Preparation of Kaolin Composites and Its Adsorption for Sb(Ⅲ)

Antimony is an important element in the production of flame retardants and semiconductor materials. In the process of antimony mining, it may cause local environmental pollution, which has adverse effects on human health, and the development of economical and efficient adsorbents to remove antimony from wastewater has become a hot research topic. In this paper, the hydrothermal synthesis method was adopted, and purified Kaolin was selected as the carrier, potassium permanganate, manganese chloride and ferric chloride are the metal sources, urea is the precipitant, and sodium dodecyl benzene sulfonate is the structure guide agent. Under the conditions of 5% mass fraction of dispersant, loading temperature of 140 ℃, reaction time of 8 h, mass ratio of iron to manganese of 1.84:1, and mass of precipitant of 0.9 g, the composites prepared were effective in adsorbing the Sb(Ⅲ) from the wastewater. The optimum adsorption efficiency of the prepared composites on Sb(Ⅲ) is 92.83%, which showed excellent adsorption performance

Coupling Global Context and Local Contents for Weakly-Supervised Semantic Segmentation

Thanks to the advantages of the friendly annotations and the satisfactory performance, Weakly-Supervised Semantic Segmentation (WSSS) approaches have been extensively studied. Recently, the single-stage WSSS was awakened to alleviate problems of the expensive computational costs and the complicated training procedures in multi-stage WSSS. However, results of such an immature model suffer from problems of \emph{background incompleteness} and \emph{object incompleteness}. We empirically find that they are caused by the insufficiency of the global object context and the lack of the local regional contents, respectively. Under these observations, we propose a single-stage WSSS model with only the image-level class label supervisions, termed as \textbf{W}eakly-\textbf{S}upervised \textbf{F}eature \textbf{C}oupling \textbf{N}etwork (\textbf{WS-FCN}), which can capture the multi-scale context formed from the adjacent feature grids, and encode the fine-grained spatial information from the low-level features into the high-level ones. Specifically, a flexible context aggregation module is proposed to capture the global object context in different granular spaces. Besides, a semantically consistent feature fusion module is proposed in a bottom-up parameter-learnable fashion to aggregate the fine-grained local contents. Based on these two modules, \textbf{WS-FCN} lies in a self-supervised end-to-end training fashion. Extensive experimental results on the challenging PASCAL VOC 2012 and MS COCO 2014 demonstrate the effectiveness and efficiency of \textbf{WS-FCN}, which can achieve state-of-the-art results by $65.02\%$ and $64.22\%$ mIoU on PASCAL VOC 2012 \emph{val} set and \emph{test} set, $34.12\%$ mIoU on MS COCO 2014 \emph{val} set, respectively. The code and weight have been released at:~\href{https://github.com/ChunyanWang1/ws-fcn}{WS-FCN}.Comment: accepted by TNNL

El estudio sobre los logros y la experiencia básica de los 40 años de la reforma y apertura de China.

Resumen: en 1978, marcado por la Tercera Sesión Plenaria del XI Comité Central, China se embarcó en un viaje histórico de reforma y apertura y exploración del socialismo con características chinas. En los últimos 40 años, la reforma y apertura de China ha logrado logros de renombre mundial. La fuerza nacional general y el nivel de vida de las personas han mejorado enormemente. China se ha situado en el centro del escenario mundial a un nivel sin precedentes. Como señaló el presidente Xi Jinping en la reunión para conmemorar el 150 aniversario del nacimiento del Sr. Sun Yat-sen, China está más cerca del objetivo de lograr el gran rejuvenecimiento de la nación china que en cualquier otro momento de la historia, "Tomando la historia como espejo para conocer el ascenso y la caída". En el contexto macro de que el socialismo con características chinas ha entrado en una nueva era, estudiar en profundidad la práctica de la reforma y apertura de China, clasificar los logros de la reforma y la apertura, resumir profundamente la experiencia básica de reforma y apertura y plantear algunas reflexiones sobre la promoción continua de la reforma y apertura, todo esto no solo tiene un profundo valor teórico para la profundización integral de la reforma, sino que también tiene una gran importancia orientadora práctica.<br /

Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand

An optimization approach for designing a transit service system is proposed. Its objective would be the maximization of total social welfare, by providing a profitable fare structure and tailoring operational strategies to passenger demand. These operational strategies include full route operation (FRO), limited stop, short turn, and a mix of the latter two strategies. The demand function is formulated to reflect the attributes of these strategies, in-vehicle crowding, and fare effects on demand variation. The fare is either a flat fare or a differential fare structure; the latter is based on trip distance and achieved service levels. This proposed methodology is applied to a case study of Dalian, China. The optimal results indicate that an optimal combination of operational strategies integrated with a differential fare structure results in the highest potential for increasing total social welfare, if the value of parameter "mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"""mml:mrow""mml:mi"ε"/mml:mi""/mml:mrow""/mml:math" related to additional service fee is low. When this value increases up to more than a threshold, strategies with a flat fare show greater benefits. If this value increases beyond yet another threshold, the use of skipped stop strategies is not recommended. Document type: Articl

Reinforced degradation of ibuprofen with MnCo2O4/FCNTs nanocatalyst as peroxymonosulfate activator : Performance and mechanism

In order to efficiently degrade ibuprofen (IBU) by peroxymonosulfate (PMS) activation, manganese cobalt oxide nanoparticles-decorated functionalized multi-walled carbon nanotubes (MnCo2O4/FCNTs) were prepared using a facile hydrothermal method. Comprehensive characterization of this PMS activator in multi-scale suggested that MnCo2O4 nanoparticles were uniformly decorated on FCNTs. The catalytic performance was systematical evaluated under various environmental conditions, including temperature, pH, and the presence of different common water matrix species (e.g., Cl-, HCO3-, and natural organic matter). The as-synthesized MnCo2O4/FCNTs demonstrated excellent catalytic activity with kapp ranging 0.285-0.327 min-1 under a wide pH range of 3-9 within 10 min, which achieved a complete removal of IBU and a mineralization rate higher than 90%. During oxidation process for stability and reusability test, recycled MnCo2O4/FCNTs was found durable with negligible leaching of metal ions from spent catalyst, exhibiting its high stability for PMS activation with merely slight decrease of kapp from 0.285 to 0.201 min-1 in the fourth cycle. Electron paramagnetic resonance analysis further confirmed that •OH, SO4•- and 1O2 were generated in the robust MnCo2O4/FCNTs-PMS system. Both radical and nonradical reactions were found to be responsible for the enhanced IBU degradation. Overall, this study sheds light on practical knowledge of IBU removal using MnCo2O4/FCNTs for PMS activation.publishedVersionPeer reviewe

Foreground Segmentation in Video Sequences with a Dynamic Background

Segmentation of a moving foreground from video sequences, in the presence of a rapidly changing background, is a difficult problem. In this paper, a novel technique for an effective segmentation of the moving foreground from video sequences with a dynamic background is developed. The segmentation problem is treated as a problem of classifying the foreground and background pixels of a video frame using the color components of the pixels as multiple features of the images. The gray levels of the pixels and the hue and saturation level components in the HSV representation of the pixels of a frame are used to form a scalar-valued feature image. This feature image incorporating multiple features of the pixels is then used to devise a simple classification scheme in the framework of a support vector machine classifier. Unlike some other data classification approaches for foreground segmentation in which a priori knowledge of the shape and size of the moving foreground is essential, in the proposed method, training samples are obtained in an automatic manner. In order to assess the effectiveness of the proposed method, the new scheme is applied to a number of video sequences with a dynamic background and the results are compared with those obtained by using other existing methods. The subjective and objective results show the superiority of the proposed scheme in providing a segmented foreground binary mask that fits more closely with the corresponding ground truth mask than those obtained by the other methods do