Abstract

Understanding the structure-function relationships of RNA has become increasingly important given the realization of its functional role in various cellular processes. Chemical denaturation of RNA by urea has been shown to be beneficial in investigating RNA stability and folding. Elucidation of the mechanism of unfolding of RNA by urea is important for understanding the folding pathways. In addition to studying denaturation of RNA in aqueous urea, it is important to understand the nature and strength of interactions of the building blocks of RNA. In this study, a systematic examination of the structural features and energetic factors involving interactions between nucleobases and urea is presented. Results from molecular dynamics (MD) simulations on each of the five DNA/RNA bases in water and eight different concentrations of aqueous urea, and free energy calculations using the thermodynamic integration method are presented. The interaction energies between all the nucleobases with the solvent environment and the transfer free energies become more favorable with respect to increase in the concentration of urea. Preferential interactions of urea versus water molecules with all model systems determined using Kirkwood-Buff integrals and two-domain models indicate preference of urea by nucleobases in comparison to water. The modes of interaction between urea and the nucleobases were analyzed in detail. In addition to the previously identified hydrogen bonding and stacking interactions between urea and nucleobases that stabilize the unfolded states of RNA in aqueous solution, NH-π interactions are proposed to be important. Dynamic properties of each of these three modes of interactions have been presented. The study provides fundamental insights into the nature of interaction of urea molecules with nucleobases and how it disrupts nucleic acids.

Abstract

Understanding synergistic effect by calculating electronic structure is essential to fine-tune the catalytic properties of bimetallic nanoalloy clusters which might be used for design of novel efficient catalysts. Density functional theory PBE0 calculations were performed to investigate the structure and energetics of various intermediates involved in the CO oxidation reaction catalyzed by Au3-xYx (x= 0–3 and Y denotes Ag or, Pt or, Pd) trimeric clusters through two possible pathways: Eley-Rideal (ER) and Langmuir-Hinshelwood (LH). The results of this investigation show that the catalytic behavior of the nanocluster highly depends on its composition and the reaction site taken into consideration. The most active reaction centres of goldsilver, gold-palladium, gold-platinum clusters are gold, palladium and platinum atoms respectively. The gold-silver clusters and AuPt2 prefer ER mechanism whereas, gold-palladium and Au2Pt selectively favour LH mechanism in comparison to the other. Bimetallic clusters, in general, are more efficient in comparison to their pristine mono-metallic counterparts, in activating the OO bond for the reaction and have relatively easy CO2 dissociation. Overall results indicate that the alloyed clusters could potentially have a better catalytic activity as compared to pure gold clusters for CO oxidation at low temperatures.

Abstract

We are interested in the problem of enabling transformation of existing, already published web pages. We call this Renarration of web content. In our earlier work, we had already established the role and importance of renarration for improving Web Accessibility. There are nearly a billion websites on the web, making transformation of pages a domain on its own. In this paper, we present the development of a Domain-Specific Language (DSL) for the purpose of web page transformation. We show how the design and implementation of our DSL is driven by our problem domain, its terminology and its unique requirements. We take up an existing online video-course delivery system, which has accessibility challenges, as a specific case to demonstrate our DSL. We end with insights and reflections for future work in both DSL and web page transformations.

Abstract

With the rise of Virtual Reality (VR) footprint in many organizations, it was unclear if traditional software engineering practices are still exercised during VR product development. As part of our research, we conducted a year-long multi-level exploratory study to understand the various software development practices within VR product development teams. An empirical study on VR practitioners from 6 different countries was done to examine their development strategies, methods, and models adopted along with the various challenges faced during the course of VR product release. We found that VR practitioners adopted hybrid Software engineering approaches in VR product development. In this paper, we present our insights from the empirical study and stress on the need for a diverse software development model for VR products.

Abstract

VR development practices have a diverse set of practices compared to traditional software development. Tasks like scene design, acoustic design, vergence manipulation, image depth, etc. are specific to VR apps and hence require evaluation processes that may be different from the traditional means. Usability Evaluation is one such process which is being executed in an unconventional way by Industrial Practitioners today. In this paper, the researchers detail a Systematic Literature Review of the Usability Evaluation Methods practised by Industrial researchers while building VR Products. The researchers found that VR Product teams follow unique methods to improve usability in their products. Further, the researchers consolidate these methods and provide insights into choosing the best to build a real-world VR Product based on the defined product constraints.

