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
Detecting faces under occlusion remains a significant challenge in computer vision due to variations caused by masks,sunglasses,and other obstructions.Addressing this issue is crucial for applications such as surveill...Detecting faces under occlusion remains a significant challenge in computer vision due to variations caused by masks,sunglasses,and other obstructions.Addressing this issue is crucial for applications such as surveillance,biometric authentication,and human-computer interaction.This paper provides a comprehensive review of face detection techniques developed to handle occluded faces.Studies are categorized into four main approaches:feature-based,machine learning-based,deep learning-based,and hybrid methods.We analyzed state-of-the-art studies within each category,examining their methodologies,strengths,and limitations based on widely used benchmark datasets,highlighting their adaptability to partial and severe occlusions.The review also identifies key challenges,including dataset diversity,model generalization,and computational efficiency.Our findings reveal that deep learning methods dominate recent studies,benefiting from their ability to extract hierarchical features and handle complex occlusion patterns.More recently,researchers have increasingly explored Transformer-based architectures,such as Vision Transformer(ViT)and Swin Transformer,to further improve detection robustness under challenging occlusion scenarios.In addition,hybrid approaches,which aim to combine traditional andmodern techniques,are emerging as a promising direction for improving robustness.This review provides valuable insights for researchers aiming to develop more robust face detection systems and for practitioners seeking to deploy reliable solutions in real-world,occlusionprone environments.Further improvements and the proposal of broader datasets are required to developmore scalable,robust,and efficient models that can handle complex occlusions in real-world scenarios.展开更多
Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantita...Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.展开更多
To address the seismic face stability challenges encountered in urban and subsea tunnel construction,an efficient probabilistic analysis framework for shield tunnel faces under seismic conditions is proposed.Based on ...To address the seismic face stability challenges encountered in urban and subsea tunnel construction,an efficient probabilistic analysis framework for shield tunnel faces under seismic conditions is proposed.Based on the upper-bound theory of limit analysis,an improved three-dimensional discrete deterministic mechanism,accounting for the heterogeneous nature of soil media,is formulated to evaluate seismic face stability.The metamodel of failure probabilistic assessments for seismic tunnel faces is constructed by integrating the sparse polynomial chaos expansion method(SPCE)with the modified pseudo-dynamic approach(MPD).The improved deterministic model is validated by comparing with published literature and numerical simulations results,and the SPCE-MPD metamodel is examined with the traditional MCS method.Based on the SPCE-MPD metamodels,the seismic effects on face failure probability and reliability index are presented and the global sensitivity analysis(GSA)is involved to reflect the influence order of seismic action parameters.Finally,the proposed approach is tested to be effective by a engineering case of the Chengdu outer ring tunnel.The results show that higher uncertainty of seismic response on face stability should be noticed in areas with intense earthquakes and variation of seismic wave velocity has the most profound influence on tunnel face stability.展开更多
Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the sim...Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled.This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image.Methods First,we transferred an input real-world portrait to a stylized cartoon image using StyleGAN.We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture.Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision.Finally,we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer.Conclusions Compared with prior arts,the qualitative and quantitative results show that our method achieves better accuracy,aesthetics,and similarity criteria.Furthermore,we demonstrated the capability of the proposed 3D model for real-time facial animation.展开更多
Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications.In this paper,we propose an efficient approach for automating 3D facial wound seg...Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications.In this paper,we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network.Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions.To achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the trainedmodels.The selectedmodel demonstrates exceptional segmentation performance for complex 3D facial wounds.Furthermore,based on the segmentation model,we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous study.Our method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous method.From this result,we use 3D printing technology to illustrate the shape of the wound filling.The outcomes of this study have significant implications for physicians involved in preoperative planning and intervention design.By automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient outcomes.Additionally,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue implants.Our source code is available at https://github.com/SIMOGroup/WoundFilling3D.展开更多
