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Anti-microbial cationic wood nanofiber films exhibiting high visible light transparency and UV-blocking ability together with good mechanical and oxygen barrier properties were produced directly from sawdust.

This paper democratizes neural information retrieval to scenarios where large scale relevance training signals are not available. We revisit the classic IR intuition that anchor-document relations approximate query-document relevance and propose a reinforcement weak supervision selection method, ReInfoSelect, which learns to select anchor-document pairs that best weakly supervise the neural ranker (action), using the ranking performance on a handful of relevance labels as the reward. Iteratively, for a batch of anchor-document pairs, ReInfoSelect back propagates the gradients through the neural ranker, gathers its NDCG reward, and optimizes the data selection network using policy gradients, until the neural ranker's performance peaks on target relevance metrics (convergence). In our experiments on three TREC benchmarks, neural rankers trained by ReInfoSelect, with only publicly available anchor data, significantly outperform feature-based learning to rank methods and match the effectiveness of neural rankers trained with private commercial search logs. Our analyses show that ReInfoSelect effectively selects weak supervision signals based on the stage of the neural ranker training, and intuitively picks anchor-document pairs similar to query-document pairs.

In the present study, interfacial complexation spinning of oppositely charged cellulose-materials is applied to fabricate hierarchical and continuous nanocellulose based filaments under aqueous conditions by using cationic cellulose nanocrystals with different anionic celluloses including soluble sodium carboxymethyl cellulose and insoluble 2,2,6,6-tetramethylpiperidinyl-1-oxy radical-oxidized cellulose nanofibers and dicarboxylated cellulose nanocrystals (DC-CNC). The morphologies of the wet and dry nanocellulose based filaments are further investigated by optical and electron microscopy. All fabricated continuous nanocellulose based filaments display a hierarchical structure similar to the natural cellulose fibers in plant cells. As far as it is known, this is not only the first report about the fabrication of nanocellulose based filaments by interfacial complexation of cationic CNCs with anionic celluloses but also the first demonstration of fabricating continuous fibers directly from oppositely charged nanoparticles by interfacial nanoparticle complexation (INC). This INC approach may provide a new route to design continuous filaments from many other oppositely charged nanoparticles with tailored characteristics.

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