nunoedgarmit Steem Profile

@nunoedgarmit

steemit.com/@nunoedgarmit

VOTING POWER100.00%

DOWNVOTE POWER100.00%

RESOURCE CREDITS100.00%

REPUTATION PROGRESS0.00%

Net Worth

0.452USD

STEEM

0.000STEEM

SBD

0.000SBD

Own SP

7.793SP

Detailed Balance

STEEM
balance	0.000STEEM	STEEM
market_balance	0.000STEEM	STEEM
savings_balance	0.000STEEM	STEEM
reward_steem_balance	0.000STEEM	STEEM
STEEM POWER
Own SP	7.793SP	SP
Delegated Out	0.000SP	SP
Delegation In	0.000SP	SP
Effective Power	7.793SP	SP
Reward SP (pending)	0.000SP	SP
SBD
sbd_balance	0.000SBD	SBD
sbd_conversions	0.000SBD	SBD
sbd_market_balance	0.000SBD	SBD
savings_sbd_balance	0.000SBD	SBD
reward_sbd_balance	0.000SBD	SBD

{
  "balance": "0.000 STEEM",
  "savings_balance": "0.000 STEEM",
  "reward_steem_balance": "0.000 STEEM",
  "vesting_shares": "12675.647784 VESTS",
  "delegated_vesting_shares": "0.000000 VESTS",
  "received_vesting_shares": "0.000000 VESTS",
  "sbd_balance": "0.000 SBD",
  "savings_sbd_balance": "0.000 SBD",
  "reward_sbd_balance": "0.000 SBD",
  "conversions": []
}

Account Info

name	nunoedgarmit
id	32013
rank	148,342
reputation	69348611
created	2016-07-23T20:19:30
recovery_account	steem
proxy	None
post_count	5
comment_count	0
lifetime_vote_count	0
witnesses_voted_for	0
last_post	2016-12-14T17:14:57
last_root_post	2016-12-14T17:14:57
last_vote_time	2016-12-14T17:14:57
proxied_vsf_votes	0, 0, 0, 0
can_vote	1
voting_power	9,950
delayed_votes	0
balance	0.000 STEEM
savings_balance	0.000 STEEM
sbd_balance	0.000 SBD
savings_sbd_balance	0.000 SBD
vesting_shares	12675.647784 VESTS
delegated_vesting_shares	0.000000 VESTS
received_vesting_shares	0.000000 VESTS
reward_vesting_balance	0.000000 VESTS
vesting_balance	0.000 STEEM
vesting_withdraw_rate	0.000000 VESTS
next_vesting_withdrawal	1969-12-31T23:59:59
withdrawn	0
to_withdraw	0
withdraw_routes	0
savings_withdraw_requests	0
last_account_recovery	1970-01-01T00:00:00
reset_account	null
last_owner_update	1970-01-01T00:00:00
last_account_update	1970-01-01T00:00:00
mined	No
sbd_seconds	0
sbd_last_interest_payment	1970-01-01T00:00:00
savings_sbd_last_interest_payment	1970-01-01T00:00:00

{
  "id": 32013,
  "name": "nunoedgarmit",
  "owner": {
    "weight_threshold": 1,
    "account_auths": [],
    "key_auths": [
      [
        "STM6MCXZim3ki1MpoL7fip9nqYZ4VPY89HBvzy4xifMfwmqtyi8vg",
        1
      ]
    ]
  },
  "active": {
    "weight_threshold": 1,
    "account_auths": [],
    "key_auths": [
      [
        "STM8fh9LYFqbR7aWKpGdo2Qi8TAtpHyypKNW9MV5F8jXx98M9nQf4",
        1
      ]
    ]
  },
  "posting": {
    "weight_threshold": 1,
    "account_auths": [],
    "key_auths": [
      [
        "STM7RbpyCTfJdAwADbUr4ZAFBxue3YqE3qeKEw12xMfxddnHT2QJ4",
        1
      ]
    ]
  },
  "memo_key": "STM5gGMTC1rxjT9GWF5DhzSMACj8QNor9FfM6JKda5hupdMhiDwKu",
  "json_metadata": "",
  "posting_json_metadata": "",
  "proxy": "",
  "last_owner_update": "1970-01-01T00:00:00",
  "last_account_update": "1970-01-01T00:00:00",
  "created": "2016-07-23T20:19:30",
  "mined": false,
  "recovery_account": "steem",
  "last_account_recovery": "1970-01-01T00:00:00",
  "reset_account": "null",
  "comment_count": 0,
  "lifetime_vote_count": 0,
  "post_count": 5,
  "can_vote": true,
  "voting_manabar": {
    "current_mana": 9950,
    "last_update_time": 1481735697
  },
  "downvote_manabar": {
    "current_mana": 0,
    "last_update_time": 1469305170
  },
  "voting_power": 9950,
  "balance": "0.000 STEEM",
  "savings_balance": "0.000 STEEM",
  "sbd_balance": "0.000 SBD",
  "sbd_seconds": "0",
  "sbd_seconds_last_update": "1970-01-01T00:00:00",
  "sbd_last_interest_payment": "1970-01-01T00:00:00",
  "savings_sbd_balance": "0.000 SBD",
  "savings_sbd_seconds": "0",
  "savings_sbd_seconds_last_update": "1970-01-01T00:00:00",
  "savings_sbd_last_interest_payment": "1970-01-01T00:00:00",
  "savings_withdraw_requests": 0,
  "reward_sbd_balance": "0.000 SBD",
  "reward_steem_balance": "0.000 STEEM",
  "reward_vesting_balance": "0.000000 VESTS",
  "reward_vesting_steem": "0.000 STEEM",
  "vesting_shares": "12675.647784 VESTS",
  "delegated_vesting_shares": "0.000000 VESTS",
  "received_vesting_shares": "0.000000 VESTS",
  "vesting_withdraw_rate": "0.000000 VESTS",
  "next_vesting_withdrawal": "1969-12-31T23:59:59",
  "withdrawn": 0,
  "to_withdraw": 0,
  "withdraw_routes": 0,
  "curation_rewards": 0,
  "posting_rewards": 0,
  "proxied_vsf_votes": [
    0,
    0,
    0,
    0
  ],
  "witnesses_voted_for": 0,
  "last_post": "2016-12-14T17:14:57",
  "last_root_post": "2016-12-14T17:14:57",
  "last_vote_time": "2016-12-14T17:14:57",
  "post_bandwidth": 10000,
  "pending_claimed_accounts": 0,
  "vesting_balance": "0.000 STEEM",
  "reputation": 69348611,
  "transfer_history": [],
  "market_history": [],
  "post_history": [],
  "vote_history": [],
  "other_history": [],
  "witness_votes": [],
  "tags_usage": [],
  "guest_bloggers": [],
  "rank": 148342
}

Withdraw Routes

Incoming	Outgoing
Empty	Empty

{
  "incoming": [],
  "outgoing": []
}

From Date

To Date

steemitboardreplied to @nunoedgarmit / steemitboard-notify-nunoedgarmit-20190723t204521000z

2019/07/23 20:45:21 UTC

34,923,631|85f4f18

author	steemitboard
body	Congratulations @nunoedgarmit! You received a personal award! <table><tr><td>https://steemitimages.com/70x70/http://steemitboard.com/@nunoedgarmit/birthday3.png</td><td>Happy Birthday! - You are on the Steem blockchain for 3 years!</td></tr></table> <sub>_You can view [your badges on your Steem Board](https://steemitboard.com/@nunoedgarmit) and compare to others on the [Steem Ranking](https://steemitboard.com/ranking/index.php?name=nunoedgarmit)_</sub> ###### [Vote for @Steemitboard as a witness](https://v2.steemconnect.com/sign/account-witness-vote?witness=steemitboard&approve=1) to get one more award and increased upvotes!
json metadata	{"image":["https://steemitboard.com/img/notify.png"]}
parent author	nunoedgarmit
parent permlink	neuroscience-of-brain-age-with-deep-learning
permlink	steemitboard-notify-nunoedgarmit-20190723t204521000z
title
Transaction Info	Block #34923631/Trx 85f4f18ac49d98bebeca16d0a12ea23b1c6f6d2a

View Raw JSON Data

{
  "block": 34923631,
  "op": [
    "comment",
    {
      "author": "steemitboard",
      "body": "Congratulations @nunoedgarmit! You received a personal award!\n\n<table><tr><td>https://steemitimages.com/70x70/http://steemitboard.com/@nunoedgarmit/birthday3.png</td><td>Happy Birthday! - You are on the Steem blockchain for 3 years!</td></tr></table>\n\n<sub>_You can view [your badges on your Steem Board](https://steemitboard.com/@nunoedgarmit) and compare to others on the [Steem Ranking](https://steemitboard.com/ranking/index.php?name=nunoedgarmit)_</sub>\n\n\n###### [Vote for @Steemitboard as a witness](https://v2.steemconnect.com/sign/account-witness-vote?witness=steemitboard&approve=1) to get one more award and increased upvotes!",
      "json_metadata": "{\"image\":[\"https://steemitboard.com/img/notify.png\"]}",
      "parent_author": "nunoedgarmit",
      "parent_permlink": "neuroscience-of-brain-age-with-deep-learning",
      "permlink": "steemitboard-notify-nunoedgarmit-20190723t204521000z",
      "title": ""
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2019-07-23T20:45:21",
  "trx_id": "85f4f18ac49d98bebeca16d0a12ea23b1c6f6d2a",
  "trx_in_block": 10,
  "virtual_op": 0
}

majnunupvoted (100.00%) @nunoedgarmit / deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk

