Context-NER : Contextual Phrase Generation at Scale

NLP research has been focused on NER extraction and how to efficiently extract them from a sentence. However, generating relevant context of entities from a sentence has remained under-explored. In this work we introduce the task Context-NER in which relevant context of an entity has to be generated. The extracted context may not be found exactly as a substring in the sentence. We also introduce the EDGAR10-Q dataset for the same, which is a corpus of 1,500 publicly traded companies. It is a manually created complex corpus and one of the largest in terms of number of sentences and entities (1 M and 2.8 M). We introduce a baseline approach that leverages phrase generation algorithms and uses the pre-trained BERT model to get 33% ROUGE-L score. We also do a one shot evaluation with GPT-3 and get 39% score, signifying the hardness and future scope of this task. We hope that addition of this dataset and our study will pave the way for further research in this domain.Comment: 12 pages, 2 Figures, 1 Algorithm, 8 Tables. Accepted in NeurIPS 2022 - Efficient Natural Language and Speech Processing (ENLSP) Worksho

Architectural Challenges and Solutions for Collocated LWIP - A Network Layer Perspective

Achieving a tighter level of aggregation between LTE and Wi-Fi networks at the radio access network (a.k.a. LTE-Wi-Fi Aggregation or LWA) has become one of the most prominent solutions in the era of 5G to boost network capacit y and improve end user's quality of experience. LWA offers flexible resource scheduling decisions for steering user tr affic via LTE and Wi-Fi links. In this work, we propose a Collocated LTE/WLAN Radio Level Integration architecture at IP layer (C-LWIP), an enhancement over 3GPP non-collocated LWIP architecture. We have evaluated C-LWIP performance in vari ous link aggregation strategies (LASs). A C-LWIP node ( i.e. , the node having collocated, aggregated LTE eNodeB and Wi-Fi access point functionalities) is implemented in NS-3 which introd uces a traffic steering layer ( i.e. , Link Aggregation Layer) for efficient integration of LTE and Wi-Fi. Using extensive simulations, we verified the correctness of C-LWIP module in NS-3 and evaluat ed the aggregation benefits over standalone LTE and Wi-Fi netwo rks with respect to varying number of users and traffic types. We found that split bearer performs equivalently to switched b earer for UDP flows and switched bearer outperforms split bearer in the case of TCP flows. Also, we have enumerated the potential challenges to be addressed for unleashing C-LWIP capabilit ies. Our findings also include WoD-Link Aggregation Strategy whi ch is shown to improve system throughput by 50% as compared to Naive-LAS in a densely populated indoor stadium environmen t

IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages

Natural Language Generation (NLG) for non-English languages is hampered by the scarcity of datasets in these languages. In this paper, we present the IndicNLG Benchmark, a collection of datasets for benchmarking NLG for 11 Indic languages. We focus on five diverse tasks, namely, biography generation using Wikipedia infoboxes, news headline generation, sentence summarization, paraphrase generation and, question generation. We describe the created datasets and use them to benchmark the performance of several monolingual and multilingual baselines that leverage pre-trained sequence-to-sequence models. Our results exhibit the strong performance of multilingual language-specific pre-trained models, and the utility of models trained on our dataset for other related NLG tasks. Our dataset creation methods can be easily applied to modest-resource languages as they involve simple steps such as scraping news articles and Wikipedia infoboxes, light cleaning, and pivoting through machine translation data. To the best of our knowledge, the IndicNLG Benchmark is the first NLG benchmark for Indic languages and the most diverse multilingual NLG dataset, with approximately 8M examples across 5 tasks and 11 languages. The datasets and models are publicly available at https://ai4bharat.iitm.ac.in/indicnlg-suite.Comment: Accepted at EMNLP 202

Growth optimization and device integration of narrow-bandgap graphene nanoribbons

