Knowledge-Based Engineering （KBE） is introduced into the ship structural design in this paper. From the implementation of KBE, the design solutions for both Rules Design Method （RDM） and Interpolation Design Meth...Knowledge-Based Engineering （KBE） is introduced into the ship structural design in this paper. From the implementation of KBE, the design solutions for both Rules Design Method （RDM） and Interpolation Design Method （IDM） are generated. The corresponding Finite Element （FE） models are generated. Topological design of the longitudinal structures is studied where the Gaussian Process （GP） is employed to build the surrogate model for FE analysis. Multi-objective optimization methods inspired by Pareto Front are used to reduce the design tank weight and outer surface area simultaneously. Additionally, an enhanced Level Set Method （LSM） which employs implicit algorithm is applied to the topological design of typical bracket plate which is used extensively in ship structures. Two different sets of boundary conditions are considered. The proposed methods show satisfactory efficiency and accuracy.展开更多
Knowledge-based engineering(KBE) has made success in automobile and molding design industry, and it is introduced into the ship structural design in this paper. From the implementation of KBE, the deterministic design...Knowledge-based engineering(KBE) has made success in automobile and molding design industry, and it is introduced into the ship structural design in this paper. From the implementation of KBE, the deterministic design solutions for both rules design method(RDM) and interpolation design method(IDM) are generated. The corresponding finite element model is generated. Gaussian process(GP) is then employed to build the surrogate model for finite element analysis, in order to increase efficiency and maintain accuracy at the same time, and the multi-modal adaptive importance sampling method is adopted to calculate the corresponding structural reliability.An example is given to validate the proposed method. Finally, the reliabilities of the structures' strength caused by uncertainty lying in water corrosion, static and wave moments are calculated, and the ship structures are optimized to resist the water corrosion by multi-island genetic algorithm. Deterministic design results from the RDM and IDM are compared with each separate robust design result. The proposed method shows great efficiency and accuracy.展开更多
The paper presents a knowledge-based engineering （KBE） approach for ship node components design. In the ship design process, many design tasks need design experiences to support. Howev- er, a ship design process is ...The paper presents a knowledge-based engineering （KBE） approach for ship node components design. In the ship design process, many design tasks need design experiences to support. Howev- er, a ship design process is a complicated process with many simultaneously repetitive and time-con- suming activities. In this research, the method combines KBE with Tribon system＇s built-in devel- opment language tools of Vitesse, captures and applies design knowledge for achieving standard com- ponents intelligent design modeling. A case study and industry implementation illustrate the feasibili- ty of the proposed methodology. The KBE technique can provide not only proper references, sug- gests and supports but also knowledge integrated in the ship structure design. Especially, these rules related to the design can avoid lots of design mistakes. During the ship design stage, getting more precise and better designs will not only reduce the time of rework and wasting resources but also shorten the construction time_ imnrov~ clilnl;hz ~nA nrnf;t展开更多
Development and application of a prototype KBE system is presented, details of the development tools and platforms, system flow chart, hybrid knowledge representation, and integrated system framework are illustrated. ...Development and application of a prototype KBE system is presented, details of the development tools and platforms, system flow chart, hybrid knowledge representation, and integrated system framework are illustrated. All design tasks of a missile seeker are integrated into a single computer-aided environment with a clear guidance to design processes from the user interface.展开更多
The agility of Internet of Things(IoT)software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments.Such developments are focused on reducing the interfa...The agility of Internet of Things(IoT)software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments.Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications.To handle the interfacing complexity problem,this article introduces a Semantic Interfacing Obscuration Model(SIOM)for IoT software-engineered platforms.The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model.Based on the level of obscuration between the infrastructure hardware to the end-user software,the modifications through device replacement,capacity amendments,or interface bug fixes are performed.These modifications are based on the level of semantic obscurations observed during the application service intervals.The obscuration level is determined using knowledge learning as a progression from hardware to software semantics.The results reported were computed using specific metrics obtained from these experimental evaluations:an 8.94%reduction in interfacing complexity and a 15.04%improvement in integration progression.The knowledge of obscurationsmaps themodifications appropriately to reinstate the agility testing of the hardware/software integrations.This modification-based semantics is verified using semantics error,modification time,and complexity.展开更多
