This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networ...This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networks.Unlike conventional Deep Reinforcement Learning(DRL)-based approaches for CW size adjustment,which often suffer from overestimation bias and limited exploration diversity,leading to suboptimal throughput and collision performance.Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions.First,SETL adopts a DDQN architecture(SETL-DDQN)to improve Q-value estimation accuracy and enhance training stability.Second,we incorporate a Gumbel distribution-driven exploration mechanism,forming SETL-DDQN(Gumbel),which employs the extreme value theory to promote diverse action selection,replacing the conventional-greedy exploration that undergoes early convergence to suboptimal solutions.Both models are evaluated through extensive simulations in static and time-varying IEEE 802.11 network scenarios.The results demonstrate that our approach consistently achieves higher throughput,lower collision rates,and improved adaptability,even under abrupt fluctuations in traffic load and network conditions.In particular,the Gumbel-based mechanism enhances the balance between exploration and exploitation,facilitating faster adaptation to varying congestion levels.These findings position Gumbel-enhanced DRL as an effective and robust solution for CW optimization in wireless networks,offering notable gains in efficiency and reliability over existing methods.展开更多
With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper pro...With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.展开更多
Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable devel...Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable development of society.Smart photovoltaic windows(SPWs)offer a promising platform for designing ESBs because they present the capability to regulate and harness solar energy.With frequent outbreaks of extreme weather all over the world,the achievement of exceptional energy-saving effect under different weather conditions is an inevitable trend for the development of ESBs but is hardly achieved via existing SPWs.Here,we substantially reduce the driving voltage of polymerdispersed liquid crystals(PDLCs)by 28.1%via molecular engineering while maintaining their high solar transmittance(T_(sol)=83.8%,transparent state)and solar modulating ability(ΔT_(sol)=80.5%).By the assembly of perovskite solar cell and a broadband thermal-managing unit encompassing the electrical-responsive PDLCs,transparent high-emissivity SiO_(2) passive radiation-cooling,and Ag low-emissivity layers possesses,we present a tri-band regulation and split-type SPW possessing superb energy-saving effect in all-season.The perovskite solar cell can produce the electric power to stimulate the electrical-responsive behavior of the PDLCs,endowing the SPWs zero-energy input solar energy regulating characteristic,and compensate the daily energy consumption needed for ESBs.Moreover,the scalable manufacturing technology holds a great potential for the real-world applications.展开更多
Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining...Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining technique that overcomes these issues by using impact to create strong bonds without melting the substrate materials.This study investigates the weldability of aluminum alloy Al-5754 with Al-7075 and MARS 380 steel,used in armouring solutions of defense systems,by the use of MPW.In this work,weldability windows are investigated by varying standoff distances between the coating material and its substrate(0.25-4.5 mm)and discharge energies(5-13 kJ)with both O-shape and U-shape inductors.Mechanical strength of the welded joints were assessed through single lap shear tests,identifying optimal welding parameters.Then,the velocity profiles of the flyer plates were measured using heterodyne velocimetry to understand the dynamics of the impact.Then,substructures assembled with the optimal welding conditions were subjected to ballistic testing using 7.62 mm×51 mm NATO and 9 mm×19 mm Parabellum munitions to evaluate the resilience of the welds under ballistic impact.The outcomes demonstrate that MPW effectively joins Al-5754 with both Al-7075 and MARS 380,producing robust welds capable of withstanding ballistic impacts under certain conditions.This research advances the application of MPW in lightweight ballistic protection of defense systems,contributing to the development of more resilient and lighter protective structures.展开更多
Objective:To observe the efficacy and safety of TCM syndrome differentiation-guided herbal intervention for patients with five constitutions during the high-risk window period of acute exacerbation of chronic obstruct...Objective:To observe the efficacy and safety of TCM syndrome differentiation-guided herbal intervention for patients with five constitutions during the high-risk window period of acute exacerbation of chronic obstructive pulmonary disease(AECOPD)based on TCM constitution theory.Methods:A total of 300 AECOPD patients in the high-risk window period(54-66 cases for each constitution)were randomly divided into two groups(150 cases each).The control group received fluticasone furoate/umeclidinium/vilanterol inhalation therapy,while the experimental group was additionally given constitution-specific TCM decoctions(e.g.,Erchen Decoction combined with Sanzi Yangqin Decoction for Phlegm-Dampness constitution).The treatment course was 8 weeks with a 6-month follow-up.CAT score,TCM syndrome score,pulmonary function,6-minute walking distance(6MWD),and levels of CRP and IL-6 were observed.Recurrence and safety indicators were recorded.Results:After treatment,all indicators improved significantly in both groups(p<0.05),with the experimental group showing superior improvements in CAT score,TCM syndrome score,FEV1,6MWD,and inflammatory indicators(p<0.01).The recurrence rate was lower in the experimental group during follow-up(p<0.05).No severe adverse reactions or abnormalities in liver/kidney function were observed in either group.Conclusion:TCM syndrome differentiation treatment guided by constitution theory can improve symptoms,quality of life,and pulmonary function,reduce inflammatory levels and recurrence rate in AECOPD patients during the high-risk window period,with good safety.展开更多