In the digital era,emojis have enriched the way people communicate and research on emojis explosively increased in recent years.However,few noticed their functions from the neurocognitive perspective,especially their ...In the digital era,emojis have enriched the way people communicate and research on emojis explosively increased in recent years.However,few noticed their functions from the neurocognitive perspective,especially their similarities and differences with facial expressions in traditional face-to-face communication.To fill this gap,we conducted a Meta-analysis with 25 independent effect sizes from previous experimental studies.The present study shows that emojis have slight advantages in processing efficiency,which might be attributed to their simplicity in design,namely the omission of complex facial features,but the difference between emoji and face processing is not significant.In addition,emotional valence and experimental methods do not have significant influences,which suggests that emojis are equally effective as human faces in emotional expression.The current research contributes to the knowledge in digital communication and the crucial role played by emojis therein.展开更多
In order to meet engineering needs of Chinese underground coal mines,a new dust-collecting fan,a device of dust separated by centrifugal force in driven cyclone passageway(DCCP)was designed.In centrifugal dust removal...In order to meet engineering needs of Chinese underground coal mines,a new dust-collecting fan,a device of dust separated by centrifugal force in driven cyclone passageway(DCCP)was designed.In centrifugal dust removal section(CDRS)of DCCP,a general equation is derived from the principle of force equilibrium.According to CDRS structure parameters and fan running parameters,the general equation is simplified,and the simplest equation is calculated numerically by MATLAB.The calculation results illustrate that increasing quantity of air current is against dust removal,but it is beneficial to dust removal by increasing the radius of driven spiral blade and increasing the particle diameter of coal dust.The conclusions show that the dust-collecting structure parameters coupled with the fan running parameters is a novel optimization approach to dust-collection fan for working and heading faces,which is especially suitable for Chinese underground mines.展开更多
By employing numerical modeling, similar material simulation and comprehen-sive field observation, investigations were made and patterns were obtained governing surrounding-rock stress distribution and strata behavior...By employing numerical modeling, similar material simulation and comprehen-sive field observation, investigations were made and patterns were obtained governing surrounding-rock stress distribution and strata behaviors. It shows that patterns governing displacement of FMC roadway surrounding rocks and those governing deformation of supports are basically the same along the strike, but the displacements vary greatly. The front stresses affect greater areas than the lateral stresses and their limit widths of equilib-rium zones and K are almost similar. The stress transmits very deep. Our findings offer scientific basis on which to determine parameters for coal pillar retaining and for roadway out-laying, thus increasing the recovery ratio and improving the maintenance of roadway.展开更多
Schwann cells are glial cells that are responsible for the synthesis and maintenance of the myelin sheath in the peripheral nerve system. Under pathological conditions, such as physical nerve injury and inflammatory n...Schwann cells are glial cells that are responsible for the synthesis and maintenance of the myelin sheath in the peripheral nerve system. Under pathological conditions, such as physical nerve injury and inflammatory neuropathies, Schwann cells undergo a substantial phenotype transformation that is not related to their intended function. For example, Schwann cells dedifferentiate into immature states and thereby cease to express myelin genes after nerve injury.展开更多
1.Introduction Spectacular advances have been made in the atmospheric sciences on a global level during a period of one hundred years or more,which is arguably most evident through"the quiet revolution of numeric...1.Introduction Spectacular advances have been made in the atmospheric sciences on a global level during a period of one hundred years or more,which is arguably most evident through"the quiet revolution of numerical weather prediction"(Bauer et展开更多
