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Previous captioning methods only rely on semantic-level information considering the similarity of features between image regions in visual space and ignoring the linguistic context incorporated in the decoder for caption generation. In this paper, a transformer-based co-attention network is proposed which uses linguistic information to capture the pairwise visual relationships among objects and significant visual features. We infer the entity words from the visual content of objects, during the caption generation process. Also, we infer the interactive words by focusing on the relationship between entity words, based on the relational context between words generated in the course of caption decoding. We use linguistic contextual information as a guiding force to discover the relationships between objects efficiently. Further, we capture both intra-modal and inter-modal interactions using the multilevel co-attention network. Our model attains 44.1/33.6 BLEU@4, 30.8/25.1 METEOR, 61.9/55.1 ROUGE, 132.1/69.8 CIDEr, and 24.1/17.8 SPICE scores on MSCOCO and Flickr30k datasets, respectively. [ABSTRACT FROM AUTHOR]

This forum takes up the question of how to do work in Historical International Relations (IR). Especially in the past decade, scholars have debated what modes of analysis are best suited to this sort of work and how Historical IR relates to the disciplines of History and International Relations. The contributors to this forum intervene in these debates and converge on three issues facing Historical IR—questions of methods, ontology, and disciplinary boundaries. We outline the convergences and differences among the contributors on those points in this introduction, and we conclude by offering a definition of Historical IR in an effort to clarify its position within the discipline of IR. [ABSTRACT FROM AUTHOR]

Scene Text Visual Question Answering (VQA) needs to understand both the visual contents and the texts in an image to predict an answer for the image-related question. Existing Scene Text VQA models predict an answer by choosing a word from a fixed vocabulary or the extracted text tokens. In this paper, we have strengthened the representation power of the text tokens by using FastText embedding, appearance, bounding box and PHOC features for text tokens. Our model employs two-way co-attention by using self-attention and guided attention mechanisms to obtain the discriminative image features. We compute the text token position and combine this information with the predicted answer embedding for final answer generation. We have achieved an accuracy of 51.27% and 52.09% on the TextVQA validation set and test set. For the ST-VQA dataset, our model predicted an ANLS score of 0.698 on validation set and 0.686 on test set. [ABSTRACT FROM AUTHOR]

Photoperiod is the most consistent environmental cue, and therefore, any change in anticipated light environment may affect subsequent response under long days. To test this hypothesis, photosensitive migratory redheaded buntings (Emberiza bruniceps) were exposed to altered photoperiods for 4 weeks [short days (SP, 8L:16D, group 1; control), short days alternated with constant dim light (SP/LLdim; group 2), constant dim light (LLdim; group 3) and constant bright light (LLbright; group 4)] before being transferred to long days (LP; 16L:8D) for 15 weeks. Group differences in long-day-induced responses were observed. The onset of migratory restlessness (Zugunruhe) was earliest in LLbrightbut persisted for maximum period in LLdimgroup. The LLdimgroup attained peak testis size significantly delayed and had more food consumption under long days. The results suggest that the altered photoperiodic exposure during photosensitive stage affects the seasonal phenotypes such as migration and reproduction in migratory buntings. [ABSTRACT FROM PUBLISHER]

In this study, we report the enhanced osteoblast differentiation of mouse embryonic stem cell (mESC) on a novel polygalacturonic acid (PGA)/gelatin scaffold. The matrices of various PGA/geletin ratios were fabricated, biophysically characterized, and optimized for cell culture applications. Blended 2% PGA/gelatin scaffolds were highly porous and were robust with enhanced mechanical strength. Swelling studies showed they had high swelling capacity (six-fold higher than only gelatin scaffold) along with complete degradation in the presence of phosphate-buffered saline. Cytocompatibility of the matrices was evaluated using mouse fibroblast 3T3-L1 cell line showing normal spreading and proliferation as assessed by scanning electron microscopy (SEM) and MTT assay. Among different blends of PGA/gelatin, 2% PGA/gelatin (2PG) scaffold showed the optimum physical and biological compatibility for use in cell culture and differentiation of mESC, especially for osteoblast differentiation. The scaffold, as reported in this study, presents a promising tool for tissue engineering applications. [ABSTRACT FROM PUBLISHER]