Nuclear heating plays an important aspect in design and deployment of both fission and fusion reactors and experimental devices in terms of cooling requirements. Two experimental campaigns in the framework of a collab...Nuclear heating plays an important aspect in design and deployment of both fission and fusion reactors and experimental devices in terms of cooling requirements. Two experimental campaigns in the framework of a collaboration project between the French Atomic and Alternative Energy Commission(CEA) and Jožef Stefan Institute(JSI), Slovenia, have been performed at the JSI TRIGA reactor for the experimental assessment of nuclear heating in fission and fusion-relevant materials by the differential calorimetry technique, based on the CALMOS and CARMEN differential calorimeters, previously developed at CEA. The results of the first campaign performed at reactor powers between 100 and 250 kW have already been reported, highlighting some measurement difficulties. Therefore, the second campaign was performed at a lower reactor power of 30 kW to overcome these issues. Moreover, a computational analysis of the experiments was performed using the JSIR2S code package to calculate the nuclear heating levels. Both experiments and their reproduction by simulations are described in detail. We present a comparison of the previously reported measured nuclear heating values of the first campaign with the computational results, with consistent underestimation by simulations by 8–35%. We report the experimental and computational results for the second experimental campaign performed at a reactor power of 30 kW. The simulated heating values were in agreement with the measurements within the measured heating uncertainty, with simulated heating 2.7–11.3% lower than the experimental values.展开更多
In this study,the effects of laser fields that can be achieved in the near future on cluster penetration probability and half-life are quantitatively investigated.The calculation results show that extreme laser fields...In this study,the effects of laser fields that can be achieved in the near future on cluster penetration probability and half-life are quantitatively investigated.The calculation results show that extreme laser fields can slightly change the cluster-decay half-life by affecting the penetration probability within a narrow range.Subsequently,we discuss the correlation between the change rate of the penetration probability and the tunneling path.The results indicate that for different parent nuclei emitting the same cluster,nuclei with longer tunneling paths are more easily affected by the laser fields.The shell effect on this correlation is also observed.In addition,the impact of laser fields on the penetration probability in any direction is investigated.展开更多
The global climate change and ocean acidification brought about by the anthropogenic release of carbon dioxide gas into the air is considered one of the greatest problems facing marine life.In this research,the intera...The global climate change and ocean acidification brought about by the anthropogenic release of carbon dioxide gas into the air is considered one of the greatest problems facing marine life.In this research,the interactions between two species of fish(the gold mollies and tiger barb)were investigated under two different environmental conditions,an elevated temperature of 28℃ and a low pH of 5 and a normal pH of 7 and a normal temperature of 24℃.The mollies at pH 7 and a temperature of 24℃ exhibited scary interactions with the tiger barb.They were scared and ran fast away from the tiger barb.At the same time,the mollies at pH 5 and a temperature of 28℃ interacted normally as though both species were one species showing behavioral changes due to these two stressors(pH 5 and elevated temperature 28℃).This could be the only research that has addressed how the kinematics and swimming interactions of two species of fish changed in response to elevated temperature and low pH.展开更多
Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign cur...Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.展开更多
The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated ...The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated spatial plan.The study used a quantitative survey using Landsat images in 2016,2019,and 2022.The data analysis techniques used geographic information systems integrated with Artificial Neural Network(ANN)and Cellular Automata(CA)models.This study aims to predict land-use change in 2031,evaluate its alignment with spatial planning,and provide guidance for controlling land-use change.The results showed that there has been an increase in land use.In 2019,built-up land reached 7,069.65 Ha.The model shows its ability to predict land simulation and transformation,where it is predicted that built-up land in 2031 will experience an increase of up to 40.10%,so development and change cannot be avoided every year.This study also suggests that decision-makers and local governments should reconsider spatial planning strategies.This study shows that there have been many land use changes from 2016 to 2022.The model shows its ability to predict simulation and land transformation.When using the model,there are many changes in the land use area in 2031.This is due to wet agricultural land turning into built-up land by almost 70%.This study shows that road network influence land-use change.The cellular automata model managed to capture the complexity with simple rules.Predictions for future research should focus on conserving wetlands and primary forests.展开更多
