1 If astronauts want to stay on the Moon for more than a few days,they must find local resources,and water is one of the most crucial ones.Scientists believe there's water on the Moon,but they're unsure of whe...1 If astronauts want to stay on the Moon for more than a few days,they must find local resources,and water is one of the most crucial ones.Scientists believe there's water on the Moon,but they're unsure of where it lies.2 Two probes are on their way to the Moon to solve this mystery.They will be launched on the same SpaceX Falcon 9 rocket from Cape Canaveral.If everything goes as planned,the first probe to reach the Moon will be Athena.Timothy Crain,the chief technology officer of Intuitive Machines,says it will take about 3 to 4 days,depending on the launch time.They'll orbit the Moon for 2 to 3 days to wait for the Sun to reach the landing site,because the lander's solar panels need sunlight to generate power.It only takes about 15 minutes to land softly after the engine is started.展开更多
IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional pro...IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.展开更多
The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primaril...The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primarily rely on physical intuition to search for potential superconductors within the existing databases.However,the known materials only scratch the surface of the extensive array of possibilities within the realm of materials.展开更多
The intuitive fuzzy set has found important application in decision-making and machine learning.To enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye ...The intuitive fuzzy set has found important application in decision-making and machine learning.To enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images converge.Retinal image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye recognition.Fuzzy degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal images.The proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between images.This methodology was used to clarify the input images and make them adequate for the process of glaucoma detection.The objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were determined.Once the peak regions were identified,the recurrence relationships among those peaks were then measured.Image partitioning was done due to varying degrees of similar and dissimilar concentrations in the image.Similar and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and FDE.This distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.展开更多
With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save inst...With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save instructors' effort as well.And it is estimated that Monte Carlo Simulation technology will be one of the major teaching methods for Probability and Mathematical Statistics course in the future.展开更多
The Paris Agreement proposed to keep the increase in global average temperature to well below 2 ℃ abovepre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 ℃ above pre-industriallevel...The Paris Agreement proposed to keep the increase in global average temperature to well below 2 ℃ abovepre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 ℃ above pre-industriallevels. It was thus the first international treaty to endow the 2 ℃ global temperature target with legal effect.The qualitative expression of the ultimate objective in Article 2 of the United Nations Framework Conventionon Climate Change （UNFCCC） has now evolved into the numerical temperature rise target in Article 2 of theParis Agreement. Starting with the Second Assessment Report （SAR） of the Intergovernmental Panel on Cli-mate Change （IPCC）, an important task for subsequent assessments has been to provide scientific informa-tion to help determine the quantified long-term goal for UNFCCC negotiation. However, due to involvementin the value judgment within the scope of non-scientific assessment, the IPCC has never scientifically af-firmed the unacceptable extent of global temperature rise. The setting of the long-term goal for addressingclimate change has been a long process, and the 2 ℃ global temperature target is the political consensuson the basis of scientific assessment. This article analyzes the evolution of the long-term global goal foraddressing climate change and its impact on scientific assessment, negotiation processes, and global low-carbon development, from aspects of the origin of the target, the series of assessments carried out by the 1PCCfocusing on Article 2 of the UNFCCC, and the promotion of the global temperature goal at the political level.展开更多
Virtual reality(VR) training technology in the mining industry is a new field of research and utilization.The successful application of VR training system is critical to mine safety and production. Through the statist...Virtual reality(VR) training technology in the mining industry is a new field of research and utilization.The successful application of VR training system is critical to mine safety and production. Through the statistics of the current research and applications of VR training systems in mining industry, all the input/output devices are classified. Based on the classifications of the input/output devices that are used in the VR system, the current VR training systems for the mining industry could be divided into three types: screen-based general type, projector-based customized type, and head-mounted display(HMD)-based intuitive type. By employing a VR headset, a smartphone and a leap motion device, an HMDbased intuitive type VR training system prototype for drilling in underground mines has been developed.Ten trainees tried both the HMD-based intuitive system and the screen-based general control system to compare the experiences and training effects. The results show that the HMD-based system can give a much better user experience and is easy to use. Three of the five components of a VR training system,namely, the user, the tasks, and software and database should be given more attention in future research.With more available technologies of input and output devices, VR engines, and system software, the VR training system will eventually yield much better training results, and will play a more important role in as a training tool for mine safety.展开更多
