{
  "block": 97159594,
  "op": [
    "delegate_vesting_shares",
    {
      "delegatee": "dimakiear",
      "delegator": "steem",
      "vesting_shares": "1665.623825 VESTS"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2025-07-09T04:45:42",
  "trx_id": "474b833ecaaa3917a21cb4800b484243f8c2d519",
  "trx_in_block": 0,
  "virtual_op": 0
}

{
  "block": 61689476,
  "op": [
    "delegate_vesting_shares",
    {
      "delegatee": "dimakiear",
      "delegator": "steem",
      "vesting_shares": "1832.191871 VESTS"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2022-02-17T04:18:45",
  "trx_id": "50c3fcb94e168c9a928748f832d5541c41f309c2",
  "trx_in_block": 4,
  "virtual_op": 0
}

{
  "block": 59734637,
  "op": [
    "delegate_vesting_shares",
    {
      "delegatee": "dimakiear",
      "delegator": "steem",
      "vesting_shares": "22691.493195 VESTS"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-12-10T17:49:51",
  "trx_id": "3b9aece06485139fee96b3b8304c7a0d17670215",
  "trx_in_block": 68,
  "virtual_op": 0
}

{
  "block": 59092608,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "dimakiear",
      "extensions": [],
      "max_accepted_payout": "100000.000 SBD",
      "percent_steem_dollars": 10000,
      "permlink": "82jqrzf4d2m2zwuc02"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-18T04:07:33",
  "trx_id": "7d105bd00cd493f26d432ed27c2742e85b1015af",
  "trx_in_block": 8,
  "virtual_op": 0
}

{
  "block": 59092608,
  "op": [
    "comment",
    {
      "author": "dimakiear",
      "body": "https://www.youtube.com/watch?v=E8diAzd2-cM\n\nThis video highlights how to use MATLAB® apps for signal processing and demonstrates the functionality of relevant apps using a demo on preprocessing and analyzing an electrocardiogram (ECG) signal.\n\nFirst, Liping introduces the Signal Analyzer app, the Filter Builder and Filter Designer apps, the Wavelet Signal Denoiser app, and the Signal Multiresolution Analyzer app.\n\nLiping uses the Signal Analyzer app to import, visualize, analyze, and preprocess an ECG signal. Preprocessing includes filtering and detrending.\n\nNext, the Signal Multiresolution Analyzer app is used to perform multiresolution analysis, through which the low frequency component representing the signal trend has been removed, and the ECG signal without trend has been reconstructed.\n\nFinally, Liping summarizes the benefits of using MATLAB apps to do signal processing.\n\n\nUnderstanding Wavelets (5 videos): https://bit.ly/37KCdvS\nTrend Detection and Isolation : https://bit.ly/2vqeUJd\nFeature Detection and Extraction Using Wavelets, Part 1: Feature Detection Using Wavelets: https://bit.ly/2O8rRhk\n\n--------------------------------------------------------------------------------------------------------\nGet a free product trial: https://goo.gl/ZHFb5u\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\nLearn more about Simulink: https://goo.gl/nqnbLe\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\n\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\ntrademarks of The MathWorks, Inc. \nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.",
      "json_metadata": "{\"video\":{\"videoId\":\"E8diAzd2-cM\",\"url\":\"https://www.youtube.com/watch?v=E8diAzd2-cM\",\"title\":\"Introduction to Signal Processing Apps in MATLAB\",\"description\":\"https://www.youtube.com/watch?v=E8diAzd2-cM\\n\\nThis video highlights how to use MATLAB® apps for signal processing and demonstrates the functionality of relevant apps using a demo on preprocessing and analyzing an electrocardiogram (ECG) signal.\\n\\nFirst, Liping introduces the Signal Analyzer app, the Filter Builder and Filter Designer apps, the Wavelet Signal Denoiser app, and the Signal Multiresolution Analyzer app.\\n\\nLiping uses the Signal Analyzer app to import, visualize, analyze, and preprocess an ECG signal. Preprocessing includes filtering and detrending.\\n\\nNext, the Signal Multiresolution Analyzer app is used to perform multiresolution analysis, through which the low frequency component representing the signal trend has been removed, and the ECG signal without trend has been reconstructed.\\n\\nFinally, Liping summarizes the benefits of using MATLAB apps to do signal processing.\\n\\n\\nUnderstanding Wavelets (5 videos): https://bit.ly/37KCdvS\\nTrend Detection and Isolation : https://bit.ly/2vqeUJd\\nFeature Detection and Extraction Using Wavelets, Part 1: Feature Detection Using Wavelets: https://bit.ly/2O8rRhk\\n\\n--------------------------------------------------------------------------------------------------------\\nGet a free product trial: https://goo.gl/ZHFb5u\\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\\nLearn more about Simulink: https://goo.gl/nqnbLe\\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\\n\\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\\ntrademarks of The MathWorks, Inc. \\nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.\",\"owner\":\"MATLAB\",\"channelId\":\"UCgdHSFcXvkN6O3NXvif0-pA\",\"thumbnailUrl\":\"https://i.ytimg.com/vi/E8diAzd2-cM/mqdefault.jpg\",\"datePublished\":\"03.03.2020 15:00:00\",\"genre\":\"28\",\"isFamilyFriendly\":true,\"duration\":613,\"channelThumbnailUrl\":\"https://i.ytimg.com/vi/E8diAzd2-cM/mqdefault.jpg\",\"providerName\":\"YouTube\",\"refs\":[]},\"tags\":[\"hive-122108\",\"programming\",\"learning\",\"education\",\"bigdata\",\"curation\",\"dtube\"],\"format\":\"markdown\"}",
      "parent_author": "",
      "parent_permlink": "hive-122108",
      "permlink": "82jqrzf4d2m2zwuc02",
      "title": "Introduction to Signal Processing Apps in MATLAB"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-18T04:07:33",
  "trx_id": "7d105bd00cd493f26d432ed27c2742e85b1015af",
  "trx_in_block": 8,
  "virtual_op": 0
}