2017/06/22 23:40:51 UTC

13,056,725|c43a55b

author	nunoedgarmit
permlink	deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk
voter	majnun
weight	10000 (100.00%)
Transaction Info	Block #13056725/Trx c43a55b833ab0382583e363a08f23a5d818d7e11

View Raw JSON Data

{
  "block": 13056725,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk",
      "voter": "majnun",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2017-06-22T23:40:51",
  "trx_id": "c43a55b833ab0382583e363a08f23a5d818d7e11",
  "trx_in_block": 13,
  "virtual_op": 0
}

micalithupvoted (100.00%) @nunoedgarmit / neuroscience-of-brain-age-with-deep-learning

2017/03/03 11:17:18 UTC

9,848,587|ad8361b

author	nunoedgarmit
permlink	neuroscience-of-brain-age-with-deep-learning
voter	micalith
weight	10000 (100.00%)
Transaction Info	Block #9848587/Trx ad8361b4fe124b543dae3857c458b76022d33b49

View Raw JSON Data

{
  "block": 9848587,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "neuroscience-of-brain-age-with-deep-learning",
      "voter": "micalith",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2017-03-03T11:17:18",
  "trx_id": "ad8361b4fe124b543dae3857c458b76022d33b49",
  "trx_in_block": 4,
  "virtual_op": 0
}

steemplayupvoted (100.00%) @nunoedgarmit / neuroscience-of-brain-age-with-deep-learning

2016/12/14 17:36:00 UTC

7,584,414|fbda469

author	nunoedgarmit
permlink	neuroscience-of-brain-age-with-deep-learning
voter	steemplay
weight	10000 (100.00%)
Transaction Info	Block #7584414/Trx fbda469b127330a263d8663830ebcc4f3f40bda7

View Raw JSON Data

{
  "block": 7584414,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "neuroscience-of-brain-age-with-deep-learning",
      "voter": "steemplay",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-14T17:36:00",
  "trx_id": "fbda469b127330a263d8663830ebcc4f3f40bda7",
  "trx_in_block": 2,
  "virtual_op": 0
}

sindyupvoted (100.00%) @nunoedgarmit / neuroscience-of-brain-age-with-deep-learning

2016/12/14 17:21:09 UTC

7,584,118|a679315

author	nunoedgarmit
permlink	neuroscience-of-brain-age-with-deep-learning
voter	sindy
weight	10000 (100.00%)
Transaction Info	Block #7584118/Trx a6793155ab216d69fac8432f3e308fec2e266fca

View Raw JSON Data

{
  "block": 7584118,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "neuroscience-of-brain-age-with-deep-learning",
      "voter": "sindy",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-14T17:21:09",
  "trx_id": "a6793155ab216d69fac8432f3e308fec2e266fca",
  "trx_in_block": 6,
  "virtual_op": 0
}

blhzupvoted (100.00%) @nunoedgarmit / neuroscience-of-brain-age-with-deep-learning

2016/12/14 17:15:48 UTC

7,584,011|5091fe1

author	nunoedgarmit
permlink	neuroscience-of-brain-age-with-deep-learning
voter	blhz
weight	10000 (100.00%)
Transaction Info	Block #7584011/Trx 5091fe1e2452f90e09f68a9c56f2b6aff5a61d17

View Raw JSON Data

{
  "block": 7584011,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "neuroscience-of-brain-age-with-deep-learning",
      "voter": "blhz",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-14T17:15:48",
  "trx_id": "5091fe1e2452f90e09f68a9c56f2b6aff5a61d17",
  "trx_in_block": 4,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @nunoedgarmit / neuroscience-of-brain-age-with-deep-learning

2016/12/14 17:14:57 UTC

7,583,994|fb67f48

author	nunoedgarmit
permlink	neuroscience-of-brain-age-with-deep-learning
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #7583994/Trx fb67f4861dcde8d6012b1ce806d3218069607ce8

View Raw JSON Data

{
  "block": 7583994,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "neuroscience-of-brain-age-with-deep-learning",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-14T17:14:57",
  "trx_id": "fb67f4861dcde8d6012b1ce806d3218069607ce8",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitupdated options for neuroscience-of-brain-age-with-deep-learning

2016/12/14 17:14:57 UTC

7,583,994|fb67f48

allow curation rewards	true
allow votes	true
author	nunoedgarmit
extensions	[]
max accepted payout	1000000.000 SBD
percent steem dollars	0
permlink	neuroscience-of-brain-age-with-deep-learning
Transaction Info	Block #7583994/Trx fb67f4861dcde8d6012b1ce806d3218069607ce8

View Raw JSON Data

{
  "block": 7583994,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "nunoedgarmit",
      "extensions": [],
      "max_accepted_payout": "1000000.000 SBD",
      "percent_steem_dollars": 0,
      "permlink": "neuroscience-of-brain-age-with-deep-learning"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-14T17:14:57",
  "trx_id": "fb67f4861dcde8d6012b1ce806d3218069607ce8",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitpublished a new post: neuroscience-of-brain-age-with-deep-learning

2016/12/14 17:14:57 UTC

7,583,994|fb67f48

author	nunoedgarmit
body	<html> <p> The human brain is the most complex object known in the Universe. At least for exactly whom is able to know – and the only known entities known to be that able are humans, at least as the current common knowledge asserts. It is a complex entangled web of organic tissue composed of an incredible diversity of cells connected in numerous ways, communicating with each other with still more complex processes. It is quite a remarkable machine.</p> <p><br></p> <p>But the human brain, like all other tissues in the human body, decays with age. The older brain does not have the performance of the younger one. Despite this, this astonishing organ displays another characteristic that may compensate for the effects of age: it is plastic, this meaning that it can change and explore in on itself different network configurations and change how their networks are connected. At least up to a point. On the counterpart to that capacity it is the recognition that plasticity is not always synonym of better performance; it just that the right set of combinations and circumstances afford increasing performance with a highly plastic brain.</p> <p><br></p> <p>With this said I present here another remarkable research paper found and reviewed by the <a href="https://www.technologyreview.com/s/603112/deep-learning-machine-uses-mri-scans-to-determine-your-brain-age/?utm_campaign=newsletters&utm_source=newsletter-weekly-robotics&utm_medium=email&utm_content=20161214&utm_source=MIT+TR+Newsletters&utm_campaign=46a4d8fff1-EMAIL_CAMPAIGN_2016_12_14&utm_medium=email&utm_term=0_997ed6f472-46a4d8fff1-153668585&goal=0_997ed6f472-46a4d8fff1-153668585&mc_cid=46a4d8fff1&mc_eid=39e517483b">MIT Technology Review</a> weekly paper round-up. It is accordingly about the determination of the human brain age using the current state-of-the-art developments within deep learning research and techniques. It is fascinating read, just the review, but the review itself definitely encourages, open the appetite to read the full paper. Interestingly one outcome of the paper is how deep learning techniques beats a traditional statistical method known as<a href="https://en.wikipedia.org/wiki/Gaussian_process"> Gaussian process regression</a> in determining brain age, by a wide margin, with increased speed and minimal requirements. </p> <p><br></p> <p> </p> <h3><a href="https://arxiv.org/ftp/arxiv/papers/1612/1612.02572.pdf"><strong>Predicting Brain Age with Deep Learning from Raw Imaging Data Results in a Reliable and Heritable Biomarker</strong></a> </h3> <p><br></p> <p> Of note is also the confirmation of links between early brain age with conditions such as diabetes, schizophrenia and traumatic brain injury. So this is a promising result for clinicians of brain health, providing these professionals with one more diagnostic tool that may help them reach a better decision for treatment prescription. </p> <p><br></p> </html>
json metadata	{"tags":["neuroscience","deep","learning"],"links":["https://www.technologyreview.com/s/603112/deep-learning-machine-uses-mri-scans-to-determine-your-brain-age/?utm_campaign=newsletters&utm_source=newsletter-weekly-robotics&utm_medium=email&utm_content=20161214&utm_source=MIT+TR+Newsletters&utm_campaign=46a4d8fff1-EMAIL_CAMPAIGN_2016_12_14&utm_medium=email&utm_term=0_997ed6f472-46a4d8fff1-153668585&goal=0_997ed6f472-46a4d8fff1-153668585&mc_cid=46a4d8fff1&mc_eid=39e517483b","https://en.wikipedia.org/wiki/Gaussian_process","https://arxiv.org/ftp/arxiv/papers/1612/1612.02572.pdf"],"app":"steemit/0.1","format":"html"}
parent author
parent permlink	neuroscience
permlink	neuroscience-of-brain-age-with-deep-learning
title	Neuroscience of brain age with deep learning
Transaction Info	Block #7583994/Trx fb67f4861dcde8d6012b1ce806d3218069607ce8

