Based on Brown &Levinson's Face Threatening Acts and Geert Hofstede's Cultural Dimensions,this study is an analysis of Chinese college students' face needs in EFL class.In this study,the subjects are 1...Based on Brown &Levinson's Face Threatening Acts and Geert Hofstede's Cultural Dimensions,this study is an analysis of Chinese college students' face needs in EFL class.In this study,the subjects are 116 freshmen,non-English majors.Selecting totally 60 students from them and dividing them into two groups according to their scores of College English Entrance Examination.The collected data from questionnaire are analyzed by statistical software SPSS16.0 version.The major findings from the analysis include the following:1) high-scored students and low-scored students have similar positive face needs;2) Weight of imposition,group tendency and uncertainty avoidance are used to exam students' negative face needs.According to the data in SPSS16.0,there is a difference between the two groups in terms of the weight of imposition.But the Independent-Samples T test of Sum of Questionnaire indicates that there is no distinct difference in the negative face needs between the two groups.展开更多
The airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections.During the COVID-19 pandemic,the use of protective face masks was essential to reduce the...The airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections.During the COVID-19 pandemic,the use of protective face masks was essential to reduce the risk of infection and spread of SARS-CoV-2.The face mask is able to significantly reduce the saliva droplet emission in front of the person.However,the use of masks also produces a particle leakage towards the back of the person,which could increase the infection risk of people behind the subject.Most of the experimental investigations applied invasive and/or complex experimental techniques to evaluate the face masks leakage.The primary objective of this study is to develop a novel,non-invasive methodology for assessing rearward droplet emission associated with the use of protective face masks.Specifically,a thermographic analysis of the thermal footprint released during ordinary and extraordinary respiratory activities is presented,evaluating the maximum temperature,the detection time,and the spread area of the thermal footprint.Both surgical and FFP2 face masks were tested.Two different subjects were involved in the experimentation to evaluate the influence of face conformation.The findings indicate that the area influenced by droplet dispersion is larger when wearing a surgical mask compared to an FFP2 mask,with the highest recorded temperatures observed for the surgical mask.The thermal footprint was found to be strongly dependent on individual facial morphology and mask fit.Notably,the FFP2 mask also altered the position of the thermal footprint,which was primarily confined to the region near the neck.展开更多
Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC rec...Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.展开更多
This study develops a contact performance-driven method for skiving face gear drives using a single cutter,eliminating the traditional need for separate cutters to reduce production costs and time.First,the mathematic...This study develops a contact performance-driven method for skiving face gear drives using a single cutter,eliminating the traditional need for separate cutters to reduce production costs and time.First,the mathematical models of the tooth flanks for the face gear drives are established based on the gear skiving processes.Then,load tooth contact analysis(LTCA)model is established to calculate the contact performance data.Next,a two-stage optimization model is employed to determine the optimal parameters of the cutting edge with improved contact performances.The effectiveness of this method is validated through simulations and rolling tests.Compared with the traditional method,the proposed method can machine both the face gear and its mating pinion with a single cutter.Simulation results show that the proposed method avoids tooth surface edge contact,with the maximum tooth surface contact stress reduced by 31.7%,the contact ratio decreases by 21.5%,and the transmission error increases by 22.3%.Rolling tests verify the consistency of tooth surface contact patterns between simulations and experiments.The proposed method provides a reference for the cutting edge design of skiving cutters for face gear pairs.展开更多
Shield tunneling in saturated ground poses challenges due to the potential risk of ground collapse resulting from seepage force and inadequate support pressure.This study employed a laboratory model test and a theoret...Shield tunneling in saturated ground poses challenges due to the potential risk of ground collapse resulting from seepage force and inadequate support pressure.This study employed a laboratory model test and a theoretical validation to elucidate the mechanisms of face failure and subsequent ground collapse in saturated ground during slurry pressure-balanced shield(SPBS)tunneling operations.A slurry circulation system was developed to ensure steady shield tunneling and to replicate the phenomena of ground collapse.Investigations into shield tunneling parameters and ground responses,including soil pressure,pore water pressure,and surface subsidence,were conducted to understand the mechanisms of face failure and subsequent ground collapse.The theoretical solution for the