A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synth...A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.展开更多
Knowledge-based VisualQuestion Answering(VQA)requires the integration of visual information with external knowledge reasoning.Existing approaches typically retrieve information from external corpora and rely on pretra...Knowledge-based VisualQuestion Answering(VQA)requires the integration of visual information with external knowledge reasoning.Existing approaches typically retrieve information from external corpora and rely on pretrained language models for reasoning.However,their performance is often hindered by the limited capabilities of retrievers and the constrained size of knowledge bases.Moreover,relying on image captions to bridge the modal gap between visual and language modalities can lead to the omission of critical visual details.To address these limitations,we propose the Reflective Chain-of-Thought(ReCoT)method,a simple yet effective framework inspired by metacognition theory.ReCoT effectively activates the reasoning capabilities ofMultimodal Large LanguageModels(MLLMs),providing essential visual and knowledge cues required to solve complex visual questions.It simulates a metacognitive reasoning process that encompasses monitoring,reflection,and correction.Specifically,in the initial generation stage,an MLLM produces a preliminary answer that serves as the model’s initial cognitive output.During the reflective reasoning stage,this answer is critically examined to generate a reflective rationale that integrates key visual evidence and relevant knowledge.In the final refinement stage,a smaller language model leverages this rationale to revise the initial prediction,resulting in amore accurate final answer.By harnessing the strengths ofMLLMs in visual and knowledge grounding,ReCoT enables smaller language models to reason effectively without dependence on image captions or external knowledge bases.Experimental results demonstrate that ReCoT achieves substantial performance improvements,outperforming state-of-the-art methods by 2.26%on OK-VQA and 5.8%on A-OKVQA.展开更多
Lacto-N-neotetraose(LNn T)is a crucial neutral core human milk oligosaccharide(HMO).In this study,we established a LNn T-producing Saccharomyces cerevisiae cell factory through comprehensive metabolic engineering.Spec...Lacto-N-neotetraose(LNn T)is a crucial neutral core human milk oligosaccharide(HMO).In this study,we established a LNn T-producing Saccharomyces cerevisiae cell factory through comprehensive metabolic engineering.Specifically,the de novo biosynthetic pathway of LNn T was assembled by heterologously expressing the lactose permease(lac12)from Kluyveromyces lactis and the glycosyltransferase from Neisseria meningitidis in S.cerevisiae.Subsequently,carbon source regulation based on the glucose-sensitive GAL regulatory system was employed to optimize the expression time of heterologous genes,achieving a production of 15.61 mg/L of LNn T in shake-flask fermentation.In addition,the key rate-limiting steps involved in LNn T synthesis pathway were identified and the corresponding genes were overexpressed to enhance LNn T production,resulting in an 8-fold increase in LNn T titer compared to that of parental strain.To our knowledge,this is the first report on LNn T biosynthesis in S.cerevisiae,opening up the possibility of green production of LNn T using food-safe microorganisms.展开更多
Electrocatalytic nitric oxide(NO)reduction reaction(NORR)is a promising and sustainable process that can simultaneously realize green ammonia(NH3)synthesis and hazardous NO removal.However,current NORR performances ar...Electrocatalytic nitric oxide(NO)reduction reaction(NORR)is a promising and sustainable process that can simultaneously realize green ammonia(NH3)synthesis and hazardous NO removal.However,current NORR performances are far from practical needs due to the lack of efficient electrocatalysts.Engineering the lattice of metal-based nanomaterials via phase control has emerged as an effective strategy to modulate their intrinsic electrocatalytic properties.Herein,we realize boron(B)-insertion-induced phase regulation of rhodium(Rh)nanocrystals to obtain amorphous Rh_(4)B nanoparticles(NPs)and hexagonal close-packed(hcp)RhB NPs through a facile wet-chemical method.A high Faradaic efficiency(92.1±1.2%)and NH_(3) yield rate(629.5±11.0μmol h^(−1) cm^(−2))are achieved over hcp RhB NPs,far superior to those of most reported NORR nanocatalysts.In situ spectro-electrochemical analysis and density functional theory simulations reveal that the excellent electrocatalytic performances of hcp RhB NPs are attributed to the upshift of d-band center,enhanced NO adsorption/activation profile,and greatly reduced energy barrier of the rate-determining step.A demonstrative Zn-NO battery is assembled using hcp RhB NPs as the cathode and delivers a peak power density of 4.33 mW cm−2,realizing simultaneous NO removal,NH3 synthesis,and electricity output.展开更多
