Transaction
ID: dd357de651...f140
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
119,999.99
Spent
Address:
Output transaction:
Settlement height:
Value:
0.693 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.203 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Outputs (4)
Unspent
Address:
Settlement height:
Value:
0.4 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.495 ERG
Tokens:
119,999.99
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 67,069
Total coins transferred: 0.898 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000478 ERG
Raw Transaction Data
{
"id": "dd357de6516b59df80fc0885a2f35ee82dd6b352c9fb573bca9129b4e0f9f140",
"blockId": "5ad70b5198bd51ed6158725a77c76d5e525722ec5053a11d90887e53a104659f",
"inclusionHeight": 1705170,
"timestamp": 1769063941547,
"index": 2,
"globalIndex": 10182802,
"numConfirmations": 67069,
"inputs": [
{
"boxId": "6500ac998e1b8aa7c97b4703b714c4374b3bc2b78e47a599c0ad84a10afde655",
"value": 1000000,
"index": 0,
"spendingProof": "28144eeaa457a5e608ea242783ad318266d5e9135ad02406122415f2b8240eedcfbbc3e3fba6dadf9ca5118715016a5f0e6b3b9207856088",
"outputBlockId": "750934efcb03227d4cd10a6424e567602015e516d74d013b82f2c2fb4c5e31f7",
"outputTransactionId": "7a19c51310e83f55c59c2bd048d04bb4b6532d99f401784faed81271607bbad3",
"outputIndex": 2,
"outputGlobalIndex": 53115065,
"outputCreatedAt": 1705054,
"outputSettledAt": 1705055,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [
{
"tokenId": "5864e8fd882300f56771e12f2ab5612c6d29e068dff4c5ac2074878ec3b4f172",
"index": 0,
"amount": 11999999,
"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0500",
"sigmaType": "SLong",
"renderedValue": "0"
},
"R5": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
},
"R6": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
},
"R7": {
"serializedValue": "0e2050565b76a30db77c52912d10ae1292a629c2ee689f3a9de07e6ad6c4f6f02918",
"sigmaType": "Coll[SByte]",
"renderedValue": "50565b76a30db77c52912d10ae1292a629c2ee689f3a9de07e6ad6c4f6f02918"
}
}
},
{
"boxId": "80f5f39ea00ce336855947bb78594e2694846792d688d0735a27eeb73c229bfa",
"value": 693000000,
"index": 1,
"spendingProof": "679a7c027de1a6da69be8e10dbee47dbd120a3891af5d6a72e8e15929178d47415a2eb18515fbc17d7c42f2b8a88186b1632aad9f137db30",
"outputBlockId": "e155780de304891920c05d5af0b055dd5973a91f6a26e9f1a52d2d9bbe98676c",
"outputTransactionId": "8bc0d1cd64cf831ec977544789f243ab2736b986a7a34fd3dac080894a2f665a",
"outputIndex": 1,
"outputGlobalIndex": 53115164,
"outputCreatedAt": 1705061,
"outputSettledAt": 1705062,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "b6f782a8a2656039d3f1feff44435d56661f9fea9ca515c92b21d79977bbecee",
"value": 203000000,
"index": 2,
"spendingProof": "9e52906e9360724ca30a444e932d30f320f8fc1c785ddb4f6050926dc04a8f13a5d24a8fff69896b570d041d7ac46aad518397962572754f",
"outputBlockId": "24747f4b1dac93c0048bec996a21b2bb3dd72129c22880ce85a407641740e996",
"outputTransactionId": "986baa16ab9a5f7e4eeaacfff154211d4e6de6fc24be1959fb3bb35bd59e94aa",
"outputIndex": 1,
"outputGlobalIndex": 53117885,
"outputCreatedAt": 1705153,
"outputSettledAt": 1705156,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(103,-25,7,-66,31,0,-59,-89,-40,-67,-12,-20,-83,-87,-32,-112,105,-42,6,-89,-40,-32,89,17,66,-56,-69,24,-100,-103,49,85)\n3: 3\n4: 0\n5: 0\n6: 0\n7: CBigInt(10000000000000000)\n8: 0\n9: 0\n10: Coll(-78,-19,-13,108,95,63,23,72,-81,59,100,-30,-20,-118,47,-20,-107,102,43,17,-42,100,-47,-100,-42,8,98,-28,-55,58,111,100)\n11: 0\n12: 1\n13: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n14: 0\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 2\n35: 0\n36: 0\n37: 0\n38: 1\n39: 0\n40: 1\n41: 10000000\n42: 1\n43: 1000000\n44: 1000\n45: 1000\n46: 0\n47: 0\n48: 0\n49: 0\n50: 1000000\n51: 10000000\n52: 5\n53: 1000000\n54: 10000000\n55: 100000000\n56: 100000000\n57: 100000000\n58: 0\n59: 1\n60: 3\n61: 2\n62: 3\n63: 5\n64: 6\n65: 7\n66: 1000\n67: 1\n68: 1\n69: 980000\n70: 1000000\n71: CBigInt(1)\n72: 0\n73: 0\n74: 0\n75: 0\n76: -1\n77: 1\n78: 1\n79: 2000000\n80: 0\n81: 0\n82: 0\n83: true\n84: 0\n85: 1000000",
"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Byte]].