Integration of TGF-β-induced Smad signaling in the insulin-induced transcriptional response in endothelial cells.

Insulin signaling governs many processes including glucose homeostasis and metabolism, and is therapeutically used to treat hyperglycemia in diabetes. We demonstrated that insulin-induced Akt activation enhances the sensitivity to TGF-β by directing an increase in cell surface TGF-β receptors from a pool of intracellular TGF-β receptors. Consequently, increased autocrine TGF-β signaling in response to insulin participates in insulin-induced angiogenic responses of endothelial cells. With TGF-β signaling controlling many cell responses, including differentiation and extracellular matrix deposition, and pathologically promoting fibrosis and cancer cell dissemination, we addressed to which extent autocrine TGF-β signaling participates in insulin-induced gene responses of human endothelial cells. Transcriptome analyses of the insulin response, in the absence or presence of a TGF-β receptor kinase inhibitor, revealed substantial positive and negative contributions of autocrine TGF-β signaling in insulin-responsive gene responses. Furthermore, insulin-induced responses of many genes depended on or resulted from autocrine TGF-β signaling. Our analyses also highlight extensive contributions of autocrine TGF-β signaling to basal gene expression in the absence of insulin, and identified many novel TGF-β-responsive genes. This data resource may aid in the appreciation of the roles of autocrine TGF-β signaling in normal physiological responses to insulin, and implications of therapeutic insulin usage

A Nested Attention Neural Hybrid Model for Grammatical Error Correction

Grammatical error correction (GEC) systems strive to correct both global errors in word order and usage, and local errors in spelling and inflection. Further developing upon recent work on neural machine translation, we propose a new hybrid neural model with nested attention layers for GEC. Experiments show that the new model can effectively correct errors of both types by incorporating word and character-level information,and that the model significantly outperforms previous neural models for GEC as measured on the standard CoNLL-14 benchmark dataset. Further analysis also shows that the superiority of the proposed model can be largely attributed to the use of the nested attention mechanism, which has proven particularly effective in correcting local errors that involve small edits in orthography

Which phonetic features should pronunciation Instructions focus on? An evaluation on the accentedness of segmental/syllable errors in L2 speech

Many English language instructors are reluctant to incorporate pronunciation instruction into their teaching curriculum (Thomson 2014). One reason for such reluctance is that L2 pronunciation errors are numerous, and there is not enough time for teachers to address all of them (Munro and Derwing 2006; Thomson 2014). The current study aims to help language teachers set priorities for their instruction by identifying the segmental and structural aspects of pronunciation that are most foreign-accented to native speakers of American English. The current study employed a perception experiment. 100 speech samples selected from the Speech Accent Archive (Weinberger 2016) were presented to 110 native American English listeners who listened to and rated the foreign accentedness of each sample on a 9-point rating scale. 20 of these samples portray no segmental or syllable structure L2 errors. The other 80 samples contain a single consonant, vowel, or syllable structure L2 error. The backgrounds of the speakers of these samples came from 52 different native languages. Global prosody of each sample was controlled for by comparing its F0 contour and duration to a native English sample using the Dynamic Time Warping method (Giorgino 2009). The results show that 1) L2 consonant errors in general are judged to be more accented than vowel or syllable structure errors; 2) phonological environment affects accent perception, 3) occurrences of non-English consonants always lead to higher accentedness ratings; 4) among L2 syllable errors, vowel epenthesis is judged to be as accented as consonant substitutions, while deletion is judged to be less accented or not accented at all. The current study, therefore, recommends that language instructors attend to consonant errors in L2 speech while taking into consideration their respective phonological environments

Dual-polarized broad-band microstrip antennas fed by proximity coupling

A novel antenna structure for dual polarisation is proposed. Advantages over previous structures include simplicity, broad bandwidth, high isolation between ports and low cross-polarization. The antenna design is readily suited to use as an array element and therefore has potential for use in a variety of practical applications. The work was supported in part by EPSRC grant GR/S42538/01

A planar integrated folded reflectarray antenna with circular polarization

This communication presents the complete design of a circularly polarized (CP) folded reflectarray (FRA) antenna with an integrated planar structure for the first time in the open literature. To achieve circularly polarized, a printed meander-line polarizer is designed and integrated with the linearly polarized (LP) FRA. To achieve a low-profile planar structure, an integrated 2×2 planar array is designed as the feed source instead of a horn. Thus, the whole antenna, including the feed source, LPFRA, and meander-line polarizer, can be fully integrated and fabricated using low-cost printed circuit board technology. To validate the concept, a right-handed CPFRA operating in C-band is designed, fabricated, and measured. The broadside axial ratio (AR) of the proposed CPFRA is lower than 1 dB over a bandwidth from 5.22 to 5.46 GHz. In addition, the maximum gain of 22.8 dBic is obtained at 5.38 GHz with the antenna efficiency of 27%. The antenna is promising for applications in satellite communication due to advantages of low profile, easy fabrication, low cost, and high gain