In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses...In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses,some properties and some equivalent characterizations of G_(C)-X-injective modules are investigated,and we also show that the triple(■,cores■,■)is a weak co-AB-context.As an application,two complete cotorsion pairs and a new model structure in Mod S are given.展开更多
Mango is a plant with high economic value in the agricultural industry;thus,it is necessary to maximize the productivity performance of the mango plant,which can be done by implementing artificial intelligence.In this...Mango is a plant with high economic value in the agricultural industry;thus,it is necessary to maximize the productivity performance of the mango plant,which can be done by implementing artificial intelligence.In this study,a lightweight object detection model will be developed that can detect mango plant conditions based on disease potential,so that it becomes an early detection warning system that has an impact on increasing agricultural productivity.The proposed lightweight model integrates YOLOv7-Tiny and the proposed modules,namely the C2S module.The C2S module consists of three sub-modules such as the convolutional block attention module(CBAM),the coordinate attention(CA)module,and the squeeze-and-excitation(SE)module.The dataset is constructed by eight classes,including seven classes of disease conditions and one class of health conditions.The experimental result shows that the proposed lightweight model has the optimal results,which increase by 13.15% of mAP50 compared to the original model YOLOv7-Tiny.While the mAP50:95 also achieved the highest results compared to other models,including YOLOv3-Tiny,YOLOv4-Tiny,YOLOv5,and YOLOv7-Tiny.The advantage of the proposed lightweightmodel is the adaptability that supports it in constrained environments,such as edge computing systems.This proposedmodel can support a robust,precise,and convenient precision agriculture system for the user.展开更多
Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefo...Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefore,a hybrid model(WM-ResNet50)integrating data enhancement,a deep convolutional neural network(CNN),and convolutional block attention modules(CBAM)was proposed.Firstly,an MS system was established at the Xieqiao coal mine in Anhui Province,China.MS waveforms and injection parameters were acquired during grouting.Secondly,signals were categorized based on time-frequency characteristics to build a dataset,which was divided into training,validation,and test sets at a ratio of 4:1:1.Subsequently,the performance of WM-ResNet50 was evaluated based on indices such as individual precision,total accuracy,recall,and loss function.The results indicated that WMResNet50 achieved an average recognition accuracy of 94.38%,surpassing that of a simple CNN(90.04%),ResNet18(91.72%),and ResNet50(92.48%).Finally,WM-ResNet50 was applied to monitor the whole process at laboratory tests and field cases.Both results affirmed the feasibility and effectiveness of MS inversion in predicting actual slurry diffusion ranges within deep rock layers.By comparison,it was revealed that the MS sources classified by WM-ResNet50 matched grouting records well.A solution to address insufficient diffusion under long-borehole grouting has been proposed.WM-ResNet50′s accuracy was validated through in-situ coring and XRD analysis for cement-based hydration products.This study provides a beneficial reference for similar rock signal processing and in-field grouting practices.展开更多
In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this pape...In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.展开更多
WiFi-based human activity recognition(HAR)provides a non-intrusive approach for ubiquitous monitoring;however,achieving both high accuracy and robustness simultaneously remains a significant challenge.This paper propo...WiFi-based human activity recognition(HAR)provides a non-intrusive approach for ubiquitous monitoring;however,achieving both high accuracy and robustness simultaneously remains a significant challenge.This paper proposes a Convolutional Neural Network with Enhanced Convolutional Block Attention Module(CNN-ECBAM)framework.The approach systematically converts raw Channel State Information(CSI)into pseudo-color images,effectively preserving essential signal characteristics for deep neural network processing.The core innovation is an Enhanced Convolutional Block Attention Module(ECBAM),tailored to CSI data characteristics,which integrates Efficient Channel Attention(ECA)and Multi-Scale Spatial Attention(MSSA).By employing learnable adaptive fusion weights,it achieves dynamic synergy between channel and spatial features,enabling the network to capture highly discriminative spatiotemporal patterns.The ECBAM module is integrated into a unified Convolutional Neural Network(CNN)to form the overall CNN-ECBAM model.Experimental results on the UT-HAR and NTU-Fi_HAR datasets demonstrate that CNN-ECBAM achieves competitive performance in recognition accuracy and outperforms mainstream baseline models.Specifically,it attains 99.20%accuracy on UT-HAR(surpassing ResNet-18 at 98.60%)and achieves 100%accuracy on NTU-Fi_HAR(exceeding GAF-CNN at 99.62%).These results validate the effectiveness of the proposed method for high-precision and reliable WiFi-based HAR.展开更多
