Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were freque...Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.展开更多
Dear Editor,This letter presents a novel latent factorization model for high dimensional and incomplete (HDI) tensor, namely the neural Tucker factorization (Neu Tuc F), which is a generic neural network-based latent-...Dear Editor,This letter presents a novel latent factorization model for high dimensional and incomplete (HDI) tensor, namely the neural Tucker factorization (Neu Tuc F), which is a generic neural network-based latent-factorization-of-tensors model under the Tucker decomposition framework.展开更多
Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data ...Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved profiles.Hourly speciated VOC data measured in Shijiazhuang,China from May to September 2021 were used to conduct study.The mean VOC concentration in the daytime and at nighttime were 32.8 and 36.0 ppbv,respectively.Alkanes and aromatics concentrations in the daytime(12.9 and 3.08 ppbv)were lower than nighttime(15.5 and 3.63 ppbv),whereas that of alkenes showed the opposite tendency.The concentration differences between daytime and nighttime for alkynes and halogenated hydrocarbonswere uniformly small.The reactivities of the dominant species in factor profiles for gasoline emissions,natural gas and diesel vehicles,and liquefied petroleum gas were relatively low and their profiles were less affected by photochemical losses.Photochemical losses produced a substantial impact on the profiles of solvent use,petrochemical industry emissions,combustion sources,and biogenic emissions where the dominant species in these factor profiles had high reactivities.Although the profile of biogenic emissions was substantially affected by photochemical loss of isoprene,the low emissions at nighttime also had an important impact on its profile.Chemical losses of highly active VOC species substantially reduced their concentrations in apportioned factor profiles.This study results were consistent with the analytical results obtained through initial concentration estimation,suggesting that the initial concentration estimation could be the most effective currently availablemethod for the source analyses of active VOCs although with uncertainty.展开更多
Data factors are becoming the core driving force in the intelligent transformation of libraries.Based on a systematic review of the progress in data governance practices in libraries both domestically and internationa...Data factors are becoming the core driving force in the intelligent transformation of libraries.Based on a systematic review of the progress in data governance practices in libraries both domestically and internationally,this study delves into the mechanism by which data governance promotes data factorization and proposes implementation paths for data governance oriented toward data factorization.The aim is to facilitate the intelligent transformation and high-quality development of libraries.展开更多
CircRNAs,widely found throughout the human bodies,play a crucial role in regulating various biological processes and are closely linked to complex human diseases.Investigating potential associations between circRNAs a...CircRNAs,widely found throughout the human bodies,play a crucial role in regulating various biological processes and are closely linked to complex human diseases.Investigating potential associations between circRNAs and diseases can enhance our understanding of diseases and provide new strategies and tools for early diagnosis,treatment,and disease prevention.However,existing models have limitations in accurately capturing similarities,handling the sparse and noise attributes of association networks,and fully leveraging bioinformatical aspects from multiple viewpoints.To address these issues,this study introduces a new non-negative matrix factorization-based framework called NMFMSN.First,we incorporate circRNA sequence data and disease semantic information to compute circRNA and disease similarity,respectively.Given the sparse known associations between circRNAs and diseases,we reconstruct the network to complete more associations by imputing missing links based on neighboring circRNA and disease interactions.Finally,we integrate these two similarity networks into a non-negative matrix factorization framework to identify potential circRNA-disease associations.Upon conducting 5-fold cross-validation and leave-one-out cross-validation,the AUC values for NMFMSN reach 0.9712 and 0.9768,respectively,outperforming the currently most advanced models.Case studies on lung cancer and hepatocellular carcinoma show that NMFMSN is a good way to predict new associations between circRNAs and diseases.展开更多