The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to...The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set （IFS） is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method.展开更多
Recent progress in deep learning is essentially based on a“big data for small tasks”paradigm,under which massive amounts of data are used to train a classifier for a single narrow task.In this paper,we call for a sh...Recent progress in deep learning is essentially based on a“big data for small tasks”paradigm,under which massive amounts of data are used to train a classifier for a single narrow task.In this paper,we call for a shift that flips this paradigm upside down.Specifically,we propose a“small data for big tasks”paradigm,wherein a single artificial intelligence(AI)system is challenged to develop“common sense,”enabling it to solve a wide range of tasks with little training data.We illustrate the potential power of this new paradigm by reviewing models of common sense that synthesize recent breakthroughs in both machine and human vision.We identify functionality,physics,intent,causality,and utility(FPICU)as the five core domains of cognitive AI with humanlike common sense.When taken as a unified concept,FPICU is concerned with the questions of“why”and“how,”beyond the dominant“what”and“where”framework for understanding vision.They are invisible in terms of pixels but nevertheless drive the creation,maintenance,and development of visual scenes.We therefore coin them the“dark matter”of vision.Just as our universe cannot be understood by merely studying observable matter,we argue that vision cannot be understood without studying FPICU.We demonstrate the power of this perspective to develop cognitive AI systems with humanlike common sense by showing how to observe and apply FPICU with little training data to solve a wide range of challenging tasks,including tool use,planning,utility inference,and social learning.In summary,we argue that the next generation of AI must embrace“dark”humanlike common sense for solving novel tasks.展开更多
Dear editor,This letter models and analyzes the Matthew effect under switching social networks via distributed competition.A competitive strategy is leveraged to trace the evolution of individuals in social systems un...Dear editor,This letter models and analyzes the Matthew effect under switching social networks via distributed competition.A competitive strategy is leveraged to trace the evolution of individuals in social systems under the Matthew effect.In addition,a consensus filter is utilized to decentralize the model with undirected graphs used to describe the interactions among individuals in social networks.Further,a term is added to the dynamic consensus filter to compensate for the influence of the switching of communication networks on the model.In this letter,the convergence of the proposed Matthew effect model is theoretically proved,and simulative experiments are conducted to verify the availability of the model.In particular,this letter points out the state and evolution of each individual in social systems with distributed competition,and the influence of the social environment on the development of individuals is also intuitively displayed.展开更多
Physical restraint is a common nursing intervention in intensive care units and nurses often use it to ensure patients'safety and to prevent unexpected accidents.However,existing literature indicated that the use ...Physical restraint is a common nursing intervention in intensive care units and nurses often use it to ensure patients'safety and to prevent unexpected accidents.However,existing literature indicated that the use of physical restraint is a complex one because of inadequate rationales,the negative physical and emotional effects on patients,but the lack of perceived alternatives.This paper is aimed to interpret the clinical decision-making theories related to the use of physical restraint in intensive care units in order to facilitate our understanding on the use of physical restraint and to evaluate the quality of decisions made by nurses.By reviewing the literature,intuition and heuristics are the main decision-making strategies related to the use of physical restraint in intensive care units because the rapid and reflexive nature of intuition and heuristics allow nurses to have a rapid response to urgent and emergent cases.However,it is problematic if nurses simply count their decision-making on experience rather than incorporate research evidence into clinical practice because of inadequate evidence to support the use of physical restraint.Besides that,such a rapid response may lead nurses to make decisions without adequate assessment and thinking and therefore biases and errors may be generated.Therefore,despite the importance of intuition and heuristics in decision-making in acute settings on the use of physical restraint,it is recommended that nurses should incorporate research evidence with their experience to make decisions and adequate assessment before implementing physical restraint is also necessary.展开更多
