Disinfection of swimming pool water is critical to ensure the safety of the recreational activity for swimmers.However,swimming pools have a constant loading of organic matter from input water and anthropogenic contam...Disinfection of swimming pool water is critical to ensure the safety of the recreational activity for swimmers.However,swimming pools have a constant loading of organic matter from input water and anthropogenic contamination,leading to elevated levels of disinfection byproducts(DBPs).Epidemiological studies have associated increased risks of adverse health effects with frequent exposure to DBPs in swimming pools.Zhang et al.(2023b)investigated the occurrence of trihalomethanes(THMs),haloacetic acids(HAAs),haloacetonitriles(HANs),and haloacetaldehydes(HALs)in eight swimming pools and the corresponding input water in a city in Eastern China.The concentrations of THMs,HAAs,HANs,and HALs in swimming poolswere 1–2 orders of magnitude higher than those detected in the input water.The total lifetime cancer and non-cancer health risks of swimmers through oral,dermal,inhalation,buccal,and aural exposure pathways were assessed using the United States Environmental Protection Agency’s(USEPA)standard model and Swimmer Exposure Assessment Model(SWIMODEL).The results showed that dermal and inhalation pathways were the most significant for the associated cancer and non-cancer risks.This article provides an overview and perspectives of DBPs in swimming pools,the benefits of swimming,the need to improve the monitoring of DBPs,and the importance of swimmers’hygiene practices to keep swimming pools clean.The benefits of swimming outweigh the risks from DBP exposure for the promotion of public health.展开更多
Addressing global warming,a common change today,requires achieving peak carbon dioxide emissions and carbon neutrality(also referred to as the dual carbon goals).Enhancing research on the carbon cycle is urgently need...Addressing global warming,a common change today,requires achieving peak carbon dioxide emissions and carbon neutrality(also referred to as the dual carbon goals).Enhancing research on the carbon cycle is urgently needed as the foundation.Water,a key carrier in the carbon cycle,necessitates investigation into groundwater carbon pools’contribution to atmospheric carbon sinks.This study assessed carbon stocks in the Yinchuan Basin’s soil and groundwater carbon pools.Findings indicate the basin’s surface soils contain approximately 24.16 Tg of organic carbon and a total of 60.01 Tg of carbon.In contrast,the basin’s groundwater holds around 4.90 Tg of carbon,roughly one-fifth of the organic carbon in surface soils.Thus,groundwater and soil carbon pools possess comparable carbon stocks,underscoring the importance of the groundwater carbon pool.Studies on terrestrial carbon balance should incorporate groundwater carbon pools,which deserve increased focus.Evaluating groundwater carbon pools’contributions is vital for achieving the dual carbon goals.展开更多
The degradation of animal carcasses can lead to rapid waste release(e.g.,pathogenic bacteria,viruses,prions,or parasites)and also result in nutrient accumulation in the surrounding environment.However,how viral profil...The degradation of animal carcasses can lead to rapid waste release(e.g.,pathogenic bacteria,viruses,prions,or parasites)and also result in nutrient accumulation in the surrounding environment.However,how viral profile responds and influences nutrient pool(carbon(C),nitrogen(N),phosphorus(P)and sulfur(S))in polluted water caused by animal carcass decomposition had not been explored.Here,we combined metagenomic analysis,16S rRNA gene sequencing and water physicochemical assessment to explore the response of viral communities under different temperatures(23℃,26℃,29℃,32℃,and 35℃)in water polluted by cadaver,as well as compare the contribution of viral/bacterial communities on water nutrient pool.We found that a total of 15,240 viral species were classified and mainly consisted of Siphoviridae.Both temperature and carrion reduced the viral diversity and abundance.Only a small portion of the viruses(∼8.8%)had significant negative correlations with temperature,while most were not sensitive.Our results revealed that the viruses had lager contribution on nutrient pool than bacteria.Besides,viral-related functional genes involved in C,N,P and S cycling.These functional genes declined during carcass decomposition and covered part of the central nutrient cycle metabolism(including carbon sugar transformation,denitrification,P mineralization and extracelluar sulfate transfer,etc.).Our result implies that human regulation of virus communities may be more important than bacterial communities in regulating and managing polluted water quality and nutrition.展开更多
Paediatric liver transplantation(PLT)is a life-saving procedure for children with advanced liver disease or hepatoblastoma.The number of available grafts is limited in relation to the number of children on PLT waiting...Paediatric liver transplantation(PLT)is a life-saving procedure for children with advanced liver disease or hepatoblastoma.The number of available grafts is limited in relation to the number of children on PLT waiting list.This graft shortage has led transplant societies and healthcare organizations to explore ways to investigate possible options and expand the donor pool.The safe use of grafts from obese donors has always been a subject of debate among PLT specialists.Donors’obesity is strongly associated with hepatic steatosis which can affect graft function by impairing microcirculation and maximizing the potential of ischemiareperfusion injury.Donor body mass index consideration should go hand in hand with the workup for hepatic steatosis which is an independent predictor for early graft dysfunction.New strategies to optimize the grafts before PLT such as normothermic regional perfusion and ex vivo liver perfusion can potentially mitigate the risk of using grafts from obese donors.This review summarizes the available evidence about the impact of donor obesity on PLT and highlights the current policies to widen the graft pool and suggest future research directions to improve donor selection and patient outcomes.展开更多
