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Transaction

9/3/2023 01:56:18 PM
ID: 1d5f51671f...c8ef
Inputs (6)
#0
e4695e21bb91...7c61
Spent
Address:
9gJUA5j4TxJ2...JPjh
Output transaction:
3e79cf006950...6fa2
Settlement height:
1,082,668
Value:
0.005 ERG
Tokens:
Loading assets...
#1
bc39345481c3...cae5
Spent
Address:
9gJUA5j4TxJ2...JPjh
Output transaction:
bedbb8f4b833...df56
Settlement height:
1,082,668
Value:
0.005 ERG
Tokens:
Loading assets...
#2
c52ada722518...b62f
Spent
Address:
9gJUA5j4TxJ2...JPjh
Output transaction:
0850821981ed...6253
Settlement height:
1,082,668
Value:
0.005 ERG
Tokens:
Loading assets...
#3
b1de5088d936...a7ca
Spent
Address:
9gJUA5j4TxJ2...JPjh
Output transaction:
73064619b844...b607
Settlement height:
1,082,668
Value:
0.005 ERG
Tokens:
Loading assets...
#4
6383f2185763...f93e
Spent
Address:
9gJUA5j4TxJ2...JPjh
Output transaction:
8bb98de95ae9...5f12
Settlement height:
1,082,668
Value:
0.005 ERG
Tokens:
Loading assets...
#5
e52ddff818c4...73a8
Spent
Address:
9gJUA5j4TxJ2...JPjh
Output transaction:
fab9cbc52317...a969
Settlement height:
1,083,144
Value:
3.2 ERG
Tokens:
Loading assets...
Outputs (8)
#0
ef2b9946cfb0...8ffd
Spent
Address:
3NtW3QbiLwaF...bV75
Spent in transaction:
dd8563d505fb...9d11
Settlement height:
1,083,147
Value:
0.015 ERG
Tokens:
Loading assets...
#1
6c27f4e58f21...709a
Spent
Address:
3NtW3QbiLwaF...bV75
Spent in transaction:
b2b6527ba752...c628
Settlement height:
1,083,147
Value:
0.015 ERG
Tokens:
Loading assets...
#2
4bc264946dfd...1782
Spent
Address:
3NtW3QbiLwaF...bV75
Spent in transaction:
e0a2d015bdf1...497a
Settlement height:
1,083,147
Value:
0.015 ERG
Tokens:
Loading assets...
#3
e220ba53afb7...a1e4
Spent
Address:
3NtW3QbiLwaF...bV75
Spent in transaction:
db41d3b4208c...936b
Settlement height:
1,083,147
Value:
0.015 ERG
Tokens:
Loading assets...
#4
ce82c25ebd4a...1a6d
Spent
Address:
3NtW3QbiLwaF...bV75
Spent in transaction:
0e8816a74988...5f14
Settlement height:
1,083,147
Value:
0.015 ERG
Tokens:
Loading assets...
#5
1d88f0424cfb...8c2f
Spent
Address:
9gJUA5j4TxJ2...JPjh
Spent in transaction:
3705dd8475a1...aa9e
Settlement height:
1,083,147
Value:
3.14 ERG
Tokens:
Loading assets...
