This study aims that Bitcoin prices are considered as dependent variables, and the total number of Coronavirus cases in the world, Ethereum Prices, Gold Prices, Coronavirus Google Trend Index, and Crypto Money Google Trend Index are considered as independent variables. Using the ARDL model, it was analyzed with a daily data set between 21.01.2020 - 04.04.2020. It is concluded that the relationship between the variables included in the analysis and Bitcoin prices exists co-integrated in the long term. Within the framework of the findings, investors' fears were interpreted by associating them with Bitcoin and Covid-19.
O. Lutz, Huili Chen, Hossein Fereidooni, Christoph Sendner · 7 authors
Ethereum smart contracts are automated decentralized applications on the blockchain that describe the terms of the agreement between buyers and sellers, reducing the need for trusted intermediaries and arbitration. However, the deployment of smart contracts introduces new attack vectors into the cryptocurrency systems. In particular, programming flaws in smart contracts can be and have already been exploited to gain enormous financial profits. It is thus an emerging yet crucial issue to detect vulnerabilities of different classes in contracts in an efficient manner. Existing machine learning-based vulnerability detection methods are limited and only inspect whether the smart contract is vulnerable, or train individual classifiers for each specific vulnerability, or demonstrate multi-class vulnerability detection without extensibility consideration. To overcome the scalability and generalization limitations of existing works, we propose ESCORT, the first Deep Neural Network (DNN)-based vulnerability detection framework for Ethereum smart contracts that support lightweight transfer learning on unseen security vulnerabilities, thus is extensible and generalizable. ESCORT leverages a multi-output NN architecture that consists of two parts: (i) A common feature extractor that learns the semantics of the input contract; (ii) Multiple branch structures where each branch learns a specific vulnerability type based on features obtained from the feature extractor. Experimental results show that ESCORT achieves an average F1-score of 95% on six vulnerability types and the detection time is 0.02 seconds per contract. When extended to new vulnerability types, ESCORT yields an average F1-score of 93%. To the best of our knowledge, ESCORT is the first framework that enables transfer learning on new vulnerability types with minimal modification of the DNN model architecture and re-training overhead.
Antonio López Vivar, Ana Lucila Sandoval Orozco, Luis Javier García Villalba
The use of blockchain and smart contracts have not stopped growing in recent years. Like all software that begins to expand its use, it is also beginning to be targeted by hackers who will try to exploit vulnerabilities in both the underlying technology and the smart contract code itself. While many tools already exist for analyzing vulnerabilities in smart contracts, the heterogeneity and variety of approaches and differences in providing the analysis data makes the learning curve for the smart contract developer steep. In this article the authors present ESAF (Ethereum Security Analysis Framework), a framework for analysis of smart contracts that aims to unify and facilitate the task of analyzing smart contract vulnerabilities which can be used as a persistent security monitoring tool for a set of target contracts as well as a classic vulnerability analysis tool among other uses.
Σε αυτή τη διατριβή, εξετάζουμε τα πιθανά οφέλη της διαφοροποίησης και την κατανομή βαρών (σταθμών) για την βελτιστοποίηση χαρτοφυλακίου κρυπτονομισμάτων. Συγκεκριμένα, δημιουργήθηκαν δύο χαρτοφυλάκια. Το πρώτο αποτελείται, αποκλειστικά, από τα πέντε πιο δημοφιλή κρυπτονομίσματα (Bitcoin, Ethereum, Litecoin, Ripple, Monero), τα οποία οδήγησαν σε υψηλό κίνδυνο λόγω της υψηλής μεταβλητότητας στις τιμές κλεισίματος. Το δεύτερο χαρτοφυλάκιο (μικτό) αποτελείται από το δείκτη αγοράς S&P500 και τα τέσσερα κρυπτονομίσματα (Bitcoin, Ethereum, Litecoin, & Ripple). Αυτό έδειξε χαμηλότερα επίπεδα κινδύνου μέσω της διαφοροποίησης. Οι αποδόσεις ήταν ελαφρώς παρόμοιες και για τα δύο χαρτοφυλάκια. Τα μοντέλα στρατηγικής που εφαρμόστηκαν στην εργασία ήταν τα ακόλουθα: α) το μοντέλο Naïve (κανόνας 1/N, ίσα σταθμά), β) το μοντέλο ελαχίστου κινδύνου, γ) το μοντέλο εφαπτομενικότητας (μεγιστοποίηση της αναλογίας Sharpe, με μηδενικό κίνδυνο) και δ) το μοντέλο της μέγιστης χρησιμότητας. Και τα δύο χαρτοφυλάκια εξετάστηκαν με δύο Rolling Windows το καθένα, για 100 ημέρες και για 252 ημέρες. Επιπλέον, εφαρμόστηκε ο περιορισμός της θέσης αγοράς (μόνο), τα σταθμά παραμένουν θετικά σε όλη τη διάρκεια της εξέτασης, (χωρίς άδεια πώλησης). Τέλος, δεν εφαρμόστηκαν προμήθειες και έξοδα σε κανένα από τα δύο χαρτοφυλάκια. Συμπερασματικά, το μικτό χαρτοφυλάκιο παρουσίασε καλύτερα αποτελέσματα μέσω της διαφοροποίησης.