To shield electronics from complicated electromagnetic environments caused by wireless electromagnetic waves,achieving elaborately structural manufacturing while not sacrificing electromagnetic interference shielding ...To shield electronics from complicated electromagnetic environments caused by wireless electromagnetic waves,achieving elaborately structural manufacturing while not sacrificing electromagnetic interference shielding performances remains crucial challenges.Herein,we propose a hierarchical manufacturing method that combines the use of 3D printing shear flow field and layer-by-layer assembly for fabricating the structurally customizable and multifunctional polylactic acid@graphene nanoparticle(PLA@GNs)materials.The dynamic behavior of polymer fluids is firstly explored via computational fluid dynamic simulation,and a Weissenberg number is employed to quantitatively analyze the disordered-to-ordered structural evolution of molecular chains and nanoparticles,allowing to tailor the micro-scale ordered structures.Subsequently,the macro-scale 3D architectures of PLA@GNs modules are fabricated by layer-by-layer assembly.Owing to the aligned GNs,the shielding performance reaches 41.2 d B,simultaneously accompanied by a directional thermal conductivity of 3.2 W m^(-1)K^(-1).Moreover,the potential application of 3D-printed shielding modules in specific civilian frequency bands such as 4G(1800–2100 MHz),Bluetooth(2402–2480 MHz),and 5G(3300–3800 MHz)is fully demonstrated.Overall,this work not only establishes a universal methodology about 3D printing shear flow field-driven orientation of two-dimensional nanoparticles within polymer fluids,but also gives a scientific method for advanced manufacturing of the next-generation electromagnetic functional modules for smart electronics.展开更多
[Background]High harmonic cavities are widely used in electron storage rings to lengthen thebunch,lower the bunch peak current,thereby reducing the IBS effect,enhancing the Touschek lifetime,as well asproviding Landau...[Background]High harmonic cavities are widely used in electron storage rings to lengthen thebunch,lower the bunch peak current,thereby reducing the IBS effect,enhancing the Touschek lifetime,as well asproviding Landau damping,which is particularly important for storage rings operating with ultra-low emittance or atlow beam energy.[Purpose]To further increase the bunch length without additional hardware costs,the phasemodulation in a dual-RF system is considered.[Methods]In this paper,turn-by-turn simulations incorporating randomsynchrotron radiation excitation are conducted,and a brief analysis is presented to explain the bunch lengtheningmechanism.[Results]Simulation results reveal that the peak current can be further reduced,thereby mitigating IBSeffects and enhancing the Touschek lifetime.Although the energy spread increases,which tends to reduce thebrightness of higher-harmonic radiation from the undulator,the brightness of the fundamental harmonic can,in fact,beimproved.展开更多
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
Grifola frondosa(Maitake)is traditionally valued for its health benefits,with polysaccharides being key bioactive components.This paper investigates a specific subfraction,Fraction D(GFP-D),evaluating its clinical eff...Grifola frondosa(Maitake)is traditionally valued for its health benefits,with polysaccharides being key bioactive components.This paper investigates a specific subfraction,Fraction D(GFP-D),evaluating its clinical effects and mechanisms in immune enhancement,adjunctive anti-tumor activity,and regulation of glucose/lipid metabolism.Three clinical trials were conducted.In an immune study,120 healthy volunteers(CD4+T cell count 500–1000 cells/μL)received 150 mg/day GFP-D for 8 weeks,resulting in significant increases in CD4+T cells(from 632±95 to 812±108 cells/μL,28.5%increase,within the physiological activation range),CD4+/CD8+ratio,NK cell activity,IL-2,and IFN-γ(all P<0.001 vs.placebo).An anti-tumor study with 80 advanced cancer patients(stratified by age,tumor stage,and histotype)showed that adding 1000 mg/day GFP-D to chemotherapy improved objective response rate(52.5%vs.30.0%,P=0.036,95%CI:1.02–3.87),one-year progression-free survival(55.8%vs.33.3%,P=0.022),and preserved immune parameters versus chemotherapy alone.A metabolic study in 90 type 2 diabetes patients found that 400 mg/day GFP-D for 12 weeks significantly lowered fasting glucose,HbA1c,total cholesterol,triglycerides,and LDL-C,while raising HDL-C(from 1.0±0.2 to 1.2±0.2 mmol/L,20%increase,supported by increased AMPK phosphorylation).Mechanistically,immune enhancement involves macrophage/dendritic cell activation via Dectin-1/TLR4 receptors(confirmed by increased receptor expression and downstream signaling molecules),promoting cytokine-driven T/NK cell responses.Anti-tumor effects stem from immunomodulation,direct induction of cancer cell apoptosis(via mitochondrial/caspase pathways,verified by increased Bax/Bcl-2 ratio and caspase-3 activation),and angiogenesis inhibition by downregulating VEGF.Metabolic benefits are linked to AMPK pathway activation in liver/muscle(confirmed by increased p-AMPK/AMPK ratio),enhancing glucose uptake and inhibiting gluconeogenesis/lipogenesis,alongside modulation of gut microbiota(increased Bifidobacterium and Lactobacillus abundance).All trials reported no severe adverse events related to GFP-D;liver/kidney function parameters(ALT,AST,creatinine,urea nitrogen)remained within normal ranges throughout the intervention.Collectively,GFP-D emerges as a multi-functional bioactive agent with substantial therapeutic potential.展开更多
While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance re...While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance remains underexplored in field investigations.To evaluate the practical applicability of this emerging technique in adverse shallow sea channels,a field experiment was conducted using three communication modes:orthogonal frequency division multiplexing(OFDM),M-ary frequency-shift keying(MFSK),and direct sequence spread spectrum(DSSS)for reinforcement learning-driven adaptive modulation.Specifically,a Q-learning method is used to select the optimal modulation mode according to the channel quality quantified by signal-to-noise ratio,multipath spread length,and Doppler frequency offset.Experimental results demonstrate that the reinforcement learning-based adaptive modulation scheme outperformed fixed threshold detection in terms of total throughput and average bit error rate,surpassing conventional adaptive modulation strategies.展开更多
