Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a fr...Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.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
Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effect...Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.展开更多
With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,exist...With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.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 increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.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
Photocatalytic transfer hydrogenation using water as the proton source has emerged as an attractive and green approach for the catalytic reduction of unsaturated bonds.Herein,we report an oxygen-defective TiO_(2)-supp...Photocatalytic transfer hydrogenation using water as the proton source has emerged as an attractive and green approach for the catalytic reduction of unsaturated bonds.Herein,we report an oxygen-defective TiO_(2)-supported palladium catalyst(Pd-TiO_(2)-Ov)for efficient photocatalytic water-donating transfer hydrogenation of anethole towards 4-n-propylanisole in a high yield of 99.9%,which is significantly higher compared to the pristine TiO_(2)-supported palladium catalyst(Pd-TiO_(2),74%).The enhanced performance is ascribed to the presence of oxygen vacancies,which facilitate light absorption and suppress the recombination of photogenerated electron-hole pairs.Furthermore,the Pd-TiO_(2)-Ov is versatile in hydrogenating various alkene substrates including those with hydroxyl,ether,fluoride,and chloride functional groups in full conversion,thus offering a green method for transfer hydrogenation of alkenes.This study provides new insights and advances in current hydrogenation technology with water as the proton source.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
Objective:This study was aimed at investigating metabolic dysregulation in tumor-associated macrophages(TAMs)in breast cancer and developing a metabolically enhanced chimeric antigen receptor macrophage(CAR-M)strategy...Objective:This study was aimed at investigating metabolic dysregulation in tumor-associated macrophages(TAMs)in breast cancer and developing a metabolically enhanced chimeric antigen receptor macrophage(CAR-M)strategy to boost antitumor potency in solid tumors.Methods:Integrated scRNA-seq and metabolomic analyses were performed to characterize metabolic alterations in macrophages within the breast cancer tumor microenvironment(TME).According to the identified metabolic vulnerabilities,SLC38A2-overexpressing anti-HER2 CAR-Ms were engineered.Glutamine uptake and phagocytic activity were assessed to evaluate functional enhancement.Results:TAMs in breast cancer exhibited substantial metabolic dysregulation,particularly impaired glutamine metabolism accompanied by decreased expression of the glutamine transporter SLC38A2.Overexpression of SLC38A2 in anti-HER2 CAR-Ms,compared with conventional anti-HER2 CAR-Ms,enhanced glutamine uptake and markedly augmented phagocytosis of HER2+breast cancer cells.Conclusions:Metabolic engineering via SLC38A2 restored glutamine fitness and enhanced the antitumor activity of HER2-targeted CAR-Ms,thus providing a promising strategy to boost CAR-M–mediated tumor suppression in solid tumors.展开更多
Understanding the intricate interplay between electrode reactivity and interfacial chemistry is crucial for advancing halide perovskite memristors toward practical applications.Here,we systematically investigate how t...Understanding the intricate interplay between electrode reactivity and interfacial chemistry is crucial for advancing halide perovskite memristors toward practical applications.Here,we systematically investigate how top electrode materials(Au,Ag,Cu,Al)influence the resistive switching behavior of quasi-2D CsPbBr_(3) devices through controlled interfacial engineering.By introducing a novel bilayer electrode architecture,we successfully decouple electrode surface oxidation effects from perovskite/electrode interfacial oxidation reactions for the first time.In situ XRD,photoluminescence spectroscopy,and interfacial XPS analysis reveal that voltage-driven bromide ion migration coupled with electrode-dependent reactions governs the switching mechanisms.Chemically inert Au electrodes show no switching due to insufficient interfacial reactivity,while highly reactive Al electrodes cause irreversible degradation through excessive chemical interactions.In contrast,moderately active Ag and Cu electrodes enable stable bipolar switching with dual negative differential resistance characteristics.The optimal performance emerges from balanced electrode reactivity that facilitates reversible interfacial redox reactions without structural degradation.These findings establish fundamental design principles linking electrode chemical activity to device functionality,providing a rational framework for engineering robust perovskite memristors with enhanced stability and performance for next-generation memory and neuromorphic computing applications.展开更多
Back-contacted perovskite solar cells(PSCs)have been demonstrated with merits of low material cost and weak ion migration,while the inferior buried surface restricts their performance and bifacial response.Herein,poly...Back-contacted perovskite solar cells(PSCs)have been demonstrated with merits of low material cost and weak ion migration,while the inferior buried surface restricts their performance and bifacial response.Herein,polyvinylidene fluoride(PVDF)with similar thermal expansion coefficient to perovskites and low tensile modulus is introduced at the substrate/crystal interface to release interface lattice strain and enhance crystallinity.Besides,PVDF can release free fluoride ions to interact with bare Pb^(2+)ions,reducing interface charge trap density and nonradiative recombination.As a result,an impressive efficiency of 13.37%is obtained,setting a new efficiency benchmark for back-contacted PSCs.Moreover,the PVDF-modified devices retain 100%of their initial efficiency after 1,200 h of maximum power point tracking at 60℃.Finally,a high bifaciality factor of 0.96 is obtained,leading to obvious increase of power output under simulated circumstance with reflected light.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
文摘Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.
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 Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R259)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.Ashit Kumar Dutta would like to thank AlMaarefa University for supporting this research under project number MHIRSP2025017.
文摘Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.
基金support of the National Key Research and Development Plan(No.2021YFB3302501)the financial support of the National Science Foundation of China(No.12161076)the financial support of the Fundamental Research Funds for the Central Universities(No.DUT25GF207).
文摘With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.
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funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
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 Key Research and Development Program of China(2023YFD2200505)National Natural Science Foundation of China(22202105),Natural Science Foundation of Jiangsu Higher Education Institutions of China(21KJA150003)the Innovation and Entrepreneurship Team Program of Jiangsu Province(JSSCTD202345).