{
  "block": 59007249,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "dimakiear",
      "extensions": [],
      "max_accepted_payout": "100000.000 SBD",
      "percent_steem_dollars": 10000,
      "permlink": "20knw3es6tse"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-15T02:55:48",
  "trx_id": "4a57db8e72ce394e9b7b9e4bcbd2d274c983f697",
  "trx_in_block": 0,
  "virtual_op": 0
}

{
  "block": 59007249,
  "op": [
    "comment",
    {
      "author": "dimakiear",
      "body": "https://www.youtube.com/watch?v=XYMJf_deg7Q\n\nLearn how to use projects in MATLAB® to more easily organize, manage, and share your work. MATLAB projects let you configure your environment, analyze dependencies, track and control changes, and package and share projects. You’ll also see how to perform source control integration, develop tests using the unit testing framework, and identify potential code compatibility issues.  \n\n--------------------------------------------------------------------------------------------------------\nGet a free product Trial: https://goo.gl/ZHFb5u\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\nLearn more about Simulink: https://goo.gl/nqnbLe\nSee What's new in MATLAB and Simulink: https://goo.gl/pgGtod\n\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\ntrademarks of The MathWorks, Inc. \nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.",
      "json_metadata": "{\"video\":{\"videoId\":\"XYMJf_deg7Q\",\"url\":\"https://www.youtube.com/watch?v=XYMJf_deg7Q\",\"title\":\"Organizing, Managing, and Sharing MATLAB Code  - New Ways to Work in MATLAB\",\"description\":\"https://www.youtube.com/watch?v=XYMJf_deg7Q\\n\\nLearn how to use projects in MATLAB® to more easily organize, manage, and share your work. MATLAB projects let you configure your environment, analyze dependencies, track and control changes, and package and share projects. You’ll also see how to perform source control integration, develop tests using the unit testing framework, and identify potential code compatibility issues.  \\n\\n--------------------------------------------------------------------------------------------------------\\nGet a free product Trial: https://goo.gl/ZHFb5u\\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\\nLearn more about Simulink: https://goo.gl/nqnbLe\\nSee What's new in MATLAB and Simulink: https://goo.gl/pgGtod\\n\\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\\ntrademarks of The MathWorks, Inc. \\nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.\",\"owner\":\"MATLAB\",\"channelId\":\"UCgdHSFcXvkN6O3NXvif0-pA\",\"thumbnailUrl\":\"https://i.ytimg.com/vi/XYMJf_deg7Q/mqdefault.jpg\",\"datePublished\":\"02.03.2020 18:59:52\",\"genre\":\"28\",\"isFamilyFriendly\":true,\"duration\":180,\"channelThumbnailUrl\":\"https://i.ytimg.com/vi/XYMJf_deg7Q/mqdefault.jpg\",\"providerName\":\"YouTube\",\"refs\":[]},\"tags\":[\"hive-122108\",\"programming\",\"learning\",\"education\",\"bigdata\",\"curation\",\"dtube\"],\"format\":\"markdown\"}",
      "parent_author": "",
      "parent_permlink": "hive-122108",
      "permlink": "20knw3es6tse",
      "title": "Organizing, Managing, and Sharing MATLAB Code  - New Ways to Work in MATLAB"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-15T02:55:48",
  "trx_id": "4a57db8e72ce394e9b7b9e4bcbd2d274c983f697",
  "trx_in_block": 0,
  "virtual_op": 0
}

{
  "block": 58835623,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "dimakiear",
      "extensions": [],
      "max_accepted_payout": "100000.000 SBD",
      "percent_steem_dollars": 10000,
      "permlink": "lelp0287648k1hp7"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-09T03:02:15",
  "trx_id": "bd2d988cc21504c2cfd9b36ae510c37f688e85f6",
  "trx_in_block": 21,
  "virtual_op": 0
}

