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Fujita, Kentaro, Yuanyu Zhang, Masahiro Sasabe, and Shoji Kasahara. "Mining Pool Selection under Block WithHolding Attack." Applied Sciences 11, no. 4 (2021): 1617. http://dx.doi.org/10.3390/app11041617.
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In current Proof-of-Work (PoW) blockchain systems, miners usually form mining pools to compete with other pools/miners in the mining competition. Forming pools can give miners steady revenues but will introduce two critical issues. One is mining pool selection, where miners select the pools to join in order to maximize their revenues. The other is a Block WithHolding (BWH) attack, where pools can inject part of their hash/mining power into other pools to obtain additional revenues without contributing to the mining process of the attacked pools. Reasoning that the BWH attack will have significant impacts on the pool selection, we therefore investigate the mining pool selection issue in the presence of a BWH attack in this paper. In particular, we model the pool selection process of miners as an evolutionary game and find the Evolutionarily Stable States (ESSs) of the game (i.e., stable pool population states) as the solutions. Previous studies investigated this problem from the perspective of pool managers and neglected the revenues from attacked pools (attacking revenues), leading to less accurate and insightful findings. This paper, however, focuses on the payoffs of miners and carefully takes the attacking revenues into consideration. To demonstrate how the problem is solved, we consider the scenario with two mining pools and further investigate the case where one pool attacks the other and the case where the two pools attack each other. The results in this paper show that pools can attract more miners to join by launching a BWH attack and the attack power significantly affects the stable pool populations.
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Liu, Xiao, Zhao Huang, Quan Wang, Yin Chen, and Yuan Cao. "A Repeated Game-Based Distributed Denial of Service Attacks Mitigation Method for Mining Pools." Electronics 13, no. 2 (2024): 398. http://dx.doi.org/10.3390/electronics13020398.
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A Distributed Denial of Service (DDoS) attack is a prevalent issue in the blockchain network layer, causing significant revenue loss for honest mining pools. This paper introduces a novel method, the Repeated Game-based DDoS attack mitigation (RGD), to address this problem. Unlike traditional methods such as game theory and machine learning-based detection, the RGD method can effectively reflect the changes in mining revenue and strategies under different network-strength environments. In particular, we abstract the problem of DDoS mining pool revenue loss into a game revenue model and propose the subgame perfect equilibrium (SPE) approach to solve the optimal payoffs and pool strategies in various network environments. Furthermore, we address the returns of mining pools in an infinitely repeated game environment using the Two-Stage Repeated Game (TSRG) method, where the strategy varies with different network environments. The Matlab experimental simulation results indicate that as the network environment improves, the optimal mining strategies of mining pools are gradually shifting from honest strategies to launching DDoS attacks against each other. The RGD method can effectively represent the impact of changes in the network environment on the mining pool’s strategy selection and optimal revenue. Consequently, with the changing network environment, the optimal revenue of the mining pool only increases by 10% of the revenue loss during a DDoS attack.
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Zhang, Yang, Yourong Chen, Kelei Miao, Tiaojuan Ren, Changchun Yang, and Meng Han. "A Novel Data-Driven Evaluation Framework for Fork after Withholding Attack in Blockchain Systems." Sensors 22, no. 23 (2022): 9125. http://dx.doi.org/10.3390/s22239125.
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In the blockchain system, mining pools are popular for miners to work collectively and obtain more revenue. Nowadays, there are consensus attacks that threaten the efficiency and security of mining pools. As a new type of consensus attack, the Fork After Withholding (FAW) attack can cause huge economic losses to mining pools. Currently, there are a few evaluation tools for FAW attacks, but it is still difficult to evaluate the FAW attack protection capability of target mining pools. To address the above problem, this paper proposes a novel evaluation framework for FAW attack protection of the target mining pools in blockchain systems. In this framework, we establish the revenue model for mining pools, including honest consensus revenue, block withholding revenue, successful fork revenue, and consensus cost. We also establish the revenue functions of target mining pools and other mining pools, respectively. In particular, we propose an efficient computing power allocation optimization algorithm (CPAOA) for FAW attacks against multiple target mining pools. We propose a model-solving algorithm based on improved Aquila optimization by improving the selection mechanism in different optimization stages, which can increase the convergence speed of the model solution and help find the optimal solution in computing power allocation. Furthermore, to greatly reduce the possibility of falling into local optimal solutions, we propose a solution update mechanism that combines the idea of scout bees in an artificial bee colony optimization algorithm and the constraint of allocating computing power. The experimental results show that the framework can effectively evaluate the revenue of various mining pools. CPAOA can quickly and accurately allocate the computing power of FAW attacks according to the computing power of the target mining pool. Thus, the proposed evaluation framework can effectively help evaluate the FAW attack protection capability of multiple target mining pools and ensure the security of the blockchain system.
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Kusin, Faradiella Mohd, Mohd Syakirin Md Zahar, Siti Nurjaliah Muhammad, Zafira Md Zin, and Sharifah Mohd Sharif. "Assessing the potential use of abandoned mining pools as an alternative resource of raw water supply." Water Supply 16, no. 2 (2015): 410–17. http://dx.doi.org/10.2166/ws.2015.150.
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The water crisis in the state of Selangor has prompted the state water authority to use water from abandoned mining pools as an alternative resource of raw water supply. In this study, the potential use of the mining pool water has been assessed to evaluate its safe use for potable water consumption, which is the source of raw water to be supplied to water treatment plants. Assessments were made between sampling sites that include abandoned mining pools, active sand mining pools, and the receiving streams (two tributaries and the main river, Selangor River) within Bestari Jaya catchment, Selangor River Basin. As anticipated, some concentrations of metals were found in the active mining pool and in its discharge, such as iron, manganese, lead, copper and zinc. However, the trace elements were found at very low concentrations or below detection limits in the abandoned mining pools and in the rivers. It was found that generally the quality of the water in the rivers (upstream of water intake of the water treatment plants) was well below the recommended guideline limits set out by the Malaysia Ministry of Health for untreated raw water, and therefore is safe for potable water use.
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Ren, Min, Hongfeng Guo, and Zhihao Wang. "Mitigation of block withholding attack based on zero-determinant strategy." PeerJ Computer Science 8 (July 21, 2022): e997. http://dx.doi.org/10.7717/peerj-cs.997.
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This article focuses on the mining dilemma of block withholding attack between the mining pools in the bitcoin system. In order to obtain the higher revenue, the rational mining pool usually chooses an infiltration attack, that is, the pool will falls into the mining dilemma of the PoW consensus algorithm. Thus the article proposes to apply zero-determinant strategies for optimizing the behavior selection of the mining pool under PoW consensus mechanism to increase the total revenues of the system, so as to solve the mining dilemma. After theoretically studying the set and extortionate strategy of zero-determinant, the article devises an adaptive zero-determinant strategy that the pool can change the corporation probability of the next round based on its previous revenues. To verify the effectiveness of zero-determinant strategies, based on the actual revenue of the mining pool defined and deduced in the paper, it simulates 30 sets of game strategies to illustrate the revenue variation of the mining pools. The simulation results show that the three zero-determinant strategies can effectively improve the convergence rate of cooperation, mitigate block withholding attack and maximize the total revenues of the system. Compared with the set and extortionate strategy, the adaptive strategy can ensure more stability and more revenue.
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Liu, Xiao, Zhao Huang, Quan Wang, and Bo Wan. "An Evolutionary Game Theory-Based Method to Mitigate Block Withholding Attack in Blockchain System." Electronics 12, no. 13 (2023): 2808. http://dx.doi.org/10.3390/electronics12132808.