文摘Photocatalytic transfer hydrogenation using water as the proton source has emerged as an attractive and green approach for the catalytic reduction of unsaturated bonds.Herein,we report an oxygen-defective TiO_(2)-supported palladium catalyst(Pd-TiO_(2)-Ov)for efficient photocatalytic water-donating transfer hydrogenation of anethole towards 4-n-propylanisole in a high yield of 99.9%,which is significantly higher compared to the pristine TiO_(2)-supported palladium catalyst(Pd-TiO_(2),74%).The enhanced performance is ascribed to the presence of oxygen vacancies,which facilitate light absorption and suppress the recombination of photogenerated electron-hole pairs.Furthermore,the Pd-TiO_(2)-Ov is versatile in hydrogenating various alkene substrates including those with hydroxyl,ether,fluoride,and chloride functional groups in full conversion,thus offering a green method for transfer hydrogenation of alkenes.This study provides new insights and advances in current hydrogenation technology with water as the proton source.
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 grants from the National Key R&D Program of China(Grant Nos.2021YFA1103000 and 2021YFA1302000)National Natural Science Foundation of China(Grant Nos.82572106,82125017,and 92359302)+7 种基金Guangdong Province Youth Top Talent Special Pillar Program 2024,Natural Science Foundation of Guangdong Province(Grant No.2314050001076)Guangdong Basic and Applied Basic Research Foundation(Grant Nos.2023A1515011033,2024B1515040006,and 2025A1515012431)Guangdong Major Project of Basic Research(Grant No.2023B0303000018)Guangzhou Science and Technology Plan Project(Grant No.2025B03J0063)Noncommunicable Chronic Diseases-National Science and Technology Major Project(Grant No.2025ZD0544000)Guangdong Provincial Clinical Research Center for Breast Diseases(Grant No.2023B110005)the Science and Technology Program of Guangzhou(Grant No.2024A04J6568)New Cornerstone Science Foundation through the New Cornerstone Investigator Program,and XPLORER PRIZE.
文摘Objective:This study was aimed at investigating metabolic dysregulation in tumor-associated macrophages(TAMs)in breast cancer and developing a metabolically enhanced chimeric antigen receptor macrophage(CAR-M)strategy to boost antitumor potency in solid tumors.Methods:Integrated scRNA-seq and metabolomic analyses were performed to characterize metabolic alterations in macrophages within the breast cancer tumor microenvironment(TME).According to the identified metabolic vulnerabilities,SLC38A2-overexpressing anti-HER2 CAR-Ms were engineered.Glutamine uptake and phagocytic activity were assessed to evaluate functional enhancement.Results:TAMs in breast cancer exhibited substantial metabolic dysregulation,particularly impaired glutamine metabolism accompanied by decreased expression of the glutamine transporter SLC38A2.Overexpression of SLC38A2 in anti-HER2 CAR-Ms,compared with conventional anti-HER2 CAR-Ms,enhanced glutamine uptake and markedly augmented phagocytosis of HER2+breast cancer cells.Conclusions:Metabolic engineering via SLC38A2 restored glutamine fitness and enhanced the antitumor activity of HER2-targeted CAR-Ms,thus providing a promising strategy to boost CAR-M–mediated tumor suppression in solid tumors.
基金financial support of the National Natural Science Foundation of China(Nos.62464011,62474084,52462025)Natural Science Foundation of Jiangxi Province(No.20242BAB25226)。
文摘Understanding the intricate interplay between electrode reactivity and interfacial chemistry is crucial for advancing halide perovskite memristors toward practical applications.Here,we systematically investigate how top electrode materials(Au,Ag,Cu,Al)influence the resistive switching behavior of quasi-2D CsPbBr_(3) devices through controlled interfacial engineering.By introducing a novel bilayer electrode architecture,we successfully decouple electrode surface oxidation effects from perovskite/electrode interfacial oxidation reactions for the first time.In situ XRD,photoluminescence spectroscopy,and interfacial XPS analysis reveal that voltage-driven bromide ion migration coupled with electrode-dependent reactions governs the switching mechanisms.Chemically inert Au electrodes show no switching due to insufficient interfacial reactivity,while highly reactive Al electrodes cause irreversible degradation through excessive chemical interactions.In contrast,moderately active Ag and Cu electrodes enable stable bipolar switching with dual negative differential resistance characteristics.The optimal performance emerges from balanced electrode reactivity that facilitates reversible interfacial redox reactions without structural degradation.These findings establish fundamental design principles linking electrode chemical activity to device functionality,providing a rational framework for engineering robust perovskite memristors with enhanced stability and performance for next-generation memory and neuromorphic computing applications.
基金economically supported by the National Natural Science Foundation of China(62474102)Key R&D Program of Shandong Province,China(2024CXGC010302)。
文摘Back-contacted perovskite solar cells(PSCs)have been demonstrated with merits of low material cost and weak ion migration,while the inferior buried surface restricts their performance and bifacial response.Herein,polyvinylidene fluoride(PVDF)with similar thermal expansion coefficient to perovskites and low tensile modulus is introduced at the substrate/crystal interface to release interface lattice strain and enhance crystallinity.Besides,PVDF can release free fluoride ions to interact with bare Pb^(2+)ions,reducing interface charge trap density and nonradiative recombination.As a result,an impressive efficiency of 13.37%is obtained,setting a new efficiency benchmark for back-contacted PSCs.Moreover,the PVDF-modified devices retain 100%of their initial efficiency after 1,200 h of maximum power point tracking at 60℃.Finally,a high bifaciality factor of 0.96 is obtained,leading to obvious increase of power output under simulated circumstance with reflected light.
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.