We present analog clocks fitted to the Mars solar day.These clocks use the standard Earth-based second of the International System of Units(SI)as their operational unit of time,unlike current practice for Mars timekee...We present analog clocks fitted to the Mars solar day.These clocks use the standard Earth-based second of the International System of Units(SI)as their operational unit of time,unlike current practice for Mars timekeeping.We discuss the importance of preserving the SI second.On this basis,we identify the two analog clocks most suitable for public use by a future Mars population.These are a 20-hour clock with a hand motion similar to that of the standard Earth clock,and a 24-hour clock with a novel“Martian”hand motion which strikes the hour when all 3 hands converge onto that hour mark on the dial.Both clocks have Earth-day equivalents to assist learning.We also present a 24-hour“SpaceClock”,similar to the Martian clock but with no favored reference plane,hence equally readable from any viewing orientation.展开更多
Fractional differential equations have garnered significant attention within the mathematical and physical sciences due to the diverse range of fractional operators available.Fractional calculus has demonstrated its u...Fractional differential equations have garnered significant attention within the mathematical and physical sciences due to the diverse range of fractional operators available.Fractional calculus has demonstrated its utility across various disciplines,including biological modeling[1–5],applications in physics[6,7],most notably in the formulation of fractional diffusion equations,in robotics,and emerging areas such as intelligent artificial systems,among others.Numerous types of fractional operators exist,including those characterized by singular kernels,such as the Caputo and Riemann-Liouville derivatives[8,9].It is important to highlight that the Riemann-Liouville derivative exhibits certain limitations;most notably,the derivative of a constant is not zero,which poses a significant inconvenience.To circumvent this issue,the Caputo derivative was introduced.Additionally,there are fractional derivatives with non-singular kernels,such as the Caputo-Fabrizio derivative[10]and the Atangana-Baleanu fractional derivative[11],each providing unique advantages for modeling purposes.Given the growing interest in utilizing fractional operators for various modeling scenarios,it is imperative to propose robust methodologies for obtaining both approximate and exact solutions.Consequently,this special issue emphasizes the exploration of diverse numerical schemes aimed at deriving approximate solutions for the models under consideration.Furthermore,analytical methods have also been discussed,providing additional avenues for obtaining exact solutions.展开更多
Cyber-Physical Systems(CPS)represent an integration of computational and physical elements,revolutionizing industries by enabling real-time monitoring,control,and optimization.A complementary technology,Digital Twin(D...Cyber-Physical Systems(CPS)represent an integration of computational and physical elements,revolutionizing industries by enabling real-time monitoring,control,and optimization.A complementary technology,Digital Twin(DT),acts as a virtual replica of physical assets or processes,facilitating better decision making through simulations and predictive analytics.CPS and DT underpin the evolution of Industry 4.0 by bridging the physical and digital domains.This survey explores their synergy,highlighting how DT enriches CPS with dynamic modeling,realtime data integration,and advanced simulation capabilities.The layered architecture of DTs within CPS is examined,showcasing the enabling technologies and tools vital for seamless integration.The study addresses key challenges in CPS modeling,such as concurrency and communication,and underscores the importance of DT in overcoming these obstacles.Applications in various sectors are analyzed,including smart manufacturing,healthcare,and urban planning,emphasizing the transformative potential of CPS-DT integration.In addition,the review identifies gaps in existing methodologies and proposes future research directions to develop comprehensive,scalable,and secure CPSDT systems.By synthesizing insights fromthe current literature and presenting a taxonomy of CPS and DT,this survey serves as a foundational reference for academics and practitioners.The findings stress the need for unified frameworks that align CPS and DT with emerging technologies,fostering innovation and efficiency in the digital transformation era.展开更多
