Transparent materials utilized as underwater optical windows are highly vulnerable to various forms of pollution or abrasion due to their intrinsic hydrophilic properties.This susceptibility is particularly pronounced...Transparent materials utilized as underwater optical windows are highly vulnerable to various forms of pollution or abrasion due to their intrinsic hydrophilic properties.This susceptibility is particularly pronounced in underwater environments where pollutants can impede the operation of these optical devices,significantly degrading or even compromising their optical properties.The glass catfish,known for its remarkable transparency in water,maintains surface cleanliness and clarity despite exposure to contaminants,impurities abrasion,and hydraulic pressure.Inspired by the glass catfish’s natural attributes,this study introduces a new solution named subaquatic abrasion-resistant and anti-fouling window(SAAW).Utilizing femtosecond laser ablation and electrodeposition,the SAAW is engineered by embedding fine metal bone structures into a transparent substrate and anti-fouling sliding layer,akin to the sturdy bones among catfish’s body.This approach significantly bolsters the window’s abrasion resistance and anti-fouling performance while maintaining high light transmittance.The sliding layer on the SAAW’s surface remarkably reduces the friction of various liquids,which is the reason that SAAW owns the great anti-fouling property.The SAAW demonstrates outstanding optical clarity even after enduring hundreds of sandpaper abrasions,attributing to the fine metal bone structures bearing all external forces and protecting the sliding layer of SAAW.Furthermore,it exhibits exceptional resistance to biological adhesion and underwater pressure.In a green algae environment,the window remains clean with minimal change in transmittance over one month.Moreover,it retains its wettability and anti-fouling properties when subjected to a depth of 30 m of underwater pressure for 30 d.Hence,the SAAW prepared by femtosecond laser ablation and electrodeposition presents a promising strategy for developing stable optical windows in liquid environments.展开更多
Based on the observational data from 60 short-period stations deployed in the Jishishan M6.2 earthquake epicenter and adjacent regions(Gansu Province,2023),this study inverted the near-surface S-wave velocity structur...Based on the observational data from 60 short-period stations deployed in the Jishishan M6.2 earthquake epicenter and adjacent regions(Gansu Province,2023),this study inverted the near-surface S-wave velocity structure through teleseismic receiver function analysis by using the amplitude of direct P-wave.The results reveal that the epicentral area(Liugou Township and surroundings)exhibits markedly low S-wave velocities of 400-600 m/s,with a mean value of(500±50)m/s.In contrast,intermountain basins-Guanting Basin and Dahejia Basin-demonstrate significantly elevated velocities,exceeding the epicentral zone by 100-300 m/s,with values concentrated at 600-900 m/s.Notably,localized areas such as Jintian Village and Caotan Village maintain stable S-wave velocities of(700±30)m/s.The western margin tectonic belt of Jishishan displays distinctive velocity differentiation:A pronounced velocity gradient zone along the 35.8°N latitude boundary separates northern areas(<550 m/s)from southern regions(>750 m/s).These findings demonstrate significant spatial heterogeneity in shallow S-wave velocity structures,primarily controlled by three factors:(1)topographic-geomorphic units,(2)stratigraphic lithological contrasts,and(3)anthropogenic modifications.The persistent low-velocity anomalies(<600 m/s)in the epicentral zone and northern Yellow River T2 terrace likely correlate with Quaternary unconsolidated sediments,enhanced groundwater circulation,and bedrock weathering.These results provide critical geophysical constraints for understanding both the seismogenic environment of the Jishishan earthquake and its damage distribution patterns.Furthermore,they establish a foundational framework for regional seismic intensity evaluation,site amplification analysis,and secondary hazard risk assessment.展开更多
With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation wind...With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.展开更多