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n })\n val coll3 = SELF.propositionBytes\n val coll4 = placeholder[Coll[Byte]](2)\n val coll5 = SELF.R9[Coll[Long]].get\n val l6 = coll5(placeholder[Int](3))\n val coll7 = SELF.tokens\n val tuple8 = coll7(placeholder[Int](4))\n val coll9 = tuple8._1\n val coll10 = SELF.R4[Coll[Byte]].get\n val ge11 = SELF.R5[GroupElement].get\n val l12 = SELF.R6[Long].get\n val coll13 = SELF.R8[Coll[Byte]].get\n val l14 = SELF.value\n val func15 = {(box15: Box) =>\n val coll17 = box15.propositionBytes\n val bool18 = coll17 == coll3\n bool18\n }\n val coll16 = OUTPUTS.filter(func15)\n val box17 = coll16.getOrElse(placeholder[Int](5), SELF)\n val coll18 = box17.tokens\n val tuple19 = coll18(placeholder[Int](6))\n val l20 = tuple19._2\n val bi21 = placeholder[BigInt](7)\n val bi22 = CONTEXT.dataInputs.filter({(box22: Box) =>\n val coll24 = box22.tokens\n (coll24.size > placeholder[Int](8)) && (coll24(placeholder[Int](9))._1 == placeholder[Coll[Byte]](10))\n })(placeholder[Int](11)).R5[BigInt].get\n val l23 = tuple8._2\n val bi24 = l23.toBigInt\n val coll25 = coll7.slice(placeholder[Int](12), coll7.size)\n val coll26 = placeholder[Coll[Byte]](13)\n val func27 = {(box27: Box) =>\n val coll29 = box27.propositionBytes\n val coll30 = blake2b256(coll29)\n val bool31 = coll30 == coll4\n bool31\n }\n val coll28 = OUTPUTS.filter(func27)\n val box29 = coll28.getOrElse(placeholder[Int](14), SELF)\n val coll30 = box29.tokens\n val tuple31 = coll30(placeholder[Int](15))\n val l32 = coll5(placeholder[Int](16))\n val i33 = INPUTS.filter({(box33: Box) => box33.propositionBytes == coll3 }).size\n val bool34 = i33 == placeholder[Int](17)\n val l35 = HEIGHT.toLong\n val l36 = coll5(placeholder[Int](18))\n val l37 = coll5(placeholder[Int](19))\n val l38 = l36 + l37\n val l39 = coll5(placeholder[Int](20))\n val coll40 = coll13.slice(placeholder[Int](21), placeholder[Int](22))\n val coll41 = coll13.slice(placeholder[Int](23), placeholder[Int](24))\n val l42 = coll5(placeholder[Int](25))\n val bi43 = bi24 * bi22 / bi21\n val bi44 = if (l35 < l38) {(\n val i44 = placeholder[Int](26)\n bi43 * l42.toBigInt + i44.toBigInt / i44.toBigInt\n )} else { bi43 }\n val box45 = coll28.getOrElse(placeholder[Int](27), SELF)\n val coll46 = box45.tokens\n val tuple47 = coll46(placeholder[Int](28))\n val func48 = {(box48: Box) =>\n val coll50 = box48.propositionBytes\n val coll51 = blake2b256(coll50)\n val bool52 = coll51 == coll4\n bool52\n }\n val coll49 = OUTPUTS.filter(func48)\n val box50 = coll49.getOrElse(placeholder[Int](29), SELF)\n val coll51 = box50.tokens\n val tuple52 = coll51(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func53 = func15\n val coll54 = coll16\n val i55 = coll54.size\n val func56 = func27\n val coll57 = coll28\n val box58 = coll2.getOrElse(placeholder[Int](32), SELF)\n val coll59 = box58.R4[Coll[Long]].get\n val l60 = coll59(placeholder[Int](33))\n val l61 = coll59(placeholder[Int](34))\n if (i55 > placeholder[Int](35)) {(\n val box62 = box17\n val bool63 = OUTPUTS.map({(box63: Box) => box63.id }).indexOf(box62.id, placeholder[Int](36)) == box58.R9[Coll[Int]].get(\n placeholder[Int](37)\n ) - placeholder[Int](38)\n val l64 = box62.value\n val coll65 = coll18\n val tuple66 = tuple19\n val coll67 = box62.R4[Coll[Byte]].get\n val ge68 = box62.R5[GroupElement].get\n val coll69 = box62.R7[Coll[Byte]].get\n val bool70 = ((((l64 >= l6) && (tuple66._1 == coll9)) && (coll67 == coll10)) && (ge68 == ge11)) && (coll69 == coll1)\n val coll71 = box62.R8[Coll[Byte]].get\n val l72 = box62.R6[Long].get\n val coll73 = box62.R9[Coll[Long]].get\n val bool74 = coll73 == coll5\n if (coll57.size > placeholder[Int](39)) {(\n val bi75 = l20.toBigInt\n val box76 = box29\n val coll77 = coll30\n val tuple78 = coll77(placeholder[Int](40))\n val tuple79 = tuple31\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (l64 >= l14)) && (l64 <= l14 + placeholder[Long](41))) && (\n bi75 >= bi24 - tuple78._2.toBigInt * bi21 / bi22\n )\n ) && (coll65.slice(placeholder[Int](42), coll65.size) == coll25)\n ) && (l72 == l12)\n ) && bool74\n ) && (((box76.value >= placeholder[Long](43)) && (tuple79._1 == coll9)) && (tuple78._1 == coll26))\n ) && (tuple79._2 == l23 - l20)\n ) && (l60.toBigInt >= bi75 * bi22 / bi21 * l32.toBigInt / placeholder[Int](44).toBigInt)\n ) && bool34\n ) && (l35 >= l38)\n )\n )} else {(\n val bi75 = l60.toBigInt\n val i76 = placeholder[Int](45)\n val bi77 = l20.toBigInt * bi22 / bi21 * l32.toBigInt / i76.toBigInt\n val bool78 = bi75 >= bi77\n val prop79 = sigmaProp(INPUTS.filter({(box79: Box) =>\n val coll81 = box79.tokens\n ((coll81.size > placeholder[Int](46)) && (coll81(placeholder[Int](47))._1 == coll40)) && (box79.R9[Coll[Coll[Byte]]].get(INPUTS.indexOf(SELF, placeholder[Int](48))) == coll41)\n }).size > placeholder[Int](49)) || proveDlog(ge11)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (l64 >= l14 - placeholder[Long](50))) && (l64 <= l14 + placeholder[Long](51))) && (\n coll65 == coll7\n )\n ) && (l72 > l35 + l39)\n ) && (l72 < l35 + l39 + placeholder[Long](52))\n ) && (bi75 < bi77)\n ) && bool74\n ) && bool34\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (l64 >= l14 - placeholder[Long](53))) && (l64 <= l14 + placeholder[Long](54))) && (\n coll65 == coll7\n )\n ) && (l12 != placeholder[Long](55))\n ) && (l72 == placeholder[Long](56))\n ) && bool78\n ) && bool74\n ) && bool34\n ) || prop79 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (bi75 >= bi44 * l61.toBigInt / i76.toBigInt)) && (tuple66 == tuple8)) && (\n