View Raw JSON Data

{
  "block": 7583994,
  "op": [
    "comment",
    {
      "author": "nunoedgarmit",
      "body": "<html>\n<p>&nbsp;The human brain is the most complex object known in the Universe. At least for exactly whom is able to know – and the only known entities known to be that able are humans, at least as the current common knowledge asserts. It is a complex entangled web of organic tissue composed of an incredible diversity of cells connected in numerous ways, communicating&nbsp;with each other with still more complex processes. It is quite a remarkable machine.</p>\n<p><br></p>\n<p>But the human brain, like all other tissues in the human body, decays with age. The older brain does not have the performance of the younger one. Despite this, this astonishing organ displays another characteristic that may compensate for the effects of age: it is&nbsp;plastic, this meaning that it can change and explore in on itself different network configurations and change&nbsp;how their networks are connected. At least up to a point. On the counterpart to that capacity it is the recognition that plasticity is not always synonym of better performance; it just that the right set of combinations and circumstances afford increasing performance with a highly plastic brain.</p>\n<p><br></p>\n<p>With this said I present here another remarkable research paper found and reviewed by the <a href=\"https://www.technologyreview.com/s/603112/deep-learning-machine-uses-mri-scans-to-determine-your-brain-age/?utm_campaign=newsletters&amp;utm_source=newsletter-weekly-robotics&amp;utm_medium=email&amp;utm_content=20161214&amp;utm_source=MIT+TR+Newsletters&amp;utm_campaign=46a4d8fff1-EMAIL_CAMPAIGN_2016_12_14&amp;utm_medium=email&amp;utm_term=0_997ed6f472-46a4d8fff1-153668585&amp;goal=0_997ed6f472-46a4d8fff1-153668585&amp;mc_cid=46a4d8fff1&amp;mc_eid=39e517483b\">MIT Technology Review</a> weekly paper round-up. It is accordingly about the determination of the human brain age using the current state-of-the-art developments within deep learning research and techniques. It is fascinating read, just the review, but the review itself definitely encourages, open the appetite to read the full paper. Interestingly one outcome of the paper is how deep learning techniques beats a traditional statistical method known as<a href=\"https://en.wikipedia.org/wiki/Gaussian_process\"> Gaussian process regression</a> in determining brain age, by a wide margin, with increased speed and minimal requirements.&nbsp;</p>\n<p><br></p>\n<p>&nbsp;</p>\n<h3><a href=\"https://arxiv.org/ftp/arxiv/papers/1612/1612.02572.pdf\"><strong>Predicting Brain Age with Deep Learning from Raw Imaging Data Results in a Reliable and Heritable Biomarker</strong></a>&nbsp;</h3>\n<p><br></p>\n<p>&nbsp;Of note is also the confirmation of links between early brain age with conditions such as diabetes, schizophrenia and traumatic brain injury. So this is a promising result for clinicians of brain health, providing these professionals with one more diagnostic tool that may help them reach a better decision for treatment prescription.&nbsp;</p>\n<p><br></p>\n</html>",
      "json_metadata": "{\"tags\":[\"neuroscience\",\"deep\",\"learning\"],\"links\":[\"https://www.technologyreview.com/s/603112/deep-learning-machine-uses-mri-scans-to-determine-your-brain-age/?utm_campaign=newsletters&utm_source=newsletter-weekly-robotics&utm_medium=email&utm_content=20161214&utm_source=MIT+TR+Newsletters&utm_campaign=46a4d8fff1-EMAIL_CAMPAIGN_2016_12_14&utm_medium=email&utm_term=0_997ed6f472-46a4d8fff1-153668585&goal=0_997ed6f472-46a4d8fff1-153668585&mc_cid=46a4d8fff1&mc_eid=39e517483b\",\"https://en.wikipedia.org/wiki/Gaussian_process\",\"https://arxiv.org/ftp/arxiv/papers/1612/1612.02572.pdf\"],\"app\":\"steemit/0.1\",\"format\":\"html\"}",
      "parent_author": "",
      "parent_permlink": "neuroscience",
      "permlink": "neuroscience-of-brain-age-with-deep-learning",
      "title": "Neuroscience of brain age with deep learning"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-14T17:14:57",
  "trx_id": "fb67f4861dcde8d6012b1ce806d3218069607ce8",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @nunoedgarmit / bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review

2016/12/14 11:44:18 UTC

7,577,390|b9d4df6

author	nunoedgarmit
permlink	bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #7577390/Trx b9d4df60794f809476cd33bd75eb94ebb1387911

View Raw JSON Data

{
  "block": 7577390,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-14T11:44:18",
  "trx_id": "b9d4df60794f809476cd33bd75eb94ebb1387911",
  "trx_in_block": 0,
  "virtual_op": 0
}

nunoedgarmitfollowed @antro735

2016/12/01 16:25:09 UTC

7,210,182|b7bd6d3

id	follow
json	["follow",{"follower":"nunoedgarmit","following":"antro735","what":["blog"]}]
required auths	[]
required posting auths	["nunoedgarmit"]
Transaction Info	Block #7210182/Trx b7bd6d32d0789a6f99f07984bfde072eebba03cd

View Raw JSON Data

{
  "block": 7210182,
  "op": [
    "custom_json",
    {
      "id": "follow",
      "json": "[\"follow\",{\"follower\":\"nunoedgarmit\",\"following\":\"antro735\",\"what\":[\"blog\"]}]",
      "required_auths": [],
      "required_posting_auths": [
        "nunoedgarmit"
      ]
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-01T16:25:09",
  "trx_id": "b7bd6d32d0789a6f99f07984bfde072eebba03cd",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @nunoedgarmit / deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk

2016/12/01 16:24:09 UTC

7,210,162|7370696

author	nunoedgarmit
permlink	deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #7210162/Trx 7370696a446b412a2e2f22a0fa14af87979ddcdb

View Raw JSON Data

{
  "block": 7210162,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-01T16:24:09",
  "trx_id": "7370696a446b412a2e2f22a0fa14af87979ddcdb",
  "trx_in_block": 10,
  "virtual_op": 0
}

nunoedgarmitpublished a new post: deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk

2016/12/01 16:24:09 UTC

7,210,162|7370696

author	nunoedgarmit
body	<html> <p> I will share a video featured in the last September 2016 Deep Learning in Finance Summit held in London. This will also serve as a needed interval from the paper review series. I think it to be wise choice. This Blog was not meant to be a daily paper review Blog.</p> <p><br></p> <p>I am also aware of yesterday’s mistakes I’ve made in the paper review post. I was doing the post a little bit too much excited and in a hurry… I will need to be more careful regarding the use of the English Language, will try to read carefully before posting from now on, and also recognize the need to properly read through the papers before posting. That is easier said than done, specially when you feel the rush to post.</p> <p><br></p> <p>So today’s post depart a bit from that stress to present a very nice talk held at the last Deep Learning in Finance Summit. This is form September this year, so it is quite fresh thinking and an update to the state-of-the-art on this subject. The speaker is Peter Sarlin from <a href="https://www.hanken.fi/en">Hanken School of Economics,</a> a Finnish Economics Higher Education Institution. Peter has extensive experience as a deep learning practitioner in the context of economics and finance having had experience in the subject before in the context of analysis of vulnerable systems in general.</p> <p><br></p> <p>In the video it is presented a link to the paper on systemic risk called  <a href="https://arxiv.org/abs/1601.06204">RiskRank: Measuring interconnected risk</a> that serves as the underlying background for the points Dr. Peter Sarlin talks about. This is recommended reading. Of note also is the work that Dr. Peter’s company  <a href="http://risklab.fi/">RiskLab</a> together with a <a href="http://cm.infolytika.com/login">financial risk analytics venture firm</a> have done in joint venture with European central bank institutions like the European Central Bank (ECB). </p> <p><br></p> <p> </p> <h1><a href="https://www.youtube.com/watch?v=Fd7Cc-KOVXg">Peter Sarlin, Hanken School of Economics - Deep Learning in Finance Summit 2016 #reworkfin</a></h1> <p><br></p> <p> </p> <p>An important remark from this talk is the fact that Dr. Sarlin emphasizes the greater need to a better human-machine interaction understanding. That understanding nowadays isn’t just a question of the practitioner or professional in deep learning implementation/ deployment or the artificial intelligence developer. It is also related with the economic/financial agent in general, that today is more and more a human-machine interaction. But, as it is pointed out, machines will need to improve their understanding of how humans interact with other humans as well.</p> <p><br></p> <p>A final comment on one specific deep learning system in the talk: <a href="http://almaxanalytics.com/">Almax Analytics </a>– semantic deep learning. This appeared to be a state of the art framework to analyse unstructured news articles form the wide media applied here to the European banking sector. It turns that unstructured data in a supervised dataset able to spot stress (negative impact) levels in that specific article. </p> <p><a href="https://www.youtube.com/user/teamrework"> </a></p> <p><br></p> </html>
json metadata	{"tags":["deep","learning","finance"],"links":["https://www.hanken.fi/en","https://arxiv.org/abs/1601.06204","http://risklab.fi/","http://cm.infolytika.com/login","https://www.youtube.com/watch?v=Fd7Cc-KOVXg","http://almaxanalytics.com/","https://www.youtube.com/user/teamrework"],"app":"steemit/0.1","format":"html"}
parent author
parent permlink	deep
permlink	deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk
title	Deep Learning in Finance Summit 2016 #reworkfin – Peter Sarlin talk
Transaction Info	Block #7210162/Trx 7370696a446b412a2e2f22a0fa14af87979ddcdb

