浅议生态环境监测机构的风险控制

现阶段,为了探索创新性的发展途径,生态环境监测机构应始终增强风险控制意识。应加强风险管理,立足于风险控制,以求不断健康发展。     

基于“天空地”一体化技术的安全监测系统建设与应用

西藏江达县白格村金沙江右岸于2018年10月11日和2018年11月3日先后发生2次大规模滑坡—堰塞湖堵江事件,溃堰洪水对下游拉哇库区不良地质体的稳定性造成不同程度的影响。为保障下游水电站建设安全,对拉哇库区主要不良地质体建立了基于星载InSAR技术、无人机技术和地面传感器实时监测的“天空地”一体化监测预警体系,以多维空间采集技术获取变形信息,通过智能监控平台对信息及时进行处理、分析和可视化呈现,利用平台、短信等方式向相关人员进行分级告警,取得了较好的应用效果。     

Statistical testing for sufficient control chart performances during monitoring of grouped processes

With ISO 7870-8, a standardized application of charting techniques for short runs and small mixed batches was presented in 2017. Similar to various scientific approaches, it requires that sample values from grouped processes follow nearly identical distributions. In practice, however, there tend to be differences between distribution parameters. Moreover, equal parameters do not ensure that distributions are properly aligned to the center line and control limits of the chart. These facts can lead to undesired control chart performances which can be expressed by average run lengths (ARL) during in-control and out-of-control conditions. In this work, a statistical test for sufficient control chart performances during monitoring of grouped processes based on preliminary samples is proposed. Control chart performances are defined as sufficient when they deviate within acceptable ranges from usual performances during single process monitoring in mass production. The ARL resulting from estimated distributions and planned production sequences is used as test statistic and calculated via the Markov chain approach. Exemplary tests are executed for scenarios with individuals and cumulated sum (CUSUM) charts. A simulative determination of error rates resulting from the ARL-based testing demonstrates its effectiveness in testing for sufficient control chart performances compared to an indirect testing with Levene's test and a one-way analysis of variance (ANOVA).     

The effectiveness of adaptive versus non-adaptive learning with digital educational games

For the training of academic skills, digital educational games with integrated adaptivity are promising. Adaptive games are considered superior to non-adaptive games, because they constantly assess children's performance, and accordingly adapt the difficulty of the tasks corresponding to the children's individual level. However, empirical evidence with regard to the effectivity of adaptive compared to non-adaptive games is limited. A study was conducted with 191 children from the third year of Kinder garten who were enrolled in one of three conditions, that is, playing an adaptive version of the reading game (RG), a non-adaptive version of the RG or training with pen-and-paper exercises. In all three conditions, children trained emergent reading (phonological awareness and letter knowledge) once a week for 30 min over a period of 5 weeks. Children's performance on cognitive (phonological awareness, letter knowledge, reading fluency) and non-cognitive (motivation, self-concept) factors was assessed. Results revealed a significant improvement in phonological awareness and letter knowledge in all conditions. However, no differences between the conditions were observed with respect to children's improvement on phonological awareness and letter knowledge or on their post-test scores for reading fluency. With regard to motivation and self-concept, again, no differences in these non-cognitive factors were observed across conditions.     

煤矿井下风水管路压力在线监测系统的研究与应用

为提高井下管路供风、供水的安全性、可靠性，以工业环网作为网络通信平台，通过分站采集数据上传至地面，实现对煤矿井下供风、供水管道的远程实时监控及远程控制，及时发现管网故障，提高维护效率、降低损失，保障供风、供水质量，达到科学预警、降低成本、提高效率的目的。     

In situ monitoring of the biocatalysed partial hydrolysis of cocoa butter and palm oil fraction

Partial glycerides are widely used ingredients in confectionery products that can be produced from natural fats. In a biocatalytic partial hydrolysis of cocoa butter and palm oil fractions, a product mixture containing 1.5% monoglycerides and 5.5% diglycerides intended for the use in confectionery products was created. This study is a proof of principle that shows the feasibility of monitoring the biocatalytic partial hydrolysis of these two natural fats in situ with ATR-FTIR spectroscopy. An economic approach was utilised for calibration since partial glyceride calibration standards are costly and poorly available. The released compounds were quantified by means of chemometric modelling, and the model was validated with gas chromatography. Resulting root mean square errors were in the low per cent range. Additionally, the results indicate that distinction of the released free fatty acids is possible with ATR-FTIR spectroscopy.     

基于可调谐半导体激光吸收光谱技术的甲烷气体监测研究

设计了一种基于可调谐半导体激光吸收光谱技术的甲烷(CH4)气体监测装置,该装置具有温度监测范围大、监测精度高和实时监测的优点。监测装置的激光光源为波长1650 nm的反馈式激光器,应用波长调谐与锁相放大器技术,对周围环境进行温度补偿与背景扣除,可以较准确地测量周围环境中CH4的体积分数。实验表明,当CH4体积分数小于1%时,该装置的监测精度为±0.02%;当CH4体积分数大于1%时,装置监测误差小于±0.8%,实时监测的最长响应时间为10 s。装置的温度范围为0~40℃,可满足大多数工业生产中对CH4等气体体积分数的监测需求。     

Ecological patterns of fish distribution in the Slave River Delta region,Northwest Territories,Canada, as relayed by traditional knowledge and Western science

Indigenous community members along the Slave River in Canada have voiced their concerns for the health of ecosystems under pressure from resource extraction, hydroelectric development and global climate change. We present a test case of traditional knowledge and scientific results about the spawning and migration patterns of fish in the Slave River and Delta. This dual knowledge system approach elucidates the broader connectivity of local study regions and can improve monitoring programmes by extending beyond the usual context/confines of the present or recent past, increasing the spatial and temporal range of system information.     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.