critical collapse pressure of the tunnel face,based on the rotational failure mechanism,was validated through the comparison with the experimentally determined critical collapse pressure.The results indicate that:(1)appropriate adjustments of tunneling parameters are crucial for promoting filtercake formation,maintaining chamber pressure,and minimizing ground subsidence;(2)chamber pressure,soil pressure,pore water pressure,and ground subsidence are closely correlated with shield tunneling parameters and the formation of filter cake;(3)ground collapse follows a continuous failure mode due to the destruction of filtercake and the decrease in chamber pressure;(4)the soil pressure at the cutterhead is more sensitive to disturbances from shield tunneling than chamber pressure;and(5)experimentally determined critical collapse pressures is consistent with the theoretical solution of limit analysis.展开更多
Many hydropower projects have been constructed in Southwest China with the strategic goal of achieving carbon neutrality.Most of these hydropower projects utilize concrete face rockfilldams(CFRDs)built on a deep overb...Many hydropower projects have been constructed in Southwest China with the strategic goal of achieving carbon neutrality.Most of these hydropower projects utilize concrete face rockfilldams(CFRDs)built on a deep overburden layer.The deep overburden layer causes uneven settlement between the overburden layer and the dam,which poses a serious threat to the safety of both the construction and operation of the dam.In this study,microseismic(MS)monitoring technology was employed for the firsttime in the fieldof dam fillingengineering,allowing for the real-time monitoring of microfracture in the bedrock during dam construction.The time-frequency analysis method was used to summarize the MS waveform characteristics induced by dam filling.The fracture mechanism of bedrock was revealed,and the relationships among slope deformation,dam settlement,and MS activity were analyzed.The following research results have been obtained.The MS signal induced by dam fillinghas low energy and amplitude,short duration,and high frequency.The fracture of the bedrock was mainly shear failure.MS monitoring can predict deformation during blasting excavation and capture the large settlement that may occur during dam fillingin advance.Research findingshave demonstrated the significantapplication value of MS monitoring technology in predicting the risk of dam settlement and provide a reference for similar projects.展开更多
Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN model...Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.展开更多
巨噬细胞样细胞(macrophage-like cells, MLC)指起源、功能与巨噬细胞类似的免疫细胞,包括小胶质细胞、玻璃体细胞及巨噬细胞。将en face OCT显示层面设置在视网膜表明即可观测到视网膜表明的MLC(epiretinal MLC, eMLC),随后利用Image ...巨噬细胞样细胞(macrophage-like cells, MLC)指起源、功能与巨噬细胞类似的免疫细胞,包括小胶质细胞、玻璃体细胞及巨噬细胞。将en face OCT显示层面设置在视网膜表明即可观测到视网膜表明的MLC(epiretinal MLC, eMLC),随后利用Image J软件即可对细胞进行提取和量化。研究表明,eMLC在炎症情况下均可出现细胞募集及活化现象,但在不同眼底病中各具特点。在糖尿病视网膜病变、视网膜静脉阻塞等视网膜缺血缺氧性疾病中,eMLC密度越高,黄斑水肿可能越严重。此外,eMLC密度更高的视网膜静脉阻塞患者抗VEGF疗效更差,视力预后不佳,提示基于en face OCT的eMLC不仅可用于评估视网膜炎症情况,而且还能充当提示疾病疗效及预后的标志物。在葡萄膜炎等免疫炎症性疾病中,en face OCT亦可观测到eMLC密度、形态等改变。白塞病葡萄膜炎患者视网膜血管渗漏程度与eMLC密度相关性强,故eMLC密度可充当无创评估视网膜血管渗漏程度的新指标。然而,目前提取和量化eMLC的方法及标准不统一,降低了各研究间的可比性。因此,亟需制定统一的操作规范和评估标准。此外eMLC所代表的具体细胞类型及功能仍需进一步探究。未来,研究者可以利用en face OCT对眼底炎症地进行无创评估。基于en face OCT的eMLC还能作为基础研究与临床研究之间的桥梁,为揭示疾病的致病机制提供重要参考。展开更多
This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,an...This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.展开更多
Face recognition has emerged as one of the most prominent applications of image analysis and under-standing,gaining considerable attention in recent years.This growing interest is driven by two key factors:its extensi...Face recognition has emerged as one of the most prominent applications of image analysis and under-standing,gaining considerable attention in recent years.This growing interest is driven by two key factors:its extensive applications in law enforcement and the commercial domain,and the rapid advancement of practical technologies.Despite the significant advancements,modern recognition algorithms still struggle in real-world conditions such as varying lighting conditions,occlusion,and diverse facial postures.In such scenarios,human perception is still well above the capabilities of present technology.Using the systematic mapping study,this paper presents an in-depth review of face detection algorithms and face recognition algorithms,presenting a detailed survey of advancements made between 2015 and 2024.We analyze key methodologies,highlighting their strengths and restrictions in the application context.Additionally,we examine various datasets used for face detection/recognition datasets focusing on the task-specific applications,size,diversity,and complexity.By analyzing these algorithms and datasets,this survey works as a valuable resource for researchers,identifying the research gap in the field of face detection and recognition and outlining potential directions for future research.展开更多