View Raw JSON Data

{
  "block": 7210162,
  "op": [
    "comment",
    {
      "author": "nunoedgarmit",
      "body": "<html>\n<p>&nbsp;I will share a video featured in the last September 2016 Deep Learning in Finance Summit held in London. This will also serve as a needed interval from the paper review series. I think it to be wise choice. This Blog was not meant to be a daily paper review Blog.</p>\n<p><br></p>\n<p>I am also aware of yesterday’s mistakes I’ve made in the paper review post. I was doing the post a little bit too much excited and in a hurry… I will need to be more careful regarding the use of the English Language, will try to read carefully before posting from now on, and also recognize the need to properly read through the papers before posting. That is easier said than done, specially when you feel the rush to post.</p>\n<p><br></p>\n<p>So today’s post depart a bit from that stress to present a very nice talk held at the last Deep Learning in Finance Summit. This is form September this year, so it is quite fresh thinking and an update to the state-of-the-art on this subject. The speaker is Peter Sarlin from <a href=\"https://www.hanken.fi/en\">Hanken School of Economics,</a> a Finnish Economics Higher Education Institution. Peter has extensive experience as a deep learning practitioner in the context of economics and finance having had experience in the subject before in the context of analysis of vulnerable systems in general.</p>\n<p><br></p>\n<p>In the video it is presented a link to the paper on systemic risk called &nbsp;<a href=\"https://arxiv.org/abs/1601.06204\">RiskRank: Measuring interconnected risk</a>&nbsp;that serves as the underlying background for the points Dr. Peter Sarlin talks about. This is recommended reading. Of note also is the work that Dr. Peter’s company &nbsp;<a href=\"http://risklab.fi/\">RiskLab</a> together with a <a href=\"http://cm.infolytika.com/login\">financial risk analytics venture firm</a> have done in joint venture with European central bank institutions like the European Central Bank (ECB).&nbsp;</p>\n<p><br></p>\n<p>&nbsp;</p>\n<h1><a href=\"https://www.youtube.com/watch?v=Fd7Cc-KOVXg\">Peter Sarlin, Hanken School of Economics - Deep Learning in Finance Summit 2016 #reworkfin</a></h1>\n<p><br></p>\n<p>&nbsp;</p>\n<p>An important remark from this talk is the fact that Dr. Sarlin emphasizes the greater need to a better human-machine interaction understanding. That understanding nowadays isn’t just a question of the practitioner or professional in deep learning implementation/ deployment or the artificial intelligence developer. It is also related with the economic/financial agent in general, that today is more and more a human-machine interaction. But, as it is pointed out, machines will need to improve their understanding of how humans interact with other humans as well.</p>\n<p><br></p>\n<p>A final comment on one specific deep learning system in the talk: <a href=\"http://almaxanalytics.com/\">Almax Analytics </a>– semantic deep learning. This appeared to be a state of the art framework to analyse unstructured news articles form the wide media applied here to the European banking sector. It turns that unstructured data in a supervised dataset able to spot stress (negative impact) levels in that specific article.&nbsp;</p>\n<p><a href=\"https://www.youtube.com/user/teamrework\">&nbsp;</a></p>\n<p><br></p>\n</html>",
      "json_metadata": "{\"tags\":[\"deep\",\"learning\",\"finance\"],\"links\":[\"https://www.hanken.fi/en\",\"https://arxiv.org/abs/1601.06204\",\"http://risklab.fi/\",\"http://cm.infolytika.com/login\",\"https://www.youtube.com/watch?v=Fd7Cc-KOVXg\",\"http://almaxanalytics.com/\",\"https://www.youtube.com/user/teamrework\"],\"app\":\"steemit/0.1\",\"format\":\"html\"}",
      "parent_author": "",
      "parent_permlink": "deep",
      "permlink": "deep-learning-in-finance-summit-2016-reworkfin-peter-sarlin-talk",
      "title": "Deep Learning in Finance Summit 2016 #reworkfin – Peter Sarlin talk"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-12-01T16:24:09",
  "trx_id": "7370696a446b412a2e2f22a0fa14af87979ddcdb",
  "trx_in_block": 10,
  "virtual_op": 0
}

jluferupvoted (100.00%) @nunoedgarmit / on-data-literacy-and-the-blogosphere

2016/11/22 16:51:33 UTC

6,951,819|a123859

author	nunoedgarmit
permlink	on-data-literacy-and-the-blogosphere
voter	jlufer
weight	10000 (100.00%)
Transaction Info	Block #6951819/Trx a123859b9f80f3a86db1a0335da09e51bdb41922

View Raw JSON Data

{
  "block": 6951819,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "on-data-literacy-and-the-blogosphere",
      "voter": "jlufer",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:51:33",
  "trx_id": "a123859b9f80f3a86db1a0335da09e51bdb41922",
  "trx_in_block": 3,
  "virtual_op": 0
}

nunoedgarmitupdated options for on-data-literacy-and-the-blogosphere

2016/11/22 16:48:51 UTC

6,951,765|5cd2043

allow curation rewards	true
allow votes	true
author	nunoedgarmit
extensions	[]
max accepted payout	1000000.000 SBD
percent steem dollars	0
permlink	on-data-literacy-and-the-blogosphere
Transaction Info	Block #6951765/Trx 5cd20436f931eb744e1bbfd9733fd7805894177f

View Raw JSON Data

{
  "block": 6951765,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "nunoedgarmit",
      "extensions": [],
      "max_accepted_payout": "1000000.000 SBD",
      "percent_steem_dollars": 0,
      "permlink": "on-data-literacy-and-the-blogosphere"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:48:51",
  "trx_id": "5cd20436f931eb744e1bbfd9733fd7805894177f",
  "trx_in_block": 2,
  "virtual_op": 0
}

nunoedgarmitpublished a new post: on-data-literacy-and-the-blogosphere

2016/11/22 16:48:51 UTC

6,951,765|5cd2043

author	nunoedgarmit
body	@@ -2459,16 +2459,1209 @@ br%3E%3C/p%3E%0A +%3Cp%3E(...)%3C/p%3E%0A%3Cp%3E%3Cbr%3E%3C/p%3E%0A%3Cp%3E %3C/p%3E%0A%3Ch3%3EConcluding remarks%3C/h3%3E%0A%3Cp%3E%3Cbr%3E%3C/p%3E%0A%3Cp%3EThis was a post from the Blog that I found through R Bloggers aggregator. The Blog is called Data Literacy - the blog of Andr%C3%A9s Guti%C3%A9rrez. The name of the blog caught my attention, as well as its epigraph by Herbert G. Wells. The important point to mention here:%3C/p%3E%0A%3Cul%3E%0A %3Cli%3EData Literacy is an important topic of study where the resources available are cheap to access. Nevertheless the learning is hard and the computing framework of the R programming language is a steep one%3C/li%3E%0A %3Cli%3ELeaning statistics may be a nice way to learn how to think about the complex reality surrounding us from every corner that we want to look upon. It is full of paradoxes such as the one presented in this post. But I think it is with this kind of hard reasoning and problem solving mindset that we better prepare ourselves to any challenge%3C/li%3E%0A %3Cli%3EThe open source community around Data Science and the R programming language may compensate for the shortcomings of our often enough contradictory human societies%3C/li%3E%0A%3C/ul%3E%0A%3Cp%3EFarewell to the data science community around aggregators such as R Bloggers. %3C/p%3E%0A %3Cp%3ENote
json metadata	{"tags":["r","bloggers"],"links":["https://www.r-bloggers.com/","http://hagutierrezro.blogspot.pt/2016/11/lord-paradox-in-r.html"],"app":"steemit/0.1","format":"html"}
parent author
parent permlink	r
permlink	on-data-literacy-and-the-blogosphere
title	On Data Literacy and the Blogosphere
Transaction Info	Block #6951765/Trx 5cd20436f931eb744e1bbfd9733fd7805894177f

