In this paper,we investigate a class of factorisable IC quasi-adequate semigroups,so-called,factorisable IC quasi-adequate semigroups of type-（H,I）.Some characterizations of factorisable IC quasi-adequate semigroups...In this paper,we investigate a class of factorisable IC quasi-adequate semigroups,so-called,factorisable IC quasi-adequate semigroups of type-（H,I）.Some characterizations of factorisable IC quasi-adequate semigroups of type-（H,I） are obtained.In particular,we prove that any IC quasi-adequate semigroup has a factorisable IC quasi-adequate subsemigroups of type-（H,I） and a band of cancellative monoids.展开更多
The key purpose of this paper is to open up the concepts of the sum of four squares and the algebra of quaternions into the attempts of factoring semiprimes, the product of two prime numbers. However, the application ...The key purpose of this paper is to open up the concepts of the sum of four squares and the algebra of quaternions into the attempts of factoring semiprimes, the product of two prime numbers. However, the application of these concepts here has been clumsy, and would be better explored by those with a more rigorous mathematical background. There may be real immediate implications on some RSA numbers that are slightly larger than a perfect square.展开更多
The algebraic structure of skew left brace has proved to be useful as a source of settheoretic solutions of theYang-Baxter equation.We study in this paper the connections between left and rightπ-nilpotency and the st...The algebraic structure of skew left brace has proved to be useful as a source of settheoretic solutions of theYang-Baxter equation.We study in this paper the connections between left and rightπ-nilpotency and the structure of finite skew left braces.We also study factorisations of skew left braces and their impact on the skew left brace structure.As a consequence of our study,we define a Fitting-like ideal of a left brace.Our approach depends strongly on a description of a skew left brace in terms of a triply factorised group obtained from the action of the multiplicative group of the skew left brace on its additive group.展开更多
Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drill...Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drilling extension limits,underground target distribution and trajectory collision risks,a model of platform location-wellbore trajectory collaborative optimization for a complex-structure well factory is developed.A hybrid heuristic algorithm is proposed by combining an improved sparrow search algorithm(ISSA)for optimizing platform parameters in the outer layer and a directed artificial bee colony algorithm(DABC)for optimizing trajectory parameters in the inner layer.The alternating iteration of ISSA-DABC facilitates the resolution of the collaborative optimization problem.The ISSA-DABC provides an effective solution to the platform-trajectory collaborative optimization problem for complex-structure well factories and overcomes the tendency of the traditional platform-trajectory stepwise optimization workflow to become trapped in local optima and yield inconsistent designs.The ISSA-DABC has a strong global search capability,fast convergence and good robustness,and can simultaneously satisfy multiple engineering constraints on drilling footage,trajectory complexity and collision risk,and enables automated,workflow-wide generation of constraint-compliant,near-globally optimal platform-trajectory configurations.Field applications further demonstrate that ISSA-DABC significantly reduces the objective function value and collision risk,yielding more rational platform layouts and well factory design parameters.展开更多
Long associated with industrial smoke and heavy pollution,the chemical industry is undergoing a rapid transition to cleaner production.In the Jintang Economic Development Zone in Chengdu,Sichuan Province,B&M Tech...Long associated with industrial smoke and heavy pollution,the chemical industry is undergoing a rapid transition to cleaner production.In the Jintang Economic Development Zone in Chengdu,Sichuan Province,B&M Tech’s lithium-ion battery materials factory exemplifies this change.展开更多
The mandibular condyle is a critical growth center in craniofacial bone development,especially during postnatal stages.Postnatal condyle osteogenesis requires precise spatiotemporal coordination of growth factor signa...The mandibular condyle is a critical growth center in craniofacial bone development,especially during postnatal stages.Postnatal condyle osteogenesis requires precise spatiotemporal coordination of growth factor signaling cascades and hierarchical gene regulatory networks.Plagl1,which encodes a zinc finger transcription factor,is a paternally expressed gene.We demonstrate that PLAGL1 is highly expressed in cranial neural crest cell(CNCC)-derived lineage cells in mouse condyles.Using the CNCC-derived lineage-specific Plagl1 knockout mouse model,we evaluate the function of PLAGL1 during postnatal mouse condyle development.Our findings show that PLAGL1 contributes significantly to osteoblast differentiation,and its deficiency impairs osteogenic lineage differentiation,which consequently disrupts mandibular condyle development.Mechanistically,insulin-like growth factor 2(IGF2)in complex with IGF-binding proteins(IGFBPs)has been identified as the principal PLAGL1 effector responsible for osteogenic regulation during postnatal condyle morphogenesis.Plagl1 deficiency significantly downregulates the IGF2/IGFBP pathway,leading to disordered glucose metabolism,defective extracellular matrix organization,and impaired ossification.Exogenous IGF2 treatment rescues impaired osteoblast differentiation caused by Plagl1 deficiency.In conclusion,the PLAGL1-IGF2 axis is a critical regulator of osteogenesis during mandibular condyle development.展开更多