The electronic, optical and magnetic properties of graphene nanoribbons (GNRs) can be engineered by controlling their edge structure and width with atomic precision through bottom-up fabrication based on molecular precursors. This approach offers a unique platform for all-carbon electronic devices but requires careful optimization of the growth conditions to match structural requirements for successful device integration, with GNR length being the most critical parameter. In this work, we study the growth, characterization, and device integration of 5-atom wide armchair GNRs (5-AGNRs), which are expected to have an optimal band gap as active material in switching devices. 5-AGNRs are obtained via on-surface synthesis under ultra-high vacuum conditions from Br- and I-substituted precursors. We show that the use of I-substituted precursors and the optimization of the initial precursor coverage quintupled the average 5-AGNR length. This significant length increase allowed us to integrate 5-AGNRs into devices and to realize the first field-effect transistor based on narrow bandgap AGNRs that shows switching behavior at room temperature. Our study highlights that optimized growth protocols can successfully bridge between the sub-nanometer scale, where atomic precision is needed to control the electronic properties, and the scale of tens of nanometers relevant for successful device integration of GNRs

Load-aware dynamic RRH assignment in Cloud Radio Access Networks

Due to spatio-temporal variation of mobile subscriber's data traffic requirements, traffic load experienced by base stations present at different cell sites exhibit highly dynamic behavior in traditional cellular systems. This non-uniform and dynamic traffic load leads to under utilization of the base station computing resources at cell sites. Cloud Radio Access Network (C-RAN) is an innovative architecture which addresses this issue and keeps the Total Cost of Ownership (TCO) under safe limit for cellular operators. In C-RAN, the baseband processing units (BBUs) are segregated from cell sites and are pooled in a central cloud data center thereby facilitating shared access for a set of Remote Radio Heads (RRHs) present at cell sites. In order to truly exploit the benefits of C-RAN, the BBU pool deployed in the cloud has to efficiently serve clusters of RRHs (i.e., many-to-one mapping between RRHs and BBUs in the BBU pool) and thereby minimizing the required number of active BBUs. In this work, potential benefits of C-RAN are studied by considering realistic traffic loads of base stations deployed in urban areas by using statistical models. We propose a lightweight and load-aware algorithm, Dynamic RRH Assignment (DRA), which achieves BBU pooling gain close to that of a well known First-Fit Decreasing (FFD) bin packing algorithm. Using extensive simulations, we show that DRA consumes only 25% of time on average compared to FFD for the case of urban cellular deployment of 1000 RRHs. DRA slightly overestimates the required number of active BBUs as compared to FFD by 1.7% and 1.4% for weekdays and weekends, respectively

Identification of Novel Inhibitors of Leishmania donovani γ‑Glutamylcysteine Synthetase Using Structure-Based Virtual Screening, Docking, Molecular Dynamics Simulation, and in Vitro Studies

Trypansomatids maintain their redox balance by the trypanothione-based redox system, enzymes of which exhibit differences from mammalian homologues. γ-Glutamylcysteine synthetase (Gcs) is an essential enzyme in this pathway that performs the first and rate-limiting step. l-Buthionine-(<i>S</i>,<i>R</i>)-sulfoximine (BSO), a specific inhibitor of Gcs, induces toxicity in hosts infected with Trypanosoma brucei, underlining the need for novel Gcs inhibitors. The present study reports identification of Leishmania donovani Gcs (LdGcs) inhibitors using computational approaches and their experimental validation. Analysis of inhibitor–LdGcs complexes shows modifications that could result in increased efficacy of these compounds

Architecture, Performance, and Usability of Mobile Cellular Network Monitoring Applications for Data-Driven Analysis

Network monitoring is essential for operators to review and optimize network behaviour, and to troubleshoot any issues that arise. With the adoption of unlicensed band and spectrum-sharing technologies, conventional optimization techniques are no longer feasible. As cellular networks grow in complexity, data-driven solutions are becoming increasingly central to ensuring optimal network performance, reliability, and user experience. Recent cellular research has focused on data-driven analysis and optimization to ensure high Quality of Service in a cellular network. However, the biggest challenge for such work is data collection at scale from sophisticated and reliable network monitoring tools. This work bridges a gap in cellular network literature with a thorough review of cellular network monitoring tools. We rigorously test and review eleven applications that are popularly used to collect information on cellular networks. We understand, analyze, and critique their architecture to assess their reliability. We share insights on their performance and ease of use. Most importantly, we analyze the ability of applications to collect accurate cellular network data at scale. We also review recent literature on cellular network monitoring and analysis after carefully selecting 32 papers relevant to the topic

Sterically Selective [3 + 3] Cycloaromatization in the On-Surface Synthesis of Nanographenes.