View Raw JSON Data

{
  "block": 6951765,
  "op": [
    "comment",
    {
      "author": "nunoedgarmit",
      "body": "@@ -2459,16 +2459,1209 @@\n br%3E%3C/p%3E%0A\n+%3Cp%3E(...)%3C/p%3E%0A%3Cp%3E%3Cbr%3E%3C/p%3E%0A%3Cp%3E&nbsp;%3C/p%3E%0A%3Ch3%3EConcluding remarks%3C/h3%3E%0A%3Cp%3E%3Cbr%3E%3C/p%3E%0A%3Cp%3EThis was a post from the Blog that I found through R Bloggers aggregator. The Blog is called Data Literacy - the blog of Andr%C3%A9s Guti%C3%A9rrez. The name of the blog caught my attention, as well as its epigraph by Herbert G. Wells. The important point to mention here:%3C/p%3E%0A%3Cul%3E%0A  %3Cli%3EData Literacy is an important topic of study where the resources available are cheap to access. Nevertheless the learning is hard and the computing framework of the R programming language is a steep one%3C/li%3E%0A  %3Cli%3ELeaning statistics may be a nice way to learn how to think about the complex reality surrounding us from&nbsp;every corner that we want to look upon. It is full of paradoxes such as the one presented in this post. But I think it is with this kind of hard reasoning and problem solving mindset that we better prepare ourselves to any challenge%3C/li%3E%0A  %3Cli%3EThe open source community around Data Science and the R programming language may compensate for the shortcomings of our often enough contradictory human societies%3C/li%3E%0A%3C/ul%3E%0A%3Cp%3EFarewell to the data science community around aggregators such as R Bloggers.&nbsp;%3C/p%3E%0A\n %3Cp%3ENote \n",
      "json_metadata": "{\"tags\":[\"r\",\"bloggers\"],\"links\":[\"https://www.r-bloggers.com/\",\"http://hagutierrezro.blogspot.pt/2016/11/lord-paradox-in-r.html\"],\"app\":\"steemit/0.1\",\"format\":\"html\"}",
      "parent_author": "",
      "parent_permlink": "r",
      "permlink": "on-data-literacy-and-the-blogosphere",
      "title": "On Data Literacy and the Blogosphere"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:48:51",
  "trx_id": "5cd20436f931eb744e1bbfd9733fd7805894177f",
  "trx_in_block": 2,
  "virtual_op": 0
}

antro735upvoted (100.00%) @nunoedgarmit / real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust

2016/11/22 16:46:15 UTC

6,951,713|cc6f091

author	nunoedgarmit
permlink	real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust
voter	antro735
weight	10000 (100.00%)
Transaction Info	Block #6951713/Trx cc6f091da3ff84689741a54208a779ea1e5cf088

View Raw JSON Data

{
  "block": 6951713,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust",
      "voter": "antro735",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:46:15",
  "trx_id": "cc6f091da3ff84689741a54208a779ea1e5cf088",
  "trx_in_block": 2,
  "virtual_op": 0
}

antro735upvoted (100.00%) @nunoedgarmit / bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review

2016/11/22 16:46:12 UTC

6,951,712|9d817d6

author	nunoedgarmit
permlink	bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review
voter	antro735
weight	10000 (100.00%)
Transaction Info	Block #6951712/Trx 9d817d6205ef99ec6f006451219f9ada2f8bbbc4

View Raw JSON Data

{
  "block": 6951712,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review",
      "voter": "antro735",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:46:12",
  "trx_id": "9d817d6205ef99ec6f006451219f9ada2f8bbbc4",
  "trx_in_block": 2,
  "virtual_op": 0
}

antro735upvoted (100.00%) @nunoedgarmit / on-data-literacy-and-the-blogosphere

2016/11/22 16:45:57 UTC

6,951,707|1035bd8

author	nunoedgarmit
permlink	on-data-literacy-and-the-blogosphere
voter	antro735
weight	10000 (100.00%)
Transaction Info	Block #6951707/Trx 1035bd88d1540e2b1aa7e86444cc504551f87cd0

View Raw JSON Data

{
  "block": 6951707,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "on-data-literacy-and-the-blogosphere",
      "voter": "antro735",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:45:57",
  "trx_id": "1035bd88d1540e2b1aa7e86444cc504551f87cd0",
  "trx_in_block": 3,
  "virtual_op": 0
}

nunoedgarmitupdated options for on-data-literacy-and-the-blogosphere

2016/11/22 16:45:27 UTC

6,951,697|4b24003

allow curation rewards	true
allow votes	true
author	nunoedgarmit
extensions	[]
max accepted payout	1000000.000 SBD
percent steem dollars	0
permlink	on-data-literacy-and-the-blogosphere
Transaction Info	Block #6951697/Trx 4b24003713f73c358534852a1efed57b73aea0b1

View Raw JSON Data

{
  "block": 6951697,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "nunoedgarmit",
      "extensions": [],
      "max_accepted_payout": "1000000.000 SBD",
      "percent_steem_dollars": 0,
      "permlink": "on-data-literacy-and-the-blogosphere"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:45:27",
  "trx_id": "4b24003713f73c358534852a1efed57b73aea0b1",
  "trx_in_block": 2,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @nunoedgarmit / on-data-literacy-and-the-blogosphere

2016/11/22 16:45:27 UTC

6,951,697|4b24003

author	nunoedgarmit
permlink	on-data-literacy-and-the-blogosphere
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #6951697/Trx 4b24003713f73c358534852a1efed57b73aea0b1

View Raw JSON Data

{
  "block": 6951697,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "on-data-literacy-and-the-blogosphere",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:45:27",
  "trx_id": "4b24003713f73c358534852a1efed57b73aea0b1",
  "trx_in_block": 2,
  "virtual_op": 0
}

nunoedgarmitpublished a new post: on-data-literacy-and-the-blogosphere

2016/11/22 16:45:27 UTC

6,951,697|4b24003

author	nunoedgarmit
body	<html> <p> I am a keen follower of the blog aggregator about the R programming language and Data Science named <a href="https://www.r-bloggers.com/">R Bloggers</a>. It is a very resource to look for all about the possibilities of this statistical programming language that is a standard in the field, and specially for the more advanced researchers. It has got some steep learning curve, so it is advisable to learn a lot about statiscal concepts and reasoning before diving in this language. It is also important to know about programming. But the open source commitment by the developers of the language and the wide community of users provides for a nice open and plentiful trove of resources.<br> I receive e-mails form <a href="https://www.r-bloggers.com/">R Bloggers</a> every single day of the week. And every day, be it  a weekday, Saturdays, Sundays or Holidays, there is always good posts, with some about a  new technique, another about a new perspective other on a relevant resource or innovative way of dealing with R and its main applications and so on... Not admissible to miss.And today was one of those days when I found an article from <a href="https://www.r-bloggers.com/">R Bloggers</a> that caught my attention again. This time the name of the blog and the article title were the triggers.  After reading the content of the post I thought I should share and reproduce part of it, for it is about the importance of Data Literacy, knowledge about statistics and what this means for the XXI Century. We are living through an age where the knowledge of these subjects is increasing, but where the mismatches as to what society needs to know and what it really knows about the subjects in question are also increasing. And this is having wide economic impacts as companies and organizations started complaining about these mismatches. On a counterfactual tone, if there is a mismatch, there is also as never before all the resources needed to bridge all the gaps, and if this isn't happening with the desired frequency, then the reasons may be of a different nature than a statistical regularity or anomaly; it is perhaps more of a human nature contradictory anomaly that we may be talking about...Nevertheless let us dive a little deeper in the post and after we will be concluding with some remarks.</p> <h3><a href="http://hagutierrezro.blogspot.pt/2016/11/lord-paradox-in-r.html">Lord's paradox in R</a></h3> <p><br></p> <p>Note to  Steemit readers: please refer to the links provided for further reading, as all that is written here is may own original</p> </html>
json metadata	{"tags":["r","bloggers"],"links":["https://www.r-bloggers.com/","http://hagutierrezro.blogspot.pt/2016/11/lord-paradox-in-r.html"],"app":"steemit/0.1","format":"html"}
parent author
parent permlink	r
permlink	on-data-literacy-and-the-blogosphere
title	On Data Literacy and the Blogosphere
Transaction Info	Block #6951697/Trx 4b24003713f73c358534852a1efed57b73aea0b1