Large-sized titanium alloy ingots produced by vacuum arc remelting(VAR)technology are susceptible to metallurgical imperfections such as compositional segregation,inconsistent solidification microstructures,black spot...Large-sized titanium alloy ingots produced by vacuum arc remelting(VAR)technology are susceptible to metallurgical imperfections such as compositional segregation,inconsistent solidification microstructures,black spots,and inclusions.These defects are intricately linked to the electromagnetic effects,temperature distribution,and fluid dynamics during the melting process.The self-induced magnetic field created by the electric current,along with the axial magnetic field applied to stabilize the arc,significantly influences the solidification of titanium alloy ingots.A mathematical model optimized for the integrated analysis of multiple fields—electromagnetic,fluid,and thermal—was developed for the VAR solidification process of titanium alloys.The influence mechanism of electromagnetic field on the macroscopic solidification process of titanium alloy was investigated.The findings indicate the presence of two competing forces within the VAR molten pool,namely,thermal buoyancy and the Lorentz force.Introducing a coupled self-induced magnetic field and elevating the current to 15 kA led to an increase in the molten pool depth by 42.9%and a reduction in the thickness of the mushy zone by 25.2%.The application of a constant axial magnetic field enhances a unidirectional momentum buildup within the molten pool,thereby enhancing the flow velocity and cooling efficiency of melt.展开更多
Cold pools(CPs)significantly influence coastal heavy rainfall,but detailed observations of them are limited due to the lack of vertical measurement instruments.This study statistically characterizes CPs in the coastal...Cold pools(CPs)significantly influence coastal heavy rainfall,but detailed observations of them are limited due to the lack of vertical measurement instruments.This study statistically characterizes CPs in the coastal monsoon region of South China using unique data from the 356-m-high Shenzhen Meteorological Tower.CP occurrence correlates with convective activities influenced by the summer monsoon in the seasonal variations and land–sea breeze activities in the diurnal cycle.The CPs predominantly dry the atmosphere,highlighting the dominant role of dry entrainment through convective downdrafts in their formation,with a minor role of hydrometeor evaporation.The average CP depth is estimated at 668.0 m,deeper than tropical CPs but shallower than midlatitude counterparts.The CP properties exhibit diurnal variability,largely influenced by mesoscale convective system(MCS)activities.MCS-induced CPs are deeper and more intense than those from individual convective cells,while linear-MCS-produced CPs are the most intense.These observations from the coastal monsoon region contribute to a comprehensive global understanding of CP characteristics,complementing existing studies from midlatitude and tropical regions.展开更多
In modern engineering,enhancing boiling heat transfer efficiency is crucial for optimizing energy use and several industrial processes involving different types of materials.This study explores the enhancement of pool...In modern engineering,enhancing boiling heat transfer efficiency is crucial for optimizing energy use and several industrial processes involving different types of materials.This study explores the enhancement of pool boiling heat transfer potentially induced by combining perforated copper particles on a heated surface with a sodium dodecyl sulfate(SDS)surfactant in saturated deionized water.Experiments were conducted at standard atmospheric pressure,with heat flux ranging from 20 to 100 kW/m2.The heating surface,positioned below the layer of freely moving copper beads,allowed the particle layer to shift due to liquid convection and steam nucleation.The study reports on the influence of copper bead diameter(2,3,4,and 5 mm),particle quantity,arrangement,and SDS concentration(20,200,and 500 ppm).It is shown that the combination of 5 mm particles and a 500 ppm SDS concentration can yield a remarkable 139%improvement in heat transfer efficiency.As demonstrated by direct flow visualization,bubble formation occurs primarily in the gaps between the particles and the heated surface,with the presence of SDS reducing bubble size and accelerating bubble detachment.展开更多
This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Tradi...This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Traditional tool monitoring methods that rely on empirical knowledge or limited mathematical models struggle to adapt to complex and dynamic machining environments.To address this,we implement real-time tool condition recognition by introducing deep learning technology.Aiming to the insufficient recognition accuracy,we propose a pyramid pooling-based vision Transformer network(P2ViT-Net)method for tool condition recognition.Using images as input effectively mitigates the issue of low-dimensional signal features.We enhance the vision Transformer(ViT)framework for image classification by developing the P2ViT model and adapt it to tool condition recognition.Experimental results demonstrate that our improved P2ViT model achieves 94.4%recognition accuracy,showing a 10%improvement over conventional ViT and outperforming all comparative convolutional neural network models.展开更多
With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance systems.This technology plays a critical role in enhan...With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance systems.This technology plays a critical role in enhancing public safety.However,traditional methods typically process images and text separately,applying upstream models directly to downstream tasks.This approach significantly increases the complexity ofmodel training and computational costs.Furthermore,the common class imbalance in existing training datasets limitsmodel performance improvement.To address these challenges,we propose an innovative framework named Person Re-ID Network Based on Visual Prompt Technology andMulti-Instance Negative Pooling(VPM-Net).First,we incorporate the Contrastive Language-Image Pre-training(CLIP)pre-trained model to accurately map visual and textual features into a unified embedding space,effectively mitigating inconsistencies in data distribution and the training process.To enhancemodel adaptability and generalization,we introduce an efficient and task-specific Visual Prompt Tuning(VPT)technique,which improves the model’s relevance to specific tasks.Additionally,we design two key modules:the Knowledge-Aware Network(KAN)and theMulti-Instance Negative Pooling(MINP)module.The KAN module significantly enhances the model’s understanding of complex scenarios through deep contextual semantic modeling.MINP module handles samples,effectively improving the model’s ability to distinguish fine-grained features.The experimental outcomes across diverse datasets underscore the remarkable performance of VPM-Net.These results vividly demonstrate the unique advantages and robust reliability of VPM-Net in fine-grained retrieval tasks.展开更多
