An Anaphe panda silk nanofibers / nets( NFN) membrane with attractive structures consisting of common electrospun nanofibers and two-dimensional( 2D) spider-web-like structured nano-nets were successfully fabricated v...An Anaphe panda silk nanofibers / nets( NFN) membrane with attractive structures consisting of common electrospun nanofibers and two-dimensional( 2D) spider-web-like structured nano-nets were successfully fabricated via electrospinning / netting technology. The unique structures of NFN membranes such as extremely small diameter( < 20 nm),high porosity,large specific surface area. and biocompatibility make this Anaphe panda silk NFN membrane a promising candidate for biomedical applications. In the present study, field emission scanning electron microscopy( FESEM) was used to investigate the influence of polymer solution and humidity on nano-nets coverage and morphology. The FE-SEM images revealed that nano-net coverage area increased with increase in concentration of solution while lowering the humidity increased the nano-nets formation. Moreover,the mechanical properties of the membrane were also tested and the result showed that the silk NFN membrane displayed a breaking stress of 3. 7 MPa and breaking strain of 13. 8%. For further structural elucidation, Fourier transform infrared spectroscopy( FT-IR) was used to analyze the structural conformation changes from random coil to β-sheet in the NFN membrane which was an important factor effecting the usability of membrane. Thus,the results above confirmed the feasibility of Anaphe panda NFN structures applicability in cell tissue culture and other biomedical applications.展开更多
To understand better the impact on mist net capture rates of the activity height of birds, light intensity, bird richness and abundance, we compared data from mist nets and point counts at the Jianfengling Forest Area...To understand better the impact on mist net capture rates of the activity height of birds, light intensity, bird richness and abundance, we compared data from mist nets and point counts at the Jianfengling Forest Area, Hainan Island. Mist-nets were operated for a total of 7135 net-hours. A total of 587 individuals of 45 bird species were captured. The total mean capture rate was 8.6 ± 10.4 per 100 net-hours. A total of 4932 individuals of 107 bird species were recorded by visual observation alone and 7616 individuals of 120 species were recorded in a visual and aural combination. The Grey-cheeked Fulvetta (Alcippe morrisonia) was the most abundant species, accounting for 38.7% of total captures, 27.9% of visual observations and 22.2% of visual + aural observations. The capture number was correlated with the number observed. Thirty-one species were more likely to be captured than observed. Canopy species, such as members of the Corvidae and Dicruridae, were seldom captured. For all ground feeding species, the capture number was greater than that of observation. Some cryptic species, such as the Lesser Wren Babbler (Napothera epilepidota), Spotnecked Babbler (Stachyris striolata) and Cuckoo Owl (Glaucidium cuculoides) also had a higher relative capture rate than that of observations. There was a significant relationship between light intensity and the number of birds captured.展开更多
Nettings are complex flexible structures used in various fisheries.Understanding the hydrodynamic characteristics,de-formation,and the flow field around nettings is important to design successful fishing gear.This stu...Nettings are complex flexible structures used in various fisheries.Understanding the hydrodynamic characteristics,de-formation,and the flow field around nettings is important to design successful fishing gear.This study investigated the hydrodynamic characteristics and deformation of five nettings made of polyethylene and nylon materials in different attack angles through numeri-cal simulation and physical model experiment.The numerical model was based on the one-way coupling between computational fluid dynamics(CFD)and large deflection nonlinear structural models.Navier-Stokes equations were solved using the finite volume ap-proach,the flow was described using the k-ωshear stress turbulent model,and the large deflection structural dynamic equation was derived using a finite element approach to understand the netting deformation and nodal displacement.The porous media model was chosen to model the nettings in the CFD solver.Numerical data were compared with the experimental results of the physical model to validate the numerical models.Results showed that the numerical data were compatible with the experimental data with an average relative error of 2.34%,3.40%,6.50%,and 5.80%in the normal drag coefficients,parallel