View Raw JSON Data

{
  "block": 6951697,
  "op": [
    "comment",
    {
      "author": "nunoedgarmit",
      "body": "<html>\n<p>&nbsp;I am a keen follower of the blog aggregator about the R programming language and Data Science named <a href=\"https://www.r-bloggers.com/\">R Bloggers</a>. It is a very resource to look for all about the possibilities of this statistical programming language that is a standard in the field, and specially for the more advanced researchers. It has got some steep learning curve, so it is advisable to learn a lot about statiscal&nbsp;concepts and reasoning before diving in this language. It is also important to know about programming. But the open source commitment by the developers of the language and the wide community of users provides for a nice open and plentiful trove of resources.<br>\nI receive e-mails form <a href=\"https://www.r-bloggers.com/\">R Bloggers</a> every single day of the week. And every day, be it &nbsp;a weekday, Saturdays, Sundays or Holidays, there is always good posts, with some about a &nbsp;new technique, another about a new perspective other on a relevant resource or innovative way of dealing with R and its main applications and so on... Not admissible to miss.And today was one of those days when I found an article from <a href=\"https://www.r-bloggers.com/\">R Bloggers</a> that caught my attention again. This time the name of the blog and the article title were the triggers. &nbsp;After reading the content of the post I thought I should share and reproduce part of it, for it is about the importance of Data Literacy, knowledge about statistics and what this means for the XXI Century. We are living through an age where the knowledge of these subjects is increasing, but where the mismatches as to what society needs to know and what it really knows about the subjects in question are also increasing. And this is having wide economic impacts as companies and organizations started complaining about these mismatches. On a counterfactual tone, if there is a mismatch, there is also as never before all the resources needed to bridge all the gaps, and if this isn't happening with the desired frequency, then the reasons may be of a different nature than a statistical regularity or anomaly; it is perhaps more of a human nature contradictory anomaly that we may be talking about...Nevertheless let us dive a little deeper in the post and after we will be concluding with some remarks.</p>\n<h3><a href=\"http://hagutierrezro.blogspot.pt/2016/11/lord-paradox-in-r.html\">Lord's paradox in R</a></h3>\n<p><br></p>\n<p>Note to &nbsp;Steemit readers: please refer to the links provided for further reading, as all that is written here is may own original</p>\n</html>",
      "json_metadata": "{\"tags\":[\"r\",\"bloggers\"],\"links\":[\"https://www.r-bloggers.com/\",\"http://hagutierrezro.blogspot.pt/2016/11/lord-paradox-in-r.html\"],\"app\":\"steemit/0.1\",\"format\":\"html\"}",
      "parent_author": "",
      "parent_permlink": "r",
      "permlink": "on-data-literacy-and-the-blogosphere",
      "title": "On Data Literacy and the Blogosphere"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:45:27",
  "trx_id": "4b24003713f73c358534852a1efed57b73aea0b1",
  "trx_in_block": 2,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @cheetah / re-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161110t162914

2016/11/22 16:37:18 UTC

6,951,534|5a5f4f3

author	cheetah
permlink	re-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161110t162914
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #6951534/Trx 5a5f4f3f8b2776f6759c38ea6470dd1953ac52df

View Raw JSON Data

{
  "block": 6951534,
  "op": [
    "vote",
    {
      "author": "cheetah",
      "permlink": "re-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161110t162914",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:37:18",
  "trx_id": "5a5f4f3f8b2776f6759c38ea6470dd1953ac52df",
  "trx_in_block": 2,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @steemcleaners / re-nunoedgarmit-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161111t053011943z

2016/11/22 16:35:54 UTC

6,951,506|cebe206

author	steemcleaners
permlink	re-nunoedgarmit-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161111t053011943z
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #6951506/Trx cebe2069856cfa897fdfc7934dcfeb9b7a7939c1

View Raw JSON Data

{
  "block": 6951506,
  "op": [
    "vote",
    {
      "author": "steemcleaners",
      "permlink": "re-nunoedgarmit-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161111t053011943z",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:35:54",
  "trx_id": "cebe2069856cfa897fdfc7934dcfeb9b7a7939c1",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitfollowed @steemcleaners

2016/11/22 16:35:51 UTC

6,951,505|3222288

id	follow
json	["follow",{"follower":"nunoedgarmit","following":"steemcleaners","what":["blog"]}]
required auths	[]
required posting auths	["nunoedgarmit"]
Transaction Info	Block #6951505/Trx 32222883df0f3e01d8b204bfc2300fb2594b332f

View Raw JSON Data

{
  "block": 6951505,
  "op": [
    "custom_json",
    {
      "id": "follow",
      "json": "[\"follow\",{\"follower\":\"nunoedgarmit\",\"following\":\"steemcleaners\",\"what\":[\"blog\"]}]",
      "required_auths": [],
      "required_posting_auths": [
        "nunoedgarmit"
      ]
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:35:51",
  "trx_id": "32222883df0f3e01d8b204bfc2300fb2594b332f",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @aaronkoenig / why-do-you-see-so-many-dollar-signs-in-argentina

2016/11/22 16:34:48 UTC

6,951,484|8be4df7

author	aaronkoenig
permlink	why-do-you-see-so-many-dollar-signs-in-argentina
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #6951484/Trx 8be4df7a6d8fadca637df1647ccef8d98eb06070

View Raw JSON Data

{
  "block": 6951484,
  "op": [
    "vote",
    {
      "author": "aaronkoenig",
      "permlink": "why-do-you-see-so-many-dollar-signs-in-argentina",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-22T16:34:48",
  "trx_id": "8be4df7a6d8fadca637df1647ccef8d98eb06070",
  "trx_in_block": 5,
  "virtual_op": 0
}

steemcleanersreplied to @nunoedgarmit / re-nunoedgarmit-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161111t053011943z

2016/11/11 05:30:15 UTC

6,621,633|7fd0db5

author	steemcleaners
body	Copying/Pasting full texts without adding anything original is frowned upon by the community. Some tips to share content and add value: - Using a few sentences from your source in “quotes.” Use HTML tags or Markdown. - Linking to your source - Include your own original thoughts and ideas on what you have shared. Repeated copy/paste posts could be considered spam. Spam is discouraged by the community, and may result in action from the [cheetah bot](https://steemit.com/steemitabuse/@cheetah/cheetah-bot-explained). Creative Commons: If you are posting content under a Creative Commons license, please attribute and link according to the specific license. If you are posting content under CC0 or Public Domain please consider noting that at the end of your post. If you are actually the original author, please do reply to let us know! Thank You!
json metadata	{"tags":["deep"],"links":["https://steemit.com/steemitabuse/@cheetah/cheetah-bot-explained"]}
parent author	nunoedgarmit
parent permlink	bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review
permlink	re-nunoedgarmit-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161111t053011943z
title
Transaction Info	Block #6621633/Trx 7fd0db5f7cba0c0c317a07840a7c3fd9c56238b0

View Raw JSON Data

{
  "block": 6621633,
  "op": [
    "comment",
    {
      "author": "steemcleaners",
      "body": "Copying/Pasting full texts without adding anything original is frowned upon by the community. \n\n\nSome tips to share content and add value:\n- Using a few sentences from your source in “quotes.” Use HTML tags or Markdown. \n- Linking to your source\n- Include your own original thoughts and ideas on what you have shared.\n\nRepeated copy/paste posts could be considered spam. Spam is discouraged by the community, and may result in action from the [cheetah bot](https://steemit.com/steemitabuse/@cheetah/cheetah-bot-explained).\n\nCreative Commons: If you are posting content under a Creative Commons license, please attribute and link according to the specific license. If you are posting content under CC0 or Public Domain please consider noting that at the end of your post. \n\nIf you are actually the original author, please do reply to let us know!\n\nThank You!",
      "json_metadata": "{\"tags\":[\"deep\"],\"links\":[\"https://steemit.com/steemitabuse/@cheetah/cheetah-bot-explained\"]}",
      "parent_author": "nunoedgarmit",
      "parent_permlink": "bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review",
      "permlink": "re-nunoedgarmit-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161111t053011943z",
      "title": ""
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-11T05:30:15",
  "trx_id": "7fd0db5f7cba0c0c317a07840a7c3fd9c56238b0",
  "trx_in_block": 4,
  "virtual_op": 0
}

ianstratupvoted (100.00%) @nunoedgarmit / bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review

2016/11/10 16:35:33 UTC

6,606,145|a0f3fc6

author	nunoedgarmit
permlink	bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review
voter	ianstrat
weight	10000 (100.00%)
Transaction Info	Block #6606145/Trx a0f3fc64f19bc0b45cf23d9dd041358366af5ce8

View Raw JSON Data

{
  "block": 6606145,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review",
      "voter": "ianstrat",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-10T16:35:33",
  "trx_id": "a0f3fc64f19bc0b45cf23d9dd041358366af5ce8",
  "trx_in_block": 0,
  "virtual_op": 0
}

cheetahreplied to @nunoedgarmit / re-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161110t162914

2016/11/10 16:29:15 UTC

6,606,020|5da1a53

author	cheetah
body	Hi! I am a content-detection robot. I found similar content that readers might be interested in: https://www.technologyreview.com/s/602807/deep-neural-network-learns-to-judge-books-by-their-covers/
json metadata
parent author	nunoedgarmit
parent permlink	bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review
permlink	re-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161110t162914
title
Transaction Info	Block #6606020/Trx 5da1a53b58cdc8b860f5d05f751a4883725117b7

View Raw JSON Data

{
  "block": 6606020,
  "op": [
    "comment",
    {
      "author": "cheetah",
      "body": "Hi! I am a content-detection robot. I found similar content that readers might be interested in:\nhttps://www.technologyreview.com/s/602807/deep-neural-network-learns-to-judge-books-by-their-covers/",
      "json_metadata": "",
      "parent_author": "nunoedgarmit",
      "parent_permlink": "bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review",
      "permlink": "re-bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review-20161110t162914",
      "title": ""
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-11-10T16:29:15",
  "trx_id": "5da1a53b58cdc8b860f5d05f751a4883725117b7",
  "trx_in_block": 6,
  "virtual_op": 0
}

nunoedgarmitpublished a new post: bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review