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Consensus algorithms are the essential components of blockchain systems. They guarantee the blockchain’s fault tolerance and security. The Proof of Work (PoW) consensus algorithm is one of the most widely used consensus algorithms in blockchain systems, using computational puzzles to enable mining pools to compete for block rewards. However, this excessive competition for computational power will bring security threats to blockchain systems. A block withholding (BWH) attack is one of the most critical security threats blockchain systems face. A BWH attack obtains the reward of illegal block extraction by replacing full proof with partial mining proof. However, the current research on the BWH game could be more extensive, considering the problem from the perspective of a static game, and it needs an optimal strategy that dynamically reflects the mining pool for multiple games. Therefore, to solve the above problems, this paper uses the method of the evolutionary game to design a time-varying dynamic game model through the degree of system supervision and punishment. Based on establishing the game model, we use the method of replicating dynamic equations to analyze and find the optimal strategy for mining pool profits under different BWH attacks. The experimental results demonstrate that the mining pools will choose honest mining for the best profit over time under severe punishment and high supervision. On the contrary, if the blockchain system is supervised with a low penalty, the mining pools will eventually choose to launch BWH attacks against each other to obtain the optimal mining reward. These experimental results also prove the validity and correctness of our model and solution.
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Alkalay-Houlihan, Colleen, and Nisarg Shah. "The Pure Price of Anarchy of Pool Block Withholding Attacks in Bitcoin Mining." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1724–31. http://dx.doi.org/10.1609/aaai.v33i01.33011724.
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Bitcoin, a cryptocurrency built on the blockchain data structure, has generated significant academic and commercial interest. Contrary to prior expectations, recent research has shown that participants of the protocol (the so-called “miners”) are not always incentivized to follow the protocol. We study the game induced by one such attack – the pool block withholding attack – in which mining pools (groups of miners) attack other mining pools. We focus on the case of two pools attacking each other, with potentially other mining power in the system.We show that this game always admits a pure Nash equilibrium, and its pure price of anarchy, which intuitively measures how much computational power can be wasted due to attacks in an equilibrium, is at most 3. We conjecture, and prove in special cases, that it is in fact at most 2. Our simulations provide compelling evidence for this conjecture, and show that players can quickly converge to the equilibrium by following best response strategies.
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Çulha, Davut. "Maximizing proof-of-work decentralization." Ingenieria Solidaria 20, no. 1 (2023): 1–16. http://dx.doi.org/10.16925/2357-6014.2024.01.04.
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Introduction: Blockchain technology is one of the emerging technologies that implements the concept of decentralization. The first application of this technology was with Bitcoin, which is a decentralized application. However, the decentralization of Bitcoin has become problematic due to the formation of mining pools. In this work, decentralization is intended to be maximized. Problem: Decentralization is the main concept of blockchain technologies. However, decentralization suffers mainly from mining pools in the Bitcoin network. Objective: In this work, the proposed solution to maximize upon the decentralized nature of Bitcoin is to revise the consensus protocol of Bitcoin. The proposed novel consensus protocol called Signature Proof-of-Work uses signatures instead of hashes. The proposed method aims to minimize the number of mining pools and maximize the number of solo miners by arguing that no one can share their private keys with others, which would ensure greater decentralization of the network. Methodology: The consensus algorithm in Bitcoin is Proof-of-Work. Proof-of-Work allows for the formation of mining pools. Mining pools control the Bitcoin network and reduce decentralization. Therefore, a novel Proof-of-Work consensus algorithm is proposed to empower decentralization. Results: The proposed consensus algorithm called Signature Proof-of-Work uses signatures instead of hashes. The proposed method aims to minimize the number of mining pools and maximize the number of solo miners by arguing that no one can share their private keys with others, which would ensure greater decentralization of the network. Conclusion: The proposed consensus algorithm minimizes mining pools by enforcing non-shareable private keys. Originality: The proposed consensus algorithm is an enhancement of the default Proof-of-Work algorithm of Bitcoin. The proposed algorithm uses signatures instead of hashes, which differentiates it from the default algorithm. Limitations: In the proposed algorithm, the main argument is that no one shares their private keys. In other words, miners cannot share their private keys with others. If they share their private keys, others can control their own money. Therefore, each miner does not want to collaborate with other miners to mine new blocks. As a result, the mining pools will not be formed.
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Toroghi Haghighat, Alireza, and Mehdi Shajari. "Block withholding game among bitcoin mining pools." Future Generation Computer Systems 97 (August 2019): 482–91. http://dx.doi.org/10.1016/j.future.2019.03.002.
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Gowan, Samuel W., and Steven M. Trader. "Mine failure associated with a pressurized brine horizon; Retsof salt mine, western New York." Environmental and Engineering Geoscience 6, no. 1 (2000): 57–70. http://dx.doi.org/10.2113/gseegeosci.6.1.57.
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Abstract The eventual loss of the Retsof Salt Mine from flooding was initiated on March 12, 1994 with a magnitude 3.6 earthquake, the collapse of a small-pillar panel, an initial inrush of brine and gas to the mine and a sustained inflow of fresh water. An examination of closure data for two mine panels involved in the inflow suggested an anomalous buildup of fluid pressure above the panels in the period leading up to their collapse. The initial brine and gas inflow immediately following the collapse coincided with the apparent relief of the excess pressure. The potential existence of a pre-collapse, pressurized, brine and gas pool above the panels was investigated through an analysis of nineteenth century solution mining data, a review of recent salt mine data, and an interpretation of geologic and geophysical data from post-collapse investigations. Published reports from the nineteenth century reveal that natural brine and gas pools existed in the region prior to mining. Correlation of gamma ray logs with geologic logs from contemporary drill holes and core holes provided a mechanism for interpreting the distribution of those natural brine pools. Our investigation indicated that natural gas and brine pools existed within Unit D of the Syracuse Formation approximately 160 ft above the mining horizon. Such brine accumulation apparently formed from the circulation of meteoric water through vertical discontinuities that were connected to overlying fresh water aquifers long before mining began in the valley in the late nineteenth century.
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Wang, Jing, and Zihao Wang. "EFAW: a new mining attack model combining FAW attacks with the Eclipse attack." Journal of Surveillance, Security and Safety 4, no. 4 (2023): 180–95. http://dx.doi.org/10.20517/jsss.2023.34.
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Aim The Proof-of-Work consensus mechanism is the core mechanism of the blockchain, but the existing Fork After Withholding (FAW) attack can earn more rewards by launching attacks on the mining pools under the Proof-of-Work consensus mechanism. This paper proposes a new attack model based on the FAW attack, which further increases the attacker’s reward to explore the impact of the attack method on the blockchain network and the losses caused by the attack, which is helpful for maintaining the blockchain. Methods This paper proposes a new mining attack model called the "Eclipse Fork After Withholding (EFAW) attack" by combining FAW attacks with the eclipse attack. In the EFAW attack, the attacker infiltrates the victim pool by dispatching infiltrator miners. At the same time, they isolate a portion of miners in the victim pool through eclipse attacks, intercepting the valid information transmitted by these isolated miners. The attacker selectively discards or strategically releases the information to gain extra rewards. Results In this paper, we launch an EFAW attack against a single mining pool and two mining pools, respectively, and evaluate the relative extra rewards of the attacker with theoretical analysis and Monte Carlo simulation experiments. Our experimental data indicate that this attack can earn more rewards than FAW attacks. Conclusion The experimental results demonstrate that the lower bound of earnings in the EFAW attack is higher than in FAW attacks, and it is directly proportional to the number of miners isolated by the attacker’s eclipse attack in the victim pool. This indicates that the EFAW attack poses a greater threat compared to FAW attacks, representing one of the major conclusions drawn from the study.