#6
c24869877460...8d55
Spent
Address:
9gjghouPwq9T...Azvo
Spent in transaction:
7fece15071d5...f796
Settlement height:
1,083,147
Value:
0.005 ERG
Tokens:
AHT
954.11
#7
3c8311485df0...3898
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
f3ce5b12f8c4...8915
Settlement height:
1,083,147
Value:
0.005 ERG
Transaction Details
Status: Confirmed
Size: 8.53 KB
Received time: 9/3/2023 01:56:18 PM
Included in blocks: 1,083,147
Confirmations: 693,694
Total coins transferred: 3.23 ERG
Fees: 0.005 ERG
Fees per byte: 0.000000572 ERG
Raw Transaction Data
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      "ergoTree": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(eaccb7,c94ac1,...)))}",
      "address": "9gJUA5j4TxJ2bMVNHSnvS7BpxhcDn7ufQa86utZGRbCHaGgJPjh",
      "assets": [
        {
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        {
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        {
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        {
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          "name": "Unreal pretty 4 - just fantasy",
          "decimals": 0,
          "type": "EIP-004"
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        {
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          "name": "WomanArts9",
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          "type": "EIP-004"
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        {
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          "name": "Stand with Ukraine",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "amount": 1,
          "name": "WomanArts24",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "amount": 76632759,
          "name": "AHT",
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          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "573d9010b852894b9f99bc072933e6cfa115b490f857451e385dbc2e8448cf7c",
      "value": 4219364,
      "index": 0,
      "outputBlockId": "b3cfb684232fe21e89a8132c966b08c6772b72369822c397d25a7bc8e98c9bda",
      "outputTransactionId": "aa58e9d389d3044fda4201159d5d62752e0820f8d0b8506cec28ac4fd0ea826e",
      "outputIndex": 0,
      "ergoTree": "0008cd03b04048a9708f0a2b109d75513a2483e3b9ede622efb3cc03bdddf93bccd93ac5",
      "address": "9hoRnjysKfkwZSCgSFNzSXMohwYn8DqruuYxD6vT7Ubw55qnwiZ",
      "assets": [],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0e240008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8"
        },
        "R6": {
          "serializedValue": "0580dac409",
          "sigmaType": "SLong",
          "renderedValue": "10000000"
        },
        "R8": {
          "serializedValue": "058084af5f",
          "sigmaType": "SLong",
          "renderedValue": "100000000"
        },
        "R7": {
          "serializedValue": "110280dddb0180fca402",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1800000,2400000]"
        },
        "R4": {
          "serializedValue": "0428",
          "sigmaType": "SInt",
          "renderedValue": "20"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "ef2b9946cfb00b7c08d099591d799624a967a66ec95364a056963d58846d8ffd",
      "transactionId": "1d5f51671f75e2d8ce5a28bce3a618b44c2e72ef6d773a5e8982a62f94e3c8ef",
      "blockId": "446cb634b2eed3e7eaddc4e761ee83bdf779ea9c827aefa0e77bd79542ed0296",
      "value": 15000000,
      "index": 0,
      "globalIndex": 32320945,
      "creationHeight": 1083145,
      "settlementHeight": 1083147,
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      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val coll2 = Coll[Byte]()\n  val l3 = SELF.value\n  val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n  val l5 = tuple4._2\n  val opt6 = SELF.R6[Coll[Long]]\n  val coll7 = opt6.get\n  val l8 = coll7(placeholder[Int](1))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n  val bool11 = l10 < l8\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val l13 = CONTEXT.preHeader.timestamp\n  val tuple14 = SELF.R5[(Long, Long)].get\n  val l15 = tuple14._1\n  val l16 = tuple14._2\n  val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n  val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n  val i19 = box18.R4[Int].get\n  val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll21 = box20.tokens\n  val l22 = box20.value\n  val tuple23 = (coll2, l22)\n  val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n  val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n  val coll26 = box25.tokens\n  val l27 = box25.value\n  val tuple28 = (coll2, l27)\n  val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n  