The Sichuan-Yunnan Block is located on the southeastern margin of the Qinghai-Xizang Plateau and has frequent seismic activity on the western border,posing a potential threat to human society and economic development....The Sichuan-Yunnan Block is located on the southeastern margin of the Qinghai-Xizang Plateau and has frequent seismic activity on the western border,posing a potential threat to human society and economic development.Therefore,it is important to understand its geological evolution,assess earthquake risks,and formulate scientific and reasonable disaster prevention and mitigation strategies.Using 23 months of continuous ambient noise records from 81 seismic stations,we obtained 1248 phasevelocity dispersion curves of the fundamental Rayleigh wave at 5–50 s.The three-dimensional(3D)S-wave velocity structure in the northwestern Sichuan-Yunnan Block was obtained by pure-path and depth inversion.The results show that three lowvelocity anomalous bands were distributed nearly north-to-south(N-S)at depths of 10–35 km.The overall shape of the lowvelocity channel gradually shifted from southeast to southwest because of the influence of the Panzhihua high-velocity blocks.The low-velocity strip consists of three branches,with the first branch extending southwest from the northern part of the Lancangjiang Fault.The second branch is distributed in the N-S direction and is blocked by two high-velocity bodies near the Longpan-Qiaohou and Honghe faults.The third branch crosses the research area from N-S and gradually extends from southeast to southwest and from shallow to deep.The three low-velocity anomaly distribution areas are likely the most severely deformed areas of the collision between the Qinghai-Xizang Plateau and Yangtze Block.The results provide a more detailed understanding of the deep structure of the western boundary of the Sichuan-Yunnan Block crustal low-velocity anomalies and reliable geophysical evidence for the morphology and continuity of crustal flows.展开更多
The Anninghe–Zemuhe Fault and the Xiaojiang Fault are critical active faults along the middle-eastern boundary of the South Chuan–Dian Block. Many researchers have identified these faults as potential strong-earthqu...The Anninghe–Zemuhe Fault and the Xiaojiang Fault are critical active faults along the middle-eastern boundary of the South Chuan–Dian Block. Many researchers have identified these faults as potential strong-earthquake risk zones. In this study, we leveraged a dense seismic array to investigate the high-resolution shallow crust shear wave velocity(Vs) structure beneath the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone, one of the most complex parts of the eastern boundary of the South Chuan–Dian Block. We analyzed the distribution of microseismic events detected between November 2022 and February 2023 based on the fine-scale Vs model obtained. The microseismicity in the study region was clustered into three groups, all spatially related to major faults in this region. These microseismic events indicate near-vertical fault planes, consistent with the fault geometry revealed by other researchers.Moreover, these microseismic events are influenced by the impoundment of the downstream Baihetan Reservoir and the complex tectonic stress near the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone. The depths of these microseismic events are shallower in the junction zone, whereas moving south along the Xiaojiang Fault Zone, the microseismic events become deeper.Additionally, we compared our fine-scale local Vs model with velocity models obtained by other researchers and found that our model offers greater detail in characterizing subsurface heterogeneity while demonstrating improved reliability in delineating fault systems.展开更多
The shear wave(S-wave)velocity is a critical rock elastic parameter in shale reservoirs,especially for evaluating shale fracability.To effectively supplement S-wave velocity under the condition of no actual measuremen...The shear wave(S-wave)velocity is a critical rock elastic parameter in shale reservoirs,especially for evaluating shale fracability.To effectively supplement S-wave velocity under the condition of no actual measurement data,this paper proposes a physically-data driven method for the S-wave velocity prediction in shale reservoirs based on the class activation mapping(CAM)technique combined with a physically constrained two-dimensional Convolutional Neural Network(2D-CNN).High-sensitivity log curves related to S-wave velocity are selected as the basis from the data sensitivity analysis.Then,we establish a petrophysical model of complex multi-mineral components based on the petrophysical properties of porous medium and the Biot-Gassmann equation.This model can help reduce the dispersion effect and constrain the 2D-CNN.In deep learning,the 2D-CNN model is optimized using the Adam,and the class activation maps(CAMs)are obtained by replacing the fully connected layer with the global average pooling(GAP)layer,resulting in explainable results.The model is then applied to wells A,B1,and B2 in the southern Songliao Basin,China and compared with the unconstrained model and the petrophysical model.The results show higher prediction accuracy and generalization ability,as evidenced by correlation coefficients and relative errors of 0.98 and 2.14%,0.97 and 2.35%,0.96 and 2.89%in the three test wells,respectively.Finally,we present the defined C-factor as a means of evaluating the extent of concern regarding CAMs in regression problems.When the results of the petrophysical model are added to the 2D feature maps,the C-factor values are significantly increased,indicating that the focus of 2D-CNN can be significantly enhanced by incorporating the petrophysical model,thereby imposing physical constraints on the 2D-CNN.In addition,we establish the SHAP model,and the results of the petrophysical model have the highest average SHAP values across the three test wells.This helps to assist in proving the importance of constraints.展开更多
Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally...Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O_(3) pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.展开更多
With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant c...With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant challenges to information security.These techniques embed hidden information into speech streams,making detection increasingly difficult,particularly under conditions of low embedding rates and short speech durations.Existing steganalysis methods often struggle to balance detection accuracy and computational efficiency due to their limited ability to effectively capture both temporal and spatial features of speech signals.To address these challenges,this paper proposes an Efficient Sliding Window Analysis Network(E-SWAN),a novel deep learning model specifically designed for real-time speech steganalysis.E-SWAN integrates two core modules:the LSTM Temporal Feature Miner(LTFM)and the Convolutional Key Feature Miner(CKFM).LTFM captures long-range temporal dependencies using Long Short-Term Memory networks,while CKFM identifies local spatial variations caused by steganographic embedding through convolutional operations.These modules operate within a sliding window framework,enabling efficient extraction of temporal and spatial features.Experimental results on the Chinese CNV and PMS datasets demonstrate the superior performance of E-SWAN.Under conditions of a ten-second sample duration and an embedding rate of 10%,E-SWAN achieves a detection accuracy of 62.09%on the PMS dataset,surpassing existing methods by 4.57%,and an accuracy of 82.28%on the CNV dataset,outperforming state-of-the-art methods by 7.29%.These findings validate the robustness and efficiency of E-SWAN under low embedding rates and short durations,offering a promising solution for real-time VoIP steganalysis.This work provides significant contributions to enhancing information security in digital communications.展开更多
In this paper,an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check(SC-LDPC)codes.For the conventional sliding window decoder,the message retention mechanism causes u...In this paper,an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check(SC-LDPC)codes.For the conventional sliding window decoder,the message retention mechanism causes unreliable messages along the edges of belief propagation(BP)decoding in the current window to be kept for subsequent window decoding.To improve the reliability of the retained messages during the window transition,a reliable termination method is embedded,where the retained messages undergo more reliable parity checks.Additionally,decoding failure is unavoidable and even causes error propagation when the number of errors exceeds the error-correcting capability of the window.To mitigate this problem,a channel value reuse mechanism is designed,where the received channel values are utilized to reinitialize the window.Furthermore,considering the complexity and performance of decoding,a feasible sliding optimized window decoding(SOWD)scheme is introduced.Finally,simulation results confirm the superior performance of the proposed SOWD scheme in both the waterfall and error floor regions.This work has great potential in the applications of wireless optical communication and fiber optic communication.展开更多
Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security...Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.展开更多
Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories...Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.展开更多
Regulating the freedom and distribution of H_(2)O molecules has become the decisive factor in enlarging the electrochemical stability window(ESW)of aqueous electrolytes.Compared with the water in a bulk electrolyte,H_...Regulating the freedom and distribution of H_(2)O molecules has become the decisive factor in enlarging the electrochemical stability window(ESW)of aqueous electrolytes.Compared with the water in a bulk electrolyte,H_(2)O molecules at the electrode-electrolyte interface tend to directly split under bias potential.Therefore,the composition and properties of the interfacial microenvironment are the crux for optimizing ESW.Herein,we developed a heterogel electrolyte with wide ESW(4.88 V)and satisfactory ionic conductivity(4.4 mS/cm)inspired by the bicontinuous architecture and surfactant self-assembly