The Ru-based catalysts with different preparation methods or supports were achieved and applied in efficientlycatalytic elimination of 1,2-dichloroethane(1,2-DCE).It wasfirstly found that the redox ability and chlorine...The Ru-based catalysts with different preparation methods or supports were achieved and applied in efficientlycatalytic elimination of 1,2-dichloroethane(1,2-DCE).It wasfirstly found that the redox ability and chlorine re-sistance of the catalyst could be improved by regulating the interaction between Ru and supports.Compared withother supports and conventionally impregnated methods,the Ru@ZSM-5 catalyst synthesized by the in-situ en-capsulation strategy exhibited an excellent low-temperature catalytic performance(T50=262°C,T90=327℃),superior stability in long-term test as well as ideal target products.The acidity,specific surface area,and in-teraction with precious metals of the supports have significant influences on the catalytic activity,and the Ruclusters inside the pore structures are more closely bound to the framework Al species,which promotes theoxidation behavior.The encapsulation strategy also significantly improves the Ru dispersion thereby facilitatesoxygen activation as well as Cl-containing volatile organic compounds(CVOCs)deep oxidation,and preserveslarge amounts of Brønsted acid sites to optimize the hydrolysis mechanism for purification of CVOCs.Subse-quently,the synergistic effect between metal redox and acidity is greatly optimized,thus extremely promotingthe catalytic efficiency of 1,2-DCE oxidation.展开更多
Large language models(LLMs)have significantly advanced artificial intelligence(AI)by excelling in tasks such as understanding,generation,and reasoning across multiple modalities.Despite these achievements,LLMs have in...Large language models(LLMs)have significantly advanced artificial intelligence(AI)by excelling in tasks such as understanding,generation,and reasoning across multiple modalities.Despite these achievements,LLMs have inherent limitations including outdated information,hallucinations,inefficiency,lack of interpretability,and challenges in domain-specific accuracy.To address these issues,this survey explores three promising directions in the post-LLM era:knowledge empowerment,model collaboration,and model co-evolution.First,we examine methods of integrating external knowledge into LLMs to enhance factual accuracy,reasoning capabilities,and interpretability,including incorporating knowledge into training objectives,instruction tuning,retrieval-augmented inference,and knowledge prompting.Second,we discuss model collaboration strategies that leverage the complementary strengths of LLMs and smaller models to improve efficiency and domain-specific performance through techniques such as model merging,functional model collaboration,and knowledge injection.Third,we delve into model co-evolution,in which multiple models collaboratively evolve by sharing knowledge,parameters,and learning strategies to adapt to dynamic environments and tasks,thereby enhancing their adaptability and continual learning.We illustrate how the integration of these techniques advances AI capabilities in science,engineering,and society—particularly in hypothesis development,problem formulation,problem-solving,and interpretability across various domains.We conclude by outlining future pathways for further advancement and applications.展开更多
构建多维度表观毛孔分级体系与客观分级图谱。选择120名受毛孔问题困扰受试者,采用VISIA-CR测试仪和Sebumeter SM 815测量仪收集数据,并利用自建的2D图像处理算法进行图像分析,通过因子分析方法建立表观毛孔指数评价算法模型,同时建立...构建多维度表观毛孔分级体系与客观分级图谱。选择120名受毛孔问题困扰受试者,采用VISIA-CR测试仪和Sebumeter SM 815测量仪收集数据,并利用自建的2D图像处理算法进行图像分析,通过因子分析方法建立表观毛孔指数评价算法模型,同时建立分级图谱,并对该评估体系进行验证。使用油脂含量、毛孔周围皮肤颜色(L^(*)值、a^(*)值、b^(*)值)、毛孔尺寸(毛孔个数、毛孔面积、毛孔面积占比和毛孔直径)等指标建模,得到公式:表观毛孔指数=0.546^(*)毛孔尺寸因子+0.296^(*)毛孔颜色因子+0.157^(*)油脂因子。构建了一个将毛孔分为轻、中、重3个等级的分级图谱,随着等级升高模型得分升高。经验证,Kappa系数为0.72(p<0.01),说明两种方法具有高度一致性,表明模型和分级图谱的准确性和可靠性较高。本研究建立了客观量化的数学模型和直观的图谱用于判定表观毛孔等级,为毛孔问题的精准评估及后续护理产品的开发提供了科学依据。展开更多