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Qin, Rui, Yong Yuan, and Fei-Yue Wang. "Optimal Block Withholding Strategies for Blockchain Mining Pools." IEEE Transactions on Computational Social Systems 7, no. 3 (2020): 709–17. http://dx.doi.org/10.1109/tcss.2020.2991097.
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Dong, Xuewen, and Sheng Gao. "GenSelfHolding: Fusing Selfish Mining and Block Withholding Attacks on Bitcoin Revisited." Journal of Networking and Network Applications 2, no. 1 (2022): 23–35. http://dx.doi.org/10.33969/j-nana.2022.020102.
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Due to the monetary value of Bitcoin, the most influential digital cryptocurrency in the world, Bitcoin has naturally become a valuable target of attacks, resulting in the emergence of many attack strategies on it. Among those attack strategies, selfish mining and block withholding attacks are two typical ones and attackers can obtain higher revenues under certain conditions than with an honest mining strategy. However, the combination of them will be a new type and more serious attack, which has not been analyzed in depth. In this paper, we propose GenSelfHolding, a general combined attack model with one selfish mining pool and random multiple honest pools on Bitcoin. Based on Markov chain, a general state transition graph and a general state distribution probability are presented to describe the internal features of our model. A general principle is then provided to calculate the attacker’s revenue. In addition, we give a detailed proof of the unique stable distribution of state transition probabilities. Such proof is an essential prerequisite for us to further present stable attacker revenue expressions under two specific scenarios, the GenSelfHolding model with two/three honest mining pools. Simulation results validate that the revenues of the attacker in these two specific models can reach up to 40% higher than those of classic selfish attackers in some cases.
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Chávez, Juan José García, and Carlo Kleber da Silva Rodrigues. "A Simple Algorithm for Automatic Hopping among Pools in the Bitcoin Mining Network." SIJ Transactions on Computer Networks & Communication Engineering 03, no. 01 (2015): 07–12. http://dx.doi.org/10.9756/sijcnce/v3i1/03020040101.
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Qin, Rui, Yong Yuan, and Fei-Yue Wang. "Research on the Selection Strategies of Blockchain Mining Pools." IEEE Transactions on Computational Social Systems 5, no. 3 (2018): 748–57. http://dx.doi.org/10.1109/tcss.2018.2861423.
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Gueth, Mareike, Gerhard Wiegleb, and Walter Durka. "Colonisation of secondary habitats in mining sites by Labidura riparia (Dermaptera: Labiduridae) from multiple natural source populations." Journal of Insect Conservation 25, no. 2 (2021): 349–59. http://dx.doi.org/10.1007/s10841-021-00305-y.
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AbstractBackgroundOpen cast lignite mines, sand pits and military training areas represent human-made, secondary habitats for specialized xerothermophilous and psammophilous species. Rare species, including the earwigLabidurariparia,are found in high population densities in such sites. However, it is unknown from which sources colonisation took place and how genetic variation compares to that of ancient populations on natural sites.MethodsUsing nine microsatellite markers, we analysed genetic variation and population structure ofL. ripariain 21 populations in NE Germany both from secondary habitats such as lignite-mining sites, military training areas and a potassium mining heap, and rare primary habitats, such as coastal and inland dunes.ResultsGenetic variation was higher in populations from post-mining sites and former military training areas than in populations from coastal or inland dune sites. Overall population differentiation was substantial (FST = 0.08;FʹST = 0.253), with stronger differentiation among primary (FST = 0.196;FʹST = 0.473) than among secondary habitats (FST = 0.043;FʹST = 0.147). Differentiation followed a pattern of isolation by distance. Bayesian structure analysis revealed three gene pools representing primary habitats on a coastal dune and two different inland dunes. All populations from secondary habitats were mixtures of the two inland dune gene pools, suggesting multiple colonization of post-mining areas from different source populations and hybridisation among source populations.DiscussionPopulations ofL. ripariafrom primary habitats deserve special conservation, because they harbour differentiated gene pools. The majority of theL. ripariapopulations, however, thrive in secondary habitats, highlighting their role for conservation.Implications for insect conservationA dual strategy should be followed of conserving both remaining natural habitat harbouring particular intraspecific gene pools and secondary habitat inhabited by large admixed and genetically highly variable populations.
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Sukoco, Sukoco, Gunawan Gunawan, and Muhamat Muhamat. "Struktur Komunitas Fitoplankton di Kolam Bekas Pertambangan Batubara Desa Kampung Baru Kecamatan Cempaka." BIOSCIENTIAE 17, no. 2 (2021): 37. http://dx.doi.org/10.20527/b.v17i2.3451.
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This study aims to determine the structure of phytoplankton communities in the pool are former coal mining Desa Kampung Baru Kecamatan Cempaka which include abundance, diversity, uniformity and dominance. Phytoplankton samples taken in two pools with a purposive sampling method with a three-point shooting at each pond. Sampling was performed three times. Phylum of phytoplankton were identified in both pools as much as 2 phylum (Chloropyta and Chrysopita) with 17 genera. Average abundance of phytoplankton in the first pool of 7174 ind / liter and 6873 ind / liter in the second pool. The average diversity index of phytoplankton in the first pool of 1.540 and 1.621 in the second pool. Average uniformity index of phytoplankton in the first pool of 0622 and 0.623 in the second pool. The average index of phytoplankton dominance in the first pool of 0271 and 0250 in the second pool. Analysis of community structure (abundance, diversity, uniformity and dominance) shows the condition of the two ponds in the state is quite stable and capable of supporting life inside the phytoplankton. Where the pool in the fertility rate is the level of contamination is, the conditions included in the category of individuals spread more evenly and there are no species that dominate other species in the extreme.
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Puppe, Daniel, Axel Höhn, Danuta Kaczorek, Manfred Wanner, Marc Wehrhan, and Michael Sommer. "How big is the influence of biogenic silicon pools on short-term changes in water-soluble silicon in soils? Implications from a study of a 10-year-old soil–plant system." Biogeosciences 14, no. 22 (2017): 5239–52. http://dx.doi.org/10.5194/bg-14-5239-2017.
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Abstract. The significance of biogenic silicon (BSi) pools as a key factor for the control of Si fluxes from terrestrial to aquatic ecosystems has been recognized for decades. However, while most research has been focused on phytogenic Si pools, knowledge of other BSi pools is still limited. We hypothesized that different BSi pools influence short-term changes in the water-soluble Si fraction in soils to different extents. To test our hypothesis we took plant (Calamagrostis epigejos, Phragmites australis) and soil samples in an artificial catchment in a post-mining landscape in the state of Brandenburg, Germany. We quantified phytogenic (phytoliths), protistic (diatom frustules and testate amoeba shells) and zoogenic (sponge spicules) Si pools as well as Tiron-extractable and water-soluble Si fractions in soils at the beginning (t0) and after 10 years (t10) of ecosystem development. As expected the results of Tiron extraction showed that there are no consistent changes in the amorphous Si pool at Chicken Creek (Hühnerwasser) as early as after 10 years. In contrast to t0 we found increased water-soluble Si and BSi pools at t10; thus we concluded that BSi pools are the main driver of short-term changes in water-soluble Si. However, because total BSi represents only small proportions of water-soluble Si at t0 (< 2 %) and t10 (2.8–4.3 %) we further concluded that smaller (< 5 µm) and/or fragile phytogenic Si structures have the biggest impact on short-term changes in water-soluble Si. In this context, extracted phytoliths (> 5 µm) only amounted to about 16 % of total Si contents of plant materials of C. epigejos and P. australis at t10; thus about 84 % of small-scale and/or fragile phytogenic Si is not quantified by the used phytolith extraction method. Analyses of small-scale and fragile phytogenic Si structures are urgently needed in future work as they seem to represent the biggest and most reactive Si pool in soils. Thus they are the most important drivers of Si cycling in terrestrial biogeosystems.