behavior in the ionic liquid microemulsion-based template.This electrolyte was capable of expanding the ESW through the dynamic oil/water/electrode interface ternary structure,which enriched the oil phase and assembled the hydrophobic surfactant tails at the interface to prevent H_(2)O molecules from approaching the electrode surface.Moreover,the surfactant Tween 20 and polymer network effectively suppressed the activity of H_(2)O molecules through H-bond interactions,which was beneficial in expanding the operating voltage range and improving the temperature tolerance.The prepared gel electrolyte demonstrated unparalleled adaptability in various aqueous lithium-based energy storage devices.Notably,the lithium-ion capacitor showed an extended operating voltage of 2.2 V and could provide a high power density of 1350.36 W/kg at an energy density of 6 Wh/kg.It maintained normal power output even in the challenging harsh environment,which enabled 11,000 uninterrupted charge-discharge cycles at 0℃.This work focuses on the regulation of the interfacial microdomain and the restriction of the degree of freedom of H_(2)O molecules to boost the ESW of aqueous electrolytes,providing a promising strategy for the advancement of energy storage technologies.展开更多
In photolithography,shortening the exposure wavelength from ultraviolet to extreme ultraviolet(EUV,13.5 nm)and soft X-ray region in terms of beyond EUV(BEUV,6.X nm)and water window X-ray(WWX,2.2–4.4 nm)is expected to...In photolithography,shortening the exposure wavelength from ultraviolet to extreme ultraviolet(EUV,13.5 nm)and soft X-ray region in terms of beyond EUV(BEUV,6.X nm)and water window X-ray(WWX,2.2–4.4 nm)is expected to further miniaturize the technology node down to sub-5 nm level.However,the absorption ability of molecules in these ranges,especially WWX region,is unknown,which should be very important for the utilization of energy.Herein,the molar absorption cross sections of different elements at 2.4 nm of WWX were firstly calculated and compared with the wavelengths of 13.5 nm and 6.7 nm.Based on the absorption cross sections in these ranges and density estimation results from the density-functional theory calculation,the linear absorption coefficients of typical resist materials,including metal-oxy clusters,organic small molecules,polymers,and photoacid generators(PAGs),are evaluated.The analysis suggests that the Zn cluster has higher absorption in BEUV,whereas the Sn cluster has higher absorption in WWX.Doping PAGs with high EUV absorption atoms improves chemically amplified photoresist(CAR)polymer absorption performance.However,for WWX,it is necessary to introduce an absorption layer containing high WWX absorption elements such as Zr,Sn,and Hf to increase the WWX absorption.展开更多
基金supported by the National Science Foundation of China under Grant Nos(Nos.12127806,62175195)the International Joint Research Laboratory for Micro/Nano Manufacturing and Measurement Technologies。
文摘Transparent materials utilized as underwater optical windows are highly vulnerable to various forms of pollution or abrasion due to their intrinsic hydrophilic properties.This susceptibility is particularly pronounced in underwater environments where pollutants can impede the operation of these optical devices,significantly degrading or even compromising their optical properties.The glass catfish,known for its remarkable transparency in water,maintains surface cleanliness and clarity despite exposure to contaminants,impurities abrasion,and hydraulic pressure.Inspired by the glass catfish’s natural attributes,this study introduces a new solution named subaquatic abrasion-resistant and anti-fouling window(SAAW).Utilizing femtosecond laser ablation and electrodeposition,the SAAW is engineered by embedding fine metal bone structures into a transparent substrate and anti-fouling sliding layer,akin to the sturdy bones among catfish’s body.This approach significantly bolsters the window’s abrasion resistance and anti-fouling performance while maintaining high light transmittance.The sliding layer on the SAAW’s surface remarkably reduces the friction of various liquids,which is the reason that SAAW owns the great anti-fouling property.The SAAW demonstrates outstanding optical clarity even after enduring hundreds of sandpaper abrasions,attributing to the fine metal bone structures bearing all external forces and protecting the sliding layer of SAAW.Furthermore,it exhibits exceptional resistance to biological adhesion and underwater pressure.In a green algae environment,the window remains clean with minimal change in transmittance over one month.Moreover,it retains its wettability and anti-fouling properties when subjected to a depth of 30 m of underwater pressure for 30 d.Hence,the SAAW prepared by femtosecond laser ablation and electrodeposition presents a promising strategy for developing stable optical windows in liquid environments.