As the most popular blockchain that supports smart contracts, there are already more than 296 thousand kinds of cryptocurrencies built on Ethereum. However, not all cryptocurrencies can be controlled by users. For example, some money is permanently locked in wallets' accounts due to attacks. In this paper, we conduct the first systematic investigation on locked cryptocurrencies in Ethereum. In particular, we define three categories of accounts with locked cryptocurrencies and develop a novel tool named Clue to discover them. Results show that there are more than 216 million dollars value of cryptocurrencies locked in Ethereum. We also analyze the reasons (i.e., attacks/behaviors) why cryptocurrencies are locked. Because the locked cryptocurrencies can never be controlled by users, avoid interacting with the accounts discovered by Clue and repeating the same mistakes again can help users to save money.
This study aims that Bitcoin prices are considered as dependent variables, and the total number of Coronavirus cases in the world, Ethereum Prices, Gold Prices, Coronavirus Google Trend Index, and Crypto Money Google Trend Index are considered as independent variables. Using the ARDL model, it was analyzed with a daily data set between 21.01.2020 - 04.04.2020. It is concluded that the relationship between the variables included in the analysis and Bitcoin prices exists co-integrated in the long term. Within the framework of the findings, investors' fears were interpreted by associating them with Bitcoin and Covid-19.
Background. Vaccine, as an irreplaceable means in herd immunization, is widely applied in prevention for communicable diseases. However, adverse impacts were frequently incurred by fake or expired vaccines in China. Given the necessity of vaccine anticounterfeiting, blockchain-based transaction platform could be practiced as a solution in addressing the issue; however, most of the available experiments focused on single-chain structured design with inventible limitations. Accordingly, exploration for the effectiveness and feasibility of mixed-chains structured platform for vaccine anticounterfeiting and tracing is essentially required. Methods. Both public chain and private chain were inserted in anticounterfeiting and tracing platform designing process, which were subsequently simulated in Ethereum environment. Results. By recording different information in public chain and private chain, partial information privacy protection requirements are realized. The transfer identification module realized the function of vaccine quality supervision and solves the problem of EPC label replication. Discussion. Compared with the traditional single-structured design, completeness information could be visited by all stakeholders in double-chain structure, including vaccine suppliers, National Medical Products Administration (NMPA), vaccine purchasers, and the vaccinated. Conclusion. Double-chain structured system for vaccine anticounterfeiting and tracing is more effective.
Cryptocurrencies are among the inventions that have caused a stir in the economy of late. Because in its use there are still pros and cons of various countries. Some countries reject the use of cryptocurrencies and others support the use of cryptocurrencies because it is considered a modernization of payment tools. Besides being used for payment instruments, cryptocurrencies can also be one of the options to invest. The number of cryptocurrencies that exist causes investors to be observant in making the right choices. In this study, the Promethee method was used I and II to determine the rank of 7 virtual currencies. Promethee I is a partial assessment method while Promethee II is a complete assessment method. The data used for ranking is obtained from the questionnaire "sentiment on the performance of cryptocurrencies". The results of the cryptocurrency performance analysis showed that the investment commodity of the most recommended in a row is Bitcoin with a net flow value of 0.33267, Cardano 0.14267, Ethereum 0.04800, Ripple 0.04733, Stellar -0.04733, Litecoin -0.04767 and Dogecoin -0.47567.