drag coefficients,inclined drag coefficients,and inclined lift coefficients,respectively.The hydrodynamic forces of the polyethylene and nylon nettings decreased by approxi-mately 52.56%and 66.66%,respectively,with decreasing net solidity.The drag and lift coefficients of the nylon netting were appro-ximately 17.15%and 6.72%lower than those of the polyethylene netting.A spatial development of turbulent flow occurred around the netting because of the netting wake.However,the flow velocity reduction downstream from the netting in the wake region in-creased with increasing attack angle and net solidity.In addition,the deformation,stress,and strain on each netting increased with in-creasing solidity ratio.展开更多
Numerous studies have been undertaken to improve the viability, durability and suitability of materials and methods used for aquaculture enclosures. While many of the previous studies considered macro-deformation of n...Numerous studies have been undertaken to improve the viability, durability and suitability of materials and methods used for aquaculture enclosures. While many of the previous studies considered macro-deformation of nets, there is a paucity of information on netting micro-deformation. When aquaculture pens are towed, industry operators have observed the motion described as ＂baffling＂ – the transverse oscillation of the net planes parallel and near parallel to the flow. The difficulty to observe and assess baffling motion in a controlled experimental environment is to sufficiently reproduce netting boundary conditions and the flow environment experienced at sea. The focus of the present study was to develop and assess experimental methods for visualisation and quantification of these transverse oscillations. Four netrig configurations with varied boundary conditions and model-netting properties were tested in a flume tank. While the Reynolds number was not equivalent to full-scale, usage of the pliable and fine mesh model netting that enabled baffling to develop at low flow velocities was deemed to be of a larger relevance to this initial study. Baffling was observed in the testing frame that constrained the net sheet on the leading edge, similarly to a flag attachment onto a pole. Baffling motion increased the hydrodynamic drag of the net by 35%–58% when compared to the previously developed formula for taut net sheets aligned parallel to the flow. Furthermore, it was found that the drag due to baffling decreased with the increasing velocity over the studied Reynolds numbers（below 200）; and the drag coefficient was non-linear for Reynolds numbers below 120. It is hypothesised that baffling motion is initially propagated by vortex shedding of the netting twine which causes the netting to oscillate; there after the restoring force causes unstable pressure differences on each side of the netting which excites the amplitude of the netting oscillations.展开更多
This study evaluated the hydrodynamic forces produced by whole panels of hand-made(geometrically different)rope meshes typically found in midwater trawls.Experimental treatments included both knotted and knotless mesh...This study evaluated the hydrodynamic forces produced by whole panels of hand-made(geometrically different)rope meshes typically found in midwater trawls.Experimental treatments included both knotted and knotless meshes constructed of helix composite ropes,conventional braided nylon(PA)ropes,and twisted polyethylene(PE)ropes.Direct measurement of lift(L)and drag(D)forces were conducted using controlled flume tank experiments on panels oriented at 21°relative to the flow.For knotted netting,our results showed that the hydrodynamic forces(L and D)were statistically higher for helix ropes compared to conventional ropes of the same diameter.For knotless netting constructed of helix ropes,our primary finding is that the arrangement of helix ropes(S and Z lay)in individual meshes significantly affects the resulting D and Cd of whole netting panels.Arranging the mesh bars in the S-Z-S-Z lay pattern exhibited 29%and 32%lower drag(D)compared to S–S–S–S and S–S-Z-Z lay meshes,respectively.We also use computational fluid dynamics(CFD)to characterize the finescale flow-field around helix and conventional ropes.The resulting streamlines and pressure contours provide a functional explanation for the empirical measurements collected in the flume tank.These results can be useful in informing the design of midwater trawls.展开更多