Porcine reproductive and respiratory syndrome(PRRS),a highly infectious immunosuppressive disease caused by porcine reproductive and respiratory syndrome virus(PRRSV),has led to significant economic losses in the glob...Porcine reproductive and respiratory syndrome(PRRS),a highly infectious immunosuppressive disease caused by porcine reproductive and respiratory syndrome virus(PRRSV),has led to significant economic losses in the global swine industry.The complexity of preventing and controlling PRRS,compounded by the limited efficacy of current vaccines,underscores the urgent need to identify antiviral targets and develop effective therapeutics against PRRSV.From the perspective of virus-host interactions,the discovery of target molecules associated with PRRSV resistance offers a promising strategy for future disease management.In this study,we conduct a comprehensive proteomic analysis using data-independent acquisition(DIA)mode to investigate the host response throughout the acute phase of PRRSV infection.This approach provides critical insights into the regulation of host antiviral and immune pathways during acute infection,advancing our theoretical understanding of PRRSV-host interactions and host gene dynamics during this critical phase.Notably,we identified SCARB2,a major lysosomal membrane protein associated with cholesterol metabolism,as a potential regulator of PRRSV replication.These findings offer novel perspectives for the prevention and control of PRRSV,contributing to the development of targeted antiviral strategies.展开更多
The estimation of quantum phase differences plays an important role in quantum simulation and quantum computation,yet existing quantum phase estimation algorithms face critical limitations in noisy intermediate-scale ...The estimation of quantum phase differences plays an important role in quantum simulation and quantum computation,yet existing quantum phase estimation algorithms face critical limitations in noisy intermediate-scale quantum(NISQ)devices due to their excessive depth and circuit complexity.We demonstrate a high-precision phase difference estimation protocol based on the Bayesian phase difference estimation algorithm and single-photon projective measurement.The iterative framework of the algorithm,combined with the independence from controlled unitary operations,inherently mitigates circuit depth and complexity limitations.Through an experimental realization on the photonic system,we demonstrate high-precision estimation of diverse phase differences,showing root-mean-square errors(RMSE)below the standard quantum limit𝒪(1/√N)and reaching the Heisenberg scaling𝒪(1/N)after a certain number of iterations.Our scheme provides a critical advantage in quantum resource-constrained scenarios,and advances practical implementations of quantum information tasks under realistic hardware constraints.展开更多
BACKGROUND Thermal ablation(TA)has been proved to be effective and safe as minimally invasive treatment method for thyroid nodules.However,patients'experience during the procedures and quality of life varies among...BACKGROUND Thermal ablation(TA)has been proved to be effective and safe as minimally invasive treatment method for thyroid nodules.However,patients'experience during the procedures and quality of life varies among operators.AIM To explore strategy to improve quality of life and subjective experiences during TA for papillary thyroid carcinoma(PTC)based on thermal field management(TFM).METHODS This retrospective propensity-matched cohort study was conducted in a single center.A total of 490 patients with PTC treated with TA from September 2023 to August 2024 were studied and divided into two groups(TFM group and non-TFM group)according to treatment strategies.Propensity score matching(PSM)was used to control for confounding factors.Complications,side effect and com-plaints of patients were compared between the two groups.RESULTS A total of 113 patients(41.7±10.6;31 men,82 women)were assigned to the TFM group,and 377 patients(mean age,41.1±10.7 year;116 men,261 women)were assigned to the non-TFM group.After PSM,a total of 108 patients were included in the TFM group,and 216 patients were included in the non-TFM group.The median follow-up was 10 months(range from 4-15 months).The incidence of voice change in the TFM group was significantly lower than that in the non-TFM group(0.9%vs 6.5%;P=0.049).Although there was no statistically significant difference in rate of pain between the two groups,the proportion of complaining of pain in the TFM group was numerically lower than that in the non-TFM group(3.7%vs 9.7%,P=0.090).CONCLUSION TFM,as a novel procedural optimization technique,can effectively improve quality of life and subjective expe-riences of patients during TA for PTC.展开更多
基金supported by the National Key Research and Development Program of China(No.2023YFC3905400)the National Natural Science Foundation of China(No.22176010).
