In this article we present our system for scalable,robust,and fast city-scale reconstruction from Internet photo collections(IPC)obtaining geo-registered dense 3D models.The major achievements of our system are the ef...In this article we present our system for scalable,robust,and fast city-scale reconstruction from Internet photo collections(IPC)obtaining geo-registered dense 3D models.The major achievements of our system are the efficient use of coarse appearance descriptors combined with strong geometric constraints to reduce the computational complexity of the image overlap search.This unique combination of recognition and geometric constraints allows our method to reduce from quadratic complexity in the number of images to almost linear complexity in the IPC size.Accordingly,our 3D-modeling framework is inherently better scalable than other state of the art methods and in fact is currently the only method to support modeling from millions of images.In addition,we propose a novel mechanism to overcome the inherent scale ambiguity of the reconstructed models by exploiting geo-tags of the Internet photo collection images and readily available StreetView panoramas for fully automatic geo-registration of the 3D model.Moreover,our system also exploits image appearance clustering to tackle the challenge of computing dense 3D models from an image collection that has significant variation in illumination between images along with a wide variety of sensors and their associated different radiometric camera parameters.Our algorithm exploits the redundancy of the data to suppress estimation noise through a novel depth map fusion.The fusion simultaneously exploits surface and free space constraints during the fusion of a large number of depth maps.Cost volume compression during the fusion achieves lower memory requirements for high-resolution models.We demonstrate our system on a variety of scenes from an Internet photo collection of Berlin containing almost three million images from which we compute dense models in less than the span of a day on a single computer.展开更多
We investigate the behavior of dissipative particle dynamics （DPD） within different scaling regimes by numerical simulations. The paper extends earlier analytical findings of Ripoll, M., Ernst, M. H., and Espafiol, ...We investigate the behavior of dissipative particle dynamics （DPD） within different scaling regimes by numerical simulations. The paper extends earlier analytical findings of Ripoll, M., Ernst, M. H., and Espafiol, P. （Large scale and mesoscopic hy- drodynamics for dissipative particle dynamics. Journal of Chemical Physics, 115（15）, 7271-7281 （2001）） by evaluation of numerical data for the particle and collective scaling regimes and the four different subregimes. DPD simulations are performed for a range of dynamic overlapping parameters. Based on analyses of the current auto-correlation functions （CACFs）, we demonstrate that within the particle regime at scales smaller than its force cut-off radius, DPD follows Langevin dynamics. For the collective regime, we show that the small-scale behavior of DPD differs from Langevin dynamics. For the wavenumber-dependent effective shear viscosity, universal scaling regimes are observed in the microscopic and mesoscopic wavenumber ranges over the considered range of dynamic overlapping parameters.展开更多
The recently experienced hype concerning the so-called “4<sup>th</sup> Industrial Revolution” of production systems has prompted several papers of various subtopics regarding Cyber-Phdysical Production S...The recently experienced hype concerning the so-called “4<sup>th</sup> Industrial Revolution” of production systems has prompted several papers of various subtopics regarding Cyber-Phdysical Production Systems (CPPS). However, important aspects such as the modelling of CPPS to understand the theory regarding the performance of highly non-ergodic and non-deterministic flexible manufacturing systems in terms of Exit Rate (ER), Manufacturing Lead Time (MLT), and On-Time Delivery (OTD) have not yet been examined systematically and even less modeled analytically. To develop the topic, in this paper, the prerequisites for modelling such systems are defined in order to be able to derive an explicit and dedicated production mathematics-based understanding of CPPS and its dynamics: switching from explorative simulation to rational modelling of the manufacturing “physics” led to an own and specific manufacturing theory. The findings have led to enouncing, among others, the Theorem of Non-Ergodicity as well as the Batch Cycle Time Deviation Function giving important insights to model digital twin-based CPPS for complying with the mandatory OTD.展开更多
Identification of the glymphatic system,defined as a perivascular network that facilitates the clearance of metabolic waste through the exchange of cerebrospinal fluid(CSF)and interstitial fluid(ISF),has reshaped pers...Identification of the glymphatic system,defined as a perivascular network that facilitates the clearance of metabolic waste through the exchange of cerebrospinal fluid(CSF)and interstitial fluid(ISF),has reshaped perspectives on cerebral homeostasis and its implications for health and disease[1].According to the Global Burden of Disease Study 2019,psychiatric disorders accounted for approximately 4.9%of global disability-adjusted life years[2],highlighting the urgent need for targeted interventions.展开更多
