In the construction of resilient cities,regional air pollution prevention plays a pivotal role.Building on the previous research experience,the relationship between air pollution concentration and urban size exhibits ...In the construction of resilient cities,regional air pollution prevention plays a pivotal role.Building on the previous research experience,the relationship between air pollution concentration and urban size exhibits a sublinear allometric growth pattern.To identify effective strategies for mitigating particulate matter air pollution,this study quantitatively explored 6 variables influencing urbanization in China’s cities and established an allometry model.Empirical analysis was conducted using data from 293 prefecturelevel cities and 1,827 county-level cities to examine the relationship between annual concentrations of fine particulate matter PM_(2.5) and PM_(10) in the atmosphere.①The findings of this study provided partial validation for the Kuznets curve and demonstrated a reverse‘U’-shaped association between urbanization and levels of PM_(2.5) and PM_(10) pollution.②By partitioning the Hu Huanyong line,this study identified the spatial distribution pattern of PM_(2.5) and PM_(10).In central and western regions,as urban size expands,inhalable particle concentrations tended to increase further;whereas in the southeast region,inhalable particle concentrations gradually decreased and stabilized after a certain threshold of urban scale expansion was reached.Among the factors influencing urban size,green coverage within built-up areas exerted the most significant impact on both PM_(2.5) and PM_(10) concentrations,followed by the extent of built-up areas and the scale of secondary industries.This study presented an effective strategy for reconciling conflicts between urban expansion and air pollution management,while concurrently promoting resilient cities characterized by high levels of modernization and superior quality.展开更多
With the digital transformation of global education and China's emphasis on education digital,generative AI technology has been widely used in the field of higher education.In this paper,the development of generat...With the digital transformation of global education and China's emphasis on education digital,generative AI technology has been widely used in the field of higher education.In this paper,the development of generative AI technology and its potential in personalized learning,interactive content creation and adaptive assessment in education were introduced firstly.Then,the application case of generative AI tools in teaching content creation,scenario-based teaching content development,visual teaching content development,complex concept deconstruction and analogy,student-led application practice and other aspects in the teaching of Building Decoration Materials was discussed.Through the teaching experiment and effect evaluation,the positive influence of generative AI technology on the improvement of students'learning effect and teaching efficiency was verified.Finally,some thoughts and inspirations on the combination of educational theory and generative AI technology,the integration of teaching design and generative AI technology,and the practice cases and effect evaluation were put forward,and the importance of teacher role transformation and personalized learning path design was emphasized to provide theoretical and practical support for the innovative development of higher education.展开更多
目的观察MRI检测早产高危孕妇宫颈变化的可行性。方法收集20例早产高危孕妇(观察组)和20例非早产孕妇(对照组)。对比分析2组宫颈基质及腺下区T2WI及DWI信号、宫颈长度、内口宽度及ADC值。结果观察组宫颈长度明显缩短,平均(25.16±15...目的观察MRI检测早产高危孕妇宫颈变化的可行性。方法收集20例早产高危孕妇(观察组)和20例非早产孕妇(对照组)。对比分析2组宫颈基质及腺下区T2WI及DWI信号、宫颈长度、内口宽度及ADC值。结果观察组宫颈长度明显缩短,平均(25.16±15.68)mm;宫颈内口宽度扩大呈喇叭口状,平均(20.46±1.82)mm;宫颈腺下区矢状位T2WI及DWI信号增高,宫颈腺下区平均ADC值为(1.87±0.52)×10-3 mm 2/s;基质平均ADC值为(1.50±0.43)×10-3 mm 2/s,与对照组[(1.37±0.06)×10-3 mm 2/s及(1.27±0.08)×10-3 mm 2/s]比较差异有统计学意义(P均<0.05)。结论MRI可显示早产高危孕妇宫颈变化,对早期预测和临床干预早产具有重要价值。展开更多
文摘In the construction of resilient cities,regional air pollution prevention plays a pivotal role.Building on the previous research experience,the relationship between air pollution concentration and urban size exhibits a sublinear allometric growth pattern.To identify effective strategies for mitigating particulate matter air pollution,this study quantitatively explored 6 variables influencing urbanization in China’s cities and established an allometry model.Empirical analysis was conducted using data from 293 prefecturelevel cities and 1,827 county-level cities to examine the relationship between annual concentrations of fine particulate matter PM_(2.5) and PM_(10) in the atmosphere.①The findings of this study provided partial validation for the Kuznets curve and demonstrated a reverse‘U’-shaped association between urbanization and levels of PM_(2.5) and PM_(10) pollution.②By partitioning the Hu Huanyong line,this study identified the spatial distribution pattern of PM_(2.5) and PM_(10).In central and western regions,as urban size expands,inhalable particle concentrations tended to increase further;whereas in the southeast region,inhalable particle concentrations gradually decreased and stabilized after a certain threshold of urban scale expansion was reached.Among the factors influencing urban size,green coverage within built-up areas exerted the most significant impact on both PM_(2.5) and PM_(10) concentrations,followed by the extent of built-up areas and the scale of secondary industries.This study presented an effective strategy for reconciling conflicts between urban expansion and air pollution management,while concurrently promoting resilient cities characterized by high levels of modernization and superior quality.