Previous studies have identified two group-level processes,neural representations of interracial between-group difference and intraracial within-group similarity,that contribute to the racial categorization of faces.W...Previous studies have identified two group-level processes,neural representations of interracial between-group difference and intraracial within-group similarity,that contribute to the racial categorization of faces.What remains unclear is how the brain tracks race-related information that varies across different faces as an individual-level neural process involved in race perception.In three studies,we recorded functional MRI signals when Chinese adults performed different tasks on morphed faces in which proportions of pixels contributing to perceived racial identity(Asian vs White)and expression(pain vs neutral)varied independently.We found that,during a pain expression judgment task,tracking other-race and same-race-related information in perceived faces recruited the ventral occipitotemporal cortices and medial prefrontal/anterior temporal cortices,respectively.However,neural tracking of race-related information tended to be weakened during explicit race judgments on perceived faces.During a donation task,the medial prefrontal activity also tracked race-related information that distinguished between two perceived faces for altruistic decision-making and encoded the Euclidean distance between the two faces that predicted decision-making speeds.Our findings revealed task-dependent neural mechanisms underlying the tracking of race-related information during face perception and altruistic decision-making.展开更多
As an important sustainable energy source,Li-ion batteries have been widely used in mobile phones,electric vehicles,large-scale energy storage and aerospace.However,due to the inevitable safety risks of traditional li...As an important sustainable energy source,Li-ion batteries have been widely used in mobile phones,electric vehicles,large-scale energy storage and aerospace.However,due to the inevitable safety risks of traditional liquid Li-ion batteries,the use of all-solid-state batteries to replace organic liquid electrolytes has become one of the most effective ways to solve safety problem.Solid-state electrolyte(SSE)is the core part of allsolid-state Li-ion battery,and ideal SSE has the characteristics of high ionic conductivity,wide enough electrochemical stability window,suitable mechanical strength and excellent chemical stability,the first among which is particularly an essential prerequisite.While,so far only a few SSEs exhibit the Li ionic conductivities higher than 10^(-4) S/cm at room temperature.展开更多
Nitrogen doping has significant effects on the photocatalytic performance of ceria(CeO_(2)),and the possible synergistic effect with the inevitably introduced abundant oxygen vacancies(OVs)is of great significance for...Nitrogen doping has significant effects on the photocatalytic performance of ceria(CeO_(2)),and the possible synergistic effect with the inevitably introduced abundant oxygen vacancies(OVs)is of great significance for further investigation,and the specifically exposed crystal faces of CeO_(2)may have an impact on the performance of nitrogen doped CeO_(2).Herein,nitrogen-doped CeO_(2)with different morphologies and exposed crystal faces was prepared,and its performances in the photocatalytic degradation of tetracycline(TC)or hydrogen production via water splitting were evaluated.Density functional theory(DFT)was used to simulate the band structures,density of states,and oxygen defect properties of different CeO_(2)structures.It was found that nitrogen doping and OVs synergistically promoted the catalytic activity of nitrogen-doped CeO_(2).In addition,the exposed crystal faces of CeO_(2)have significant effects on the introduction of nitrogen and the ease of OV generation,as well as the synergistic effect of nitrogen doping with OVs.Among them,the rod-like nitrogen-doped CeO_(2)with exposed(110)face(R-CeO_(2)-NH_(3))showed a photocatalytic degradation ratio of 73.59%for TC and hydrogen production of 156.89μmol/g,outperforming other prepared photocatalysts.展开更多
Face antispoofing has received a lot of attention because it plays a role in strengthening the security of face recognition systems.Face recognition is commonly used for authentication in surveillance applications.How...Face antispoofing has received a lot of attention because it plays a role in strengthening the security of face recognition systems.Face recognition is commonly used for authentication in surveillance applications.However,attackers try to compromise these systems by using spoofing techniques such as using photos or videos of users to gain access to services or information.Many existing methods for face spoofing face difficulties when dealing with new scenarios,especially when there are variations in background,lighting,and other environmental factors.Recent advancements in deep learning with multi-modality methods have shown their effectiveness in face antispoofing,surpassing single-modal methods.However,these approaches often generate several features that can lead to issues with data dimensionality.In this study,we introduce a multimodal deep fusion network for face anti-spoofing that incorporates cross-axial attention and deep reinforcement learning techniques.This network operates at three patch levels and analyzes images from modalities(RGB,IR,and depth).Initially,our design includes an axial attention network(XANet)model that extracts deeply hidden features from multimodal images.Further,we use a bidirectional fusion technique that pays attention to both directions to combine features from each mode effectively.We further improve feature optimization by using the Enhanced Pity Beetle Optimization(EPBO)algorithm,which selects the features to address data dimensionality problems.Moreover,our proposed model employs a hybrid federated reinforcement learning(FDDRL)approach to detect and classify face anti-spoofing,achieving a more optimal tradeoff between detection rates and false positive rates.We evaluated the proposed approach on publicly available datasets,including CASIA-SURF and GREATFASD-S,and realized 98.985%and 97.956%classification accuracy,respectively.In addition,the current method outperforms other state-of-the-art methods in terms of precision,recall,and Fmeasures.Overall,the developed methodology boosts the effectiveness of our model in detecting various types of spoofing attempts.展开更多