val coll30 = SELF.R8[Coll[Byte]].get\n  val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n  sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n        val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n        val i33 = OUTPUTS.size\n        val box34 = OUTPUTS(placeholder[Int](13))\n        val l35 = placeholder[Long](14) * box18.R6[Long].get\n        val box36 = box20\n        val coll37 = coll21\n        val l38 = l22\n        val tuple39 = tuple23\n        val tuple40 = tuple24\n        val box41 = box25\n        val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n        val opt43 = box42.R4[Int]\n        val bool44 = opt43.isDefined\n        val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n          val i45 = opt43.getOrElse(placeholder[Int](17))\n          if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n        )} else { placeholder[Int](23) }\n        val coll46 = coll26\n        val l47 = l27\n        val tuple48 = tuple28\n        val tuple49 = tuple29\n        val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n        val tuple51 = coll1(placeholder[Int](25))\n        ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n                val i52 = opt43.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i54 = coll53.size\n                    coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n              val tuple40 = box32.R5[(Long, Long)].get\n              (tuple40._1 == l15) && (tuple40._2 <= l13)\n            )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "1837e646c5876d11f70e30bbf827095235af152d861be36b4c781c02a9ae2c6c",
          "index": 0,
          "amount": 1,
          "name": "LiveArts 46",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59fcf3cfb5cb62a0a3f0aee862",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693749738750,1697634978000]"
        },
        "R6": {
          "serializedValue": "110280d88ee16f80a8d6b907",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[15000000000,1000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        }
      },
      "spentTransactionId": "dd8563d505fb05c5e706dc6470e929a188ce8bbe753cfbf03e99edbb81569d11",
      "mainChain": true
    },
    {
      "boxId": "6c27f4e58f219c8f476ed864859b1e545e47ba1554fe2b933a8d81ee8a66709a",
      "transactionId": "1d5f51671f75e2d8ce5a28bce3a618b44c2e72ef6d773a5e8982a62f94e3c8ef",
      "blockId": "446cb634b2eed3e7eaddc4e761ee83bdf779ea9c827aefa0e77bd79542ed0296",
      "value": 15000000,
      "index": 1,
      "globalIndex": 32320946,
      "creationHeight": 1083145,
      "settlementHeight": 1083147,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val coll2 = Coll[Byte]()\n  val l3 = SELF.value\n  val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n  val l5 = tuple4._2\n  val opt6 = SELF.R6[Coll[Long]]\n  val coll7 = opt6.get\n  val l8 = coll7(placeholder[Int](1))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n  val bool11 = l10 < l8\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val l13 = CONTEXT.preHeader.timestamp\n  val tuple14 = SELF.R5[(Long, Long)].get\n  val l15 = tuple14._1\n  val l16 = tuple14._2\n  val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n  val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n  val i19 = box18.R4[Int].get\n  val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll21 = box20.tokens\n  val l22 = box20.value\n  val tuple23 = (coll2, l22)\n  val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n  val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n  val coll26 = box25.tokens\n  val l27 = box25.value\n  val tuple28 = (coll2, l27)\n  val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n  val coll30 = SELF.R8[Coll[Byte]].get\n  val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n  sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n        val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n        val i33 = OUTPUTS.size\n        val box34 = OUTPUTS(placeholder[Int](13))\n        val l35 = placeholder[Long](14) * box18.R6[Long].get\n        val box36 = box20\n        val coll37 = coll21\n        val l38 = l22\n        val tuple39 = tuple23\n        val tuple40 = tuple24\n        val box41 = box25\n        val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n        val opt43 = box42.R4[Int]\n        val bool44 = opt43.isDefined\n        val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n          val i45 = opt43.getOrElse(placeholder[Int](17))\n          if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n        )} else { placeholder[Int](23) }\n        val coll46 = coll26\n        val l47 = l27\n        val tuple48 = tuple28\n        val tuple49 = tuple29\n        val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n        val tuple51 = coll1(placeholder[Int](25))\n        ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n                val i52 = opt43.