针对无线可充电传感器网络中现有充电路径与充电时长联合调度的方法未充分考虑信用分配问题和时序依赖性而导致充电效率低、节点失效多的问题,提出了一种基于单调值函数分解的时空协同充电调度方法。首先研究了保证节点正常工作的充电...针对无线可充电传感器网络中现有充电路径与充电时长联合调度的方法未充分考虑信用分配问题和时序依赖性而导致充电效率低、节点失效多的问题,提出了一种基于单调值函数分解的时空协同充电调度方法。首先研究了保证节点正常工作的充电阈值及充电上限范围;其次简化了问题的动作空间;最后通过门控循环单元提取充电请求队列的时序特征,并通过基于单调值函数分解的多智能体深度强化学习方法得到充电路径与充电时长的联合调度策略。仿真实验表明,该方法与动态时空充电调度方法(a dynamic Spatiotemporal Charging Scheduling scheme based on Deep reinforcement learning,SCSD)、最近作业下一步抢占规则(Nearest-Job-Next with Preemption,NJNP)、先来先服务规则(First-Come-First-Serve,FCFS)相比,失效节点数减少了7.41%~21.88%,充电延迟减少了3.28%~10.94%,吞吐量增加了5.63%~49.3%。展开更多
Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have de...Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have developed a vertical hydroponic breeding system integrated with light-emitting diodes(LEDs)light-ing in a closed plant factory(PF),which significantly accelerates rice growth and generation advance-ment.The results show that indica rice can be harvested as early as after 63 days of cultivation,a 50%reduction compared with field cultivation,enabling the annual harvesting of 5-6 generations within the PF.A hyperspectral imaging(HSI)system and attenuated total reflectance infrared(ATR-IR)spec-troscopy were further employed to characterize the chemical composition of the PF-and field-cultivated rice.Metabolomics analysis with ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)and gas chromatography-mass spectrometry(GC-MS)revealed that,com-pared with the field-cultivated rice,the PF-cultivated rice exhibited an up-regulation of total phenolic acids along with 68 non-volatile and 19 volatile metabolites,such as isovitexin,succinic acid,and methylillicinone F.Overall,this study reveals the unique metabolic profile of PF-cultivated rice and high-lights the potential of PFs to accelerate the breeding of crops such as rice,offering an innovative agricul-tural strategy to support food security in the face of global population growth and climate change.展开更多
The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability an...The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability and resource efficiency,particularly in mass customization scenarios where production schedules must accommodate dynamic and personalized demands.To address the challenges of dynamic task allocation,uncertainty,and realtime decision-making,this paper proposes Pathfinder,a deep reinforcement learning-based scheduling framework.Pathfinder models scheduling data through three key matrices:execution time(the time required for a job to complete),completion time(the actual time at which a job is finished),and efficiency(the performance of executing a single job).By leveraging neural networks,Pathfinder extracts essential features from these matrices,enabling intelligent decision-making in dynamic production environments.Unlike traditional approaches with fixed scheduling rules,Pathfinder dynamically selects from ten diverse scheduling rules,optimizing decisions based on real-time environmental conditions.To further enhance scheduling efficiency,a specialized reward function is designed to support dynamic task allocation and real-time adjustments.This function helps Pathfinder continuously refine its scheduling strategy,improving machine utilization and minimizing job completion times.Through reinforcement learning,Pathfinder adapts to evolving production demands,ensuring robust performance in real-world applications.Experimental results demonstrate that Pathfinder outperforms traditional scheduling approaches,offering improved coordination and efficiency in smart factories.By integrating deep reinforcement learning,adaptable scheduling strategies,and an innovative reward function,Pathfinder provides an effective solution to the growing challenges of multi-robot job scheduling in mass customization environments.展开更多