{
  "block": 58835623,
  "op": [
    "comment",
    {
      "author": "dimakiear",
      "body": "https://www.youtube.com/watch?v=xOvuQ6DY_4w\n\nIn this video, Neha Goel joins Connell D’Souza how you can design and train a deep neural network in MATLAB®. The example discussed is a You-Only-Look-Once (YOLOv2) neural network. YOLOv2 is a popular real-time object detection algorithm for autonomous systems.\n\nNeha first discusses the architecture of a YOLOv2 network and the different layers and then demonstrates how to assemble the layers in the network and visualize them in MATLAB. She also explains the importance of anchor boxes in a YOLOv2 network.\n\nNeha also covers training options and how they can be manipulated to achieve the best results. The trained model is tested on a test dataset to visually inspect performance before evaluating the network with numerical performance metrics like precision-recall curves.\n\n\nResources:\n\n- Deep Learning with MATLAB: https://bit.ly/37APNSf\n- Anchor Boxes for Object Detection: https://bit.ly/2uHqqiU\n- Getting Started with YOLO V2: https://bit.ly/2O6pJqx\n\n\n- Download the files used in this video: https://bit.ly/2U4pb8e\n- Contact the MathWorks student competitions team: [email protected]\n- Visit the MATLAB and Simulink Robotics Arena for additional videos: https://bit.ly/2U4vubN\n- Request software for your student competition: https://bit.ly/2RxWrmU\n\n--------------------------------------------------------------------------------------------------------\nGet a free product trial: https://goo.gl/ZHFb5u\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\nLearn more about Simulink: https://goo.gl/nqnbLe\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\n\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\ntrademarks of The MathWorks, Inc. \nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.",
      "json_metadata": "{\"video\":{\"videoId\":\"xOvuQ6DY_4w\",\"url\":\"https://www.youtube.com/watch?v=xOvuQ6DY_4w\",\"title\":\"Design and Train a YOLOv2 Network in MATLAB\",\"description\":\"https://www.youtube.com/watch?v=xOvuQ6DY_4w\\n\\nIn this video, Neha Goel joins Connell D’Souza how you can design and train a deep neural network in MATLAB®. The example discussed is a You-Only-Look-Once (YOLOv2) neural network. YOLOv2 is a popular real-time object detection algorithm for autonomous systems.\\n\\nNeha first discusses the architecture of a YOLOv2 network and the different layers and then demonstrates how to assemble the layers in the network and visualize them in MATLAB. She also explains the importance of anchor boxes in a YOLOv2 network.\\n\\nNeha also covers training options and how they can be manipulated to achieve the best results. The trained model is tested on a test dataset to visually inspect performance before evaluating the network with numerical performance metrics like precision-recall curves.\\n\\n\\nResources:\\n\\n- Deep Learning with MATLAB: https://bit.ly/37APNSf\\n- Anchor Boxes for Object Detection: https://bit.ly/2uHqqiU\\n- Getting Started with YOLO V2: https://bit.ly/2O6pJqx\\n\\n\\n- Download the files used in this video: https://bit.ly/2U4pb8e\\n- Contact the MathWorks student competitions team: [email protected]\\n- Visit the MATLAB and Simulink Robotics Arena for additional videos: https://bit.ly/2U4vubN\\n- Request software for your student competition: https://bit.ly/2RxWrmU\\n\\n--------------------------------------------------------------------------------------------------------\\nGet a free product trial: https://goo.gl/ZHFb5u\\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\\nLearn more about Simulink: https://goo.gl/nqnbLe\\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\\n\\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\\ntrademarks of The MathWorks, Inc. \\nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.\",\"owner\":\"MATLAB\",\"channelId\":\"UCgdHSFcXvkN6O3NXvif0-pA\",\"thumbnailUrl\":\"https://i.ytimg.com/vi/xOvuQ6DY_4w/mqdefault.jpg\",\"datePublished\":\"02.03.2020 14:00:38\",\"genre\":\"28\",\"isFamilyFriendly\":true,\"duration\":1131,\"channelThumbnailUrl\":\"https://i.ytimg.com/vi/xOvuQ6DY_4w/mqdefault.jpg\",\"providerName\":\"YouTube\",\"refs\":[]},\"tags\":[\"hive-122108\",\"programming\",\"learning\",\"education\",\"bigdata\",\"curation\",\"dtube\"],\"format\":\"markdown\"}",
      "parent_author": "",
      "parent_permlink": "hive-122108",
      "permlink": "lelp0287648k1hp7",
      "title": "Design and Train a YOLOv2 Network in MATLAB"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-09T03:02:15",
  "trx_id": "bd2d988cc21504c2cfd9b36ae510c37f688e85f6",
  "trx_in_block": 21,
  "virtual_op": 0
}

{
  "block": 58826978,
  "op": [
    "vote",
    {
      "author": "qimain",
      "permlink": "euvs4thqop98",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-08T19:47:12",
  "trx_id": "f5bb2ed075abb6142895bad736f863e143b7c39d",
  "trx_in_block": 9,
  "virtual_op": 0
}

{
  "block": 58826943,
  "op": [
    "vote",
    {
      "author": "breachedrosa",
      "permlink": "7653s5inznmd37",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-08T19:45:27",
  "trx_id": "e7d72948eef5a4bc523f2f989945b574f30c2125",
  "trx_in_block": 1,
  "virtual_op": 0
}

{
  "block": 58825760,
  "op": [
    "vote",
    {
      "author": "gmarmoonralet",
      "permlink": "ddg2mx9bbra1oh9ks7q",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-08T18:46:06",
  "trx_id": "bd0e158037318b1997118572ce51c49bad045ef8",
  "trx_in_block": 2,
  "virtual_op": 0
}

{
  "block": 58825566,
  "op": [
    "vote",
    {
      "author": "morcaryre",
      "permlink": "4mp0tb5mtmp",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-08T18:36:21",
  "trx_id": "c7f8848fc4e8ee260c27512c96ba15aef63e3da6",
  "trx_in_block": 3,
  "virtual_op": 0
}

{
  "block": 58825403,
  "op": [
    "vote",
    {
      "author": "joiconbullqua",
      "permlink": "zkfe5uhbpbadkxfkxnv",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-11-08T18:28:12",
  "trx_id": "eb98d94e1421e67369d25660bf432034dde29298",
  "trx_in_block": 5,
  "virtual_op": 0
}

{
  "block": 57736576,
  "op": [
    "transfer",
    {
      "amount": "1.692 STEEM",
      "from": "dimakiear",
      "memo": "107430887",
      "to": "deepcrypto8"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-10-01T17:40:39",
  "trx_id": "2f78d57508494a389038ba99e4614318b3155d12",
  "trx_in_block": 4,
  "virtual_op": 0
}

{
  "block": 57735535,
  "op": [
    "transfer",
    {
      "amount": "0.001 STEEM",
      "from": "executive-board",
      "memo": "❗ Hello dimakiear, great that you are using the STEEM blockchain. The Executive Board is publishing insider infos at https://discord.gg/KyBbmhh on how you will be earning the most coins. It's easy, just follow the instructions. THE 1000X BOOSTER KEY is already waiting for you over there too. 😉 Warm regards, The Executive Board.",
      "to": "dimakiear"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-10-01T16:48:18",
  "trx_id": "e50a3265d8bbb52e87b5e1e44fb07bb98c5f6959",
  "trx_in_block": 13,
  "virtual_op": 0
}