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Raza, Zeeshan, Irfan ul Haq, Muhammad Muneeb, and Omair Shafiq. "Energy Efficient Multiprocessing Solo Mining Algorithms for Public Blockchain Systems." Scientific Programming 2021 (October 31, 2021): 1–13. http://dx.doi.org/10.1155/2021/9996132.
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Blockchain as a decentralized distributed ledger is revolutionizing the world with a secure design data storage mechanism. In the case of Bitcoin, mining involves a process of packing transactions in a block by calculating a random number termed as a nonce. The nonce calculation is done by special nodes called miners, and all the miners follow the Proof of Work (PoW) mining mechanism to perform the mining task. The transaction verification time in PoW-based blockchain systems, i.e., Bitcoin, is much slower than other digital transaction systems such as PayPal. It needs to be quicker if a system adapts PoW-based blockchain solutions, where there are thousands of transactions being computed at a time. Besides this, PoW mining also consumes a lot of energy to calculate the nonce of a block. Mining pools resulting into aggregated hashpower have been a popular solution to speed up the PoW mining, but they can be attacked by using different types of attacks. Parallel computing can be used to speed up the solo mining methods by utilizing the multiple processes of the contributing processors. In this research, we analyze various consensus mechanisms and see that the PoW-based blockchain systems have the limitations of low transaction confirmation time and high energy consumption. We also analyze various types of consensus layer attacks and their effects on miners and mining pools. To tackle these issues, we propose parallel PoW nonce calculation methods to accelerate the transaction verification process especially in solo mining. We have tested our techniques on different difficulty levels, and our proposed techniques yield better results than the traditional nonce computation mechanisms.
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Donovan, Joseph J., and Eric F. Perry. "Mine Flooding History of a Regional Below-Drainage Coalfield Dominated by Barrier Leakage (1970–2014)." Geofluids 2019 (March 11, 2019): 1–16. http://dx.doi.org/10.1155/2019/5703108.
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A 44-year record of water level fluctuations in a series of adjacent closed underground mines documents the history of closure and mine flooding in the Fairmont Coalfield, one of the oldest coal mining districts in the Pittsburgh coal basin, West Virginia, USA. As closures proceeded and mines began to flood, US environmental regulations were first enacted mandating mine water control and treatment, rendering uncontrolled surface discharges unacceptable. The purpose of this study is to present this flooding history and to identify critical events that determined how mine pools evolved in this case. Also examined is the strategy developed to control and treat water from these mines. Flooding is visualized using both water level hydrographs and mine flooding maps with the latter constructed assuming mine water hydraulic continuity between one or more mines. The earliest flooding formed small pools within near-surface mines closed prior to 1962 yet still pumped following closure to minimize leaking into adjacent still-active workings. These subpools gradually enlarged and merged as more closures occurred and the need for protective pumping was removed, forming what is today referred to as the unconfined Fairmont Pool. Later, deeper mines, separated by intact updip barriers from the Fairmont Pool, were closed and flooded more gradually, supplied in large part by leakage from the Fairmont Pool. By 1985, all mines except 2 had closed and by 1994 all had fully flooded, with the Fairmont Pool interconnected to deeper single mine pools via barrier leakage. As protective pumping ceased, the Fairmont Pool rose to a water level 3 m higher than surface drainage elevation and in 1997 discharged from an undermined section of Buffalo Creek near the Monongahela River. The principal mine operator in the basin then designed a pumping system to transfer water from the Fairmont Pool to their existing treatment facilities to the north, thus terminating the discharge. It may be concluded that the progress of mine flooding was influenced by mining history and design, by the timing of closures, by barrier leakage conditions, and by geologic structure. A key element in how flooding proceeded was the presence of a series of intact barriers separating deep from shallow mines. The shallow mines closed and flooded early, but then lost sufficient water by barrier leakage into the deeper mines to delay the completion of flooding until after the deep mines had all closed and flooded as well. Intensive mine water control has continued from the 1997 breakout to the present. The final water control scheme was likely unanticipated and serendipitous; future district-wide mining efforts should be advised to consider in advance closeout strategies to control mine water postmining.
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Sun, Linhua, Xianghong Liu, and Chen Cheng. "Quality of water from subsidence area: a case study in the Luling coal mine, northern Anhui Province, China." Water Practice and Technology 10, no. 4 (2015): 777–86. http://dx.doi.org/10.2166/wpt.2015.096.
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Quality of water in the subsidence area related to coal mining is important for water usage in the coal mining areas. In this study, forty-two samples from the subsidence pools in the Luling coal mine, northern Anhui Province, China have been collected and measured for their major ion concentrations, and the data have been applied for quality evaluating of drinking and irrigation purposes. The results suggest that the water samples from different pools have different concentrations of major ions and all of them can be classified to be Na-HCO3 type. According to the results of water quality index, all of them are suitable for drinking (considering only about the major ion concentrations). However, sodium absorption ratio (SAR) and residual sodium carbonate (RSC) give different answers about irrigation purpose, the water can be used for irrigation according to SAR whereas cannot be used according to RSC, and can be attributed to the high concentrations of CO32− and HCO3−. Gibbs diagrams and relationships between Na+ normalized Ca2+, Mg2+ and HCO3− suggest that different extents of contributions from weathering of silicate, dissolution of carbonates and evaporates are the main mechanism controlling the major ion concentrations of water from the subsidence areas in this study, which is related to the natural conditions of the pools.
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Qadir, Danial, Hilmi Mukhtar, and Kok Keong Lau. "MONITORING AND PHYSICO-CHEMICAL ASSESSMENT OF EX-MINING POOLS IN PERAK, MALAYSIA." Malaysian Journal of Science 36, no. 1 (2017): 32–46. http://dx.doi.org/10.22452/mjs.vol36no1.4.
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Schlötterer, Christian, Raymond Tobler, Robert Kofler, and Viola Nolte. "Sequencing pools of individuals — mining genome-wide polymorphism data without big funding." Nature Reviews Genetics 15, no. 11 (2014): 749–63. http://dx.doi.org/10.1038/nrg3803.
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Sitanayah, Lanny, Apriandy Angdresey, and Vandri Josua Abram Sampul. "Monitoring and Predicting Water Quality in Swimming Pools." EPI International Journal of Engineering 3, no. 2 (2021): 119–25. http://dx.doi.org/10.25042/epi-ije.082020.05.
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Water quality in public swimming pools affects human health. While changing the water too soon is wasteful, postponing changing the dirty water is not hygiene. In this paper, we propose an Internet of Things-based wireless system to monitor and predict water quality in public swimming pools. Our system utilizes an Arduino Uno, an ESP8266 ESP-01 WiFi module, a DS18B20 temperature sensor, a pH sensor, and a turbidity sensor. We predict the water quality using a data mining prediction model, namely the decision tree Iterative Dichotomiser 3 algorithm. We show by experiment that our sensor node and the wireless monitoring system work correctly. We also show by simulation using Weka that we can get 100% accuracy with a kappa statistical value of 1 and 0% error rate.