文摘The Ru-based catalysts with different preparation methods or supports were achieved and applied in efficientlycatalytic elimination of 1,2-dichloroethane(1,2-DCE).It wasfirstly found that the redox ability and chlorine re-sistance of the catalyst could be improved by regulating the interaction between Ru and supports.Compared withother supports and conventionally impregnated methods,the Ru@ZSM-5 catalyst synthesized by the in-situ en-capsulation strategy exhibited an excellent low-temperature catalytic performance(T50=262°C,T90=327℃),superior stability in long-term test as well as ideal target products.The acidity,specific surface area,and in-teraction with precious metals of the supports have significant influences on the catalytic activity,and the Ruclusters inside the pore structures are more closely bound to the framework Al species,which promotes theoxidation behavior.The encapsulation strategy also significantly improves the Ru dispersion thereby facilitatesoxygen activation as well as Cl-containing volatile organic compounds(CVOCs)deep oxidation,and preserveslarge amounts of Brønsted acid sites to optimize the hydrolysis mechanism for purification of CVOCs.Subse-quently,the synergistic effect between metal redox and acidity is greatly optimized,thus extremely promotingthe catalytic efficiency of 1,2-DCE oxidation.
基金supported in part by National Natural Science Foundation of China(62441605)。
文摘Large language models(LLMs)have significantly advanced artificial intelligence(AI)by excelling in tasks such as understanding,generation,and reasoning across multiple modalities.Despite these achievements,LLMs have inherent limitations including outdated information,hallucinations,inefficiency,lack of interpretability,and challenges in domain-specific accuracy.To address these issues,this survey explores three promising directions in the post-LLM era:knowledge empowerment,model collaboration,and model co-evolution.First,we examine methods of integrating external knowledge into LLMs to enhance factual accuracy,reasoning capabilities,and interpretability,including incorporating knowledge into training objectives,instruction tuning,retrieval-augmented inference,and knowledge prompting.Second,we discuss model collaboration strategies that leverage the complementary strengths of LLMs and smaller models to improve efficiency and domain-specific performance through techniques such as model merging,functional model collaboration,and knowledge injection.Third,we delve into model co-evolution,in which multiple models collaboratively evolve by sharing knowledge,parameters,and learning strategies to adapt to dynamic environments and tasks,thereby enhancing their adaptability and continual learning.We illustrate how the integration of these techniques advances AI capabilities in science,engineering,and society—particularly in hypothesis development,problem formulation,problem-solving,and interpretability across various domains.We conclude by outlining future pathways for further advancement and applications.