Guglielmo Maria Caporale, Woo-Young Kang, Fabio Spagnolo, Nicola Spagnolo
This paper provides comprehensive evidence on the effects of cyber-attacks (cyber-crime, cyber espionage, cyber warfare and hacktivism) and cyber security on the risk-adjusted returns, realised volatilities and trading volumes of the three main cryptocurrencies (Bitcoin, Ethereum and Litecoin).We find that stronger cyber security is generally effective in increasing the riskadjusted returns of cryptocurrencies and trading activity even in the presence of cyber-attacks.Hacktivism appears to be the most significant threat to cryptocurrency investors.Further, cyberattackers hitting the cryptocurrency exchanges are most likely to attack other sectors (government, industry and finance) as well.In addition, in the case of the US they target the government and industry sectors in preference to the cryptocurrency exchanges given the corresponding potential benefits and costs.In all cases appropriate strategies should be designed to enhance cyber security.
Block chain technology (BT) is an evolving technology with reliable and protective measured for sharing data in various applications. This work concentrates on healthcare based BT over Ethereum platform for data management. The medical applications include complex medical procedures with clinical and surgical trials. It includes managing and accessing of huge medical data. With the execution of medical applications factors like system cost are estimated for providing feasibility. This works provide multiple flows of healthcare BT over Ethereum platform. The performance of this model is analyzed with multiple flows. The data management, security, identity, and autonomy are considered as an essential factor.
Ahmet Faruk Aysan, Asad Ul Islam Khan, Humeyra Topuz
The main aim of this article is to examine the inter-relationships among the top cryptocurrencies on the crypto stock market in the presence and absence of the COVID-19 pandemic. The nine chosen cryptocurrencies are Bitcoin, Ethereum, Ripple, Litecoin, Eos, BitcoinCash, Binance, Stellar, and Tron and their daily closing price data are captured from coinmarketcap over the period from 13 September 2017 to 21 September 2020. All of the cryptocurrencies are integrated of order 1 i.e., I(1). There is strong evidence of a long-run relationship between Bitcoin and altcoins irrespective of whether it is pre-pandemic or pandemic period. It has also been found that these cryptocurrencies’ prices and their inter-relationship are resilient to the pandemic. It is recommended that when the investors create investment plans and strategies they may highly consider Bitcoin and altcoins jointly as they give sustainability and resilience in the long run against the geopolitical risks and even in the tough time of the COVID-19 pandemic.
Filippo Contro, Marco Crosara, Mariano Ceccato, Mila Dalla Preda
Motivated by the immutable nature of Ethereum smart contracts and of their transactions, quite many approaches have been proposed to detect defects and security problems before smart contracts become persistent in the blockchain and they are granted control on substantial financial value. Because smart contracts source code might not be available, static analysis approaches mostly face the challenge of analysing compiled Ethereum bytecode, that is available directly from the official blockchain. However, due to the intrinsic complexity of Ethereum bytecode (especially in jump resolution), static analysis encounters significant obstacles that reduce the accuracy of exiting automated tools. This paper presents a novel static analysis algorithm based on the symbolic execution of the Ethereum operand stack that allows us to resolve jumps in Ethereum bytecode and to construct an accurate control-flow graph (CFG) of the compiled smart contracts. EtherSolve is a prototype implementation of our approach. Experimental results on a significant set of real world Ethereum smart contracts show that EtherSolve improves the accuracy of the execrated CFGs with respect to the state of the art available approaches. Many static analysis techniques are based on the CFG representation of the code and would therefore benefit from the accurate extraction of the CFG. For example, we implemented a simple extension of EtherSolve that allows to detect instances of the re-entrancy vulnerability.