Aiming at the problem that the existing algorithms for vehicle detection in smart factories are difficult to detect partial occlusion of vehicles,vulnerable to background interference,lack of global vision,and excessi...Aiming at the problem that the existing algorithms for vehicle detection in smart factories are difficult to detect partial occlusion of vehicles,vulnerable to background interference,lack of global vision,and excessive suppression of real targets,which ultimately cause accuracy degradation.At the same time,to facilitate the subsequent positioning of vehicles in the factory,this paper proposes an improved YOLOv8 algorithm.Firstly,the RFCAConv module is combined to improve the original YOLOv8 backbone.Pay attention to the different features in the receptive field,and give priority to the spatial features of the receptive field to capture more vehicle feature information and solve the problem that the vehicle is partially occluded and difficult to detect.Secondly,the SFE module is added to the neck of v8,which improves the saliency of the target in the reasoning process and reduces the influence of background interference on vehicle detection.Finally,the head of the RT-DETR algorithm is used to replace the head in the original YOLOv8 algorithm,which avoids the excessive suppression of the real target while combining the context information.The experimental results show that compared with the original YOLOv8 algorithm,the detection accuracy of the improved YOLOv8 algorithm is improved by 4.6%on the self-made smart factory data set,and the detection speed also meets the real-time requirements of smart factory vehicle detection and subsequent vehicle positioning.展开更多
Li Auto’s Beijing factory is a highly advanced,intelligent,and green-oriented factory.EVERY minute,one MEGA,Li Auto’s flagship multi-purpose vehicle(MPV)priced at over RMB 500,000,rolls off its production line.New-e...Li Auto’s Beijing factory is a highly advanced,intelligent,and green-oriented factory.EVERY minute,one MEGA,Li Auto’s flagship multi-purpose vehicle(MPV)priced at over RMB 500,000,rolls off its production line.New-energy vehicles(NEVs)epitomize China’s upgrade towards premium,intelligent,and green manufacturing.展开更多
基金Supported by the NSF of Jiangxi Province(0511037)
文摘In this paper,we investigate a class of factorisable IC quasi-adequate semigroups,so-called,factorisable IC quasi-adequate semigroups of type-（H,I）.Some characterizations of factorisable IC quasi-adequate semigroups of type-（H,I） are obtained.In particular,we prove that any IC quasi-adequate semigroup has a factorisable IC quasi-adequate subsemigroups of type-（H,I） and a band of cancellative monoids.
文摘The key purpose of this paper is to open up the concepts of the sum of four squares and the algebra of quaternions into the attempts of factoring semiprimes, the product of two prime numbers. However, the application of these concepts here has been clumsy, and would be better explored by those with a more rigorous mathematical background. There may be real immediate implications on some RSA numbers that are slightly larger than a perfect square.
基金supported by the research Grant PGC2018-095140-B-I00 from the Ministerio de Ciencia,Innovacion y Universidades(Spanish Government),the Agencia Estatal de Investigacion(Spain),and FEDER(European Union)PROMETEO/2017/057 from the Generalitat(Valencian Community,Spain).
文摘The algebraic structure of skew left brace has proved to be useful as a source of settheoretic solutions of theYang-Baxter equation.We study in this paper the connections between left and rightπ-nilpotency and the structure of finite skew left braces.We also study factorisations of skew left braces and their impact on the skew left brace structure.As a consequence of our study,we define a Fitting-like ideal of a left brace.Our approach depends strongly on a description of a skew left brace in terms of a triply factorised group obtained from the action of the multiplicative group of the skew left brace on its additive group.
基金Supported by Key Program of Natural Science Foundation of China(52234002)Major Program Project of the National Natural Science Foundation of China(52394255)。
文摘Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drilling extension limits,underground target distribution and trajectory collision risks,a model of platform location-wellbore trajectory collaborative optimization for a complex-structure well factory is developed.A hybrid heuristic algorithm is proposed by combining an improved sparrow search algorithm(ISSA)for optimizing platform parameters in the outer layer and a directed artificial bee colony algorithm(DABC)for optimizing trajectory parameters in the inner layer.The alternating iteration of ISSA-DABC facilitates the resolution of the collaborative optimization problem.The ISSA-DABC provides an effective solution to the platform-trajectory collaborative optimization problem for complex-structure well factories and overcomes the tendency of the traditional platform-trajectory stepwise optimization workflow to become trapped in local optima and yield inconsistent designs.The ISSA-DABC has a strong global search capability,fast convergence and good robustness,and can simultaneously satisfy multiple engineering constraints on drilling footage,trajectory complexity and collision risk,and enables automated,workflow-wide generation of constraint-compliant,near-globally optimal platform-trajectory configurations.Field applications further demonstrate that ISSA-DABC significantly reduces the objective function value and collision risk,yielding more rational platform layouts and well factory design parameters.