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Wu, Shuangke, Yanjiao Chen, Minghui Li, Xiangyang Luo, Zhe Liu, and Lan Liu. "Survive and Thrive: A Stochastic Game for DDoS Attacks in Bitcoin Mining Pools." IEEE/ACM Transactions on Networking 28, no. 2 (2020): 874–87. http://dx.doi.org/10.1109/tnet.2020.2973410.
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Möser, Malte, Kyle Soska, Ethan Heilman, et al. "An Empirical Analysis of Traceability in the Monero Blockchain." Proceedings on Privacy Enhancing Technologies 2018, no. 3 (2018): 143–63. http://dx.doi.org/10.1515/popets-2018-0025.
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Abstract Monero is a privacy-centric cryptocurrency that allows users to obscure their transactions by including chaff coins, called “mixins,” along with the actual coins they spend. In this paper, we empirically evaluate two weaknesses in Monero’s mixin sampling strategy. First, about 62% of transaction inputs with one or more mixins are vulnerable to “chain-reaction” analysis - that is, the real input can be deduced by elimination. Second, Monero mixins are sampled in such a way that they can be easily distinguished from the real coins by their age distribution; in short, the real input is usually the “newest” input. We estimate that this heuristic can be used to guess the real input with 80% accuracy over all transactions with 1 or more mixins. Next, we turn to the Monero ecosystem and study the importance of mining pools and the former anonymous marketplace AlphaBay on the transaction volume. We find that after removing mining pool activity, there remains a large amount of potentially privacy-sensitive transactions that are affected by these weaknesses. We propose and evaluate two countermeasures that can improve the privacy of future transactions.
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Kiswanto, Heru Susanto, and Sudarno. "Characterization Of Coal Acid Water In Void Pools Of Coal Mining In South Kalimantan." E3S Web of Conferences 73 (2018): 05030. http://dx.doi.org/10.1051/e3sconf/20187305030.
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This study aims to determine the characteristics of acidic water derived from void coal mine by taking samples from voids located in South Kalimantan. Method used in this research was field work and laboratory work. The result of measurement of acid characterization of coal mine acid was analyzed to have the highest pH value of 4.01, the highest temperature was 33.9 oC, the highest Color was 3.01 NTU, the highest COD was 56.50 ppm, the highest BOD was 20,34 ppm , The highest DHL of 1 us, the highest TSS of 652.67 ppm, the highest Fe of 9.46 ppm, the highest Mn of 1.72 ppm and the Cd content is still below the defined standard of less than 0.01 ppm. Decree of the State Minister of Environment No. 113 of 2003 on Liquid Waste Quality Standards for Coal Mining.
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Hanna, Rifaat G. M. "Levels of heavy metals in some Red Sea fish before hot brine pools mining." Marine Pollution Bulletin 20, no. 12 (1989): 631–35. http://dx.doi.org/10.1016/0025-326x(89)90403-7.
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Mazanetz, Michael P., Catherine B. T. Reisser, Robert J. Marmon, and Inaki Morao. "Drug Discovery Applications for KNIME: An Open Source Data Mining Platform." Current Topics in Medicinal Chemistry 12, no. 18 (2013): 1965–79. http://dx.doi.org/10.2174/1568026611212180004.
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Technological advances in high-throughput screening methods, combinatorial chemistry and the design of virtual libraries have evolved in the pursuit of challenging drug targets. Over the last two decades a vast amount of data has been generated within these fields and as a consequence data mining methods have been developed to extract key pieces of information from these large data pools. Much of this data is now available in the public domain. This has been helpful in the arena of drug discovery for both academic groups and for small to medium sized enterprises which previously would not have had access to such data resources. Commercial data mining software is sometimes prohibitively expensive and the alternate open source data mining software is gaining momentum in both academia and in industrial applications as the costs of research and development continue to rise. KNIME, the Konstanz Information Miner, has emerged as a leader in open source data mining tools. KNIME provides an integrated solution for the data mining requirements across the drug discovery pipeline through a visual assembly of data workflows drawing from an extensive repository of tools. This review will examine KNIME as an open source data mining tool and its applications in drug discovery.
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Sun, Linhua, Xianghong Liu, and Ning Min. "Identifying the potential sources of trace metals in water from subsidence area based on positive matrix factorization." Water Practice and Technology 11, no. 2 (2016): 279–87. http://dx.doi.org/10.2166/wpt.2016.030.
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Water in the subsidence area is a good choice for solving the water shortage in the coal mining area of China. In this study, positive matrix factorization model has been applied for the concentrations of seven kinds of trace metals (Pb, V, Cr, Mn, Co, Ni and Cu) in water from the subsidence area in the Luling coal mine, northern Anhui Province, China for identifying and quantifying their potential sources. Statistical analyses (including coefficients of variation and P-value of Anderson–Darling test) of metal concentrations indicate that multi factors (geological weathering/dissolution, filling of coal gauge and anthropogenic discharge) are responsible for the metal concentrations in the water. Based on the variations of Q values, three sources have been determined by US EPA (US Environmental Protection Agency) positive matrix factorization model: coal gauge filling, geological weathering or dissolution and waste discharge. The contribution degrees of these sources for all of the pools are different, and therefore, different strategies (e.g. clean the waste and the coal gauge around and in the pools) should be applied with different pools.
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Gist, Conra D., Margarita Bianco, and Marvin Lynn. "Examining Grow Your Own Programs Across the Teacher Development Continuum: Mining Research on Teachers of Color and Nontraditional Educator Pipelines." Journal of Teacher Education 70, no. 1 (2018): 13–25. http://dx.doi.org/10.1177/0022487118787504.
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Grow Your Own (GYO) programs are cited in recent policy briefs as viable pathways for increasing the racial/ethnic diversity of teachers, yet recent scholarship on GYO programs is minimal. To address this issue, this article investigates what we know, and do not know, about GYO programs, by examining a range of data sources on different types of GYO program teacher pools (e.g., middle/high school, paraprofessional, community activists/parents mentors) and making sense of findings over a continuum of teacher development (e.g., recruitment, preparation, induction, and retention). Based on a research synthesis within and across GYO program teacher pools, we argue implications for policy, practice, and research that should accompany increased recommendations for expanding GYO models for Teachers of Color.
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Blekanov, Ivan S., Nikita Tarasov, and Svetlana S. Bodrunova. "Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages." Future Internet 14, no. 3 (2022): 69. http://dx.doi.org/10.3390/fi14030069.
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Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s abstractive summarization research is limited to testing the models on various types of data, which brings only marginal improvements and does not lead to massive practical employment of the method. In particular, abstractive summarization is not used for social media research, where it would be very useful for opinion and topic mining due to the complications that social media data create for other methods of textual analysis. Of all social media, Reddit is most frequently used for testing new neural models of text summarization on large-scale datasets in English, without further testing on real-world smaller-size data in various languages or from various other platforms. Moreover, for social media, summarizing pools of texts (one-author posts, comment threads, discussion cascades, etc.) may bring crucial results relevant for social studies, which have not yet been tested. However, the existing methods of abstractive summarization are not fine-tuned for social media data and have next-to-never been applied to data from platforms beyond Reddit, nor for comments or non-English user texts. We address these research gaps by fine-tuning the newest Transformer-based neural network models LongFormer and T5 and testing them against BART, and on real-world data from Reddit, with improvements of up to 2%. Then, we apply the best model (fine-tuned T5) to pools of comments from Reddit and assess the similarity of post and comment summarizations. Further, to overcome the 500-token limitation of T5 for analyzing social media pools that are usually bigger, we apply LongFormer Large and T5 Large to pools of tweets from a large-scale discussion on the Charlie Hebdo massacre in three languages and prove that pool summarizations may be used for detecting micro-shifts in agendas of networked discussions. Our results show, however, that additional learning is definitely needed for German and French, as the results for these languages are non-satisfactory, and more fine-tuning is needed even in English for Twitter data. Thus, we show that a ‘one-for-all’ neural-network summarization model is still impossible to reach, while fine-tuning for platform affordances works well. We also show that fine-tuned T5 works best for small-scale social media data, but LongFormer is helpful for larger-scale pool summarizations.