Abstract

Identifying dependency between various artifacts in a large scale software system is a non-trivial task. As the software evolves, multiple artifacts like files, docs, classes, database scripts, etc., are likely to undergo change concurrently. Such artifacts tend to have a dependency between them, otherwise referred to as logical coupling. Researchers have used Support and Confidence as an association rule based measurement to predict the levels of logical coupling among the software artifacts. However, employing a single change on a software artifact can span across various closely related changes when many code contributors are working on the same change. Thus it is important to preprocess and group these semantically related change-sets before identifying logical coupling. In this paper, we propose a method to identify logical coupling and group semantically related change sets. We evaluate our method on real-world git repositories and document our observations

Abstract

With more than a trillion web pages, there is a plethora of content available for consumption. Search Engine queries invariably lead to overwhelming information, parts of it relevant and some others irrelevant. Often the information provided can be conflicting, ambiguous, and inconsistent contributing to the loss of credibility of the content. In the past, researchers have proposed approaches for credibility assessment and enumerated factors influencing the credibility of web pages. In this work, we detailed a W EBCred framework for automated genre-aware credibility assessment of web pages. We developed a tool based on the proposed framework to extract web page features instances and identify genre a web page belongs to while assessing it’s Genre Credibility Score (GCS). We validated our approach on ‘Information Security’ dataset of 8,550 URLs with 171 features across 7 genres. The supervised learning algorithm, Gradient Boosted Decision Tree classified genres with 88.75% testing accuracy over 10 fold cross-validation, an improvement over the current benchmark. We also examined our approach on ‘Health’ domain web pages and had comparable results. The calculated GCS correlated 69% with crowdsourced Web Of Trust (W OT) score and 13% with algorithm based Alexa ranking across 5 Information security groups. This variance in correlation states that our GCS approach aligns with human way (W OT) as compared to algorithmic way (Alexa) of web assessment in both the experiments.

Abstract

While edge computing is gaining traction, organizations operating in geographically distributed locations are still using cloud computing to collect and post-process data. In this context, it is useful to analyze the performance trade-offs of cloud-only, edge-only and hybrid edge-cloud processing. To facilitate this analysis, we provide an analytic model validated by measurements on representative edge and cloud platforms. Our model is easy to apply even without performing measurements on the target edge hardware, as long as useful performance specifications are available. Our measurement-driven analysis reveals a diverse performance landscape where there is no clear winner among cloud-only, edge-only and hybrid processing. However, application characteristics and edge-cloud transfer bandwidth are the key factors affecting performance.

Abstract

Software Engineering Researchers in India from both academia and industry are widely contributing to various research problems. In this report, we briefly summarize the key insights from 1st Software Engineering Research in India Update Meeting (SERI 2019), which provides a platform for all the researchers to present and discuss their research work. The essence of this research meeting is to examine the current\ research areas within the software engineering research community and discover the scope of collaboration. Specifically, the first SERI update meeting had a series of invited research talks presented by researchers from academia and industry representing various software engineering labs across India. These talks unveiled notable views through presentations and group discussions, and cogitation of topics that can lead to fruitful collaborations between software engineering researchers and industry practitioners. The main objective of this update meeting is the exchange of research areas that promotes successful short-term and long-term collaborations.

Abstract

Community Question and Answer (CQA) platforms are expected to provide relevant content that is not readily available through search engines. With an increase in the number of users and growth of internet, CQA platforms have transitioned from generic to domain specific systems. Expert rating, machine learning and statistical methods are being used for assessing the quality of answers. However, the research on importance of consistency as a quality parameter in the form of text cohesion in CQAs is limited. We extracted 109,113 CQAs from StackExchange related to Information Security of the last 8 years to evaluate text cohesion in answers. An empirical study conducted with 246 participants (Information Security Experts, Software Engineers and Computational Linguists) on the extracted answers stated that lack of text cohesion impacts the rating of answers in CQA. Software Engineers are seekers and viewers of answers, they responded to a survey that lack of text cohesion leads to difficulty in reading and remembering. Information Security Experts providing answers to CQA stated that they need text cohesion for understandability.