With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE ...With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE to stimulate students’innovative consciousness and teamwork ability,enabling students to identify some problems in a certain industry or field and creatively propose feasible solutions,and truly achieve the cultivation of new models in software engineering course teaching with the assistance of generative AI tools?This paper presents research and practice on a new model for cultivating software engineering courses that integrates generative AI and OBE,introduces the specific process of teaching reform and practice,and finally explains the achievements of teaching reform.展开更多
All-inorganic lead-free perovskite solar cells have emerged as environmentally benign candidates;however,their device performance is still constrained by pronounced carrier recombination losses in the bulk and at inte...All-inorganic lead-free perovskite solar cells have emerged as environmentally benign candidates;however,their device performance is still constrained by pronounced carrier recombination losses in the bulk and at interfaces.By combining energy band alignment analysis with detailed modeling of recombination mechanisms,a systematic strategy for optimizing hole transport layers is developed.The results reveal that a negative valence band offset produces a cliff-like interface,which facilitates hole extraction while also accounting for the observed variations in open-circuit voltage.Furthermore,short-circuit current losses are quantitatively attributed to different recombination pathways,modeled by incorporating radiative,Shockley–Read–Hall,Auger,and interface recombination processes.This comprehensive approach not only clarifies the correlation between energy level alignment and recombination dynamics but also highlights the competing roles of band offset and interface defects in determining device performance.The optimized device architecture,based on Ge-based lead-free perovskites,achieves a power conversion efficiency of 25.1%,with an open-circuit voltage of 1.29 V,a short-circuit current density of 22.5 mA·cm^(-2),and a fill factor of 86.3%.These findings provide theoretical guidance for designing stable,high-performance,and environmentally friendly lead-free perovskite solar cells.展开更多
High-performance alloys are indispensable in modern engineering because of their exceptional strength,ductility,corrosion resistance,fatigue resistance,and thermal stability,which are all significantly influenced by t...High-performance alloys are indispensable in modern engineering because of their exceptional strength,ductility,corrosion resistance,fatigue resistance,and thermal stability,which are all significantly influenced by the alloy interface structures.Despite substantial efforts,a comprehensive overview of interface engineering of high-performance alloys has not been presented so far.In this study,the interfaces in high-performance alloys,particularly grain and phase boundaries,were systematically examined,with emphasis on their crystallographic characteristics and chemical element segregations.The effects of the interfaces on the electrical conductivity,mechanical strength,toughness,hydrogen embrittlement resistance,and thermal stability of the alloys were elucidated.Moreover,correlations among various types of interfaces and advanced experimental and computational techniques were examined using big data analytics,enabling robust design strategies.Challenges currently faced in the field of interface engineering and emerging opportunities in the field are also discussed.The study results would guide the development of next-generation high-performance alloys.展开更多
Aqueous zinc(Zn)metal batteries(AZMBs)have distinct advantages in terms of safety and cost-effectiveness.However,the industrial application of AZMBs is currently not ready due to challenges of Zn dendrite growth and t...Aqueous zinc(Zn)metal batteries(AZMBs)have distinct advantages in terms of safety and cost-effectiveness.However,the industrial application of AZMBs is currently not ready due to challenges of Zn dendrite growth and the side reactions such as hydrogen evolution reaction(HER)on the Zn anodes.In this review,we discuss how inorganic interfaces impact the Zn^(2+)plating/stripping reaction and overall cell performance.The discussion is categorized based on the types of inorganic materials,including metal oxides,other metal compounds,and inorganic salts.The proposed protection mechanisms for Zn metal anodes are highlighted,with a focus on the dendrite and HER inhibition mechanisms facilitated by various inorganic materials.We also provide our perspective on the rational design of advanced interfaces to enable highly reversible Zn^(2+)plating/stripping reactions toward highly stable AZMBs,paving the way for their practical implementation in energy storage.展开更多