In recent work,adversarial stickers are widely used to attack face recognition(FR)systems in the physical world.However,it is difficult to evaluate the performance of physical attacks because of the lack of volunteers...In recent work,adversarial stickers are widely used to attack face recognition(FR)systems in the physical world.However,it is difficult to evaluate the performance of physical attacks because of the lack of volunteers in the experiment.In this paper,a simple attack method called incomplete physical adversarial attack(IPAA)is proposed to simulate physical attacks.Different from the process of physical attacks,when an IPAA is conducted,a photo of the adversarial sticker is embedded into a facial image as the input to attack FR systems,which can obtain results similar to those of physical attacks without inviting any volunteers.The results show that IPAA has a higher similarity with physical attacks than digital attacks,indicating that IPAA is able to evaluate the performance of physical attacks.IPAA is effective in quantitatively measuring the impact of the sticker location on the results of attacks.展开更多
With extensive attention being paid to the potential environmental hazards of discarded face masks,catalytic pyrolysis technologies have been proposed to realize the valorization of wastes.However,recent catalyst sele...With extensive attention being paid to the potential environmental hazards of discarded face masks,catalytic pyrolysis technologies have been proposed to realize the valorization of wastes.However,recent catalyst selection and system design have focused solely on conversion efficiency,ignoring economic cost and potential life-cycle environmental damage.Here,we propose an economic-environmental hybrid pre-assessment method to help identify catalysts and reactors with less environmental impact and high economic returns among various routes to convert discarded face masks into carbon nanotubes(CNTs)and hydrogen.In catalyst selection,it was found that a widely known Fe-Ni catalyst exhibits higher catalytic activity than a cheaper Fe catalyst,potentially increasing the economic viability of the catalytic pyrolysis system by 38%-55%.The use of this catalyst also results in a carbon reduction of 4.12-10.20kilogram CO_(2) equivalent for 1 kilogram of discarded face masks,compared with the cheaper Fe catalyst.When the price of CNTs exceeds 1.49×10^(4) USD·t^(-1),microwave-assisted pyrolysis is the optimal choice due to its superior environmental performance(in terms of its life-cycle greenhouse gas reduction potential,eutrophication potential,and human toxicity)and economic benefits.In contrast,conventional heating pyrolysis may be a more economical option due to its good stability over 43 reaction regeneration cycles,as compared with a microwave-assisted pyrolysis catalyst with a higher conversion efficiency.This study connects foundational science with ecological economics to guide emerging technologies in their research stage toward technical efficiency,economic benefits,and environmental sustainability.展开更多
In interpersonal communication,the principle of politeness is an important communicative principle that is widely applied in people’s daily life.However,the communication patterns of the principle of politeness and f...In interpersonal communication,the principle of politeness is an important communicative principle that is widely applied in people’s daily life.However,the communication patterns of the principle of politeness and face theory in the travel planning process among friends still need further exploration.This study aims to analyze the specific manifestations of these principles in the communication patterns of travel planning among friends through a pragmatic interpretation of the principle of politeness and face theory,providing a new perspective for understanding linguistic behavior in interpersonal relationships.展开更多
文摘Based on Brown &Levinson's Face Threatening Acts and Geert Hofstede's Cultural Dimensions,this study is an analysis of Chinese college students' face needs in EFL class.In this study,the subjects are 116 freshmen,non-English majors.Selecting totally 60 students from them and dividing them into two groups according to their scores of College English Entrance Examination.The collected data from questionnaire are analyzed by statistical software SPSS16.0 version.The major findings from the analysis include the following:1) high-scored students and low-scored students have similar positive face needs;2) Weight of imposition,group tendency and uncertainty avoidance are used to exam students' negative face needs.According to the data in SPSS16.0,there is a difference between the two groups in terms of the weight of imposition.But the Independent-Samples T test of Sum of Questionnaire indicates that there is no distinct difference in the negative face needs between the two groups.
