Study of cement-fly ash paste exposed to sodium sulfate solutions with different concentrations at different temperatures

When concrete elements are partially exposed to sulfate environment, in the upper part of concrete elements above ground an aquiferous zone containing almost saturated and high pH value (> 12.5) sulfate pore solution will be formed. The concentration of sulfate solution is much higher than 5 %, as usually used in laboratory. It is necessary to study the performance of cement-fly ash paste in different high concentration sulfate solutions at different temperatures. In this paper, pure cement paste and cement - fly ash (25 % dosage) paste specimens were immersed in the 5 %, 15 %, 20 %, 30 %, 40 % and 50 % sodium solutions at 20°C, 30°C and 40°C respectively. After 1, 3 and 6 months immersion, the compressive strength of the specimens was measured. XRD and thermal analysis were employed to analyze the reactive products of the paste. The experimental results show that the reactive aluminum in fly ash is activated by high concentration sodium sulfate solution at different temperatures and more ettringite is generated than pure cement paste

Human excreta as a stable and important source of atmospheric ammonia in the megacity of Shanghai

Although human excreta as a NH3 source has been recognized globally, this source has never been quantitatively determined in cities, hampering efforts to fully assess the causes of urban air pollution. In the present study, the exhausts of 15 ceiling ducts from collecting septic tanks in 13 buildings with 6 function types were selected to quantify NH3 emission rates in the megacity of Shanghai. As a comparison, the ambient NH3 concentrations across Shanghai were also measured at 13 atmospheric monitoring sites. The concentrations of NH3 in the ceiling ducts (2809 μg m-3) outweigh those of the open air (~10 μg m-3) by 2–3 orders of magnitude, and there is no significant difference between different seasons. δ15N values of NH3 emitted from two ceiling ducts are also seasonally consistent, suggesting that human excreta may be a stable source of NH3 in urban areas. The NH3 concentration levels were variable and dependent on the different building types and the level of human activity. NH3 emission rates of the six residential buildings (RBNH3) were in agreement with each other. Taking occupation time into account, we confined the range of the average NH3 emission factor for human excreta to be 2–4 times (with the best estimate of 3 times) of the averaged RBNH3 of 66.0±58.9 g NH3 capita-1 yr-1. With this emission factor, the population of ~21 million people living in the urban areas of Shanghai annually emitted approximately 1386 Mg NH3, which corresponds to over 11.4% of the total NH3 emissions in the Shanghai urban areas. The spatial distribution of NH3 emissions from human excreta based on population data was calculated for the city of Shanghai at a high-resolution (100×100 m). Our results demonstrate that human excreta should be included in official ammonia emission inventories

Assessing contributions of agricultural and nonagricultural emissions to atmospheric ammonia in a Chinese megacity

Ammonia (NH3) is the predominant alkaline gas in the atmosphere contributing to formation of fine particles—a leading environmental cause of increased morbidity and mortality worldwide. Prior findings suggest that NH3 in the urban atmosphere derives from a complex mixture of agricultural (mainly livestock production and fertilizer application) and nonagricultural (e.g., urban waste, fossil fuel-related emissions) sources; however, a citywide holistic assessment is hitherto lacking. Here we show that NH3 from nonagricultural sources rivals agricultural NH3 source contributions in the Shanghai urban atmosphere. We base our conclusion on four independent approaches: (i) a full-year operation of a passive NH3 monitoring network at 14 locations covering urban, suburban, and rural landscapes; (ii) model-measurement comparison of hourly NH3 concentrations at a pair of urban and rural supersites; (iii) source-specific NH3 measurements from emission sources; and (iv) localized isotopic signatures of NH3 sources integrated in a Bayesian isotope mixing model to make isotope-based source apportionment estimates of ambient NH3. Results indicate that nonagricultural sources and agricultural sources are both important contributors to NH3 in the urban atmosphere. These findings highlight opportunities to limit NH3 emissions from nonagricultural sources to help curb PM2.5 pollution in urban China

Software for doing computations in graded Lie algebras

We introduce the Macaulay2 package GradedLieAlgebras for doing computations in graded Lie algebras presented by generators and relations.Comment: 5 page

A flexible and accurate total variation and cascaded denoisers-based image reconstruction algorithm for hyperspectrally compressed ultrafast photography