Surface-catalyzed reactions have been used to synthesize carbon nanomaterials with atomically predefined structures. The recent discovery of a gold surface-catalyzed [3 + 3] cycloaromatization of isopropyl substituted arenes has enabled the on-surface synthesis of arylene-phenylene copolymers, where the surface activates the isopropyl substituents to form phenylene rings by intermolecular coupling. However, the resulting polymers suffered from undesired cross-linking when more than two molecules reacted at a single site. Here we show that such cross-links can be prevented through steric protection by attaching the isopropyl groups to larger arene cores. Upon thermal activation of isopropyl-substituted 8,9-dioxa-8a-borabenzo[fg]tetracene on Au(111), cycloaromatization is observed to occur exclusively between the two molecules. The cycloaromatization intermediate formed by the covalent linking of two molecules is prevented from reacting with further molecules by the wide benzotetracene core, resulting in highly selective one-to-one coupling. Our findings extend the versatility of the [3 + 3] cycloaromatization of isopropyl substituents and point toward steric protection as a powerful concept for suppressing competing reaction pathways in on-surface synthesis

On‐Surface Synthesis of Cumulene‐Containing Polymers via Two‐Step Dehalogenative Homocoupling of Dibromomethylene‐Functionalized Tribenzoazulene

Cumulene compounds are notoriously difficult to prepare and study due to dramatically increasing reactivity with increasing number of consecutive double bonds. In this respect, the emerging field of on‐surface synthesis provides exceptional opportunities because it relies on reactions on clean metal substrates under well‐controlled ultrahigh vacuum conditions. Here we report the on‐surface synthesis of a polymer linked by cumulene‐like bonds on a Au(111) surface via sequential thermally activated dehalogenative C-C coupling of a tribenzo‐azulene precursor equipped with two dibromomethylenes. The structure and electronic properties of the resulting polymer with cumulene‐like pentagon‐pentagon and heptagon‐heptagon connections have been investigated by means of scanning probe microscopy and spectroscopy methods and X‐ray photoelectron spectroscopy, complemented by density functional theory calculations. Our results provide perspectives for the on‐surface synthesis of compounds containing cumulene‐like bonds, as well as protocols relevant to the stepwise fabrication of carbon‐carbon bonds on surfaces

On-surface synthesis and characterization of teranthene and hexanthene: ultrashort graphene nanoribbons with mixed armchair and zigzag edges.

Graphene nanoribbons (GNRs) exhibit a broad range of physicochemical properties that critically depend on their width and edge topology. GNRs with armchair edges (AGNRs) are usually more stable than their counterparts with zigzag edges (ZGNRs) where the low-energy spin-polarized edge states render the ribbons prone to being altered by undesired chemical reactions. On the other hand, such edge-localized states make ZGNRs highly appealing for applications in spintronic and quantum technologies. For GNRs fabricated via on-surface synthesis under ultrahigh vacuum conditions on metal substrates, the expected reactivity of zigzag edges is a serious concern in view of substrate transfer and device integration under ambient conditions, but corresponding investigations are scarce. Using 10-bromo-9,9':10',9''-teranthracene as a precursor, we have thus synthesized hexanthene (HA) and teranthene (TA) as model compounds for ultrashort GNRs with mixed armchair and zigzag edges, characterized their chemical and electronic structure by means of scanning probe methods, and studied their chemical reactivity upon air exposure by Raman spectroscopy. We present a detailed identification of molecular orbitals and vibrational modes, assign their origin to armchair or zigzag edges, and discuss the chemical reactivity of these edges based on characteristic Raman spectral features