Filippo Contro, Marco Crosara, Mariano Ceccato, Mila Dalla Preda
Motivated by the immutable nature of Ethereum smart contracts and of their\ntransactions, quite many approaches have been proposed to detect defects and\nsecurity problems before smart contracts become persistent in the blockchain\nand they are granted control on substantial financial value.\n Because smart contracts source code might not be available, static analysis\napproaches mostly face the challenge of analysing compiled Ethereum bytecode,\nthat is available directly from the official blockchain. However, due to the\nintrinsic complexity of Ethereum bytecode (especially in jump resolution),\nstatic analysis encounters significant obstacles that reduce the accuracy of\nexiting automated tools.\n This paper presents a novel static analysis algorithm based on the symbolic\nexecution of the Ethereum operand stack that allows us to resolve jumps in\nEthereum bytecode and to construct an accurate control-flow graph (CFG) of the\ncompiled smart contracts. EtherSolve is a prototype implementation of our\napproach. Experimental results on a significant set of real world Ethereum\nsmart contracts show that EtherSolve improves the accuracy of the execrated\nCFGs with respect to the state of the art available approaches.\n Many static analysis techniques are based on the CFG representation of the\ncode and would therefore benefit from the accurate extraction of the CFG. For\nexample, we implemented a simple extension of EtherSolve that allows to detect\ninstances of the re-entrancy vulnerability.\n
Cüneyt Gürcan Akçora, Yulia R. Gel, Murat Kantarcıoğlu
Blockchain is an emerging technology that has enabled many applications, from cryptocurrencies to digital asset management and supply chains. Due to this surge of popularity, analyzing the data stored on blockchains poses a new critical challenge in data science. To assist data scientists in various analytic tasks for a blockchain, in this tutorial, we provide a systematic and comprehensive overview of the fundamental elements of blockchain network models. We discuss how we can abstract blockchain data as various types of networks and further use such associated network abstractions to reap important insights on blockchains' structure, organization, and functionality. This article is categorized under:Technologies > Data PreprocessingApplication Areas > Business and IndustryFundamental Concepts of Data and Knowledge > Data ConceptsFundamental Concepts of Data and Knowledge > Knowledge Representation.
Cüneyt Gürcan Akçora, Murat Kantarcıoğlu, Yulia R. Gel
Blockchain is an emerging technology that has enabled many applications, from\ncryptocurrencies to digital asset management and supply chains. Due to this\nsurge of popularity, analyzing the data stored on blockchains poses a new\ncritical challenge in data science.\n To assist data scientists in various analytic tasks on a blockchain, in this\ntutorial, we provide a systematic and comprehensive overview of the fundamental\nelements of blockchain network models. We discuss how we can abstract\nblockchain data as various types of networks and further use such associated\nnetwork abstractions to reap important insights on blockchains' structure,\norganization, and functionality.\n
Rapid technological advances have made blockchain technology applicable not only to digital money, but in various fields. One of the areas that can be implemented by blockchain is digital tourism, specifically in the online review system of tourism products. The current online review system has several problems due to its centralized nature. The problem faced is the manipulation of review data which can be in the form of review deletion by a centralized party. This research proposes a decentralized online review system using the Ethereum blockchain technology, Smart Contracts, and IPFS to provide a secure, transparent, and trustworthy online review system platform. The purpose of this research is to implement a permission-less blockchain as a storage for reviews (review forms and log notes) and develop a web application as a user interface. The data used is data from travel sites which contain details about hotels and restaurants in Bukhara. The results displayed are the development of a web application that implements a permission-less blockchain using Ethereum and the system performance is displayed based on system testing, which comprised of unit testing and Black-Box testing.
Cryptocurrencies have emerged as a disruptive force in global financial markets, presenting both unique opportunities and significant challenges, particularly for developing economies like India. This paper examines the economics of cryptocurrency within the Indian context, exploring the potential rewards and inherent risks of its adoption. India, with its burgeoning digital economy, is witnessing growing interest in cryptocurrencies such as Bitcoin, Ethereum, and others, driven by factors like financial inclusion, investment diversification, and the promise of decentralization. However, the widespread adoption of cryptocurrency in India has been slowed by a number of economic, regulatory, and security concerns, which have led to a complex and sometimes contradictory relationship between market participants, regulators, and policymakers. This study utilizes both qualitative and quantitative methods to provide a comprehensive analysis of how cryptocurrencies could impact India’s financial system. Through interviews with key stakeholders, including policymakers, financial analysts, and cryptocurrency exchange operators, as well as an analysis of historical market data, the paper investigates the implications of cryptocurrency in India. It focuses on areas such as investment behavior, regulatory uncertainty, security risks, and the potential for blockchain technology to drive innovation in financial services. The research aims to strike a balance between the potential benefits cryptocurrencies could offer, such as enhanced financial inclusion and lower transaction costs, and the challenges they pose, including volatility and fraud. Ultimately, this paper offers insights into how India can harness the economic potential of cryptocurrencies while managing the associated risks, providing a roadmap for future regulatory and policy decisions.