Hyperspectrally compressed ultrafast photography (HCUP) based on compressed sensing and the time- and spectrum-to-space mappings can simultaneously realize the temporal and spectral imaging of non-repeatable or difficult-to-repeat transient events passively in a single exposure. It possesses an incredibly high frame rate of tens of trillions of frames per second and a sequence depth of several hundred, and plays a revolutionary role in single-shot ultrafast optical imaging. However, due to the ultra-high data compression ratio induced by the extremely large sequence depth as well as the limited fidelities of traditional reconstruction algorithms over the reconstruction process, HCUP suffers from a poor image reconstruction quality and fails to capture fine structures in complex transient scenes. To overcome these restrictions, we propose a flexible image reconstruction algorithm based on the total variation (TV) and cascaded denoisers (CD) for HCUP, named the TV-CD algorithm. It applies the TV denoising model cascaded with several advanced deep learning-based denoising models in the iterative plug-and-play alternating direction method of multipliers framework, which can preserve the image smoothness while utilizing the deep denoising networks to obtain more priori, and thus solving the common sparsity representation problem in local similarity and motion compensation. Both simulation and experimental results show that the proposed TV-CD algorithm can effectively improve the image reconstruction accuracy and quality of HCUP, and further promote the practical applications of HCUP in capturing high-dimensional complex physical, chemical and biological ultrafast optical scenes.Comment: 25 pages, 5 figures and 1 tabl

Exosomal miRNAs in autoimmune skin diseases

Exosomes, bilaterally phospholipid-coated small vesicles, are produced and released by nearly all cells, which comprise diverse biological macromolecules, including proteins, DNA, RNA, and others, that participate in the regulation of their biological functions. An increasing number of studies have revealed that the contents of exosomes, particularly microRNA(miRNA), play a significant role in the pathogenesis of various diseases, including autoimmune skin diseases. MiRNA is a class of single-stranded non-coding RNA molecules that possess approximately 22 nucleotides in length with the capability of binding to the untranslated as well as coding regions of target mRNA to regulate gene expression precisely at the post-transcriptional level. Various exosomal miRNAs have been found to be significantly expressed in some autoimmune skin diseases and involved in the pathogenesis of conditions via regulating the secretion of crucial pathogenic cytokines and the direction of immune cell differentiation. Thus, exosomal miRNAs might be promising biomarkers for monitoring disease progression, relapse and reflection to treatment based on their functions and changes. This review summarized the current studies on exosomal miRNAs in several common autoimmune skin diseases, aiming to dissect the underlying mechanism from a new perspective, seek novel biomarkers for disease monitoring and lay the foundation for developing innovative target therapy in the future

Heat diffusion based dynamic load balancing for distributed virtual environments

Distributed virtual environments (DVEs) are becoming very popular in recent years, due to their application in online gaming and social networking.One of the main research problems in DVEs is on how to balance the workload when a lot of concurrent users are accessing it. There are a number of load balancing methods proposed to address this problem. However, they either spend too much time on optimizing the partitioning process and become too slow or emphasize on efficiency and the repartitioning process becomes too ineffective. In this paper, we propose a new dynamic load balancing approach for DVEs based on the heat diffusion approach which has been studied in other areas and proved to be very effective and efficient for dynamic load balancing. We have two main contributions. First, we propose an efficient cell selection scheme to identify and select appropriate cells for load migration. Second, we propose two heat diffusion based load balancing algorithms, local and global diffusion. Our results show that the new algorithms are both efficient and effective compared with some existing methods, and the global diffusion method performs the best

Quantitative Assessment of Variational Surface Reconstruction from Sparse Point Clouds in Freehand 3D Ultrasound Imaging during Image-Guided Tumor Ablation

Surface reconstruction for freehand 3D ultrasound is used to provide 3D visualization of a VOI (volume of interest) during image-guided tumor ablation surgery. This is a challenge because the recorded 2D B-scans are not only sparse but also non-parallel. To solve this issue, we established a framework to reconstruct the surface of freehand 3D ultrasound imaging in 2011. The key technique for surface reconstruction in that framework is based on variational interpolation presented by Greg Turk for shape transformation and is named Variational Surface Reconstruction (VSR). The main goal of this paper is to evaluate the quality of surface reconstructions, especially when the input data are extremely sparse point clouds from freehand 3D ultrasound imaging, using four methods: Ball Pivoting, Power Crust, Poisson, and VSR. Four experiments are conducted, and quantitative metrics, such as the Hausdorff distance, are introduced for quantitative assessment. The experiment results show that the performance of the proposed VSR method is the best of the four methods at reconstructing surface from sparse data. The VSR method can produce a close approximation to the original surface from as few as two contours, whereas the other three methods fail to do so. The experiment results also illustrate that the reproducibility of the VSR method is the best of the four methods