Knotless polyethylene(PE)netting is widely used in fisheries because of its excellent hydrodynamic performance and low cost.Netting deformation and the surrounding flow field distribution play an important role in det...Knotless polyethylene(PE)netting is widely used in fisheries because of its excellent hydrodynamic performance and low cost.Netting deformation and the surrounding flow field distribution play an important role in determining the hydrodynamic characteristics of netting in moving water.In order to investigate the effect of solidity ratio and attack angle on drag,netting deformation,and flow field distribution through the netting,a fluid-structure interaction(FSI)model based on a one-way coupling combining the shear stress turbulent(SST)k-omega model and the large deformation nonlinear structural finite element model was evaluated.Our results showed the difference between the parallel and normal drag forces found in the present numerical model and experimental flume tank data were 9.17%and 11.58%,respectively.The mean relative error in the inclined hydrodynamic drag for different flow velocities and attack angles was 8.35%,6.69%,and 5.37%for the nettings 1,2,and 3,respectively.These results show that the present numerical simulation based on FSI one-way coupling can be used to examine hydrodynamic forces on netting.The flow simulation results show that there is a noticeable flow velocity decrease through the netting and a rather large velocity reduction region downstream from the netting for different attack angles.These results reveal the existence of turbulent flow due to the netting wake.It was found that the equivalent stress and total deformation increase as the flow velocity increases and solidity ratio decreases.展开更多
Math is the foundation of everything. The Chinese know this too well and have dominated international math competitions for years. So when the news came that U.S. high school students had won the first prize for a sec...Math is the foundation of everything. The Chinese know this too well and have dominated international math competitions for years. So when the news came that U.S. high school students had won the first prize for a second consecutive year at the Romanian Master of Mathematics 2019, it was no laughing matter.展开更多
With the increase of semiconductor integration density,in order to cope with the increase of wafer defect complexity and types,especially the low recognition accuracy of overlapping mixed defects and unknown wafer def...With the increase of semiconductor integration density,in order to cope with the increase of wafer defect complexity and types,especially the low recognition accuracy of overlapping mixed defects and unknown wafer defects,this study proposes a lightweight model for wafer defect detection called LightWMNet.First,using a hierarchical attention Encoder-Decoder architecture,the features of wafer defect pattern(WDP)are channel recalibrated to generate high-resolution fine-grained features and low-resolution coarse-grained features.Secondly,the backbone network incorporates two novel attention modules—feedforward spatial attention(FFSa)and feedforward channel attention(FFCa)—to amplify responses in critical defect regions and suppress noise from stochastic discrete pixels.These mechanisms synergistically enhance feature discriminability without introducing significant parametric overhead.Finally,the Dice loss function and the cross entropy loss function are combined to jointly evaluate the segmentation and classification accuracy of the model.Experimental results on the public mixed wafer defect dataset MixedWM38 show that the pixel accuracy(PA),intersection over union(IoU)and Dice coefficient of the proposed network reach 98.26%,94.83%and 97.22%,respectively.Without significantly increasing the computational complexity and size of the model,compared with the existing state-of-the-art(SOTA)model,the classification accuracy of lightWMNet in single defect,three mixed defects and four mixed defects is improved by 0.5%,0.25%and 0.89%respectively.Furthermore,we used transfer learning for the first time to evaluate the model's generalisation ability for unseen defect categories.The results showed that LightWMNet still has a certain recognition ability even in untrained wafer defects.展开更多
A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or l...A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.展开更多