With the rise in drowning accidents in swimming pools,the demand for the precision and speed in artificial intelligence(AI)drowning detection methods has become increasingly crucial.Here,an improved YOLO-based method,...With the rise in drowning accidents in swimming pools,the demand for the precision and speed in artificial intelligence(AI)drowning detection methods has become increasingly crucial.Here,an improved YOLO-based method,named DrownACB-YOLO,for drowning detection in swimming pools is proposed.Since existing methods focus on the drowned state,a transition label is added to the original dataset to provide timely alerts.Following this expanded dataset,two improvements are implemented in the original YOLOv5.Firstly,the spatial pyramid pooling(SPP)module and the default upsampling operator are replaced by the atrous spatial pyramid pooling(ASPP)module and the content-aware reassembly of feature(CARAFE)module,respectively.Secondly,the cross stage partial bottleneck with three convolutions(C3)module at the end of the backbone is replaced with the bottleneck transformer(BotNet)module.The results of comparison experiments demonstrate that DrownACB-YOLO performs better than other models.展开更多
To build a community of scientific innovation,serve the country’s goals of carbon peak and carbon neutrality,promote application of scientific research outcomes in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA),...To build a community of scientific innovation,serve the country’s goals of carbon peak and carbon neutrality,promote application of scientific research outcomes in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA),and accelerate the formation of new quality productive forces in the green energy industry,the Yangjiang Offshore Wind Power Laboratory and the GBA Institute of Industry and Talent(GBAIIT)recently signed a strategic cooperation agreement.展开更多
In convolutional neural networks,pooling methods are used to reduce both the size of the data and the number of parameters after the convolution of the models.These methods reduce the computational amount of convoluti...In convolutional neural networks,pooling methods are used to reduce both the size of the data and the number of parameters after the convolution of the models.These methods reduce the computational amount of convolutional neural networks,making the neural network more efficient.Maximum pooling,average pooling,and minimum pooling methods are generally used in convolutional neural networks.However,these pooling methods are not suitable for all datasets used in neural network applications.In this study,a new pooling approach to the literature is proposed to increase the efficiency and success rates of convolutional neural networks.This method,which we call MAM(Maximum Average Minimum)pooling,is more interactive than other traditional maximum pooling,average pooling,and minimum pooling methods and reduces data loss by calculating the more appropriate pixel value.The proposed MAM pooling method increases the performance of the neural network by calculating the optimal value during the training of convolutional neural networks.To determine the success accuracy of the proposed MAM pooling method and compare it with other traditional pooling methods,training was carried out on the LeNet-5 model using CIFAR-10,CIFAR-100,and MNIST datasets.According to the results obtained,the proposed MAM pooling method performed better than the maximum pooling,average pooling,and minimum pooling methods in all pool sizes on three different datasets.展开更多
Aiming at the problem of low surface defect detection accuracy of industrial products, an object detection method based on simplified spatial pyramid pooling fast(Sim SPPF) hybrid pooling improved you only look once v...Aiming at the problem of low surface defect detection accuracy of industrial products, an object detection method based on simplified spatial pyramid pooling fast(Sim SPPF) hybrid pooling improved you only look once version 5s(YOLOV5s) model is proposed. The algorithm introduces channel attention(CA) module, simplified SPPF feature vector pyramid and efficient intersection over union(EIOU) loss function. Feature vector pyramids fuse high-dimensional and low-dimensional features, which makes semantic information richer. The CA mechanism performs maximum pooling and average pooling operations on the feature map. Hybrid pooling comprehensively improves detection computing efficiency and accurate deployment ability. The results show that the improved YOLOV5s model is better than the original YOLOV5s model. The average test accuracy(mAP) can reach 91.8%, which can be increased by 17.4%, and the detection speed can reach 108 FPS, which can be increased by 18 FPS. The improved model is practicable, and the overall performance is better than other conventional models.展开更多
There are three formation stages of Silurian hydrocarbon pools in the Tarim Basin. The widely distributed asphaltic sandstones in the Tazhong （central Tarim） and Tabei （northern Tarim） areas are the results of des...There are three formation stages of Silurian hydrocarbon pools in the Tarim Basin. The widely distributed asphaltic sandstones in the Tazhong （central Tarim） and Tabei （northern Tarim） areas are the results of destruction of hydrocarbon pools formed in the first-stage, and the asphaltic sandstones around the Awati Sag were formed in the second-stage. The hydrocarbon migration characteristics reflected by the residual dry asphalts could represent the migration characteristics of hydrocarbons in the Silurian paleo-pools, while the present movable oil in the Silurian reservoirs is related to the iater-stage （the third-stage） hydrocarbon accumulation.展开更多
In order to investigate the process of laser cladding(LC)Inconel 625 alloy powder on Q235 steel plate,this paper focuses on analyzing the effects of different process parameters on the temperature field,stress field a...In order to investigate the process of laser cladding(LC)Inconel 625 alloy powder on Q235 steel plate,this paper focuses on analyzing the effects of different process parameters on the temperature field,stress field and flow behavior of the molten pool through a combination of finite element simulation and experiment.The simulation part established a geometric model,applied the Goldak double el-lipsoid heat source model,and simulated the LC process by varying the laser power and scanning speed.For the experimental part,LC equipment was used,parameters such as laser power and scanning speed were adjusted,and the molten pool dynamics were observed by in-frared temperature measurement and high-speed photography.The results show that the laser power and scanning speed are the key factors affecting the quality of cladding,and the experimental observation coincides with the simulation results,which verifies the validity of the simulation method and provides theoretical basis and experimental support for the optimization of the LC process.展开更多