The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seco...The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.展开更多
Nutritional imbalance has led to many chronic diseases and severely affected people’s quality of life.Developing nutrient-dense crops has emerged as a strategy for improving the current state of human nutritional int...Nutritional imbalance has led to many chronic diseases and severely affected people’s quality of life.Developing nutrient-dense crops has emerged as a strategy for improving the current state of human nutritional intake globally.We summarized recent advances in rice biotechnology breeding focusing on increasing micronutrients and active natural products,highlighting the cutting-edge metabolic engineering technologies and strategies employed.We discussed common challenges and potential solutions in metabolic engineering breeding.On this basis,the future development direction of rice nutrient metabolism industrialization was prospected.展开更多
The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to res...The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to reshape talent cultivation but also presents significant challenges,including skill hollowing,ethical risks,and a growing disconnect between education and industry needs.Currently,graduate-level software engineering education struggles with outdated curricula and insufficient alignment with practical demands.In this paper,we propose a dual-core collaborative framework driven by“GenAI technology”and“industry demand”.Under this framework,we design a four-dimensional capability development path to enhance graduate students’innovation in software engineering practice.This path focuses on①scientific research innovation,②engineering problem-solving,③cross-domain collaborative evolution,and④ethical risk governance.The proposed approach promotes a shift from traditional knowledge transfer to human-machine collaborative innovation,aligning talent cultivation with the demands of the NQPF.展开更多
The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytot...The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytotoxicity.These limitations have catalyzed the development of intelligent stimuli-responsive block copolymers-based bioimaging agents,which was engineered to dynamically respond to endogenous biochemical cues(e.g.,p H gradients,redox potential,enzyme activity,hypoxia environment) or exogenous physical triggers(e.g.,photoirradiation,thermal gradients,ultrasound(US)/magnetic stimuli).Through spatiotemporally controlled structural transformations,stimuli-responsive block copolymers enable precise contrast targeting,activatable signal amplification,and theranostic integration,thereby substantially enhancing signal-to-noise ratios of bioimaging and diagnostic specificity.Hence,this mini-review systematically examines molecular engineering principles for designing p H-,redox-,enzyme-,light-,thermo-,and US/magnetic-responsive polymers,with emphasis on structure-property relationships governing imaging performance modulation.Furthermore,we critically analyze emerging strategies for optical imaging,US synergies,and magnetic resonance imaging(MRI).Multimodal bioimaging has also been elaborated,which could overcome the inherent trade-offs between resolution,penetration depth,and functional specificity in single-modal approaches.By elucidating mechanistic insights and translational challenges,this mini-review aims to establish a design framework of stimuli-responsive block copolymersbased for high fidelity bioimaging agents and accelerate their clinical translation in precise diagnosis and therapy.展开更多
基金financially supported by the Project of Ministry of Education and Finance of China(Grant Nos.200512 and 201335)the Project of the State Key Laboratory of Ocean Engineering,Shanghai Jiao Tong University(Grant No.GKZD010053-10)
文摘Knowledge-Based Engineering （KBE） is introduced into the ship structural design in this paper. From the implementation of KBE, the design solutions for both Rules Design Method （RDM） and Interpolation Design Method （IDM） are generated. The corresponding Finite Element （FE） models are generated. Topological design of the longitudinal structures is studied where the Gaussian Process （GP） is employed to build the surrogate model for FE analysis. Multi-objective optimization methods inspired by Pareto Front are used to reduce the design tank weight and outer surface area simultaneously. Additionally, an enhanced Level Set Method （LSM） which employs implicit algorithm is applied to the topological design of typical bracket plate which is used extensively in ship structures. Two different sets of boundary conditions are considered. The proposed methods show satisfactory efficiency and accuracy.
