Evaluating the effectiveness of automatic image captioning for web accessibility

The web has become a fundamental tool for carrying out many activities spanning from education to work and private life. For this reason, it must be accessible to every user regardless of any form of impairment or disability. Images on the web are a primary means for communicating information, and specific HTML elements were defined to enrich images with textual descriptions, which can be read aloud by screen readers or rendered by braille displays. A relevant problem is that adding a text describing each image published on a website is a demanding task requiring a non-negligible effort for web developers. Several tools based on machine learning have emerged, which can automatically return descriptions for the images. In this work, we evaluate the correctness of their outputs by comparing the generated descriptions with human-defined references. More specifically, we selected 60 images from Wikipedia and their corresponding descriptions as defined by Wikipedia contributors. We then generated the corresponding descriptions employing four state of the art tools (Azure Computer Vision Engine, Amazon Rekognition, Cloudsight, and Auto Alt-Text for Google Chrome) and asked 76 computer science students to blindly evaluate the perceived correctness of the descriptions without being aware of their source. The results show that the descriptions available in Wikipedia are still perceived as the best ones. However, some tools generate good results for specific categories of images, and they can represent proper candidates for the automated and massive addition of image descriptions to websites, helping to increase the accessibility level of the web drastically

Molecular recognition of carbonyl compounds by uranyl-salophen based neutral receptors driven by Van der Waals forces

The complexation of the salophen-uranyl metallocleft 2 and of its half-cleft analogue 3 with enones and other carbonyl compounds was assessed in chloroform by UV-Vis titration and, occasionally, by FT-IR measurements. Complexes with receptors 2 and 3 are in all cases more stable than those with the control unsubstituted uranyl-salophen 1 , showing that in addition to the primary binding force provided by coordination of the carbonyl oxygen to the uranium, a significant driving force for complexation, typically in the range of 2-3 kcal/mol, results from van der Waals interactions of the guest with the aromatic walls. Replacement of the phenyl group in 3 with larger aromatic residues to give 4 and 5 , led to enhanced complex stabilities, due to more extended contact surfaces between host and guest

Phosphorus Functionalized Dendrimers and Hyperbranched Polymers: Is There a Need for Perfect Dendrimers in Catalysis?

In this paper we describe the facile and straightforward covalent functionalization of commercially available dendritic poly(propylenimine) and hyperbranched poly(ethylenimine) with P-containing functional groups. The P-functionalized macromolecules have been applied as multivalent ligands in the Pd-catalyzed allylic substitution reactions (batch and continuous process) using either morpholine or thiophenol as nucleophile. Palladium complexes of all described molecules are active in allylic substitution reactions. The PEI functionalized polymers appear more sensitive to small changes in the P/Pd ratio than the PPI analogues, but form catalysts that are more active. When used in a continuous flow process the macromolecules are completely retained by the nanofiltration membrane, while the catalytic activity decreases with time because of palladium depletion. This is more severe for the allylic thiolation, probably because of the stronger affinity of sulfur for palladium, facilitating palladium leaching