3a1 could physically interact with the NAC master switches PtoWND2A/3A to enhance the expression of downstream MYB TFs and SCW biosynthetic genes(including PtoMYB20,PtoMYB21,PtoMYB90,PtoCoMT2,PtoGT43B and PtoCesA8).Meanwhile,the studies also demonstrate that the KNAT3 has functional differentiation in xylem development.Taken together,these data suggest that the KNAT3a1-WND2A/3A module positively regulates fiber development of the secondary xylem in poplar via the WND2A/3A-mediated hierarchical regulatory network,and supplies useful information for fiber SCW formation.The research not only deepens the understanding of the hierarchical regulatory network affecting SCW formation but also supplies genetic resources and molecular targets for plant fiber utilization.展开更多
Gibberella stalk rot(GSR)caused by Fusarium graminearum is one of the most devastating diseases of maize,seriously impacting maize yield and quality,as well as the ability to use technology of mechanical harvesting.En...Gibberella stalk rot(GSR)caused by Fusarium graminearum is one of the most devastating diseases of maize,seriously impacting maize yield and quality,as well as the ability to use technology of mechanical harvesting.Environmental conditions including photoperiod affect crop disease resistance.However,the mechanism underlying photoperiod-regulated maize GSR resistance remains unexplored.We found in this study that GSR resistance is regulated by the ZmPIF4.1(Phytochrome-Interacting Factor4)-ZmPTI1c(Pto-Interacting 1)-ZmMYB31 module coupled with photoperiod.The functional analysis of zmpti1c mutant indicated that ZmPTI1c negatively regulates maize GSR resistance.Short day promoted the disease progression in both zmpti1c and wild-type plants.ZmPTI1c promoter contains multiple predicted cis-acting elements for light responses.Yeast one-hybrid assay(Y1H),Electrophoretic mobility shift analysis(EMSA),and Dual-luciferase(LUC)reporter assays demonstrated that ZmPIF4.1 binds to the G-box in ZmPTI1c promoter and activates its expression.Moreover,expression levels of ZmPIF4 and ZmPTI1c were significantly higher under short day than under long day.ZmPTI1c interacted with and phosphorylated ZmMYB31.GSR resistance in zmmyb31 mutant was significantly increased than in wild type,indicating that ZmMYB31 also negatively regulated GSR resistance.Furthermore,ZmMYB31 suppressed the transcriptional activation of ZmPTI1c by ZmPIF4.1.Overall,ZmPIF4.1-ZmPTI1c-ZmMYB31negatively regulates maize immunity to GSR,which is likely modulated by photoperiod.展开更多
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
文摘Some homological properties of R-modules were investigated by matrices over aring R. Given two cardinal numbers α, β and an α x β row-finite matrix A, it was proved thatExt_R^1(R^((α))/R^((β))A, M) = 0 if and only if M_α/r_(M_α)(R^((β))A) ≈ Hom_R(R^((β))A,M) ifand only if r_(M_β)l_(R^((β)))(A) = AM_α. Thus, the notion of (m,n)-injectivity was extended.Moreover, ( α, β) -flatness was characterized via annihilators of matrices, factorizations ofhomomorphisms as well as homological groups so that (m, n)-flat modules, f-projective modules andn-projective modules were consolidated under the notion of (α, β)-flat modules. Furthermore, acharacterization of left R-ML modules and some equivalent conditions for R^((β)) to be left R-MLwere presented. Consequently, the notions of coherent rings, (m, n)-coherent rings and π-coherentrings were consolidated under that of (α, β)-coherent rings.
基金Supported by the National Natural Science Foundation of China(Grant No.11261050)
文摘Let R be a commutative noetherian local ring. In this paper, we study Gorenstein projective, injective and flat modules with respect to a semidualizing R-module C, and we give some connections between C-Gorenstein homological dimensions and the Auslander categories of R.
文摘In this article, we define almost prime submodules as a new generalization of prime and weakly prime submodules of unitary modules over a commutative ring with identity. We study some basic properties of almost prime submodules and give some characterizations of them, especially for （finitely generated faithful） multiplication modules.
文摘The aim of this paper is to study the conditions by which a P-prime sub-module can be expressed as a finite intersection or union of P-prime submodules. Also corresponding to dimension and rank of modules, some equivalent conditions for a ring to be a Dedekind domain are given.