{
  "block": 57735505,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "f8msm4alv4q7",
      "voter": "sqube",
      "weight": 100
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-10-01T16:46:48",
  "trx_id": "d1b7528864716e6d4db1c4900d92fae6efd70add",
  "trx_in_block": 11,
  "virtual_op": 0
}

{
  "block": 57735502,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "dimakiear",
      "extensions": [],
      "max_accepted_payout": "100000.000 SBD",
      "percent_steem_dollars": 10000,
      "permlink": "f8msm4alv4q7"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-10-01T16:46:39",
  "trx_id": "542c8bebeca3d666712722a853654c91d28e0c8b",
  "trx_in_block": 7,
  "virtual_op": 0
}

{
  "block": 57735502,
  "op": [
    "comment",
    {
      "author": "dimakiear",
      "body": "https://www.youtube.com/watch?v=EE_Y89lWC2c\n\nAI, or artificial intelligence, is powering a massive shift in the roles that computers play in our personal and professional lives. Two new workflows, deep learning and reinforcement learning, are transforming industries and improving applications such as diagnosing medical conditions, driving autonomous vehicles, and controlling robots. \n\nThis talk dives into how MATLAB® supports deep learning and reinforcement workflows, including:\n\n- Automating preparation and labelling of training data\n- Interoperability with open-source deep learning frameworks\n- Training deep neural networks on image, signal, and text data\n- Tuning hyper-parameters to accelerate training time and increase network accuracy\n- Generating multi-target code for NVIDIA®, Intel®, and ARM®\n\nAdditional Resources:\n\n- Request Trial: https://bit.ly/2XrfzVI\n- View slides: https://bit.ly/31GLFhg\n- See all proceedings from MATLAB EXPO 2019 United Kingdom: https://www.matlabexpo.com/uk/2019.html\n\n--------------------------------------------------------------------------------------------------------\nGet a free product trial: https://goo.gl/ZHFb5u\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\nLearn more about Simulink: https://goo.gl/nqnbLe\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\n\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\ntrademarks of The MathWorks, Inc. \nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.",
      "json_metadata": "{\"video\":{\"videoId\":\"EE_Y89lWC2c\",\"url\":\"https://www.youtube.com/watch?v=EE_Y89lWC2c\",\"title\":\"MATLAB EXPO 2019: Deep Learning and Reinforcement Learning Workflows in AI\",\"description\":\"https://www.youtube.com/watch?v=EE_Y89lWC2c\\n\\nAI, or artificial intelligence, is powering a massive shift in the roles that computers play in our personal and professional lives. Two new workflows, deep learning and reinforcement learning, are transforming industries and improving applications such as diagnosing medical conditions, driving autonomous vehicles, and controlling robots. \\n\\nThis talk dives into how MATLAB® supports deep learning and reinforcement workflows, including:\\n\\n- Automating preparation and labelling of training data\\n- Interoperability with open-source deep learning frameworks\\n- Training deep neural networks on image, signal, and text data\\n- Tuning hyper-parameters to accelerate training time and increase network accuracy\\n- Generating multi-target code for NVIDIA®, Intel®, and ARM®\\n\\nAdditional Resources:\\n\\n- Request Trial: https://bit.ly/2XrfzVI\\n- View slides: https://bit.ly/31GLFhg\\n- See all proceedings from MATLAB EXPO 2019 United Kingdom: https://www.matlabexpo.com/uk/2019.html\\n\\n--------------------------------------------------------------------------------------------------------\\nGet a free product trial: https://goo.gl/ZHFb5u\\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\\nLearn more about Simulink: https://goo.gl/nqnbLe\\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\\n\\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\\ntrademarks of The MathWorks, Inc. \\nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.\",\"owner\":\"MATLAB\",\"channelId\":\"UCgdHSFcXvkN6O3NXvif0-pA\",\"thumbnailUrl\":\"https://i.ytimg.com/vi/EE_Y89lWC2c/mqdefault.jpg\",\"datePublished\":\"28.02.2020 19:12:16\",\"genre\":\"28\",\"isFamilyFriendly\":true,\"duration\":1518,\"channelThumbnailUrl\":\"https://i.ytimg.com/vi/EE_Y89lWC2c/mqdefault.jpg\",\"providerName\":\"YouTube\",\"refs\":[]},\"tags\":[\"hive-122108\",\"programming\",\"learning\",\"education\",\"bigdata\",\"curation\",\"dtube\"],\"format\":\"markdown\"}",
      "parent_author": "",
      "parent_permlink": "hive-122108",
      "permlink": "f8msm4alv4q7",
      "title": "MATLAB EXPO 2019: Deep Learning and Reinforcement Learning Workflows in AI"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-10-01T16:46:39",
  "trx_id": "542c8bebeca3d666712722a853654c91d28e0c8b",
  "trx_in_block": 7,
  "virtual_op": 0
}

{
  "block": 57578964,
  "op": [
    "fill_convert_request",
    {
      "amount_in": "0.839 SBD",
      "amount_out": "1.691 STEEM",
      "owner": "dimakiear",
      "requestid": 185
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-09-26T05:33:24",
  "trx_id": "0000000000000000000000000000000000000000",
  "trx_in_block": 4294967295,
  "virtual_op": 2
}

{
  "block": 57557436,
  "op": [
    "delegate_vesting_shares",
    {
      "delegatee": "dimakiear",
      "delegator": "steem",
      "vesting_shares": "22875.852451 VESTS"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-09-25T10:57:21",
  "trx_id": "77bf8bb93bb51b9d3a751ddfaa69ccfce855e801",
  "trx_in_block": 1,
  "virtual_op": 0
}