The escalating global issues of water scarcity and pollution emphasize the critical need for the rapid development of efficient and eco-friendly water treatment technologies.Photoelectrocatalytic technology has emerge...The escalating global issues of water scarcity and pollution emphasize the critical need for the rapid development of efficient and eco-friendly water treatment technologies.Photoelectrocatalytic technology has emerged as a promising solution for effectively degrading refractory organic pollutants in water under light conditions.This review delves into the advancements made in the field,focusing on strategies to enhance the generation of active species by modulating the micro-interface of the photoanode.Strategies,such as morphological control,element doping,introduction of surface oxygen vacancies,and construction of heterostructures,significantly improve the separation efficiency of photogenerated charges and the generation of active species,thereby boosting the efficiency of photoelectrocatalytic performance.Furthermore,the review explores the potential applications of photoelectrocatalytic technology in organic pollutant degradation in solutions.It also outlines the current challenges and future development directions.Despite its remarkable laboratory success,practical implementation of photoelectrocatalytic technology encounters obstacles related to stability,cost-effectiveness,and operational efficiency.Future investigations need to focus on optimizing the performance of photoelectrocatalytic materials and exploring strategies for upscaling their application in real water treatment scenarios.展开更多
Controlling film morphology remains an inherent challenge limiting the performance of all-smallmolecule organic solar cells(ASM-OSCs),primarily due to excessive donor-acceptor compatibility restricting further improve...Controlling film morphology remains an inherent challenge limiting the performance of all-smallmolecule organic solar cells(ASM-OSCs),primarily due to excessive donor-acceptor compatibility restricting further improvements.Here,we introduce a novel strategy employing rhodanine-based film-forming kinetic modulators-specifically tailored for the high-performance donor BTR-Clincluding 3-methylrhodanine(C1),3-ethylrhodanine(C2),3-buty lr hod a nine(C4),and 3-hexylrhodanine(C6).We demonstrate that the C2 modulator uniquely optimizes morphology by extending film-formation time and fine-tuning donor-acceptor miscibility,leading to enhanced molecular ordering,uniform vertical distributio n,and optimal phase sepa ration.This synergistic morphological control significantly boosts BTR-Cl crystallinity and facilitates efficient three-dimensional charge transport networks.Consequently,C2-treated BTR-Cl:N3 ASM-OSCs achieve an outstanding power conversion efficiency(PCE)of 17.12%,ranking among the highest reported for this system.Crucially,this work introduces a novel"donor-modulator structural matching"strategy,providing a powerful new avenue for controlling film-forming kinetics to realize high-performance ASM-OSCs.展开更多
AIM:To investigate the effects of different light intensities and various mydriatic and miotic drugs on pupil accommodation in guinea pigs.METHODS:Forty-two-week-old guinea pigs were randomly divided into four groups ...AIM:To investigate the effects of different light intensities and various mydriatic and miotic drugs on pupil accommodation in guinea pigs.METHODS:Forty-two-week-old guinea pigs were randomly divided into four groups to assess pupillary responses under varying light intensities(100,250,500 lx)and pharmacological interventions(1%atropine,1%cyclopentolate,1%tropicamide,or 2%pilocarpine).Baseline pupil size and eccentricity were recorded using a non-contact Python-based imaging system integrating edge detection and pixel-to-distance conversion.Direct illumination effects were measured at sequential time points,followed by drug administration and longitudinal tracking of pupillary changes.The protocol was repeated at 12wk of age for developmental comparisons.Postexperiment,enucleated eyes were analyzed to evaluate in vitro vs in vivo differences.RESULTS:Significant age-dependent differences in pupil dynamics were observed.Both 2-and 12-week-old guinea pigs exhibited marked pupil constriction under direct illumination(P<0.001),with decreased eccentricity post-constriction(P<0.001).Indirect illumination caused inconsistent pupil size changes(2-week:P=0.68;12-week:P=0.49).Pharmacologically,atropine,cyclopentolate,and tropicamide induced pupil dilation(P<0.001),whereas pilocarpine caused constriction(P<0.001).All drug groups showed reduced eccentricity(P<0.001).In vivo/in vitro comparisons revealed significant structural differences.CONCLUSION:This study investigates pupillary responses in developing guinea pigs,revealing a direct pupillary light reflex(PLR)with light intensity-dependent responses,while indirect PLR was undetectable.The differential effects of muscarinic modulators on pupillary responses underscore the critical role of cholinergic signaling in ocular accommodation,with age-related variations in sensitivity.Additionally,a novel non-contact measurement methodology achieved a precision of 0.01 mm for pupillary quantification,enhancing accuracy in ocular studies.展开更多