基金the Project of Ministry of Finance andMinistry of Education of China(Nos.200512 and201335)the State Key Laboratory of Ocean Engineering Foundation of Shanghai Jiao Tong University(No.GKZD010053-10)
文摘Knowledge-based engineering(KBE) has made success in automobile and molding design industry, and it is introduced into the ship structural design in this paper. From the implementation of KBE, the deterministic design solutions for both rules design method(RDM) and interpolation design method(IDM) are generated. The corresponding finite element model is generated. Gaussian process(GP) is then employed to build the surrogate model for finite element analysis, in order to increase efficiency and maintain accuracy at the same time, and the multi-modal adaptive importance sampling method is adopted to calculate the corresponding structural reliability.An example is given to validate the proposed method. Finally, the reliabilities of the structures' strength caused by uncertainty lying in water corrosion, static and wave moments are calculated, and the ship structures are optimized to resist the water corrosion by multi-island genetic algorithm. Deterministic design results from the RDM and IDM are compared with each separate robust design result. The proposed method shows great efficiency and accuracy.
基金Supported by the'Knowledge-based Ship-design Hyper-integrated Platform(KSHIP)'of Ministry of Education and Finance of P.R.China(No.200512)the National Natural Science Foundation of China(No.51009093)
文摘The paper presents a knowledge-based engineering （KBE） approach for ship node components design. In the ship design process, many design tasks need design experiences to support. Howev- er, a ship design process is a complicated process with many simultaneously repetitive and time-con- suming activities. In this research, the method combines KBE with Tribon system＇s built-in devel- opment language tools of Vitesse, captures and applies design knowledge for achieving standard com- ponents intelligent design modeling. A case study and industry implementation illustrate the feasibili- ty of the proposed methodology. The KBE technique can provide not only proper references, sug- gests and supports but also knowledge integrated in the ship structure design. Especially, these rules related to the design can avoid lots of design mistakes. During the ship design stage, getting more precise and better designs will not only reduce the time of rework and wasting resources but also shorten the construction time_ imnrov~ clilnl;hz ~nA nrnf;t
基金Supported by the National High-Tech. R&D Program (863 program) for CIMS(2003AA411350)
文摘Development and application of a prototype KBE system is presented, details of the development tools and platforms, system flow chart, hybrid knowledge representation, and integrated system framework are illustrated. All design tasks of a missile seeker are integrated into a single computer-aided environment with a clear guidance to design processes from the user interface.
文摘The agility of Internet of Things(IoT)software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments.Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications.To handle the interfacing complexity problem,this article introduces a Semantic Interfacing Obscuration Model(SIOM)for IoT software-engineered platforms.The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model.Based on the level of obscuration between the infrastructure hardware to the end-user software,the modifications through device replacement,capacity amendments,or interface bug fixes are performed.These modifications are based on the level of semantic obscurations observed during the application service intervals.The obscuration level is determined using knowledge learning as a progression from hardware to software semantics.The results reported were computed using specific metrics obtained from these experimental evaluations:an 8.94%reduction in interfacing complexity and a 15.04%improvement in integration progression.The knowledge of obscurationsmaps themodifications appropriately to reinstate the agility testing of the hardware/software integrations.This modification-based semantics is verified using semantics error,modification time,and complexity.
基金supported by grants from the Guangxi Science and Technology Major Project(GKAA24206023)the Biological Breeding-National Science and Technology Major Project(2024ZD04077)+2 种基金the National Natural Science Foundation of China(32272120)the National Key Research and Development Program of China(2024YFF1000800)the Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops Major Project(FCBRCE-202502,FCBRCE-202504).
文摘A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.
基金supported by the National Natural Science Foundation of China(Nos.62572017,62441232,62206007)R&D Program of Beijing Municipal Education Commission(KZ202210005008).
