鸭绿江(丹东段)水污染控制系统规划研究

鸭绿江是中朝两国的界河,是沿江两国人民生活和生产的主要水源。下游河道长233km,可分为各具特点的三个江段:上段由浑江至水丰电站,为水库淹没区;中段由太平湾电站至马市为河流段;下段由马市至江海分界线为感潮河口段,该段长约55km,潮流界在东尖头处,距江口27km。下段中,由大沙河口开始承纳中朝两国沿岸工矿、城镇排放的大量污水,使宽阔(干流宽度为1～3km)江面的沿岸两侧形成了二条明显的岸边污染带,中方江桥处污染带宽达200m左右。从目前和未来都不能满足水产养殖和旅游的要求。本研究的目的是为经济有效地改善鸭     

炸药及火工品可靠性与安全性评定方法

可靠性的评定结果是否可信,直接关系到炸药及火工品的使用安全性和作用可靠性。但是,现有炸药及火工品可靠性评定方法却存在着达不到置信度要求、评价结果偏于危险的缺点。为此,提出了一种确定炸药及火工品安全度和可靠度的高精度方法,并给出了应用实例。该方法不仅可信程度高,而且适用于小样本情况,尤其是在利用了以往试验数据后,既可提高安全性和可靠性评定的精度,又可大大节省试验的费用及时间     

邻苯二甲酸二丁酯的微生物降解

通过驯化富集培养,从处理石化厂废水的活性污泥中分离出１株邻苯二甲酸酯降解菌ＦＳＩ,研究了邻苯二甲酸酯菌ＦＳＩ对邻苯二甲酸二丁酯的生物降解特性。邻苯二甲酸酯降解菌ＦＳＩ降解最适酸度为ｐＨ６．５～８．０,温度为２０～３５℃。菌株ＦＳＩ对邻苯二甲酸二丁酯的生物降解反应速率遵循一级反应动力学模式。试验结果表明,菌株ＦＳＩ对邻苯二甲本二丁酯具有高效降解作用。     

天津地区土壤中萘的生态风险分析

以天津地区表土188个样点的实测萘浓度以及萘对10种代表性土壤生物的半致死浓度为基础资料,尝试用3种方式评价了该地区土壤中萘的生态风险.并进行了方法学比较.研究结果发现,暴露浓度和毒性效应概率密度函数的重叠面积与联合概率曲线一致地反映出很低的生态风险,准确计算的暴露浓度超过LC50的概率仅为1.67%.结果说明该地区土壤萘的生态风险极低,仅严重污染的局部地区可能发生最敏感生物种受害.用于进行风险评价的3种方法各有利弊.     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

电子废弃物中持久性有机污染物分析检测方法的研究进展

针对目前电子废弃物中持久性有机污染物(POPs)尚未形成有效快速分析检测方法的问题,介绍了溶剂萃取、固相萃取、微波萃取和超临界流体萃取等POPs前处理技术的研究进展,总结了POPs的分析方法,如:气相色谱、液相色谱、气相色谱-质谱法、高分辨率气相色谱-高分辨质谱法等化学分析方法,以及生物传感器测定法、表面胞质团共振检测法、酶联免疫检测法等生物分析方法。分析了各方法的优劣,并提出了展望。     

Effects of Zr substitution on soot combustion over cubic fluorite-structured nanoceria: Soot-ceria contact and interfacial oxygen evolution

Ceria is widely used as a catalyst for soot combustion, but effects of Zr substitution on the reaction mechanism is ambiguous. The present work elucidates effects of Zr substitution on soot combustion over cubic fluorite-structured nanoceria. The nanostructured CeO₂, Ce_0.92Zr_0.08O₂, and Ce_0.84Zr_0.16O₂ composed of 5–6 nm crystallites display T_m-CO2 (the temperature at maximum CO₂ yield) at 383, 355, and 375°C under 10 vol.% O₂/N₂, respectively. The size of agglomerate decreases from 165.5 to 51.9–57.3 nm, which is beneficial for the soot-ceria contact. Moreover, Zr increases the amount of surface oxygen vacancies, generating more active oxygen (O₂^? and O^?) for soot oxidation. Thus, the activities of Ce_0.92Zr_0.08O₂ and Ce_0.84Zr_0.16O₂ in soot combustion are better than that of CeO₂. Although oxygen vacancies promote the migration of lattice O^2?, the enriched surface Zr also inhibits the mobility of lattice O^2?. Therefore, the T_m-CO2 of Ce_0.84Zr_0.16O₂ is higher than that of Ce_0.92Zr_0.08O₂. Based on reaction kinetic study, soot in direct contact with ceria preferentially decomposes with low activation energy, while the oxidation of isolated soot occurs through diffusion with high activation energy. The obtained findings provide new understanding on the soot combustion over nanoceria.     

自动变光焊接滤光片响应时间快速测试设备

自动变光焊接防护装备已在欧美国家得到广泛应用,其关键部件是自动变光焊接滤光片。响应时间是自动变光焊接滤光片的关键技术指标,目前国内缺乏响应时间快速测试技术。本文介绍了一种响应时间快速测试设备,可以满足符合欧洲标准及我国国家标准中的测试要求。     

煤矿火灾爆炸外因火源来源及预防方法研究

对我国1950～2009年煤矿特别重大火灾、爆炸事故进行统计分析,找到引起事故的火源分布规律。结果表明,88.1%的事故由外因火源引起;引起事故的外因火源来源按发生频率大小主要有：违章放炮、仪器设备失爆、摩擦撞击、带电作业、电缆短路、拆卸设备、电缆接头漏电、明火明电、吸烟;其中,68%的外因火源来源于工人的违章行为,32%的外因火源来源于电气设备原因。在对近年外因点火源特征分析的基础上,笔者针对工人违章行为及电气设备原因提出预防措施：完善安全结构工资;逐步建立工人违章联锁制度,又称＂安全伙伴＂;对一线工人普及电气安全知识,并将可能存在明显电气安全隐患的部分分配给普通工人负责。