The suppression of ablative Rayleigh–Taylor instability(ARTI)by a spatially modulated laser in inertial confinement fusion(ICF)is studied through numerical simulations.The results show that in the acceleration phase ...The suppression of ablative Rayleigh–Taylor instability(ARTI)by a spatially modulated laser in inertial confinement fusion(ICF)is studied through numerical simulations.The results show that in the acceleration phase of ICF implosion,the growth of ARTI can be suppressed by using a short-wavelength spatially modulated laser.The ARTI growth rate decreases as the wavelength of the spatially modulated laser decreases,and ARTI is completely suppressed after a certain wavelength has been reached.A spatially uniform laser is introduced to keep the state of motion of the implosion fluid consistent,and it is found that the proportion of the spatially modulated laser required for complete suppression of ARTI decreases as the wavelength continues to decrease.We also optimize the spatial intensity distribution of the spatially modulated laser.In addition,as the duration of the spatially modulated laser decreases,the proportion required for completely suppressing ARTI increases,but the required energy decreases.When the perturbation wavenumber decreases,the wavelength of the spatially modulated laser required for complete suppression of ARTI becomes longer.In the case of multimode perturbation,ARTI can also be significantly suppressed by a spatially modulated laser,and the perturbation amplitude can be reduced to less than 10% of that without a spatially modulated laser.We believe that the conclusions drawn from our simulations can provide the basis for new approaches to control ARTI in ICF.展开更多
Peroxymonosulfate(PMS)-based advanced oxidation technology has been proven to be a viable option for the decontamination of organic pollutants from water bodies.Advanced catalyst design is essential to this technology...Peroxymonosulfate(PMS)-based advanced oxidation technology has been proven to be a viable option for the decontamination of organic pollutants from water bodies.Advanced catalyst design is essential to this technology.Herein,a vanadium-doped LaFeO_(3) perovskite(LFO-V)featuring asymmetric Fe-O-V sites was rationally designed.Thanks to orbital electron interaction between Fe and V atoms,the modified electronic structure elevated electron density near the Fermi energy level while reducing the energy barrier toward effective PMS activation.This facilitated concurrent PMS reduction at the Fe sites to generate SO_(4)^(·-)and·OH(57.7%),and PMS oxidation at V sites to produce ^(1)O_(2)(42.3%).The LFO-V/PMS system demonstrated excellent tetracycline(TC)degradation performance with a 2-fold enhancement in rate constant compared to that of pristine LFO.Further,the LFO-V maintained long-term stability,and the toxicity of degradation intermediates was evaluated through microbial metabolomics.This work establishes an effective route to regulate the PMS activation pathways through precise electronic structure modulation,advancing the rational design of advanced Fenton-like catalysts.展开更多
The photovoltaic performance of metal halide perovskite solar cells often respond divergently to environmental conditions during storage.In particular,light exposure can either enhance or degrade device efficiency,yet...The photovoltaic performance of metal halide perovskite solar cells often respond divergently to environmental conditions during storage.In particular,light exposure can either enhance or degrade device efficiency,yet the mechanisms underlying these antithetical behaviors are still under investigation.In this study,we explore the modulation of the open-circuit voltage(Voc)in triple-cation mixed-halide perovskite solar cells by systematically controlling storage environments.While light intensity exhibits minimal impact during storage,the spectral composition of illumination selectively enhances Voc comprising reversible and irreversible contributions.Structural characterization reveals that prolonged storage degrades the quality of perovskite crystals in the upper region of the perovskite layer,whereas light storage promotes the relaxation of microstrain at the buried interface with a p-type organic layer.This structural reorganization at the interface,accompanied by lattice expansion,accounts for suppressed nonradiative recombination and a corresponding increase in quasi-Fermi level splitting.Consequently,devices fabricated without chemical defect passivation achieve a power conversion efficiency of higher than 40%under indoor lighting conditions after preconditioned by continuous exposure to ambient light during storage.These findings highlight the critical role of controlled light exposure during storage not only in enhancing efficiency,but also in ensuring reproducibility of perovskite solar cell characterization.展开更多
Cannabidiol(CBD),the second most significant phytocannabinoid in the plant Cannabis sativa,which lacks potential as a drug of abuse(Viudez-Martinez et al.,2019),has gained widespread attention due to its anti-inflamma...Cannabidiol(CBD),the second most significant phytocannabinoid in the plant Cannabis sativa,which lacks potential as a drug of abuse(Viudez-Martinez et al.,2019),has gained widespread attention due to its anti-inflammatory,antioxidant,and antidepressant properties(Garci a-Gutierrez et al.,2020).Additionally,CBD exhibits neuroprotective properties,preserving neuronal viability and function by preventing or limiting cellular damage.Our team has demonstrated that CBD produces rapid antidepressant-like effects in a murine model of chronic mild stress,restoring hippocampal expression of brain-derived neurotrophic factor(BDNF).展开更多
文摘In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses,some properties and some equivalent characterizations of G_(C)-X-injective modules are investigated,and we also show that the triple(■,cores■,■)is a weak co-AB-context.As an application,two complete cotorsion pairs and a new model structure in Mod S are given.
基金supported by National Science and Technology Council(NSTC)Taiwan,Grant No.NSTC 113-2221-E-167-023.