基金project is supported in part by Broadband Seismic 3D Array Detection(PhaseⅠ),Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(Grant No.2024ZD1000300)National Natural Science Foundation of China(42204061)Gansu Jishishan 6.2 magnitude earthquake scientific investigation(DQJB23Y45)program。
文摘Based on the observational data from 60 short-period stations deployed in the Jishishan M6.2 earthquake epicenter and adjacent regions(Gansu Province,2023),this study inverted the near-surface S-wave velocity structure through teleseismic receiver function analysis by using the amplitude of direct P-wave.The results reveal that the epicentral area(Liugou Township and surroundings)exhibits markedly low S-wave velocities of 400-600 m/s,with a mean value of(500±50)m/s.In contrast,intermountain basins-Guanting Basin and Dahejia Basin-demonstrate significantly elevated velocities,exceeding the epicentral zone by 100-300 m/s,with values concentrated at 600-900 m/s.Notably,localized areas such as Jintian Village and Caotan Village maintain stable S-wave velocities of(700±30)m/s.The western margin tectonic belt of Jishishan displays distinctive velocity differentiation:A pronounced velocity gradient zone along the 35.8°N latitude boundary separates northern areas(<550 m/s)from southern regions(>750 m/s).These findings demonstrate significant spatial heterogeneity in shallow S-wave velocity structures,primarily controlled by three factors:(1)topographic-geomorphic units,(2)stratigraphic lithological contrasts,and(3)anthropogenic modifications.The persistent low-velocity anomalies(<600 m/s)in the epicentral zone and northern Yellow River T2 terrace likely correlate with Quaternary unconsolidated sediments,enhanced groundwater circulation,and bedrock weathering.These results provide critical geophysical constraints for understanding both the seismogenic environment of the Jishishan earthquake and its damage distribution patterns.Furthermore,they establish a foundational framework for regional seismic intensity evaluation,site amplification analysis,and secondary hazard risk assessment.
文摘With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.
基金support from the National Natural Science Foundation of China(No.42474081)Basic Research Business of the Institute of Geophysics,China Earthquake Administration(Nos.DQJB 22R29 and DQJB19B30)Basic Research Business Special Project of the Earthquake Prediction Institute of the China Earthquake Administration(No.CEAIEF20220204).
文摘The Sichuan-Yunnan Block is located on the southeastern margin of the Qinghai-Xizang Plateau and has frequent seismic activity on the western border,posing a potential threat to human society and economic development.Therefore,it is important to understand its geological evolution,assess earthquake risks,and formulate scientific and reasonable disaster prevention and mitigation strategies.Using 23 months of continuous ambient noise records from 81 seismic stations,we obtained 1248 phasevelocity dispersion curves of the fundamental Rayleigh wave at 5–50 s.The three-dimensional(3D)S-wave velocity structure in the northwestern Sichuan-Yunnan Block was obtained by pure-path and depth inversion.The results show that three lowvelocity anomalous bands were distributed nearly north-to-south(N-S)at depths of 10–35 km.The overall shape of the lowvelocity channel gradually shifted from southeast to southwest because of the influence of the Panzhihua high-velocity blocks.The low-velocity strip consists of three branches,with the first branch extending southwest from the northern part of the Lancangjiang Fault.The second branch is distributed in the N-S direction and is blocked by two high-velocity bodies near the Longpan-Qiaohou and Honghe faults.The third branch crosses the research area from N-S and gradually extends from southeast to southwest and from shallow to deep.The three low-velocity anomaly distribution areas are likely the most severely deformed areas of the collision between the Qinghai-Xizang Plateau and Yangtze Block.The results provide a more detailed understanding of the deep structure of the western boundary of the Sichuan-Yunnan Block crustal low-velocity anomalies and reliable geophysical evidence for the morphology and continuity of crustal flows.
基金funded by the National Key R&D Program of China (Grant No. 2021YFC3000704)the National Natural Science Foundation of China (Grant No. 42125401)the Central Public-interest Scientific Institution Basal Research Fund (Grant No. CEAIEF20240401)。
文摘The Anninghe–Zemuhe Fault and the Xiaojiang Fault are critical active faults along the middle-eastern boundary of the South Chuan–Dian Block. Many researchers have identified these faults as potential strong-earthquake risk zones. In this study, we leveraged a dense seismic array to investigate the high-resolution shallow crust shear wave velocity(Vs) structure beneath the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone, one of the most complex parts of the eastern boundary of the South Chuan–Dian Block. We analyzed the distribution of microseismic events detected between November 2022 and February 2023 based on the fine-scale Vs model obtained. The microseismicity in the study region was clustered into three groups, all spatially related to major faults in this region. These microseismic events indicate near-vertical fault planes, consistent with the fault geometry revealed by other researchers.Moreover, these microseismic events are influenced by the impoundment of the downstream Baihetan Reservoir and the complex tectonic stress near the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone. The depths of these microseismic events are shallower in the junction zone, whereas moving south along the Xiaojiang Fault Zone, the microseismic events become deeper.Additionally, we compared our fine-scale local Vs model with velocity models obtained by other researchers and found that our model offers greater detail in characterizing subsurface heterogeneity while demonstrating improved reliability in delineating fault systems.