文摘构建多维度表观毛孔分级体系与客观分级图谱。选择120名受毛孔问题困扰受试者,采用VISIA-CR测试仪和Sebumeter SM 815测量仪收集数据,并利用自建的2D图像处理算法进行图像分析,通过因子分析方法建立表观毛孔指数评价算法模型,同时建立分级图谱,并对该评估体系进行验证。使用油脂含量、毛孔周围皮肤颜色(L^(*)值、a^(*)值、b^(*)值)、毛孔尺寸(毛孔个数、毛孔面积、毛孔面积占比和毛孔直径)等指标建模,得到公式:表观毛孔指数=0.546^(*)毛孔尺寸因子+0.296^(*)毛孔颜色因子+0.157^(*)油脂因子。构建了一个将毛孔分为轻、中、重3个等级的分级图谱,随着等级升高模型得分升高。经验证,Kappa系数为0.72(p<0.01),说明两种方法具有高度一致性,表明模型和分级图谱的准确性和可靠性较高。本研究建立了客观量化的数学模型和直观的图谱用于判定表观毛孔等级,为毛孔问题的精准评估及后续护理产品的开发提供了科学依据。
基金supported by the National Natural Science Foundation of China(grant no.:3217190296,82102755 and 32302887)Guangdong Basic and Applied Basic Research Foundation(grant no.:2023A1515012623 and 2019B1515210030)China Postdoctoral Science Foundation(grant no.:2021M703739)。
文摘Porcine reproductive and respiratory syndrome(PRRS),a highly infectious immunosuppressive disease caused by porcine reproductive and respiratory syndrome virus(PRRSV),has led to significant economic losses in the global swine industry.The complexity of preventing and controlling PRRS,compounded by the limited efficacy of current vaccines,underscores the urgent need to identify antiviral targets and develop effective therapeutics against PRRSV.From the perspective of virus-host interactions,the discovery of target molecules associated with PRRSV resistance offers a promising strategy for future disease management.In this study,we conduct a comprehensive proteomic analysis using data-independent acquisition(DIA)mode to investigate the host response throughout the acute phase of PRRSV infection.This approach provides critical insights into the regulation of host antiviral and immune pathways during acute infection,advancing our theoretical understanding of PRRSV-host interactions and host gene dynamics during this critical phase.Notably,we identified SCARB2,a major lysosomal membrane protein associated with cholesterol metabolism,as a potential regulator of PRRSV replication.These findings offer novel perspectives for the prevention and control of PRRSV,contributing to the development of targeted antiviral strategies.
基金Project supported by the Natural Science Foundation of Jiangsu Province(Grant Nos.BK20233001 and BK20243060)the National Natural Science Foundation of China(Grant No.62288101)。
文摘The estimation of quantum phase differences plays an important role in quantum simulation and quantum computation,yet existing quantum phase estimation algorithms face critical limitations in noisy intermediate-scale quantum(NISQ)devices due to their excessive depth and circuit complexity.We demonstrate a high-precision phase difference estimation protocol based on the Bayesian phase difference estimation algorithm and single-photon projective measurement.The iterative framework of the algorithm,combined with the independence from controlled unitary operations,inherently mitigates circuit depth and complexity limitations.Through an experimental realization on the photonic system,we demonstrate high-precision estimation of diverse phase differences,showing root-mean-square errors(RMSE)below the standard quantum limit𝒪(1/√N)and reaching the Heisenberg scaling𝒪(1/N)after a certain number of iterations.Our scheme provides a critical advantage in quantum resource-constrained scenarios,and advances practical implementations of quantum information tasks under realistic hardware constraints.
基金Supported by National High Level Hospital Clinical Research Funding,No.2022-NHLHCRF-PY-07National Natural Science Foundation of China,No.62176268.
文摘BACKGROUND Thermal ablation(TA)has been proved to be effective and safe as minimally invasive treatment method for thyroid nodules.However,patients'experience during the procedures and quality of life varies among operators.AIM To explore strategy to improve quality of life and subjective experiences during TA for papillary thyroid carcinoma(PTC)based on thermal field management(TFM).METHODS This retrospective propensity-matched cohort study was conducted in a single center.A total of 490 patients with PTC treated with TA from September 2023 to August 2024 were studied and divided into two groups(TFM group and non-TFM group)according to treatment strategies.Propensity score matching(PSM)was used to control for confounding factors.Complications,side effect and com-plaints of patients were compared between the two groups.RESULTS A total of 113 patients(41.7±10.6;31 men,82 women)were assigned to the TFM group,and 377 patients(mean age,41.1±10.7 year;116 men,261 women)were assigned to the non-TFM group.After PSM,a total of 108 patients were included in the TFM group,and 216 patients were included in the non-TFM group.The median follow-up was 10 months(range from 4-15 months).The incidence of voice change in the TFM group was significantly lower than that in the non-TFM group(0.9%vs 6.5%;P=0.049).Although there was no statistically significant difference in rate of pain between the two groups,the proportion of complaining of pain in the TFM group was numerically lower than that in the non-TFM group(3.7%vs 9.7%,P=0.090).CONCLUSION TFM,as a novel procedural optimization technique,can effectively improve quality of life and subjective expe-riences of patients during TA for PTC.
