“黄金分割法”在爆破工程中的应用探讨

"黄金分割法"是一种古老的数学方法,它无处不在并造就了事物的和谐美,多年来经常被应用到艺术、摄影、绘画、设计等多个领域,而且得到了意想不到的效果。根据多年的爆破工程实践,将"黄金分割法"与工程爆破实例相结合,应用到露天爆破、高耸建(构)筑物爆破拆除等工程中,取得了很好的爆破效果。     

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。     

粉体含能材料生产与储运中的静电安全及防护

分析了静电产生的原因,阐述了粉体含能材料生产中的静电起电现象、静电的危害、静电安全性评估标准以及建立在此标准基础上的静电放电危险的评价办法,提出了粉体含能材料在生产、运输中所需要采取的静电防护措施。     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.     

钢混结构大型厂房整体式爆破拆除

采用整体式控制爆破拆除方案对华电扬州电厂钢筋混凝土框-排架结构厂房进行了爆破拆除。爆破前,对汽机房、厂房外墙和楼梯进行了预处理。将厂房划分为3个爆区,采用非电多回路网格式爆破网路,依靠东侧锅炉房倒塌施加在西侧锅炉房上的倾覆力矩,有效地克服了西侧锅炉房向西倒的难题,可为同类工程提供一定的参考。     

面粉厂车间楼定向倾倒爆破

该楼体为框架结构,是车间楼和办公楼的结合体,由于加工面粉设备流程的需要,该楼同时承受动荷载和静荷载。楼体按照伸缩缝分为3部分,每部分的结构不相同,同部分不同层结构也各异。在爆破过程中严格控制各种参数,并采取有效的减振与防护措施,使此爆破工程在安全和质量上都达到了预期效果。     

Additional deepwater sampling of prey fish in Lake Michigan annual bottom trawl survey reveals new insights for depth distribution dynamics

Beginning in 2013, sites at the 128-m bottom depth contour were added to the sampling design of the annual Lake Michigan bottom trawl survey for prey fish, which has been conducted by the U.S. Geological Survey Great Lakes Science Center (GLSC) each fall since 1973, to better assess fish depth distributions in a changing ecosystem. The standard sampling design included bottom depths from 9 to 110 m, although the GLSC also sporadically conducted bottom trawl tows at the 128-m bottom depth contour during 1973–1988. Enactment of this new sampling design in 2013 revealed that mean biomass density of deepwater sculpins (Myoxocephalus thompsonii) at the 128-m depth exceeded the sum of mean biomass densities at shallower depths, indicating that the bulk of the deepwater sculpin population is residing in waters deeper than 110 m. Thus, our findings supported the hypothesis that the depth distribution of the deepwater sculpin population had shifted to deeper waters beginning in 2007, thereby explaining, at least in part, the marked decline in deepwater sculpin abundance since 2006 based on the standard sampling design. In contrast, our results did not support the hypothesis that the slimy sculpin (Cottus cognatus) population had shifted to deeper waters sometime after 2000. A portion of the burbot (Lota lota) population may have also shifted in depth distribution to waters deeper than 110 m after 2007, based on our results. Our findings have served as an impetus to further expand the range of depths sampled in our bottom trawl survey.     

Mathematical Modeling of Drying Processes of Selected Fruits and Vegetables

This study investigates the behavior of fruit and vegetable samples during drying. The experimental data are fitted to several different thin-layer drying models. Regression analysis is used to determine model parameters, while statistical indicators serve to evaluate the goodness of fit. The power function model gives the best fit for all examined samples. Based on this model, different drying and heat storage technologies can be combined to ensure that the required residual moisture content of an agricultural product is reached. It is demonstrated on the case of a specific Togolese processing plant that under favorable conditions, fossil fuel consumption can be decreased by 33 %.     

Improving the shelf life stability of vacuum-packed fresh-cut peaches (Prunus persica L.) by radio frequency heating in water

The present study aimed to investigate the influence of radio frequency (RF) heating at 70 and 80 °C, in comparison with the traditional conventional heating. The RF heating technology was applied for maintaining the colour and textural quality as well as inactivating the enzymatic activity of polyphenol oxidase (PPO) and reducing the Escherichia coli growth in packaged fresh-cut peach samples. To evaluate this, 120 g of freshly cut peach fruit was placed in heat-resistant plastic bags, and 50 mL of sugar solution (12°Brix) was added to each bag and vacuum-packed for conventional heating and radio frequency (RF) heating. Our results demonstrated that the RF heating process could reduce the heating time by up to 83% at 70 and 80 °C as compared to conventional heating. Moreover, RF heating at 70 and 80 °C reduced the PPO enzymatic activity, which caused enzymatic browning, up to 85.46% and 93.5%, respectively, as compared to 40.86% reduction only for conventional heating. Furthermore, RF heating completely inhibited E. coli growth. Collectively, we demonstrated that RF heating is an emerging and promising technology for improving the quality of fresh-cut fruits such as peach during various storage conditions. The present study provides relatively novel information on the effectiveness of RF heating in maintaining the quality of fresh-cut peaches. In the future, we would like to investigate the effectiveness of RF heating on other agricultural products.     

Stability of electronic nose (e-nose) as determined by considering date-pits heated at different temperatures

Variability and sensitivity of a portable electronic nose (32 sensors) was assessed by considering different variables for measurement (i.e., reference, standard, first and second purges, sample draw time, waiting time for the volatiles released in the headspace, and mass of sample or headspace volume of the jar containing sample). In this study, dried date-pits were used a model sample. The highest stability was achieved when both reference and standard (i.e., dried date-pits, no heating treatment) were used before test sample measurement. Higher sample draw time more than 10 s significantly decreased the stability, whereas optimum second purge was observed at 50 s. Optimum time to generate volatile was observed as 24 h. A sample of 100 g increased the signal intensity compared to the 50 g sample for the 60°C and 100°C treated samples, while an opposite trend was observed for the 150°C treated sample. Finally, the responses of volatile components in date-pits heated at different temperatures (60°C, 100°C, and 150°C) were measured using the optimum operating conditions. Principal component analysis explored the relationships between the volatile features and classified date-pits heated at different temperatures. The results showed that an electronic nose was able to classify date-pits based on their volatile components generated by different degrees of heating (93.3% accuracy).