基金supported by the National Natural Science Foundation of China(Nos.42374150,42374152)Natural Science Foundation of Shandong Province(ZR2020MD050).
文摘The shear wave(S-wave)velocity is a critical rock elastic parameter in shale reservoirs,especially for evaluating shale fracability.To effectively supplement S-wave velocity under the condition of no actual measurement data,this paper proposes a physically-data driven method for the S-wave velocity prediction in shale reservoirs based on the class activation mapping(CAM)technique combined with a physically constrained two-dimensional Convolutional Neural Network(2D-CNN).High-sensitivity log curves related to S-wave velocity are selected as the basis from the data sensitivity analysis.Then,we establish a petrophysical model of complex multi-mineral components based on the petrophysical properties of porous medium and the Biot-Gassmann equation.This model can help reduce the dispersion effect and constrain the 2D-CNN.In deep learning,the 2D-CNN model is optimized using the Adam,and the class activation maps(CAMs)are obtained by replacing the fully connected layer with the global average pooling(GAP)layer,resulting in explainable results.The model is then applied to wells A,B1,and B2 in the southern Songliao Basin,China and compared with the unconstrained model and the petrophysical model.The results show higher prediction accuracy and generalization ability,as evidenced by correlation coefficients and relative errors of 0.98 and 2.14%,0.97 and 2.35%,0.96 and 2.89%in the three test wells,respectively.Finally,we present the defined C-factor as a means of evaluating the extent of concern regarding CAMs in regression problems.When the results of the petrophysical model are added to the 2D feature maps,the C-factor values are significantly increased,indicating that the focus of 2D-CNN can be significantly enhanced by incorporating the petrophysical model,thereby imposing physical constraints on the 2D-CNN.In addition,we establish the SHAP model,and the results of the petrophysical model have the highest average SHAP values across the three test wells.This helps to assist in proving the importance of constraints.
基金supported by the Natural Science Foundation of Henan Province[grant number:242300420115]Key Scientific Research Projects in Universities of Henan Province[grant number:23A330006].
文摘Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O_(3) pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.
基金supported in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LQ20F020004in part by the National College Student Innovation and Research Training Program under Grant 202313283002.
文摘With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant challenges to information security.These techniques embed hidden information into speech streams,making detection increasingly difficult,particularly under conditions of low embedding rates and short speech durations.Existing steganalysis methods often struggle to balance detection accuracy and computational efficiency due to their limited ability to effectively capture both temporal and spatial features of speech signals.To address these challenges,this paper proposes an Efficient Sliding Window Analysis Network(E-SWAN),a novel deep learning model specifically designed for real-time speech steganalysis.E-SWAN integrates two core modules:the LSTM Temporal Feature Miner(LTFM)and the Convolutional Key Feature Miner(CKFM).LTFM captures long-range temporal dependencies using Long Short-Term Memory networks,while CKFM identifies local spatial variations caused by steganographic embedding through convolutional operations.These modules operate within a sliding window framework,enabling efficient extraction of temporal and spatial features.Experimental results on the Chinese CNV and PMS datasets demonstrate the superior performance of E-SWAN.Under conditions of a ten-second sample duration and an embedding rate of 10%,E-SWAN achieves a detection accuracy of 62.09%on the PMS dataset,surpassing existing methods by 4.57%,and an accuracy of 82.28%on the CNV dataset,outperforming state-of-the-art methods by 7.29%.These findings validate the robustness and efficiency of E-SWAN under low embedding rates and short durations,offering a promising solution for real-time VoIP steganalysis.This work provides significant contributions to enhancing information security in digital communications.
基金supported by the National Natural Science Foundation of China (No.62275193)。
文摘In this paper,an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check(SC-LDPC)codes.For the conventional sliding window decoder,the message retention mechanism causes unreliable messages along the edges of belief propagation(BP)decoding in the current window to be kept for subsequent window decoding.To improve the reliability of the retained messages during the window transition,a reliable termination method is embedded,where the retained messages undergo more reliable parity checks.Additionally,decoding failure is unavoidable and even causes error propagation when the number of errors exceeds the error-correcting capability of the window.To mitigate this problem,a channel value reuse mechanism is designed,where the received channel values are utilized to reinitialize the window.Furthermore,considering the complexity and performance of decoding,a feasible sliding optimized window decoding(SOWD)scheme is introduced.Finally,simulation results confirm the superior performance of the proposed SOWD scheme in both the waterfall and error floor regions.This work has great potential in the applications of wireless optical communication and fiber optic communication.
