Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

A recurrent neural network using historical data to predict time series indoor PM2.5 concentrations for residential buildings

Due to the severe outdoor PM2.5 pollution in China, many people have installed air-cleaning systems in homes. To make the systems run automatically and intelligently, we developed a recurrent neural network (RNN) that uses historical data to predict the future indoor PM2.5 concentration. The RNN architecture includes an autoencoder and a recurrent part. We used data measured in an apartment over the course of an entire year to train and test the RNN. The data include indoor/outdoor PM2.5 concentration, environmental parameters and time of day. By comparing three different input strategies, we found that a strategy employing historical PM2.5 and time of day as inputs performed best. With this strategy, the model can be applied to predict the relatively stable trend of indoor PM2.5 concentration in advance. When the input length is 2 h and the prediction horizon is 30 min, the median prediction error is 8.3 µg/m³ for the whole test set. For times with indoor PM2.5 concentrations between (20,50] µg/m³ and (50,100] µg/m³, the median prediction error is 8.3 and 9.2 µg/m³, respectively. The low prediction error between the ground-truth and predicted values shows that the RNN can predict indoor PM2.5 concentrations with satisfactory performance.     

Transient Simulation of Hollow‐Fiber Membrane Filtration with Nonuniform Permeability Distribution

Transient simulation of filtration in hollow‐fiber membranes with nonuniform permeability distribution was conducted. The diversity of permeability distributions caused different initial flux and transmembrane pressure distributions. Manipulating the permeability distribution enables a hollow‐fiber membrane to achieve its maximum volumetric flow rate. During solid‐liquid separation, the inter‐adjustment between flux and cake distributions improved their uniformities simultaneously. The reciprocal of the volumetric flow rate of the membranes all increased linearly with water production. Severely nonuniform permeability distribution caused low water production. The numerical results could be applicable to account for the non‐ideal performance of industrial hollow‐fiber membrane modules.     

Alkali metal ion substitution induced luminescence enhancement of NaLaMgWO6:Eu3+ red phosphor for white light-emitting diodes

Alkali metal ion substitution is an effective strategy to improve the luminescence properties of phosphors. In this work, a series of red-emitting phosphors Na_1-xLi_x/2K_x/2La_0.6Eu_0.4MgWO₆ were prepared by a traditional high-temperature solid-state reaction. Their phase structure, microstructure, luminescence properties and potential application in phosphor-converted white light-emitting diodes (pc-WLEDs) were investigated in detail. X-ray diffraction (XRD) result revealed the formation of a solid solution when x?≤?0.3, which kept monoclinic structure of NaLaMgWO₆. Photoluminescence investigation indicated that the partial substitution of Li⁺/K⁺ ions for Na⁺ ions improved largely the red emission of Eu³⁺. Based on the optimized Na_0.7Li_0.15K_0.15La_0.6Eu_0.4MgWO₆ sample with relatively good thermal stability, a WLED device was fabricated by combining a near-ultraviolet (NUV) chip (~400?nm) with the phosphor mixture of commercial green/blue phosphors and the optimized red phosphor. The results indicated that the optimized red phosphor in this work could be a potential candidate for WLEDs pumped by NUV chips.     

浙江示范型居家养老服务中心建设的最新进展——来自杭州市主城区的调查报告

在"十三五"国家老龄事业发展和养老体系建设规划的指引下,示范型居家养老服务中心建设在浙江省全面展开.文章选取杭州主城区三个有代表性的区域,对其中全部18家示范型居家养老服务中心进行了使用后评价普查.通过对设施布点、硬件设施、服务内容、使用状况及户外环境的调查与分析,为改进和完善城市社区养老设施建设提出了相关建议.     

A fuzzy logic PI control with feedforward compensation for hydrogen pressure in vehicular fuel cell system

In a vehicular fuel cell system, alternative load and frequent purge action can lead to anode pressure varies with the hydrogen mass flow fluctuation. It's crucial to control the pressure difference between anode and cathode within a reasonable range to avoid adverse phenomena such as membrane failure, reactant starvation, or even water management fault. In this paper, an improved proportional integrative (PI) controller by the fuzzy logic technique that considers the engineer experience and knowledge on the hydrogen supply system behavior is proposed for hydrogen pressure control, in which the PI parameters are tuned by a fuzzy decision process. Furthermore, load current and purge action regarded as input disturbances are applied for feedforward compensation to reduce the pressure response hysteresis. A hydrogen supply subsystem based on the proportional valve is modeled, and corresponding parameters are determined by analyzing the response time and steady pressure fluctuation. The performance of the conventional PI controller, the fuzzy logic PI (FLPI) controller and fuzzy logic PI with feedforward (FLPIF) controller is validated. The presented results indicated that the FLPI controller significantly improves the dynamic response of hydrogen pressure compared to the PI controller, and the FLPIF controller can further reduce overshoot caused by disturbance. Finally, the proposed FLPIF controller is implemented on a rapid prototype platform of the hydrogen supply subsystem and an actual fuel cell system, exhibiting satisfactory performance.     