l72 == placeholder[Long](57)\n )\n ) && bool78\n ) && ((coll73(placeholder[Int](58)) == l61) && (coll73(placeholder[Int](59)) == coll59(placeholder[Int](60))))\n ) && (i33 == i55)\n ) && (coll73(placeholder[Int](61)) == l39)\n ) && (coll73(placeholder[Int](62)) == l6)\n ) && (coll73(placeholder[Int](63)) == l36)\n ) && (coll73(placeholder[Int](64)) == l42)\n ) && (coll73(placeholder[Int](65)) == l37)\n ) || prop79 && sigmaProp(\n ((((((bool70 && (l64 == l14)) && (coll65 == coll7)) && (coll67 == coll10)) && (ge68 == ge11)) && (coll69 == coll1)) && bool74) && (i33 == i55)\n )\n )}\n )} else {(\n val bi62 = l60.toBigInt\n val i63 = placeholder[Int](66)\n val box64 = box45\n val coll65 = coll46\n val tuple66 = tuple47\n val tuple67 = coll65(placeholder[Int](67))\n val coll68 = SELF.id\n val bi69 = bi62 - bi44\n val bi70 = coll5(placeholder[Int](68)).toBigInt\n val bi71 = bi69 * i63.toBigInt - bi70 / i63.toBigInt\n val l72 = tuple67._2\n sigmaProp(\n (\n (\n (\n (\n (((bi62 <= bi44 * l32.toBigInt / i63.toBigInt) && (l35 >= l12)) || (l35 > SELF.creationInfo._1.toLong + placeholder[Long](69))) && (\n (((box64.value >= placeholder[Long](70)) && (tuple66._1 == coll9)) && (tuple67._1 == coll26)) && (box64.id != coll68)\n )\n ) && (tuple66._2 == l23)\n ) && if (bi71 < placeholder[BigInt](71)) { l72.toBigInt >= bi62 } else {(\n val box73 = OUTPUTS.filter({(box73: Box) => box73.propositionBytes == coll10 }).getOrElse(placeholder[Int](72), SELF)\n val tuple74 = box73.tokens(placeholder[Int](73))\n (((l72.toBigInt >= bi44 + bi69 * bi70 / i63.toBigInt) && (tuple74._2.toBigInt >= bi71)) && (tuple74._1 == coll26)) && (box73.id != coll68)\n )}\n ) && (\n INPUTS.map({(box73: Box) => box73.id }).indexOf(coll68, placeholder[Int](74)) == box58.R9[Coll[Int]].get(placeholder[Int](75)) * placeholder[Int](\n 76\n ) - placeholder[Int](77)\n )\n ) && bool34\n )\n )}\n )} else {(\n val func53 = func48\n val coll54 = coll49\n val box55 = box50\n val coll56 = coll51\n val tuple57 = tuple52\n val tuple58 = coll56(placeholder[Int](78))\n sigmaProp(\n (\n (\n (((((box55.value >= placeholder[Long](79)) && (tuple57._1 == coll9)) && (tuple58._1 == coll26)) && (box55.id != SELF.id)) && (tuple57._2 == l23)) && (\n tuple58._2.toBigInt > bi44\n )\n ) && if (INPUTS.filter({(box59: Box) =>\n val coll61 = box59.tokens\n ((coll61.size > placeholder[Int](80)) && (coll61(placeholder[Int](81))._1 == coll40)) && (box59.R9[Coll[Byte]].get == coll41)\n }).size > placeholder[Int](82)) { placeholder[Boolean](83) } else {(\n val box59 = OUTPUTS.filter({(box59: Box) => box59.propositionBytes == coll10 }).getOrElse(placeholder[Int](84), SELF)\n ((box59.value >= l14 - placeholder[Long](85)) && (box59.tokens == coll25)) && (box59.id != SELF.id)\n )}\n ) && bool34\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "623668c9bb119b8e7c7edffee09211bd6d7ff48499c7e1834e33c3fe9c36a025",
"index": 0,
"amount": 4000000,
"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
},
"R6": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R8": {
"serializedValue": "0e0100",
"sigmaType": "Coll[SByte]",
"renderedValue": "00"
},
"R7": {
"serializedValue": "0e20b7a6020e0fdcfdc2fe1d7b49ac656441e44bae5bf89d9bdc56418f1145dd5d75",
"sigmaType": "Coll[SByte]",
"renderedValue": "b7a6020e0fdcfdc2fe1d7b49ac656441e44bae5bf89d9bdc56418f1145dd5d75"
},
"R9": {
"serializedValue": "1108b6163c108087a70e008c93d001641e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1435,30,8,15000000,0,1705158,50,15]"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
}
},
{
"boxId": "8dda85e37ba0fb942ed01936b04814d9e59055a00220b73c8cf60b74c7ea8107",
"value": 1000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "24747f4b1dac93c0048bec996a21b2bb3dd72129c22880ce85a407641740e996",
"outputTransactionId": "986baa16ab9a5f7e4eeaacfff154211d4e6de6fc24be1959fb3bb35bd59e94aa",
"outputIndex": 3,
"outputGlobalIndex": 53117887,
"outputCreatedAt": 1705153,
"outputSettledAt": 1705156,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val box2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n })(placeholder[Int](3))\n val coll3 = box2.propositionBytes\n val coll4 = box2.R4[Coll[Long]].get\n val l5 = coll4(placeholder[Int](4))\n val coll6 = SELF.R4[Coll[Long]].get\n val l7 = coll6(placeholder[Int](5))\n val l8 = coll4(placeholder[Int](6))\n val l9 = coll6(placeholder[Int](7))\n val l10 = coll4(placeholder[Int](8))\n val l11 = coll6(placeholder[Int](9))\n val l12 = coll4(placeholder[Int](10))\n val l13 = coll6(placeholder[Int](11))\n val l14 = coll4(placeholder[Int](12))\n val l15 = coll6(placeholder[Int](13))\n val l16 = coll4(placeholder[Int](14))\n val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n val coll18 = box2.R5[Coll[Coll[Byte]]].get\n val coll19 = SELF.R6[Coll[Long]].get\n val coll20 = box2.R6[Coll[Long]].get\n val coll21 = CONTEXT.dataInputs\n val