文摘Knowledge-based VisualQuestion Answering(VQA)requires the integration of visual information with external knowledge reasoning.Existing approaches typically retrieve information from external corpora and rely on pretrained language models for reasoning.However,their performance is often hindered by the limited capabilities of retrievers and the constrained size of knowledge bases.Moreover,relying on image captions to bridge the modal gap between visual and language modalities can lead to the omission of critical visual details.To address these limitations,we propose the Reflective Chain-of-Thought(ReCoT)method,a simple yet effective framework inspired by metacognition theory.ReCoT effectively activates the reasoning capabilities ofMultimodal Large LanguageModels(MLLMs),providing essential visual and knowledge cues required to solve complex visual questions.It simulates a metacognitive reasoning process that encompasses monitoring,reflection,and correction.Specifically,in the initial generation stage,an MLLM produces a preliminary answer that serves as the model’s initial cognitive output.During the reflective reasoning stage,this answer is critically examined to generate a reflective rationale that integrates key visual evidence and relevant knowledge.In the final refinement stage,a smaller language model leverages this rationale to revise the initial prediction,resulting in amore accurate final answer.By harnessing the strengths ofMLLMs in visual and knowledge grounding,ReCoT enables smaller language models to reason effectively without dependence on image captions or external knowledge bases.Experimental results demonstrate that ReCoT achieves substantial performance improvements,outperforming state-of-the-art methods by 2.26%on OK-VQA and 5.8%on A-OKVQA.
基金funded by the National Key Research and Development Program of China(2022YFF1100300)National Natural Science Foundation of China(22108097)+2 种基金Key Research and Development Program of Jiangsu Province(BE2022850)Taihu Innovation-Leading Talent of Wuxi City(1026010241230040)Cross-Integration Innovation Funding of SFST(SFST2023-KY-10).
文摘Lacto-N-neotetraose(LNn T)is a crucial neutral core human milk oligosaccharide(HMO).In this study,we established a LNn T-producing Saccharomyces cerevisiae cell factory through comprehensive metabolic engineering.Specifically,the de novo biosynthetic pathway of LNn T was assembled by heterologously expressing the lactose permease(lac12)from Kluyveromyces lactis and the glycosyltransferase from Neisseria meningitidis in S.cerevisiae.Subsequently,carbon source regulation based on the glucose-sensitive GAL regulatory system was employed to optimize the expression time of heterologous genes,achieving a production of 15.61 mg/L of LNn T in shake-flask fermentation.In addition,the key rate-limiting steps involved in LNn T synthesis pathway were identified and the corresponding genes were overexpressed to enhance LNn T production,resulting in an 8-fold increase in LNn T titer compared to that of parental strain.To our knowledge,this is the first report on LNn T biosynthesis in S.cerevisiae,opening up the possibility of green production of LNn T using food-safe microorganisms.
基金funding support from General Research Fund[Project No.14300525]from the Research Grants Council(RGC)of Hong Kong SAR,Chinafunding support from Natural Science Foundation of China(NSFC)Young Scientists Fund(Project No.22305203)+2 种基金NSFC Projects Nos.22309123,22422303,22303011,22033002,92261112 and U21A20328support from the Hong Kong Branch of National Precious Metals Material Engineering Research Center(NPMM)at City University of Hong Kongsupport from Young Collaborative Research Grant[Project No.C1003-23Y]support from RGC of Hong Kong SAR,China.
文摘Electrocatalytic nitric oxide(NO)reduction reaction(NORR)is a promising and sustainable process that can simultaneously realize green ammonia(NH3)synthesis and hazardous NO removal.However,current NORR performances are far from practical needs due to the lack of efficient electrocatalysts.Engineering the lattice of metal-based nanomaterials via phase control has emerged as an effective strategy to modulate their intrinsic electrocatalytic properties.Herein,we realize boron(B)-insertion-induced phase regulation of rhodium(Rh)nanocrystals to obtain amorphous Rh_(4)B nanoparticles(NPs)and hexagonal close-packed(hcp)RhB NPs through a facile wet-chemical method.A high Faradaic efficiency(92.1±1.2%)and NH_(3) yield rate(629.5±11.0μmol h^(−1) cm^(−2))are achieved over hcp RhB NPs,far superior to those of most reported NORR nanocatalysts.In situ spectro-electrochemical analysis and density functional theory simulations reveal that the excellent electrocatalytic performances of hcp RhB NPs are attributed to the upshift of d-band center,enhanced NO adsorption/activation profile,and greatly reduced energy barrier of the rate-determining step.A demonstrative Zn-NO battery is assembled using hcp RhB NPs as the cathode and delivers a peak power density of 4.33 mW cm−2,realizing simultaneous NO removal,NH3 synthesis,and electricity output.
