Abuse filter log

Details for log entry 137,556

22:25, 30 March 2020: DarellTranter (talk | contribs) triggered filter 0, performing the action "edit" on User:DarellTranter. Actions taken: Warn; Filter description: (examine)

Changes made in edit

Action parameters

Variable	Value
Name of the user account `(user_name)`	'DarellTranter'
Age of the user account `(user_age)`	6750
Groups (including implicit) the user is in `(user_groups)`	[ 0 => '*', 1 => 'user', 2 => 'autoconfirmed' ]
Page ID `(page_id)`	0
Page namespace `(page_namespace)`	2
Page title (without namespace) `(page_title)`	'DarellTranter'
Full page title `(page_prefixedtitle)`	'User:DarellTranter'
Action `(action)`	'edit'
Edit summary/reason `(summary)`	''
Old content model `(old_content_model)`	''
New content model `(new_content_model)`	'wikitext'
Old page wikitext, before the edit `(old_wikitext)`	''
New page wikitext, after the edit `(new_wikitext)`	'As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another fee methodology that may change intermediaries with cryptographic strategies and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we propose to treatment this problem by using the methods originally developed for the computer-aided analysis for hardware and software programs, specifically those based on the timed automata. On this paper we introduce a instrument to review and analyze the UTXO set, together with a detailed description of the set format and performance. This paper gives an assessment of the present state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and [https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/ Bitcoin]. After this course, you’ll know every part you need to have the ability to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. We show the time-varying contribution ui(t) of the primary six base networks on determine 2. Generally, ui(t) features a couple of abrupt adjustments, partitioning the historical past of Bitcoin into separate time periods. In the initial section is excessive, fluctuating around (see Fig. 5), possibly a result of transactions happening between addresses belonging to some fans trying out the Bitcoin system by moving cash between their own addresses.<br><br>Review my web page: [https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien https://erfahrungenscout.de]'
Old page size `(old_size)`	0
All external links added in the edit `(added_links)`	[ 0 => 'https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/', 1 => 'https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien' ]
All external links in the new text `(all_links)`	[ 0 => 'https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/', 1 => 'https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien' ]
Links in the page, before the edit `(old_links)`	[]
Unix timestamp of change `(timestamp)`	1585607148


			As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. We argue that cryptocurrencies are another fee methodology that may change intermediaries with cryptographic strategies and must be embedded within the analysis areas of SIGeBIZ and SIGSEC. In this paper we propose to treatment this problem by using the methods originally developed for the computer-aided analysis for hardware and software programs, specifically those based on the timed automata. On this paper we introduce a instrument to review and analyze the UTXO set, together with a detailed description of the set format and performance. This paper gives an assessment of the present state of the literature. This systematic literature evaluation examines cryptocurrencies (CCs) and [https://www.steuergo.de/blog/bitcoin-und-steuern-wie-werden-kryptowaehrungen-versteuert/ Bitcoin]. After this course, you’ll know every part you need to have the ability to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. We show the time-varying contribution ui(t) of the primary six base networks on determine 2. Generally, ui(t) features a couple of abrupt adjustments, partitioning the historical past of Bitcoin into separate time periods. In the initial section is excessive, fluctuating around (see Fig. 5), possibly a result of transactions happening between addresses belonging to some fans trying out the Bitcoin system by moving cash between their own addresses.<br><br>Review my web page: [https://erfahrungenscout.de/nachrichten/passives-einkommen-mit-aktien https://erfahrungenscout.de]