Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop spec...Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop species,is a promising source forβ-ionone production.This study aimed to modify CCD4 activity to increaseβ-ionone yield in tobacco.We identified two isoforms of CCD4 in N.tabacum,NtCCD4a and NtCCD4b,with NtCCD4a exhibiting significantly higher expression levels than NtCCD4b.Using solid-phase microextraction gas chromatography-mass spectrometry(SPME-GC–MS),we demonstrated that NtCCD4a effectively catalyzes the cleavage ofβ-carotene to produceβ-ionone.To improve its enzymatic activity,we applied structure-based rational design to reconstruct the active pocket of NtCCD4a,followed by high-throughput screening of mutant variants.Three single base mutants,F181G,F184L,and F337M,in NtCCD4a showed enhancedβ-ionone production compared to the wild-type,with F337M yielding the highest amount.No synergistic effects were observed among the three mutants.Transgenic tobacco plants expressing the F181G,F184L,and F337M mutations had acceleratedβ-carotene cleavage and increasedβ-ionone production relative to the wild-type NtCCD4a.Our results establish a framework for the design of CCD4 in major crop species through genome editing technology.展开更多
During the process of rail grinding,the local high temperature generated in the grinding contact area can affect the physical properties of the rail,thereby affecting its service performance.Therefore,studying the tem...During the process of rail grinding,the local high temperature generated in the grinding contact area can affect the physical properties of the rail,thereby affecting its service performance.Therefore,studying the temperature field of rail grinding is of great significance for improving the quality of rail grinding.In this paper,a calculation model for the grinding depth and contour of the semi elliptical contact area was established based on the contact geometry relationship between the steel rail and the abrasive belt for the first time,and the influence of grinding process parameters on the parameters of the contact area was elucidated.Combined with the characteristics of steel rail abrasive belt grinding process,a calculation model for heat flux density in the semi elliptical contact area was obtained and verified.Based on the above research results,the temperature field of the moving surface heat source with continuous action in the semi elliptical contact area is solved by discretization.Research has shown that under the set grinding process parameters,the simulation and theoretical temperature changes of the rail grinding surface in the semi elliptical contact area are similar and almost reach the maximum temperature at the same time.The relative error between the simulation and theoretical maximum temperature is 6.14%.Comparative analysis of theoretical calculations and simulation of maximum temperature under different grinding speeds shows good consistency in size and trend.The correctness of the above theoretical model has been verified through existing research results.This study proposes a new method for calculating the tem-perature field in the actual semi elliptical grinding area considering the rail profile,which has important the-oretical significance for the calculation of the temperature field and stress field in the grinding area.展开更多
Dear Editor,This letter presents techniques to simplify dataset generation for instance segmentation of raw meat products,a critical step toward automating food production lines.Accurate segmentation is essential for ...Dear Editor,This letter presents techniques to simplify dataset generation for instance segmentation of raw meat products,a critical step toward automating food production lines.Accurate segmentation is essential for addressing challenges such as occlusions,indistinct edges,and stacked configurations,which demand large,diverse datasets.To meet these demands,we propose two complementary approaches:a semi-automatic annotation interface using tools like the segment anything model(SAM)and GrabCut and a synthetic data generation pipeline leveraging 3D-scanned models.These methods reduce reliance on real meat,mitigate food waste,and improve scalability.Experimental results demonstrate that incorporating synthetic data enhances segmentation model performance and,when combined with real data,further boosts accuracy,paving the way for more efficient automation in the food industry.展开更多
