Blockchain Papers

Magnus W. D. Hanson‐Heine, Alexander P. Ashmore

Blockchain technology has had a substantial impact across multiple disciplines, creating new methods for storing and processing data with improved transparency, immutability, and reproducibility. These developments come at a time when the reproducibility of many scientific findings has been called into question, including computational studies. Here we present a computational chemistry simulation run directly on a blockchain virtual machine, using a harmonic potential to model the vibration of carbon monoxide. The results demonstrate for the first time that computational science calculations are feasible entirely within a blockchain environment and that they can be used to increase transparency and accessibility across the computational sciences.

Ferdınando Chıacchıo, Lucio Compagno, Diego D’Urso, Luca Velardita · 5 authors

With the growth of a global market, new regulations aiming at preventing the fraud of counterfeiting drugs have been released all over the world. In the pharma industry, an innovative technology named serialization is becoming more and more popular as it allows to implement a packaging process based on a hierarchical aggregation. This guarantees that each box entering in the distribution network is marked with a unique identifier for an easy traceability by a central regulatory in charge to follow the life cycle of the product until given to the final patient. In this scenario, the blockchain might offer a breakthrough proposing a decentralized and immutable traceability mechanism able to increase the security of the data and to reduce the success of a fraud attempt. To demonstrate the effectiveness of this technology, in this paper, a DAPP based on the Ethereum blockchain has been coded and tested as prototype in a pharma industry.

Stephan Leible, Steffen Schlager, Moritz Schubotz, Béla Gipp

Many sectors, like finance, medicine, manufacturing, and education, use blockchain applications to profit from the unique bundle of characteristics of this technology. Blockchain technology (BT) promises benefits in trustability, collaboration, organization, identification, credibility, and transparency. In this paper, we conduct an analysis in which we show how open science can benefit from this technology and its properties. For this, we determined the requirements of an open science ecosystem and compared them with the characteristics of BT to prove that the technology suits as an infrastructure. We also review literature and promising blockchain-based projects for open science to describe the current research situation. To this end, we examine the projects in particular for their relevance and contribution to open science and categorize them afterwards according to their primary purpose. Several of them already provide functionalities that can have a positive impact on current research workflows. So, BT offers promising possibilities for its use in science, but why is it then not used on a large-scale in that area? To answer this question, we point out various shortcomings, challenges, unanswered questions, and research potentials that we found in the literature and identified during our analysis. These topics shall serve as starting points for future research to foster the BT for open science and beyond, especially in the long-term.

Pieter Hartel, Richard Schumi

It is crucial that smart contracts are tested thoroughly due to their immutable nature. Even small bugs in smart contracts can lead to huge monetary losses. However, testing is not enough; it is also important to ensure the quality and completeness of the tests. There are already several approaches that tackle this challenge with mutation testing, but their effectiveness is questionable since they only considered small contract samples. Hence, we evaluate the quality of smart contract mutation testing at scale. We choose the most promising of the existing (smart contract specific) mutation operators, analyse their effectiveness in terms of killability and highlight severe vulnerabilities that can be injected with the mutations. Moreover, we improve the existing mutation methods by introducing a novel killing condition that is able to detect a deviation in the gas consumption, i.e., in the monetary value that is required to perform transactions. This paper has a replication package at https://github.com/pieterhartel/Mutation-at-scale

Scott Thiebes, Matthias Schlesner, Benedikt Brors, Ali Sunyaev

Modern life sciences with their highly sensitive omics data face several challenges regarding data storage and sharing [ 1 , 2 ]. On the one hand data must be protected to preserve the privacy of those individuals who contributed their data to research. On the other hand, omics data’s true value is only to be realized if shared with as many researchers as possible. In an ideal world, patients can flexibly control access to their personal data on a case-by-case basis [ 3 ]. However, granting and revoking access to data is a slow and tedious process within the current life sciences research paradigm, where most data is either stored on central controlled-access data repositories or kept locally within the respective research groups [ 3 ].

Mikael Beyene, Kannengießer, Niclas, Pandl, Konstantin D, Thiebes, Scott · 5 authors

A concept for distributed gene-drug interaction data sharing based on Ethereum Smart Contracts. The data is stored in a map with, both, keys and values utilizing a mixed-radix integer encoding that relies on the finiteness of the domains of given genes, drugs, and interactions. Thus, we get random access and, further, data queries are reduced to cheap bit comparisons.