Although laser powder bed fusion(LPBF)technology is considered one of the most promising additive man-ufacturing techniques,the fabricated parts still suffer from porosity defects,which can severely impact their mecha...Although laser powder bed fusion(LPBF)technology is considered one of the most promising additive man-ufacturing techniques,the fabricated parts still suffer from porosity defects,which can severely impact their mechanical performance.Monitoring the printing process using a variety of sensors to collect process signals can realize a comprehensive capture of the processing status;thus,the monitoring accuracy can be improved.However,existing multi-sensing signals are mainly optical and acoustic,and camera-based signals are mostly layer-wise images captured after printing,preventing real-time monitoring.This paper proposes a real-time melt-pool-based in-situ quality monitoring method for LPBF using multiple sensors.High-speed cameras,photodiodes,and microphones were used to collect signals during the experimental process.All three types of signals were transformed from one-dimensional time-domain signals into corresponding two-dimensional grayscale images,which enabled the capture of more localized features.Based on an improved LeNet-5 model and the weighted Dempster-Shafer evidence theory,single-sensor,dual-sensor and triple-sensor fusion monitoring models were in-vestigated with the three types of signals,and their performances were compared.The results showed that the triple-sensor fusion monitoring model achieved the highest recognition accuracy,with accuracy rates of 97.98%,92.63%,and 100%for high-,medium-,and low-quality samples,respectively.Hence,a multi-sensor fusion based melt pool monitoring system can improve the accuracy of quality monitoring in the LPBF process,which has the potential to reduce porosity defects.Finally,the experimental analysis demonstrates that the convolutional neural network proposed in this study has better classification accuracy compared to other machine learning models.展开更多
The malicious mining pool can sacrifice part of its revenue to employ the computing power of blockchain network.The employed computing power carries out the pool mining attacks on the attacked mining pool.To realize t...The malicious mining pool can sacrifice part of its revenue to employ the computing power of blockchain network.The employed computing power carries out the pool mining attacks on the attacked mining pool.To realize the win-win game between the malicious mining pool and the employee,the paper proposes an Employment Attack Pricing Algorithm(EAPA)of mining pools in blockchain based on game theory.In the EAPA,the paper uses mathematical formulas to express the revenue of malicious mining pools under the employment attack,the revenue increment of malicious mining pools,and the revenue of the employee.It establishes a game model between the malicious mining pool and the employee under the employment attack.Then,the paper proposes an optimal computing power price selection strategy of employment attack based on model derivation.In the strategy,the malicious mining pool analyzes the conditions for the employment attack,and uses the derivative method to find the optimal utilization value of computing power,employees analyze the conditions for accepting employment,and use the derivative method to find the optimal reward value of computing power.Finally,the strategy finds the optimal employment computing power price to realize Nash equilibrium between the malicious mining pool and the employee under the current computing power allocation.The simulation results show that the EAPA could find the employment computing power price that realizes the win-win game between the malicious mining pool and the employee.The EAPA also maximizes the unit computing power revenue of employment and the unit computing power revenue of honest mining in malicious mining pool at the same time.The EAPA outperforms the state-of-the-art methods such as SPSUCP,DPSACP,and FPSUCP.展开更多
Pooling,unpooling/specialization,and discretionary task completion are typical operational strategies in queueing systems that arise in healthcare,call centers,and online sales.These strategies may have advantages and...Pooling,unpooling/specialization,and discretionary task completion are typical operational strategies in queueing systems that arise in healthcare,call centers,and online sales.These strategies may have advantages and disadvantages in different operational environments.This paper uses the M/M/1 and M/M/2 queues to study the impact of pooling,specialization,and discretionary task completion on the average queue length.Closed-form solutions for the average M/M/2 queue length are derived.Computational examples illustrate how the average queue length changes with the strength of pooling,specialization,and discretionary task completion.Finally,several conjectures are made in the paper.展开更多
文摘Disinfection of swimming pool water is critical to ensure the safety of the recreational activity for swimmers.However,swimming pools have a constant loading of organic matter from input water and anthropogenic contamination,leading to elevated levels of disinfection byproducts(DBPs).Epidemiological studies have associated increased risks of adverse health effects with frequent exposure to DBPs in swimming pools.Zhang et al.(2023b)investigated the occurrence of trihalomethanes(THMs),haloacetic acids(HAAs),haloacetonitriles(HANs),and haloacetaldehydes(HALs)in eight swimming pools and the corresponding input water in a city in Eastern China.The concentrations of THMs,HAAs,HANs,and HALs in swimming poolswere 1–2 orders of magnitude higher than those detected in the input water.The total lifetime cancer and non-cancer health risks of swimmers through oral,dermal,inhalation,buccal,and aural exposure pathways were assessed using the United States Environmental Protection Agency’s(USEPA)standard model and Swimmer Exposure Assessment Model(SWIMODEL).The results showed that dermal and inhalation pathways were the most significant for the associated cancer and non-cancer risks.This article provides an overview and perspectives of DBPs in swimming pools,the benefits of swimming,the need to improve the monitoring of DBPs,and the importance of swimmers’hygiene practices to keep swimming pools clean.The benefits of swimming outweigh the risks from DBP exposure for the promotion of public health.