{
  "block": 57556422,
  "op": [
    "vote",
    {
      "author": "newmanaleks",
      "permlink": "j4vg9e92qz1wuxp",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-09-25T10:06:33",
  "trx_id": "74b7f6e92cf7fcadc2eeba9a9e1e969b58611bf1",
  "trx_in_block": 1,
  "virtual_op": 0
}

{
  "block": 57479551,
  "op": [
    "transfer",
    {
      "amount": "0.150 STEEM",
      "from": "dimakiear",
      "memo": "107430887",
      "to": "deepcrypto8"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-09-22T17:33:30",
  "trx_id": "070ea294c7b03e0b57d5043b4d297ee44cabc5f1",
  "trx_in_block": 1,
  "virtual_op": 0
}

{
  "block": 57479549,
  "op": [
    "convert",
    {
      "amount": "0.839 SBD",
      "owner": "dimakiear",
      "requestid": 185
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2021-09-22T17:33:24",
  "trx_id": "0f68aff2c15bab4f20ef932bb5e7b5f471f62681",
  "trx_in_block": 5,
  "virtual_op": 0
}

{
  "block": 49492188,
  "op": [
    "transfer",
    {
      "amount": "0.001 STEEM",
      "from": "blurtofficial",
      "memo": "CONGRATS! You have a 1:1 BLURT AIRDROP of 4.810 BLURT and 5.079000 BLURT POWER waiting for you. Check out https://blurtwallet.com/@dimakiear and https://blurt.blog/ TODAY!",
      "to": "dimakiear"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-12-16T07:23:54",
  "trx_id": "5188327f74799273cc87bd6c1044a0d163bbb9e6",
  "trx_in_block": 0,
  "virtual_op": 0
}

{
  "block": 46297889,
  "op": [
    "delegate_vesting_shares",
    {
      "delegatee": "dimakiear",
      "delegator": "steem",
      "vesting_shares": "1935.400555 VESTS"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-08-25T16:11:18",
  "trx_id": "0179f289bcdc20e559561e7a79dcdcb1dae804f0",
  "trx_in_block": 6,
  "virtual_op": 0
}

{
  "block": 45563139,
  "op": [
    "delegate_vesting_shares",
    {
      "delegatee": "dimakiear",
      "delegator": "steem",
      "vesting_shares": "24145.658731 VESTS"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-07-30T19:35:57",
  "trx_id": "2c14a70e615897c5ee19f2758568ce4976aac2c8",
  "trx_in_block": 0,
  "virtual_op": 0
}

{
  "block": 43698197,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "alishi",
      "weight": 5000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-26T07:32:51",
  "trx_id": "9667b2d897733f54e69545f88bac8f501356934d",
  "trx_in_block": 3,
  "virtual_op": 0
}

{
  "block": 43686888,
  "op": [
    "vote",
    {
      "author": "morcaryre",
      "permlink": "r7bzromb8dr",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T21:56:33",
  "trx_id": "143415451d7dc8a3d26040830fe84033113228d9",
  "trx_in_block": 5,
  "virtual_op": 0
}

{
  "block": 43686030,
  "op": [
    "vote",
    {
      "author": "olonaa",
      "permlink": "fqapf56cvtzybn",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T21:12:48",
  "trx_id": "cb4afbb4be160a0950a0e9da4ebdf1aa9ae92c9d",
  "trx_in_block": 0,
  "virtual_op": 0
}

{
  "block": 43684967,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "trasrogetib",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:18:27",
  "trx_id": "86fff1dca50959ead357540e904fb1d0fdb5062a",
  "trx_in_block": 2,
  "virtual_op": 0
}

{
  "block": 43684958,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "rdisinreler",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:18:00",
  "trx_id": "96e86bba20b9682dec32eb7eb92c6be478005747",
  "trx_in_block": 14,
  "virtual_op": 0
}

{
  "block": 43684952,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "gangcoulen",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:17:42",
  "trx_id": "596565117791caf2446e9b802c7b7ce0b39843c2",
  "trx_in_block": 3,
  "virtual_op": 0
}

{
  "block": 43684944,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "brazexguislav",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:17:18",
  "trx_id": "c539c86484312df108f8c7a36366a2f4c8978ccb",
  "trx_in_block": 13,
  "virtual_op": 0
}

{
  "block": 43684937,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "meovesbimu",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:16:57",
  "trx_id": "30fc01f77fad120f803f28e817e328e2ea5a6463",
  "trx_in_block": 3,
  "virtual_op": 0
}

{
  "block": 43684930,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "potapkin",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:16:36",
  "trx_id": "190c2f0998ea1b67ffbb2e3846fc0be782e722cf",
  "trx_in_block": 2,
  "virtual_op": 0
}

{
  "block": 43684924,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "jillyns",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:16:18",
  "trx_id": "9ad53cbf49943716518dd5c2b1ef4500905b17cc",
  "trx_in_block": 14,
  "virtual_op": 0
}

{
  "block": 43684919,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "suamily",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:16:00",
  "trx_id": "8f51cbd431089a4952e27fabd63a820550c24fcc",
  "trx_in_block": 12,
  "virtual_op": 0
}

{
  "block": 43684912,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "samlimiless1971",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:15:39",
  "trx_id": "9fb6697bb5065eb86e2e13a2bc226a7b52181eb0",
  "trx_in_block": 5,
  "virtual_op": 0
}

{
  "block": 43684906,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "rummisi",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:15:21",
  "trx_id": "b7e8df8394edb02e78d9c5090fb0c01a25b6a542",
  "trx_in_block": 14,
  "virtual_op": 0
}