文摘The airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections.During the COVID-19 pandemic,the use of protective face masks was essential to reduce the risk of infection and spread of SARS-CoV-2.The face mask is able to significantly reduce the saliva droplet emission in front of the person.However,the use of masks also produces a particle leakage towards the back of the person,which could increase the infection risk of people behind the subject.Most of the experimental investigations applied invasive and/or complex experimental techniques to evaluate the face masks leakage.The primary objective of this study is to develop a novel,non-invasive methodology for assessing rearward droplet emission associated with the use of protective face masks.Specifically,a thermographic analysis of the thermal footprint released during ordinary and extraordinary respiratory activities is presented,evaluating the maximum temperature,the detection time,and the spread area of the thermal footprint.Both surgical and FFP2 face masks were tested.Two different subjects were involved in the experimentation to evaluate the influence of face conformation.The findings indicate that the area influenced by droplet dispersion is larger when wearing a surgical mask compared to an FFP2 mask,with the highest recorded temperatures observed for the surgical mask.The thermal footprint was found to be strongly dependent on individual facial morphology and mask fit.Notably,the FFP2 mask also altered the position of the thermal footprint,which was primarily confined to the region near the neck.
基金supported by the National Natural Science Foundation of China(Grant Nos.42077242 and 42171407)the Graduate Innovation Fund of Jilin University.
文摘Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.
基金Project(2024YFB3410402)supported by the National Key R&D Program of ChinaProject(52075558)supported by the National Natural Science Foundation of China+2 种基金Project(2021RC3012)supported by the Science and Technology Innovation Program of Hunan Province,ChinaProject(2023CXQD050)supported by the Central South University Innovation-Driven Research Program,ChinaProject(CX20230255)supported by the Fundamental Research Funds for the Central Universities,China。
文摘This study develops a contact performance-driven method for skiving face gear drives using a single cutter,eliminating the traditional need for separate cutters to reduce production costs and time.First,the mathematical models of the tooth flanks for the face gear drives are established based on the gear skiving processes.Then,load tooth contact analysis(LTCA)model is established to calculate the contact performance data.Next,a two-stage optimization model is employed to determine the optimal parameters of the cutting edge with improved contact performances.The effectiveness of this method is validated through simulations and rolling tests.Compared with the traditional method,the proposed method can machine both the face gear and its mating pinion with a single cutter.Simulation results show that the proposed method avoids tooth surface edge contact,with the maximum tooth surface contact stress reduced by 31.7%,the contact ratio decreases by 21.5%,and the transmission error increases by 22.3%.Rolling tests verify the consistency of tooth surface contact patterns between simulations and experiments.The proposed method provides a reference for the cutting edge design of skiving cutters for face gear pairs.
基金support of the National Natural Science Foundation of China(Grant Nos.52179116 and 51991392)the support of Key Deployment Projects of Chinese Academy of Sciences(Grant No.ZDRW-ZS-2021-3).