coll22 = box2.R9[Coll[Int]].get\n val i23 = coll22(placeholder[Int](15))\n val box24 = coll21(i23)\n val coll25 = box24.tokens\n val i26 = coll22(placeholder[Int](16))\n val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n val bi28 = box27.value.toBigInt\n val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n val coll30 = box2.R7[Coll[Long]].get\n val bi31 = placeholder[BigInt](22)\n val bi32 = placeholder[BigInt](23)\n val bi33 = placeholder[BigInt](24)\n val bi34 = placeholder[BigInt](25)\n val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n val tuple37 = tuple35._2\n val l38 = tuple37._2\n val box39 = tuple37._1\n val bi40 = tuple35._1\n if (l38 > placeholder[Long](26)) {(\n val bi41 = l38.toBigInt\n val bi42 = box39.R4[Int].get.toBigInt\n val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n )} else { bi40 }\n }) - placeholder[Int](28).toBigInt\n val bi36 = box24.R4[Int].get.toBigInt\n val bi37 = box24.value.toBigInt\n val l38 = placeholder[Long](29)\n val coll39 = box27.tokens\n val i40 = coll39.size\n val coll41 = box2.R8[Coll[Coll[Byte]]].get\n val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n val i43 = coll29.size\n val i44 = coll30.size\n sigmaProp(\n (\n (\n (\n (\n (\n (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n l9 == l10\n )\n ) && (l11 == l12)\n ) && (l13 == l14)\n ) && (l15 == l16)\n ) && (coll17 == coll18)\n ) && (coll19 == coll20)\n ) && placeholder[SigmaProp](32) || sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n placeholder[Int](34)\n ).toBigInt\n )\n ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n val i47 = tuple45._2\n val l48 = coll30(i47)\n val bi49 = tuple45._1\n if (l48 > placeholder[Long](40)) {(\n val box50 = coll29(i47)\n val bi51 = l48.toBigInt\n val bi52 = box50.R4[Int].get.toBigInt\n val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n )} else { bi49 }\n }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n ) && coll39.slice(placeholder[Int](45), i40).forall(\n {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n )\n ) && coll42.indices.forall({(i45: Int) =>\n val coll47 = coll29(i45).tokens\n (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n })\n ) && ((i43 == i44) && (i43 == coll42.size))\n ) && (i44 == coll41.size)\n ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n ) && (l7 == max(l8, placeholder[Long](52)))\n ) && (l9 == max(l10, placeholder[Long](53)))\n ) && (l11 == max(l12, placeholder[Long](54)))\n ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n ) && (l13 == max(l14, placeholder[Long](57)))\n ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "b7a6020e0fdcfdc2fe1d7b49ac656441e44bae5bf89d9bdc56418f1145dd5d75",
"index": 0,
"amount": 1,
"name": "Logic NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1a012046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1]"
},
"R6": {
"serializedValue": "1101f015",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1400]"
},
"R8": {
"serializedValue": "1a00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[]"
},
"R7": {
"serializedValue": "1100",
"sigmaType": "Coll[SLong]",
"renderedValue": "[]"
},
"R9": {
"serializedValue": "10020404",
"sigmaType": "Coll[SInt]",
"renderedValue": "[2,2]"
},
"R4": {
"serializedValue": "110a80a0b787e905a6c1ed0bb6163c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,12431443,1435,30,15000000,8,0,50,15,20000000]"
}
}
}
],
"dataInputs": [
{
"boxId": "7efe87b885fa3bec1ee78e7c6f6a3ec3f16cdc00847ab8c0beb7eea0a2f1cdf4",
"value": 1000000,
"index": 0,
"outputBlockId": "9e0e43b81ce361c7b32be4d3800862d2554def5ec0bcbff3acfd63f5ec8ebb8f",
"outputTransactionId": "066c27a47f66a438c502067285dbb29911ceef4600b3a58a7ccd93389234bb0e",
"outputIndex": 0,
"ergoTree": "10140400058084af5f04020400058080d4aff9dcfc1f040405808088fccdbcc3230406048092f40104000402040404060408040a04f00104000e2057c8fe647105822b59b93ab9b3d00fa0d68b10e8f3f24ddba6b9c45ba3469dda04000e20b5f5970d9327ff47bf72f6f351b0487cf2b2273573c491d971ef1e315c4d3a10d80ad601e4c6a70405d602b2a5730000d603e4c6a70506d6047301d605db6501fed606b27205730200d607e4c672060411d608db6308b27205730300d6099d9c7e9973048cb27208730500020672037e730606d60a9d9c7e72040672099a7e8cb2720873070002067209d1edededededededed927ea305720193c2a7c2720292c1720299c1a77e73080593db63087202db6308a793e4c6720205069d9c72039a7e7204069a9a9a9a9a7eb27207730900069d9c7eb27207730a0006720a7e7204069d9c9d9c7eb27207730b0006720a7e720406720a7e7204069d9c9d9c9d9c7eb27207730c0006720a7e720406720a7e720406720a7e7204069d9c9d9c9d9c9d9c7eb27207730d0006720a7e720406720a7e720406720a7e720406720a7e7204069d9c9d9c9d9c9d9c9d9c7eb27207730e0006720a7e720406720a7e720406720a7e720406720a7e720406720a7e7204067e72040693e4c6720204059a72017e730f05938cb27208731000017311938cb2db63087206731200017313ededede4c672020601e4c672020701e4c672020801e4c672020901",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "05e692d001",