Monge–Ampere equations(MAEs)are fully nonlinear second-order partial differential equations(PDEs),which are closely related to various fields including optimal transport(OT)theory,geometrical optics and affine geomet...Monge–Ampere equations(MAEs)are fully nonlinear second-order partial differential equations(PDEs),which are closely related to various fields including optimal transport(OT)theory,geometrical optics and affine geometry.Despite their significance,MAEs are extremely challenging to solve.Although some classical numerical approaches can solve MAEs,their computational efficiency deteriorates significantly on fine grids,with convergence often heavily dependent on the quality of initial estimate.Research on deep learning methods for solving MAEs is still in its early stages,which predominantly addresses simple formulations with basic Dirichlet boundary conditions.Here,we propose a deep learning method based on physicsdriven deep neural networks,enabling the solution of both simple and generalised MAEs with transport boundary conditions.In this method,we deal with two first-order sub-equations separated from MAE instead of solving the single MAE directly,which facilitates the imposition of transport boundary conditions and simplifies the training of neural networks.Moreover,we constrain the convexity of solution using the Lagrange multiplier method and maintain the optimisation process differentiable with bilinear interpolation.We provide three progressively complex examples ranging from a simple MAE with an analytical solution to a highly nonlinear variant arising in phase retrieval to validate the effectiveness of our method.For comparison,we benchmark against state-of-the-art deep learning approaches that have been systematically adapted to accommodate the specific requirements of each example.展开更多
Neutrophil extracellular traps(NETs)have emerged as key mediators of cardiovascular diseases(CVDs),linking innate immune activation to vascular injury,thrombosis,and maladaptive remodeling.This review synthesizes rece...Neutrophil extracellular traps(NETs)have emerged as key mediators of cardiovascular diseases(CVDs),linking innate immune activation to vascular injury,thrombosis,and maladaptive remodeling.This review synthesizes recent insights into the molecular and cellular pathways driving NET formation,including post-translational modifications,metabolic reprogramming,inflammasome signaling,and autophagy.It highlights the role of NETs in atherosclerosis,thrombosis,myocardial ischemia-reperfusion injury,and hypertension,emphasizing common control points such as peptidylarginine deiminase 4(PAD4)-dependent histone citrullination and nicotinamide adenine dinucleotide phosphate oxidases 2(NOX2)-mediated oxidative stress.Mechanistic interpretation of circulating biomarkers,includingmyeloperoxidase(MPO)-DNA complexes,citrullinated histoneH3,and cell-free DNA,provides a translational bridge between NET biology and patient stratification.Therapeutic strategies targeting NETs are examined through three main approaches:inhibition of NET initiation,enhancement of chromatin clearance,and neutralization of toxic extracellular components,with attention to both established and emerging interventions.In contrast to previous reviews,this study highlights the novelty of a mechano-therapeutic framework by providing a mechanistic roadmap linking NET formation pathways to therapeutic targeting in cardiovascular disease.Moving forward,integrating mechanistic information with biomarker discovery,precision profiling,and targeted therapies offers innovative strategies to reduce vascular inflammation and improve outcomes in cardiovascular disease.展开更多
基金National Basic Research Program of China(973 Program)(No.2012CB525005)National Natural Science Foundations of China(Nos.51173022,51273038,51322304)
文摘An Anaphe panda silk nanofibers / nets( NFN) membrane with attractive structures consisting of common electrospun nanofibers and two-dimensional( 2D) spider-web-like structured nano-nets were successfully fabricated via electrospinning / netting technology. The unique structures of NFN membranes such as extremely small diameter( < 20 nm),high porosity,large specific surface area. and biocompatibility make this Anaphe panda silk NFN membrane a promising candidate for biomedical applications. In the present study, field emission scanning electron microscopy( FESEM) was used to investigate the influence of polymer solution and humidity on nano-nets coverage and morphology. The FE-SEM images revealed that nano-net coverage area increased with increase in concentration of solution while lowering the humidity increased the nano-nets formation. Moreover,the mechanical properties of the membrane were also tested and the result showed that the silk NFN membrane displayed a breaking stress of 3. 7 MPa and breaking strain of 13. 8%. For further structural elucidation, Fourier transform infrared spectroscopy( FT-IR) was used to analyze the structural conformation changes from random coil to β-sheet in the NFN membrane which was an important factor effecting the usability of membrane. Thus,the results above confirmed the feasibility of Anaphe panda NFN structures applicability in cell tissue culture and other biomedical applications.