基金supported by the third scientific survey project in Xinjiang(2022xjkk0300)the public welfare geological survey projects initiated by the China Geological Survey(DD20190296,DD20221731).
文摘Addressing global warming,a common change today,requires achieving peak carbon dioxide emissions and carbon neutrality(also referred to as the dual carbon goals).Enhancing research on the carbon cycle is urgently needed as the foundation.Water,a key carrier in the carbon cycle,necessitates investigation into groundwater carbon pools’contribution to atmospheric carbon sinks.This study assessed carbon stocks in the Yinchuan Basin’s soil and groundwater carbon pools.Findings indicate the basin’s surface soils contain approximately 24.16 Tg of organic carbon and a total of 60.01 Tg of carbon.In contrast,the basin’s groundwater holds around 4.90 Tg of carbon,roughly one-fifth of the organic carbon in surface soils.Thus,groundwater and soil carbon pools possess comparable carbon stocks,underscoring the importance of the groundwater carbon pool.Studies on terrestrial carbon balance should incorporate groundwater carbon pools,which deserve increased focus.Evaluating groundwater carbon pools’contributions is vital for achieving the dual carbon goals.
基金supported by the National Natural Science Foundation of China (No.42007026)the Medical Innovation and Development Project of Lanzhou University (lzuyxcx-2022-172)
文摘The degradation of animal carcasses can lead to rapid waste release(e.g.,pathogenic bacteria,viruses,prions,or parasites)and also result in nutrient accumulation in the surrounding environment.However,how viral profile responds and influences nutrient pool(carbon(C),nitrogen(N),phosphorus(P)and sulfur(S))in polluted water caused by animal carcass decomposition had not been explored.Here,we combined metagenomic analysis,16S rRNA gene sequencing and water physicochemical assessment to explore the response of viral communities under different temperatures(23℃,26℃,29℃,32℃,and 35℃)in water polluted by cadaver,as well as compare the contribution of viral/bacterial communities on water nutrient pool.We found that a total of 15,240 viral species were classified and mainly consisted of Siphoviridae.Both temperature and carrion reduced the viral diversity and abundance.Only a small portion of the viruses(∼8.8%)had significant negative correlations with temperature,while most were not sensitive.Our results revealed that the viruses had lager contribution on nutrient pool than bacteria.Besides,viral-related functional genes involved in C,N,P and S cycling.These functional genes declined during carcass decomposition and covered part of the central nutrient cycle metabolism(including carbon sugar transformation,denitrification,P mineralization and extracelluar sulfate transfer,etc.).Our result implies that human regulation of virus communities may be more important than bacterial communities in regulating and managing polluted water quality and nutrition.
文摘Paediatric liver transplantation(PLT)is a life-saving procedure for children with advanced liver disease or hepatoblastoma.The number of available grafts is limited in relation to the number of children on PLT waiting list.This graft shortage has led transplant societies and healthcare organizations to explore ways to investigate possible options and expand the donor pool.The safe use of grafts from obese donors has always been a subject of debate among PLT specialists.Donors’obesity is strongly associated with hepatic steatosis which can affect graft function by impairing microcirculation and maximizing the potential of ischemiareperfusion injury.Donor body mass index consideration should go hand in hand with the workup for hepatic steatosis which is an independent predictor for early graft dysfunction.New strategies to optimize the grafts before PLT such as normothermic regional perfusion and ex vivo liver perfusion can potentially mitigate the risk of using grafts from obese donors.This review summarizes the available evidence about the impact of donor obesity on PLT and highlights the current policies to widen the graft pool and suggest future research directions to improve donor selection and patient outcomes.
基金financially supported by the National Natural Science Foundation of China(Nos.52422408 and 52171031)the Excellent Youth Fund of Liaoning Natural Science Foundation(No.2023JH3/10200001)the Liaoning Xingliao Talents-Top-notch Young Talents Project(No.XLYC2203064).