文摘Shield tunneling in saturated ground poses challenges due to the potential risk of ground collapse resulting from seepage force and inadequate support pressure.This study employed a laboratory model test and a theoretical validation to elucidate the mechanisms of face failure and subsequent ground collapse in saturated ground during slurry pressure-balanced shield(SPBS)tunneling operations.A slurry circulation system was developed to ensure steady shield tunneling and to replicate the phenomena of ground collapse.Investigations into shield tunneling parameters and ground responses,including soil pressure,pore water pressure,and surface subsidence,were conducted to understand the mechanisms of face failure and subsequent ground collapse.The theoretical solution for the critical collapse pressure of the tunnel face,based on the rotational failure mechanism,was validated through the comparison with the experimentally determined critical collapse pressure.The results indicate that:(1)appropriate adjustments of tunneling parameters are crucial for promoting filtercake formation,maintaining chamber pressure,and minimizing ground subsidence;(2)chamber pressure,soil pressure,pore water pressure,and ground subsidence are closely correlated with shield tunneling parameters and the formation of filter cake;(3)ground collapse follows a continuous failure mode due to the destruction of filtercake and the decrease in chamber pressure;(4)the soil pressure at the cutterhead is more sensitive to disturbances from shield tunneling than chamber pressure;and(5)experimentally determined critical collapse pressures is consistent with the theoretical solution of limit analysis.
基金support from the Joint Funds of the National Natural Science Foundation of China(Grant No.42177143)the National Natural Science Foundation of China(Grant No.U23A2060).
文摘Many hydropower projects have been constructed in Southwest China with the strategic goal of achieving carbon neutrality.Most of these hydropower projects utilize concrete face rockfilldams(CFRDs)built on a deep overburden layer.The deep overburden layer causes uneven settlement between the overburden layer and the dam,which poses a serious threat to the safety of both the construction and operation of the dam.In this study,microseismic(MS)monitoring technology was employed for the firsttime in the fieldof dam fillingengineering,allowing for the real-time monitoring of microfracture in the bedrock during dam construction.The time-frequency analysis method was used to summarize the MS waveform characteristics induced by dam filling.The fracture mechanism of bedrock was revealed,and the relationships among slope deformation,dam settlement,and MS activity were analyzed.The following research results have been obtained.The MS signal induced by dam fillinghas low energy and amplitude,short duration,and high frequency.The fracture of the bedrock was mainly shear failure.MS monitoring can predict deformation during blasting excavation and capture the large settlement that may occur during dam fillingin advance.Research findingshave demonstrated the significantapplication value of MS monitoring technology in predicting the risk of dam settlement and provide a reference for similar projects.
基金funded by Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),Faculty of Engineering and IT,University of Technology Sydney.Moreover,Ongoing Research Funding Program(ORF-2025-14)King Saud University,Riyadh,Saudi Arabia,under Project ORF-2025-。
文摘Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.
文摘巨噬细胞样细胞(macrophage-like cells, MLC)指起源、功能与巨噬细胞类似的免疫细胞,包括小胶质细胞、玻璃体细胞及巨噬细胞。将en face OCT显示层面设置在视网膜表明即可观测到视网膜表明的MLC(epiretinal MLC, eMLC),随后利用Image J软件即可对细胞进行提取和量化。研究表明,eMLC在炎症情况下均可出现细胞募集及活化现象,但在不同眼底病中各具特点。在糖尿病视网膜病变、视网膜静脉阻塞等视网膜缺血缺氧性疾病中,eMLC密度越高,黄斑水肿可能越严重。此外,eMLC密度更高的视网膜静脉阻塞患者抗VEGF疗效更差,视力预后不佳,提示基于en face OCT的eMLC不仅可用于评估视网膜炎症情况,而且还能充当提示疾病疗效及预后的标志物。在葡萄膜炎等免疫炎症性疾病中,en face OCT亦可观测到eMLC密度、形态等改变。白塞病葡萄膜炎患者视网膜血管渗漏程度与eMLC密度相关性强,故eMLC密度可充当无创评估视网膜血管渗漏程度的新指标。然而,目前提取和量化eMLC的方法及标准不统一,降低了各研究间的可比性。因此,亟需制定统一的操作规范和评估标准。此外eMLC所代表的具体细胞类型及功能仍需进一步探究。未来,研究者可以利用en face OCT对眼底炎症地进行无创评估。基于en face OCT的eMLC还能作为基础研究与临床研究之间的桥梁,为揭示疾病的致病机制提供重要参考。
基金Supported by the Fundamental Research Funds for the Central Universities(2024300443)the Natural Science Foundation of Jiangsu Province(BK20241224).
文摘This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.