Objective Category-specific recognition and naming deficits have been observed in a variety of patient populations. However, the category-specific cortices for naming famous faces, animals and man-made objects remain ...Objective Category-specific recognition and naming deficits have been observed in a variety of patient populations. However, the category-specific cortices for naming famous faces, animals and man-made objects remain controversial. The present study aimed to study the specific areas involved in naming pictures of these 3 categories using functional magnetic resonance imaging. Methods Functional images were analyzed using statistical parametric mapping and the 3 different contrasts were evaluated using t statistics by comparing the naming tasks to their baselines.The contrast images were entered into a random-effects group level analysis.The results were reported in Montreal Neurological Institute co-ordinates,and anatomical regions were identified using an automated anatomical labeling method with XJview 8.Results Naming famous faces caused more activation in the bilateral head of the hippocampus and amygdala with significant left dominance. Bilateral activation of pars triangularis and pars opercularis in the naming of famous faces was also revealed. Naming animals evoked greater responses in the left supplementary motor area, while naming man-made objects evoked more in the left premotor area,left pars orbitalis and right supplementary motor area. The extent of bilateral fusiform gyri activation by naming man-made objects was much larger than that by naming of famous faces or animals.Even in the overlapping sites of activation,some differences among the categories were found for activation in the fusiform gyri.Conclusion The cortices involved in the naming process vary with the naming of famous faces,animals and man-made objects.This finding suggests that different categories of pictures should be used during intra-operative language mapping to generate a broader map of language function, in order to minimize the incidence of false-negative stimulation and permanent post-operative deficits.展开更多
As the information network plays a more and more important role globally, the traditional network theories and technologies, especially those related to network security, can no longer meet the network development req...As the information network plays a more and more important role globally, the traditional network theories and technologies, especially those related to network security, can no longer meet the network development requirements. Offering the system with secure and trusted services has become a new focus in network research. This paper first discusses the meaning of and aspects involved in the trusted network. According to this paper, the trusted network should be a network where the network’s and users’ behaviors and their results are always predicted and manageable. The trustworthiness of a network mainly involves three aspects: service provider, information transmission and terminal user. This paper also analyzes the trusted network in terms of trusted model for network/user behaviors, architecture of trusted network, service survivability and network manageability, which is designed to give ideas on solving the problems that may be faced in developing the trusted network.展开更多
In recent years,with the rapid growth of generative adversarial networks(GANs),a photo-realistic face can be easily generated from a random vector.Moreover,the faces generated by advanced GANs are very realistic.It is...In recent years,with the rapid growth of generative adversarial networks(GANs),a photo-realistic face can be easily generated from a random vector.Moreover,the faces generated by advanced GANs are very realistic.It is reasonable to acknowledge that even a well-trained viewer has difficulties to distinguish artificial from real faces.Therefore,detecting the face generated by GANs is a necessary work.This paper mainly introduces some methods to detect GAN-generated fake faces,and analyzes the advantages and disadvantages of these models based on the network structure and evaluation indexes,and the results obtained in the respective data sets.On this basis,the challenges faced in this field and future research directions are discussed.展开更多
Convolutional Neural Networks(CNN)have been successfully employed in the field of image classification.However,CNN trained using images from several years ago may be unable to identify how such images have changed ove...Convolutional Neural Networks(CNN)have been successfully employed in the field of image classification.However,CNN trained using images from several years ago may be unable to identify how such images have changed over time.Cross-age face recognition is,therefore,a substantial challenge.Several efforts have been made to resolve facial changes over time utilizing recurrent neural networks(RNN)with CNN.The structure of RNN contains hidden contextual information in a hidden state to transfer a state in the previous step to the next step.This paper proposes a novel model called Hidden State-CNN(HSCNN).This adds to CNN a convolution layer of the hidden state saved as a parameter in the previous step and requires no more computing resources than CNN.The previous CNN-RNN models perform CNN and RNN,separately and then merge the results.Therefore,their systems consume twice the memory resources and CPU time,compared with the HSCNN system,which works the same as CNN only.HSCNN consists of 3 types of models.All models load hidden state ht−1 from parameters of the previous step and save ht as a parameter for the next step.In addition,modelB adds ht−1 to x,which is the previous output.The summation of ht−1 and x is multiplied by weight W.In model-C the convolution layer has two weights:W1 and W2.Training HSCNN with faces of the previous step is for testing faces of the next step in the experiment.That is,HSCNN trained with past facial data is then used to verify future data.It has been found to exhibit 10 percent greater accuracy than traditional CNN with a celeb face database.展开更多
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.
基金funded by A’Sharqiyah University,Sultanate of Oman,under Research Project grant number(BFP/RGP/ICT/22/490).
