Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

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The Structure and Function of Complex Networks

https://link.springer.com/content/pdf/10.2307%2F3343168.pdf

Development as Freedom

We investigate whether income inequality affects subsequent growth in a cross-country sample for 1965-90, using the models of Barro (1997), Bleaney and Nishiyama (2002) and Sachs and Warner (1997), with negative results. We then investigate the evolution of income inequality over the same period and its correlation with growth. The dominating feature is inequality convergence across countries. This convergence has been significantly faster amongst developed countries. Growth does not appear to influence the evolution of inequality over time. Outline

https://www.econstor.eu/bitstream/10419/81822/1/02-28.pdf

Economic growth and income inequality

Social Network Analysis

ChEMBL is an Open Data database containing binding, functional and ADMET information for a large number of drug-like bioactive compounds. These data are manually abstracted from the primary published literature on a regular basis, then further curated and standardized to maximize their quality and utility across a wide range of chemical biology and drug-discovery research problems. Currently, the database contains 5.4 million bioactivity measurements for more than 1 million compounds and 5200 protein targets. Access is available through a web-based interface, data downloads and web services at: https://www.ebi.ac.uk/chembldb.

/pdf/chembl-a-large-scale-bioactivity-database-for-drug-discovery-4mahqu7a7p.pdf

ChEMBL: a large-scale bioactivity database for drug discovery

Most public blockchains are riddled with problems such as centralization trends and increasing processing fees, along with scalability and throughput bottlenecks. In an attempt to mitigate these problems, we propose a new blockchain design: the crypto-commodity protocol. Unlike crypto-currencies whose valuation fluctuates due to market volatility, crypto-commodity has an intrinsic value that is not influenced by any external factor: digital commodity owned by users is the number of bytes that can be consumed in the form of block records. It is inherently spam resistant by virtue of its design, and does not rely upon processing fees to achieve this goal. We suggest to improve throughput scalability through a dynamic block size adaptive to the network’s hashing power. To combat centralization trends, we have augmented proof of work with two refinements: public key based mining history and proof of consumption. Our design also guarantees monotonous timestamps and incorporates a reward scheme that incentivizes processing of records without fee.

Crypto-commodity Protocol for Addressing Blockchain Problems and Bottlenecks

Studies suggest that the 1'β-CN moiety in remdesivir sterically clashes with the Ser861 residue of the RNA-dependent-RNA polymerase (RdRp), causing a delayed chain termination in the RNA replication process. Replacing C1'β-CN with 5-membered heterocycles such as tetrazoles, oxadiazoles, and triazoles can augment the inhibitory activity and pharmacokinetic profile of C-nucleotides. Synthesis of tetrazole-, triazole-, and oxadiazole-integrated C1' analogues of remdesivir was attempted using general synthetic routes. The final compounds 26, 28, and 29 did not inhibit viral replication; however, the synthetic intermediates, i.e., 27 and 50, exhibited an IC90 = 14.1 μM each. The trifluoromethyl-substituted 1,2,4-oxadiazole 59 showed an IC90 of 33.5 μM. This work adds to the growing evidence of the beneficial medicinal impact of C1,1'-disubstituted C-nucleotides.

Multistep Synthesis of Analogues of Remdesivir: Incorporating Heterocycles at the C-1' Position.

This study proposes content and interaction analysis techniques for a large repository created from social media content. Though we have presented our study for a large platform dedicated to discussions around financial topics, the proposed methods are generic and applicable to all platforms. Along with an extension of topic extraction method using Latent Dirichlet Allocation, we propose a few measures to assess user participation, influence and topic affinities specifically. Our study also maps user-generated content to components of behavioral finance. While these types of information are usually gathered through surveys, it is obvious that large scale data analysis from social media can reveal many potentially unknown or rare insights. Characterising users based on their platform behavior to provide critical insights about how communities are formed and trust is established in these platforms using graphical analysis is also studied.

Understanding how social discussion platforms like Reddit are influencing financial behavior

This review presents an overview of the current research in kinetic exchange models for opinion formation in a society. The review begins with a brief introduction to previous models and subsequently provides an in-depth discussion of the progress achieved in the Biswas-Chatterjee-Sen model proposed in 2012, also known as the BChS model in some later research publications. The unique feature of the model is its inclusion of negative interaction between agents. The review covers various topics, including phase transitions between different opinion states, critical behavior dependent on various parameters, and applications in realistic scenarios such as the United States presidential election and Brexit.

/pdf/social-dynamics-through-kinetic-exchange-the-bchs-model-3q0f1cnz.pdf

Social dynamics through kinetic exchange: the BChS model

Smart contracts have been established as the standard mechanism for online crypto-currency transactions in blockchains such as Bitcoin and Ethereum. The application scope of smart contracts is predicted to expand beyond crypto-currency in upcoming years, and this emerging technology is likely to play a significant role in other major domains. Smart contracts are usually created using a special purpose programming language. In this paper, we explore an alternative mechanism based on propositional calculus, using multisignature and lock-based boolean variables. Higher order boolean quantifiers have been avoided, and from a security standpoint, the design is deliberately kept Turing-incomplete to guarantee bounded runtime and well-defined termination paths for any valid smart contract (for homogeneous locks, our validation checks run in linear time for best case and quadratic time for worst case). Keeping in mind a widening scope for smart contracts, the applicability of our design is not confined to blockchain transactions, but can be easily integrated into other application domains.

Arnab Chatterjee

Papers

Crypto-commodity Protocol for Addressing Blockchain Problems and Bottlenecks

Multistep Synthesis of Analogues of Remdesivir: Incorporating Heterocycles at the C-1' Position.

Understanding how social discussion platforms like Reddit are influencing financial behavior

Social dynamics through kinetic exchange: the BChS model

Deploying Transactional Smart Contracts using Multisignature Boolean Formulas