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Stylianou, Konstantinos, and Nic Carter. "The Size of the Crypto Economy: Calculating Market Shares of Cryptoassets, Exchanges and Mining Pools." Journal of Competition Law & Economics 16, no. 4 (2020): 511–51. http://dx.doi.org/10.1093/joclec/nhaa016.
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Abstract Cryptoassets and related actors such as crypto exchanges and mining pools are now fully integrated into mainstream economic activity. A necessary corollary is that they have attracted heightened regulatory and investor scrutiny. Although some rules and obligations apply uniformly across all economic actors in a given sector, many others, such as antitrust laws and some financial regulations as well as investor decisions are informed by actors’ relative economic size—meaning that those with larger market shares can become more attractive regulatory or investing targets. It is therefore a foundational issue to properly measure the economic footprint of economic actors in the crypto economy, for otherwise regulatory oversight and investor decisions risk being misled. This has proven a remarkably difficult exercise for multiple reasons including unfamiliarity with the underlying technology and role of involved actors, lack of understanding of the applicable metrics’ economic significance, and the unreliability of self-reported statistics, partly enabled by lack of regulation. Acknowledging the centrality of cryptoasset size in a number of regulatory and policymaking areas and the fact that previous attempts have been incomplete, simplistic, or even plainly wrong, this paper presents the first systematic examination of the economic footprint of cryptoassets and their constituent actors—mining pools and crypto exchanges. We aim to achieve a number of objectives: to introduce, identify, and organize all relevant and meaningful metrics of crypto economic actors market share calculation; to develop associations between metrics, and to explain their meaning, application, and limitations so that it becomes obvious in which context metrics can be useful or not, and what the potential caveats are; and to present rich, curated, and vetted data to illustrate metrics and their use in measuring the shares of crypto economic actors in their respective markets. The result is a comprehensive guidance into the size of the crypto economy.
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YAO, En-qin, and He-rong GUI. "Characteristics of the main polluting trace elements in the water environment of mining subsidence pools." Journal of China University of Mining and Technology 18, no. 3 (2008): 362–67. http://dx.doi.org/10.1016/s1006-1266(08)60076-0.
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Levasseur, Patrick A., Julian Aherne, Nathan Basiliko, et al. "Soil carbon pools and fluxes following the regreening of a mining and smelting degraded landscape." Science of The Total Environment 904 (December 2023): 166734. http://dx.doi.org/10.1016/j.scitotenv.2023.166734.
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Han, Jiazheng, Zhenqi Hu, Zhen Mao, et al. "How to Account for Changes in Carbon Storage from Coal Mining and Reclamation in Eastern China? Taking Yanzhou Coalfield as an Example to Simulate and Estimate." Remote Sensing 14, no. 9 (2022): 2014. http://dx.doi.org/10.3390/rs14092014.
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Carbon sequestration in terrestrial ecosystems plays an essential role in coping with global climate change and achieving regional carbon neutrality. In mining areas with high groundwater levels in eastern China, underground coal mining has caused severe damage to surface ecology. It is of practical significance to evaluate and predict the positive and negative effects of coal mining and land reclamation on carbon pools. This study set up three scenarios for the development of the Yanzhou coalfield (YZC) in 2030, including: (1) no mining activities (NMA); (2) no reclamation after mining (NRM); (3) mining and reclamation (MR). The probability integral model (PIM) was used to predict the subsidence caused by mining in YZC in 2030, and land use and land cover (LULC) of 2010 and 2020 were interpreted by remote sensing images. Based on the classification of land damage, the LULC of different scenarios in the future was simulated by integrating various social and natural factors. Under different scenarios, the InVEST model evaluated carbon storage and its temporal and spatial distribution characteristics. The results indicated that: (1) By 2030, YZC would have 4341.13 ha of land disturbed by coal mining activities. (2) Carbon storage in the NRM scenario would be 37,647.11 Mg lower than that in the NMA scenario, while carbon storage in the MR scenario would be 18,151.03 Mg higher than that in the NRM scenario. Significantly, the Nantun mine would reduce carbon sequestration loss by 72.29% due to reclamation measures. (3) Carbon storage has a significant positive spatial correlation, and coal mining would lead to the fragmentation of the carbon sink. The method of accounting for and predicting carbon storage proposed in this study can provide data support for mining and reclamation planning of coal mine enterprises and carbon-neutral planning of government departments.
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Wu, Xiaolong, Chong Feng, Qiyuan Li, and Jianping Zhu. "Keyword Pool Generation for Web Text Collecting: A Framework Integrating Sample and Semantic Information." Mathematics 12, no. 3 (2024): 405. http://dx.doi.org/10.3390/math12030405.
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Keyword pools are used as search queries to collect web texts, largely determining the size and coverage of the samples and provide a data base for subsequent text mining. However, how to generate a refined keyword pool with high similarity and some expandability is a challenge. Currently, keyword pools for search queries aimed at collecting web texts either lack an objective generation method and evaluation system, or have a low utilization rate of sample semantic information. Therefore, this paper proposed a keyword generation framework that integrates sample and semantic information to construct a complete and objective keyword pool generation and evaluation system. The framework includes a data phase and a modeling phase, and its core is in the modeling phase, where both feature ranking and model performance are considered. A regression model about a topic vector and word vectors is constructed for the first time based on word embedding, and keyword pools are generated from the perspective of model performance. In addition, two keyword generation methods, Recursive Feature Introduction (RFI) and Recursive Feature Introduction and Elimination (RFIE), are also proposed in this paper. Different feature ranking algorithms, keyword generation methods and regression models are compared in the experiments. The results show that: (1) When using RFI to generate keywords, the regression model using ranked features has better prediction performance than the baseline model, and the number of generated keywords is refiner, and the prediction performance of the regression model using tree-based ranked features is significantly better than that of the one using SHAP-based ranked features. (2) The prediction performance of the regression model using RFI with tree-based ranked features is significantly better than that using Recursive Feature Elimination (RFE) with tree-based one. (3) All four regression models using RFI/RFE with SHAP- based/tree-based ranked features have significantly higher average similarity scores and cumulative advantages than the baseline model (the model using RFI with unranked features). (4) Light Gradient Boosting Machine (LGBM) using RFI with SHAP-based ranked features has significantly better prediction performance, higher average similarity scores, and cumulative advantages. In conclusion, our framework can generate a keyword pool that is more similar to the topic, and more refined and expandable, which provides certain research ideas for expanding the research sample size while ensuring the coverage of topics in web text collecting.
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Chen, Yourong, Hao Chen, Meng Han, Banteng Liu, Qiuxia Chen, and Tiaojuan Ren. "A Novel Computing Power Allocation Algorithm for Blockchain System in Multiple Mining Pools Under Withholding Attack." IEEE Access 8 (2020): 155630–44. http://dx.doi.org/10.1109/access.2020.3017716.