Marine vessels play a vital role in the global economy;however,their negative impact on the marine atmospheric environment is a growing concern.Quantifying marine vessel emissions is an essential prerequisite for cont...Marine vessels play a vital role in the global economy;however,their negative impact on the marine atmospheric environment is a growing concern.Quantifying marine vessel emissions is an essential prerequisite for controlling these emissions and improving the marine atmospheric environment.Optical imaging remote sensing is a vital technique for quantifying marine vessel emissions.However,the available imaging techniques have suffered from insufficient detection accuracy and inadequate spatiotemporal resolution.Herein,we propose a fast-hyperspectral imaging remote sensing technique that achieved precise imaging of nitrogen dioxide(NO_(2))and sulfur dioxide(SO_(2))from marine vessels.Several key techniques are developed,including the coaxial design of three camera systems(hyperspectral camera,visible camera,and multiwavelength filters)and a high-precision temperature control system for a spectrometer(20℃±0.5℃).Moreover,based on the variation of O_(4)within them,plumes are categorized as aerosol-present and aerosol-absent,with different air mass factor(AMF)calculation schemes developed accordingly.Multiwavelength filters combined with spectral analysis enable precise identification of the plume outline and a detailed observation of the trace gas distribution inside the plume emitted from marine vessels.In addition,we focuse on the emission characteristics of NO_(2) and SO_(2) from large ocean cargo ships and small offshore cargo ships.Although there are still many emerging issues,such as measurement of cross-sections of trace gases at different temperature,nighttime imaging,and greenhouse gas imaging,this study opens a gate for synergies in pollution and carbon reductions and the continuous improvement of the marine atmospheric environment.展开更多
As built environments become more complex,indoor wayfinding challenges increase,especially for first-time visitors.Effective wayfinding design and signage are crucial for helping people reach their destinations.Occupa...As built environments become more complex,indoor wayfinding challenges increase,especially for first-time visitors.Effective wayfinding design and signage are crucial for helping people reach their destinations.Occupant simulations can analyze these features before construction and identify potential issues.However,current models for human wayfinding in unfamiliar environments are limited and rarely predict continuous experiences like perceived path uncertainty.This study developed an integrated agent-based model called“PATH-U”,which simulates multi-floor wayfinding tasks without prior knowledge of the environment and provides feedback on uncertainty levels.This model is based on an observational study with 39 participants completing 273 wayfinding tasks in a complex university building.We developed a path-planning model incorporating visual perception,natural movements,short-term memory,heuristic strategies,and a data-driven multiple linear regression model for uncertainty prediction based on data from 28 participants.Validation with data from 11 participants under a different signage condition shows that the model mostly mirrors human wayfinding behavior and perceived uncertainty,with a few notable discrepancies.The findings suggest that wayfinding design should consider spatial dimensions,confirmational signage,and enhanced cues at crucial intersections to reduce uncertainty and improve performance.Future simulations should incorporate on-route behaviors and environmental reasoning.展开更多
Understanding the way genes work amongst individuals and across generations to shape form and function is a common theme for many genetic studies.The recent advances in genetics,genome engineering and DNA sequencing r...Understanding the way genes work amongst individuals and across generations to shape form and function is a common theme for many genetic studies.The recent advances in genetics,genome engineering and DNA sequencing reinforced the notion that genes are not the only players that determine a phenotype.Due to physiological or pathological fluctuations in gene expression,even genetically identical cells can behave and manifest different phenotypes under the same conditions.Here,we discuss mechanisms that can influence or even disrupt the axis between genotype and phenotype;the role of modifier genes,the general concept of genetic redundancy,genetic compensation,the recently described transcriptional adaptation,environmental stressors,and phenotypic plasticity.We furthermore highlight the usage of induced pluripotent stem cells(iPSCs),the generation of isogenic lines through genome engineering,and sequencing technologies can help extract new genetic and epigenetic mechanisms from what is hitherto considered‘noise’.展开更多