1 Introduction onMultimodal Learning in Image Processing IP(Image processing),as a classical research domain in computer application technology,has been researched for decades.It is one of the most important research ...1 Introduction onMultimodal Learning in Image Processing IP(Image processing),as a classical research domain in computer application technology,has been researched for decades.It is one of the most important research directions in computer vision,which is the basis for many current hotspots such as intelligent transportation/education/industry,etc.Because image processing is the strongest link for AI(artificial intelligence)applying to real world application,it has been a challenging research field with the development of AI,from DNN(deep convolutional network),Attention/LSTM(long-short term memory),to Transformer/Diffusion/Mamba based GAI(generated AI)models,e.g.,GPT and Sora[1].Today,the description ability of single-model feature limits the performance of image processing.More comprehensive description of the image is required to match the computational performance of current large scale models.展开更多
Pollution of transboundary rivers can result from anthropogenic activities in their watersheds.In this study,sediment traps were deployed to determine the fluxes,concentrations,and health risks associated with arsenic...Pollution of transboundary rivers can result from anthropogenic activities in their watersheds.In this study,sediment traps were deployed to determine the fluxes,concentrations,and health risks associated with arsenic,cadmium,mercury,lead,and iron in the estuaries of three transboundary rivers(Comoé,Bia,and Tanoé)in West Africa.Thus,the analysis of metal-associated sedimentation particle samples collected in rainy,flood,and dry seasons was required.Sediment traps were used to calculate the metal fluxes associated with sedimentation particles towards the Atlantic Ocean.Finally,the carcinogenic and non-carcinogenic risks of ingestion and dermal contact associated with sedimentation particles were assessed.The results showed that the total concentrations of trace metals in particulate matter were higher than in the UCC(Upper Crust Continental),with the exception of lead.The highest fluxes of lead,mercury,iron and arsenic associated with sedimented particles were observed during flood periods in the estuary of the Comoé,Bia and Tanoérivers.Cadmium fluxes associated with sedimentation particles were highest in the rainy season in the Bia and Comoéestuaries and in the flood season in the Tanoéestuary.Pearson’s correlation analysis and the enrichment factor showed that the trace metals were derived from anthropogenic activities such as mining and farming.In addition,contamination indices showed that sediment particles in the estuaries of the three rivers were severely contaminated with mercury.However,the results of potential human health risks associated with trace metals show that there is no probability of exposure of the community to harmful and carcinogenic effects through ingestion and dermal absorption of sediment particles.It is essential to integrate the information from this study into policy-and decision-making processes for better management of transboundary river water resources in coastal countries,particularly the Côte d’Ivoire.展开更多
Background Zonal application maps are designed to represent field variability using key variables that can be translated into tailored management practices.For cotton,zonal maps for crop growth regulator(CGR)applicati...Background Zonal application maps are designed to represent field variability using key variables that can be translated into tailored management practices.For cotton,zonal maps for crop growth regulator(CGR)applications under variable-rate(VR)strategies are commonly based exclusively on vegetation indices(VIs)variability.However,VIs often saturate in dense crop vegetation areas,limiting their effectiveness in distinguishing variability in crop growth.This study aimed to compare unsupervised framework(UF)and supervised framework(SUF)approaches for generat-ing zonal application maps for CGR under VR conditions.During 2022-2023 agricultural seasons,an UF was employed to generate zonal maps based on locally collected field data on plant height of cotton,satellite imagery,soil texture,and phenology data.Subsequently,a SUF(based on historical data between 2020-2021 to 2022-2023 agricultural seasons)was developed to predict plant height using remote sensing and phenology data,aiming to replicate same zonal maps but without relying on direct field measurements of plant height.Both approaches were tested in three fields and on two different dates per field.Results The predictive model for plant height of SUF performed