Davi R. Ortega, Catherine M. Oikonomou, H. Ding, Prudence Rees-Lee · 6 authors

Abstract Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu , for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets.

Martin Westerkamp, Friedhelm Victor, Axel Küpper

Growing consumer awareness as well as manufacturers' internal quality\nrequirements lead to novel demands on supply chain traceability. Existing\ncentralized solutions suffer from isolated data storage and lacking trust when\nmultiple parties are involved. Decentralized blockchain-based approaches\nattempt to overcome these shortcomings by creating digital representations of\nphysical goods to facilitate tracking across multiple entities. However, they\ncurrently do not capture the transformation of goods in manufacturing\nprocesses. Therefore, the relation between ingredients and product is lost,\nlimiting the ability to trace a product's provenance. We propose a\nblockchain-based supply chain traceability system using smart contracts. In\nsuch contracts, manufacturers define the composition of products in the form of\nrecipes. Each ingredient of the recipe is a non-fungible token that corresponds\nto a batch of physical goods. When the recipe is applied, its ingredients are\nconsumed and a new token is produced. This mechanism preserves the traceability\nof product transformations. The system is implemented for the Ethereum Virtual\nMachine and is applicable to any blockchain configuration that supports it. Our\nevaluation reveals that the gas costs scale linearly with the number of\nproducts considered in the system. This leads to the conclusion that the\nsolution can handle complex use cases.\n

Seo-Joon Lee, Gyoun-Yon Cho, Fumiaki Ikeno, Tae-Ro Lee

Due to the development of high-throughput DNA sequencing technology, genome-sequencing costs have been significantly reduced, which has led to a number of revolutionary advances in the genetics industry. However, the problem is that compared to the decrease in time and cost needed for DNA sequencing, the management of such large volumes of data is still an issue. Therefore, this research proposes Blockchain Applied FASTQ and FASTA Lossless Compression (BAQALC), a lossless compression algorithm that allows for the efficient transmission and storage of the immense amounts of DNA sequence data that are being generated by Next Generation Sequencing (NGS). Also, security and reliability issues exist in public sequence databases. For methods, compression ratio comparisons were determined for genetic biomarkers corresponding to the five diseases with the highest mortality rates according to the World Health Organization. The results showed an average compression ratio of approximately 12 for all the genetic datasets used. BAQALC performed especially well for lung cancer genetic markers, with a compression ratio of 17.02. BAQALC performed not only comparatively higher than widely used compression algorithms, but also higher than algorithms described in previously published research. The proposed solution is envisioned to contribute to providing an efficient and secure transmission and storage platform for next-generation medical informatics based on smart devices for both researchers and healthcare users.

Halil Ibrahim Ozercan, Atalay Mert Ileri, Erman Ayday, Can Alkan

Genomics data introduce a substantial computational burden as well as data privacy and ownership issues. Data sets generated by high-throughput sequencing platforms require immense amounts of computational resources to align to reference genomes and to call and annotate genomic variants. This problem is even more pronounced if reanalysis is needed for new versions of reference genomes, which may impose high loads to existing computational infrastructures. Additionally, after the compute-intensive analyses are completed, the results are either kept in centralized repositories with access control, or distributed among stakeholders using standard file transfer protocols. This imposes two main problems: (1) Centralized servers become gatekeepers of the data, essentially acting as an unnecessary mediator between the actual data owners and data users; and (2) servers may create single points of failure both in terms of service availability and data privacy. Therefore, there is a need for secure and decentralized platforms for data distribution with user-level data governance. A new technology, blockchain, may help ameliorate some of these problems. In broad terms, the blockchain technology enables decentralized, immutable, incorruptible public ledgers. In this Perspective, we aim to introduce current developments toward using blockchain to address several problems in omics, and to provide an outlook of possible future implications of the blockchain technology to life sciences.

Jay Jay Billings

Sharing provenance across workflow management systems automatically is not currently possible, but the value of such a capability is high since it could greatly reduce the amount of duplicated workflows, accelerate the discovery of new knowledge, and verify the integrity of past and present analyses. Although numerous technological challenges exist to efficiently share provenance information across workflow management systems, permissioned distributed ledgers could surmount many of them. The primary benefit of permissioned distributed ledgers over other technologies is that their distribution is over a peer-to-peer network that encodes transactions across the network into an immutable hash list and achieves consensus on the validity of the new data through a common consensus mechanism. This work discusses provenance and distributed ledgers on their own and then presents an argument that distributed ledgers naturally satisfy many of the requirements of workflow provenance, that provenance information can exist in the ledger in multiple ways, and that a number of novel research areas exist based on this strategy.