In this paper,a nonlinear control approach for an unstable networked plant in the presence of actuator and sensor limitations using robust right coprime factorization is proposed.The actuator is limited by upper and l...In this paper,a nonlinear control approach for an unstable networked plant in the presence of actuator and sensor limitations using robust right coprime factorization is proposed.The actuator is limited by upper and lower constraints and the sensor in the feedback loop is subjected to network-induced unknown time-varying delay and noise.With this nonlinear control method,we first employ right coprime factorization based on isomorphism and operator theory to factorize the plant,so that bounded input bounded output(BIBO)stability can be guaranteed.Next,continuous-time generalized predictive control(CGPC)is utilized for the unstable operator of the right coprime factorized plant to guarantee inner stability and enables the closed-loop dynamics of the system with predictive characteristics.Meanwhile,a second-Do F(degrees of freedom)switched controller that satisfies a perturbed Bezout identity and a robustness condition is designed.By using the CGPC controller that possesses predictive behavior and the second-Do F switched stabilizer,the overall stability of the plant subjected to actuator limitations is guaranteed.To address sensor limitations that exist in networked plants in the form of delay and noise which often cause system performance degradation,we implement an identity operator definition in the feedback loop to compensate for these adverse effects.Further,a pre-operator is designed to ensure that the plant output tracks the reference input.Finally,the effectiveness of the proposed design scheme is demonstrated by simulations.展开更多
Dear Editor,This letter presents a latent-factorization-of-tensors(LFT)-incorporated battery cycle life prediction framework.Data-driven prognosis and health management(PHM)for battery pack(BP)can boost the safety and...Dear Editor,This letter presents a latent-factorization-of-tensors(LFT)-incorporated battery cycle life prediction framework.Data-driven prognosis and health management(PHM)for battery pack(BP)can boost the safety and sustainability of a battery management system(BMS),which relies heavily on the quality of the measured BP data like the voltage(V),current(I),and temperature(T).展开更多
黄螟Tetramoera schistaceana(Snellen)是甘蔗上的重要钻蛀性害虫。近年来,黄螟种群数量呈增长趋势,已跃升为广西蔗区的优势害虫种群。为明确影响黄螟自然种群发生发展的各项作用因子及其作用大小,2023年和2024年采用田间调查、室内饲...黄螟Tetramoera schistaceana(Snellen)是甘蔗上的重要钻蛀性害虫。近年来,黄螟种群数量呈增长趋势,已跃升为广西蔗区的优势害虫种群。为明确影响黄螟自然种群发生发展的各项作用因子及其作用大小,2023年和2024年采用田间调查、室内饲养观察以及桶栽甘蔗接虫试验相结合的方法,研究了甘蔗苗期黄螟各虫期种群数量变动规律与关键致死因子。构建黄螟自然种群生命表,运用种群数量排除作用控制指数(exclusion index of population control,EIPC)分析不同作用因子对黄螟种群数量的控制作用。结果表明,2023年和2024年黄螟自然种群趋势指数分别达到19.6425和19.3955,幼虫低龄期(1~3龄)的存活率均最低,是种群数量控制的关键期。在黄螟整个生长发育过程中,“捕食及病原菌”因素的种群控制效应最大,赤眼蜂作为卵期的优势天敌,对黄螟自然种群数量调控起关键作用。人工释放赤眼蜂后,2023年和2024年其对黄螟的排除作用控制指数比对照区分别提高1.0540和0.9632,控害效果显著。天敌赤眼蜂对黄螟种群数量有较为明显的控制作用。该结果为黄螟预测预报和综合防治提供坚实的理论基础。展开更多
目的探讨动脉粥样硬化(AS)患者口腔菌群多样性与炎症因子水平的特征及关联。方法纳入AS患者50例与健康对照50例,采集唾液和血样进行16S rRNA测序、IL-6、IL-1β、TNF-α、CRP检测;比较两组菌群结构与炎症指标差异,并进行Spearman相关和...目的探讨动脉粥样硬化(AS)患者口腔菌群多样性与炎症因子水平的特征及关联。方法纳入AS患者50例与健康对照50例,采集唾液和血样进行16S rRNA测序、IL-6、IL-1β、TNF-α、CRP检测;比较两组菌群结构与炎症指标差异,并进行Spearman相关和多因素回归分析。结果AS组IL-6、IL-1β、TNF-α、CRP水平均显著高于对照组(IL-6:8.24±2.15 vs 6.15±1.76,P<0.01;CRP:7.42±2.41 vs 3.98±1.57,P<0.01);口腔菌群Shannon指数低于对照组(4.38±0.55 vs 4.61±0.52,P=0.040);Fusobacterium与CRP、IL-6正相关(r=0.41、0.36,均P<0.05)。多因素回归提示Fusobacterium丰度及IL-6、CRP水平均为AS潜在危险因素。结论AS患者口腔菌群多样性下降伴随炎症显著增高,二者或通过免疫和代谢途径相互作用,为AS的风险评估与干预策略提供新的思路。展开更多
基金supported by the National Institute of Environmental Research(NIER)funded by the Ministry of Environment(No.NIER-2019-04-02-039)supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry&Technology Institute(KEITI)funded by the Ministry of Environment(MOE).
文摘Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.
基金supported by the National Natural Science Foundation of China(62272078)Chongqing Natural Science Foundation(CSTB2023NSCQ-LZX0069)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202300210)
文摘Dear Editor,This letter presents a novel latent factorization model for high dimensional and incomplete (HDI) tensor, namely the neural Tucker factorization (Neu Tuc F), which is a generic neural network-based latent-factorization-of-tensors model under the Tucker decomposition framework.
基金supported by the National Key R&D Program of China(No.2023YFC3705801)the National Natural Science Foundation of China(No.42177085).