文摘Large-sized titanium alloy ingots produced by vacuum arc remelting(VAR)technology are susceptible to metallurgical imperfections such as compositional segregation,inconsistent solidification microstructures,black spots,and inclusions.These defects are intricately linked to the electromagnetic effects,temperature distribution,and fluid dynamics during the melting process.The self-induced magnetic field created by the electric current,along with the axial magnetic field applied to stabilize the arc,significantly influences the solidification of titanium alloy ingots.A mathematical model optimized for the integrated analysis of multiple fields—electromagnetic,fluid,and thermal—was developed for the VAR solidification process of titanium alloys.The influence mechanism of electromagnetic field on the macroscopic solidification process of titanium alloy was investigated.The findings indicate the presence of two competing forces within the VAR molten pool,namely,thermal buoyancy and the Lorentz force.Introducing a coupled self-induced magnetic field and elevating the current to 15 kA led to an increase in the molten pool depth by 42.9%and a reduction in the thickness of the mushy zone by 25.2%.The application of a constant axial magnetic field enhances a unidirectional momentum buildup within the molten pool,thereby enhancing the flow velocity and cooling efficiency of melt.
基金supported by the National Key Research and Development Program of China (Grant No. 2024YFC3013003)the National Natural Science Foundation of China (Grant No. 42475002)+2 种基金the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (Grant Nos. SML2024SP035, SML2024SP012, and 311024001)the Guangdong Basic and Applied Basic Research Foundation (Grant Nos. 2025A1515011974, 2024A1515510005 and 2020B0301030004)the Key Innovation Team of China Meteorological Administration (Grant No. CMA2023ZD08)
文摘Cold pools(CPs)significantly influence coastal heavy rainfall,but detailed observations of them are limited due to the lack of vertical measurement instruments.This study statistically characterizes CPs in the coastal monsoon region of South China using unique data from the 356-m-high Shenzhen Meteorological Tower.CP occurrence correlates with convective activities influenced by the summer monsoon in the seasonal variations and land–sea breeze activities in the diurnal cycle.The CPs predominantly dry the atmosphere,highlighting the dominant role of dry entrainment through convective downdrafts in their formation,with a minor role of hydrometeor evaporation.The average CP depth is estimated at 668.0 m,deeper than tropical CPs but shallower than midlatitude counterparts.The CP properties exhibit diurnal variability,largely influenced by mesoscale convective system(MCS)activities.MCS-induced CPs are deeper and more intense than those from individual convective cells,while linear-MCS-produced CPs are the most intense.These observations from the coastal monsoon region contribute to a comprehensive global understanding of CP characteristics,complementing existing studies from midlatitude and tropical regions.
基金supported by the National Natural Science Foundation of China(Project No.52166004)the National Key Research and Development Program of China(Project No.2022YFC3902000)+2 种基金the Major Science and Technology Special Project of Yunnan Province(Project Nos.202202AG050007202202AG050002)the Research on the Development of Complete Sets of Technology for Extraction of Aromatic Substances from Tobacco Waste and Its Application,Applied Research-Pyrolysis Process Technology Research(2023QT01).
文摘In modern engineering,enhancing boiling heat transfer efficiency is crucial for optimizing energy use and several industrial processes involving different types of materials.This study explores the enhancement of pool boiling heat transfer potentially induced by combining perforated copper particles on a heated surface with a sodium dodecyl sulfate(SDS)surfactant in saturated deionized water.Experiments were conducted at standard atmospheric pressure,with heat flux ranging from 20 to 100 kW/m2.The heating surface,positioned below the layer of freely moving copper beads,allowed the particle layer to shift due to liquid convection and steam nucleation.The study reports on the influence of copper bead diameter(2,3,4,and 5 mm),particle quantity,arrangement,and SDS concentration(20,200,and 500 ppm).It is shown that the combination of 5 mm particles and a 500 ppm SDS concentration can yield a remarkable 139%improvement in heat transfer efficiency.As demonstrated by direct flow visualization,bubble formation occurs primarily in the gaps between the particles and the heated surface,with the presence of SDS reducing bubble size and accelerating bubble detachment.
基金supported by China Postdoctoral Science Foundation(No.2024M754122)the Postdoctoral Fellowship Programof CPSF(No.GZB20240972)+3 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent(No.2024ZB194)Natural Science Foundation of Jiangsu Province(No.BK20241389)Basic Science ResearchFund of China(No.JCKY2023203C026)2024 Jiangsu Province Talent Programme Qinglan Project.
文摘This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Traditional tool monitoring methods that rely on empirical knowledge or limited mathematical models struggle to adapt to complex and dynamic machining environments.To address this,we implement real-time tool condition recognition by introducing deep learning technology.Aiming to the insufficient recognition accuracy,we propose a pyramid pooling-based vision Transformer network(P2ViT-Net)method for tool condition recognition.Using images as input effectively mitigates the issue of low-dimensional signal features.We enhance the vision Transformer(ViT)framework for image classification by developing the P2ViT model and adapt it to tool condition recognition.Experimental results demonstrate that our improved P2ViT model achieves 94.4%recognition accuracy,showing a 10%improvement over conventional ViT and outperforming all comparative convolutional neural network models.
基金funded by the Key Research and Development Program of Hubei Province,China(Grant No.2023BEB024)the Young and Middle-aged Scientific and Technological Innova-tion Team Plan in Higher Education Institutions inHubei Province,China(GrantNo.T2023007)the key projects ofHubei Provincial Department of Education(No.D20161403).