基金supported by the National Undergraduate Innovation and Entrepreneurship Training Program of China(Project No.202510559076)at Jinan University,a nationwide initiative administered by the Ministry of Educationthe National Natural Science Foundation of China(NSFC)under Grant No.62172189.
文摘Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.
基金supported by the National Natural Science Foundation of China(32371028,32300822,U24A20373,and 82071177)the Shanghai Rising-Star Program(24QA2704800)+2 种基金the Shanghai Jiao Tong University 2030 InitiativeShanghai Municipal Health Commission(202340046)the Fund for Excellent Young Scholars of Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine.
文摘Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.
基金supported by the National Natural Science Foundation of China(Grant Nos.22032003 and 22072073)。
文摘Regulating the freedom and distribution of H_(2)O molecules has become the decisive factor in enlarging the electrochemical stability window(ESW)of aqueous electrolytes.Compared with the water in a bulk electrolyte,H_(2)O molecules at the electrode-electrolyte interface tend to directly split under bias potential.Therefore,the composition and properties of the interfacial microenvironment are the crux for optimizing ESW.Herein,we developed a heterogel electrolyte with wide ESW(4.88 V)and satisfactory ionic conductivity(4.4 mS/cm)inspired by the bicontinuous architecture and surfactant self-assembly behavior in the ionic liquid microemulsion-based template.This electrolyte was capable of expanding the ESW through the dynamic oil/water/electrode interface ternary structure,which enriched the oil phase and assembled the hydrophobic surfactant tails at the interface to prevent H_(2)O molecules from approaching the electrode surface.Moreover,the surfactant Tween 20 and polymer network effectively suppressed the activity of H_(2)O molecules through H-bond interactions,which was beneficial in expanding the operating voltage range and improving the temperature tolerance.The prepared gel electrolyte demonstrated unparalleled adaptability in various aqueous lithium-based energy storage devices.Notably,the lithium-ion capacitor showed an extended operating voltage of 2.2 V and could provide a high power density of 1350.36 W/kg at an energy density of 6 Wh/kg.It maintained normal power output even in the challenging harsh environment,which enabled 11,000 uninterrupted charge-discharge cycles at 0℃.This work focuses on the regulation of the interfacial microdomain and the restriction of the degree of freedom of H_(2)O molecules to boost the ESW of aqueous electrolytes,providing a promising strategy for the advancement of energy storage technologies.
基金supported by the National Natural Science Foundation of China(22090011,22378052)the Fundamental Research Funds for China Central Universities(DUT22LAB608 and DUT20RC(3)030)+1 种基金Liaoning Binhai Laboratory(LBLB-2023-03)Key R&D Program of Shandong Province(2021CXGC010308).
文摘In photolithography,shortening the exposure wavelength from ultraviolet to extreme ultraviolet(EUV,13.5 nm)and soft X-ray region in terms of beyond EUV(BEUV,6.X nm)and water window X-ray(WWX,2.2–4.4 nm)is expected to further miniaturize the technology node down to sub-5 nm level.However,the absorption ability of molecules in these ranges,especially WWX region,is unknown,which should be very important for the utilization of energy.Herein,the molar absorption cross sections of different elements at 2.4 nm of WWX were firstly calculated and compared with the wavelengths of 13.5 nm and 6.7 nm.Based on the absorption cross sections in these ranges and density estimation results from the density-functional theory calculation,the linear absorption coefficients of typical resist materials,including metal-oxy clusters,organic small molecules,polymers,and photoacid generators(PAGs),are evaluated.The analysis suggests that the Zn cluster has higher absorption in BEUV,whereas the Sn cluster has higher absorption in WWX.Doping PAGs with high EUV absorption atoms improves chemically amplified photoresist(CAR)polymer absorption performance.However,for WWX,it is necessary to introduce an absorption layer containing high WWX absorption elements such as Zr,Sn,and Hf to increase the WWX absorption.