{
  "block": 43684899,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "ccmsx90obgabi",
      "voter": "supernoim",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:15:00",
  "trx_id": "75c433a0be2e27faec82b7d6cd3c24c32c4b74e7",
  "trx_in_block": 2,
  "virtual_op": 0
}

{
  "block": 43684877,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "dimakiear",
      "extensions": [],
      "max_accepted_payout": "100000.000 SBD",
      "percent_steem_dollars": 10000,
      "permlink": "ccmsx90obgabi"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:13:51",
  "trx_id": "48dd6c579c28fcecfaa1f62000b1dbb8df1ffa7c",
  "trx_in_block": 5,
  "virtual_op": 0
}

{
  "block": 43684877,
  "op": [
    "comment",
    {
      "author": "dimakiear",
      "body": "https://www.youtube.com/watch?v=AmHln1mSwlM\n\nLearn the basics behind color science and photo manipulation, so you can replicate common photo effects right in MATLAB. \n\nIn this video, you will learn about science of what exactly makes up an image, and how these components play an important role in image processing. From pixels to RGB to HSV, you will learn the ways to describe the makeup of colors in a picture. \n\nNext, you will explore popular methods of photo editing, and how to do them in MATLAB. First, you’ll learn about editing the saturation of an image using the rgb2hsv command. \n\nThen, the video discusses how to rotate an image using the imrotate command. The video also walks through other effects that you can do in MATLAB as quickly as with a smartphone, including image cropping using the imcrop command and image resizing using the imresize command. \n\nFinally, the video dives into how to replicate social media filters using imadjust, showing how photo sharing apps use universal color science concepts to develop filters. \n\n\n--------------------------------------------------------------------------------------------------------\nGet a free product trial: https://goo.gl/ZHFb5u\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\nLearn more about Simulink: https://goo.gl/nqnbLe\nSee What's new in MATLAB and Simulink: https://goo.gl/pgGtod\n\n© 2020 The MathWorks, Inc. MATLAB and Simulink are registered\ntrademarks of The MathWorks, Inc. \nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.",
      "json_metadata": "{\"video\":{\"videoId\":\"AmHln1mSwlM\",\"url\":\"https://www.youtube.com/watch?v=AmHln1mSwlM\",\"title\":\"The Basics Behind Image Processing | Working with Images in MATLAB\",\"description\":\"https://www.youtube.com/watch?v=AmHln1mSwlM\\n\\nLearn the basics behind color science and photo manipulation, so you can replicate common photo effects right in MATLAB. \\n\\nIn this video, you will learn about science of what exactly makes up an image, and how these components play an important role in image processing. From pixels to RGB to HSV, you will learn the ways to describe the makeup of colors in a picture. \\n\\nNext, you will explore popular methods of photo editing, and how to do them in MATLAB. First, you’ll learn about editing the saturation of an image using the rgb2hsv command. \\n\\nThen, the video discusses how to rotate an image using the imrotate command. The video also walks through other effects that you can do in MATLAB as quickly as with a smartphone, including image cropping using the imcrop command and image resizing using the imresize command. \\n\\nFinally, the video dives into how to replicate social media filters using imadjust, showing how photo sharing apps use universal color science concepts to develop filters. \\n\\n\\n--------------------------------------------------------------------------------------------------------\\nGet a free product trial: https://goo.gl/ZHFb5u\\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\\nLearn more about Simulink: https://goo.gl/nqnbLe\\nSee What's new in MATLAB and Simulink: https://goo.gl/pgGtod\\n\\n© 2020 The MathWorks, Inc. MATLAB and Simulink are registered\\ntrademarks of The MathWorks, Inc. \\nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.\",\"owner\":\"MATLAB\",\"channelId\":\"UCgdHSFcXvkN6O3NXvif0-pA\",\"thumbnailUrl\":\"https://i.ytimg.com/vi/AmHln1mSwlM/maxresdefault.jpg\",\"datePublished\":\"2020-03-18\",\"genre\":\"Science & Technology\",\"isFamilyFriendly\":true,\"duration\":308,\"channelThumbnailUrl\":\"https://yt3.ggpht.com/a/AATXAJwGwy5K-LtzQm_gSrA5HW766O-c8cCL-k0LXw=s48-c-k-c0xffffffff-no-rj-mo\",\"providerName\":\"YouTube\",\"refs\":[]},\"tags\":[\"hive-122108\",\"programming\",\"learning\",\"education\",\"bigdata\",\"curation\",\"dtube\"],\"format\":\"markdown\"}",
      "parent_author": "",
      "parent_permlink": "hive-122108",
      "permlink": "ccmsx90obgabi",
      "title": "The Basics Behind Image Processing | Working with Images in MATLAB"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T20:13:51",
  "trx_id": "48dd6c579c28fcecfaa1f62000b1dbb8df1ffa7c",
  "trx_in_block": 5,
  "virtual_op": 0
}

{
  "block": 43684207,
  "op": [
    "vote",
    {
      "author": "enpidownkas",
      "permlink": "a2xit1txz84i",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T19:39:51",
  "trx_id": "2485e38f3dbef7035137e91fa7b66bcf73c9d2f8",
  "trx_in_block": 5,
  "virtual_op": 0
}

{
  "block": 43683801,
  "op": [
    "vote",
    {
      "author": "mewipufusoo",
      "permlink": "hxkbrrealgk",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T19:19:03",
  "trx_id": "9545f978808f108479c87ad37314cdc712a4364b",
  "trx_in_block": 21,
  "virtual_op": 0
}