基金supported by the Shanghai Municipal Education Research Project“Exploring the Practical Application of Generative Artificial Intelligence in Cultivating Innovative Thinking and Capabilities of Interdisciplinary Application Technology Talents‘Practice Path’”(C2025299)the university-level postgraduate course project“Software Process Management”(PX-2025251502)of Shanghai Sanda Universitythe key course project at the university level of Shanghai Sanda University,“Introduction to Software Engineering”(PX-5241216).
文摘With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE to stimulate students’innovative consciousness and teamwork ability,enabling students to identify some problems in a certain industry or field and creatively propose feasible solutions,and truly achieve the cultivation of new models in software engineering course teaching with the assistance of generative AI tools?This paper presents research and practice on a new model for cultivating software engineering courses that integrates generative AI and OBE,introduces the specific process of teaching reform and practice,and finally explains the achievements of teaching reform.
基金supported by the National Natural Science Foundation of China(Grant Nos.52102165 and 62474056)the Natural Science Foundation of Nanjing University of Posts and Telecommunications(Grant Nos.NY221029 and NY222165)。
文摘All-inorganic lead-free perovskite solar cells have emerged as environmentally benign candidates;however,their device performance is still constrained by pronounced carrier recombination losses in the bulk and at interfaces.By combining energy band alignment analysis with detailed modeling of recombination mechanisms,a systematic strategy for optimizing hole transport layers is developed.The results reveal that a negative valence band offset produces a cliff-like interface,which facilitates hole extraction while also accounting for the observed variations in open-circuit voltage.Furthermore,short-circuit current losses are quantitatively attributed to different recombination pathways,modeled by incorporating radiative,Shockley–Read–Hall,Auger,and interface recombination processes.This comprehensive approach not only clarifies the correlation between energy level alignment and recombination dynamics but also highlights the competing roles of band offset and interface defects in determining device performance.The optimized device architecture,based on Ge-based lead-free perovskites,achieves a power conversion efficiency of 25.1%,with an open-circuit voltage of 1.29 V,a short-circuit current density of 22.5 mA·cm^(-2),and a fill factor of 86.3%.These findings provide theoretical guidance for designing stable,high-performance,and environmentally friendly lead-free perovskite solar cells.
基金supported by the National Natural Science Foundation of China(Nos.52122408 and 52474397)the High-level Talent Research Start-up Project Funding of Henan Academy of Sciences(No.242017127)+1 种基金the financial support from the Fundamental Research Funds for the Central Universities(University of Science and Technology Beijing(USTB),Nos.FRF-TP-2021-04C1 and 06500135)supported by USTB MatCom of Beijing Advanced Innovation Center for Materials Genome Engineering。
文摘High-performance alloys are indispensable in modern engineering because of their exceptional strength,ductility,corrosion resistance,fatigue resistance,and thermal stability,which are all significantly influenced by the alloy interface structures.Despite substantial efforts,a comprehensive overview of interface engineering of high-performance alloys has not been presented so far.In this study,the interfaces in high-performance alloys,particularly grain and phase boundaries,were systematically examined,with emphasis on their crystallographic characteristics and chemical element segregations.The effects of the interfaces on the electrical conductivity,mechanical strength,toughness,hydrogen embrittlement resistance,and thermal stability of the alloys were elucidated.Moreover,correlations among various types of interfaces and advanced experimental and computational techniques were examined using big data analytics,enabling robust design strategies.Challenges currently faced in the field of interface engineering and emerging opportunities in the field are also discussed.The study results would guide the development of next-generation high-performance alloys.