基金funded by the Kadoorie Farm and Botanical Garden and the Hong Kong Special Administrative Region,China
文摘To understand better the impact on mist net capture rates of the activity height of birds, light intensity, bird richness and abundance, we compared data from mist nets and point counts at the Jianfengling Forest Area, Hainan Island. Mist-nets were operated for a total of 7135 net-hours. A total of 587 individuals of 45 bird species were captured. The total mean capture rate was 8.6 ± 10.4 per 100 net-hours. A total of 4932 individuals of 107 bird species were recorded by visual observation alone and 7616 individuals of 120 species were recorded in a visual and aural combination. The Grey-cheeked Fulvetta (Alcippe morrisonia) was the most abundant species, accounting for 38.7% of total captures, 27.9% of visual observations and 22.2% of visual + aural observations. The capture number was correlated with the number observed. Thirty-one species were more likely to be captured than observed. Canopy species, such as members of the Corvidae and Dicruridae, were seldom captured. For all ground feeding species, the capture number was greater than that of observation. Some cryptic species, such as the Lesser Wren Babbler (Napothera epilepidota), Spotnecked Babbler (Stachyris striolata) and Cuckoo Owl (Glaucidium cuculoides) also had a higher relative capture rate than that of observations. There was a significant relationship between light intensity and the number of birds captured.
基金This study was financially sponsored by the National Natural Science Foundation of China(Nos.31902426,41806110)the Shanghai Sailing Program(No.19YF1419800)+1 种基金the National Key R&D Program of China(No.2019YFD 0901502)the Special Project for the Exploitation and Utilization of Antarctic Biological Resources of Ministry of Agriculture and Rural Affairs(No.D-8002-18-0097).
文摘Nettings are complex flexible structures used in various fisheries.Understanding the hydrodynamic characteristics,de-formation,and the flow field around nettings is important to design successful fishing gear.This study investigated the hydrodynamic characteristics and deformation of five nettings made of polyethylene and nylon materials in different attack angles through numeri-cal simulation and physical model experiment.The numerical model was based on the one-way coupling between computational fluid dynamics(CFD)and large deflection nonlinear structural models.Navier-Stokes equations were solved using the finite volume ap-proach,the flow was described using the k-ωshear stress turbulent model,and the large deflection structural dynamic equation was derived using a finite element approach to understand the netting deformation and nodal displacement.The porous media model was chosen to model the nettings in the CFD solver.Numerical data were compared with the experimental results of the physical model to validate the numerical models.Results showed that the numerical data were compatible with the experimental data with an average relative error of 2.34%,3.40%,6.50%,and 5.80%in the normal drag coefficients,parallel drag coefficients,inclined drag coefficients,and inclined lift coefficients,respectively.The hydrodynamic forces of the polyethylene and nylon nettings decreased by approxi-mately 52.56%and 66.66%,respectively,with decreasing net solidity.The drag and lift coefficients of the nylon netting were appro-ximately 17.15%and 6.72%lower than those of the polyethylene netting.A spatial development of turbulent flow occurred around the netting because of the netting wake.However,the flow velocity reduction downstream from the netting in the wake region in-creased with increasing attack angle and net solidity.In addition,the deformation,stress,and strain on each netting increased with in-creasing solidity ratio.
文摘Numerous studies have been undertaken to improve the viability, durability and suitability of materials and methods used for aquaculture enclosures. While many of the previous studies considered macro-deformation of nets, there is a paucity of information on netting micro-deformation. When aquaculture pens are towed, industry operators have observed the motion described as ＂baffling＂ – the transverse oscillation of the net planes parallel and near parallel to the flow. The difficulty to observe and assess baffling motion in a controlled experimental environment is to sufficiently reproduce netting boundary conditions and the flow environment experienced at sea. The focus of the present study was to develop and assess experimental methods for visualisation and quantification of these transverse oscillations. Four netrig configurations with varied boundary conditions and model-netting properties were tested in a flume tank. While the Reynolds number was not equivalent to full-scale, usage of the pliable and fine mesh model netting that enabled baffling to develop at low flow velocities was deemed to be of a larger relevance to this initial study. Baffling was observed in the testing frame that constrained the net sheet on the leading edge, similarly to a flag attachment onto a pole. Baffling motion increased the hydrodynamic drag of the net by 35%–58% when compared to the previously developed formula for taut net sheets aligned parallel to the flow. Furthermore, it was found that the drag due to baffling decreased with the increasing velocity over the studied Reynolds numbers（below 200）; and the drag coefficient was non-linear for Reynolds numbers below 120. It is hypothesised that baffling motion is initially propagated by vortex shedding of the netting twine which causes the netting to oscillate; there after the restoring force causes unstable pressure differences on each side of the netting which excites the amplitude of the netting oscillations.
