电子雷管技术的推广应用助力爆破器材安全管理工作

电子雷管技术提高了爆破器材的本质安全。通过对电子雷管技术发展历程的介绍,对其推广应用的可行性进行了深入分析,论述了电子雷管技术的推广应用对爆破器材安全管理工作的促进作用,并提出了今后推广应用中还需加强的工作。     

A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy

Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.     

Effects of multiple freeze–thaw cycles on meat quality,nutrients, water distribution and microstructure in bovine rumen smooth muscle

This study investigated the effect of 5 freeze–thaw cycles (freezing at −18°C for 12 h and then thawing at 4°C for approximately 12 h) on the meat quality, proximate composition, water distribution and microstructure of bovine rumen smooth muscle (BSM). As the number of freeze–thaw cycles increased, BSM pH, shear force, water content and protein content decreased by 3.06%, 35.50%, 14.49% and 21.11%, respectively, whereas BSM thawing loss, cooking loss, pressing loss, total aerobic count (TAC), ash content and fat content increased by 108.12%, 47.75%, 78.33%, 90.99%, 105% and 35.20%, respectively. The freeze–thaw cycles resulted in greater protein and lipid oxidation, as evidenced by a 36.46% reduction in the sulfhydryl content and a 209.06% and 338.46% increase in the carbonyl and malondialdehyde contents, respectively. Ice crystal formation disrupted the structural integrity of the muscle tissue. Low-field nuclear magnetic resonance results showed that the freeze–thaw cycles prolonged the relaxation times (T_2b, T₂₁ and T₂₂), indicating that immobile water shifted to free water, and consequently, free water mobility increased. After 3 freeze–thaw cycles, the decline in shear force slowed, the increase in thawing loss became accelerated, and the TAC approached the domain value (6 log colony-forming units/g). Therefore, the number of freeze–thaw cycles of smooth muscle during transport, storage and distribution should be controlled to 3 or fewer. The current results provide a theoretical basis and data support for the further utilisation and culinary processing of smooth muscle.     

Removing data and using metafounders alleviates biases for all traits in Lacaune dairy sheep predictions

Bias in dairy genetic evaluations, when it exists, has to be understood and properly addressed. The origin of biases is not always clear. We analyzed 40 yr of records from the Lacaune dairy sheep breeding program to evaluate the extent of bias, assess possible corrections, and emit hypotheses on its origin. The data set included 7 traits (milk yield, fat and protein contents, somatic cell score, teat angle, udder cleft, and udder depth) with records from 600,000 to 5 million depending on the trait, ～1,900,000 animals, and ～5,900 genotyped elite artificial insemination rams. For the ～8% animals with missing sire, we fit 25 unknown parent groups. We used the linear regression method to compare “partial” and “whole” predictions of young rams before and after progeny testing, with 7 cut-off points, and we obtained estimates of their bias, (over)dispersion, and accuracy in early proofs. We tried (1) several scenarios as follows: multiple or single trait, the “official” (routine) evaluation, which is a mixture of both single and multiple trait, and “deletion” of data before 1990; and (2) several models as follows: BLUP and single-step genomic (SSG)BLUP with fixed unknown parent groups or metafounders, where, for metafounders, their relationship matrix gamma was estimated using either a model for inbreeding trend, or base allele frequencies estimated by peeling. The estimate of gamma obtained by modeling the inbreeding trend resulted in an estimated increase of inbreeding, based on markers, faster than the pedigree-based one. The estimated genetic trends were similar for most models and scenarios across all traits, but were shrunken when gamma was estimated by peeling. This was due to shrinking of the estimates of metafounders in the latter case. Across scenarios, all traits showed bias, generally as an overestimate of genetic trend for milk yield and an underestimate for the other traits. As for the slope, it showed overdispersion of estimated breeding values for all traits. Using multiple-trait models slightly reduced the overestimate of genetic trend and the overdispersion, as did including genomic information (i.e., SSGBLUP) when the gamma matrix was estimated by the model for inbreeding trend. However, only deletion of historical data before 1990 resulted in elimination of both kind of biases. The SSGBLUP resulted in more accurate early proofs than BLUP for all traits. We considered that a snowball effect of small errors in each genetic evaluation, combined with selection, may have resulted in biased evaluations. Improving statistical methods reduced some bias but not all, and a simple solution for this data set was to remove historical records.     