well,as indicated by the model metrics.However,when comparing zonal application maps for specific field-date combinations,the predicted plant height exhibited lower variability compared with field measurements.This led to variable compatibility between SUF maps,which utilized the model predictions,and the UF maps,which were based on the real field data.Fields characterized by much pronounced soil texture variability yielded the highest compatibility between the zonal application maps produced by both SUF and UF approaches.This was predominantly due to the greater consistency in estimating plant development patterns within these heterogeneous field environments.While VR application approach can facilitate product savings during the application operation,other key factors must be considered.These include the availability of specialized machinery required for this type of applications,as well as the inherent operational costs associated with applying a single CGR product which differs from the typical uniform rate applications that often integrate multi-ple inputs.Conclusion Predictive modeling shows promise for assisting in the creation of zonal application maps for VR of CGR applications.However,the degree of agreement with the actual variability in crop growth found in the field should be evaluated on a field-by-field basis.The SUF approach,which is based on plant heigh prediction,demonstrated potential for supporting the development of zonal application maps for VR of CGR applications.However,the degree to which this approach aligns itself with the actual variability in crop growth observed in the field may vary,necessi-tating field-by-field evaluation.展开更多
Soil erosion from water has become a relevant issue at global level.In Guinea in particular,erosion has worrying effects,due to natural conditions and human impact,especially in the Nzérékore city in forest ...Soil erosion from water has become a relevant issue at global level.In Guinea in particular,erosion has worrying effects,due to natural conditions and human impact,especially in the Nzérékore city in forest region.This paper proposed a soil erosion modeling by rainfall effect in the prefecture of N'Zérékoré.To achieve this objective,monthly and annual rainfall data for the N'Zérékorécity were collected at the meteorological station over the period from 1980 to 2024.The analysis of rainfall aggressiveness was possible using the Fournier index.For data processing,we used Microsoft Excel,Python and the ARIMA(AutoRegressive Integrated Moving Average)model for soil aggressiveness predicted by rainfall.It was found that,from 2000 to 2009,erosion was higher compared to other periods with a rate of 60%,or 6 years of high rainfall aggression.From the periods 1990 to 1999 and 2010 to 2019,the lowest rainfall aggressiveness was recorded,with 60%or 6 years of low erosivity.However,from period 1980 to 1989 the highest rate(70%)of very high rainfall erosivity was recorded.The results show three levels of rainfall aggressiveness on an annual scale:a very high level of erosivity with a rate of 22.2%or 10 years,followed by a high level of 35.6%or 16 years of strong erosion.The moderate erosivity level corresponds to 42.2%or 19 years.The model predicts a stability of the erosivity index around 77.14 over the period 2025-2034.During the forty(45)years the rainfall erosivity index was very unstable characterized by strong erosion,however it would be stable in the next ten(10)years.展开更多
Deep Learning(DL)offers promising solutions for analyzing wearable signals and gaining valuable insights into cognitive disorders.While previous review studies have explored various aspects of DL in cognitive healthca...Deep Learning(DL)offers promising solutions for analyzing wearable signals and gaining valuable insights into cognitive disorders.While previous review studies have explored various aspects of DL in cognitive healthcare,there remains a lack of comprehensive analysis that integrates wearable signals,data processing techniques,and the broader applications,benefits,and challenges of DL methods.Addressing this limitation,our study provides an extensive review of DL’s role in cognitive healthcare,with a particular emphasis on wearables,data processing,and the inherent challenges in this field.This review also highlights the considerable promise of DL approaches in addressing a broad spectrum of cognitive issues.By enhancing the understanding and analysis of wearable signal modalities,DL models can achieve remarkable accuracy in cognitive healthcare.Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),and Long Short-term Memory(LSTM)networks have demonstrated improved performance and effectiveness in the early diagnosis and progression monitoring of neurological disorders.Beyond cognitive impairment detection,DL has been applied to emotion recognition,sleep analysis,stress monitoring,and neurofeedback.These applications lead to advanced diagnosis,personalized treatment,early intervention,assistive technologies,remote monitoring,and reduced healthcare costs.Nevertheless,the integration of DL and wearable technologies presents several challenges,such as data quality,privacy,interpretability,model generalizability,ethical concerns,and clinical adoption.These challenges emphasize the importance of conducting future research in areas such as multimodal signal analysis and explainable AI.The findings of this review aim to benefit clinicians,healthcare professionals,and society by facilitating better patient outcomes in cognitive healthcare.展开更多