2016/11/10 16:28:48 UTC

6,606,011|92b91b3

author	nunoedgarmit
body	I will disclose today one of my dearest passion: bookstores. I just love bookstores, period. Honestly when I was living in London one of my favorites ways ( I think it was the main way, excessively maybe…) of passing my free time was to go to a Waterstone’s bookstore – I was specially fond of Gower Street’s store right next to University College London, and the routine of going there is one of nostalgic memories of my London. It just is that kind of sensation of pleasure and respect for books, which I think is one of my lucky traits. (...) This is the way to introduce the motive for today’s post. I will re-post a link from the excellent MIT Review newsletter about scientific and technological subjects that I receive every day in my mailbox. The quality of the scientific paper review section is an inspiration for improvements in the way this blog wants it to be reviewing papers. So I will do more often this kind of post, and I hope that it serves well the purpose of achieving here an approximation to that quality in future posts on reviews by The Information Age. Today’s paper is about the application of a machine vision system in bookstores to judge the content of a book by its cover. To this purpose it is used a deep neural network, and it goes like this: Deep Neural Network Learns to Judge Books by Their Covers "The idiom “never judge a book by its cover” warns against evaluating something purely by the way it looks. And yet book covers are designed to give readers an idea of the content, to make them want to pick up a book and read it. Good book covers are designed to be judged. And humans are quite good at it. It’s relatively straightforward to pick out a cookery book or a biography or a travel guide just by looking at the cover. And that raises an interesting question: can machines judge books by their covers, too? We already know they judge people by their faces. Today we get an answer thanks to the work of Brian Kenji Iwana and Seiichi Uchida at Kyushu University in Japan. These guys have trained a deep neural network to study book covers and determine the category of book they come from. Their method is straightforward. Iwana and Uchida downloaded 137,788 unique book covers from Amazon.com along with the genre of book. There are 20 possible genres but where a book was listed in more than one category, the researchers used just the first. Next, the pair used 80 percent of the data set to train a neural network to recognize the genre by looking at the cover image. Their neural network has four layers, each with up to 512 neurons, which together learn to recognize the correlation between cover design and genre. The pair used a further 10 percent of the dataset to validate the model and then tested the neural network on the final 10 percent to see how well it categorizes covers it has never seen. The results make for interesting reading. The algorithm listed the correct genre in its top 3 choices over 40 percent of the time and found the exact genre more than 20 percent of the time. That’s significantly better than chance. “This shows that classification of book cover designs is possible, although a very difficult task,” say Iwana and Uchida. Some categories turn out to be easier to recognize than others. For example, travel books and books about computer and technology are relatively easy for the neural network to spot because book designers consistently use similar images and design for these genres. The neural net also found that cookbooks were easy to recognize if they used pictures of food but were entirely ambiguous if they used a different design such as a picture of the chef. Biographies and memoires were also problematic with the algorithm often selecting history as the category. Interestingly, for many of these books, history is the secondary genre listed on Amazon, suggesting that the algorithm wasn’t entirely bamboozled. The algorithm also confused children’s books with comics and graphic novels as well as medical books and science books. Perhaps that’s also understandable given the similarities between these categories. There is one shortcoming in this work. Iwana and Uchida have not compared the performance of their neural network against humans’ ability to recognize book genres by their covers. That would be an interesting experiment and one that would be relatively straightforward to do with an online crowdsourcing service such as Amazon’s Mechanical Turk. Until that work is done, there is no way of knowing whether machines are any better at this task than humans. Although, no matter how good humans are at this task, it is surely only a matter of time before machines outperform them. Nevertheless, this is interesting work that could help designers improve their skills when it comes to book covers. A more likely outcome, however, is that it could be used to train machines to design book covers without the need for human input. And that means book cover design is just another job that is set to be consigned to the history books. Ref: arxiv.org/abs/1610.09204: Judging a Book by Its Cover " Fascinating read indeed. And I just wonder what on earth would think of the last two paragraphs some good giants of the book industry history such as Guttenberg or Michael Faraday. Yes the great English scientist and engineer – who was also a great Londoner – started his job life as a bookbinder. But Faraday found reading the books much more pleasurable, and would certainly look at these developments with a nice sense of irony, I would say the least.
json metadata	{"tags":["deep","learning","neural","netowrks","mit"],"app":"steemit/0.1","format":"markdown"}
parent author
parent permlink	deep
permlink	bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review
title	Bookstore day: Deep Neural Network learns the bookcovers – MIT paper Review
Transaction Info	Block #6606011/Trx 92b91b3f0dc6942448dd34ef199d0b94374fcc9a

View Raw JSON Data

{
"block": 6606011,
"op": [
"comment",
{
"author": "nunoedgarmit",
"body": "I will disclose today one of my dearest passion: bookstores. I just love bookstores, period. Honestly when I was living in London one of my favorites ways ( I think it was the main way, excessively maybe…) of passing my free time was to go to a Waterstone’s bookstore – I was specially fond of Gower Street’s store right next to University College London, and the routine of going there is one of nostalgic memories of my London. It just is that kind of sensation of pleasure and respect for books, which I think is one of my lucky traits.\n\n(...)\n\nThis is the way to introduce the motive for today’s post. I will re-post a link from the excellent MIT Review newsletter about scientific and technological subjects that I receive every day in my mailbox. The quality of the scientific paper review section is an inspiration for improvements in the way this blog wants it to be reviewing papers. So I will do more often this kind of post, and I hope that it serves well the purpose of achieving here an approximation to that quality in future posts on reviews by The Information Age. Today’s paper is about the application of a machine vision system in bookstores to judge the content of a book by its cover. To this purpose it is used a deep neural network, and it goes like this:\n\n\nDeep Neural Network Learns to Judge Books by Their Covers\n\n \n\n \n\n \"The idiom “never judge a book by its cover” warns against evaluating something purely by the way it looks. And yet book covers are designed to give readers an idea of the content, to make them want to pick up a book and read it. Good book covers are designed to be judged.\nAnd humans are quite good at it. It’s relatively straightforward to pick out a cookery book or a biography or a travel guide just by looking at the cover.\nAnd that raises an interesting question: can machines judge books by their covers, too? We already know they judge people by their faces. \n\nToday we get an answer thanks to the work of Brian Kenji Iwana and Seiichi Uchida at Kyushu University in Japan. These guys have trained a deep neural network to study book covers and determine the category of book they come from.\n \nTheir method is straightforward. Iwana and Uchida downloaded 137,788 unique book covers from Amazon.com along with the genre of book. There are 20 possible genres but where a book was listed in more than one category, the researchers used just the first.\n \nNext, the pair used 80 percent of the data set to train a neural network to recognize the genre by looking at the cover image. Their neural network has four layers, each with up to 512 neurons, which together learn to recognize the correlation between cover design and genre. The pair used a further 10 percent of the dataset to validate the model and then tested the neural network on the final 10 percent to see how well it categorizes covers it has never seen.\n \n\nThe results make for interesting reading. The algorithm listed the correct genre in its top 3 choices over 40 percent of the time and found the exact genre more than 20 percent of the time. That’s significantly better than chance. “This shows that classification of book cover designs is possible, although a very difficult task,” say Iwana and Uchida.\n\nSome categories turn out to be easier to recognize than others. For example, travel books and books about computer and technology are relatively easy for the neural network to spot because book designers consistently use similar images and design for these genres.\n \nThe neural net also found that cookbooks were easy to recognize if they used pictures of food but were entirely ambiguous if they used a different design such as a picture of the chef.\n \nBiographies and memoires were also problematic with the algorithm often selecting history as the category. Interestingly, for many of these books, history is the secondary genre listed on Amazon, suggesting that the algorithm wasn’t entirely bamboozled.\n \nThe algorithm also confused children’s books with comics and graphic novels as well as medical books and science books. Perhaps that’s also understandable given the similarities between these categories.\n \nThere is one shortcoming in this work. Iwana and Uchida have not compared the performance of their neural network against humans’ ability to recognize book genres by their covers. That would be an interesting experiment and one that would be relatively straightforward to do with an online crowdsourcing service such as Amazon’s Mechanical Turk.\n \nUntil that work is done, there is no way of knowing whether machines are any better at this task than humans. Although, no matter how good humans are at this task, it is surely only a matter of time before machines outperform them.\n \n\nNevertheless, this is interesting work that could help designers improve their skills when it comes to book covers. A more likely outcome, however, is that it could be used to train machines to design book covers without the need for human input. And that means book cover design is just another job that is set to be consigned to the history books.\n \n \nRef: arxiv.org/abs/1610.09204: Judging a Book by Its Cover \"\n\n\nFascinating read indeed. And I just wonder what on earth would think of the last two paragraphs some good giants of the book industry history such as Guttenberg or Michael Faraday. Yes the great English scientist and engineer – who was also a great Londoner – started his job life as a bookbinder. But Faraday found reading the books much more pleasurable, and would certainly look at these developments with a nice sense of irony, I would say the least.",
"json_metadata": "{\"tags\":[\"deep\",\"learning\",\"neural\",\"netowrks\",\"mit\"],\"app\":\"steemit/0.1\",\"format\":\"markdown\"}",
"parent_author": "",
"parent_permlink": "deep",
"permlink": "bookstore-day-deep-neural-network-learns-the-bookcovers-mit-paper-review",
"title": "Bookstore day: Deep Neural Network learns the bookcovers – MIT paper Review"
}
],
"op_in_trx": 0,
"timestamp": "2016-11-10T16:28:48",
"trx_id": "92b91b3f0dc6942448dd34ef199d0b94374fcc9a",
"trx_in_block": 1,
"virtual_op": 0
}

nunoedgarmitupdated options for real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust

