The Influence of Fiber on the Mechanical Properties of Geopolymer Concrete: A Review.

Geopolymer is widely used as a supplement to cementitious composites because of its advantages of low carbon and environmental protection, and geopolymer concrete is also broadly used in practical engineering. In recent years, geopolymer concrete has attracted increasing interest owing to its superior mechanical properties, and a series of research results have been obtained. In this paper, from the preparation of geopolymer concrete, based on the characteristics that geopolymer concrete is brittle and easy to crack, the types and basic properties of fibers to enhance the toughness of concrete are analyzed, the advantages and disadvantages of different fibers used as a material to enhance the toughness of concrete are summarized, and we review the effects of type, shape, volume rate, aspect ratio, and hybrid fiber combinations on the static mechanical properties. The results indicate that fibers have significant potential to enhance the compressive strength, splitting tensile strength, flexural strength, and fracture toughness of geopolymer concrete, and the optimal fiber volume rate seems to be related to the fiber type. Whereas the effect of aspect ratio and hybrid fiber combinations on the properties of geopolymer concrete seems to be obvious. This paper reviews the influence of fiber on the basic mechanical properties of geopolymer concrete, which provides a solid foundation to promote the further development and application of the research on the toughness of fiber-reinforced geopolymer concrete and provides recommendations for future research.

Electrochemical detection mechanism of estrogen effect induced by cadmium: The regulation of purine metabolism by the estrogen effect of cadmium.

Some heavy metals in the environment may have estrogen-like activity, which probably lead to major diseases such as breast cancer. It is of great importance to establish new methods to evaluate the estrogen effect of heavy metals from multiple angles due to the complex mechanism of estrogen effect. In this paper, using MCF-7 cells as model, the electrochemical detection mechanism of the estrogen effect of heavy metal cadmium (Cd) was studied. The two electrochemical signals of MCF-7 cells derived from uric acid (0.30 V) and the mixture of guanine and xanthine (0.68 V) increased in a time and dose-dependent manner when MCF-7 cells induced by Cd, reaching the maximum at 96 h and 10-9 mol L-1. Further studies found that three purine metabolism pathways about de novo synthesis, salvage synthesis and decomposition metabolism were activated by the estrogen effect of Cd. The expression of PRPP amidotransferase in purine de novo synthesis pathway and HPRT in purine salvage synthesis pathway up-regulated, especially HPRT, which promoted cell proliferation together. Nevertheless, the expression of GDA and ADA, the key enzymes in purine decomposition metabolism pathway, up-regulated in a time and dose-dependent manner, which had same tendency with that of ERα, thereby increased the content of intracellular hypoxanthine, guanine, xanthine and uric acid, and enhanced electrochemical signals.

The response of electrochemical method to estrogen effect and the tolerance to culture factors: Comparison with MTT and cell counting methods.

Estrogen substances in the environment are increasing dramatically, which interfere with the normal hormone level of human body, lead to the disorder of endocrine system and even cancer. It is difficult to screen a large number of environmental estrogen substances by existing estrogen effect detection methods, and the results are often affected by many factors, thus the development of new method has become an urgent task. Electrochemical method is promising to reflect cell proliferation by tracking intracellular purine bases directly. In this study, the estrogen level in MCF-7 cells on multiwall carbon nanotubes modified glassy carbon electrode (MWCNTs/GCE) could be tracked simply and conveniently, and the estrogen effect of estradiol could be reflected by electrochemistry in time and dose-dependent manners. Electrochemical method displayed the best tolerance to culture factors, such as different cell densities, serum types, culture medium types and serum estrogen-free methods, which responsed to estrogen effect higher than MTT (about 40%) and cell counting methods (about 50%). Further Western blotting analysis showed that the estrogen effect of estradiol promoted purine catabolism and up-regulated guanine deaminase (GDA) and adenine deaminase (ADA) expression, the key enzymes of purine catabolism pathway, in a dose-dependent manner. The up-regulation of GDA and ADA led to the increase of intracellular guanine and xanthine, which enhanced the electrochemical signal derived from guanine and xanthine.

SSSIC: Semantics-to-Signal Scalable Image Coding With Learned Structural Representations.

We address the requirement of image coding for joint human-machine vision, i.e., the decoded image serves both human observation and machine analysis/understanding. Previously, human vision and machine vision have been extensively studied by image (signal) compression and (image) feature compression, respectively. Recently, for joint human-machine vision, several studies have been devoted to joint compression of images and features, but the correlation between images and features is still unclear. We identify the deep network as a powerful toolkit for generating structural image representations. From the perspective of information theory, the deep features of an image naturally form an entropy decreasing series: a scalable bitstream is achieved by compressing the features backward from a deeper layer to a shallower layer until culminating with the image signal. Moreover, we can obtain learned representations by training the deep network for a given semantic analysis task or multiple tasks and acquire deep features that are related to semantics. With the learned structural representations, we propose SSSIC, a framework to obtain an embedded bitstream that can be either partially decoded for semantic analysis or fully decoded for human vision. We implement an exemplar SSSIC scheme using coarse-to-fine image classification as the driven semantic analysis task. We also extend the scheme for object detection and instance segmentation tasks. The experimental results demonstrate the effectiveness of the proposed SSSIC framework and establish that the exemplar scheme achieves higher compression efficiency than separate compression of images and features.

Use of mitochondrial cytochrome oxidase I polymerase chain reaction-restriction fragment length polymorphism for identifying subclades of Bemisia tabaci Mediterranean group.

The Mediterranean group (commonly known as Q biotype; hereafter MED) of the sweetpotato whitefly, Bemisia tabaci (Gennadius), originated in the Mediterranean region, but it now has been found in at least 10 countries outside the Mediterranean. Collections of B. tabaci from some of these countries exhibit different pest behaviors and pesticide resistance characteristics, yet all may be classified as MED. A phylogenetic analysis of 120 mitochondrial cytochrome oxidase I (mtCOI) sequences (JN966761-JN966880) of MED whiteflies collected in Arizona and of 417 retrieved from the GenBank database resolves the MED into five subclades, designated as Q1-Q5. Only subclades Q1 and Q2 have been detected in the United States. Q1 and the other four subclades (Q2-Q5) differ in the number or position of the AluI recognition sites. Based on the differences in the AluI recognition sites reported here and the previously reported differences in VspI recognition sites, we developed a simple diagnostic technique to identify subclades Q1-Q5 by using mtCOI polymerase chain reaction (PCR)-restriction fragment-length polymorphism (RFLP). A test of a worldwide collection of whiteflies demonstrates that this combination mtCOIPCR-RFLP technique can reliably distinguish not only the MED from the Middle East-Asia Minor 1 group but also the Q1 from any of the other four MED subclades.