文摘Mango is a plant with high economic value in the agricultural industry;thus,it is necessary to maximize the productivity performance of the mango plant,which can be done by implementing artificial intelligence.In this study,a lightweight object detection model will be developed that can detect mango plant conditions based on disease potential,so that it becomes an early detection warning system that has an impact on increasing agricultural productivity.The proposed lightweight model integrates YOLOv7-Tiny and the proposed modules,namely the C2S module.The C2S module consists of three sub-modules such as the convolutional block attention module(CBAM),the coordinate attention(CA)module,and the squeeze-and-excitation(SE)module.The dataset is constructed by eight classes,including seven classes of disease conditions and one class of health conditions.The experimental result shows that the proposed lightweight model has the optimal results,which increase by 13.15% of mAP50 compared to the original model YOLOv7-Tiny.While the mAP50:95 also achieved the highest results compared to other models,including YOLOv3-Tiny,YOLOv4-Tiny,YOLOv5,and YOLOv7-Tiny.The advantage of the proposed lightweightmodel is the adaptability that supports it in constrained environments,such as edge computing systems.This proposedmodel can support a robust,precise,and convenient precision agriculture system for the user.
基金financial support from the National Natural Science Foundation of China(Nos.52204089,52374082)the Young Elite Scientists Sponsorship Program(No.2023QNRC001)by China Association for Science and Technology(CAST).
文摘Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefore,a hybrid model(WM-ResNet50)integrating data enhancement,a deep convolutional neural network(CNN),and convolutional block attention modules(CBAM)was proposed.Firstly,an MS system was established at the Xieqiao coal mine in Anhui Province,China.MS waveforms and injection parameters were acquired during grouting.Secondly,signals were categorized based on time-frequency characteristics to build a dataset,which was divided into training,validation,and test sets at a ratio of 4:1:1.Subsequently,the performance of WM-ResNet50 was evaluated based on indices such as individual precision,total accuracy,recall,and loss function.The results indicated that WMResNet50 achieved an average recognition accuracy of 94.38%,surpassing that of a simple CNN(90.04%),ResNet18(91.72%),and ResNet50(92.48%).Finally,WM-ResNet50 was applied to monitor the whole process at laboratory tests and field cases.Both results affirmed the feasibility and effectiveness of MS inversion in predicting actual slurry diffusion ranges within deep rock layers.By comparison,it was revealed that the MS sources classified by WM-ResNet50 matched grouting records well.A solution to address insufficient diffusion under long-borehole grouting has been proposed.WM-ResNet50′s accuracy was validated through in-situ coring and XRD analysis for cement-based hydration products.This study provides a beneficial reference for similar rock signal processing and in-field grouting practices.
基金supported by the Gansu Provincial Department of Education Industry Support Plan Project(2025CYZC-018).
文摘In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.
基金Supported by Anhui Provincial Engineering Research Center for Sports and Health Information Monitoring Technology(KF2023012)。
文摘WiFi-based human activity recognition(HAR)provides a non-intrusive approach for ubiquitous monitoring;however,achieving both high accuracy and robustness simultaneously remains a significant challenge.This paper proposes a Convolutional Neural Network with Enhanced Convolutional Block Attention Module(CNN-ECBAM)framework.The approach systematically converts raw Channel State Information(CSI)into pseudo-color images,effectively preserving essential signal characteristics for deep neural network processing.The core innovation is an Enhanced Convolutional Block Attention Module(ECBAM),tailored to CSI data characteristics,which integrates Efficient Channel Attention(ECA)and Multi-Scale Spatial Attention(MSSA).By employing learnable adaptive fusion weights,it achieves dynamic synergy between channel and spatial features,enabling the network to capture highly discriminative spatiotemporal patterns.The ECBAM module is integrated into a unified Convolutional Neural Network(CNN)to form the overall CNN-ECBAM model.Experimental results on the UT-HAR and NTU-Fi_HAR datasets demonstrate that CNN-ECBAM achieves competitive performance in recognition accuracy and outperforms mainstream baseline models.Specifically,it attains 99.20%accuracy on UT-HAR(surpassing ResNet-18 at 98.60%)and achieves 100%accuracy on NTU-Fi_HAR(exceeding GAF-CNN at 99.62%).These results validate the effectiveness of the proposed method for high-precision and reliable WiFi-based HAR.