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i54 = coll53.size\n                    coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n              val tuple40 = box32.R5[(Long, Long)].get\n              (tuple40._1 == l15) && (tuple40._2 <= l13)\n            )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "abb2290e9b19e75afbc5a7038929dd6e5f602cfc0c557f54fc25b17db28e13e8",
          "index": 0,
          "amount": 1,
          "name": "LiveArts 42",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59fcf3cfb5cb62a0a3f0aee862",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693749738750,1697634978000]"
        },
        "R6": {
          "serializedValue": "110280d88ee16f80a8d6b907",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[15000000000,1000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        }
      },
      "spentTransactionId": "b2b6527ba752eedb29e8289e3b2feaf95966bb046687f912f15b9c2eb71ac628",
      "mainChain": true
    },
    {
      "boxId": "4bc264946dfde434210d3d0afcaaa9475b9853deb4535ab86705541ec3591782",
      "transactionId": "1d5f51671f75e2d8ce5a28bce3a618b44c2e72ef6d773a5e8982a62f94e3c8ef",
      "blockId": "446cb634b2eed3e7eaddc4e761ee83bdf779ea9c827aefa0e77bd79542ed0296",
      "value": 15000000,
      "index": 2,
      "globalIndex": 32320947,
      "creationHeight": 1083145,
      "settlementHeight": 1083147,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val coll2 = Coll[Byte]()\n  val l3 = SELF.value\n  val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n  val l5 = tuple4._2\n  val opt6 = SELF.R6[Coll[Long]]\n  val coll7 = opt6.get\n  val l8 = coll7(placeholder[Int](1))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n  val bool11 = l10 < l8\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val l13 = CONTEXT.preHeader.timestamp\n  val tuple14 = SELF.R5[(Long, Long)].get\n  val l15 = tuple14._1\n  val l16 = tuple14._2\n  val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n  val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n  val i19 = box18.R4[Int].get\n  val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll21 = box20.tokens\n  val l22 = box20.value\n  val tuple23 = (coll2, l22)\n  val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n  val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n  val coll26 = box25.tokens\n  val l27 = box25.value\n  val tuple28 = (coll2, l27)\n  val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n  val coll30 = SELF.R8[Coll[Byte]].get\n  val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n  sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n        val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n        val i33 = OUTPUTS.size\n        val box34 = OUTPUTS(placeholder[Int](13))\n        val l35 = placeholder[Long](14) * box18.R6[Long].get\n        val box36 = box20\n        val coll37 = coll21\n        val l38 = l22\n        val tuple39 = tuple23\n        val tuple40 = tuple24\n        val box41 = box25\n        val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n        val opt43 = box42.R4[Int]\n        val bool44 = opt43.isDefined\n        val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n          val i45 = opt43.getOrElse(placeholder[Int](17))\n          if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n        )} else { placeholder[Int](23) }\n        val coll46 = coll26\n        val l47 = l27\n        val tuple48 = tuple28\n        val tuple49 = tuple29\n        val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n        val tuple51 = coll1(placeholder[Int](25))\n        ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n                val i52 = opt43.