1.Introduction As China’s first floating production platform in ultra-deepwater,the“Deep Sea No.1”energy station is a milestone in China’s deepwater resource utilization.The energy station is located in the LS17-2...1.Introduction As China’s first floating production platform in ultra-deepwater,the“Deep Sea No.1”energy station is a milestone in China’s deepwater resource utilization.The energy station is located in the LS17-2 gas field,150 km off the southeast coast of Hainan Island,China.It is a semi-submersible platform(Fig.1)with a displacement of 101 thousand tonnes and an operational draft of 35 to 40 m.The platform is permanently moored in 1422 m water by 16 chain-polyester-chain mooring lines in a 4×4 pattern,and six steel catenary risers(SCRs)are attached to the platform.It is the world’s first and only semi-submersible platform with the function of condensate storage,so it can be regarded as a floating production storage and offloading(FPSO)unit.With the ability to produce 3 billion m3 of natural gas each year(enough for over 10 million families),the Deep Sea No.1 energy station is a key step toward China’s energy independence.The LS17-2 gas field,where the Deep Sea No.1 energy station is located,was discovered in 2014.Plans for its development were made in 2015,followed by research and a preliminary design.Deep Sea No.1 went into operation on June 25,2021,and will operate onsite continuously without dry-docking for 30 years.展开更多
Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],th...Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],the algorithm combines a consensus protocol on with a local Riemannian gradient term,but the state of each agent evolves on the nonlinear manifold.In absence of global information for each node,a coordinator is introduced in the communication network to ensure that all agents achieve convergence with consensus.Resorting to Lyapunov approaches,it is shown that the proposed algorithm reaches an optimal solution.展开更多
Recent developments suggest that the race to power electric vehicles(EV)withsolid-statebatteries(SSB)hasgainedmomentum.In January 2024,Toyota Motor Corporation(Toyota City,Japan)confirmed its previously stated plans t...Recent developments suggest that the race to power electric vehicles(EV)withsolid-statebatteries(SSB)hasgainedmomentum.In January 2024,Toyota Motor Corporation(Toyota City,Japan)confirmed its previously stated plans to start producing SSB EV in the2027-2028timeframe[1].InMay2024,itemergedthattheChi-nesegovernmentplanstoinvestmorethansixbillionCNY(830mil-lion USD)in projects intended to speed up SSB development[2].In June 2024,the automaker Nio(Shanghai,China)began supplying customers with EVs containing“semi-solid-state”batteries-a hybrid technology that could serve as a stepping stone to fully solid versions[3].In September 2024,SAIC Motor(Shanghai,China),China’s largest automobile manufacturer,announced that it would deliver its first SSB-powered vehicles in 2025[4].展开更多
With the rapid urbanization and exponential population growth in China,two-wheeled vehicles have become a popular mode of transportation,particularly for short-distance travel.However,due to a lack of safety awareness...With the rapid urbanization and exponential population growth in China,two-wheeled vehicles have become a popular mode of transportation,particularly for short-distance travel.However,due to a lack of safety awareness,traffic violations by two-wheeled vehicle riders have become a widespread concern,contributing to urban traffic risks.Currently,significant human and material resources are being allocated to monitor and intercept non-compliant riders to ensure safe driving behavior.To enhance the safety,efficiency,and cost-effectiveness of traffic monitoring,automated detection systems based on image processing algorithms can be employed to identify traffic violations from eye-level video footage.In this study,we propose a robust detection algorithm specifically designed for two-wheeled vehicles,which serves as a fundamental step toward intelligent traffic monitoring.Our approach integrates a novel convolutional and attention mechanism to improve detection accuracy and efficiency.Additionally,we introduce a semi-supervised training strategy that leverages a large number of unlabeled images to enhance the model’s learning capability by extracting valuable background information.This method enables the model to generalize effectively to diverse urban environments and varying lighting conditions.We evaluate our proposed algorithm on a custom-built dataset,and experimental results demonstrate its superior performance,achieving an average precision(AP)of 95%and a recall(R)of 90.6%.Furthermore,the model maintains a computational efficiency of only 25.7 GFLOPs while achieving a high processing speed of 249 FPS,making it highly suitable for deployment on edge devices.Compared to existing detection methods,our approach significantly enhances the accuracy and robustness of two-wheeled vehicle identification while ensuring real-time performance.展开更多
Photoredox catalysis has made significant advances in stateof-the-art chemical synthesis,drawing energy from inexhaustible light and enabling various organic transformations to occur under mild reaction conditions.Ove...Photoredox catalysis has made significant advances in stateof-the-art chemical synthesis,drawing energy from inexhaustible light and enabling various organic transformations to occur under mild reaction conditions.Over the past few years,a variety of homogeneous and heterogeneous photocatalysts have been applied in the photoredox catalysis.Heterogeneous photoredox catalysis offers advantages such as easy separation and superior recyclability compared to homogeneous counterparts,although homogenous catalysts are usually associated with higher activities and selectivity.From a practical perspective,an optimal photoredox catalytic system would integrate the advantages of both homogeneous and heterogeneous cases.展开更多