基金financially supported by the National Natural Science Foundation of China(52303036)the Natural Science Foundation of Guangxi(2024GXNSFBA010123)+2 种基金the International Science&Technology Innovation Cooperation Project of Sichuan Province(2024YFHZ0232)the International Science&Technology Cooperation Project of Chengdu(2021-GH03-00009-HZ)the Opening Project of State Key Laboratory of Polymer Materials Engineering(Sichuan University)(Sklpme2023-3-18)。
文摘To shield electronics from complicated electromagnetic environments caused by wireless electromagnetic waves,achieving elaborately structural manufacturing while not sacrificing electromagnetic interference shielding performances remains crucial challenges.Herein,we propose a hierarchical manufacturing method that combines the use of 3D printing shear flow field and layer-by-layer assembly for fabricating the structurally customizable and multifunctional polylactic acid@graphene nanoparticle(PLA@GNs)materials.The dynamic behavior of polymer fluids is firstly explored via computational fluid dynamic simulation,and a Weissenberg number is employed to quantitatively analyze the disordered-to-ordered structural evolution of molecular chains and nanoparticles,allowing to tailor the micro-scale ordered structures.Subsequently,the macro-scale 3D architectures of PLA@GNs modules are fabricated by layer-by-layer assembly.Owing to the aligned GNs,the shielding performance reaches 41.2 d B,simultaneously accompanied by a directional thermal conductivity of 3.2 W m^(-1)K^(-1).Moreover,the potential application of 3D-printed shielding modules in specific civilian frequency bands such as 4G(1800–2100 MHz),Bluetooth(2402–2480 MHz),and 5G(3300–3800 MHz)is fully demonstrated.Overall,this work not only establishes a universal methodology about 3D printing shear flow field-driven orientation of two-dimensional nanoparticles within polymer fluids,but also gives a scientific method for advanced manufacturing of the next-generation electromagnetic functional modules for smart electronics.
基金National Natural Science Foundation of China(12405168)The Fundamental Research Funds for the Central Universities,China(2024CDJXY004)。
文摘[Background]High harmonic cavities are widely used in electron storage rings to lengthen thebunch,lower the bunch peak current,thereby reducing the IBS effect,enhancing the Touschek lifetime,as well asproviding Landau damping,which is particularly important for storage rings operating with ultra-low emittance or atlow beam energy.[Purpose]To further increase the bunch length without additional hardware costs,the phasemodulation in a dual-RF system is considered.[Methods]In this paper,turn-by-turn simulations incorporating randomsynchrotron radiation excitation are conducted,and a brief analysis is presented to explain the bunch lengtheningmechanism.[Results]Simulation results reveal that the peak current can be further reduced,thereby mitigating IBSeffects and enhancing the Touschek lifetime.Although the energy spread increases,which tends to reduce thebrightness of higher-harmonic radiation from the undulator,the brightness of the fundamental harmonic can,in fact,beimproved.
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Grifola frondosa(Maitake)is traditionally valued for its health benefits,with polysaccharides being key bioactive components.This paper investigates a specific subfraction,Fraction D(GFP-D),evaluating its clinical effects and mechanisms in immune enhancement,adjunctive anti-tumor activity,and regulation of glucose/lipid metabolism.Three clinical trials were conducted.In an immune study,120 healthy volunteers(CD4+T cell count 500–1000 cells/μL)received 150 mg/day GFP-D for 8 weeks,resulting in significant increases in CD4+T cells(from 632±95 to 812±108 cells/μL,28.5%increase,within the physiological activation range),CD4+/CD8+ratio,NK cell activity,IL-2,and IFN-γ(all P<0.001 vs.placebo).An anti-tumor study with 80 advanced cancer patients(stratified by age,tumor stage,and histotype)showed that adding 1000 mg/day GFP-D to chemotherapy improved objective response rate(52.5%vs.30.0%,P=0.036,95%CI:1.02–3.87),one-year progression-free survival(55.8%vs.33.3%,P=0.022),and preserved immune parameters versus chemotherapy alone.A metabolic study in 90 type 2 diabetes patients found that 400 mg/day GFP-D for 12 weeks significantly lowered fasting glucose,HbA1c,total cholesterol,triglycerides,and LDL-C,while raising HDL-C(from 1.0±0.2 to 1.2±0.2 mmol/L,20%increase,supported by increased AMPK phosphorylation).Mechanistically,immune enhancement involves macrophage/dendritic cell activation via Dectin-1/TLR4 receptors(confirmed by increased receptor expression and downstream signaling molecules),promoting cytokine-driven T/NK cell responses.Anti-tumor effects stem from immunomodulation,direct induction of cancer cell apoptosis(via mitochondrial/caspase pathways,verified by increased Bax/Bcl-2 ratio and caspase-3 activation),and angiogenesis inhibition by downregulating VEGF.Metabolic benefits are linked to AMPK pathway activation in liver/muscle(confirmed by increased p-AMPK/AMPK ratio),enhancing glucose uptake and inhibiting gluconeogenesis/lipogenesis,alongside modulation of gut microbiota(increased Bifidobacterium and Lactobacillus abundance).All trials reported no severe adverse events related to GFP-D;liver/kidney function parameters(ALT,AST,creatinine,urea nitrogen)remained within normal ranges throughout the intervention.Collectively,GFP-D emerges as a multi-functional bioactive agent with substantial therapeutic potential.
基金funding from the National Key Research and Development Program of China(No.2018YFE0110000)the National Natural Science Foundation of China(No.11274259,No.11574258)the Science and Technology Commission Foundation of Shanghai(21DZ1205500)in support of the present research.