文摘Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address this challenge,a mushroom recognition method was proposed based on an erase module integrated into the EL-DenseNet model.EL-DenseNet,an extension of DenseNet,incorporated an erase attention module designed to enhance sensitivity to visible features.The erase module helped eliminate complex backgrounds and irrelevant information,allowing the mushroom body to be preserved and increasing recognition accuracy in cluttered environments.Considering the difficulty in distinguishing similar mushroom species,label smoothing regularization was employed to mitigate mislabeling errors that commonly arose from human observers.This strategy converted hard labels into soft labels during training,reducing the model’s overreliance on noisy labels and improving its generalization ability.Experimental results showed that the proposed EL-DenseNet,when combined with transfer learning,achieved a recognition accuracy of 96.7%for mushrooms in occluded and complex backgrounds.Compared with the original DenseNet and other classic models,this approach demonstrated superior accuracy and robustness,providing a promising solution for intelligent mushroom recognition.
基金The NSF(11501451)of Chinathe Fundamental Research Funds(31920150038)for the Central Universities and XBMUYJRC(201406)
文摘In this article, we introduce and study the concept of n-Gorenstein injective （resp., n-Gorenstein flat） modules as a nontrivial generalization of Gorenstein injective （resp., Gorenstein flat） modules. We investigate the properties of these modules in various ways. For example, we show that the class of n-Gorenstein injective （resp., n -Gorenstein flat） modules is closed under direct sums and direct products for n ≥ 2. To this end, we first introduce and study the notions of n-injective modules and n-flat modules.
基金Supported by the Ph.D.Programs Foundation of Ministry of Education of China(200803570003)
文摘The definition of principally pseudo injectivity motivates us to generalize tae notion of injectivity, noted SP pseudo injectivity. The aim of this paper is to investigate characterizations and properties of SP pseudo injective modules. Various results are devel- oped, many extending known results. As applications, we give some characterizations on Noetherian rings, QI rings, quasi-Frobenius rings.
基金supported by the National Natural Science Foundation of China,(Nos.82272151,82204318)Liaoning Revitalization Talents Program(No.XLYC2203083)+2 种基金Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program(No.RC220389)Postdoctoral Fellowship Program of CPSF(No.GZC20231732)China Postdoctoral Science Foundation(Nos.2023TQ0222,2023MD744229).
文摘Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differences between single types of modification modules,neglecting the impact of steric-hindrance effect caused by chemical structure.Herein,single-tailed modification module with low-steric-hindrance effect and two-tailed modification module with high-steric-hindrance effect were selected to construct paclitaxel prodrugs(P-LA_(C18)and P-BAC18),and the in-depth insights of the sterichindrance effect on prodrug nanoassemblies were explored.Notably,the size stability of the two-tailed prodrugs was enhanced due to improved intermolecular interactions and steric hindrance.Single-tailed prodrug nanoassemblies were more susceptible to attack by redox agents,showing faster drug release and stronger antitumor efficacy,but with poorer safety.In contrast,two-tailed prodrug nanoassemblies exhibited significant advantages in terms of pharmacokinetics,tumor accumulation and safety due to the good size stability,thus ensuring equivalent antitumor efficacy at tolerance dose.These findings highlighted the critical role of steric-hindrance effect of the modification module in regulating the structureactivity relationship of prodrug nanoassemblies and proposed new perspectives into the precise design of self-assembled prodrugs for high-performance cancer therapeutics.
文摘With the rapid development of the new energy automotive industry,the enhancement of lithium battery performance and production efficiency has become critical.This article explores the application of artificial intelligence technology in the lithium battery module PACK line,analyzing how it optimizes the production process and improves production efficiency,and predicts future development trends.The PACK line is an important link in battery manufacturing,involving complex processes such as cell sorting,welding,assembly and testing.The application of AI technology in image recognition,data analysis and predictive maintenance provides new solutions for the intelligent upgrading of the PACK line.This article describes the process of the PACK line in detail,analyzes the challenges under current technological levels,and reviews the application cases of AI technology in the manufacturing industry.The study aims to provide theoretical and practical guidance for the intelligent development of lithium battery module PACK lines,discussing the integration of AI technology,its actual performance,technical challenges,and solutions.It is expected that AI technology will play a greater role in the PACK line,and future research will focus on improving the adaptability of models,developing efficient algorithms,and further integrating into the production line.