Because methane is flammable and explosive,the detection process is time-consuming and dangerous,and it is difficult to obtain labeled data.In order to reduce the dependence on marker data when detecting methane conce...Because methane is flammable and explosive,the detection process is time-consuming and dangerous,and it is difficult to obtain labeled data.In order to reduce the dependence on marker data when detecting methane concentration using tunable diode laser absorption spectroscopy(TDLAS)technology,this paper designs a methane gas acquisition platform based on TDLAS and proposes a methane gas concentration detection model based on semi-supervised learning.Firstly,the methane gas is feature extracted,and then semi-supervised learning is introduced to select the optimal feature combination;subsequently,the traditional whale optimization algorithm is improved to optimize the parameters of the random forest to detect the methane gas concentration.The results show that the model is not only able to select the optimal feature combination under limited labeled data,but also has an accuracy of 94.25%,which is better than the traditional model,and is robust in terms of parameter optimization.展开更多
Dear Editor,This letter introduces an innovative event-triggered secondary control strategy for Microgrid(MG)to address challenges of low inertia and renewable energy integration.Utilizing semi-Markov switching topolo...Dear Editor,This letter introduces an innovative event-triggered secondary control strategy for Microgrid(MG)to address challenges of low inertia and renewable energy integration.Utilizing semi-Markov switching topologies,this method employs semi-Markov jump processes for accurate load forecasting,facilitating adaptive adjustments of distributed generators(DGs)in response to load changes.展开更多
The research on materials capable of manipulating thermal conductivity continues to fuel the development of thermal controlling devices.Here,using ab initio calculations and the Boltzmann transport equation,we demonst...The research on materials capable of manipulating thermal conductivity continues to fuel the development of thermal controlling devices.Here,using ab initio calculations and the Boltzmann transport equation,we demonstrate that the thermal conductivity of semi-fluorinated hexagonal boron nitride(h-BN)can be reversibly manipulated at 300 K,and the ratio for the regulation of thermal conductivity reaches up to 11.23.Such behavior originates from the high sensitivity of thermal conductivity to magnetic ordering.Semi-fluorinated h-BN is a paramagnetic material at room temperature due to its Curie temperature of 270 K.Impressively,semi-fluorinated h-BN can be modulated into a ferromagnetic system by adding an external magnetic field of 11.15 T,resulting in greatly and reversibly tunable thermal conductivity at room temperature.Furthermore,in-depth analyses of phonon properties show that compared with the paramagnetic phase,both ferromagnetic and antiferromagnetic semi-fluorinated h-BN significantly reduce phonon scattering and anharmonicity,thereby enhancing thermal conductivity.The results qualify semi-fluorinated h-BN as a potential candidate for thermal switching applications at room temperature.展开更多
The transverse single-spin asymmetry forρ^(0) production in semi-inclusive deep inelastic scattering was recently reported by the COMPASS Collaboration.Using the Sivers function extracted from pion and kaon productio...The transverse single-spin asymmetry forρ^(0) production in semi-inclusive deep inelastic scattering was recently reported by the COMPASS Collaboration.Using the Sivers function extracted from pion and kaon productions,we perform a calculation of the Sivers asymmetry within the transverse momentum-dependent factorization.Our results are consistent with the COMPASS data,supporting the universality of the Sivers function in the semi-inclusive deep inelastic scattering process for different final-state hadrons within current experimental uncertainties.While different parametrizations of the Sivers function from global analyses allow describing the data equally well,we obtain very different predictions on the Sivers asymmetry ofρand K^(*)productions at electron-ion colliders,which therefore are expected to provide further constraints.展开更多
基金funded High-Level Talents project of Henan Agricultural University(111-30501301)Project of the National key R&D Program of China(2021YFA0909600)+3 种基金Natural Science Foundation of Henan Province(242300420141)the China Postdoctoral Science Foundation(2020M672308)Cultivation Program for Young Backbone Teachers at Henan University of Technology(DC 11)Science Project 110202101042(JY 19)/2022530000241007,110202102033,110202202038.