"sigmaType": "SLong",
"renderedValue": "1705139"
},
"R5": {
"serializedValue": "06072386f26fc10000",
"sigmaType": "SBigInt",
"renderedValue": "CBigInt(10000000000000000)"
}
}
},
{
"boxId": "70e7023d5a7e52c9e617fc714180d7f21603b5671e79dec8e2eb39679ec679e6",
"value": 18212416862359,
"index": 1,
"outputBlockId": "a22193c71f3b82bc5bf01cd67e1c430ffbaab904142b3c71a28e623b1d43fa45",
"outputTransactionId": "12ef44d01c154a01d8930a26c603ac2987d33556f04e78a7b391631405fe10e9",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04ca0f",
"sigmaType": "SInt",
"renderedValue": "997"
}
}
}
],
"outputs": [
{
"boxId": "a21851b57cf124b2aa3f1b29098bcee07338494eeed129a208f47ad9470a7fb6",
"transactionId": "dd357de6516b59df80fc0885a2f35ee82dd6b352c9fb573bca9129b4e0f9f140",
"blockId": "5ad70b5198bd51ed6158725a77c76d5e525722ec5053a11d90887e53a104659f",
"value": 400000000,
"index": 0,
"globalIndex": 53118235,
"creationHeight": 1705166,
"settlementHeight": 1705170,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(103,-25,7,-66,31,0,-59,-89,-40,-67,-12,-20,-83,-87,-32,-112,105,-42,6,-89,-40,-32,89,17,66,-56,-69,24,-100,-103,49,85)\n3: 3\n4: 0\n5: 0\n6: 0\n7: CBigInt(10000000000000000)\n8: 0\n9: 0\n10: Coll(-78,-19,-13,108,95,63,23,72,-81,59,100,-30,-20,-118,47,-20,-107,102,43,17,-42,100,-47,-100,-42,8,98,-28,-55,58,111,100)\n11: 0\n12: 1\n13: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n14: 0\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 2\n35: 0\n36: 0\n37: 0\n38: 1\n39: 0\n40: 1\n41: 10000000\n42: 1\n43: 1000000\n44: 1000\n45: 1000\n46: 0\n47: 0\n48: 0\n49: 0\n50: 1000000\n51: 10000000\n52: 5\n53: 1000000\n54: 10000000\n55: 100000000\n56: 100000000\n57: 100000000\n58: 0\n59: 1\n60: 3\n61: 2\n62: 3\n63: 5\n64: 6\n65: 7\n66: 1000\n67: 1\n68: 1\n69: 980000\n70: 1000000\n71: CBigInt(1)\n72: 0\n73: 0\n74: 0\n75: 0\n76: -1\n77: 1\n78: 1\n79: 2000000\n80: 0\n81: 0\n82: 0\n83: true\n84: 0\n85: 1000000",
"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Byte]].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n })\n val coll3 = SELF.propositionBytes\n val coll4 = placeholder[Coll[Byte]](2)\n val coll5 = SELF.R9[Coll[Long]].get\n val l6 = coll5(placeholder[Int](3))\n val coll7 = SELF.tokens\n val tuple8 = coll7(placeholder[Int](4))\n val coll9 = tuple8._1\n val coll10 = SELF.R4[Coll[Byte]].get\n val ge11 = SELF.R5[GroupElement].get\n val l12 = SELF.R6[Long].get\n val coll13 = SELF.R8[Coll[Byte]].get\n val l14 = SELF.value\n val func15 = {(box15: Box) =>\n val coll17 = box15.propositionBytes\n val bool18 = coll17 == coll3\n bool18\n }\n val coll16 = OUTPUTS.filter(func15)\n val box17 = coll16.getOrElse(placeholder[Int](5), SELF)\n val coll18 = box17.tokens\n val tuple19 = coll18(placeholder[Int](6))\n val l20 = tuple19._2\n val bi21 = placeholder[BigInt](7)\n val bi22 = CONTEXT.dataInputs.filter({(box22: Box) =>\n val coll24 = box22.tokens\n (coll24.size > placeholder[Int](8)) && (coll24(placeholder[Int](9))._1 == placeholder[Coll[Byte]](10))\n })(placeholder[Int](11)).R5[BigInt].get\n val l23 = tuple8._2\n val bi24 = l23.toBigInt\n val coll25 = coll7.slice(placeholder[Int](12), coll7.size)\n val coll26 = placeholder[Coll[Byte]](13)\n val func27 = {(box27: Box) =>\n val coll29 = box27.propositionBytes\n val coll30 = blake2b256(coll29)\n val bool31 = coll30 == coll4\n bool31\n }\n val coll28 = OUTPUTS.filter(func27)\n val box29 = coll28.getOrElse(placeholder[Int](14), SELF)\n val coll30 = box29.tokens\n val tuple31 = coll30(placeholder[Int](15))\n val l32 = coll5(placeholder[Int](16))\n val i33 = INPUTS.filter({(box33: Box) => box33.propositionBytes == coll3 }).size\n val bool34 = i33 == placeholder[Int](17)\n val l35 = HEIGHT.toLong\n val l36 = coll5(placeholder[Int](18))\n val l37 = coll5(placeholder[Int](19))\n val l38 = l36 + l37\n val l39 = coll5(placeholder[Int](20))\n val coll40 = coll13.slice(placeholder[Int](21), placeholder[Int](22))\n val coll41 = coll13.slice(placeholder[Int](23), placeholder[Int](24))\n val l42 = coll5(placeholder[Int](25))\n val bi43 = bi24 * bi22 / bi21\n val bi44 = if (l35 < l38) {(\n val i44 = placeholder[Int](26)\n bi43 * l42.toBigInt + i44.toBigInt / i44.toBigInt\n )} else { bi43 }\n val box45 = coll28.getOrElse(placeholder[Int](27), SELF)\n val coll46 = box45.tokens\n val tuple47 = coll46(placeholder[Int](28))\n val func48 = {(box48: Box) =>\n val coll50 = box48.propositionBytes\n val coll51 = blake2b256(coll50)\n val bool52 = coll51 == coll4\n bool52\n }\n val coll49 = OUTPUTS.filter(func48)\n val box50 = coll49.getOrElse(placeholder[Int](29), SELF)\n val coll51 = box50.tokens\n val tuple52 = coll51(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func53 = func15\n val coll54 = coll16\n val i55 = coll54.size\n val func56 = func27\n val coll57 = coll28\n val box58 = coll2.getOrElse(placeholder[Int](32), SELF)\n val coll59 = box58.R4[Coll[Long]].get\n val l60 = coll59(placeholder[Int](33))\n val l61 = coll59(placeholder[Int](34))\n if (i55 > placeholder[Int](35)) {(\n val box62 = box17\n val bool63 = OUTPUTS.map({(box63: Box) => box63.id }).indexOf(box62.id, placeholder[Int](36)) == box58.R9[Coll[Int]].get(\n placeholder[Int](37)\n ) - placeholder[Int](38)\n val l64 = box62.value\n val coll65 = coll18\n val tuple66 = tuple19\n val coll67 = box62.R4[Coll[Byte]].get\n val ge68 = box62.R5[GroupElement].get\n val coll69 = box62.R7[Coll[Byte]].get\n val bool70 = ((((l64 >= l6) && (tuple66._1 == coll9)) && (coll67 == coll10)) && (ge68 == ge11)) && (coll69 == coll1)\n val coll71 = box62.R8[Coll[Byte]].get\n val l72 = box62.R6[Long].get\n val coll73 = box62.R9[Coll[Long]].get\n val bool74 = coll73 == coll5\n if (coll57.size > placeholder[Int](39)) {(\n val bi75 = l20.toBigInt\n val box76 = box29\n val coll77 = coll30\n val tuple78 = coll77(placeholder[Int](40))\n val tuple79 = tuple31\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (l64 >= l14)) && (l64 <= l14 + placeholder[Long](41))) && (\n bi75 >= bi24 - tuple78._2.toBigInt * bi21 / bi22\n )\n ) && (coll65.slice(placeholder[Int](42), coll65.size) == coll25)\n ) && (l72 == l12)\n ) && bool74\n ) && (((box76.value >= placeholder[Long](43)) && (tuple79._1 == coll9)) && (tuple78._1 == coll26))\n ) && (tuple79._2 == l23 - l20)\n ) && (l60.toBigInt >= bi75 * bi22 / bi21 * l32.toBigInt / placeholder[Int](44).toBigInt)\n ) && bool34\n ) && (l35 >= l38)\n )\n )} else {(\n val bi75 = l60.toBigInt\n val i76 = placeholder[Int](45)\n val bi77 = l20.toBigInt * bi22 / bi21 * l32.toBigInt / i76.toBigInt\n val bool78 = bi75 >= bi77\n val prop79 = sigmaProp(INPUTS.filter({(box79: Box) =>\n val coll81 = box79.tokens\n ((coll81.size > placeholder[Int](46)) && (coll81(placeholder[Int](47))._1 == coll40)) && (box79.R9[Coll[Coll[Byte]]].get(INPUTS.indexOf(SELF, placeholder[Int](48))) == coll41)\n }).size > placeholder[Int](49)) || proveDlog(ge11)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (l64 >= l14 - placeholder[Long](50))) && (l64 <= l14 + placeholder[Long](51))) && (\n coll65 == coll7\n )\n ) && (l72 > l35 + l39)\n ) && (l72 < l35 + l39 + placeholder[Long](52))\n ) && (bi75 < bi77)\n ) && bool74\n ) && bool34\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (l64 >= l14 - placeholder[Long](53))) && (l64 <= l14 + placeholder[Long](54))) && (\n coll65 == coll7\n )\n ) && (l12 != placeholder[Long](55))\n ) && (l72 == placeholder[Long](56))\n ) && bool78\n ) && bool74\n ) && bool34\n ) || prop79 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool70 && bool63) && (coll13 == coll71)) && (bi75 >= bi44 * l61.toBigInt / i76.toBigInt)) && (tuple66 == tuple8)) && (\n l72 == placeholder[Long](57)\n )\n ) && bool78\n ) && ((coll73(placeholder[Int](58)) == l61) && (coll73(placeholder[Int](59)) == coll59(placeholder[Int](60))))\n ) && (i33 == i55)\n ) && (coll73(placeholder[Int](61)) == l39)\n ) && (coll73(placeholder[Int](62)) == l6)\n ) && (coll73(placeholder[Int](63)) == l36)\n ) && (coll73(placeholder[Int](64)) == l42)\n ) && (coll73(placeholder[Int](65)) == l37)\n ) || prop79 && sigmaProp(\n ((((((bool70 && (l64 == l14)) && (coll65 == coll7)) && (coll67 == coll10)) && (ge68 == ge11)) && (coll69 == coll1)) && bool74) && (i33 == i55)\n )\n )}\n )} else {(\n val bi62 = l60.toBigInt\n val i63 = placeholder[Int](66)\n val box64 = box45\n val coll65 = coll46\n val tuple66 = tuple47\n val tuple67 = coll65(placeholder[Int](67))\n val coll68 = SELF.id\n val bi69 = bi62 - bi44\n val bi70 = coll5(placeholder[Int](68)).toBigInt\n val bi71 = bi69 * i63.toBigInt - bi70 / i63.toBigInt\n val l72 = tuple67._2\n sigmaProp(\n (\n (\n (\n (\n (((bi62 <= bi44 * l32.toBigInt / i63.toBigInt) && (l35 >= l12)) || (l35 > SELF.creationInfo._1.toLong + placeholder[Long](69))) && (\n (((box64.value >= placeholder[Long](70)) && (tuple66._1 == coll9)) && (tuple67._1 == coll26)) && (box64.id != coll68)\n )\n ) && (tuple66._2 == l23)\n ) && if (bi71 < placeholder[BigInt](71)) { l72.toBigInt >= bi62 } else {(\n val box73 = OUTPUTS.filter({(box73: Box) => box73.propositionBytes == coll10 }).getOrElse(placeholder[Int](72), SELF)\n val tuple74 = box73.tokens(placeholder[Int](73))\n (((l72.toBigInt >= bi44 + bi69 * bi70 / i63.toBigInt) && (tuple74._2.toBigInt >= bi71)) && (tuple74._1 == coll26)) && (box73.id != coll68)\n )}\n ) && (\n INPUTS.map({(box73: Box) => box73.id }).indexOf(coll68, placeholder[Int](74)) == box58.R9[Coll[Int]].get(placeholder[Int](75)) * placeholder[Int](\n 76\n ) - placeholder[Int](77)\n )\n ) && bool34\n )\n )}\n )} else {(\n val func53 = func48\n val coll54 = coll49\n val box55 = box50\n val coll56 = coll51\n val tuple57 = tuple52\n val tuple58 = coll56(placeholder[Int](78))\n sigmaProp(\n (\n (\n (((((box55.value >= placeholder[Long](79)) && (tuple57._1 == coll9)) && (tuple58._1 == coll26)) && (box55.id != SELF.id)) && (tuple57._2 == l23)) && (\n tuple58._2.toBigInt > bi44\n )\n ) && if (INPUTS.filter({(box59: Box) =>\n val coll61 = box59.tokens\n ((coll61.size > placeholder[Int](80)) && (coll61(placeholder[Int](81))._1 == coll40)) && (box59.R9[Coll[Byte]].get == coll41)\n }).size > placeholder[Int](82)) { placeholder[Boolean](83) } else {(\n val box59 = OUTPUTS.filter({(box59: Box) => box59.propositionBytes == coll10 }).getOrElse(placeholder[Int](84), SELF)\n ((box59.value >= l14 - placeholder[Long](85)) && (box59.tokens == coll25)) && (box59.id != SELF.id)\n )}\n ) && bool34\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "623668c9bb119b8e7c7edffee09211bd6d7ff48499c7e1834e33c3fe9c36a025",
"index": 0,
"amount": 4000000,
"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
},
"R6": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R8": {
"serializedValue": "0e0100",
"sigmaType": "Coll[SByte]",
"renderedValue": "00"
},
"R7": {
"serializedValue": "0e20b7a6020e0fdcfdc2fe1d7b49ac656441e44bae5bf89d9bdc56418f1145dd5d75",
"sigmaType": "Coll[SByte]",
"renderedValue": "b7a6020e0fdcfdc2fe1d7b49ac656441e44bae5bf89d9bdc56418f1145dd5d75"
},
"R9": {
"serializedValue": "110892163c108087a70e008c93d001641e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1417,30,8,15000000,0,1705158,50,15]"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "616069c1ecac4db1ab30fa121c0e1bd3eba968585a6a7e4adebecbe3aaa648b4",
"transactionId": "dd357de6516b59df80fc0885a2f35ee82dd6b352c9fb573bca9129b4e0f9f140",
"blockId": "5ad70b5198bd51ed6158725a77c76d5e525722ec5053a11d90887e53a104659f",
"value": 495000000,
"index": 1,
"globalIndex": 53118236,
"creationHeight": 1705166,
"settlementHeight": 1705170,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [
{
"tokenId": "5864e8fd882300f56771e12f2ab5612c6d29e068dff4c5ac2074878ec3b4f172",
"index": 0,
"amount": 11999999,
"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "bca67c4a8c877b4678259455cfc2389da8abd69530e7cc798a5ab53be033798e",
"mainChain": true
},
{
"boxId": "1f1665707b947d3075d08128db66df5896614fad1150a00651bfbc72fd997809",
"transactionId": "dd357de6516b59df80fc0885a2f35ee82dd6b352c9fb573bca9129b4e0f9f140",
"blockId": "5ad70b5198bd51ed6158725a77c76d5e525722ec5053a11d90887e53a104659f",
"value": 1000000,
"index": 2,
"globalIndex": 53118237,
"creationHeight": 1705166,
"settlementHeight": 1705170,
"ergoTree": "103f0400040004000400040004080408040a040a040c040c04100410040e040e0402040004000402040104020402060100060102060164060203e8050004040480ade2040580c0a8ca9a3a0402050008cd03dda8fe44b65ff96eb9dd442e6f10aca93f7351e96f2cbb1862c21a9055bc8b9604040402040605d00f0500053c0400050004040402040405d20f04020400040405000402040005000580a4e8030502050005d00f0500050004120412050004000400d82cd601c2a7d602b2b5a5d9010263d801d604db63087202ed91b17204730093b27204730100b2db6308a7730200730300d603c27202d604e4c672020411d605b27204730400d606e4c6a70411d607b27206730500d608b27204730600d609b27206730700d60ab27204730800d60bb27206730900d60cb27204730a00d60db27206730b00d60eb27204730c00d60fb27206730d00d610b27204730e00d611e4c6a7051ad612e4c67202051ad613e4c6a70611d614e4c672020611d615db6501fed616e4c672020910d617b27216730f00d618b27215721700d619db63087218d61ab27216731000d61b9591721a7311b2a599721a731200b2a4999c721a7313731400d61c7ec1721b06d61db472159a72177315b17215d61ee4c672020711d61f7316d6207317d6217318d6227319d623999a721cb0dc0c1d721d01721e721fd90123424d63d804d6258c722302d6268c722502d6278c722501d6288c72230195917226731ad803d6297e722606d62a7ee4c67227040406d62b7e8cb2db63087227731b0002069a72289d9c9c7ec17227067229722a9a9c9a722b9d9c722b7220722172229c7229722a72287e731c06d6247ee4c67218040406d6257ec1721806d626731dd627db6308721bd628b17227d629e4c67202081ad62ab47212731eb17212d62bb1721dd62cb1721eeb02ea02d1edededededededededed937201720393c1a7c1720293db6308a7db63087202937205731f9372077208937209720a93720b720c93720d720e93720f7210937211721293721372147320d1ededededededededededededededededed9372037201ed93721272119372147213939d9c9c7e8cb272197321000206722372249a9c9a72259d9c72257220722172229c722372247eb272047322000693a2a1b27204732300732473257326939d9a9d9c9c721c7e7226067eb27214732700067223b0db0c0e721e721fd9012d4204d803d62f8c722d02d630b2721e722f00d6318c722d01959172307328d804d632b2721d722f00d6337e723006d6347ee4c67232040406d6357e8cb2db6308723273290002069a72319d9c9c9d9c9c7ec1723206723372349a9c9a72359d9c72357220722172229c723372347e7226067eb2b47214732ab17214722f0006722372317e7226067ea2b27204732b00732c06afb47227732d7228d9012d4d0eaedc0c1d722901721ed9012f4d0e93722f722dafdb0c0e722ad9012d04d801d62fdb6308b2721d722d00ed93b2722a722d008cb2722f732e000193b27229722d008cb2722f732f0001ed93722b722c93722bb1722a93722cb1722993b1b5721ed9012d0593722d733099722c997228733193b27206733200a272057333937207a272087334937209a2720a733593720ba2720c733693720fa2a172107337733893720da2720e733993b27206733a00a2b27204733b00733c938cb27219733d0001b27212733e00",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val