Nearly all inf-sup stable mixed finite elements for the incompressible Stokes equations relax the divergence constraint. The price to pay is that a priori estimates for the ve- locity error become pressure-dependent, ...Nearly all inf-sup stable mixed finite elements for the incompressible Stokes equations relax the divergence constraint. The price to pay is that a priori estimates for the ve- locity error become pressure-dependent, while divergence-free mixed finite elements de- liver pressure-independent estimates. A recently introduced new variational crime using lowest-order Raviart-Thomas velocity reconstructions delivers a much more robust modi- fied Crouzeix-Raviart element, obeying an optimal pressure-independent discrete H1 ve- locity estimate. Refining this approach, a more sophisticated variational crime employing the lowest-order BDM element is proposed, which also allows proving an optimal pressure- independent L2 velocity error. Numerical examples confirm the analysis and demonstrate the improved robustness in the Navier-Stokes case.展开更多
文摘In this article we present our system for scalable,robust,and fast city-scale reconstruction from Internet photo collections(IPC)obtaining geo-registered dense 3D models.The major achievements of our system are the efficient use of coarse appearance descriptors combined with strong geometric constraints to reduce the computational complexity of the image overlap search.This unique combination of recognition and geometric constraints allows our method to reduce from quadratic complexity in the number of images to almost linear complexity in the IPC size.Accordingly,our 3D-modeling framework is inherently better scalable than other state of the art methods and in fact is currently the only method to support modeling from millions of images.In addition,we propose a novel mechanism to overcome the inherent scale ambiguity of the reconstructed models by exploiting geo-tags of the Internet photo collection images and readily available StreetView panoramas for fully automatic geo-registration of the 3D model.Moreover,our system also exploits image appearance clustering to tackle the challenge of computing dense 3D models from an image collection that has significant variation in illumination between images along with a wide variety of sensors and their associated different radiometric camera parameters.Our algorithm exploits the redundancy of the data to suppress estimation noise through a novel depth map fusion.The fusion simultaneously exploits surface and free space constraints during the fusion of a large number of depth maps.Cost volume compression during the fusion achieves lower memory requirements for high-resolution models.We demonstrate our system on a variety of scenes from an Internet photo collection of Berlin containing almost three million images from which we compute dense models in less than the span of a day on a single computer.
文摘We investigate the behavior of dissipative particle dynamics （DPD） within different scaling regimes by numerical simulations. The paper extends earlier analytical findings of Ripoll, M., Ernst, M. H., and Espafiol, P. （Large scale and mesoscopic hy- drodynamics for dissipative particle dynamics. Journal of Chemical Physics, 115（15）, 7271-7281 （2001）） by evaluation of numerical data for the particle and collective scaling regimes and the four different subregimes. DPD simulations are performed for a range of dynamic overlapping parameters. Based on analyses of the current auto-correlation functions （CACFs）, we demonstrate that within the particle regime at scales smaller than its force cut-off radius, DPD follows Langevin dynamics. For the collective regime, we show that the small-scale behavior of DPD differs from Langevin dynamics. For the wavenumber-dependent effective shear viscosity, universal scaling regimes are observed in the microscopic and mesoscopic wavenumber ranges over the considered range of dynamic overlapping parameters.
文摘The recently experienced hype concerning the so-called “4<sup>th</sup> Industrial Revolution” of production systems has prompted several papers of various subtopics regarding Cyber-Phdysical Production Systems (CPPS). However, important aspects such as the modelling of CPPS to understand the theory regarding the performance of highly non-ergodic and non-deterministic flexible manufacturing systems in terms of Exit Rate (ER), Manufacturing Lead Time (MLT), and On-Time Delivery (OTD) have not yet been examined systematically and even less modeled analytically. To develop the topic, in this paper, the prerequisites for modelling such systems are defined in order to be able to derive an explicit and dedicated production mathematics-based understanding of CPPS and its dynamics: switching from explorative simulation to rational modelling of the manufacturing “physics” led to an own and specific manufacturing theory. The findings have led to enouncing, among others, the Theorem of Non-Ergodicity as well as the Batch Cycle Time Deviation Function giving important insights to model digital twin-based CPPS for complying with the mandatory OTD.
基金supported by the STI2030-Major Projects(2021ZD0200800)the National Natural Science Foundation of China(82288101)Joint Innovation Team for Clinical&Basic Research of Shandong First Medical University(202404).
文摘Identification of the glymphatic system,defined as a perivascular network that facilitates the clearance of metabolic waste through the exchange of cerebrospinal fluid(CSF)and interstitial fluid(ISF),has reshaped perspectives on cerebral homeostasis and its implications for health and disease[1].According to the Global Burden of Disease Study 2019,psychiatric disorders accounted for approximately 4.9%of global disability-adjusted life years[2],highlighting the urgent need for targeted interventions.