基金This project was part of Module H of the Ocean Frontier Institute,funded by the Canada First Research Excellence Fund.
文摘This study evaluated the hydrodynamic forces produced by whole panels of hand-made(geometrically different)rope meshes typically found in midwater trawls.Experimental treatments included both knotted and knotless meshes constructed of helix composite ropes,conventional braided nylon(PA)ropes,and twisted polyethylene(PE)ropes.Direct measurement of lift(L)and drag(D)forces were conducted using controlled flume tank experiments on panels oriented at 21°relative to the flow.For knotted netting,our results showed that the hydrodynamic forces(L and D)were statistically higher for helix ropes compared to conventional ropes of the same diameter.For knotless netting constructed of helix ropes,our primary finding is that the arrangement of helix ropes(S and Z lay)in individual meshes significantly affects the resulting D and Cd of whole netting panels.Arranging the mesh bars in the S-Z-S-Z lay pattern exhibited 29%and 32%lower drag(D)compared to S–S–S–S and S–S-Z-Z lay meshes,respectively.We also use computational fluid dynamics(CFD)to characterize the finescale flow-field around helix and conventional ropes.The resulting streamlines and pressure contours provide a functional explanation for the empirical measurements collected in the flume tank.These results can be useful in informing the design of midwater trawls.
基金the National Natural Science Foundation of China(Grand No.31902426,41806110)Shanghai Sailing Program(19YF1419800),China Postdoctoral Science Foundation funded project(2018M630471)Special project for the exploitation and utilization of Antarctic biological resources of Ministry of Agriculture and Rural Affairs(D-8002-18-0097).
文摘Knotless polyethylene(PE)netting is widely used in fisheries because of its excellent hydrodynamic performance and low cost.Netting deformation and the surrounding flow field distribution play an important role in determining the hydrodynamic characteristics of netting in moving water.In order to investigate the effect of solidity ratio and attack angle on drag,netting deformation,and flow field distribution through the netting,a fluid-structure interaction(FSI)model based on a one-way coupling combining the shear stress turbulent(SST)k-omega model and the large deformation nonlinear structural finite element model was evaluated.Our results showed the difference between the parallel and normal drag forces found in the present numerical model and experimental flume tank data were 9.17%and 11.58%,respectively.The mean relative error in the inclined hydrodynamic drag for different flow velocities and attack angles was 8.35%,6.69%,and 5.37%for the nettings 1,2,and 3,respectively.These results show that the present numerical simulation based on FSI one-way coupling can be used to examine hydrodynamic forces on netting.The flow simulation results show that there is a noticeable flow velocity decrease through the netting and a rather large velocity reduction region downstream from the netting for different attack angles.These results reveal the existence of turbulent flow due to the netting wake.It was found that the equivalent stress and total deformation increase as the flow velocity increases and solidity ratio decreases.
文摘Math is the foundation of everything. The Chinese know this too well and have dominated international math competitions for years. So when the news came that U.S. high school students had won the first prize for a second consecutive year at the Romanian Master of Mathematics 2019, it was no laughing matter.
基金supported by the National Natural Science Foundation of China under Grant 61573183.