基金supported by the National Key Research and Development Program of China(2021YFD2200505)the National Natural Science Foundation of China(32071849)。
文摘Monocot root systems comprise a large number of lateral roots to allow them to survive and colonize land.Auxin signaling pathways centered on Aux/IAA play a crucial role in lateral root development.However,in non-model monocot plants,the effects of Aux/IAA on lateral root initiation and number remain largely unknown.The present study transformed PheIAA17,a member of the Aux/IAA family of Moso bamboo,into rice and found that it significantly drove plants to produce lateral roots and improved the rooting rate.Quantitative experiments showed that PheIAA17 overexpression significantly affected the expression of ARF family members.Phylogenetic and promoter analyses indicate that PheARF3-2 belongs to class B ARF,and the promoter region contains auxin response elements.The results of yeast one-hybrid and dual-luciferase reporter assays confirmed that PheIAA17 bound specific fragments of the PheARF3-2 promoter to repress its transcriptional activity.Y2H and BiFC assay have shown that PheIAA17 and PheIAA30-3 could physically interact in vitro and in vivo.Taken together,this study reports a new molecular module centered on PheIAA17,which directs plants to alter root morphology through an increase in lateral roots.
文摘Modules enable students to engage with content at their own pace,fostering autonomy and deeper understanding.The modular approach ensures clarity in presenting objectives,instructions,and concepts,while having illustrations,activities,and assessments could enhance comprehension and retention.This paper was a developmental study on STS module for college students using the ADDIE Model(Analysis,Design,Development,Implementation,and Evaluation).Sampled 673 first-year students from Northwest Samar State University participated in the study,with 299 participating in a test try-out and 374 in the students’performance evaluation.Three expert evaluators with backgrounds in science,English,and psychology,each with over four years of experience,assessed the modules to ensure alignment with the study’s constructivist learning goals and instructional integrity.The findings revealed that both students and experts had rated the instructional module positively,indicating its effectiveness in facilitating learning and completing lessons.Key aspects such as the style of illustrations and written expressions,the usefulness of learning activities,and the guidance provided by illustrations and captions were especially well-received.The module was praised for its clear objectives,understandable instructions,and engaging tasks like trivia and puzzles.Expert evaluations highlighted relevance,simplicity,and balanced emphasis on topics in the module content.Furthermore,students in test group demonstrated significant improvement in performance,with post-test scores notably higher than pre-test scores,confirming the module’s effectiveness in enhancing learning outcomes.Consequently,this paper provides an opportunity to integrate science learning with initiatives aimed at promoting environmental preservation and driving social change.
基金supported by the National Natural Science Foundation of China (31371557 and 31571574)Wenzhou Basic Scientific Research Project (N20240009)。
文摘Transcription factors(TFs)play key roles in the regulatory network of leaf senescence.However,many nodes in this network remain unclear.To elucidate the mechanism of leaf senescence mediated by a rice TF,WRKY10,the expression of multiple senescence-related genes and physiological phenotypes were monitored in WRKY10-and VQ MOTIF-CONTAINING PROTEIN8(VQ8)-overexpressing plants and the wrky10 and vq8 mutants.Our results showed that WRKY10 positively regulates abscisic acid(ABA)-and dark-induced senescence(DIS)by directly regulating the expression of multiple senescence-related genes.The VQ8 protein,a repressor of WRKY10,negatively regulates WRKY10-mediated DIS.The WRKY10-VQ8 module fine-tunes the progression of DIS.ABA,methyl jasmonate,and H_(2)O_(2) accelerate WRKY10-mediated DIS,whereas ammonium nitrate and dithiothreitol delay WRKY10-mediated DIS.Further analysis revealed that WRKY10 and VQ8 interact with ABA RESPONSIVE ELEMENT BINDING FACTOR1(ABF1)or ABF2.VQ8 represses the transcriptional activity of ABF1 and ABF2.Overexpression of ABF1 or ABF2 accelerates ABA-and dark-induced senescence and H_(2)O_(2) accumulation in N.benthamiana leaves,and WRKY10 and VQ8 can inhibit either ABF1-or ABF2-induced cell necrosis.Taken together,WRKY10 integrates multiple senescence signals to establish an orderly progression of leaf senescence.The VQ8 protein acts as a brake on WRKY10-induced senescence and ABF1/2-induced cell death,preventing uncontrolled cell death.