文摘Detecting faces under occlusion remains a significant challenge in computer vision due to variations caused by masks,sunglasses,and other obstructions.Addressing this issue is crucial for applications such as surveillance,biometric authentication,and human-computer interaction.This paper provides a comprehensive review of face detection techniques developed to handle occluded faces.Studies are categorized into four main approaches:feature-based,machine learning-based,deep learning-based,and hybrid methods.We analyzed state-of-the-art studies within each category,examining their methodologies,strengths,and limitations based on widely used benchmark datasets,highlighting their adaptability to partial and severe occlusions.The review also identifies key challenges,including dataset diversity,model generalization,and computational efficiency.Our findings reveal that deep learning methods dominate recent studies,benefiting from their ability to extract hierarchical features and handle complex occlusion patterns.More recently,researchers have increasingly explored Transformer-based architectures,such as Vision Transformer(ViT)and Swin Transformer,to further improve detection robustness under challenging occlusion scenarios.In addition,hybrid approaches,which aim to combine traditional andmodern techniques,are emerging as a promising direction for improving robustness.This review provides valuable insights for researchers aiming to develop more robust face detection systems and for practitioners seeking to deploy reliable solutions in real-world,occlusionprone environments.Further improvements and the proposal of broader datasets are required to developmore scalable,robust,and efficient models that can handle complex occlusions in real-world scenarios.
基金supported by the National Natural Science Foundation of China(Nos.52279107 and 52379106)the Qingdao Guoxin Jiaozhou Bay Second Submarine Tunnel Co.,Ltd.,the Academician and Expert Workstation of Yunnan Province(No.202205AF150015)the Science and Technology Innovation Project of YCIC Group Co.,Ltd.(No.YCIC-YF-2022-15)。
文摘Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.
基金Project([2018]3010)supported by the Guizhou Provincial Science and Technology Major Project,China。
文摘To address the seismic face stability challenges encountered in urban and subsea tunnel construction,an efficient probabilistic analysis framework for shield tunnel faces under seismic conditions is proposed.Based on the upper-bound theory of limit analysis,an improved three-dimensional discrete deterministic mechanism,accounting for the heterogeneous nature of soil media,is formulated to evaluate seismic face stability.The metamodel of failure probabilistic assessments for seismic tunnel faces is constructed by integrating the sparse polynomial chaos expansion method(SPCE)with the modified pseudo-dynamic approach(MPD).The improved deterministic model is validated by comparing with published literature and numerical simulations results,and the SPCE-MPD metamodel is examined with the traditional MCS method.Based on the SPCE-MPD metamodels,the seismic effects on face failure probability and reliability index are presented and the global sensitivity analysis(GSA)is involved to reflect the influence order of seismic action parameters.Finally,the proposed approach is tested to be effective by a engineering case of the Chengdu outer ring tunnel.The results show that higher uncertainty of seismic response on face stability should be noticed in areas with intense earthquakes and variation of seismic wave velocity has the most profound influence on tunnel face stability.
文摘Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled.This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image.Methods First,we transferred an input real-world portrait to a stylized cartoon image using StyleGAN.We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture.Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision.Finally,we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer.Conclusions Compared with prior arts,the qualitative and quantitative results show that our method achieves better accuracy,aesthetics,and similarity criteria.Furthermore,we demonstrated the capability of the proposed 3D model for real-time facial animation.
文摘Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications.In this paper,we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network.Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions.To achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the trainedmodels.The selectedmodel demonstrates exceptional segmentation performance for complex 3D facial wounds.Furthermore,based on the segmentation model,we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous study.Our method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous method.From this result,we use 3D printing technology to illustrate the shape of the wound filling.The outcomes of this study have significant implications for physicians involved in preoperative planning and intervention design.By automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient outcomes.Additionally,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue implants.Our source code is available at https://github.com/SIMOGroup/WoundFilling3D.
基金supported by Science Foundation of China University of Petroleum,Beijing(No.2462023YXZZ006)Undergraduate Key Teaching Reform Project(30GK2312).