In some special cases of flight simulation (e.g. for formation flight, in-flight tanking) it is required to generate a two-dimensional field of turbulence, in which the turbulent wind speeds are stochastic functions o...In some special cases of flight simulation (e.g. for formation flight, in-flight tanking) it is required to generate a two-dimensional field of turbulence, in which the turbulent wind speeds are stochastic functions of two coordinates (e.g. x in the flight direction and y in the wing span direction). For this purpose a simple and efficient technique for the digital generation of a two-dimensional field of turbulence, i.e. for the production of turbulent speed sequences on a rectangular network, is proposed in this paper. The correlation of the turbulent field so generated is found to be in good agreement with the theoretical correlation of the turbulence model, and thus the feasibility of the proposed method is verified. Two possible operation modes (off-line and on-line) of the turbulence generator in flight simulation are also discussed.展开更多
Time-temperature indicators(TTIs) are convenient intuitive devices that are widely used to predict food quality. The aim of this study is to develop a new simple device which can be attached to food packages as a qual...Time-temperature indicators(TTIs) are convenient intuitive devices that are widely used to predict food quality. The aim of this study is to develop a new simple device which can be attached to food packages as a quality indicator for turbot sashimi. In this study, a solid TTI based on the reaction between tyrosinase and tyrosine was developed. The Arrhenius behavior of this enzymatic TTI was studied. The kinetics of the tyrosinase-based TTI was investigated in the form of color change from colorless to dark black induced by the enzymatic reaction. The mathematical formula for the color alterations as a function of time and temperature was established. The longest indication time for the developed TTI was 50 hours at 4℃. The activation energy of the tyrosinase-based TTI was 0.409 k J mol^(-1). The suitability of the tyrosinase-based TTI was validated for turbot sashimi using total plate count. The feasibility of using this TTI as a quality indicator for turbot sashimi was assessed based on the activation energy and indication time. Therefore, the tyrosinasebased TTI system developed in this study could be used as an effective tool for monitoring the quality changes of turbot sashimi during the distribution and storage.展开更多
文摘1 If astronauts want to stay on the Moon for more than a few days,they must find local resources,and water is one of the most crucial ones.Scientists believe there's water on the Moon,but they're unsure of where it lies.2 Two probes are on their way to the Moon to solve this mystery.They will be launched on the same SpaceX Falcon 9 rocket from Cape Canaveral.If everything goes as planned,the first probe to reach the Moon will be Athena.Timothy Crain,the chief technology officer of Intuitive Machines,says it will take about 3 to 4 days,depending on the launch time.They'll orbit the Moon for 2 to 3 days to wait for the Sun to reach the landing site,because the lander's solar panels need sunlight to generate power.It only takes about 15 minutes to land softly after the engine is started.
文摘IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.62476278,12434009,and 12204533)the National Key R&D Program of China(Grant No.2024YFA1408601)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302402)。
文摘The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primarily rely on physical intuition to search for potential superconductors within the existing databases.However,the known materials only scratch the surface of the extensive array of possibilities within the realm of materials.
基金funding the publication of this research through the Researchers Supporting Program (RSPD2023R809),King Saud University,Riyadh,Saudi Arabia.
文摘The intuitive fuzzy set has found important application in decision-making and machine learning.To enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images converge.Retinal image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye recognition.Fuzzy degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal images.The proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between images.This methodology was used to clarify the input images and make them adequate for the process of glaucoma detection.The objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were determined.Once the peak regions were identified,the recurrence relationships among those peaks were then measured.Image partitioning was done due to varying degrees of similar and dissimilar concentrations in the image.Similar and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and FDE.This distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.
文摘With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save instructors' effort as well.And it is estimated that Monte Carlo Simulation technology will be one of the major teaching methods for Probability and Mathematical Statistics course in the future.