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i54 = coll53.size\n                    coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n              val tuple40 = box32.R5[(Long, Long)].get\n              (tuple40._1 == l15) && (tuple40._2 <= l13)\n            )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "3NtW3QbiLwaF7f2h7NyiFZwSV3LqNwFNBH5HQgzeGtttvsLCS4e19bjkpDbuNbzBXtjvK3eyi94G9YNjeR94F4ix5iAXHSwmSsZ2ftbMCBfxf9JfgouBAvbrcKoDnioJmQdTfQLi8ubzsnzfi3aCE9sV1mXLxob6Dto5XCCGhuBXEB631qRpxaWkASSpgwHhAJdJQcM1ikTtfTXcVmx7n3rtQ83i1xvb4zaJYHA4SGBwT4je2dFd27k8gRpvTgk5RbxxzsiBTpdbyB1a2eEfHfyQztYrC7NPD6M94aiHKtfzCvXjGZPpFohMLsdV4H8yggtqeiay3Nxj2MctjkyTWfKkr1dbWit9bHGyT58fXMpPbBr96NQfZsPNgWFMpusN2VJo9LyMFaGZYZgDyzykTuD6UvwfC2GBLuW1bk12YvuTbqhszbxVaWjf47Kzm13xkotdseL6a7NTULKFbFv8uLUVindCiqu4Gbv26V6kh9xCSM9vPvbqw67uH4QXUcj2N2THFS8CjZkatjHBQhMzDngiAyd8jKfhqa9w6N87S2jJNnZoKT87tKqLXA5oyvVfz4BNFqhHANfGfrQvAXLfoiZ2nCRyYYcy1BCvQ8TWiwf48MPuhKcipa5UdrndgAe7EZrVB3SbFnP7a3KfHkX36LfZBxbH7V2g9C3a9JnkkFhAFM1wfBYrvbJbSN8siGqEusfPh3D6UFAwNNN9aAKiYXZE3H1u4zVb8trNawRp7Ye3Rr8bTBEqX65xs1jpdZCzHUzQMikjBsUaRrCtkWut3PEtmVeQXUVRKwz2eYFaE4sX2zUuMuswKY911Lw38jNHcmUdwXYXCEEZNGY4b2LbMjyMpFHcnM5PMdoAPtx21LTB2oSMqGGcDPr5kigNeYUacjxEjimhMSnxYiVhnoQPKjftvzJwtvdT55fewwLGcRUDP8Koa31pkjubLtpPbiXCyiZ4iXZ2c1M82Wpxsb6EpGvkuhm5iiUi6Kdj6Ya4fzJhmgZLJZu57TxxTr1AB3EfH4AYqnKhrJeBwb5jcv5YD8vtWVeZ53wDaBGyEgkCZxZvgff4rkX2yBu3pCpQZheTxUepQzykqNJck3Y2gMJcC8nxYyjbtpgckReo2LT4bZi5DKsyv6QNWruenSEd3KavrMuyaiBu3LFxxvKwGJFXfZiEku5pALnbi15npqHuxhmwXwhbQFXUVfwviHsJH71qY889oQjERkweQkEB9AFk8hkkLG5aGyWruGLJa3546CPc6Zvbqwt33CZGbpo7jcuuG4rP4G2dpefASG8H45A8NeiGcQq3LXCvAw9MyzLmkVpvFG71nqurqdJCexWcawiLC1QiQwis4AFn9qgf4TLNprpAHPWr1nYAXa78f8DiXy5ahCNjArVq1SdseuFG3S1aoCEP8hbTWmHzBeRmJVsGhJXpNi2h9UiePxWsBBzVm5usMpsaBuckmxxXJyQAantCqFCVXcB71ZLi3pUjTYv2E4Ldf8QEjuSHMqmUv8HWvUudHRiPpCnqoyxyzjQtjbbcqAaSo7zKF1i3d6swUQbcjyULQTkL2oPwYy6vB7yenYXrCEWmyV85iH3wdYzdJj6CYoD5vRKAoNh1kMxZ82nkyB7KoCqr3AePVdSoWned8LMURXdGDdGCpVr7QtcHBL2E3RY4A3drPYpc1DWct8gwPGbowLJkHLNhPwsxTuLReLuotmT7Gheyd6NYUFtz1aWM516uNdDDg5bEPGXzJAGEx1UjZArrStByZcMKRDYVMG6NtNjLvDJCZEvLgBRG1Bi79mgBBbV75",
      "assets": [
        {
          "tokenId": "ae3b8449d6713a608ae33999f56dc1ddb1036523a1c290c46a1cde0bde2b3b95",
          "index": 0,
          "amount": 1,
          "name": "LiveArts 45",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59fcf3cfb5cb62a0a3f0aee862",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693749738750,1697634978000]"
        },
        "R6": {
          "serializedValue": "110280d88ee16f80a8d6b907",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[15000000000,1000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        }
      },
      "spentTransactionId": "e0a2d015bdf1c8b47adb0b9da588ba4fc90c586cf9c8c2907f3beef37614497a",
      "mainChain": true
    },
    {
      "boxId": "e220ba53afb7360350d445eb316f653dc48f0bcfd8557e82881edbceabf1a1e4",
      "transactionId": "1d5f51671f75e2d8ce5a28bce3a618b44c2e72ef6d773a5e8982a62f94e3c8ef",
      "blockId": "446cb634b2eed3e7eaddc4e761ee83bdf779ea9c827aefa0e77bd79542ed0296",
      "value": 15000000,
      "index": 3,
      "globalIndex": 32320948,
      "creationHeight": 1083145,
      "settlementHeight": 1083147,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val coll2 = Coll[Byte]()\n  val l3 = SELF.value\n  val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n  val l5 = tuple4._2\n  val opt6 = SELF.R6[Coll[Long]]\n  val coll7 = opt6.get\n  val l8 = coll7(placeholder[Int](1))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n  val bool11 = l10 < l8\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val l13 = CONTEXT.preHeader.timestamp\n  val tuple14 = SELF.R5[(Long, Long)].get\n  val l15 = tuple14._1\n  val l16 = tuple14._2\n  val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n  val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n  val i19 = box18.R4[Int].get\n  val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll21 = box20.tokens\n  val l22 = box20.value\n  val tuple23 = (coll2, l22)\n  val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n  val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n  val coll26 = box25.tokens\n  val l27 = box25.value\n  val tuple28 = (coll2, l27)\n  val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n  val coll30 = SELF.R8[Coll[Byte]].get\n  val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n  sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n        val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n        val i33 = OUTPUTS.size\n        val box34 = OUTPUTS(placeholder[Int](13))\n        val l35 = placeholder[Long](14) * box18.R6[Long].get\n        val box36 = box20\n        val coll37 = coll21\n        val l38 = l22\n        val tuple39 = tuple23\n        val tuple40 = tuple24\n        val box41 = box25\n        val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n        val opt43 = box42.R4[Int]\n        val bool44 = opt43.isDefined\n        val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n          val i45 = opt43.getOrElse(placeholder[Int](17))\n          if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n        )} else { placeholder[Int](23) }\n        val coll46 = coll26\n        val l47 = l27\n        val tuple48 = tuple28\n        val tuple49 = tuple29\n        val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n        val tuple51 = coll1(placeholder[Int](25))\n        ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n                val i52 = opt43.