基金supported by the National Natural Science Foundation of China(52272183)the Fundamental Research Funds for the Central Universities(buctrc202316)the support of the China Experience Fund and the Stephen Slavens Faculty Scholar Endowment Fund from Oregon State University。
文摘Aqueous zinc(Zn)metal batteries(AZMBs)have distinct advantages in terms of safety and cost-effectiveness.However,the industrial application of AZMBs is currently not ready due to challenges of Zn dendrite growth and the side reactions such as hydrogen evolution reaction(HER)on the Zn anodes.In this review,we discuss how inorganic interfaces impact the Zn^(2+)plating/stripping reaction and overall cell performance.The discussion is categorized based on the types of inorganic materials,including metal oxides,other metal compounds,and inorganic salts.The proposed protection mechanisms for Zn metal anodes are highlighted,with a focus on the dendrite and HER inhibition mechanisms facilitated by various inorganic materials.We also provide our perspective on the rational design of advanced interfaces to enable highly reversible Zn^(2+)plating/stripping reactions toward highly stable AZMBs,paving the way for their practical implementation in energy storage.
基金supported in part by the Northeastern University’s 2024 Undergraduate Education and Teaching Reform Research Project:Innovation and Practice of Professional Course Teaching Paradigms in the Context of Digital Education.
文摘The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.
基金supported by the National Key Research and Development Program of China(2024YFF1000600)the National Natural Science Foundation of China(32241040).
文摘Nutritional imbalance has led to many chronic diseases and severely affected people’s quality of life.Developing nutrient-dense crops has emerged as a strategy for improving the current state of human nutritional intake globally.We summarized recent advances in rice biotechnology breeding focusing on increasing micronutrients and active natural products,highlighting the cutting-edge metabolic engineering technologies and strategies employed.We discussed common challenges and potential solutions in metabolic engineering breeding.On this basis,the future development direction of rice nutrient metabolism industrialization was prospected.
基金supported in part by the Graduate Education Reform Research Project of Hubei University of Technology under Grant 2024YB003the Hubei University of Arts and Science,Teaching Research Project,under Grant JY2025018.
文摘The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to reshape talent cultivation but also presents significant challenges,including skill hollowing,ethical risks,and a growing disconnect between education and industry needs.Currently,graduate-level software engineering education struggles with outdated curricula and insufficient alignment with practical demands.In this paper,we propose a dual-core collaborative framework driven by“GenAI technology”and“industry demand”.Under this framework,we design a four-dimensional capability development path to enhance graduate students’innovation in software engineering practice.This path focuses on①scientific research innovation,②engineering problem-solving,③cross-domain collaborative evolution,and④ethical risk governance.The proposed approach promotes a shift from traditional knowledge transfer to human-machine collaborative innovation,aligning talent cultivation with the demands of the NQPF.
基金supported by the National Natural Science Foundation of China (Nos.22208218,22078196,and 22278268)the Natural Science Foundation of Shanghai (No.22ZR1460400)Collaborative Innovation Center of Fragrance Flavour and Cosmetics,and Collaborative Innovation Project of Shanghai Institute of Technology (No.XTCX2023-07)。
文摘The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytotoxicity.These limitations have catalyzed the development of intelligent stimuli-responsive block copolymers-based bioimaging agents,which was engineered to dynamically respond to endogenous biochemical cues(e.g.,p H gradients,redox potential,enzyme activity,hypoxia environment) or exogenous physical triggers(e.g.,photoirradiation,thermal gradients,ultrasound(US)/magnetic stimuli).Through spatiotemporally controlled structural transformations,stimuli-responsive block copolymers enable precise contrast targeting,activatable signal amplification,and theranostic integration,thereby substantially enhancing signal-to-noise ratios of bioimaging and diagnostic specificity.Hence,this mini-review systematically examines molecular engineering principles for designing p H-,redox-,enzyme-,light-,thermo-,and US/magnetic-responsive polymers,with emphasis on structure-property relationships governing imaging performance modulation.Furthermore,we critically analyze emerging strategies for optical imaging,US synergies,and magnetic resonance imaging(MRI).Multimodal bioimaging has also been elaborated,which could overcome the inherent trade-offs between resolution,penetration depth,and functional specificity in single-modal approaches.By elucidating mechanistic insights and translational challenges,this mini-review aims to establish a design framework of stimuli-responsive block copolymersbased for high fidelity bioimaging agents and accelerate their clinical translation in precise diagnosis and therapy.