文摘Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop species,is a promising source forβ-ionone production.This study aimed to modify CCD4 activity to increaseβ-ionone yield in tobacco.We identified two isoforms of CCD4 in N.tabacum,NtCCD4a and NtCCD4b,with NtCCD4a exhibiting significantly higher expression levels than NtCCD4b.Using solid-phase microextraction gas chromatography-mass spectrometry(SPME-GC–MS),we demonstrated that NtCCD4a effectively catalyzes the cleavage ofβ-carotene to produceβ-ionone.To improve its enzymatic activity,we applied structure-based rational design to reconstruct the active pocket of NtCCD4a,followed by high-throughput screening of mutant variants.Three single base mutants,F181G,F184L,and F337M,in NtCCD4a showed enhancedβ-ionone production compared to the wild-type,with F337M yielding the highest amount.No synergistic effects were observed among the three mutants.Transgenic tobacco plants expressing the F181G,F184L,and F337M mutations had acceleratedβ-carotene cleavage and increasedβ-ionone production relative to the wild-type NtCCD4a.Our results establish a framework for the design of CCD4 in major crop species through genome editing technology.
基金Supported by National Natural Science Foundation of China(Grant No.52275399).
文摘During the process of rail grinding,the local high temperature generated in the grinding contact area can affect the physical properties of the rail,thereby affecting its service performance.Therefore,studying the temperature field of rail grinding is of great significance for improving the quality of rail grinding.In this paper,a calculation model for the grinding depth and contour of the semi elliptical contact area was established based on the contact geometry relationship between the steel rail and the abrasive belt for the first time,and the influence of grinding process parameters on the parameters of the contact area was elucidated.Combined with the characteristics of steel rail abrasive belt grinding process,a calculation model for heat flux density in the semi elliptical contact area was obtained and verified.Based on the above research results,the temperature field of the moving surface heat source with continuous action in the semi elliptical contact area is solved by discretization.Research has shown that under the set grinding process parameters,the simulation and theoretical temperature changes of the rail grinding surface in the semi elliptical contact area are similar and almost reach the maximum temperature at the same time.The relative error between the simulation and theoretical maximum temperature is 6.14%.Comparative analysis of theoretical calculations and simulation of maximum temperature under different grinding speeds shows good consistency in size and trend.The correctness of the above theoretical model has been verified through existing research results.This study proposes a new method for calculating the tem-perature field in the actual semi elliptical grinding area considering the rail profile,which has important the-oretical significance for the calculation of the temperature field and stress field in the grinding area.
基金supported by European Union’s Horizon Europe research and innovation programme,project AGILEHAND(Smart Grading,Handling and Packaging Solutions for Soft and Deformable Products in Agile and Reconfigurable Lines)(101092043).
文摘Dear Editor,This letter presents techniques to simplify dataset generation for instance segmentation of raw meat products,a critical step toward automating food production lines.Accurate segmentation is essential for addressing challenges such as occlusions,indistinct edges,and stacked configurations,which demand large,diverse datasets.To meet these demands,we propose two complementary approaches:a semi-automatic annotation interface using tools like the segment anything model(SAM)and GrabCut and a synthetic data generation pipeline leveraging 3D-scanned models.These methods reduce reliance on real meat,mitigate food waste,and improve scalability.Experimental results demonstrate that incorporating synthetic data enhances segmentation model performance and,when combined with real data,further boosts accuracy,paving the way for more efficient automation in the food industry.