文摘In the digital era,emojis have enriched the way people communicate and research on emojis explosively increased in recent years.However,few noticed their functions from the neurocognitive perspective,especially their similarities and differences with facial expressions in traditional face-to-face communication.To fill this gap,we conducted a Meta-analysis with 25 independent effect sizes from previous experimental studies.The present study shows that emojis have slight advantages in processing efficiency,which might be attributed to their simplicity in design,namely the omission of complex facial features,but the difference between emoji and face processing is not significant.In addition,emotional valence and experimental methods do not have significant influences,which suggests that emojis are equally effective as human faces in emotional expression.The current research contributes to the knowledge in digital communication and the crucial role played by emojis therein.
基金supported by the National Natural Science Foundation of China and Shenhua Group Corpo-ration Limited(U1361118)the Hunan Provincial Natural Science Foundation of China(13JJ8016)+2 种基金the State Key Laboratory for GeoMechanics and Deep Underground Engineering(SKLG-DUEK1018)the Open Research Fund Program of Hunan Province Key Laboratory of Safe Mining Techniques of Coal Mines(Hunan University of Science and Technology)(201105)the Project of Outstanding(Postgraduate)Dissertation Growth Foundation of HNUST(SNY005).
文摘In order to meet engineering needs of Chinese underground coal mines,a new dust-collecting fan,a device of dust separated by centrifugal force in driven cyclone passageway(DCCP)was designed.In centrifugal dust removal section(CDRS)of DCCP,a general equation is derived from the principle of force equilibrium.According to CDRS structure parameters and fan running parameters,the general equation is simplified,and the simplest equation is calculated numerically by MATLAB.The calculation results illustrate that increasing quantity of air current is against dust removal,but it is beneficial to dust removal by increasing the radius of driven spiral blade and increasing the particle diameter of coal dust.The conclusions show that the dust-collecting structure parameters coupled with the fan running parameters is a novel optimization approach to dust-collection fan for working and heading faces,which is especially suitable for Chinese underground mines.
基金Supported by the Natural Sciences of Anhui Provincial Education Division(2002kj286ZD,01044403)
文摘By employing numerical modeling, similar material simulation and comprehen-sive field observation, investigations were made and patterns were obtained governing surrounding-rock stress distribution and strata behaviors. It shows that patterns governing displacement of FMC roadway surrounding rocks and those governing deformation of supports are basically the same along the strike, but the displacements vary greatly. The front stresses affect greater areas than the lateral stresses and their limit widths of equilib-rium zones and K are almost similar. The stress transmits very deep. Our findings offer scientific basis on which to determine parameters for coal pillar retaining and for roadway out-laying, thus increasing the recovery ratio and improving the maintenance of roadway.
基金supported by research funds from Dong-A University
文摘Schwann cells are glial cells that are responsible for the synthesis and maintenance of the myelin sheath in the peripheral nerve system. Under pathological conditions, such as physical nerve injury and inflammatory neuropathies, Schwann cells undergo a substantial phenotype transformation that is not related to their intended function. For example, Schwann cells dedifferentiate into immature states and thereby cease to express myelin genes after nerve injury.
基金Support for this study was provided by the “Waves to Weather” initiative (SFB/TRR 165) of the German Research Foundation (DFG)
文摘1.Introduction Spectacular advances have been made in the atmospheric sciences on a global level during a period of one hundred years or more,which is arguably most evident through"the quiet revolution of numerical weather prediction"(Bauer et
基金supported bythe Foundation of Science and Technology Program of Guangdong Province,China(No.2008A030201021)the Natural Science Foundation of Guangdong Province,China(No.10151001002000010)
文摘Objective Category-specific recognition and naming deficits have been observed in a variety of patient populations. However, the category-specific cortices for naming famous faces, animals and man-made objects remain controversial. The present study aimed to study the specific areas involved in naming pictures of these 3 categories using functional magnetic resonance imaging. Methods Functional images were analyzed using statistical parametric mapping and the 3 different contrasts were evaluated using t statistics by comparing the naming tasks to their baselines.The contrast images were entered into a random-effects group level analysis.The results were reported in Montreal Neurological Institute co-ordinates,and anatomical regions were identified using an automated anatomical labeling method with XJview 8.Results Naming famous faces caused more activation in the bilateral head of the hippocampus and amygdala with significant left dominance. Bilateral activation of pars triangularis and pars opercularis in the naming of famous faces was also revealed. Naming animals evoked greater responses in the left supplementary motor area, while naming man-made objects evoked more in the left premotor area,left pars orbitalis and right supplementary motor area. The extent of bilateral fusiform gyri activation by naming man-made objects was much larger than that by naming of famous faces or animals.Even in the overlapping sites of activation,some differences among the categories were found for activation in the fusiform gyri.Conclusion The cortices involved in the naming process vary with the naming of famous faces,animals and man-made objects.This finding suggests that different categories of pictures should be used during intra-operative language mapping to generate a broader map of language function, in order to minimize the incidence of false-negative stimulation and permanent post-operative deficits.