文摘Current research focuses on the performance degradation of photovoltaic(PV)modules,examining both crystalline silicon(p-Si and m-Si)and thin-film technologies,including a-Si/μc-Si,HIT,CdTe and CIGS.These modules were operated outdoors in two distinct climatic zones in the United States(US)over a period of three years.The degradation analysis includes the study of various quantities,such as the decrease in peak power,the reduction in current and voltage,and the variation in the fill factor.The annual degradation rate(DR)of PV modules is obtained by a linear fit of the effective maximum power evolution over time.The results indicate that m-Si and p-Si modules experienced a slight decrease in performance,with DRs of−0.83%and−1.07%,respectively.Subsequently,the HIT module exhibited a DR of−1.75%,while CdTe and CIGS modules demonstrated DRs of−2.03%and−2.45%,respectively.The a-Si/μc-Si module showed the highest DR at−3.26%.Using the Single Diode Model(SDM),we monitored the temporal evolution of physical parameters as well as changes in the shape of the I-V and P-V curves over time.We found that the key points of the I-V curve degrade over time,as do the I-V and P-V characteristics between two days approximately 30 months apart.
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 Key R&D Program of China under grant no.2022YFB2703000in part by the Young Backbone Teachers Support Plan of BISTU under grant no.YBT202437+1 种基金in part by the R&D Program of Beijing Municipal Education Commission under grant no.KM202211232012in part by the Educational Innovation Program of BISTU under grant no.2025JGYB19。
文摘Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant attention.Compared with traditional encryption and blockchain technologies,PLA provides a more computationally efficient alternative to exploiting the properties of the wireless medium itself.Some existing PLA solutions rely on static mechanisms,which are insufficient to address the authentication challenges in fifth generation(5G)and beyond wireless networks.Additionally,with the massive increase in mobile device access,the communication security of the IoT is vulnerable to spoofing attacks.To overcome the above challenges,this paper proposes a lightweight deep convolutional neural network(CNN)equipped with squeeze and excitation module(SE module)in dynamic wireless environments,namely SE-ConvNet.To be more specific,a convolution factorization is developed to reduce the complexity of PLA models based on deep learning.Moreover,an SE module is designed in the deep CNN to enhance useful features andmaximize authentication accuracy.Compared with the existing solutions,the proposed SE-ConvNet enabled PLA scheme performs excellently in mobile and time-varying wireless environments while maintaining lower computational complexity.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance.The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules.This enables accurate determination of the optimal timing for postfailure corrective maintenance.To optimize the maintenance strategy,the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate.The model considers multiple cost factors,including inspection costs,preventive maintenance costs,restorative maintenance costs,and penalty costs associated with delayed fault detection.Through this optimization framework,the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions.Comparative analysis demonstrates that the twostage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models.When evaluated against traditional maintenance approaches,including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies,the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components.The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization,leading to enhanced power generation performance.These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance.
基金Supported by National Natural Science Foundation of China(Grant No.52332013)。
文摘The intelligent vehicle corner module system,which integrates four-wheel independent drive,independent steering,independent braking and active suspension,can accurately and efficiently perform vehicle driving tasks and is the best carrier of intelligent vehicles.Nevertheless,too many angle/torque control inputs make control difficult and non-real-time.In this paper,a hierarchical real-time motion control framework for corner module configuration intelligent electric vehicles is proposed.In the trajectory planning module,an improved driving risk field is designed to describe the surrounding environment’s driving risk.Combined with the kinematic vehicle-road model,model predictive control(MPC)method,spline curve method,the local reference trajectory of safety,comfort and smoothness is planned in real time.The optimal steering angle is determined using MPC method in path tracking module.In the motion control module,a feedforward-feedback controller assigns the optimal steering angle to the front/rear axles,and an angle allocation controller distributes the target angles of the front/rear axles to four steered wheels.Finally,the PreScan-Simulink-CarSim joint simulation environment is established for conducting the human-in-the-loop emergency obstacle avoidance experiment.It took only 0.005 s for the hierarchical motion control system to determine its average solution time.This proves the effectiveness of the hierarchical motion control system.