基金supported by the Slovenian Research Agency(research project NC-0001-Analysis of nuclear heating in a reactor,research core funding Reactor physics No.P2-0073,infrastructure program I0-0005)。
文摘Nuclear heating plays an important aspect in design and deployment of both fission and fusion reactors and experimental devices in terms of cooling requirements. Two experimental campaigns in the framework of a collaboration project between the French Atomic and Alternative Energy Commission(CEA) and Jožef Stefan Institute(JSI), Slovenia, have been performed at the JSI TRIGA reactor for the experimental assessment of nuclear heating in fission and fusion-relevant materials by the differential calorimetry technique, based on the CALMOS and CARMEN differential calorimeters, previously developed at CEA. The results of the first campaign performed at reactor powers between 100 and 250 kW have already been reported, highlighting some measurement difficulties. Therefore, the second campaign was performed at a lower reactor power of 30 kW to overcome these issues. Moreover, a computational analysis of the experiments was performed using the JSIR2S code package to calculate the nuclear heating levels. Both experiments and their reproduction by simulations are described in detail. We present a comparison of the previously reported measured nuclear heating values of the first campaign with the computational results, with consistent underestimation by simulations by 8–35%. We report the experimental and computational results for the second experimental campaign performed at a reactor power of 30 kW. The simulated heating values were in agreement with the measurements within the measured heating uncertainty, with simulated heating 2.7–11.3% lower than the experimental values.
基金supported in part by the National Natural Science Foundation of China(Nos.12175100 and 11975132)the Construct Program of the Key Discipline in Hunan Province+5 种基金the Research Foundation of Education Bureau of Hunan Province,China(Nos.21B0402,18A237,22A0305)the Natural Science Foundation of Hunan Province,China(No.2018JJ2321)the Innovation Group of Nuclear and Particle Physics in USCthe Shandong Province Natural Science Foundation,China(No.ZR2022JQ04)the Opening Project of Cooperative Innovation Center for Nuclear Fuel Cycle Technology and Equipment,University of South China(No.2019KFZ10)the Hunan Provincial Innovation Foundation for Postgraduate(No.CX20251453)。
文摘In this study,the effects of laser fields that can be achieved in the near future on cluster penetration probability and half-life are quantitatively investigated.The calculation results show that extreme laser fields can slightly change the cluster-decay half-life by affecting the penetration probability within a narrow range.Subsequently,we discuss the correlation between the change rate of the penetration probability and the tunneling path.The results indicate that for different parent nuclei emitting the same cluster,nuclei with longer tunneling paths are more easily affected by the laser fields.The shell effect on this correlation is also observed.In addition,the impact of laser fields on the penetration probability in any direction is investigated.
文摘The global climate change and ocean acidification brought about by the anthropogenic release of carbon dioxide gas into the air is considered one of the greatest problems facing marine life.In this research,the interactions between two species of fish(the gold mollies and tiger barb)were investigated under two different environmental conditions,an elevated temperature of 28℃ and a low pH of 5 and a normal pH of 7 and a normal temperature of 24℃.The mollies at pH 7 and a temperature of 24℃ exhibited scary interactions with the tiger barb.They were scared and ran fast away from the tiger barb.At the same time,the mollies at pH 5 and a temperature of 28℃ interacted normally as though both species were one species showing behavioral changes due to these two stressors(pH 5 and elevated temperature 28℃).This could be the only research that has addressed how the kinematics and swimming interactions of two species of fish changed in response to elevated temperature and low pH.
文摘Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.
基金supported by the Ministry of Education,Culture,Research,and Technology Directorate General of Higher Education,Research,and Technology grant number[2147/UN2621/PN/2022].