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i54 = coll53.size\n                    coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n              val tuple40 = box32.R5[(Long, Long)].get\n              (tuple40._1 == l15) && (tuple40._2 <= l13)\n            )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "e2aafb7dcae26415e5b2f07c7610bb02b0590b6112e263acf6d93f3fe5e74319",
          "index": 0,
          "amount": 1,
          "name": "LiveArts 43",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59fcf3cfb5cb62a0a3f0aee862",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693749738750,1697634978000]"
        },
        "R6": {
          "serializedValue": "110280d88ee16f80a8d6b907",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[15000000000,1000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
        }
      },
      "spentTransactionId": "db41d3b4208c086bcee345a38cd954d0d6ce7f93c2dc9fb62d92dc0a60f8936b",
      "mainChain": true
    },
    {
      "boxId": "ce82c25ebd4afa975465a1fc71195ea5f230c3bc88757cf844e584afbb1f1a6d",
      "transactionId": "1d5f51671f75e2d8ce5a28bce3a618b44c2e72ef6d773a5e8982a62f94e3c8ef",
      "blockId": "446cb634b2eed3e7eaddc4e761ee83bdf779ea9c827aefa0e77bd79542ed0296",
      "value": 15000000,
      "index": 4,
      "globalIndex": 32320949,
      "creationHeight": 1083145,
      "settlementHeight": 1083147,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val coll2 = Coll[Byte]()\n  val l3 = SELF.value\n  val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n  val l5 = tuple4._2\n  val opt6 = SELF.R6[Coll[Long]]\n  val coll7 = opt6.get\n  val l8 = coll7(placeholder[Int](1))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n  val bool11 = l10 < l8\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val l13 = CONTEXT.preHeader.timestamp\n  val tuple14 = SELF.R5[(Long, Long)].get\n  val l15 = tuple14._1\n  val l16 = tuple14._2\n  val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n  val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n  val i19 = box18.R4[Int].get\n  val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll21 = box20.tokens\n  val l22 = box20.value\n  val tuple23 = (coll2, l22)\n  val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n  val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n  val coll26 = box25.tokens\n  val l27 = box25.value\n  val tuple28 = (coll2, l27)\n  val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n  val coll30 = SELF.R8[Coll[Byte]].get\n  val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n  sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n        val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n        val i33 = OUTPUTS.size\n        val box34 = OUTPUTS(placeholder[Int](13))\n        val l35 = placeholder[Long](14) * box18.R6[Long].get\n        val box36 = box20\n        val coll37 = coll21\n        val l38 = l22\n        val tuple39 = tuple23\n        val tuple40 = tuple24\n        val box41 = box25\n        val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n        val opt43 = box42.R4[Int]\n        val bool44 = opt43.isDefined\n        val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n          val i45 = opt43.getOrElse(placeholder[Int](17))\n          if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n        )} else { placeholder[Int](23) }\n        val coll46 = coll26\n        val l47 = l27\n        val tuple48 = tuple28\n        val tuple49 = tuple29\n        val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n        val tuple51 = coll1(placeholder[Int](25))\n        ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n                val i52 = opt43.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i54 = coll53.size\n                    coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n              val tuple40 = box32.R5[(Long, Long)].get\n              (tuple40._1 == l15) && (tuple40._2 <= l13)\n            )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
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