Turabek Gaybullaev, Hee-Yong Kwon, Taesic Kim, Mun‐Kyu Lee
The rapidly increasing expansion of distributed energy resources (DER), such as renewable energy systems and energy storage systems into the electric power system and the integration of advanced information and communication technologies enable DER owners to participate in the electricity market for grid services. For more efficient and reliable power system operation, the concept of peer-to-peer (P2P) energy trading has recently been proposed. The adoption of blockchain technology in P2P energy trading has been considered to be the most promising solution enabling secure smart contracts between prosumers and users. However, privacy concerns arise because the sensitive data and transaction records of the participants, i.e., the prosumers and the distribution system operator (DSO), become available to the blockchain nodes. Many efforts have been made to resolve this issue. A recent breakthrough in a P2P energy trading system on an Ethereum blockchain is that all bid values are encrypted using functional encryption and peer matching for trading is performed securely on these encrypted bids. Their protocol is based on a method that encodes integers to vectors and an algorithm that securely compares the ciphertexts of these vectors. However, the comparison method is not very efficient in terms of the range of possible bid values because the amount of computation grows linearly according to the size of this range. This paper addresses this challenge by proposing a new bid encoding algorithm called dual binary encoding, which dramatically reduces the amount of computation as it is only proportional to the square of the logarithm of the size of the encoding range. Moreover, we propose a practical mechanism for rebidding the remaining amount caused when the amounts from the two matching peers are not equal. Finally, the feasibility of the proposed method is evaluated by using a virtual energy trade testbed and a private Ethereum blockchain platform.
The current electricity networks were not initially designed for the high integration of variable generation technologies. They suffer significant losses due to the combustion of fossil fuels, the long-distance transmission, and distribution of the power to the network. Recently, \emph{prosumers}, both consumers and producers, emerge with the increasing affordability to invest in domestic solar systems. Prosumers may trade within their communities to better manage their demand and supply as well as providing social and economic benefits. In this paper, we explore the use of Blockchain technologies and auction mechanisms to facilitate autonomous peer-to-peer energy trading within microgrids. We design two frameworks that utilize the smart contract functionality in Ethereum and employ the continuous double auction and uniform-price double-sided auction mechanisms, respectively. We validate our design by conducting A/B tests to compare the performance of different frameworks on a real-world dataset. The key characteristics of the two frameworks and several cost analyses are presented for comparison. Our results demonstrate that a P2P trading platform that integrates the blockchain technologies and agent-based systems is promising to complement the current centralized energy grid. We also identify a number of limitations, alternative solutions, and directions for future work.
Jae Song, Eung Seon Kang, Hyeon Woo Shin, Ju Wook Jang
We implement a peer-to-peer (P2P) energy trading system between prosumers and consumers using a smart contract on Ethereum blockchain. The smart contract resides on a blockchain shared by participants and hence guarantees exact execution of trade and keeps immutable transaction records. It removes high cost and overheads needed against hacking or tampering in traditional server-based P2P energy trade systems. The salient features of our implementation include: 1. Dynamic pricing for automatic balancing of total supply and total demand within a microgrid, 2. prevention of double sale, 3. automatic and autonomous operation, 4. experiment on a testbed (Node.js and web3.js API to access Ethereum Virtual Machine on Raspberry Pis with MATLAB interface), and 5. simulation via personas (virtual consumers and prosumers generated from benchmark). Detailed description of our implementation is provided along with state diagrams and core procedures.
Yunshu Liu, Zhixuan Fang, Man Hon Cheung, Wei Cai · 5 authors
Miners in a blockchain system are suffering from ever-increasing storage costs, which in general have not been properly compensated by the users’ transaction fees. This reduces the incentives for the miners’ participation and may jeopardize the blockchain security. To mitigate this blockchain insufficient fee issue, we propose a Fee and Waiting Tax (FWT) mechanism, which explicitly considers the two types of negative externalities in the system. Specifically, we model the interactions between the protocol designer, users, and miners as a three-stage Stackelberg game. By characterizing the equilibrium of the game, we find that miners neglecting the negative externality in transaction selection cause they are willing to accept insufficient-fee transactions. This leads to the insufficient storage fee issue in the existing protocol (i.e., deployed in Bitcoin and Ethereum). Moreover, our proposed optimal FWT mechanism can motivate users to pay sufficient transaction fees to cover the storage costs and achieve the unconstrained social optimum. Numerical results show that the optimal FWT mechanism guarantees sufficient transaction fees and achieves an average social welfare improvement of 51.43% or more over the existing protocol. Furthermore, the optimal FWT mechanism reduces the average waiting time of low-fee transactions and all transactions by 68.49% and 61.56%, respectively.