{
  "block": 43682728,
  "op": [
    "vote",
    {
      "author": "a1den",
      "permlink": "k46s9ta4uqsyx43w",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T18:24:12",
  "trx_id": "bef1cb70a16c2ae6ecb4fe9e643a2569103aff42",
  "trx_in_block": 13,
  "virtual_op": 0
}

{
  "block": 43681263,
  "op": [
    "vote",
    {
      "author": "sioveltider1982",
      "permlink": "7pvo6yo985fgms7di4",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T17:09:24",
  "trx_id": "1fd0148ac94cb3ba08fde0595b6c7f6691a51bcc",
  "trx_in_block": 6,
  "virtual_op": 0
}

{
  "block": 43679840,
  "op": [
    "vote",
    {
      "author": "beauti4",
      "permlink": "13siunlvar48",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T15:57:00",
  "trx_id": "1f4040d9c48af567a99341520c0a8942489f3b87",
  "trx_in_block": 10,
  "virtual_op": 0
}

{
  "block": 43679385,
  "op": [
    "vote",
    {
      "author": "trafunmagi",
      "permlink": "dliisfl7si77oqe0",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T15:33:48",
  "trx_id": "69482486bee6efd69600587ebd105a7aa27f158c",
  "trx_in_block": 10,
  "virtual_op": 0
}

{
  "block": 43679106,
  "op": [
    "vote",
    {
      "author": "supernoim",
      "permlink": "o9a9enm3zcdzfgss",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-25T15:19:39",
  "trx_id": "7c0e067a34d5c9f1d435a1cae350d818f449d5dd",
  "trx_in_block": 1,
  "virtual_op": 0
}

{
  "block": 43586320,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "gripsaem",
      "weight": -10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-22T08:24:48",
  "trx_id": "f1ca5404431c2e4fc4a615abd048e476b3befec0",
  "trx_in_block": 14,
  "virtual_op": 0
}

{
  "block": 43572073,
  "op": [
    "vote",
    {
      "author": "gmarmoonralet",
      "permlink": "1bng2grao7g82u",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T20:20:51",
  "trx_id": "4fba6e297d8ee986e1025e93b3560aec718b5070",
  "trx_in_block": 13,
  "virtual_op": 0
}

{
  "block": 43571776,
  "op": [
    "vote",
    {
      "author": "jinnyla",
      "permlink": "3esy5aimye2sgcy",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T20:05:42",
  "trx_id": "2efa372a87574d2ec3685c842d7826fd18054309",
  "trx_in_block": 3,
  "virtual_op": 0
}

{
  "block": 43571666,
  "op": [
    "vote",
    {
      "author": "dionis10",
      "permlink": "7lfszey9rp",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T20:00:06",
  "trx_id": "f61d99b510c71fd6218af1251c0ce87303b5ab06",
  "trx_in_block": 24,
  "virtual_op": 0
}

{
  "block": 43571503,
  "op": [
    "vote",
    {
      "author": "olonaa",
      "permlink": "4cv1zde0p24de",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T19:51:54",
  "trx_id": "f0f505af17f0d115184d5ef207079e2ed209c011",
  "trx_in_block": 13,
  "virtual_op": 0
}

{
  "block": 43570314,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "sillaha",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:51:24",
  "trx_id": "03efc2e2b9442e0d3343b667fd647a9b51c0e384",
  "trx_in_block": 10,
  "virtual_op": 0
}

{
  "block": 43570307,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "gangcoulen",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:51:03",
  "trx_id": "554d8889903b11a1c48d7efcaa65a1b29bf81aa7",
  "trx_in_block": 13,
  "virtual_op": 0
}

{
  "block": 43570300,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "jinnyla",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:50:42",
  "trx_id": "493c42e2c887660ffd6988e50ce561ea927eeeb5",
  "trx_in_block": 20,
  "virtual_op": 0
}

{
  "block": 43570293,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "xiande",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:50:21",
  "trx_id": "b7260cd1a162b67145b7d2fbefcd8cb90f64e875",
  "trx_in_block": 4,
  "virtual_op": 0
}

{
  "block": 43570287,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "harromilvie",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:50:03",
  "trx_id": "ee131484d4c94076b9ea1b8aecba414a059bd1a7",
  "trx_in_block": 20,
  "virtual_op": 0
}

{
  "block": 43570280,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "writrackturly",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:49:42",
  "trx_id": "72c5b01d24b6caaef30854f1fc80a66bfefb4543",
  "trx_in_block": 4,
  "virtual_op": 0
}

{
  "block": 43570273,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "rummisi",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:49:21",
  "trx_id": "d935b58308892326665913e59681a3defc742dbb",
  "trx_in_block": 13,
  "virtual_op": 0
}

{
  "block": 43570267,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "toneya",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:49:03",
  "trx_id": "2069f2e731b7c8d798587f9486e0e5b9c7d6daac",
  "trx_in_block": 11,
  "virtual_op": 0
}

{
  "block": 43570261,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "dionis10",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:48:45",
  "trx_id": "2c154a37e5401c9876c01ef239d44bbfc3ded83c",
  "trx_in_block": 21,
  "virtual_op": 0
}

{
  "block": 43570256,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "nitpayneyglas",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:48:27",
  "trx_id": "98f94730f0f7b3792e15637b2ce74173f81cc608",
  "trx_in_block": 21,
  "virtual_op": 0
}

{
  "block": 43570250,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "mewipufusoo",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:48:09",
  "trx_id": "82bb75d18ce66fa9c5d17dd7d4e9620d2276dd21",
  "trx_in_block": 7,
  "virtual_op": 0
}

{
  "block": 43570243,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "larinni",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:47:48",
  "trx_id": "950b72fde9175e21392c9d84076fbdfd47db8505",
  "trx_in_block": 17,
  "virtual_op": 0
}