文摘While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance remains underexplored in field investigations.To evaluate the practical applicability of this emerging technique in adverse shallow sea channels,a field experiment was conducted using three communication modes:orthogonal frequency division multiplexing(OFDM),M-ary frequency-shift keying(MFSK),and direct sequence spread spectrum(DSSS)for reinforcement learning-driven adaptive modulation.Specifically,a Q-learning method is used to select the optimal modulation mode according to the channel quality quantified by signal-to-noise ratio,multipath spread length,and Doppler frequency offset.Experimental results demonstrate that the reinforcement learning-based adaptive modulation scheme outperformed fixed threshold detection in terms of total throughput and average bit error rate,surpassing conventional adaptive modulation strategies.
基金financially supported by the National Natural Science Foundation of China (No.52100076)the Fundamental Research Funds for the Central Universities (No.2023MS064)。
文摘The escalating global issues of water scarcity and pollution emphasize the critical need for the rapid development of efficient and eco-friendly water treatment technologies.Photoelectrocatalytic technology has emerged as a promising solution for effectively degrading refractory organic pollutants in water under light conditions.This review delves into the advancements made in the field,focusing on strategies to enhance the generation of active species by modulating the micro-interface of the photoanode.Strategies,such as morphological control,element doping,introduction of surface oxygen vacancies,and construction of heterostructures,significantly improve the separation efficiency of photogenerated charges and the generation of active species,thereby boosting the efficiency of photoelectrocatalytic performance.Furthermore,the review explores the potential applications of photoelectrocatalytic technology in organic pollutant degradation in solutions.It also outlines the current challenges and future development directions.Despite its remarkable laboratory success,practical implementation of photoelectrocatalytic technology encounters obstacles related to stability,cost-effectiveness,and operational efficiency.Future investigations need to focus on optimizing the performance of photoelectrocatalytic materials and exploring strategies for upscaling their application in real water treatment scenarios.
基金supported by the National Natural Science Foundation of China(no.62304149 and no.52473318)the Zhejiang Province Natural Science Foundation of China(no.LY24E030008)+1 种基金the Key Research Program of Chinese Academy of Sciences(E4226101)supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIP)(2021R1A2C3004202)。
文摘Controlling film morphology remains an inherent challenge limiting the performance of all-smallmolecule organic solar cells(ASM-OSCs),primarily due to excessive donor-acceptor compatibility restricting further improvements.Here,we introduce a novel strategy employing rhodanine-based film-forming kinetic modulators-specifically tailored for the high-performance donor BTR-Clincluding 3-methylrhodanine(C1),3-ethylrhodanine(C2),3-buty lr hod a nine(C4),and 3-hexylrhodanine(C6).We demonstrate that the C2 modulator uniquely optimizes morphology by extending film-formation time and fine-tuning donor-acceptor miscibility,leading to enhanced molecular ordering,uniform vertical distributio n,and optimal phase sepa ration.This synergistic morphological control significantly boosts BTR-Cl crystallinity and facilitates efficient three-dimensional charge transport networks.Consequently,C2-treated BTR-Cl:N3 ASM-OSCs achieve an outstanding power conversion efficiency(PCE)of 17.12%,ranking among the highest reported for this system.Crucially,this work introduces a novel"donor-modulator structural matching"strategy,providing a powerful new avenue for controlling film-forming kinetics to realize high-performance ASM-OSCs.
文摘AIM:To investigate the effects of different light intensities and various mydriatic and miotic drugs on pupil accommodation in guinea pigs.METHODS:Forty-two-week-old guinea pigs were randomly divided into four groups to assess pupillary responses under varying light intensities(100,250,500 lx)and pharmacological interventions(1%atropine,1%cyclopentolate,1%tropicamide,or 2%pilocarpine).Baseline pupil size and eccentricity were recorded using a non-contact Python-based imaging system integrating edge detection and pixel-to-distance conversion.Direct illumination effects were measured at sequential time points,followed by drug administration and longitudinal tracking of pupillary changes.The protocol was repeated at 12wk of age for developmental comparisons.Postexperiment,enucleated eyes were analyzed to evaluate in vitro vs in vivo differences.RESULTS:Significant age-dependent differences in pupil dynamics were observed.Both 2-and 12-week-old guinea pigs exhibited marked pupil constriction under direct illumination(P<0.001),with decreased eccentricity post-constriction(P<0.001).Indirect illumination caused inconsistent pupil size changes(2-week:P=0.68;12-week:P=0.49).Pharmacologically,atropine,cyclopentolate,and tropicamide induced pupil dilation(P<0.001),whereas pilocarpine caused constriction(P<0.001).All drug groups showed reduced eccentricity(P<0.001).In vivo/in vitro comparisons revealed significant structural differences.CONCLUSION:This study investigates pupillary responses in developing guinea pigs,revealing a direct pupillary light reflex(PLR)with light intensity-dependent responses,while indirect PLR was undetectable.The differential effects of muscarinic modulators on pupillary responses underscore the critical role of cholinergic signaling in ocular accommodation,with age-related variations in sensitivity.Additionally,a novel non-contact measurement methodology achieved a precision of 0.01 mm for pupillary quantification,enhancing accuracy in ocular studies.
基金supported by the National Natural Science Foundation of China(NSFC)(Nos.12074399,12204500,and 12004403)the Key Projects of Intergovernmental International Scientific and Technological Innovation Cooperation(No.2021YFE0116700)+1 种基金the Shanghai Natural Science Foundation(No.20ZR1464400)the Shanghai Sailing Program(No.22YF1455300).