基金the National NaturalScience Foundation of China under Grant90412012 and 60673187
文摘As the information network plays a more and more important role globally, the traditional network theories and technologies, especially those related to network security, can no longer meet the network development requirements. Offering the system with secure and trusted services has become a new focus in network research. This paper first discusses the meaning of and aspects involved in the trusted network. According to this paper, the trusted network should be a network where the network’s and users’ behaviors and their results are always predicted and manageable. The trustworthiness of a network mainly involves three aspects: service provider, information transmission and terminal user. This paper also analyzes the trusted network in terms of trusted model for network/user behaviors, architecture of trusted network, service survivability and network manageability, which is designed to give ideas on solving the problems that may be faced in developing the trusted network.
基金supported by National Natural Science Foundation of China(62072251).
文摘In recent years,with the rapid growth of generative adversarial networks(GANs),a photo-realistic face can be easily generated from a random vector.Moreover,the faces generated by advanced GANs are very realistic.It is reasonable to acknowledge that even a well-trained viewer has difficulties to distinguish artificial from real faces.Therefore,detecting the face generated by GANs is a necessary work.This paper mainly introduces some methods to detect GAN-generated fake faces,and analyzes the advantages and disadvantages of these models based on the network structure and evaluation indexes,and the results obtained in the respective data sets.On this basis,the challenges faced in this field and future research directions are discussed.
基金This work was supported by the National Research Foundation of Korea(NRF)grant in 2019(NRF-2019R1G1A1004773).
文摘Convolutional Neural Networks(CNN)have been successfully employed in the field of image classification.However,CNN trained using images from several years ago may be unable to identify how such images have changed over time.Cross-age face recognition is,therefore,a substantial challenge.Several efforts have been made to resolve facial changes over time utilizing recurrent neural networks(RNN)with CNN.The structure of RNN contains hidden contextual information in a hidden state to transfer a state in the previous step to the next step.This paper proposes a novel model called Hidden State-CNN(HSCNN).This adds to CNN a convolution layer of the hidden state saved as a parameter in the previous step and requires no more computing resources than CNN.The previous CNN-RNN models perform CNN and RNN,separately and then merge the results.Therefore,their systems consume twice the memory resources and CPU time,compared with the HSCNN system,which works the same as CNN only.HSCNN consists of 3 types of models.All models load hidden state ht−1 from parameters of the previous step and save ht as a parameter for the next step.In addition,modelB adds ht−1 to x,which is the previous output.The summation of ht−1 and x is multiplied by weight W.In model-C the convolution layer has two weights:W1 and W2.Training HSCNN with faces of the previous step is for testing faces of the next step in the experiment.That is,HSCNN trained with past facial data is then used to verify future data.It has been found to exhibit 10 percent greater accuracy than traditional CNN with a celeb face database.
文摘近日,安徽农业大学动物科技学院查丽莎教授团队与合肥工业大学查正宝教授团队联合共同研究了纳米材料Mo-Based Polyoxometalate Nanoclusters(钼基多氧金属酸纳米团簇)在抗辐射方面超凡的应用前景。相关研究成果作为封面文章发表在ACS APPLIED MATERIALS&INTERFACES期刊上(ACS AMI 2023.02 IF 10.383)。
