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.     

Evaluation of activated sludge properties’ changes in industrial-wastewater pre-treatment: role of residual aluminum hydrolyzed species with different polymerization degree

● Medium poly Al salts dominated the PAC residual salts with a rational dosage. ● Settlement flocculation effect under medium poly Al salts showed a better trend. ● Complex of medium poly Al salts and enzymes promoted cell activity. ● Medium poly Al salts were beneficial to the effluent indexes. With the widespread introduction of pre-coagulation prior to the biological unit in various industrial wastewater treatments, it is noteworthy that long-term accumulation of residual coagulants has certains effect on both micro and macro characteristics of activated sludge (AS). In this study, the morphology distributions of residual aluminum salts (RAS) and their effects on the removal efficiency of AS were investigated under different PAC concentrations. The results showed that the dominance of medium polymeric RAS, formed under an appropriate PAC dose of 20 mg/L enhanced the hydrophobicity, flocculation, and sedimentation performances of AS, as well as the enzymatic activity in cells in the sludge system, improving the main pollutants removal efficiency of the treatment system. Comparatively the species composition with monomer and dimer / high polymer RAS as the overwhelming parts under an over-dosed PAC concentration of 55 mg/L resulted in excessive secretion of EPS with loose flocs structure and conspicuous inhibition of cellular activity, leading to the deterioration of physico-chemical and biological properties of AS. Based on these findings, this study can shed light on the role of the RAS hydrolyzed species distributions, closely relevant to Al dosage, in affecting the comprehensive properties of AS and provide a theoretical reference for coagulants dosage precise control in the pretreatment of industrial wastewater.     

Screening of indicator pharmaceuticals and personal care products in landfill leachates: a case study in Shanghai,China

● A systematic framework was developed to identify i-PPCPs for landfill leachate. ● The wide-scope target analysis offered a basis for comprehensive i-PPCP screening. ● Source-specificity and representativeness analysis helped to refine i-PPCPs. ● Erythromycin, gemfibrozil and albendazole were identified as i-PPCPs for leachate. Identifying potential sources of pharmaceuticals and personal care products (PPCPs) in the environment is critical for the effective control of PPCP contamination. Landfill leachate is an important source of PPCPs in water; however, it has barely been involved in source apportionment due to the lack of indicator-PPCPs (i-PPCPs) in landfill leachates. This study provides the first systematic framework for identifying i-PPCPs for landfill leachates based on the wide-scope target monitoring of PPCPs. The number of target PPCPs increased from < 20 in previous studies to 68 in the present study. Fifty-nine PPCPs were detected, with median concentrations in leachate samples ranging from below the method quantification limit (MQL) to 41 μg/L, and 19 of them were rarely reported previously. A total of 29 target compounds were determined to be PPCPs of high concern by principal component analysis according to multiple criteria, including occurrence, exposure potential, and ecological effect. Coupled with source-specificity and representativeness analysis, erythromycin, gemfibrozil, and albendazole showed a significant difference in their occurrence in leachate compared to other potential sources (untreated and treated municipal wastewater and livestock wastewater) and correlated with total PPCP concentrations; these were recommended as i-PPCPs for leachates. Indicator screening procedure can be used to develop a sophisticated source apportionment method to identify sources of PPCPs from adjacent landfills.     

城市地震次生火灾分析及处置对策

现代城市地震次生火灾发生概率大,扑救难度大,极易造成大量的人员伤亡以及财产损失。大量的统计数据表明,震后火灾的诱因、时空分布及消亡因素有着一定的规律性。本文在详细分析城市地震次生火灾发生的原因、火灾时空分布及危害特点的基础上,针对应急处置对策和长远处置对策等方面提出了新的观点,可供消防部队处置此类灾害时参考。     

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。     

儿童在道路行驶中的安全与防护——加拿大新的儿童汽车座椅法规与测试方法

本文主要介绍加拿大新的《机动车辆约束系统和加高座椅安全法规》（SOR/2011-16）的相关内容,同时对儿童汽车座椅的研究与测试方法也进行了详细描述,以对我国相关行业提供借鉴。     

Scenario simulation of water security in China

Umited water resources, increasing demand, low use efficiency, and serious pollution result in severe water resource difficult in China. The evaluation of addressing water problems and the search for effective countermeasures that ensure sustainable water use are key to China‘ s sustainable development. The “compound water security“ consists of food security, life security, environmental security, and economic security. By establishing a conceptual model, the water security of China has been simulated in terms of four scenarios called BAU(the business-as-usual scenario), TEC(the technology and economics scenario), IVL(the institution, values, and lifestyles scenario) and TSD(toward sustainable development) in this paper. The results indicated that water crises, especially water shortages, are being experienced now and will continue to do so for a relatively long time in China and that it is possible to reach a basic balance between supply and demand of water and grain under the TSD developing pattern by a series of approaches including technological innovation, policy adjustments, and behaviour inducement.     

胶结液注入轮数和体积对微生物加固粉土的影响∗

通过微生物诱导碳酸钙沉积可以将松散土颗粒胶结成整体从而达到加固目的。胶结液的注入轮数和每轮使用的胶结液体积会影响加固效果,但目前关于这方面的研究还不充分。以海相粉土为处理对象,通过室内试验来研究胶结液的注入轮数和体积对加固效果的影响。改变胶结液注入轮数的试验结果表明:随着注入轮数的增加,试样中沉积生成的碳酸钙逐渐增多,碳酸钙的分布比较均匀,加固后的无侧限抗压强度逐渐提高;但当胶结液的注入达到一定轮数后,强度的增长幅度逐渐减缓。改变每轮胶结液体积用量的试验结果表明:胶结液体积的增加会带来碳酸钙数量的增加和强度的提高,但当胶结液体积从1.5Vv(孔隙体积)增加至2Vv后,效果改善不明显。从钙离子用量与无侧限抗压强度的关系也表明,每轮注入的胶结液体积应选择1.5Vv。     

镉"加标"沉积物对泥鳅(Misgurnus anguillicaudatus)生物毒性研究

选择泥鳅(Misgurnus anguillicaudaus)作为受试生物,以泥鳅死亡率、血液红细胞数量、红细胞体积、红细胞微核率和核异常率作为测试指标,考察了沉积物中"加标"金属镉(Cd)的毒性状况,探讨了水体沉积物中重金属的生物毒性影响.结果表明:高有机质的粘土粉砂性沉积物能够有效吸附重金属镉;镉加标暴露组泥鳅的死...