Yunshu Liu, Zhixuan Fang, Man Hon Cheung, Wei Cai · 5 authors
Miners in a blockchain system are suffering from the ever-increasing storage costs, which in general have not been properly compensated by the users' transaction fees. In the long run, this may lead to less participation of miners in the system and jeopardize the blockchain security. In this work, we mitigate such a blockchain storage sustainability issue by proposing a social welfare maximization mechanism, which encourages each user to pay sufficient transaction fees for the storage costs and consider the waiting time costs imposing on others. We model the interactions between the protocol designer, users, and miners as a three-stage Stackelberg game. In Stage I, the protocol designer optimizes the consensus parameters associated with the transaction fee per byte values and waiting time costs to maximize the social welfare. In Stage II, the users decide the transaction generation rates to maximize their payoffs. In Stage III, the miners select the transactions and record them into the blockchain to maximize their payoffs. Through characterizing the Nash equilibrium of the three-stage game, we find that the protocol designer can not only achieve maximum social welfare in Stage II and III of the model, but also incentivize each user pays sufficient transaction fees for storage costs. We also find that for users who generate transactions at lower rates, they may pay higher waiting time price per transaction for the waiting time costs they impose on other users. Ethereum-based numerical results showed that our proposed mechanism dominates the existing protocol in both social welfare and fees, achieves a higher fairness index than the existing protocol, and performs well even under heterogeneous-storage-cost miners.
Since the introduction of the first Bitcoin blockchain in 2008, different decentralized blockchain systems such as Ethereum, Hyperledger Fabric, and Corda, have emerged with public and private accessibility. It has been widely acknowledged that no single blockchain network will fit all use cases. As a result, we have observed the increasing popularity of multi-blockchain ecosystem in which customers will move toward different blockchains based on their particular requirements. Hence, the efficiency and security requirements of interactions among these heterogeneous blockchains become critical. In realization of this multi-blockchain paradigm, initiatives in building Interoperability-Facilitating Platforms (IFPs) that aim at bridging different blockchains (a.k.a. blockchain interoperability) have come to the fore. Despite current efforts, it is extremely difficult for blockchain customers (organizations, governments, companies) to understand the trade-offs between different IFPs and their suitability for different application domains before adoption. A key reason is due to a lack of fundamental and systematic approaches to assess the variables among different IFPs. To fill this gap, developing new IFP requirements specification and open-source benchmark tools to advance research in distributed, multi-blockchain interoperability, with emphasis on IFP performance and security challenges are required. In this document, we outline a research proposal study to the community to realize this gap.
Since the introduction of the first Bitcoin blockchain in 2008, different\ndecentralized blockchain systems such as Ethereum, Hyperledger Fabric, and\nCorda, have emerged with public and private accessibility. It has been widely\nacknowledged that no single blockchain network will fit all use cases. As a\nresult, we have observed the increasing popularity of multi-blockchain\necosystem in which customers will move toward different blockchains based on\ntheir particular requirements. Hence, the efficiency and security requirements\nof interactions among these heterogeneous blockchains become critical. In\nrealization of this multi-blockchain paradigm, initiatives in building\nInteroperability-Facilitating Platforms (IFPs) that aim at bridging different\nblockchains (a.k.a. blockchain interoperability) have come to the fore. Despite\ncurrent efforts, it is extremely difficult for blockchain customers\n(organizations, governments, companies) to understand the trade-offs between\ndifferent IFPs and their suitability for different application domains before\nadoption. A key reason is due to a lack of fundamental and systematic\napproaches to assess the variables among different IFPs. To fill this gap,\ndeveloping new IFP requirements specification and open-source benchmark tools\nto advance research in distributed, multi-blockchain interoperability, with\nemphasis on IFP performance and security challenges are required. In this\ndocument, we outline a research proposal study to the community to realize this\ngap.\n