Dimka Karastoyanova, Ludwig Stage

No abstract is available for this record.

Olugbemi T. Olaniyan, Mayowa J. Adeniyi, Charles Oluwaseun Adetunji, Omosigho Omoruyi Pius · 7 authors

Abstract Objectives To introduce blockchain technologies, including their benefits, pitfalls, and the latest applications, to the biomedical and health care domains. Target Audience Biomedical and health care informatics researchers who would like to learn about blockchain technologies and their applications in the biomedical/health care domains. Scope The covered topics include: (1) introduction to the famous Bitcoin crypto-currency and the underlying blockchain technology; (2) features of blockchain; (3) review of alternative blockchain technologies; (4) emerging nonfinancial distributed ledger technologies and applications; (5) benefits of blockchain for biomedical/health care applications when compared to traditional distributed databases; (6) overview of the latest biomedical/health care applications of blockchain technologies; and (7) discussion of the potential challenges and proposed solutions of adopting blockchain technologies in biomedical/health care domains.

Mitra Mojtahedi, Aymeric Fouquier d’Hérouël, Sui Huang

Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is determined, allowing inferring the original template concentration. Here we present a novel protocol to efficiently infer the concentration of a sample and its optimal dilution for dPCR from few targeted qPCR assays. By taking advantage of the real-time amplification feature of qPCR as opposed to relying on endpoint PCR assessment as in standard dPCR prior knowledge of template concentration is not necessary. This eliminates the need for serial dilutions in a separate titration and reduces the number of necessary reactions. We describe the theory underlying our approach and discuss experimental moments that contribute to uncertainty. We present data from a controlled experiment where the initial template concentration is known as proof of principle and apply our method on directly monitoring transcript level change during cell differentiation as well as gauging amplicon numbers in cDNA samples after pre-amplification.

S. Nangle-Smith

A short, 30cm, test section was used to study the effect of electrohydrodynamic (EHD) forces on flow redistribution in a horizontal, shell and tube heat exchanger subject to both boiling and condensation. The use of a short test section allows for a consistent flow pattern across the test section length which provides further insight into the true effect of EHD. It was found that the voltage polarity of the applied voltages influences the flow distribution. For the current geometry studied, it was found that positive polarity voltages tend to pull liquid away from heat transfer surface and that negative voltages tended to repel more liquid toward the heat transfer surface. Using this knowledge we were able to show that positive voltages were more effective for convective condensation heat transfer enhancement, whereas negative voltages were more effective for convective boiling heat transfer enhancement. A twofold enhancement of convective boiling heat transfer was achieved for positive voltages and a 4fold enhancement was achieved for negative voltages. Similar pressure drop penalties were seen for both cases, approximately twice that of the no EHD case. Furthermore, the effect of DC level, peak to peak voltage, frequency and duty cycle waveform parameters on convective boiling enhancement were studied to explore the range of controllability for the current set of flow parameters. It was found that these various waveform parameters can induce different flow patterns and consequently different heat transfer and pressure drop configurations. In general the heat transfer is enhanced by EHD, but different pressure drop penalties can be achieved for a given enhancement ratio using different waveforms. High heat transfer for relatively low pressure drop was achieved using either negative DC signals or 50%duty cycle pulse waveforms. In some cases the enhancement is quite little compared to the pressure drop, for example the zero DC level, varying peak to peak voltage data. It is suggested that in a system where the heat exchanger pressure drop due to EHD is more dominant than the system pressure drop, it may be possible to use EHD as a method of retarding the system rather than enhancing it thereby broadening the scope of controllability. Finally we showed the proof of concept of using DC EHD as a rapid control mechanism for the load conditions. Using -8kVDC the water side heat flux could be varied by approximately ±3.2 kW/m² within 5 seconds. As a comparison, the same experiment was repeated using the refrigerant flow rate to control the load. Response times were similar for both experiments and although the power required for the flow rate control was less, the minimal variability in flow parameters for the EHD control make it a more attractive method of load control.