文摘Long associated with industrial smoke and heavy pollution,the chemical industry is undergoing a rapid transition to cleaner production.In the Jintang Economic Development Zone in Chengdu,Sichuan Province,B&M Tech’s lithium-ion battery materials factory exemplifies this change.
基金sponsored by funding from the National Natural Science Foundation of China(82201004 to J.D.,81921002 to X.J.,82130027 to X.J.)the Young Elite Scientists Sponsorship Program by CAST(YESS20230102 to J.D.)the innovative research team of high-level local universities in Shanghai(SHSMU-ZLCX20212400 to X.J.).
文摘The mandibular condyle is a critical growth center in craniofacial bone development,especially during postnatal stages.Postnatal condyle osteogenesis requires precise spatiotemporal coordination of growth factor signaling cascades and hierarchical gene regulatory networks.Plagl1,which encodes a zinc finger transcription factor,is a paternally expressed gene.We demonstrate that PLAGL1 is highly expressed in cranial neural crest cell(CNCC)-derived lineage cells in mouse condyles.Using the CNCC-derived lineage-specific Plagl1 knockout mouse model,we evaluate the function of PLAGL1 during postnatal mouse condyle development.Our findings show that PLAGL1 contributes significantly to osteoblast differentiation,and its deficiency impairs osteogenic lineage differentiation,which consequently disrupts mandibular condyle development.Mechanistically,insulin-like growth factor 2(IGF2)in complex with IGF-binding proteins(IGFBPs)has been identified as the principal PLAGL1 effector responsible for osteogenic regulation during postnatal condyle morphogenesis.Plagl1 deficiency significantly downregulates the IGF2/IGFBP pathway,leading to disordered glucose metabolism,defective extracellular matrix organization,and impaired ossification.Exogenous IGF2 treatment rescues impaired osteoblast differentiation caused by Plagl1 deficiency.In conclusion,the PLAGL1-IGF2 axis is a critical regulator of osteogenesis during mandibular condyle development.
文摘针对无线可充电传感器网络中现有充电路径与充电时长联合调度的方法未充分考虑信用分配问题和时序依赖性而导致充电效率低、节点失效多的问题,提出了一种基于单调值函数分解的时空协同充电调度方法。首先研究了保证节点正常工作的充电阈值及充电上限范围;其次简化了问题的动作空间;最后通过门控循环单元提取充电请求队列的时序特征,并通过基于单调值函数分解的多智能体深度强化学习方法得到充电路径与充电时长的联合调度策略。仿真实验表明,该方法与动态时空充电调度方法(a dynamic Spatiotemporal Charging Scheduling scheme based on Deep reinforcement learning,SCSD)、最近作业下一步抢占规则(Nearest-Job-Next with Preemption,NJNP)、先来先服务规则(First-Come-First-Serve,FCFS)相比,失效节点数减少了7.41%~21.88%,充电延迟减少了3.28%~10.94%,吞吐量增加了5.63%~49.3%。
基金supported by the National Key Research and Development Program(2023YFF1001500)the Local Financial Funds of National Agricultural Science and Technology Center,Chengdu(NASC2022KR02,NASC2023TD08,NASC2021ST08,NASC2021PC04,NASC2022KR07,NASC2022KR06,and NASC2023ST04)+2 种基金the Agricultural Science and Technology Innova-tion Program(ASTIP-34-IUA-01,ASTIP-34-IUA-02,ASTIP-IUA-2023003,and ASTIP2024-34-IUA-09)the Central Public-interest Scientific Institution Basal Research Fund(Y2023YJ07 and SZ202403)the Sichuan Science and Technology Program(2023YFN003,2024NSFC1261,2023YFQ0100,and 2023ZYD0089).