文摘Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved profiles.Hourly speciated VOC data measured in Shijiazhuang,China from May to September 2021 were used to conduct study.The mean VOC concentration in the daytime and at nighttime were 32.8 and 36.0 ppbv,respectively.Alkanes and aromatics concentrations in the daytime(12.9 and 3.08 ppbv)were lower than nighttime(15.5 and 3.63 ppbv),whereas that of alkenes showed the opposite tendency.The concentration differences between daytime and nighttime for alkynes and halogenated hydrocarbonswere uniformly small.The reactivities of the dominant species in factor profiles for gasoline emissions,natural gas and diesel vehicles,and liquefied petroleum gas were relatively low and their profiles were less affected by photochemical losses.Photochemical losses produced a substantial impact on the profiles of solvent use,petrochemical industry emissions,combustion sources,and biogenic emissions where the dominant species in these factor profiles had high reactivities.Although the profile of biogenic emissions was substantially affected by photochemical loss of isoprene,the low emissions at nighttime also had an important impact on its profile.Chemical losses of highly active VOC species substantially reduced their concentrations in apportioned factor profiles.This study results were consistent with the analytical results obtained through initial concentration estimation,suggesting that the initial concentration estimation could be the most effective currently availablemethod for the source analyses of active VOCs although with uncertainty.
文摘Data factors are becoming the core driving force in the intelligent transformation of libraries.Based on a systematic review of the progress in data governance practices in libraries both domestically and internationally,this study delves into the mechanism by which data governance promotes data factorization and proposes implementation paths for data governance oriented toward data factorization.The aim is to facilitate the intelligent transformation and high-quality development of libraries.
基金the Gansu Province Industrial Support Plan(No.2023CYZC-25)Natural Science Foundation of Gansu Province(No.23JRRA770)the National Natural Science Foundation of China(No.62162040)。
文摘CircRNAs,widely found throughout the human bodies,play a crucial role in regulating various biological processes and are closely linked to complex human diseases.Investigating potential associations between circRNAs and diseases can enhance our understanding of diseases and provide new strategies and tools for early diagnosis,treatment,and disease prevention.However,existing models have limitations in accurately capturing similarities,handling the sparse and noise attributes of association networks,and fully leveraging bioinformatical aspects from multiple viewpoints.To address these issues,this study introduces a new non-negative matrix factorization-based framework called NMFMSN.First,we incorporate circRNA sequence data and disease semantic information to compute circRNA and disease similarity,respectively.Given the sparse known associations between circRNAs and diseases,we reconstruct the network to complete more associations by imputing missing links based on neighboring circRNA and disease interactions.Finally,we integrate these two similarity networks into a non-negative matrix factorization framework to identify potential circRNA-disease associations.Upon conducting 5-fold cross-validation and leave-one-out cross-validation,the AUC values for NMFMSN reach 0.9712 and 0.9768,respectively,outperforming the currently most advanced models.Case studies on lung cancer and hepatocellular carcinoma show that NMFMSN is a good way to predict new associations between circRNAs and diseases.
文摘In this paper,a nonlinear control approach for an unstable networked plant in the presence of actuator and sensor limitations using robust right coprime factorization is proposed.The actuator is limited by upper and lower constraints and the sensor in the feedback loop is subjected to network-induced unknown time-varying delay and noise.With this nonlinear control method,we first employ right coprime factorization based on isomorphism and operator theory to factorize the plant,so that bounded input bounded output(BIBO)stability can be guaranteed.Next,continuous-time generalized predictive control(CGPC)is utilized for the unstable operator of the right coprime factorized plant to guarantee inner stability and enables the closed-loop dynamics of the system with predictive characteristics.Meanwhile,a second-Do F(degrees of freedom)switched controller that satisfies a perturbed Bezout identity and a robustness condition is designed.By using the CGPC controller that possesses predictive behavior and the second-Do F switched stabilizer,the overall stability of the plant subjected to actuator limitations is guaranteed.To address sensor limitations that exist in networked plants in the form of delay and noise which often cause system performance degradation,we implement an identity operator definition in the feedback loop to compensate for these adverse effects.Further,a pre-operator is designed to ensure that the plant output tracks the reference input.Finally,the effectiveness of the proposed design scheme is demonstrated by simulations.
文摘Dear Editor,This letter presents a latent-factorization-of-tensors(LFT)-incorporated battery cycle life prediction framework.Data-driven prognosis and health management(PHM)for battery pack(BP)can boost the safety and sustainability of a battery management system(BMS),which relies heavily on the quality of the measured BP data like the voltage(V),current(I),and temperature(T).