2016/10/07 18:02:42 UTC

5,629,807|f4055c0

allow curation rewards	true
allow votes	true
author	nunoedgarmit
extensions	[]
max accepted payout	1000000.000 SBD
percent steem dollars	0
permlink	real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust
Transaction Info	Block #5629807/Trx f4055c0e7b8f21a6b21d8241825e9eda953b7c9c

View Raw JSON Data

{
  "block": 5629807,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "nunoedgarmit",
      "extensions": [],
      "max_accepted_payout": "1000000.000 SBD",
      "percent_steem_dollars": 0,
      "permlink": "real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-10-07T18:02:42",
  "trx_id": "f4055c0e7b8f21a6b21d8241825e9eda953b7c9c",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitupvoted (100.00%) @nunoedgarmit / real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust

2016/10/07 18:02:42 UTC

5,629,807|f4055c0

author	nunoedgarmit
permlink	real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust
voter	nunoedgarmit
weight	10000 (100.00%)
Transaction Info	Block #5629807/Trx f4055c0e7b8f21a6b21d8241825e9eda953b7c9c

View Raw JSON Data

{
  "block": 5629807,
  "op": [
    "vote",
    {
      "author": "nunoedgarmit",
      "permlink": "real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust",
      "voter": "nunoedgarmit",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-10-07T18:02:42",
  "trx_id": "f4055c0e7b8f21a6b21d8241825e9eda953b7c9c",
  "trx_in_block": 1,
  "virtual_op": 0
}

nunoedgarmitpublished a new post: real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust

2016/10/07 18:02:42 UTC

5,629,807|f4055c0

author	nunoedgarmit
body	https://cryptortrust.com/2016/07/07/real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin/
json metadata	{"tags":["bitcoin","cryptor","trust"],"links":["https://cryptortrust.com/2016/07/07/real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin/"]}
parent author
parent permlink	bitcoin
permlink	real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust
title	REAL REASON FOR CASH BAN AND WHY IT WILL ONLY BOOST BITCOIN - Cryptor Trust
Transaction Info	Block #5629807/Trx f4055c0e7b8f21a6b21d8241825e9eda953b7c9c

View Raw JSON Data

{
  "block": 5629807,
  "op": [
    "comment",
    {
      "author": "nunoedgarmit",
      "body": "https://cryptortrust.com/2016/07/07/real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin/",
      "json_metadata": "{\"tags\":[\"bitcoin\",\"cryptor\",\"trust\"],\"links\":[\"https://cryptortrust.com/2016/07/07/real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin/\"]}",
      "parent_author": "",
      "parent_permlink": "bitcoin",
      "permlink": "real-reason-for-cash-ban-and-why-it-will-only-boost-bitcoin-cryptor-trust",
      "title": "REAL REASON FOR CASH BAN AND WHY IT WILL ONLY BOOST BITCOIN  -  Cryptor Trust"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-10-07T18:02:42",
  "trx_id": "f4055c0e7b8f21a6b21d8241825e9eda953b7c9c",
  "trx_in_block": 1,
  "virtual_op": 0
}

steemcreated a new account: @nunoedgarmit

2016/07/23 20:19:30 UTC

3,454,410|a4d63b6

active	{"account_auths":[],"key_auths":[["STM8fh9LYFqbR7aWKpGdo2Qi8TAtpHyypKNW9MV5F8jXx98M9nQf4",1]],"weight_threshold":1}
creator	steem
fee	3.000 STEEM
json metadata
memo key	STM5gGMTC1rxjT9GWF5DhzSMACj8QNor9FfM6JKda5hupdMhiDwKu
new account name	nunoedgarmit
owner	{"account_auths":[],"key_auths":[["STM6MCXZim3ki1MpoL7fip9nqYZ4VPY89HBvzy4xifMfwmqtyi8vg",1]],"weight_threshold":1}
posting	{"account_auths":[],"key_auths":[["STM7RbpyCTfJdAwADbUr4ZAFBxue3YqE3qeKEw12xMfxddnHT2QJ4",1]],"weight_threshold":1}
Transaction Info	Block #3454410/Trx a4d63b6d1c5f13c24d07eebddd23750fab089b55

View Raw JSON Data

{
  "block": 3454410,
  "op": [
    "account_create",
    {
      "active": {
        "account_auths": [],
        "key_auths": [
          [
            "STM8fh9LYFqbR7aWKpGdo2Qi8TAtpHyypKNW9MV5F8jXx98M9nQf4",
            1
          ]
        ],
        "weight_threshold": 1
      },
      "creator": "steem",
      "fee": "3.000 STEEM",
      "json_metadata": "",
      "memo_key": "STM5gGMTC1rxjT9GWF5DhzSMACj8QNor9FfM6JKda5hupdMhiDwKu",
      "new_account_name": "nunoedgarmit",
      "owner": {
        "account_auths": [],
        "key_auths": [
          [
            "STM6MCXZim3ki1MpoL7fip9nqYZ4VPY89HBvzy4xifMfwmqtyi8vg",
            1
          ]
        ],
        "weight_threshold": 1
      },
      "posting": {
        "account_auths": [],
        "key_auths": [
          [
            "STM7RbpyCTfJdAwADbUr4ZAFBxue3YqE3qeKEw12xMfxddnHT2QJ4",
            1
          ]
        ],
        "weight_threshold": 1
      }
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2016-07-23T20:19:30",
  "trx_id": "a4d63b6d1c5f13c24d07eebddd23750fab089b55",
  "trx_in_block": 2,
  "virtual_op": 0
}

Manabar

Voting Power100.00%

Downvote Power100.00%

Resource Credits100.00%

Reputation Progress0.00%

{
  "voting_manabar": {
    "current_mana": 9950,
    "last_update_time": 1481735697
  },
  "downvote_manabar": {
    "current_mana": 0,
    "last_update_time": 1469305170
  },
  "rc_account": {
    "account": "nunoedgarmit",
    "rc_manabar": {
      "current_mana": "14696396757",
      "last_update_time": 1537887600
    },
    "max_rc_creation_adjustment": {
      "amount": "2020748973",
      "precision": 6,
      "nai": "@@000000037"
    },
    "max_rc": "14696396757"
  }
}

Account Metadata

POSTING JSON METADATA
None
JSON METADATA
None

{
  "posting_json_metadata": {},
  "json_metadata": {}
}

Auth Keys

Owner

Single Signature

Public Keys

STM6MCXZim3ki1MpoL7fip9nqYZ4VPY89HBvzy4xifMfwmqtyi8vg1/1

Active

Single Signature

Public Keys

STM8fh9LYFqbR7aWKpGdo2Qi8TAtpHyypKNW9MV5F8jXx98M9nQf41/1

Posting

Single Signature

Public Keys

STM7RbpyCTfJdAwADbUr4ZAFBxue3YqE3qeKEw12xMfxddnHT2QJ41/1

Memo

STM5gGMTC1rxjT9GWF5DhzSMACj8QNor9FfM6JKda5hupdMhiDwKu

{
  "owner": {
    "weight_threshold": 1,
    "account_auths": [],
    "key_auths": [
      [
        "STM6MCXZim3ki1MpoL7fip9nqYZ4VPY89HBvzy4xifMfwmqtyi8vg",
        1
      ]
    ]
  },
  "active": {
    "weight_threshold": 1,
    "account_auths": [],
    "key_auths": [
      [
        "STM8fh9LYFqbR7aWKpGdo2Qi8TAtpHyypKNW9MV5F8jXx98M9nQf4",
        1
      ]
    ]
  },
  "posting": {
    "weight_threshold": 1,
    "account_auths": [],
    "key_auths": [
      [
        "STM7RbpyCTfJdAwADbUr4ZAFBxue3YqE3qeKEw12xMfxddnHT2QJ4",
        1
      ]
    ]
  },
  "memo": "STM5gGMTC1rxjT9GWF5DhzSMACj8QNor9FfM6JKda5hupdMhiDwKu"
}

Witness Votes

0 / 30

No active witness votes.

[]