文摘Face recognition has emerged as one of the most prominent applications of image analysis and under-standing,gaining considerable attention in recent years.This growing interest is driven by two key factors:its extensive applications in law enforcement and the commercial domain,and the rapid advancement of practical technologies.Despite the significant advancements,modern recognition algorithms still struggle in real-world conditions such as varying lighting conditions,occlusion,and diverse facial postures.In such scenarios,human perception is still well above the capabilities of present technology.Using the systematic mapping study,this paper presents an in-depth review of face detection algorithms and face recognition algorithms,presenting a detailed survey of advancements made between 2015 and 2024.We analyze key methodologies,highlighting their strengths and restrictions in the application context.Additionally,we examine various datasets used for face detection/recognition datasets focusing on the task-specific applications,size,diversity,and complexity.By analyzing these algorithms and datasets,this survey works as a valuable resource for researchers,identifying the research gap in the field of face detection and recognition and outlining potential directions for future research.
基金supported by the National Natural Science Foundation of China(32230043 and 32371092)the Ministry of Science and Technology of China(2019YFA0707103)+1 种基金Das Chinesisch-Deutsche Zentrum für Wissenschaftsförderung(M-0093)the High-performance Computing Platform of Peking University.
文摘Previous studies have identified two group-level processes,neural representations of interracial between-group difference and intraracial within-group similarity,that contribute to the racial categorization of faces.What remains unclear is how the brain tracks race-related information that varies across different faces as an individual-level neural process involved in race perception.In three studies,we recorded functional MRI signals when Chinese adults performed different tasks on morphed faces in which proportions of pixels contributing to perceived racial identity(Asian vs White)and expression(pain vs neutral)varied independently.We found that,during a pain expression judgment task,tracking other-race and same-race-related information in perceived faces recruited the ventral occipitotemporal cortices and medial prefrontal/anterior temporal cortices,respectively.However,neural tracking of race-related information tended to be weakened during explicit race judgments on perceived faces.During a donation task,the medial prefrontal activity also tracked race-related information that distinguished between two perceived faces for altruistic decision-making and encoded the Euclidean distance between the two faces that predicted decision-making speeds.Our findings revealed task-dependent neural mechanisms underlying the tracking of race-related information during face perception and altruistic decision-making.
基金supported by the Natural Science Foundation of Shandong Province(No.ZR2020MB049)the Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai(No.AMGM2023A07)。
文摘As an important sustainable energy source,Li-ion batteries have been widely used in mobile phones,electric vehicles,large-scale energy storage and aerospace.However,due to the inevitable safety risks of traditional liquid Li-ion batteries,the use of all-solid-state batteries to replace organic liquid electrolytes has become one of the most effective ways to solve safety problem.Solid-state electrolyte(SSE)is the core part of allsolid-state Li-ion battery,and ideal SSE has the characteristics of high ionic conductivity,wide enough electrochemical stability window,suitable mechanical strength and excellent chemical stability,the first among which is particularly an essential prerequisite.While,so far only a few SSEs exhibit the Li ionic conductivities higher than 10^(-4) S/cm at room temperature.
基金Project(52164025)supported by the National Natural Science Foundation of ChinaProject([2020]1Y219)supported by the Basic Research Program from the Science&Technology Department of Guizhou Province,China+2 种基金Project([2019]30)supported by the Training Project from Guizhou University,ChinaProject([2023]04)supported by the Guizhou University Innovation Talent Team Project,ChinaProject([2022]041)supported by the Natural Science Research Project of Guizhou Provincial Department of Education,China。
文摘Nitrogen doping has significant effects on the photocatalytic performance of ceria(CeO_(2)),and the possible synergistic effect with the inevitably introduced abundant oxygen vacancies(OVs)is of great significance for further investigation,and the specifically exposed crystal faces of CeO_(2)may have an impact on the performance of nitrogen doped CeO_(2).Herein,nitrogen-doped CeO_(2)with different morphologies and exposed crystal faces was prepared,and its performances in the photocatalytic degradation of tetracycline(TC)or hydrogen production via water splitting were evaluated.Density functional theory(DFT)was used to simulate the band structures,density of states,and oxygen defect properties of different CeO_(2)structures.It was found that nitrogen doping and OVs synergistically promoted the catalytic activity of nitrogen-doped CeO_(2).In addition,the exposed crystal faces of CeO_(2)have significant effects on the introduction of nitrogen and the ease of OV generation,as well as the synergistic effect of nitrogen doping with OVs.Among them,the rod-like nitrogen-doped CeO_(2)with exposed(110)face(R-CeO_(2)-NH_(3))showed a photocatalytic degradation ratio of 73.59%for TC and hydrogen production of 156.89μmol/g,outperforming other prepared photocatalysts.