文摘1.Introduction As China’s first floating production platform in ultra-deepwater,the“Deep Sea No.1”energy station is a milestone in China’s deepwater resource utilization.The energy station is located in the LS17-2 gas field,150 km off the southeast coast of Hainan Island,China.It is a semi-submersible platform(Fig.1)with a displacement of 101 thousand tonnes and an operational draft of 35 to 40 m.The platform is permanently moored in 1422 m water by 16 chain-polyester-chain mooring lines in a 4×4 pattern,and six steel catenary risers(SCRs)are attached to the platform.It is the world’s first and only semi-submersible platform with the function of condensate storage,so it can be regarded as a floating production storage and offloading(FPSO)unit.With the ability to produce 3 billion m3 of natural gas each year(enough for over 10 million families),the Deep Sea No.1 energy station is a key step toward China’s energy independence.The LS17-2 gas field,where the Deep Sea No.1 energy station is located,was discovered in 2014.Plans for its development were made in 2015,followed by research and a preliminary design.Deep Sea No.1 went into operation on June 25,2021,and will operate onsite continuously without dry-docking for 30 years.
基金supported by the National Key Research and Development Program of China(2022YFA1004701)the National Natural Science Foundation of China(72271187,62373283)Shanghai Municipal Science and Technology Major(2021SHZDZX0100).
文摘Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],the algorithm combines a consensus protocol on with a local Riemannian gradient term,but the state of each agent evolves on the nonlinear manifold.In absence of global information for each node,a coordinator is introduced in the communication network to ensure that all agents achieve convergence with consensus.Resorting to Lyapunov approaches,it is shown that the proposed algorithm reaches an optimal solution.
文摘Recent developments suggest that the race to power electric vehicles(EV)withsolid-statebatteries(SSB)hasgainedmomentum.In January 2024,Toyota Motor Corporation(Toyota City,Japan)confirmed its previously stated plans to start producing SSB EV in the2027-2028timeframe[1].InMay2024,itemergedthattheChi-nesegovernmentplanstoinvestmorethansixbillionCNY(830mil-lion USD)in projects intended to speed up SSB development[2].In June 2024,the automaker Nio(Shanghai,China)began supplying customers with EVs containing“semi-solid-state”batteries-a hybrid technology that could serve as a stepping stone to fully solid versions[3].In September 2024,SAIC Motor(Shanghai,China),China’s largest automobile manufacturer,announced that it would deliver its first SSB-powered vehicles in 2025[4].
基金supported by the Natural Science Foundation Project of Fujian Province,China(Grant No.2023J011439 and No.2019J01859).
文摘With the rapid urbanization and exponential population growth in China,two-wheeled vehicles have become a popular mode of transportation,particularly for short-distance travel.However,due to a lack of safety awareness,traffic violations by two-wheeled vehicle riders have become a widespread concern,contributing to urban traffic risks.Currently,significant human and material resources are being allocated to monitor and intercept non-compliant riders to ensure safe driving behavior.To enhance the safety,efficiency,and cost-effectiveness of traffic monitoring,automated detection systems based on image processing algorithms can be employed to identify traffic violations from eye-level video footage.In this study,we propose a robust detection algorithm specifically designed for two-wheeled vehicles,which serves as a fundamental step toward intelligent traffic monitoring.Our approach integrates a novel convolutional and attention mechanism to improve detection accuracy and efficiency.Additionally,we introduce a semi-supervised training strategy that leverages a large number of unlabeled images to enhance the model’s learning capability by extracting valuable background information.This method enables the model to generalize effectively to diverse urban environments and varying lighting conditions.We evaluate our proposed algorithm on a custom-built dataset,and experimental results demonstrate its superior performance,achieving an average precision(AP)of 95%and a recall(R)of 90.6%.Furthermore,the model maintains a computational efficiency of only 25.7 GFLOPs while achieving a high processing speed of 249 FPS,making it highly suitable for deployment on edge devices.Compared to existing detection methods,our approach significantly enhances the accuracy and robustness of two-wheeled vehicle identification while ensuring real-time performance.
基金the National Natural Science Foundation of China(No.22271060),The Department of Chemistry at Fudan University and College of Chemistry and Chemical Engineering at Ningxia University is gratefully acknowledged.