基金supported by the National Natural Science Foundation of China(42475148)the National Key Research and Development Program of China(2023YFC3705400,2022YFC3704200)+1 种基金the major science and technology special project of the Xinjiang Uygur Autonomous Region(2024A03012)the President’s Foundation of Hefei Institutes of Physical Science,Chinese Academy of Sciences(YZJJQY202401,BJPY2024B09).
文摘Marine vessels play a vital role in the global economy;however,their negative impact on the marine atmospheric environment is a growing concern.Quantifying marine vessel emissions is an essential prerequisite for controlling these emissions and improving the marine atmospheric environment.Optical imaging remote sensing is a vital technique for quantifying marine vessel emissions.However,the available imaging techniques have suffered from insufficient detection accuracy and inadequate spatiotemporal resolution.Herein,we propose a fast-hyperspectral imaging remote sensing technique that achieved precise imaging of nitrogen dioxide(NO_(2))and sulfur dioxide(SO_(2))from marine vessels.Several key techniques are developed,including the coaxial design of three camera systems(hyperspectral camera,visible camera,and multiwavelength filters)and a high-precision temperature control system for a spectrometer(20℃±0.5℃).Moreover,based on the variation of O_(4)within them,plumes are categorized as aerosol-present and aerosol-absent,with different air mass factor(AMF)calculation schemes developed accordingly.Multiwavelength filters combined with spectral analysis enable precise identification of the plume outline and a detailed observation of the trace gas distribution inside the plume emitted from marine vessels.In addition,we focuse on the emission characteristics of NO_(2) and SO_(2) from large ocean cargo ships and small offshore cargo ships.Although there are still many emerging issues,such as measurement of cross-sections of trace gases at different temperature,nighttime imaging,and greenhouse gas imaging,this study opens a gate for synergies in pollution and carbon reductions and the continuous improvement of the marine atmospheric environment.
文摘As built environments become more complex,indoor wayfinding challenges increase,especially for first-time visitors.Effective wayfinding design and signage are crucial for helping people reach their destinations.Occupant simulations can analyze these features before construction and identify potential issues.However,current models for human wayfinding in unfamiliar environments are limited and rarely predict continuous experiences like perceived path uncertainty.This study developed an integrated agent-based model called“PATH-U”,which simulates multi-floor wayfinding tasks without prior knowledge of the environment and provides feedback on uncertainty levels.This model is based on an observational study with 39 participants completing 273 wayfinding tasks in a complex university building.We developed a path-planning model incorporating visual perception,natural movements,short-term memory,heuristic strategies,and a data-driven multiple linear regression model for uncertainty prediction based on data from 28 participants.Validation with data from 11 participants under a different signage condition shows that the model mostly mirrors human wayfinding behavior and perceived uncertainty,with a few notable discrepancies.The findings suggest that wayfinding design should consider spatial dimensions,confirmational signage,and enhanced cues at crucial intersections to reduce uncertainty and improve performance.Future simulations should incorporate on-route behaviors and environmental reasoning.
文摘Understanding the way genes work amongst individuals and across generations to shape form and function is a common theme for many genetic studies.The recent advances in genetics,genome engineering and DNA sequencing reinforced the notion that genes are not the only players that determine a phenotype.Due to physiological or pathological fluctuations in gene expression,even genetically identical cells can behave and manifest different phenotypes under the same conditions.Here,we discuss mechanisms that can influence or even disrupt the axis between genotype and phenotype;the role of modifier genes,the general concept of genetic redundancy,genetic compensation,the recently described transcriptional adaptation,environmental stressors,and phenotypic plasticity.We furthermore highlight the usage of induced pluripotent stem cells(iPSCs),the generation of isogenic lines through genome engineering,and sequencing technologies can help extract new genetic and epigenetic mechanisms from what is hitherto considered‘noise’.
文摘Nearly all inf-sup stable mixed finite elements for the incompressible Stokes equations relax the divergence constraint. The price to pay is that a priori estimates for the ve- locity error become pressure-dependent, while divergence-free mixed finite elements de- liver pressure-independent estimates. A recently introduced new variational crime using lowest-order Raviart-Thomas velocity reconstructions delivers a much more robust modi- fied Crouzeix-Raviart element, obeying an optimal pressure-independent discrete H1 ve- locity estimate. Refining this approach, a more sophisticated variational crime employing the lowest-order BDM element is proposed, which also allows proving an optimal pressure- independent L2 velocity error. Numerical examples confirm the analysis and demonstrate the improved robustness in the Navier-Stokes case.