{
  "block": 43570237,
  "op": [
    "vote",
    {
      "author": "dimakiear",
      "permlink": "u5hrby9svp3qw",
      "voter": "raidustrilus1985",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:47:30",
  "trx_id": "6145a05efa17c544a5936181f7ed604c3e214636",
  "trx_in_block": 17,
  "virtual_op": 0
}

{
  "block": 43570215,
  "op": [
    "comment_options",
    {
      "allow_curation_rewards": true,
      "allow_votes": true,
      "author": "dimakiear",
      "extensions": [],
      "max_accepted_payout": "100000.000 SBD",
      "percent_steem_dollars": 10000,
      "permlink": "u5hrby9svp3qw"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:46:24",
  "trx_id": "bb1e50b904352184baffdbfeea7ab1294c28e106",
  "trx_in_block": 8,
  "virtual_op": 0
}

{
  "block": 43570215,
  "op": [
    "comment",
    {
      "author": "dimakiear",
      "body": "https://www.youtube.com/watch?v=-d7-RyErCSI\n\nLearn how to sample parameter values from covariate models in SimBiology™. Covariate models are used for nonlinear mixed-effect modeling. They allow you to see population-wide parameters while considering individual variations by including fixed parameter-covariate relationships and random effects.\n--------------------------------------------------------------------------------------------------------\nGet a free product trial: https://goo.gl/ZHFb5u\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\nLearn more about Simulink: https://goo.gl/nqnbLe\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\n\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\ntrademarks of The MathWorks, Inc. \nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.",
      "json_metadata": "{\"video\":{\"videoId\":\"-d7-RyErCSI\",\"url\":\"https://www.youtube.com/watch?v=-d7-RyErCSI\",\"title\":\"SimBiology Tutorials: Sampling Parameters from Covariate Models in SimBiology\",\"description\":\"https://www.youtube.com/watch?v=-d7-RyErCSI\\n\\nLearn how to sample parameter values from covariate models in SimBiology™. Covariate models are used for nonlinear mixed-effect modeling. They allow you to see population-wide parameters while considering individual variations by including fixed parameter-covariate relationships and random effects.\\n--------------------------------------------------------------------------------------------------------\\nGet a free product trial: https://goo.gl/ZHFb5u\\nLearn more about MATLAB: https://goo.gl/8QV7ZZ\\nLearn more about Simulink: https://goo.gl/nqnbLe\\nSee what's new in MATLAB and Simulink: https://goo.gl/pgGtod\\n\\n© 2019 The MathWorks, Inc. MATLAB and Simulink are registered\\ntrademarks of The MathWorks, Inc. \\nSee www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.\",\"owner\":\"MATLAB\",\"channelId\":\"UCgdHSFcXvkN6O3NXvif0-pA\",\"thumbnailUrl\":\"https://i.ytimg.com/vi/-d7-RyErCSI/hqdefault.jpg\",\"datePublished\":\"2020-03-17\",\"genre\":\"Science & Technology\",\"isFamilyFriendly\":true,\"duration\":212,\"channelThumbnailUrl\":\"https://yt3.ggpht.com/a/AATXAJwGwy5K-LtzQm_gSrA5HW766O-c8cCL-k0LXw=s48-c-k-c0xffffffff-no-rj-mo\",\"providerName\":\"YouTube\",\"refs\":[]},\"tags\":[\"hive-122108\",\"programming\",\"learning\",\"education\",\"bigdata\",\"curation\",\"dtube\"],\"format\":\"markdown\"}",
      "parent_author": "",
      "parent_permlink": "hive-122108",
      "permlink": "u5hrby9svp3qw",
      "title": "SimBiology Tutorials: Sampling Parameters from Covariate Models in SimBiology"
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T18:46:24",
  "trx_id": "bb1e50b904352184baffdbfeea7ab1294c28e106",
  "trx_in_block": 8,
  "virtual_op": 0
}

{
  "block": 43568871,
  "op": [
    "vote",
    {
      "author": "mewipufusoo",
      "permlink": "nwa3tf0j85evj",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T17:38:03",
  "trx_id": "1fdf2a6e5d09e5e04d57221cca14d786a1a1d41f",
  "trx_in_block": 6,
  "virtual_op": 0
}

{
  "block": 43567706,
  "op": [
    "vote",
    {
      "author": "dendysa",
      "permlink": "vg2m3b2k7g0om",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T16:38:48",
  "trx_id": "e967dc3158d2682417753c3c2aeec869383fe993",
  "trx_in_block": 3,
  "virtual_op": 0
}

{
  "block": 43567224,
  "op": [
    "vote",
    {
      "author": "vedantiy",
      "permlink": "k498rlpzz0j13nziiin",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T16:14:24",
  "trx_id": "d9106a259f0804571f1e43429ae012dca93423d0",
  "trx_in_block": 11,
  "virtual_op": 0
}

{
  "block": 43566330,
  "op": [
    "vote",
    {
      "author": "toneya",
      "permlink": "xyvszm4h17gybqi",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T15:29:00",
  "trx_id": "9464f309cb4fede5b76cbf7a52c23c784cc2a36d",
  "trx_in_block": 3,
  "virtual_op": 0
}

{
  "block": 43565545,
  "op": [
    "vote",
    {
      "author": "newmanaleks",
      "permlink": "3evj6thvwkt5jds3o51",
      "voter": "dimakiear",
      "weight": 10000
    }
  ],
  "op_in_trx": 0,
  "timestamp": "2020-05-21T14:48:48",
  "trx_id": "c3ab26aaccf9ec91ab3987100de004df0ddd9e13",
  "trx_in_block": 10,
  "virtual_op": 0
}