CFRP筋增强钢纤维混凝土梁受剪承载力试验与分析∗

对 CFRP 箍筋和纵筋增强钢纤维混凝土梁的受剪承载力进行研究,通过 6 根梁的加载试验研究了剪跨比、配箍率和箍筋种类对受剪承载力的影响。考虑 CFRP 纵筋与混凝土的粘结性能,建立了 CFRP 筋增强钢纤维梁受剪承载力计算方法。结果表明：①CFRP 筋增强钢纤维混凝土梁受剪承载力高,破坏前斜裂缝宽度大,破坏有明显预兆;②钢纤维可有效减小斜截面开裂后前期的 CFRP 箍筋应力,有利于箍筋强度发挥,CFRP 箍筋的极限应变可取为 0.004;③CFRP 纵筋发挥强度高,需注意锚固长度和设计使用应力,防止滑移拔出和销栓破断;④给出的受剪承载力计算方法具有较高的计算精度高。     

兰州市城区河道表层沉积物重金属污染及磁学参数相关关系研究

以兰州市城区8条河流的表层沉积物为研究载体,通过Hakanson潜在生态风险指数法、地质累积指数法及富集因子评价法等3种污染评价指标以及环境磁学方法对As、Co、Cr、Cu、Ni、Pb、V、Zn共8种重金属元素污染特征进行分析.结果显示,①元素As、Co、Ni、V在8条河流中均表现为轻微生态危害;元素Cr、Pb、Zn在...     

生物制药污水处理中自动控制系统运行的分析

污水处理中,自动控制系统的运行方式关系到污水处理是否达标的关键,尤其是在运行细节中,运行控制考虑得不周全,往往会影响到污水处理的效果。生物制药污水处理中,设备在运行细节控制方法中的有效解决,保证了出水稳定可靠。     

Mineral nutrient imbalance, DNA lesion and DNA-protein crosslink involved in growth retardation of Vicia faba L. seedlings exposed to lanthanum ions

Effects of mineral nutrient imbalance, DNA lesion and DNA-protein crosslink on growth of Vicia faba L. seedlings hydroponically cultivated in concentrations of extraneous lanthanum (La) for 20 days were investigated in the present experiment. The results showed that contents of La, Cu or K elements in roots generally changed synchronously with those in leaves, while Ca, Fe, Zn, Mg, Mn or P in the roots altered inversely to those in the leaves. Thus, the extraneous La led to redistribution and imbalance of mineral nutrient elements in the roots and leaves. DNA lesion and DNA-protein crosslink were investigated by single cell gel electrophoresis (SCGE) and sodium dodecyl sulfate/potassium (SDS/K⁺) precipitation methods, respectively. The results demonstrated that the increasing La induced DNA break and DNA-protein crosslinks (DPCs) in the seedlings. These results suggested that mineral nutrient imbalance, DNA lesion and DNA-protein crosslink were involved in the growth retardation and growth alteration of the seedlings, which may help to understand the mechanisms of rare earth elements (REEs) on plant growth.     

Preparation of birnessite-supported Pt nanoparticles and their application in catalytic oxidation of formaldehyde

Flaky and nanospherical birnessite and birnessite-supported Pt catalysts were successfully prepared and characterized by means of X-ray diffraction (XRD), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS) and N₂ adsorption-desorption. Effects of the birnessite morphology and Pt reduction method on the catalytic activity for the complete oxidation of formaldehyde (HCHO) were investigated. It was found that flaky birnessite exhibited higher catalytic activity than nanospherical birnessite. The promoting effect of Pt on the birnessite catalyst indicated that the reduction method of the Pt precursor greatly influenced the catalytic performance. Flaky birnessite-supported Pt nanoparticles reduced by KBH₄ showed the highest catalytic activity and could completely oxidize HCHO into CO₂ and H₂O at 50℃, whereas the sample reduced using H₂-plasma showed lower activity for HCHO oxidation. The differences in catalytic activity of these materials were jointly attributed to the effects of pore structure, surface active sites exposed to HCHO and the dispersion of Pt nanoparticles.     

Removal of sulfamethazine antibiotics by aerobic sludge and an isolated Achromobacter sp. S-3

Removal characteristics of sulfamethazine (SMZ) by sludge and a bacterial strain using an aerobic sequence batch reactor (ASBR) were studied. Operating conditions were optimized by varying the reaction time and sludge retention time (SRT). An Achromobacter sp. (S-3) with the ability to remove SMZ was isolated from the ASBR. The effects of different operating parameters (pH and temperature) on the biodegradation of SMZ by S-3 were determined. The results indicate that, between 0.5 and 4 hr, reaction time of the ASBR had a significant effect on the SMZ removal efficiency in the system. The SMZ removal efficiency also increased from 45% to 80% when SRT was prolonged from 5 to 25 days, although longer SRT had no impact on SMZ removal. The SMZ adsorption rate decreased with increasing temperature, which fitted Freundlich isotherm well. The removal of SMZ in the ASBR was due to the combined effects of adsorption and degradation, and degradation played a leading role.     