文摘With the increase of semiconductor integration density,in order to cope with the increase of wafer defect complexity and types,especially the low recognition accuracy of overlapping mixed defects and unknown wafer defects,this study proposes a lightweight model for wafer defect detection called LightWMNet.First,using a hierarchical attention Encoder-Decoder architecture,the features of wafer defect pattern(WDP)are channel recalibrated to generate high-resolution fine-grained features and low-resolution coarse-grained features.Secondly,the backbone network incorporates two novel attention modules—feedforward spatial attention(FFSa)and feedforward channel attention(FFCa)—to amplify responses in critical defect regions and suppress noise from stochastic discrete pixels.These mechanisms synergistically enhance feature discriminability without introducing significant parametric overhead.Finally,the Dice loss function and the cross entropy loss function are combined to jointly evaluate the segmentation and classification accuracy of the model.Experimental results on the public mixed wafer defect dataset MixedWM38 show that the pixel accuracy(PA),intersection over union(IoU)and Dice coefficient of the proposed network reach 98.26%,94.83%and 97.22%,respectively.Without significantly increasing the computational complexity and size of the model,compared with the existing state-of-the-art(SOTA)model,the classification accuracy of lightWMNet in single defect,three mixed defects and four mixed defects is improved by 0.5%,0.25%and 0.89%respectively.Furthermore,we used transfer learning for the first time to evaluate the model's generalisation ability for unseen defect categories.The results showed that LightWMNet still has a certain recognition ability even in untrained wafer defects.
基金The authors extend their appreciation to King Saud University,Saudi Arabia for funding this work through the Ongoing Research Funding Program(ORF-2025-704),King Saud University,Riyadh,Saudi Arabia.
文摘A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.
基金supported by CAAI-Huawei MindSpore Open Fund(CAAIXSJLJJ-2022-010A).
文摘Monge–Ampere equations(MAEs)are fully nonlinear second-order partial differential equations(PDEs),which are closely related to various fields including optimal transport(OT)theory,geometrical optics and affine geometry.Despite their significance,MAEs are extremely challenging to solve.Although some classical numerical approaches can solve MAEs,their computational efficiency deteriorates significantly on fine grids,with convergence often heavily dependent on the quality of initial estimate.Research on deep learning methods for solving MAEs is still in its early stages,which predominantly addresses simple formulations with basic Dirichlet boundary conditions.Here,we propose a deep learning method based on physicsdriven deep neural networks,enabling the solution of both simple and generalised MAEs with transport boundary conditions.In this method,we deal with two first-order sub-equations separated from MAE instead of solving the single MAE directly,which facilitates the imposition of transport boundary conditions and simplifies the training of neural networks.Moreover,we constrain the convexity of solution using the Lagrange multiplier method and maintain the optimisation process differentiable with bilinear interpolation.We provide three progressively complex examples ranging from a simple MAE with an analytical solution to a highly nonlinear variant arising in phase retrieval to validate the effectiveness of our method.For comparison,we benchmark against state-of-the-art deep learning approaches that have been systematically adapted to accommodate the specific requirements of each example.
文摘Neutrophil extracellular traps(NETs)have emerged as key mediators of cardiovascular diseases(CVDs),linking innate immune activation to vascular injury,thrombosis,and maladaptive remodeling.This review synthesizes recent insights into the molecular and cellular pathways driving NET formation,including post-translational modifications,metabolic reprogramming,inflammasome signaling,and autophagy.It highlights the role of NETs in atherosclerosis,thrombosis,myocardial ischemia-reperfusion injury,and hypertension,emphasizing common control points such as peptidylarginine deiminase 4(PAD4)-dependent histone citrullination and nicotinamide adenine dinucleotide phosphate oxidases 2(NOX2)-mediated oxidative stress.Mechanistic interpretation of circulating biomarkers,includingmyeloperoxidase(MPO)-DNA complexes,citrullinated histoneH3,and cell-free DNA,provides a translational bridge between NET biology and patient stratification.Therapeutic strategies targeting NETs are examined through three main approaches:inhibition of NET initiation,enhancement of chromatin clearance,and neutralization of toxic extracellular components,with attention to both established and emerging interventions.In contrast to previous reviews,this study highlights the novelty of a mechano-therapeutic framework by providing a mechanistic roadmap linking NET formation pathways to therapeutic targeting in cardiovascular disease.Moving forward,integrating mechanistic information with biomarker discovery,precision profiling,and targeted therapies offers innovative strategies to reduce vascular inflammation and improve outcomes in cardiovascular disease.