Backoff mechanism is a key component of contention-based medium access control（MAC） layer protocol.It has been shown that the backoff mechanism of IEEE 802.11 standard may be very inefficient especially when the net...Backoff mechanism is a key component of contention-based medium access control（MAC） layer protocol.It has been shown that the backoff mechanism of IEEE 802.11 standard may be very inefficient especially when the network is congested.Numbers of methods have been proposed to tune the contention window（CW） with the aim to achieve the optimal throughput in IEEE 802.11 WLANs.However,the mechanisms do not specifically address proper settings for the variable packet length influence and CW diverging problem.This paper proposes a novel four-way handshaking full-feedback backoff algorithm named adoptive contention window backoff（ACWB） to overcome these drawbacks.The performance of the proposed algorithm is investigated through analysis and simulation.Simulation results demonstrate that the ACWB algorithm provides a remarkable performance improvement in terms of short-term fairness,packet delay and delay jitter,while maintaining an optimal throughput close to the theoretical throughput limit of the IEEE 802.11 distributed coordination function（DCF） access scheme.展开更多
HomePlug AV (HPAV) is a standard developed by HomePlug Powerline Alliance (HPA) for power line communication. In HomePlug AV, it uses a technology named Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA)...HomePlug AV (HPAV) is a standard developed by HomePlug Powerline Alliance (HPA) for power line communication. In HomePlug AV, it uses a technology named Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) to reduce collision happened in network. However, when network nodes increase, the contention window number may not be wide enough. It will cause collision probability to increase. In this paper, we introduce a new idea of adaptive contention window which will produce suitable contention window under actual network environment. Our method only requires the information of CSMA/CA parameters. It means that one doesn’t need to correct the original CSMA/CA procedure but substitutes old parameters by the new ones. Simulation experiments conducted in the network simulator NS3 show that compared with HomePlug AV, our method promotes throughput significantly when the node number increases.展开更多
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
Convolutional neural network(CNN)with the encoder-decoder structure is popular in medical image segmentation due to its excellent local feature extraction ability but it faces limitations in capturing the global featu...Convolutional neural network(CNN)with the encoder-decoder structure is popular in medical image segmentation due to its excellent local feature extraction ability but it faces limitations in capturing the global feature.The transformer can extract the global information well but adapting it to small medical datasets is challenging and its computational complexity can be heavy.In this work,a serial and parallel network is proposed for the accurate 3D medical image segmentation by combining CNN and transformer and promoting feature interactions across various semantic levels.The core components of the proposed method include the cross window self-attention based transformer(CWST)and multi-scale local enhanced(MLE)modules.The CWST module enhances the global context understanding by partitioning 3D images into non-overlapping windows and calculating sparse global attention between windows.The MLE module selectively fuses features by computing the voxel attention between different branch features,and uses convolution to strengthen the dense local information.The experiments on the prostate,atrium,and pancreas MR/CT image datasets consistently demonstrate the advantage of the proposed method over six popular segmentation models in both qualitative evaluation and quantitative indexes such as dice similarity coefficient,Intersection over Union,95%Hausdorff distance and average symmetric surface distance.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
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
文摘This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networks.Unlike conventional Deep Reinforcement Learning(DRL)-based approaches for CW size adjustment,which often suffer from overestimation bias and limited exploration diversity,leading to suboptimal throughput and collision performance.Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions.First,SETL adopts a DDQN architecture(SETL-DDQN)to improve Q-value estimation accuracy and enhance training stability.Second,we incorporate a Gumbel distribution-driven exploration mechanism,forming SETL-DDQN(Gumbel),which employs the extreme value theory to promote diverse action selection,replacing the conventional-greedy exploration that undergoes early convergence to suboptimal solutions.Both models are evaluated through extensive simulations in static and time-varying IEEE 802.11 network scenarios.The results demonstrate that our approach consistently achieves higher throughput,lower collision rates,and improved adaptability,even under abrupt fluctuations in traffic load and network conditions.In particular,the Gumbel-based mechanism enhances the balance between exploration and exploitation,facilitating faster adaptation to varying congestion levels.These findings position Gumbel-enhanced DRL as an effective and robust solution for CW optimization in wireless networks,offering notable gains in efficiency and reliability over existing methods.