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

● A novel deep learning framework for short-term water demand forecasting. ● Model prediction accuracy outperforms other traditional deep learning models. ● Wavelet multi-resolution analysis automatically extracts key water demand features. ● An analysis is performed to explain the improved mechanism of the proposed method. Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of methods have been proposed to improve forecast accuracy, it is still difficult for statistical models to learn the periodic patterns due to the chaotic nature of the water demand data with high temporal resolution. To overcome this issue from the perspective of improving data predictability, we proposed a hybrid Wavelet-CNN-LSTM model, that combines time-frequency decomposition characteristics of Wavelet Multi-Resolution Analysis (MRA) and implement it into an advanced deep learning model, CNN-LSTM. Four models - ANN, Conv1D, LSTM, GRUN - are used to compare with Wavelet-CNN-LSTM, and the results show that Wavelet-CNN-LSTM outperforms the other models both in single-step and multi-steps prediction. Besides, further mechanistic analysis revealed that MRA produce significant effect on improving model accuracy.     

Long-term exposure to air pollution and cerebrovascular disease: findings from Beijing Health Management Cohort study

● This study explored the long-term association by double robust additive models. ● Individual exposure concentrations were assessed by integrating GAM, LUR and BPNN. ● PM_2.5, SO₂ and NO₂ are positively associated with cerebrovascular disease. ● CO could reduce the risk of cerebrovascular disease with the highest robustness. ● The elderly, women and people with normal BMI are at higher risk for air pollution. The relationship between air pollution and cerebrovascular disease has become a popular topic, yet research findings are highly heterogeneous. This study aims to investigate this association based on detailed individual health data and a precise evaluation of their exposure levels. The integrated models of generalized additive model, land use regression model and back propagation neural network were used to evaluate the exposure concentrations. And doubly robust additive model was conducted to explore the association between cerebrovascular disease and air pollution after adjusted for demographic characteristics, physical examination, disease information, geographic and socioeconomic status. A total of 25097 subjects were included in the Beijing Health Management Cohort from 2013 to 2018. With a 1 μg/m³ increase in the concentrations of PM_2.5, SO₂ and NO₂, the incidence risk of cerebrovascular disease increased by 1.02 (95% CI: 1.008–1.034), 1.06 (95% CI: 1.034–1.095) and 1.02 (95% CI: 1.010–1.029) respectively. Whereas CO exposure could decrease the risk, with an odds ratio of 0.38 (95% CI: 0.212–0.626). In the subgroup analysis, individuals under the age of 50 with normal BMI were at higher risk caused by PM_2.5, and SO₂ was considered more hazardous to women. Meanwhile, the protective effect of CO on women and those with normal BMI was stronger. Successful reduction of long-term exposure to PM_2.5, SO₂ and NO₂ would lead to substantial benefits for decrease the risk of cerebrovascular disease especially for the health of the susceptible individuals.     

悬浮态水泥生料固硫效率试验研究

在水泥工业领域,水泥生料作为悬浮预热预分解系统脱硫过程中的固硫剂,为了研究固气比、温度、气体流速、SO2浓度以及水泥生料比表面积对悬浮态水泥固硫效率影响规律,采用水泥工厂的生料,利用悬浮电阻炉对水泥生料固硫效率进行试验研究,研究发现固气比和温度对水泥生料固硫效率影响较大。     

北京市大气PM10源解析研究

于2004年在北京市定陵、车公庄、古城、亦庄、房山和奥体中心6个采样点采集大气PM10环境样品,针对北京市颗粒物主要排放源采集土壤尘、建筑水泥尘、燃煤等污染源PM10样品,分别对其中的无机元素、离子、有机碳(OC)和元素碳(EC)进行测定。采用代表北京市颗粒物主要排放源PM10组分特征的成分谱,利用CMB受体模型对PM10来源进行解析。结果表明,PM10的最大来源为土壤尘,其它贡献源类依次为燃煤排放、机动车/燃油排放、二次粒子(SO42-、NO3-和NH4 )、建筑水泥尘。污染源贡献具有明显的季节变化,并存在一定的地域变化。