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Yusof, A. M., M. N. Mahat, N. Omar, and A. K. H. Wood. "Water quality studies in an aquatic environment of disused tin-mining pools and in drinking water." Ecological Engineering 16, no. 3 (2001): 405–14. http://dx.doi.org/10.1016/s0925-8574(00)00124-5.
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Williams, Michael, Mucahit Kochan, and David Green. "Impact of Chinese Capital Outflows on Bitcoin vs. Yuan Relationships: A Multi-Period Analysis." Journal of Finance Issues 20, no. 2 (2022): 53–69. http://dx.doi.org/10.58886/jfi.v20i2.3432.
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We examine the relationships among Bitcoin (BTC), the Chinese Yuan (CNY), and Chinese capital outflows between 2014-2021. We find that BTC returns strongly comove with CNY returns after 2018Q1, while no significant BTC/CNY relationship exists before 2018Q1. Further, the strength of the BTC/CNY relationship increases throughout 2018 to the present date. Yet, this relationship strength cannot be explained by periods of ascending BTC prices, changes in crypto mining location, nor changes in the use of BTC "mining pools". Instead, we find that the strength of the BTC/CNY relationship is strongly and directly related to Chinese capital outflows. We find no similar relationship with a "bogey" currency, the Euro, implying that the capital outflows -to- BTC/CNY relationship is unique to China and its capital outflow environment. In total, our novel results suggest that BTC is used as part of a process to move economically significant amounts of capital from mainland China.
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Tošić, Aleksandar, Niki Hrovatin, and Jernej Vičič. "Dataset of Linkability Networks of Ethereum Accounts Involved in NFT Trading of Top 15 NFT Collections." Data 8, no. 7 (2023): 116. http://dx.doi.org/10.3390/data8070116.
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In this paper, we present subgraphs of Ethereum wallets involved in NFT trades of the top 15 ERC721 NFT collections. To obtain the subgraphs, we have extracted the Ethereum transaction graph from a live Ethereum node and filtered out exchanges, mining pools, and smart contracts. For each of the selected collections, we identified the set of accounts involved in NFT trading, which we used to perform a breadth-first search in the Ethereum transaction graph to obtain a subgraph. These subgraphs can offer insight into the linkability of accounts participating in NFT trading on the Ethereum blockchain.
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Wang, Dingyi, and Haishun Du. "Multi-level Salient Feature Mining Network for Person Re-identification." Journal of Physics: Conference Series 2640, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1742-6596/2640/1/012001.
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Abstract Person re-identification (Re-ID) algorithms can retrieve the same pedestrian’s images from an image gallery captured by multiple cameras when given a pedestrian image. Due to changes in pedestrian postures, illuminations, and perspectives, it remains a significant challenge to improve the accuracy of person re-identification. Although the attention mechanism can alleviate some of these issues, it causes attention-based methods to pay excessive attention to features in the most salient areas of images while ignoring discriminant features outside the most salient areas, resulting in the insufficient discriminability of features extracted by attention-based methods. For this purpose, we propose a Multi-level Salient Feature Mining Network (MSFM-Net). First, by embedding attention modules in ResNet50, the model extract the most salient pedestrian feature maps. Second, the model uses two sub-salient feature mining branches to extract the second-level and third-level salient feature maps (collectively referred to as sub-salient feature maps). Third, the model uses the feature maps fusion module to combine the most salient feature maps with sub-salient feature maps to obtain the fused salient feature maps. Finally, the model pools the fused salient feature maps to produce more discriminant pedestrian representations. The results of two benchmark datasets demonstrate that MSFM-Nets performance reaches the current advanced level.
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Oza, Tejas, Pooja Patel, and Vrinda S. Thaker. "A Comparative Genomic Analysis of Georgenia sps. for Mining of LysR Transcriptional Regulator Sequences." International Journal of Bioinformatics and Intelligent Computing 3, no. 1 (2024): 1–12. http://dx.doi.org/10.61797/ijbic.v3i1.285.
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Georgenia is a genus belonging to the actinomycetes group. The genera comprise only 33 poorly characterized species with reference genomes of 10 distinct species. However, none of the species is well characterized for their genome characteristics. Our laboratory isolate from tomato plant leaf was identified and sequenced for identification and found to be Georgenia sp. Later genomic analysis revealed many functional genes having characteristic functions to be analysed. The source of isolation raised the possibility of having functional genes to enhance senescence or having plant pathogenic activity by Georgenia sp. SUBG003. To explore in silico presence of these genes or gene pools genomic islands were identified and analysed for our isolate and other 10 reference genomes of the Georgenia genus. Genomic islands were further explored for transcription regulators and finally, LysR transcriptional regulator sequences were extracted and a phylogeny among sequences was built from multiple sequence alignment.
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Komulaynen, Sergey, and Tatiana Chekryzheva. "Response of Algal Communities to Anthropogenic Changes in Mineralization." Botanica Lithuanica 19, no. 1 (2013): 57–66. http://dx.doi.org/10.2478/botlit-2013-0010.
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Abstract A relatively new type of impact of human activities on lake-river system has resulted from mining operations in the Kostomuksha iron deposit, Karelia, NW Russia. Lake Kostumus was isolated by a dam and has since acted as a waste accumulator for ore-dressing production. The total mineral content of the water has reached 400 mg l-1. Comparative analysis of the structural organization and functioning of phytoperiphyton and phytoplankton in the Kenti lake-river system and subject to anthropogenic load resulting from urbanization is presented. The algal communities influenced by mineralized mining mill wastes were analysed in terms of species richness, species diversity, species ecology values, biomass and chlorophyll a concentration. When the anthropogenic load is minimized, the natural structure of algal assemblages quickly restores. This is most typical of lake-river systems with alternations of lakes and rivers, rapids and pools, playing the role of natural water treatment facilities. The possibility of using algal assemblages as an indicator of the ecological state of lake-river ecosystems is analysed.
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Schwarz-Schilling, Caspar, Sheng-Nan Li, and Claudio J. Tessone. "Stochastic Modelling of Selfish Mining in Proof-of-Work Protocols." Journal of Cybersecurity and Privacy 2, no. 2 (2022): 292–310. http://dx.doi.org/10.3390/jcp2020016.
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In blockchain-based systems whose consensus mechanisms resort to Proof-of-Work (PoW), it is expected that a miner’s share of total block revenue is proportional to their share of hashing power with respect to the rest of the network. The protocol relies on the immediate broadcast of blocks by miners, to earn precedence in peers’ local blockchains. However, a deviation from this strategy named selfish mining (SM), may lead miners to earn more than their “fair share”. In this paper, we introduce an agent-based model to simulate the dynamics of SM behaviour by a single miner as well as mining pools to understand the influence of (a) mining power distribution, (b) overlay network topology, (c) positioning of the selfish nodes within the peer to peer network. Our minimalistic model allows us to find that in high levels of latency, SM is always a more profitable strategy; our results are very robust to different network topologies and mining nodes’ centrality in the network. Moreover, the power-law distribution of the miners’ hashing power can make it harder for a selfish miner to be profitable. In addition, we analyze the effect of SM on system global efficiency and fairness. Our analysis confirms that SM is always more profitable for hashing powers representing more than one-third of the total computing power. Further, it also confirms that SM behaviour could cause a statistically significant high probability of continuously mined blocks opening the door for empirical verification of the phenomenon.