Facile access to carboxyl-terminated polybutadiene and polyethylene from cis-polybutadiene rubber

Carboxyl-terminated polybutadiene (CTPB) is a widely used telechelic liquid rubber, which is mainly prepared by anionic or free-radical polymerization of 1,3-butadiene. It is known that the microstructure of liquid polybutadiene rubber largely affects its processability and mechanical properties. However, it is hard to control its microstructure in the free radical or anionic polymerization. In this study, a series of CTPB with high cis-1,4 content has been prepared for the first time via the oxidolysis and selective oxidation of cis-polybutadiene rubber (BR). Hydrogenation of their CC double bonds with p-toluenesulfonyl hydrazide/tri-n-propylamine (TSH/TPA) reagents afforded carboxyl-terminated polyethylenes (CTPE). For comparison, commercial CTPB (FCTPB), prepared by free-radical polymerization of 1,3-butadiene, was also hydrogenated and gave FCTPE with more ethyl branches. Linear CTPE (L-CTPE) was synthesized by ring-opening metathesis polymerization of 1,5-cyclooctadiene in the presence of maleic acid and subsequent hydrogenation. The microstructure of the polymers was established by FT-IR, ¹H NMR, ¹³C NMR, and GPC and their thermal properties were determined by DSC and TGA. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 46934.     

Remarkable Antibacterial Activity of Reduced Graphene Oxide Functionalized by Copper Ions

Despite long-term efforts for exploring antibacterial agents or drugs, potentiating antibacterial activity and meanwhile minimizing toxicity to the environment remains a challenge. Here, it is experimentally shown that the functionality of reduced graphene oxide (rGO) through copper ions displays selective antibacterial activity that is significantly stronger than that of rGO itself and no toxicity to mammalian cells. Remarkably, this antibacterial activity is two-orders-of-magnitude greater than the activity of its surrounding copper ions. It is demonstrated that rGO is functionalized through the cation–π interaction to massively adsorb copper ions to form a rGO–copper composite and result in an extremely low concentration level of surrounding copper ions (less than ≈0.5 µm ). These copper ions on rGO are positively charged and strongly interact with negatively charged bacterial cells to selectively achieve antibacterial activity, while rGO exhibits the functionality to not only actuate rapid delivery of copper ions and massive assembly onto bacterial cells but also result in the valence shift in the copper ions from Cu²⁺ into Cu⁺, which greatly enhances the antibacterial activity. Notably, this rGO functionality through cation–π interaction with copper ions can similarly achieve algaecidal activity but does not exert cytotoxicity against neutrally charged mammalian cells.     

Distant Supervised Relation Extraction with Cost-Sensitive Loss

Recently, many researchers have concentrated on distant supervision relation extraction (DSRE). DSRE has solved the problem of the lack of data for supervised learning, however, the data automatically labeled by DSRE has a serious problem, which is class imbalance. The data from the majority class obviously dominates the dataset, in this case, most neural network classifiers will have a strong bias towards the majority class, so they cannot correctly classify the minority class. Studies have shown that the degree of separability between classes greatly determines the performance of imbalanced data. Therefore, in this paper we propose a novel model, which combines class-to-class separability and cost-sensitive learning to adjust the maximum reachable cost of misclassification, thus improving the performance of imbalanced data sets under distant supervision. Experiments have shown that our method is more effective for DSRE than baseline methods.     

吐哈盆地葡北地区“两宽一高”地震勘探技术及应用效果

吐哈盆地台北凹陷圈闭落实的准确度和储层分布预测的精度一直是制约该区油气发现的关键因素。通过可控震源“两宽一高”地震采集、OVT域时间偏移、地质导向深度偏移初始模型建立及各向异性深度偏移迭代处理，在地震资料的信噪比、频带宽度和分辨率等方面明显提高的基础上，以高精度层序地层学为指导，基于高分辨率地震资料与钻井、测井资料的综合分析，识别出侏罗系6个三级层序，在三级层序格架内将研究区七克台组底部和三间房组顶部砂体识别为两个连续上升半旋回四级层序；通过构造几何属性分析及精细构造分析，揭示了本区“四带、两凹”的构造格局及形成机制；以宽频带多种反演技术为手段，对含油气层段的七克台组和三间房组砂体分布进行了预测；在综合构造分析、储层分析和油藏成藏规律分析的基础上，提出本区油气沿构造带脊线聚集，断裂系统是油气运移的优势路径，七克台组、三间房组储层在葡北构造带发育，向玉果构造带和胜北次凹减薄尖灭，葡北构造带与玉果构造带结合部位的，具有鼻状构造背景的岩性圈闭是获得油气突破的有利地区。