基于VMD和改进TCN的短期光伏发电功率预测

光伏发电功率存在波动性,且光伏出力易受各种气象特征影响,传统TCN网络容易过度强化空间特性而弱化个体特性。针对上述问题,文中提出一种基于VMD和改进TCN的短期光伏发电功率预测模型。通过VMD将原始光伏发电功率时间序列分解为若干不同频率的模态分量,将各个模态分量以及相对应的气象数据输入至改进TCN网络进行建模学习。利用中心频率法确定VMD的最优分解模态分解个数。在传统TCN预测模型的基础上,使用DropBlock正则化取代Dropout正则化以达到抑制卷积层中信息协同的效果,并引入注意力机制自主挖掘并突出关键气象输入特征的影响,量化各气象因素对光伏发电的影响,从而提高预测精度。以江苏省某光伏电站真实数据为例进行仿真实验,结果表明所提预测方法的RMSE为0.62 MW,MAPE为2.03%。     

基于多媒体技术的思想政治教育课程资源整合系统

为解决资源种类划分结果异常,设计基于多媒体技术的思想政治教育课程资源整合系统。选用CYUSB3014芯片作为此次设计系统的主控芯片,并设定信息处理芯片以及外围电路。在此基础上,对思政课程信息进行分类,建立了课程资源库。优化资源整合模块,设定多媒体资源整合流程,并添加DataSet与.NET Framework数据处理程序,实现对多媒体数据的高效处理。构建系统测试环节显示,此系统资源种类划分结果较为合理且系统承载率较高。由此可知,此系统在应用中具有较高的综合性能。     

“自动控制系统工程设计”课程思政教学实践

学习不仅仅是自然科学知识的学习，更是社会科学、民族文化、正确人生观和价值观的形成过程，“课程思政”无疑正是实现该目标的捷径，它是当前高等院校思想政治教育的新模式。如何提升学生解决“复杂工程问题”的能力成为高校开展工程教育和“新工科”的难点和重点，而课程思政正是培养学生解决“复杂工程问题”中所需要的非技术因素的重要途径。“自动控制系统工程设计”是自动化专业高年级学生的一门专业课，当前关于“课程思政”的论述是指导思想居多、实施经验以及案例设计较少，针对该问题以“自动控制系统工程设计”为例，详细给出了“课程思政”教学案例的具体实施过程，对同类课程提供参考。     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Experimental and numerical investigations on the heat production and thermal storage characteristics of rapid preparation amorphous powder activated coke

The heat production and thermal storage characteristics of rapid-preparation amorphous powder activated coke (RAC) were investigated. RAC was prepared by using a drop-tube reactor system. The natural oxidation characteristics of RAC were studied through combined TG–FTIR analysis and temperature-programmed experiment. Experimental results showed that CO and CO₂ were the main oxidation products of RAC in air, and that the oxidation reaction was in accordance with the Arrhenius equation and law of mass action. Thermal storage characteristics were studied through computational fluid dynamics simulation. The maximum excess temperature θ_max increases linearly with the increase of the initial temperature. The concentration fields of the products show that CO₂ is mainly concentrated in the upper part of the coke bin, and the CO generated by CO₂ at high temperature is mainly concentrated in the central part of the coke bin.     

Natural hydrogen emanations in Namibia: Field acquisition and vegetation indexes from multispectral satellite image analysis

Natural hydrogen exploration is now active in various places of the world. Onshore, correlation between natural H₂ generation and the presence of iron rich rocks especially from Archean and Neoproterozoic cratons have been observed. Emanations and accumulations of H₂ have already been confirmed in such geological settings in Australia, South Africa and Brazil. The geological similitude and the presence of numerous sub circular depressions that are a good proxy for hydrogen emanations suggest that hydrogen resources may also exist in Namibia. We present here the results of a data acquisition campaign which allowed us to confirm the presence of natural hydrogen in this country in the vicinity of Neoproterozoic Banded Iron Formation. The H₂ content in the soil, as in Brazil, is variable within the depressions in time and space and is particularly time sensitive across the day. Comparison of the H₂ signal versus time within these two regions shows a similar behavior of the soils with an increase of the H₂ flow at the middle of the day. In addition, these new data allow us to better constrain the morphological characteristics of such H₂-emiting depressions. By using satellite images and digital elevation model we propose a new proxy to differentiate potentially H₂-emiting features from other type of depressions such as Salt Pan. The Landsat multispectral images and their processing through NDVI and SAVI indexes, that highlight a ring of healthy vegetation around the sub circular area with scarce vegetation already observed appear able to discriminate between H₂ emitting structures and other soft depressions.