文摘With the digital transformation of global education and China's emphasis on education digital,generative AI technology has been widely used in the field of higher education.In this paper,the development of generative AI technology and its potential in personalized learning,interactive content creation and adaptive assessment in education were introduced firstly.Then,the application case of generative AI tools in teaching content creation,scenario-based teaching content development,visual teaching content development,complex concept deconstruction and analogy,student-led application practice and other aspects in the teaching of Building Decoration Materials was discussed.Through the teaching experiment and effect evaluation,the positive influence of generative AI technology on the improvement of students'learning effect and teaching efficiency was verified.Finally,some thoughts and inspirations on the combination of educational theory and generative AI technology,the integration of teaching design and generative AI technology,and the practice cases and effect evaluation were put forward,and the importance of teacher role transformation and personalized learning path design was emphasized to provide theoretical and practical support for the innovative development of higher education.
文摘目的观察MRI检测早产高危孕妇宫颈变化的可行性。方法收集20例早产高危孕妇(观察组)和20例非早产孕妇(对照组)。对比分析2组宫颈基质及腺下区T2WI及DWI信号、宫颈长度、内口宽度及ADC值。结果观察组宫颈长度明显缩短,平均(25.16±15.68)mm;宫颈内口宽度扩大呈喇叭口状,平均(20.46±1.82)mm;宫颈腺下区矢状位T2WI及DWI信号增高,宫颈腺下区平均ADC值为(1.87±0.52)×10-3 mm 2/s;基质平均ADC值为(1.50±0.43)×10-3 mm 2/s,与对照组[(1.37±0.06)×10-3 mm 2/s及(1.27±0.08)×10-3 mm 2/s]比较差异有统计学意义(P均<0.05)。结论MRI可显示早产高危孕妇宫颈变化,对早期预测和临床干预早产具有重要价值。
文摘目的探讨蜗神经发育不良(cochlear nerve deficiency,CND)儿童的临床特征。方法以43例(60耳)CND患儿(4个月~10岁,平均2.6±2.8岁)为研究对象,总结分析其是否存在听力损失高危因素、影像学检查及听性脑干反应(ABR)、畸变产物耳声发射(DPOAE)、Chirp声诱发听性稳态反应(Chirp-ASSR)检测等结果。结果43例患儿中,26例(60.5%,26/43)为单侧病变,17例(39.5%,17/43)为双侧病变;仅7例患儿有听力损失高危因素。50耳(83.3%,50/60)为蜗神经缺如,10耳(16.7%,10/60)为蜗神经细小;16耳(26.7%,16/60)伴面神经细小,8耳(13.3%,8/60)伴前庭神经异常。4耳(6.7%,4/60)仅伴前庭畸形为第一组,21耳(35%,21/60)合并耳蜗畸形或同时合并前庭畸形为第二组,35耳(58.3%,35/60)不伴内耳畸形为第三组。26耳(43.3%,26/60)ABR仅见波Ⅲ以前波形分化,随后波形消失;23耳(38.3%,23/60)ABR无波形分化;11耳(18.3%,11/60)可见分化不良的波V,其反应阈值为75~100 dB nHL。24耳(40%,24/60)DPOAE或/和CM引出,且第三组CND患儿DPOAE的信噪比(SNR)值和引出率均明显高于CND合并内耳畸形的第一、二组患儿。49耳ABR最大声输出时未引出波V的CND患儿中,41耳(83.7%,41/49)Chirp-ASSR可在不同频率不同程度引出,500、1000、2000和4000 Hz Chirp-ASSR平均反应阈分别为87.14±21.33、89.27±16.09、89.37±15.85和91.10±15.77 dB corHL。结论本组CND患儿多无明确听力损失高危因素或病因,多表现为重度或极重度感音神经性聋,高发于先天性单侧感音神经性聋婴幼儿,可表现出听神经病的特征,ABR仅见波III以前波形分化,随后波形消失,Chirp-ASSR测得残余听力明显优于ABR检测结果。