文摘The Paris Agreement proposed to keep the increase in global average temperature to well below 2 ℃ abovepre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 ℃ above pre-industriallevels. It was thus the first international treaty to endow the 2 ℃ global temperature target with legal effect.The qualitative expression of the ultimate objective in Article 2 of the United Nations Framework Conventionon Climate Change （UNFCCC） has now evolved into the numerical temperature rise target in Article 2 of theParis Agreement. Starting with the Second Assessment Report （SAR） of the Intergovernmental Panel on Cli-mate Change （IPCC）, an important task for subsequent assessments has been to provide scientific informa-tion to help determine the quantified long-term goal for UNFCCC negotiation. However, due to involvementin the value judgment within the scope of non-scientific assessment, the IPCC has never scientifically af-firmed the unacceptable extent of global temperature rise. The setting of the long-term goal for addressingclimate change has been a long process, and the 2 ℃ global temperature target is the political consensuson the basis of scientific assessment. This article analyzes the evolution of the long-term global goal foraddressing climate change and its impact on scientific assessment, negotiation processes, and global low-carbon development, from aspects of the origin of the target, the series of assessments carried out by the 1PCCfocusing on Article 2 of the UNFCCC, and the promotion of the global temperature goal at the political level.
基金funded by the ‘‘twelfth five” National Key Technology Research and Development Program of the Ministry of Science and Technology of China (Grant No. 2015BAK10B00)
文摘Virtual reality(VR) training technology in the mining industry is a new field of research and utilization.The successful application of VR training system is critical to mine safety and production. Through the statistics of the current research and applications of VR training systems in mining industry, all the input/output devices are classified. Based on the classifications of the input/output devices that are used in the VR system, the current VR training systems for the mining industry could be divided into three types: screen-based general type, projector-based customized type, and head-mounted display(HMD)-based intuitive type. By employing a VR headset, a smartphone and a leap motion device, an HMDbased intuitive type VR training system prototype for drilling in underground mines has been developed.Ten trainees tried both the HMD-based intuitive system and the screen-based general control system to compare the experiences and training effects. The results show that the HMD-based system can give a much better user experience and is easy to use. Three of the five components of a VR training system,namely, the user, the tasks, and software and database should be given more attention in future research.With more available technologies of input and output devices, VR engines, and system software, the VR training system will eventually yield much better training results, and will play a more important role in as a training tool for mine safety.
基金supported by the National Natural Science Foundation of China (70871117 70571086)the Development Foundation of Dalian Naval Academy
文摘The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set （IFS） is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method.
文摘Recent progress in deep learning is essentially based on a“big data for small tasks”paradigm,under which massive amounts of data are used to train a classifier for a single narrow task.In this paper,we call for a shift that flips this paradigm upside down.Specifically,we propose a“small data for big tasks”paradigm,wherein a single artificial intelligence(AI)system is challenged to develop“common sense,”enabling it to solve a wide range of tasks with little training data.We illustrate the potential power of this new paradigm by reviewing models of common sense that synthesize recent breakthroughs in both machine and human vision.We identify functionality,physics,intent,causality,and utility(FPICU)as the five core domains of cognitive AI with humanlike common sense.When taken as a unified concept,FPICU is concerned with the questions of“why”and“how,”beyond the dominant“what”and“where”framework for understanding vision.They are invisible in terms of pixels but nevertheless drive the creation,maintenance,and development of visual scenes.We therefore coin them the“dark matter”of vision.Just as our universe cannot be understood by merely studying observable matter,we argue that vision cannot be understood without studying FPICU.We demonstrate the power of this perspective to develop cognitive AI systems with humanlike common sense by showing how to observe and apply FPICU with little training data to solve a wide range of challenging tasks,including tool use,planning,utility inference,and social learning.In summary,we argue that the next generation of AI must embrace“dark”humanlike common sense for solving novel tasks.
基金This work was supported by the National Natural Science Foundation of China(62176109)the Natural Science Foundation of Gansu Province(21JR7RA531)+2 种基金the Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province(2021-Z-003)the Youth Science and Technology Foundation of Gansu Province(20JR10RA639)the SuperComputing Center of Lanzhou University.
