Aiming at the demand of mileage statistics, work area statistics, fault site return and related data automatic retention in the current agricultural machinery reliability appraisal process, the optimization of agricul...
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Aiming at the demand of mileage statistics, work area statistics, fault site return and related data automatic retention in the current agricultural machinery reliability appraisal process, the optimization of agricultural machinery video monitoring system based on artificial neural network algorithm was studied. Together with the new video monitoring technology, the agricultural machinery GPS, GSM and fuel consumption recorder technology are combined to realize the functions of real-time data transmission, monitoring, analysis and statistics. Aiming at intelligent fault analysis, a real-time online detection mechanism is proposed, and a cloud collaborative detection mechanism is proposed to solve the problem of inaccurate offline model detection. Use plane map or satellite map to browse. Thus, an online monitoring and visual testing platform for agricultural machinery faults without real-time monitoring records is established. Finally, the test platform is tested and applied. Test results show that the algorithm can greatly shorten the training time and improve the accuracy of training model detection. With the increase of online training iterations, it is helpful to improve the detection accuracy of the generated model. In a word, the system service platform can provide scientific and transparent data for agricultural machinery fault identification, ensure the scientific, open and fair principles of agricultural machinery fault identification, and greatly improve the efficiency of agricultural machinery management.
目的探讨食管闭锁术后经鼻胃管进行高能量密度的早期肠内营养模式对术后恢复的影响。方法收集2016年1月至2022年12月在天津市儿童医院一期食管吻合手术治疗的Ⅲb型先天性食管闭锁36例患儿的资料,所有患儿均于术后早期经鼻胃管进行肠内营养(enteral nutrition,EN)。根据所使用配方奶能量密度分为两组:一组为早期微量EN组17例,其中男11例,女6例,胎龄为(38.8±1.3)周,出生体重为(2.6±0.3)kg,术后早期给予深度水解配方奶微量喂养;另一组早期强化EN组19例,其中男13例,女6例,胎龄为(38.5±1.8)周,出生体重为(2.8±0.4)kg,术后早期给予高能量密度深度水解配方奶喂养。两组均根据胃肠道耐受情况,逐步增加肠内营养量,最终过渡至完全经口喂养。采用IBM SPSS Statistics 26软件处理所有数据,符合正态分布的定量资料用独立样本t检验,非正态分布用非参数检验。结果两组在术前一般指标、手术方式、喂养不耐受、术后首次排便时间、术后14 d血清前白蛋白水平及术后1个月年龄别体重Z值(weight for age z score,WAZ)方面差异无统计学意义(P>0.05);早期强化EN组术后7 d血清前白蛋白水平、日均体重增长、达到全肠内营养时间、住院时长、住院总费用方面明显优于早期微量EN组,差异均有统计学意义(P<0.05)。结论新生儿食管闭锁术后早期高能量密度的肠内营养有助于改善围手术期营养状态,缩短住院时间及减少医疗花费,值得临床推广。
The 2021 Mw 7.4 Maduo (Madoi) earthquake that struck the northern Tibetan Plateau resulted in widespread coseismic deformation features, such as surface ruptures and soil liquefaction. By utilizing the unmanned aerial...
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The 2021 Mw 7.4 Maduo (Madoi) earthquake that struck the northern Tibetan Plateau resulted in widespread coseismic deformation features, such as surface ruptures and soil liquefaction. By utilizing the unmanned aerial vehicle (UAV) photogrammetry technology, we accurately recognize and map 39,286 liquefaction sites within a 1.5 km wide zone along the coseismic surface rupture. We then systematically analyze the coseismic liquefaction distribution characteristics and the possible influencing factors. The coseismic liquefaction density remains on a higher level within 250 m from the surface rupture and decreases in a power law with the increasing distance. The amplification of the seismic waves in the vicinity of the rupture zone enhances the liquefaction effects near it. More than 90% of coseismic liquefaction occurs in the peak ground acceleration (PGA) > 0.50 g, and the liquefaction density is significantly higher in the region with seismic intensity > VIII. Combined with the sedimentary distribution along-strike of the surface rupture, the mapped liquefaction sites indicate that the differences in the sedimentary environments could cause more intense liquefaction on the western side of the epicenter, where loose Quaternary deposits are widely spread. The stronger coseismic liquefaction sites correspond to the Eling Lake section, the Yellow River floodplain, and the Heihe River floodplain, where the soil is mostly saturated with loose fine-grained sand and the groundwater level is high. Our results show that the massive liquefaction caused by the strong ground shaking during the Maduo (Madoi) earthquake was distributed as the specific local sedimentary environment and the groundwater level changed.
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