文摘With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance systems.This technology plays a critical role in enhancing public safety.However,traditional methods typically process images and text separately,applying upstream models directly to downstream tasks.This approach significantly increases the complexity ofmodel training and computational costs.Furthermore,the common class imbalance in existing training datasets limitsmodel performance improvement.To address these challenges,we propose an innovative framework named Person Re-ID Network Based on Visual Prompt Technology andMulti-Instance Negative Pooling(VPM-Net).First,we incorporate the Contrastive Language-Image Pre-training(CLIP)pre-trained model to accurately map visual and textual features into a unified embedding space,effectively mitigating inconsistencies in data distribution and the training process.To enhancemodel adaptability and generalization,we introduce an efficient and task-specific Visual Prompt Tuning(VPT)technique,which improves the model’s relevance to specific tasks.Additionally,we design two key modules:the Knowledge-Aware Network(KAN)and theMulti-Instance Negative Pooling(MINP)module.The KAN module significantly enhances the model’s understanding of complex scenarios through deep contextual semantic modeling.MINP module handles samples,effectively improving the model’s ability to distinguish fine-grained features.The experimental outcomes across diverse datasets underscore the remarkable performance of VPM-Net.These results vividly demonstrate the unique advantages and robust reliability of VPM-Net in fine-grained retrieval tasks.
文摘With the rise in drowning accidents in swimming pools,the demand for the precision and speed in artificial intelligence(AI)drowning detection methods has become increasingly crucial.Here,an improved YOLO-based method,named DrownACB-YOLO,for drowning detection in swimming pools is proposed.Since existing methods focus on the drowned state,a transition label is added to the original dataset to provide timely alerts.Following this expanded dataset,two improvements are implemented in the original YOLOv5.Firstly,the spatial pyramid pooling(SPP)module and the default upsampling operator are replaced by the atrous spatial pyramid pooling(ASPP)module and the content-aware reassembly of feature(CARAFE)module,respectively.Secondly,the cross stage partial bottleneck with three convolutions(C3)module at the end of the backbone is replaced with the bottleneck transformer(BotNet)module.The results of comparison experiments demonstrate that DrownACB-YOLO performs better than other models.
文摘To build a community of scientific innovation,serve the country’s goals of carbon peak and carbon neutrality,promote application of scientific research outcomes in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA),and accelerate the formation of new quality productive forces in the green energy industry,the Yangjiang Offshore Wind Power Laboratory and the GBA Institute of Industry and Talent(GBAIIT)recently signed a strategic cooperation agreement.
文摘In convolutional neural networks,pooling methods are used to reduce both the size of the data and the number of parameters after the convolution of the models.These methods reduce the computational amount of convolutional neural networks,making the neural network more efficient.Maximum pooling,average pooling,and minimum pooling methods are generally used in convolutional neural networks.However,these pooling methods are not suitable for all datasets used in neural network applications.In this study,a new pooling approach to the literature is proposed to increase the efficiency and success rates of convolutional neural networks.This method,which we call MAM(Maximum Average Minimum)pooling,is more interactive than other traditional maximum pooling,average pooling,and minimum pooling methods and reduces data loss by calculating the more appropriate pixel value.The proposed MAM pooling method increases the performance of the neural network by calculating the optimal value during the training of convolutional neural networks.To determine the success accuracy of the proposed MAM pooling method and compare it with other traditional pooling methods,training was carried out on the LeNet-5 model using CIFAR-10,CIFAR-100,and MNIST datasets.According to the results obtained,the proposed MAM pooling method performed better than the maximum pooling,average pooling,and minimum pooling methods in all pool sizes on three different datasets.
基金supported by the Tianjin Postgraduate Research Innovation Project (No.2022SKY286)the National Science and the National Key Research and Development Program (No.2022YFF0706000)。
文摘Aiming at the problem of low surface defect detection accuracy of industrial products, an object detection method based on simplified spatial pyramid pooling fast(Sim SPPF) hybrid pooling improved you only look once version 5s(YOLOV5s) model is proposed. The algorithm introduces channel attention(CA) module, simplified SPPF feature vector pyramid and efficient intersection over union(EIOU) loss function. Feature vector pyramids fuse high-dimensional and low-dimensional features, which makes semantic information richer. The CA mechanism performs maximum pooling and average pooling operations on the feature map. Hybrid pooling comprehensively improves detection computing efficiency and accurate deployment ability. The results show that the improved YOLOV5s model is better than the original YOLOV5s model. The average test accuracy(mAP) can reach 91.8%, which can be increased by 17.4%, and the detection speed can reach 108 FPS, which can be increased by 18 FPS. The improved model is practicable, and the overall performance is better than other conventional models.
文摘There are three formation stages of Silurian hydrocarbon pools in the Tarim Basin. The widely distributed asphaltic sandstones in the Tazhong （central Tarim） and Tabei （northern Tarim） areas are the results of destruction of hydrocarbon pools formed in the first-stage, and the asphaltic sandstones around the Awati Sag were formed in the second-stage. The hydrocarbon migration characteristics reflected by the residual dry asphalts could represent the migration characteristics of hydrocarbons in the Silurian paleo-pools, while the present movable oil in the Silurian reservoirs is related to the iater-stage （the third-stage） hydrocarbon accumulation.