文摘目的回顾单中心行外科治疗的感染性心内膜炎(infective endocarditis,IE)患者的临床特征、短期预后及危险因素,总结治疗经验。方法连续性纳入2012年5月—2024年6月因IE就诊于北京协和医院心外科并行手术治疗的患者。分别对患者基线资料、合并症情况、IE易感因素、手术指征、病原体分布、手术方式、短期预后及其危险因素进行统计学分析。结果共709例符合纳入和排除标准的IE患者入选本研究,其中85.3%累及左心瓣膜,中位年龄48(35,58)岁,68.0%为男性,8.7%为人工瓣膜感染心内膜炎,累及左心的IE患者合并症比例更高。43.2%的患者感染病原体为链球菌,右心IE感染金黄色葡萄球菌的比例更高,66.4%的患者存在心内结构异常的基础病因,32.7%的患者术前发生心力衰竭,90.1%的患者存在瓣膜功能障碍,11.3%的患者接受了急诊手术,24.8%的患者术前出现神经系统并发症。95.3%的主动脉瓣受累患者进行了瓣膜置换,二尖瓣受累患者瓣膜修复率达55.4%。院内死亡率为3.5%,院内复合不良事件发生率为13.5%。术前纽约心脏病协会(New York Heart Association,NYHA)心功能Ⅲ~Ⅳ级(OR=5.24,95%CI:2.01~13.71)、感染性三系减低(OR=3.32,95%CI:1.29~8.51)、区域性脑梗死(OR=4.09,95%CI:1.34~12.49)、术前发热(OR=2.34,95%CI:1.00~5.47)是院内死亡的独立危险因素。年龄每增加10岁(OR=1.20,95%CI:1.02~1.40)、金黄色葡萄球菌感染(OR=2.15,95%CI:1.13~4.11)、术前生命体征不平稳(OR=2.29,95%CI:1.26~4.17)、NYHA心功能Ⅲ~Ⅳ级(OR=3.07,95%CI:1.84~5.10)及既往心脏手术史(OR=2.10,95%CI:1.12~3.96)是复合终点事件的独立危险因素。结论左心IE与右心IE患者在病原体感染分布上存在明显差异,心力衰竭是手术治疗患者围术期死亡及不良预后的独立危险因素,通过严格把控手术时机、优化围术期管理,外科治疗或可有效降低IE患者的死亡率,改善患者预后。
文摘黄螟Tetramoera schistaceana(Snellen)是甘蔗上的重要钻蛀性害虫。近年来,黄螟种群数量呈增长趋势,已跃升为广西蔗区的优势害虫种群。为明确影响黄螟自然种群发生发展的各项作用因子及其作用大小,2023年和2024年采用田间调查、室内饲养观察以及桶栽甘蔗接虫试验相结合的方法,研究了甘蔗苗期黄螟各虫期种群数量变动规律与关键致死因子。构建黄螟自然种群生命表,运用种群数量排除作用控制指数(exclusion index of population control,EIPC)分析不同作用因子对黄螟种群数量的控制作用。结果表明,2023年和2024年黄螟自然种群趋势指数分别达到19.6425和19.3955,幼虫低龄期(1~3龄)的存活率均最低,是种群数量控制的关键期。在黄螟整个生长发育过程中,“捕食及病原菌”因素的种群控制效应最大,赤眼蜂作为卵期的优势天敌,对黄螟自然种群数量调控起关键作用。人工释放赤眼蜂后,2023年和2024年其对黄螟的排除作用控制指数比对照区分别提高1.0540和0.9632,控害效果显著。天敌赤眼蜂对黄螟种群数量有较为明显的控制作用。该结果为黄螟预测预报和综合防治提供坚实的理论基础。
文摘目的探讨动脉粥样硬化(AS)患者口腔菌群多样性与炎症因子水平的特征及关联。方法纳入AS患者50例与健康对照50例,采集唾液和血样进行16S rRNA测序、IL-6、IL-1β、TNF-α、CRP检测;比较两组菌群结构与炎症指标差异,并进行Spearman相关和多因素回归分析。结果AS组IL-6、IL-1β、TNF-α、CRP水平均显著高于对照组(IL-6:8.24±2.15 vs 6.15±1.76,P<0.01;CRP:7.42±2.41 vs 3.98±1.57,P<0.01);口腔菌群Shannon指数低于对照组(4.38±0.55 vs 4.61±0.52,P=0.040);Fusobacterium与CRP、IL-6正相关(r=0.41、0.36,均P<0.05)。多因素回归提示Fusobacterium丰度及IL-6、CRP水平均为AS潜在危险因素。结论AS患者口腔菌群多样性下降伴随炎症显著增高,二者或通过免疫和代谢途径相互作用,为AS的风险评估与干预策略提供新的思路。