文摘Face antispoofing has received a lot of attention because it plays a role in strengthening the security of face recognition systems.Face recognition is commonly used for authentication in surveillance applications.However,attackers try to compromise these systems by using spoofing techniques such as using photos or videos of users to gain access to services or information.Many existing methods for face spoofing face difficulties when dealing with new scenarios,especially when there are variations in background,lighting,and other environmental factors.Recent advancements in deep learning with multi-modality methods have shown their effectiveness in face antispoofing,surpassing single-modal methods.However,these approaches often generate several features that can lead to issues with data dimensionality.In this study,we introduce a multimodal deep fusion network for face anti-spoofing that incorporates cross-axial attention and deep reinforcement learning techniques.This network operates at three patch levels and analyzes images from modalities(RGB,IR,and depth).Initially,our design includes an axial attention network(XANet)model that extracts deeply hidden features from multimodal images.Further,we use a bidirectional fusion technique that pays attention to both directions to combine features from each mode effectively.We further improve feature optimization by using the Enhanced Pity Beetle Optimization(EPBO)algorithm,which selects the features to address data dimensionality problems.Moreover,our proposed model employs a hybrid federated reinforcement learning(FDDRL)approach to detect and classify face anti-spoofing,achieving a more optimal tradeoff between detection rates and false positive rates.We evaluated the proposed approach on publicly available datasets,including CASIA-SURF and GREATFASD-S,and realized 98.985%and 97.956%classification accuracy,respectively.In addition,the current method outperforms other state-of-the-art methods in terms of precision,recall,and Fmeasures.Overall,the developed methodology boosts the effectiveness of our model in detecting various types of spoofing attempts.
文摘In recent work,adversarial stickers are widely used to attack face recognition(FR)systems in the physical world.However,it is difficult to evaluate the performance of physical attacks because of the lack of volunteers in the experiment.In this paper,a simple attack method called incomplete physical adversarial attack(IPAA)is proposed to simulate physical attacks.Different from the process of physical attacks,when an IPAA is conducted,a photo of the adversarial sticker is embedded into a facial image as the input to attack FR systems,which can obtain results similar to those of physical attacks without inviting any volunteers.The results show that IPAA has a higher similarity with physical attacks than digital attacks,indicating that IPAA is able to evaluate the performance of physical attacks.IPAA is effective in quantitatively measuring the impact of the sticker location on the results of attacks.
基金supported by the National Natural Science Foundation of China(52076099,52306257,and 72293601)。
文摘With extensive attention being paid to the potential environmental hazards of discarded face masks,catalytic pyrolysis technologies have been proposed to realize the valorization of wastes.However,recent catalyst selection and system design have focused solely on conversion efficiency,ignoring economic cost and potential life-cycle environmental damage.Here,we propose an economic-environmental hybrid pre-assessment method to help identify catalysts and reactors with less environmental impact and high economic returns among various routes to convert discarded face masks into carbon nanotubes(CNTs)and hydrogen.In catalyst selection,it was found that a widely known Fe-Ni catalyst exhibits higher catalytic activity than a cheaper Fe catalyst,potentially increasing the economic viability of the catalytic pyrolysis system by 38%-55%.The use of this catalyst also results in a carbon reduction of 4.12-10.20kilogram CO_(2) equivalent for 1 kilogram of discarded face masks,compared with the cheaper Fe catalyst.When the price of CNTs exceeds 1.49×10^(4) USD·t^(-1),microwave-assisted pyrolysis is the optimal choice due to its superior environmental performance(in terms of its life-cycle greenhouse gas reduction potential,eutrophication potential,and human toxicity)and economic benefits.In contrast,conventional heating pyrolysis may be a more economical option due to its good stability over 43 reaction regeneration cycles,as compared with a microwave-assisted pyrolysis catalyst with a higher conversion efficiency.This study connects foundational science with ecological economics to guide emerging technologies in their research stage toward technical efficiency,economic benefits,and environmental sustainability.
文摘In interpersonal communication,the principle of politeness is an important communicative principle that is widely applied in people’s daily life.However,the communication patterns of the principle of politeness and face theory in the travel planning process among friends still need further exploration.This study aims to analyze the specific manifestations of these principles in the communication patterns of travel planning among friends through a pragmatic interpretation of the principle of politeness and face theory,providing a new perspective for understanding linguistic behavior in interpersonal relationships.