文摘The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated spatial plan.The study used a quantitative survey using Landsat images in 2016,2019,and 2022.The data analysis techniques used geographic information systems integrated with Artificial Neural Network(ANN)and Cellular Automata(CA)models.This study aims to predict land-use change in 2031,evaluate its alignment with spatial planning,and provide guidance for controlling land-use change.The results showed that there has been an increase in land use.In 2019,built-up land reached 7,069.65 Ha.The model shows its ability to predict land simulation and transformation,where it is predicted that built-up land in 2031 will experience an increase of up to 40.10%,so development and change cannot be avoided every year.This study also suggests that decision-makers and local governments should reconsider spatial planning strategies.This study shows that there have been many land use changes from 2016 to 2022.The model shows its ability to predict simulation and land transformation.When using the model,there are many changes in the land use area in 2031.This is due to wet agricultural land turning into built-up land by almost 70%.This study shows that road network influence land-use change.The cellular automata model managed to capture the complexity with simple rules.Predictions for future research should focus on conserving wetlands and primary forests.
文摘We present analog clocks fitted to the Mars solar day.These clocks use the standard Earth-based second of the International System of Units(SI)as their operational unit of time,unlike current practice for Mars timekeeping.We discuss the importance of preserving the SI second.On this basis,we identify the two analog clocks most suitable for public use by a future Mars population.These are a 20-hour clock with a hand motion similar to that of the standard Earth clock,and a 24-hour clock with a novel“Martian”hand motion which strikes the hour when all 3 hands converge onto that hour mark on the dial.Both clocks have Earth-day equivalents to assist learning.We also present a 24-hour“SpaceClock”,similar to the Martian clock but with no favored reference plane,hence equally readable from any viewing orientation.
文摘Fractional differential equations have garnered significant attention within the mathematical and physical sciences due to the diverse range of fractional operators available.Fractional calculus has demonstrated its utility across various disciplines,including biological modeling[1–5],applications in physics[6,7],most notably in the formulation of fractional diffusion equations,in robotics,and emerging areas such as intelligent artificial systems,among others.Numerous types of fractional operators exist,including those characterized by singular kernels,such as the Caputo and Riemann-Liouville derivatives[8,9].It is important to highlight that the Riemann-Liouville derivative exhibits certain limitations;most notably,the derivative of a constant is not zero,which poses a significant inconvenience.To circumvent this issue,the Caputo derivative was introduced.Additionally,there are fractional derivatives with non-singular kernels,such as the Caputo-Fabrizio derivative[10]and the Atangana-Baleanu fractional derivative[11],each providing unique advantages for modeling purposes.Given the growing interest in utilizing fractional operators for various modeling scenarios,it is imperative to propose robust methodologies for obtaining both approximate and exact solutions.Consequently,this special issue emphasizes the exploration of diverse numerical schemes aimed at deriving approximate solutions for the models under consideration.Furthermore,analytical methods have also been discussed,providing additional avenues for obtaining exact solutions.
文摘Cyber-Physical Systems(CPS)represent an integration of computational and physical elements,revolutionizing industries by enabling real-time monitoring,control,and optimization.A complementary technology,Digital Twin(DT),acts as a virtual replica of physical assets or processes,facilitating better decision making through simulations and predictive analytics.CPS and DT underpin the evolution of Industry 4.0 by bridging the physical and digital domains.This survey explores their synergy,highlighting how DT enriches CPS with dynamic modeling,realtime data integration,and advanced simulation capabilities.The layered architecture of DTs within CPS is examined,showcasing the enabling technologies and tools vital for seamless integration.The study addresses key challenges in CPS modeling,such as concurrency and communication,and underscores the importance of DT in overcoming these obstacles.Applications in various sectors are analyzed,including smart manufacturing,healthcare,and urban planning,emphasizing the transformative potential of CPS-DT integration.In addition,the review identifies gaps in existing methodologies and proposes future research directions to develop comprehensive,scalable,and secure CPSDT systems.By synthesizing insights fromthe current literature and presenting a taxonomy of CPS and DT,this survey serves as a foundational reference for academics and practitioners.The findings stress the need for unified frameworks that align CPS and DT with emerging technologies,fostering innovation and efficiency in the digital transformation era.