文摘Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have developed a vertical hydroponic breeding system integrated with light-emitting diodes(LEDs)light-ing in a closed plant factory(PF),which significantly accelerates rice growth and generation advance-ment.The results show that indica rice can be harvested as early as after 63 days of cultivation,a 50%reduction compared with field cultivation,enabling the annual harvesting of 5-6 generations within the PF.A hyperspectral imaging(HSI)system and attenuated total reflectance infrared(ATR-IR)spec-troscopy were further employed to characterize the chemical composition of the PF-and field-cultivated rice.Metabolomics analysis with ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)and gas chromatography-mass spectrometry(GC-MS)revealed that,com-pared with the field-cultivated rice,the PF-cultivated rice exhibited an up-regulation of total phenolic acids along with 68 non-volatile and 19 volatile metabolites,such as isovitexin,succinic acid,and methylillicinone F.Overall,this study reveals the unique metabolic profile of PF-cultivated rice and high-lights the potential of PFs to accelerate the breeding of crops such as rice,offering an innovative agricul-tural strategy to support food security in the face of global population growth and climate change.
基金supported by National Natural Science Foundation of China under Grant No.62372110Fujian Provincial Natural Science of Foundation under Grants 2023J02008,2024H0009.
文摘The rapid advancement of Industry 4.0 has revolutionized manufacturing,shifting production from centralized control to decentralized,intelligent systems.Smart factories are now expected to achieve high adaptability and resource efficiency,particularly in mass customization scenarios where production schedules must accommodate dynamic and personalized demands.To address the challenges of dynamic task allocation,uncertainty,and realtime decision-making,this paper proposes Pathfinder,a deep reinforcement learning-based scheduling framework.Pathfinder models scheduling data through three key matrices:execution time(the time required for a job to complete),completion time(the actual time at which a job is finished),and efficiency(the performance of executing a single job).By leveraging neural networks,Pathfinder extracts essential features from these matrices,enabling intelligent decision-making in dynamic production environments.Unlike traditional approaches with fixed scheduling rules,Pathfinder dynamically selects from ten diverse scheduling rules,optimizing decisions based on real-time environmental conditions.To further enhance scheduling efficiency,a specialized reward function is designed to support dynamic task allocation and real-time adjustments.This function helps Pathfinder continuously refine its scheduling strategy,improving machine utilization and minimizing job completion times.Through reinforcement learning,Pathfinder adapts to evolving production demands,ensuring robust performance in real-world applications.Experimental results demonstrate that Pathfinder outperforms traditional scheduling approaches,offering improved coordination and efficiency in smart factories.By integrating deep reinforcement learning,adaptable scheduling strategies,and an innovative reward function,Pathfinder provides an effective solution to the growing challenges of multi-robot job scheduling in mass customization environments.
基金funded by Changzhou Science and Technology Project(No.CZ20230025)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.XSJCX23_36).
文摘Aiming at the problem that the existing algorithms for vehicle detection in smart factories are difficult to detect partial occlusion of vehicles,vulnerable to background interference,lack of global vision,and excessive suppression of real targets,which ultimately cause accuracy degradation.At the same time,to facilitate the subsequent positioning of vehicles in the factory,this paper proposes an improved YOLOv8 algorithm.Firstly,the RFCAConv module is combined to improve the original YOLOv8 backbone.Pay attention to the different features in the receptive field,and give priority to the spatial features of the receptive field to capture more vehicle feature information and solve the problem that the vehicle is partially occluded and difficult to detect.Secondly,the SFE module is added to the neck of v8,which improves the saliency of the target in the reasoning process and reduces the influence of background interference on vehicle detection.Finally,the head of the RT-DETR algorithm is used to replace the head in the original YOLOv8 algorithm,which avoids the excessive suppression of the real target while combining the context information.The experimental results show that compared with the original YOLOv8 algorithm,the detection accuracy of the improved YOLOv8 algorithm is improved by 4.6%on the self-made smart factory data set,and the detection speed also meets the real-time requirements of smart factory vehicle detection and subsequent vehicle positioning.
文摘Li Auto’s Beijing factory is a highly advanced,intelligent,and green-oriented factory.EVERY minute,one MEGA,Li Auto’s flagship multi-purpose vehicle(MPV)priced at over RMB 500,000,rolls off its production line.New-energy vehicles(NEVs)epitomize China’s upgrade towards premium,intelligent,and green manufacturing.