文摘Dear editor,This letter models and analyzes the Matthew effect under switching social networks via distributed competition.A competitive strategy is leveraged to trace the evolution of individuals in social systems under the Matthew effect.In addition,a consensus filter is utilized to decentralize the model with undirected graphs used to describe the interactions among individuals in social networks.Further,a term is added to the dynamic consensus filter to compensate for the influence of the switching of communication networks on the model.In this letter,the convergence of the proposed Matthew effect model is theoretically proved,and simulative experiments are conducted to verify the availability of the model.In particular,this letter points out the state and evolution of each individual in social systems with distributed competition,and the influence of the social environment on the development of individuals is also intuitively displayed.
文摘Physical restraint is a common nursing intervention in intensive care units and nurses often use it to ensure patients'safety and to prevent unexpected accidents.However,existing literature indicated that the use of physical restraint is a complex one because of inadequate rationales,the negative physical and emotional effects on patients,but the lack of perceived alternatives.This paper is aimed to interpret the clinical decision-making theories related to the use of physical restraint in intensive care units in order to facilitate our understanding on the use of physical restraint and to evaluate the quality of decisions made by nurses.By reviewing the literature,intuition and heuristics are the main decision-making strategies related to the use of physical restraint in intensive care units because the rapid and reflexive nature of intuition and heuristics allow nurses to have a rapid response to urgent and emergent cases.However,it is problematic if nurses simply count their decision-making on experience rather than incorporate research evidence into clinical practice because of inadequate evidence to support the use of physical restraint.Besides that,such a rapid response may lead nurses to make decisions without adequate assessment and thinking and therefore biases and errors may be generated.Therefore,despite the importance of intuition and heuristics in decision-making in acute settings on the use of physical restraint,it is recommended that nurses should incorporate research evidence with their experience to make decisions and adequate assessment before implementing physical restraint is also necessary.
基金This project is supported by China National Sciences Foundation and finished in the Institute of Flight Guidance of Technical University Braunschweig (West Germany).
文摘In some special cases of flight simulation (e.g. for formation flight, in-flight tanking) it is required to generate a two-dimensional field of turbulence, in which the turbulent wind speeds are stochastic functions of two coordinates (e.g. x in the flight direction and y in the wing span direction). For this purpose a simple and efficient technique for the digital generation of a two-dimensional field of turbulence, i.e. for the production of turbulent speed sequences on a rectangular network, is proposed in this paper. The correlation of the turbulent field so generated is found to be in good agreement with the theoretical correlation of the turbulence model, and thus the feasibility of the proposed method is verified. Two possible operation modes (off-line and on-line) of the turbulence generator in flight simulation are also discussed.
基金the Science and Technology Major Projects of Shandong Province (No. 2015ZDZX05 003)the National Science & Technology Pillar Program (No. 2015BAD16B0902)
文摘Time-temperature indicators(TTIs) are convenient intuitive devices that are widely used to predict food quality. The aim of this study is to develop a new simple device which can be attached to food packages as a quality indicator for turbot sashimi. In this study, a solid TTI based on the reaction between tyrosinase and tyrosine was developed. The Arrhenius behavior of this enzymatic TTI was studied. The kinetics of the tyrosinase-based TTI was investigated in the form of color change from colorless to dark black induced by the enzymatic reaction. The mathematical formula for the color alterations as a function of time and temperature was established. The longest indication time for the developed TTI was 50 hours at 4℃. The activation energy of the tyrosinase-based TTI was 0.409 k J mol^(-1). The suitability of the tyrosinase-based TTI was validated for turbot sashimi using total plate count. The feasibility of using this TTI as a quality indicator for turbot sashimi was assessed based on the activation energy and indication time. Therefore, the tyrosinasebased TTI system developed in this study could be used as an effective tool for monitoring the quality changes of turbot sashimi during the distribution and storage.