文摘With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.
基金supported by Natural Science Foundation of China(Grant No.52372076,52073081,52203322,5252200843)Ministry of Science and Technology of the People’s Republic of China(2023YFB3812800)Fundamental Research Funds for the Central Universities(FRF-TP-25-073)。
文摘Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable development of society.Smart photovoltaic windows(SPWs)offer a promising platform for designing ESBs because they present the capability to regulate and harness solar energy.With frequent outbreaks of extreme weather all over the world,the achievement of exceptional energy-saving effect under different weather conditions is an inevitable trend for the development of ESBs but is hardly achieved via existing SPWs.Here,we substantially reduce the driving voltage of polymerdispersed liquid crystals(PDLCs)by 28.1%via molecular engineering while maintaining their high solar transmittance(T_(sol)=83.8%,transparent state)and solar modulating ability(ΔT_(sol)=80.5%).By the assembly of perovskite solar cell and a broadband thermal-managing unit encompassing the electrical-responsive PDLCs,transparent high-emissivity SiO_(2) passive radiation-cooling,and Ag low-emissivity layers possesses,we present a tri-band regulation and split-type SPW possessing superb energy-saving effect in all-season.The perovskite solar cell can produce the electric power to stimulate the electrical-responsive behavior of the PDLCs,endowing the SPWs zero-energy input solar energy regulating characteristic,and compensate the daily energy consumption needed for ESBs.Moreover,the scalable manufacturing technology holds a great potential for the real-world applications.
基金funded on the one hand by Agence de l'Innovation de Défense(AID)grant reference number 2021650044on the other hand by Ecole Centrale de Nantes。
文摘Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining technique that overcomes these issues by using impact to create strong bonds without melting the substrate materials.This study investigates the weldability of aluminum alloy Al-5754 with Al-7075 and MARS 380 steel,used in armouring solutions of defense systems,by the use of MPW.In this work,weldability windows are investigated by varying standoff distances between the coating material and its substrate(0.25-4.5 mm)and discharge energies(5-13 kJ)with both O-shape and U-shape inductors.Mechanical strength of the welded joints were assessed through single lap shear tests,identifying optimal welding parameters.Then,the velocity profiles of the flyer plates were measured using heterodyne velocimetry to understand the dynamics of the impact.Then,substructures assembled with the optimal welding conditions were subjected to ballistic testing using 7.62 mm×51 mm NATO and 9 mm×19 mm Parabellum munitions to evaluate the resilience of the welds under ballistic impact.The outcomes demonstrate that MPW effectively joins Al-5754 with both Al-7075 and MARS 380,producing robust welds capable of withstanding ballistic impacts under certain conditions.This research advances the application of MPW in lightweight ballistic protection of defense systems,contributing to the development of more resilient and lighter protective structures.