基金supported by 2023 Key Supported Project of the 14th Five Year Plan for Education and Science in Hunan Province with No.XJK23AXX0012021 Supported Project of the Educational Science Plan in Hunan Province with No.XJK21BXX010.
文摘1 Introduction onMultimodal Learning in Image Processing IP(Image processing),as a classical research domain in computer application technology,has been researched for decades.It is one of the most important research directions in computer vision,which is the basis for many current hotspots such as intelligent transportation/education/industry,etc.Because image processing is the strongest link for AI(artificial intelligence)applying to real world application,it has been a challenging research field with the development of AI,from DNN(deep convolutional network),Attention/LSTM(long-short term memory),to Transformer/Diffusion/Mamba based GAI(generated AI)models,e.g.,GPT and Sora[1].Today,the description ability of single-model feature limits the performance of image processing.More comprehensive description of the image is required to match the computational performance of current large scale models.
文摘Pollution of transboundary rivers can result from anthropogenic activities in their watersheds.In this study,sediment traps were deployed to determine the fluxes,concentrations,and health risks associated with arsenic,cadmium,mercury,lead,and iron in the estuaries of three transboundary rivers(Comoé,Bia,and Tanoé)in West Africa.Thus,the analysis of metal-associated sedimentation particle samples collected in rainy,flood,and dry seasons was required.Sediment traps were used to calculate the metal fluxes associated with sedimentation particles towards the Atlantic Ocean.Finally,the carcinogenic and non-carcinogenic risks of ingestion and dermal contact associated with sedimentation particles were assessed.The results showed that the total concentrations of trace metals in particulate matter were higher than in the UCC(Upper Crust Continental),with the exception of lead.The highest fluxes of lead,mercury,iron and arsenic associated with sedimented particles were observed during flood periods in the estuary of the Comoé,Bia and Tanoérivers.Cadmium fluxes associated with sedimentation particles were highest in the rainy season in the Bia and Comoéestuaries and in the flood season in the Tanoéestuary.Pearson’s correlation analysis and the enrichment factor showed that the trace metals were derived from anthropogenic activities such as mining and farming.In addition,contamination indices showed that sediment particles in the estuaries of the three rivers were severely contaminated with mercury.However,the results of potential human health risks associated with trace metals show that there is no probability of exposure of the community to harmful and carcinogenic effects through ingestion and dermal absorption of sediment particles.It is essential to integrate the information from this study into policy-and decision-making processes for better management of transboundary river water resources in coastal countries,particularly the Côte d’Ivoire.
文摘Background Zonal application maps are designed to represent field variability using key variables that can be translated into tailored management practices.For cotton,zonal maps for crop growth regulator(CGR)applications under variable-rate(VR)strategies are commonly based exclusively on vegetation indices(VIs)variability.However,VIs often saturate in dense crop vegetation areas,limiting their effectiveness in distinguishing variability in crop growth.This study aimed to compare unsupervised framework(UF)and supervised framework(SUF)approaches for generat-ing zonal application maps for CGR under VR conditions.During 2022-2023 agricultural seasons,an UF was employed to generate zonal maps based on locally collected field data on plant height of cotton,satellite imagery,soil texture,and phenology data.Subsequently,a SUF(based on historical data between 2020-2021 to 2022-2023 agricultural seasons)was developed to predict plant height using remote sensing and phenology data,aiming to replicate same zonal maps but without relying on direct field measurements of plant height.Both approaches were tested in three fields and on two different dates per field.Results The predictive model for plant height of SUF performed well,as indicated by the model metrics.However,when comparing zonal application maps for specific field-date combinations,the predicted plant height exhibited lower variability compared with field measurements.This led to variable compatibility between SUF maps,which utilized the model predictions,and the UF maps,which were based on the real field data.Fields characterized by much pronounced soil texture variability yielded the highest compatibility between the zonal application maps produced by both SUF and UF approaches.This was predominantly due to the greater consistency in estimating plant development patterns within these heterogeneous field environments.While VR application approach can facilitate product savings during the application operation,other key factors must be considered.These include the availability of specialized machinery required for this type of applications,as well as the inherent operational costs associated with applying a single CGR product which differs from the typical uniform rate applications that often integrate multi-ple inputs.Conclusion Predictive modeling shows promise for assisting in the creation of zonal application maps for VR of CGR applications.However,the degree of agreement with the actual variability in crop growth found in the field should be evaluated on a field-by-field basis.The SUF approach,which is based on plant heigh prediction,demonstrated potential for supporting the development of zonal application maps for VR of CGR applications.However,the degree to which this approach aligns itself with the actual variability in crop growth observed in the field may vary,necessi-tating field-by-field evaluation.
