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BACKGROUND Waxy maize is grown in South China, where high temperatures frequently prevail. The effect of high-temperature stress on grain development of waxy maize is not known. RESULTS High temperature decreased the grain fresh weight and volume, and lowered the grain dry weight and water content after 22 days after pollination (DAP). Plants exposed to high temperature had low starch content, and high protein and soluble sugar contents at maturity. Starch iodine binding capacity and granule size were increased by heat stress at all grain-filling stages. The former parameter decreased, while the latter parameter increased gradually with grain development. High temperature increased the peak and breakdown viscosity before 30 DAP, but the value decreased at maturity. Pasting and gelatinization temperatures at different stages were increased by heat stress and gradually decreased with grain development under both high-temperature and control conditions. Gelatinization enthalpy increased initially but decreased after peaking at 22 DAP under both control and heat stress conditions. High temperature decreased gelatinization enthalpy after 10 DAP. Retrogradation percentage value increased with high temperature throughout grain development. CONCLUSION High temperature after pollination changes the dynamics of grain filling of waxy maize, which may underlie the observed changes in its pasting and thermal properties. © 2013 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Effects of heat stress (mean day/night temperatures of 35.2/16.1 and 27.4/15.6°C for heat stress and control, respectively) during different grain‐filling phases (1–10, 11–20, 21–30, 31–40, and 1–40 days after pollination [DAP]) on the grain yield and quality of waxy maize were investigated using two varieties. Heat stress decreased the number and weight of grains, thereby reducing grain yield. The effects of heat stress at an early grain development stage (before 20 DAP) were severe. Compared with the control, starch deposition was not affected by heat stress in Suyunuo5, and it was only decreased by heat stress at 1–10 DAP in Yunuo7. Protein content responses to heat stress were variety and stage dependent. Heat stress increased the iodine‐binding capacities of both varieties. Peak and breakdown viscosities were decreased by heat stress, and the effects gradually decreased with postponement of high temperature. Heat stress increased gelatinization temperature and retrogradation percentage for both varieties, and the response was stage dependent. Heat stress during the whole grain‐filling period increased the pasting and gelatinization temperatures but decreased gelatinization enthalpy. Changes in protein and starch contents as well as the proportion of long chains in amylopectin affected the pasting and thermal properties. [ABSTRACT FROM AUTHOR]

In traditional machine learning, conditional random fields (CRF) is the mainstream probability model for sequence labeling problems. CRF considers the relation between adjacent labels other than decoding each label independently, and better performance is expected to achieve. However, there are few multi-view learning methods involving CRF which can be directly used for sequence labeling tasks. In this paper, we propose a novel multi-view CRF model to label sequential data, called MVCRF, which well exploits two principles for multi-view learning: consensus and complementary. We first use different neural networks to extract features from multiple views. Then, considering the consistency among the different views, we introduce a joint representation space for the extracted features and minimize the distance between the two views for regularization. Meanwhile, following the complementary principle, the features of multiple views are integrated into the framework of CRF. We train MVCRF in an end-to-end fashion and evaluate it on two benchmark data sets. The experimental results illustrate that MVCRF obtains state-of-the-art performance: F 1 score 95.44% for chunking on CoNLL-2000, 95.06% for chunking and 96.99% for named entity recognition (NER) on CoNLL-2003. • We propose a hybrid neural CRF for multi-view sequence labeling, called MVCRF. • Our model combines multi-view learning by utilizing consensus and complementary principles. • We systematically compare the performance of MVCRF with other models. • The experimental results show MVCRF achieves state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Clnk, as a third member of the Blnk/SLP-76 adapter family, is involved in the positive regulation of immunoreceptor signaling. Here we provide findings that Clnk may be is required for TNF induced cell death, it functions downstream of RIP3 and promotes TNF- induced ROS generation and MLKL tetramer formation and subsequent necrosis of L929 cells. Therefore, Clnk, as an adaptor protein, may take part in the other cellular processes. [ABSTRACT FROM AUTHOR]