基金Longquan Yi District Health Bureau Project(Project No.:WJKY2023009)。
文摘Objective:To observe the efficacy and safety of TCM syndrome differentiation-guided herbal intervention for patients with five constitutions during the high-risk window period of acute exacerbation of chronic obstructive pulmonary disease(AECOPD)based on TCM constitution theory.Methods:A total of 300 AECOPD patients in the high-risk window period(54-66 cases for each constitution)were randomly divided into two groups(150 cases each).The control group received fluticasone furoate/umeclidinium/vilanterol inhalation therapy,while the experimental group was additionally given constitution-specific TCM decoctions(e.g.,Erchen Decoction combined with Sanzi Yangqin Decoction for Phlegm-Dampness constitution).The treatment course was 8 weeks with a 6-month follow-up.CAT score,TCM syndrome score,pulmonary function,6-minute walking distance(6MWD),and levels of CRP and IL-6 were observed.Recurrence and safety indicators were recorded.Results:After treatment,all indicators improved significantly in both groups(p<0.05),with the experimental group showing superior improvements in CAT score,TCM syndrome score,FEV1,6MWD,and inflammatory indicators(p<0.01).The recurrence rate was lower in the experimental group during follow-up(p<0.05).No severe adverse reactions or abnormalities in liver/kidney function were observed in either group.Conclusion:TCM syndrome differentiation treatment guided by constitution theory can improve symptoms,quality of life,and pulmonary function,reduce inflammatory levels and recurrence rate in AECOPD patients during the high-risk window period,with good safety.
文摘Backoff mechanism is a key component of contention-based medium access control（MAC） layer protocol.It has been shown that the backoff mechanism of IEEE 802.11 standard may be very inefficient especially when the network is congested.Numbers of methods have been proposed to tune the contention window（CW） with the aim to achieve the optimal throughput in IEEE 802.11 WLANs.However,the mechanisms do not specifically address proper settings for the variable packet length influence and CW diverging problem.This paper proposes a novel four-way handshaking full-feedback backoff algorithm named adoptive contention window backoff（ACWB） to overcome these drawbacks.The performance of the proposed algorithm is investigated through analysis and simulation.Simulation results demonstrate that the ACWB algorithm provides a remarkable performance improvement in terms of short-term fairness,packet delay and delay jitter,while maintaining an optimal throughput close to the theoretical throughput limit of the IEEE 802.11 distributed coordination function（DCF） access scheme.
文摘HomePlug AV (HPAV) is a standard developed by HomePlug Powerline Alliance (HPA) for power line communication. In HomePlug AV, it uses a technology named Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) to reduce collision happened in network. However, when network nodes increase, the contention window number may not be wide enough. It will cause collision probability to increase. In this paper, we introduce a new idea of adaptive contention window which will produce suitable contention window under actual network environment. Our method only requires the information of CSMA/CA parameters. It means that one doesn’t need to correct the original CSMA/CA procedure but substitutes old parameters by the new ones. Simulation experiments conducted in the network simulator NS3 show that compared with HomePlug AV, our method promotes throughput significantly when the node number increases.
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National Key Research and Development Program of China,Grant/Award Number:2018YFE0206900China Postdoctoral Science Foundation,Grant/Award Number:2023M731204+2 种基金The Open Project of Key Laboratory for Quality Evaluation of Ultrasound Surgical Equipment of National Medical Products Administration,Grant/Award Number:SMDTKL-2023-1-01The Hubei Province Key Research and Development Project,Grant/Award Number:2023BCB007CAAI-Huawei MindSpore Open Fund。
文摘Convolutional neural network(CNN)with the encoder-decoder structure is popular in medical image segmentation due to its excellent local feature extraction ability but it faces limitations in capturing the global feature.The transformer can extract the global information well but adapting it to small medical datasets is challenging and its computational complexity can be heavy.In this work,a serial and parallel network is proposed for the accurate 3D medical image segmentation by combining CNN and transformer and promoting feature interactions across various semantic levels.The core components of the proposed method include the cross window self-attention based transformer(CWST)and multi-scale local enhanced(MLE)modules.The CWST module enhances the global context understanding by partitioning 3D images into non-overlapping windows and calculating sparse global attention between windows.The MLE module selectively fuses features by computing the voxel attention between different branch features,and uses convolution to strengthen the dense local information.The experiments on the prostate,atrium,and pancreas MR/CT image datasets consistently demonstrate the advantage of the proposed method over six popular segmentation models in both qualitative evaluation and quantitative indexes such as dice similarity coefficient,Intersection over Union,95%Hausdorff distance and average symmetric surface distance.
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.