文摘Soil erosion from water has become a relevant issue at global level.In Guinea in particular,erosion has worrying effects,due to natural conditions and human impact,especially in the Nzérékore city in forest region.This paper proposed a soil erosion modeling by rainfall effect in the prefecture of N'Zérékoré.To achieve this objective,monthly and annual rainfall data for the N'Zérékorécity were collected at the meteorological station over the period from 1980 to 2024.The analysis of rainfall aggressiveness was possible using the Fournier index.For data processing,we used Microsoft Excel,Python and the ARIMA(AutoRegressive Integrated Moving Average)model for soil aggressiveness predicted by rainfall.It was found that,from 2000 to 2009,erosion was higher compared to other periods with a rate of 60%,or 6 years of high rainfall aggression.From the periods 1990 to 1999 and 2010 to 2019,the lowest rainfall aggressiveness was recorded,with 60%or 6 years of low erosivity.However,from period 1980 to 1989 the highest rate(70%)of very high rainfall erosivity was recorded.The results show three levels of rainfall aggressiveness on an annual scale:a very high level of erosivity with a rate of 22.2%or 10 years,followed by a high level of 35.6%or 16 years of strong erosion.The moderate erosivity level corresponds to 42.2%or 19 years.The model predicts a stability of the erosivity index around 77.14 over the period 2025-2034.During the forty(45)years the rainfall erosivity index was very unstable characterized by strong erosion,however it would be stable in the next ten(10)years.
基金the Asian Institute of Technology,Khlong Nueng,Thailand for their support in carrying out this study。
文摘Deep Learning(DL)offers promising solutions for analyzing wearable signals and gaining valuable insights into cognitive disorders.While previous review studies have explored various aspects of DL in cognitive healthcare,there remains a lack of comprehensive analysis that integrates wearable signals,data processing techniques,and the broader applications,benefits,and challenges of DL methods.Addressing this limitation,our study provides an extensive review of DL’s role in cognitive healthcare,with a particular emphasis on wearables,data processing,and the inherent challenges in this field.This review also highlights the considerable promise of DL approaches in addressing a broad spectrum of cognitive issues.By enhancing the understanding and analysis of wearable signal modalities,DL models can achieve remarkable accuracy in cognitive healthcare.Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),and Long Short-term Memory(LSTM)networks have demonstrated improved performance and effectiveness in the early diagnosis and progression monitoring of neurological disorders.Beyond cognitive impairment detection,DL has been applied to emotion recognition,sleep analysis,stress monitoring,and neurofeedback.These applications lead to advanced diagnosis,personalized treatment,early intervention,assistive technologies,remote monitoring,and reduced healthcare costs.Nevertheless,the integration of DL and wearable technologies presents several challenges,such as data quality,privacy,interpretability,model generalizability,ethical concerns,and clinical adoption.These challenges emphasize the importance of conducting future research in areas such as multimodal signal analysis and explainable AI.The findings of this review aim to benefit clinicians,healthcare professionals,and society by facilitating better patient outcomes in cognitive healthcare.