文摘The suppression of ablative Rayleigh–Taylor instability(ARTI)by a spatially modulated laser in inertial confinement fusion(ICF)is studied through numerical simulations.The results show that in the acceleration phase of ICF implosion,the growth of ARTI can be suppressed by using a short-wavelength spatially modulated laser.The ARTI growth rate decreases as the wavelength of the spatially modulated laser decreases,and ARTI is completely suppressed after a certain wavelength has been reached.A spatially uniform laser is introduced to keep the state of motion of the implosion fluid consistent,and it is found that the proportion of the spatially modulated laser required for complete suppression of ARTI decreases as the wavelength continues to decrease.We also optimize the spatial intensity distribution of the spatially modulated laser.In addition,as the duration of the spatially modulated laser decreases,the proportion required for completely suppressing ARTI increases,but the required energy decreases.When the perturbation wavenumber decreases,the wavelength of the spatially modulated laser required for complete suppression of ARTI becomes longer.In the case of multimode perturbation,ARTI can also be significantly suppressed by a spatially modulated laser,and the perturbation amplitude can be reduced to less than 10% of that without a spatially modulated laser.We believe that the conclusions drawn from our simulations can provide the basis for new approaches to control ARTI in ICF.
基金supported by the National Natural Science Foundation of China(Nos.W2412093 and 52170068)the Fundamental Research Funds for the Central Universities(No.DUT24RC(3)079).
文摘Peroxymonosulfate(PMS)-based advanced oxidation technology has been proven to be a viable option for the decontamination of organic pollutants from water bodies.Advanced catalyst design is essential to this technology.Herein,a vanadium-doped LaFeO_(3) perovskite(LFO-V)featuring asymmetric Fe-O-V sites was rationally designed.Thanks to orbital electron interaction between Fe and V atoms,the modified electronic structure elevated electron density near the Fermi energy level while reducing the energy barrier toward effective PMS activation.This facilitated concurrent PMS reduction at the Fe sites to generate SO_(4)^(·-)and·OH(57.7%),and PMS oxidation at V sites to produce ^(1)O_(2)(42.3%).The LFO-V/PMS system demonstrated excellent tetracycline(TC)degradation performance with a 2-fold enhancement in rate constant compared to that of pristine LFO.Further,the LFO-V maintained long-term stability,and the toxicity of degradation intermediates was evaluated through microbial metabolomics.This work establishes an effective route to regulate the PMS activation pathways through precise electronic structure modulation,advancing the rational design of advanced Fenton-like catalysts.
基金supported by a National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-NR076521,RS-2025-00519481)the Research Grant of Kwangwoon University in 2023.
文摘The photovoltaic performance of metal halide perovskite solar cells often respond divergently to environmental conditions during storage.In particular,light exposure can either enhance or degrade device efficiency,yet the mechanisms underlying these antithetical behaviors are still under investigation.In this study,we explore the modulation of the open-circuit voltage(Voc)in triple-cation mixed-halide perovskite solar cells by systematically controlling storage environments.While light intensity exhibits minimal impact during storage,the spectral composition of illumination selectively enhances Voc comprising reversible and irreversible contributions.Structural characterization reveals that prolonged storage degrades the quality of perovskite crystals in the upper region of the perovskite layer,whereas light storage promotes the relaxation of microstrain at the buried interface with a p-type organic layer.This structural reorganization at the interface,accompanied by lattice expansion,accounts for suppressed nonradiative recombination and a corresponding increase in quasi-Fermi level splitting.Consequently,devices fabricated without chemical defect passivation achieve a power conversion efficiency of higher than 40%under indoor lighting conditions after preconditioned by continuous exposure to ambient light during storage.These findings highlight the critical role of controlled light exposure during storage not only in enhancing efficiency,but also in ensuring reproducibility of perovskite solar cell characterization.
基金supported by Instituto de Salud CarlosⅢ,Spanish Ministry of Science and Innovation,grant number PI18/00576 to MSGG and JMRRed de Investigación en Atención Primaria de Adicciones,Instituto de Salud CarlosⅢ,Spanish Ministry of Science and Innovation,grant number RD21/0009/0008 and RD24/0003/0002+1 种基金Instituto de Investigación Sanitaria y Biomédica de Alicante(ISABIAL)to JMThe Instituto de Neurociencias is a“Centre of Excellence Severo Ochoa”(CEX2021-001165-S).
文摘Cannabidiol(CBD),the second most significant phytocannabinoid in the plant Cannabis sativa,which lacks potential as a drug of abuse(Viudez-Martinez et al.,2019),has gained widespread attention due to its anti-inflammatory,antioxidant,and antidepressant properties(Garci a-Gutierrez et al.,2020).Additionally,CBD exhibits neuroprotective properties,preserving neuronal viability and function by preventing or limiting cellular damage.Our team has demonstrated that CBD produces rapid antidepressant-like effects in a murine model of chronic mild stress,restoring hippocampal expression of brain-derived neurotrophic factor(BDNF).
