Approximation Algorithms for Directed Weighted Spanners

In the pairwise weighted spanner problem, the input consists of an $n$-vertex-directed graph, where each edge is assigned a cost and a length. Given $k$ vertex pairs and a distance constraint for each pair, the goal is to find a minimum-cost subgraph in which the distance constraints are satisfied. This formulation captures many well-studied connectivity problems, including spanners, distance preservers, and Steiner forests. In the offline setting, we show: 1. An $\tilde{O}(n^{4/5 + \epsilon})$-approximation algorithm for pairwise weighted spanners. When the edges have unit costs and lengths, the best previous algorithm gives an $\tilde{O}(n^{3/5 + \epsilon})$-approximation, due to Chlamt\'a\v{c}, Dinitz, Kortsarz, and Laekhanukit (TALG, 2020). 2. An $\tilde{O}(n^{1/2+\epsilon})$-approximation algorithm for all-pair weighted distance preservers. When the edges have unit costs and arbitrary lengths, the best previous algorithm gives an $\tilde{O}(n^{1/2})$-approximation for all-pair spanners, due to Berman, Bhattacharyya, Makarychev, Raskhodnikova, and Yaroslavtsev (Information and Computation, 2013). In the online setting, we show: 1. An $\tilde{O}(k^{1/2 + \epsilon})$-competitive algorithm for pairwise weighted spanners. The state-of-the-art results are $\tilde{O}(n^{4/5})$-competitive when edges have unit costs and arbitrary lengths, and $\min\{\tilde{O}(k^{1/2 + \epsilon}), \tilde{O}(n^{2/3 + \epsilon})\}$-competitive when edges have unit costs and lengths, due to Grigorescu, Lin, and Quanrud (APPROX, 2021). 2. An $\tilde{O}(k^{\epsilon})$-competitive algorithm for single-source weighted spanners. Without distance constraints, this problem is equivalent to the directed Steiner tree problem. The best previous algorithm for online directed Steiner trees is $\tilde{O}(k^{\epsilon})$-competitive, due to Chakrabarty, Ene, Krishnaswamy, and Panigrahi (SICOMP, 2018)

CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet Extraction

Existing works on Aspect Sentiment Triplet Extraction (ASTE) explicitly focus on developing more efficient fine-tuning techniques for the task. Instead, our motivation is to come up with a generic approach that can improve the downstream performances of multiple ABSA tasks simultaneously. Towards this, we present CONTRASTE, a novel pre-training strategy using CONTRastive learning to enhance the ASTE performance. While we primarily focus on ASTE, we also demonstrate the advantage of our proposed technique on other ABSA tasks such as ACOS, TASD, and AESC. Given a sentence and its associated (aspect, opinion, sentiment) triplets, first, we design aspect-based prompts with corresponding sentiments masked. We then (pre)train an encoder-decoder model by applying contrastive learning on the decoder-generated aspect-aware sentiment representations of the masked terms. For fine-tuning the model weights thus obtained, we then propose a novel multi-task approach where the base encoder-decoder model is combined with two complementary modules, a tagging-based Opinion Term Detector, and a regression-based Triplet Count Estimator. Exhaustive experiments on four benchmark datasets and a detailed ablation study establish the importance of each of our proposed components as we achieve new state-of-the-art ASTE results.Comment: Accepted as a Long Paper at EMNLP 2023 (Findings); 16 pages; Codes: https://github.com/nitkannen/CONTRASTE

RECENT TRENDS IN MANAGEMENT OF KERATOCONJUNCTIVITIS SICCA (DRY EYE DISEASE)

At the air-water interface, the tear film lipid layer (TFLL), a combination of lipids and proteins plays an important role in surface tension of the tear and is necessary for the physiological hydration of the ocular surface and maintenance of ocular homeostasis. Alteration in lacrimal fluid rheology, differences in lipid constitution or down regulation of particular tear proteins are found in maximum types of ocular surface disease including dry eye disease (DED). Dry eye is a disorder of the tear film due to tear deficiency or excessive tear evaporation, which causes damage to the interpalpebral ocular surface and is associated with symptoms of discomfort. It results in changes on the ocular surface epithelia causing reduced tear quantity and surface sensitivity which leads to inflammation reactions. Managing this inflammation is very helpful in dry eye disease patients. In this article we revise the current understanding of tear film properties, ocular surface and review the effectiveness of topically applied tear supplements, thermo sensitive atelocollagen punctal plug, subtrasal ultrasonic transducers, novel liposome based gelling tear formation and insulin based ophthalmic delivery systems which help in restoring the healthy tear film

Recent Developments in Copper-Based Catalysts for Enhanced Electrochemical CO₂ Reduction

The drastic climate change imposing adverse environmental effects receives serious research attention for finding a suitable solution. The replacement of conventional fossil energy sources with renewable and sustainable energy sources is the potential route; and thus, manifests as a viable solution. Accordingly, the electrocatalytic carbon dioxide (CO2) reduction process coupled with the renewable energy source is an emerging strategy for adopting a sustainable approach. However, the existing challenges in designing suitable catalyst, support material, electrolyte, inadequate selectivity, and intermediate reactions of CO2 reduction demand substantial research advancement. Numerous studies reported for the CO2 reduction process highlight the importance of catalyst design and product selectivity. Importantly, the copper-based catalysts, capable in the output of multi-carbon products, are reported as a “star” material. This review; therefore, focuses on catalyst design strategies, unique structural/morphological features, and product selectivity of diverse copper-based catalysts. The outstanding findings of copper-based catalysts and the corresponding products are critically discussed with adequate figures of merits. The impact of structural/morphological features on product selectivity is discussed in detail. The future scope and author perspectives on copper-based catalysts for the feasible electrocatalytic CO2 reduction application are summarized.</p