基金supported by Natural Science Foundation of Shandong Province of China(Grant No.ZR2023ME201)Qingdao Key Technology Research and Industrialization Demonstration Project(23-1-2-qljh-17-gx).
文摘In order to investigate the process of laser cladding(LC)Inconel 625 alloy powder on Q235 steel plate,this paper focuses on analyzing the effects of different process parameters on the temperature field,stress field and flow behavior of the molten pool through a combination of finite element simulation and experiment.The simulation part established a geometric model,applied the Goldak double el-lipsoid heat source model,and simulated the LC process by varying the laser power and scanning speed.For the experimental part,LC equipment was used,parameters such as laser power and scanning speed were adjusted,and the molten pool dynamics were observed by in-frared temperature measurement and high-speed photography.The results show that the laser power and scanning speed are the key factors affecting the quality of cladding,and the experimental observation coincides with the simulation results,which verifies the validity of the simulation method and provides theoretical basis and experimental support for the optimization of the LC process.
基金supported by Key Research and Development Pro-gram of Jiangsu Province(Grant Nos.BE2022069-1 and BE2022069-2)Natural Science Research Project of Jiangsu Higher Education Institu-tions(Grant Nos.22KJB460030 and 22KJB460004)+2 种基金Suzhou Science and Technology Development Plan(Grant No.SYC2022020)startup fund-ing at the Nanjing Normal University(Grant No.184080H202B318)2022 Nanjing Carbon Peak and Neutrality Technology Innovation Special Fund(Grant No.202211017).
文摘Although laser powder bed fusion(LPBF)technology is considered one of the most promising additive man-ufacturing techniques,the fabricated parts still suffer from porosity defects,which can severely impact their mechanical performance.Monitoring the printing process using a variety of sensors to collect process signals can realize a comprehensive capture of the processing status;thus,the monitoring accuracy can be improved.However,existing multi-sensing signals are mainly optical and acoustic,and camera-based signals are mostly layer-wise images captured after printing,preventing real-time monitoring.This paper proposes a real-time melt-pool-based in-situ quality monitoring method for LPBF using multiple sensors.High-speed cameras,photodiodes,and microphones were used to collect signals during the experimental process.All three types of signals were transformed from one-dimensional time-domain signals into corresponding two-dimensional grayscale images,which enabled the capture of more localized features.Based on an improved LeNet-5 model and the weighted Dempster-Shafer evidence theory,single-sensor,dual-sensor and triple-sensor fusion monitoring models were in-vestigated with the three types of signals,and their performances were compared.The results showed that the triple-sensor fusion monitoring model achieved the highest recognition accuracy,with accuracy rates of 97.98%,92.63%,and 100%for high-,medium-,and low-quality samples,respectively.Hence,a multi-sensor fusion based melt pool monitoring system can improve the accuracy of quality monitoring in the LPBF process,which has the potential to reduce porosity defects.Finally,the experimental analysis demonstrates that the convolutional neural network proposed in this study has better classification accuracy compared to other machine learning models.
基金funded by the“Ling Yan”Research and Development Project of Science Technology Department of Zhejiang Province of China under Grants No.2022C03122Public Welfare Technology Application and Research Projects of Science Technology Department of Zhejiang Province of China under Grants No.LGF22F020006 and LGF21F010004.
文摘The malicious mining pool can sacrifice part of its revenue to employ the computing power of blockchain network.The employed computing power carries out the pool mining attacks on the attacked mining pool.To realize the win-win game between the malicious mining pool and the employee,the paper proposes an Employment Attack Pricing Algorithm(EAPA)of mining pools in blockchain based on game theory.In the EAPA,the paper uses mathematical formulas to express the revenue of malicious mining pools under the employment attack,the revenue increment of malicious mining pools,and the revenue of the employee.It establishes a game model between the malicious mining pool and the employee under the employment attack.Then,the paper proposes an optimal computing power price selection strategy of employment attack based on model derivation.In the strategy,the malicious mining pool analyzes the conditions for the employment attack,and uses the derivative method to find the optimal utilization value of computing power,employees analyze the conditions for accepting employment,and use the derivative method to find the optimal reward value of computing power.Finally,the strategy finds the optimal employment computing power price to realize Nash equilibrium between the malicious mining pool and the employee under the current computing power allocation.The simulation results show that the EAPA could find the employment computing power price that realizes the win-win game between the malicious mining pool and the employee.The EAPA also maximizes the unit computing power revenue of employment and the unit computing power revenue of honest mining in malicious mining pool at the same time.The EAPA outperforms the state-of-the-art methods such as SPSUCP,DPSACP,and FPSUCP.
文摘Pooling,unpooling/specialization,and discretionary task completion are typical operational strategies in queueing systems that arise in healthcare,call centers,and online sales.These strategies may have advantages and disadvantages in different operational environments.This paper uses the M/M/1 and M/M/2 queues to study the impact of pooling,specialization,and discretionary task completion on the average queue length.Closed-form solutions for the average M/M/2 queue length are derived.Computational examples illustrate how the average queue length changes with the strength of pooling,specialization,and discretionary task completion.Finally,several conjectures are made in the paper.