基金supported by grants from the Biological Breeding-National Science and Technology Major Project(Grant No.2023ZD0406803)the National Key Research and Development Program(Grant No.2021YFD2200204)+2 种基金the National Science Foundation of China(Grant No.32071791 and 32271835)the Chongqing Youth Top Talent Program(Grant No.CQYC201905028)Fundamental Research Funds for the Central Universities(Grant No.XDJK2020B036).
文摘The secondary cell wall(SCW)is essential for plant growth and development in vascular plants,and its biosynthesis is mainly controlled by a complex hierarchical regulatory network involving multiple transcription factors(TFs)at the transcription level.However,TFs that specifically regulate secondary xylem have not been widely reported.In this study,we described a poplar KNOTTED1-like homeobox(KNOX)TF PtoKNAT3a1,which was mainly expressed in the expanding xylem cells of stems.PtoKNAT3a1 overexpression caused fiber SCW thickening and increased all measured SCW compositions by upregulating the expression of SCW-biosynthetic genes and-associated TFs,but had no effect on the vessels of SCW.The opposite phenotype was observed in the PtoKNAT3a1-knockout lines.Hence,we further demonstrated that Pto-KNAT3a1 could physically interact with the NAC master switches PtoWND2A/3A to enhance the expression of downstream MYB TFs and SCW biosynthetic genes(including PtoMYB20,PtoMYB21,PtoMYB90,PtoCoMT2,PtoGT43B and PtoCesA8).Meanwhile,the studies also demonstrate that the KNAT3 has functional differentiation in xylem development.Taken together,these data suggest that the KNAT3a1-WND2A/3A module positively regulates fiber development of the secondary xylem in poplar via the WND2A/3A-mediated hierarchical regulatory network,and supplies useful information for fiber SCW formation.The research not only deepens the understanding of the hierarchical regulatory network affecting SCW formation but also supplies genetic resources and molecular targets for plant fiber utilization.
基金supported financially by the grants from the JBGS[2021]002 project from the Jiangsu Governmentthe National Nature Science Foundation of China(32472095)+2 种基金the National Key Research and Development Program of China(2020YFE02029002)Collaborative Innovation Center for Modern Crop Production(CIC-MCP)to Xiquan Gaosupported in part by the high-performance computing platform of Bioinformatics Center,Nanjing Agricultural University。
文摘Gibberella stalk rot(GSR)caused by Fusarium graminearum is one of the most devastating diseases of maize,seriously impacting maize yield and quality,as well as the ability to use technology of mechanical harvesting.Environmental conditions including photoperiod affect crop disease resistance.However,the mechanism underlying photoperiod-regulated maize GSR resistance remains unexplored.We found in this study that GSR resistance is regulated by the ZmPIF4.1(Phytochrome-Interacting Factor4)-ZmPTI1c(Pto-Interacting 1)-ZmMYB31 module coupled with photoperiod.The functional analysis of zmpti1c mutant indicated that ZmPTI1c negatively regulates maize GSR resistance.Short day promoted the disease progression in both zmpti1c and wild-type plants.ZmPTI1c promoter contains multiple predicted cis-acting elements for light responses.Yeast one-hybrid assay(Y1H),Electrophoretic mobility shift analysis(EMSA),and Dual-luciferase(LUC)reporter assays demonstrated that ZmPIF4.1 binds to the G-box in ZmPTI1c promoter and activates its expression.Moreover,expression levels of ZmPIF4 and ZmPTI1c were significantly higher under short day than under long day.ZmPTI1c interacted with and phosphorylated ZmMYB31.GSR resistance in zmmyb31 mutant was significantly increased than in wild type,indicating that ZmMYB31 also negatively regulated GSR resistance.Furthermore,ZmMYB31 suppressed the transcriptional activation of ZmPTI1c by ZmPIF4.1.Overall,ZmPIF4.1-ZmPTI1c-ZmMYB31negatively regulates maize immunity to GSR,which is likely modulated by photoperiod.
