Retrofitting Light-weight Language Models for Emotions using Supervised Contrastive Learning

We present a novel retrofitting method to induce emotion aspects into pre-trained language models (PLMs) such as BERT and RoBERTa. Our method updates pre-trained network weights using contrastive learning so that the text fragments exhibiting similar emotions are encoded nearby in the representation space, and the fragments with different emotion content are pushed apart. While doing so, it also ensures that the linguistic knowledge already present in PLMs is not inadvertently perturbed. The language models retrofitted by our method, i.e., BERTEmo and RoBERTaEmo, produce emotion-aware text representations, as evaluated through different clustering and retrieval metrics. For the downstream tasks on sentiment analysis and sarcasm detection, they perform better than their pre-trained counterparts (about 1% improvement in F1-score) and other existing approaches. Additionally, a more significant boost in performance is observed for the retrofitted models over pre-trained ones in few-shot learning setting.Comment: EMNLP 2023 Camera Ready Versio

DYNAMIC, CLOUD AGNOSTIC END-TO-END PATH SELECTION

Cloud connectivity may take different forms including, for example, the Internet, a private connection (such as a direct connection, an express route, or a partner interconnect), or a cloud backbone. Techniques are presented herein that allow different arrangements – such as a branch or a user connecting to a cloud, one region connecting to another region within one public cloud, one public cloud connecting to another public cloud, or a data center (DC) connecting to a cloud – to be able to leverage one or more of those connectivity options flexibly and in an automated fashion. The presented techniques are cloud agnostic and may be implemented using a software-defined networking (SDN) controller (that makes use of cloud-native routing constructs such as a virtual private cloud, a transit gateway, a virtual network, or virtual wide area network hub routing); may include the construction of a topology and the mapping of applications and consumers to one or more topologies depending upon the (dynamic and static) application needs, tenancy requirements, a consumption model, billing needs, etc.; may convey such mappings through tagging or through inferences from other signals; and may support dynamic user-defined intent and application-based path selection. Aspects of the presented techniques may be extended to custom routers to augment the capabilities of a current software-defined wide area network (SDWAN) solution for branch-to-cloud connectivity

Difference in clinical profile between juvenile onset and adult-onset systemic lupus erythematosus: a meta-analysis

The aim was to systematically review the studies that compared clinical and serological variation between adult-onset systematic lupus erythematosus (aSLE) andjuvenile-onset systematic lupus erythematosus (jSLE). A comprehensive literature search was done, in various available electronic databases for relevant publication that compared juvenile onset SLE and adult onset SLE. The data of adverse clinical features, serological profile and mortality were extracted. Juvenile onset was defined as 18 years. The methodological quality of study was assessed by Newcastle Ottawa scale (NOS) criteria and R version 3.3.1 was used for analysis and ORs and 95% CIs, were used as statistical parameter. A total of 14,920 patients; (12,230: aSLE, and 2,690: jSLE) were included. Renal involvement especially nephritis was significantly more in j-SLE OR: 2.18, 95% CI: [1.81;2.62]; I2=10.8% whereas musculoskeletal was significant in aSLE O.R: 0.64; C.I: [0.44; 0.93]; I2=83.4%. Seizure and malar rash were significantly higher in J-SLE OR:1.69, CI: [1.31; 2.18]; I2=31.1%,1.43; C.I [1.04; 1.97]; I2=82%, respectively. Raynaud’s phenomenon and pleuritis were significantly higher in adult onset SLE. Anemia and thrombocytopenia were significantly higher in juvenile onset SLE. Anti-ds DNA, anti-histone, and anti-ribosomal-P were more frequent in juvenile-onset SLE while, anti-Ro was more common in adult-onset disease. The cause of mortality was not significantly different in both groups. Renal biopsy of class III and IV combined and class V were significantly more in adult-onset SLE. SLEDAI was higher in j-SLE. Meta-analysis indicated that, regardless of many similar clinical and serological manifestations, there is still some variation between adult-onset SLE and juvenile-onset SLE. Although, SLE disease is continuum from juvenile to adult but disease aggressive in juvenile onset SLE

Investigation of Neolamarckia cadamba phytoconstituents against SARS-CoV-2 3CL Pro: An In-Silico Approach

In present study, the inhibitory potential of Neolamarckia cadamba phytoconstituents was investigated against SARS-CoV-2 3CL protease (3CL pro) (PDB ID: 6M2N). Molecular docking was analyzed using AutoDock Vina software by setting the grid parameter as X= -33.163, Y= -65.074 and Z= 41.434 with dimensions of the grid box 25 × 25 × 25 Å. Remdesivir was taken as the standard for comparative analysis along with inhibitor 5, 6, 7-trihydroxy-2-phenyl-4H-chromen-4-one. Furthermore, the exploration of 2 D Hydrogen-bond interactions was performed by Biovia Discovery Studio 4.5 program to identify the interactions between an amino acid of target and ligand followed by assessment of physicochemical properties using Lipinski’s rule and Swiss ADME database. The decent bonding scores of secondary metabolites owing to hydrogen bonding with catalytic residues suggest the effectiveness of these phytochemicals towards 3CLpro. The results are further consolidated positively by Lipinski’s rule and Swiss ADME prediction. Thus reasonably, observations with docking studies suggest possibility of phytochemicals from Neolamarckia cadamba to inhibit the 3CLpro and consequently would be explored further as agents for preventing COVID-19

Cost benefit analysis for software process improvements

Software Process Improvement (SPI) techniques have repeatedly proven to be effective in removing defects from software artefacts and thereby reducing the costs Process improvement, however, is not always successful effort. Very few are able to quantify the short and long term costs and benefits of implementing effective SPIs. To solve this, here we propose an approach, which helps not only to implement effective software process, but also to analyse costs and benefits associated with improving the process.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Projecting parameters for multilingual word sense disambiguation

We report in this paper a way of doing Word Sense Disambiguation (WSD) that has its origin in multilingual MT and that is cognizant of the fact that parallel corpora, wordnets and sense annotated corpora are scarce resources. With respect to these resources, languages show different levels of readiness; however a more resource fortunate language can help a less resource fortunate language. Our WSD method can be applied to a language even when no sense tagged corpora for that language is available. This is achieved by projecting wordnet and corpus parameters from another language to the language in question. The approach is centered around a novel synset based multilingual dictionary and the empirical observation that within a domain the distribution of senses remains more or less invariant across languages. The effectiveness of our approach is verified by doing parameter projection and then running two different WSD algorithms. The accuracy values of approximately 75 % (F1-score) for three languages in two different domains establish the fact that within a domain it is possible to circumvent the problem of scarcity of resources by projecting parameters like sense distributions, corpus-co-occurrences, conceptual distance, etc. from one language to another