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Khanal, Jharana. "Alluvial mining and its impact on deterioration of physical health of Malekhu Khola, Central Nepal." Bulletin of the Department of Geology 18 (January 23, 2017): 59–66. http://dx.doi.org/10.3126/bdg.v18i0.16457.
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The Malekhu Khola is accessible and potential for the construction materials in today’s developing phase. The study mainly concerns with mining of construction aggregate and effect of indiscriminate mining from river and its basin area which may impose many harmful effects on environment. The objective of the study is to identify the condition of river using morphological and physical parameters, and to investigate the factors which are directly responsible for the environmental degradation. Such study of rivers in present context is essential as it provides insights of strength of the river. To examine the circumstance of river, the study was proceed by selecting the area into three reaches of each 500 m, and further each reaches are divided into six transects. Both reach-scale and transect-scale attributes were assessed. The scoring was done by adding all the attributes of the standard survey sheet. A cross-sectional study was carried out along 3 different stations, Reach 1 to Reach 3 from upstream to downstream. Various fluvial parameters and data from pebble count were used to calculate morphological parameter and grain size distribution. The channel sediments were found to be extremely poorly sorted, the distribution of grain size is varied from transect to transect, which might be the result of unplanned mining. All the result acquired from field study and satellite image confirms that the river is worsening day by day. The formation of pools and deposition of organic matter show that the river is not flowing in its natural way. After all the examination, it indicates that the Malekhu Khola is being violated by the human and mining activities, thus the river reclamation measure is required at abandoned mining sites to maintain the Malekhu Khola channel morphology and habitat of the river.Bulletin of the Department of Geology, Vol. 18, 2015, pp. 59-66
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Kim, Heesang, and Dohoon Kim. "Adjusting the Block Interval in PoW Consensus by Block Interval Process Improvement." Electronics 10, no. 17 (2021): 2135. http://dx.doi.org/10.3390/electronics10172135.
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Blockchain is not widely applied in various fields due to the critical issue of scalability as part of the blockchain trilemma. This issue arises during consensus among the nodes in a public blockchain. To address the issue of low scalability with proof-of-work (PoW) consensus, various methods have been proposed for transaction per second (TPS) improvement. However, no such methods include an improvement in the consensus step. Therefore, to improve PoW public blockchain scalability, it is important to shorten the time required for PoW consensus. This paper proposes a method for minimizing the block intervals that occur during consensus over a PoW blockchain network. A shortened block interval leads to an increase in the probability of three different attacks: selfish mining, double-spending, and eclipse attacks. According to an experiment using Ethereum, with a typical PoW blockchain, it is inevitable to provide rewards for stable block mining in competition between mining pools. To find an optimal block interval in the PoW consensus algorithm, we conducted a four-step experiment. The purpose of this experiment was to verify the difficulty level and issues with Mainnet security. Therefore, considering stale block mining rewards, an optimal block interval is proposed. The Ethereum TPS was improved by at least 200%. Given this finding, it is considered possible to achieve a similar improvement in a different PoW blockchain. On balance, even if the block interval is shorter than that of the PoW Mainnet, network security falls by only 1.21% in Testnet, even with a rise in the stale block rate, while performance is increased at up to 120 TPS, which is three times higher than that in Mainnet.
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Liu, Xiao, Zhao Huang, Quan Wang, Xiaohong Jiang, Yin Chen, and Bo Wan. "Analyzing Miners’ Dynamic Equilibrium in Blockchain Networks under DDoS Attacks." Electronics 12, no. 18 (2023): 3903. http://dx.doi.org/10.3390/electronics12183903.
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Proof of work (PoW) is one of the most widely used consensus algorithms in blockchain networks. It mainly uses the competition between mining nodes to obtain block rewards. However, this competition for computational power will allow malicious nodes to obtain illegal profits, bringing potential security threats to blockchain systems. A distributed denial of service (DDoS) attack is a major threat to the PoW algorithm. It utilizes multiple nodes in the blockchain network to attack honest miners to obtain illegal rewards. To solve this problem, academia has proposed a DDoS attack detection mechanism based on reinforcement learning methods and static game modeling methods based on mining pools. However, these methods cannot effectively make miners choose the strategy with the best profit over time when facing DDoS attacks. Therefore, this paper proposes a dynamic evolutionary game model for miners facing DDoS attacks under blockchain networks to solve the above problems for the first time. We address the model by replicating the dynamic equation to obtain a stable solution. According to the theorem of the Lyapunov method, we also obtain the only stable strategy for miners facing DDoS attacks. The experimental results show that compared with the static method, the dynamic method can affect game playing and game evolution over time. Moreover, miners’ strategy to face DDoS attacks gradually shifts from honest mining to launching DDoS attacks against each other as the blockchain network improves.
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Beran, Luboš, and Karel Beran. "Ranská jezírka – významná lokalita vodních měkkýšů na okraji Žďárských vrchů [Ranská jezírka – an important site of aquatic molluscs on the edge of the Žďárské vrchy]." Malacologica Bohemoslovaca 23 (June 6, 2024): 37–41. http://dx.doi.org/10.5817/mab2024-23-37.
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The Ranská jezírka are system of water bodies located in a forest complex on the western edge of the Žďárské vrchy PLA. These water bodies were created by flooding of depressions after surface mining of iron limonite ores. Currently, there are several larger and a number of smaller oligotrophic to mesotrophic pools covered with various types of littoral vegetation. Aquatic molluscs of this isolated and biologically interesting site were studied in 2023. In total, 15 species (6 gastropods and 9 bivalves) were found at 7 sites. Molluscan communities in water bodies with poorer vegetation were species-poor while water bodies more overgrown with littoral vegetation were inhabited by relatively species-richer communities. The rare and endangered bivalve Sphaerium nucleus was found. No non-native species were found.
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Gonzales, Eloy, Karla Taboada, Shingo Mabu, Kaoru Shimada, and Kotaro Hirasawa. "Combination of Two Evolutionary Methods for Mining Association Rules in Large and Dense Databases." Journal of Advanced Computational Intelligence and Intelligent Informatics 13, no. 5 (2009): 561–72. http://dx.doi.org/10.20965/jaciii.2009.p0561.
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Among several methods of extracting association rules that have been reported, a new evolutionary method named Genetic Network Programming (GNP) has also shown its effectiveness for small databases in the sense that they have a relatively small number of attributes. However, this conventional GNP method is not be able to deal with large databases with a huge number of attributes, because its search space becomes very large, causing bad performance at running time. The aim of this paper is to propose a new method to extract association rules from large and dense databases with a huge amount of attributes through the combination of conventional GNP based mining method and a specially designed genetic algorithm (GA). Each of these evolutionary methods works in its own processing level and they are highly synchronized to act as one system.Our strategy consists in the division of a large and dense database into many small databases. These small databases are considered as individuals and form a population. Then the conventional GNP based mining method is applied to extract association rules for each of these individuals. Finally, the population is evolved through several generations using GA with special genetic operators considering the acquired information. Two complementary processing levels are defined: Global Level and Local Level, each with its own independent tasks and processes. In the Global Level mainly GA process is carried out, whereas in the Local Level, conventional GNP based mining method is carried out in parallel and they generate their own local pools of association rules. Several special genetic operations for GA in the Global Level are proposed and the performance of each of them and their combination is shown and compared.In our simulations, the conventional GNP based mining method and our proposed method are compared using a real world large and dense database with a huge amount of attributes. The results show that extending the conventional GNP based mining method using GA allows to extract association rules from large and dense databases directly and more efficiently than the conventional GNP method.