文摘Photoredox catalysis has made significant advances in stateof-the-art chemical synthesis,drawing energy from inexhaustible light and enabling various organic transformations to occur under mild reaction conditions.Over the past few years,a variety of homogeneous and heterogeneous photocatalysts have been applied in the photoredox catalysis.Heterogeneous photoredox catalysis offers advantages such as easy separation and superior recyclability compared to homogeneous counterparts,although homogenous catalysts are usually associated with higher activities and selectivity.From a practical perspective,an optimal photoredox catalytic system would integrate the advantages of both homogeneous and heterogeneous cases.
基金supported by the Ministry of Education Chunhui Program of China(No.HZKY20220304).
文摘Because methane is flammable and explosive,the detection process is time-consuming and dangerous,and it is difficult to obtain labeled data.In order to reduce the dependence on marker data when detecting methane concentration using tunable diode laser absorption spectroscopy(TDLAS)technology,this paper designs a methane gas acquisition platform based on TDLAS and proposes a methane gas concentration detection model based on semi-supervised learning.Firstly,the methane gas is feature extracted,and then semi-supervised learning is introduced to select the optimal feature combination;subsequently,the traditional whale optimization algorithm is improved to optimize the parameters of the random forest to detect the methane gas concentration.The results show that the model is not only able to select the optimal feature combination under limited labeled data,but also has an accuracy of 94.25%,which is better than the traditional model,and is robust in terms of parameter optimization.
基金supported by the Shandong Provincial Natural Science Foundation(ZR2023QF092)the National Natural Science Foundation of China(62373224).
文摘Dear Editor,This letter introduces an innovative event-triggered secondary control strategy for Microgrid(MG)to address challenges of low inertia and renewable energy integration.Utilizing semi-Markov switching topologies,this method employs semi-Markov jump processes for accurate load forecasting,facilitating adaptive adjustments of distributed generators(DGs)in response to load changes.
基金supported by the Postdoctoral Fellowship Program(Grade C)China Postdoctoral Science Foundation(Grant No.GZC20241421)the Sichuan Science and Technology Program(Grant No.2025ZNSFSC0864)the Fundamental Re search Funds for the Central Universities(Grant No.2682025CX029).
文摘The research on materials capable of manipulating thermal conductivity continues to fuel the development of thermal controlling devices.Here,using ab initio calculations and the Boltzmann transport equation,we demonstrate that the thermal conductivity of semi-fluorinated hexagonal boron nitride(h-BN)can be reversibly manipulated at 300 K,and the ratio for the regulation of thermal conductivity reaches up to 11.23.Such behavior originates from the high sensitivity of thermal conductivity to magnetic ordering.Semi-fluorinated h-BN is a paramagnetic material at room temperature due to its Curie temperature of 270 K.Impressively,semi-fluorinated h-BN can be modulated into a ferromagnetic system by adding an external magnetic field of 11.15 T,resulting in greatly and reversibly tunable thermal conductivity at room temperature.Furthermore,in-depth analyses of phonon properties show that compared with the paramagnetic phase,both ferromagnetic and antiferromagnetic semi-fluorinated h-BN significantly reduce phonon scattering and anharmonicity,thereby enhancing thermal conductivity.The results qualify semi-fluorinated h-BN as a potential candidate for thermal switching applications at room temperature.
基金supported by the National Key R&D Program of China(Grant No.2024YFA1611004)the National Natural Science Foundation of China(Grant Nos.12175117,12475084,and 12321005)the Shandong Province Natural Science Foundation(Grant Nos.ZFJH202303 and ZR2024MA012)。
文摘The transverse single-spin asymmetry forρ^(0) production in semi-inclusive deep inelastic scattering was recently reported by the COMPASS Collaboration.Using the Sivers function extracted from pion and kaon productions,we perform a calculation of the Sivers asymmetry within the transverse momentum-dependent factorization.Our results are consistent with the COMPASS data,supporting the universality of the Sivers function in the semi-inclusive deep inelastic scattering process for different final-state hadrons within current experimental uncertainties.While different parametrizations of the Sivers function from global analyses allow describing the data equally well,we obtain very different predictions on the Sivers asymmetry ofρand K^(*)productions at electron-ion colliders,which therefore are expected to provide further constraints.