box2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n })(placeholder[Int](3))\n val coll3 = box2.propositionBytes\n val coll4 = box2.R4[Coll[Long]].get\n val l5 = coll4(placeholder[Int](4))\n val coll6 = SELF.R4[Coll[Long]].get\n val l7 = coll6(placeholder[Int](5))\n val l8 = coll4(placeholder[Int](6))\n val l9 = coll6(placeholder[Int](7))\n val l10 = coll4(placeholder[Int](8))\n val l11 = coll6(placeholder[Int](9))\n val l12 = coll4(placeholder[Int](10))\n val l13 = coll6(placeholder[Int](11))\n val l14 = coll4(placeholder[Int](12))\n val l15 = coll6(placeholder[Int](13))\n val l16 = coll4(placeholder[Int](14))\n val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n val coll18 = box2.R5[Coll[Coll[Byte]]].get\n val coll19 = SELF.R6[Coll[Long]].get\n val coll20 = box2.R6[Coll[Long]].get\n val coll21 = CONTEXT.dataInputs\n val coll22 = box2.R9[Coll[Int]].get\n val i23 = coll22(placeholder[Int](15))\n val box24 = coll21(i23)\n val coll25 = box24.tokens\n val i26 = coll22(placeholder[Int](16))\n val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n val bi28 = box27.value.toBigInt\n val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n val coll30 = box2.R7[Coll[Long]].get\n val bi31 = placeholder[BigInt](22)\n val bi32 = placeholder[BigInt](23)\n val bi33 = placeholder[BigInt](24)\n val bi34 = placeholder[BigInt](25)\n val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n val tuple37 = tuple35._2\n val l38 = tuple37._2\n val box39 = tuple37._1\n val bi40 = tuple35._1\n if (l38 > placeholder[Long](26)) {(\n val bi41 = l38.toBigInt\n val bi42 = box39.R4[Int].get.toBigInt\n val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n )} else { bi40 }\n }) - placeholder[Int](28).toBigInt\n val bi36 = box24.R4[Int].get.toBigInt\n val bi37 = box24.value.toBigInt\n val l38 = placeholder[Long](29)\n val coll39 = box27.tokens\n val i40 = coll39.size\n val coll41 = box2.R8[Coll[Coll[Byte]]].get\n val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n val i43 = coll29.size\n val i44 = coll30.size\n sigmaProp(\n (\n (\n (\n (\n (\n (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n l9 == l10\n )\n ) && (l11 == l12)\n ) && (l13 == l14)\n ) && (l15 == l16)\n ) && (coll17 == coll18)\n ) && (coll19 == coll20)\n ) && placeholder[SigmaProp](32) || sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n placeholder[Int](34)\n ).toBigInt\n )\n ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n val i47 = tuple45._2\n val l48 = coll30(i47)\n val bi49 = tuple45._1\n if (l48 > placeholder[Long](40)) {(\n val box50 = coll29(i47)\n val bi51 = l48.toBigInt\n val bi52 = box50.R4[Int].get.toBigInt\n val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n )} else { bi49 }\n }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n ) && coll39.slice(placeholder[Int](45), i40).forall(\n {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n )\n ) && coll42.indices.forall({(i45: Int) =>\n val coll47 = coll29(i45).tokens\n (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n })\n ) && ((i43 == i44) && (i43 == coll42.size))\n ) && (i44 == coll41.size)\n ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n ) && (l7 == max(l8, placeholder[Long](52)))\n ) && (l9 == max(l10, placeholder[Long](53)))\n ) && (l11 == max(l12, placeholder[Long](54)))\n ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n ) && (l13 == max(l14, placeholder[Long](57)))\n ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "b7a6020e0fdcfdc2fe1d7b49ac656441e44bae5bf89d9bdc56418f1145dd5d75",
"index": 0,
"amount": 1,
"name": "Logic NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1a012046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1]"
},
"R6": {
"serializedValue": "1101f015",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1400]"
},
"R8": {
"serializedValue": "1a00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[]"
},
"R7": {
"serializedValue": "1100",
"sigmaType": "Coll[SLong]",
"renderedValue": "[]"
},
"R9": {
"serializedValue": "10020202",
"sigmaType": "Coll[SInt]",
"renderedValue": "[1,1]"
},
"R4": {
"serializedValue": "110a80a0b787e905bea9d31792163c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,24799839,1417,30,15000000,8,0,50,15,20000000]"
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "94009868a9902fe8df2f50ebdd15ee58ed7fcfc7cf791b1fa4bd4b522051c332",
"transactionId": "dd357de6516b59df80fc0885a2f35ee82dd6b352c9fb573bca9129b4e0f9f140",
"blockId": "5ad70b5198bd51ed6158725a77c76d5e525722ec5053a11d90887e53a104659f",
"value": 2000000,
"index": 3,
"globalIndex": 53118238,
"creationHeight": 1705166,
"settlementHeight": 1705170,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "2a00b0fd08ffb5dc9a190abe9cfe90b8026870a0fbd315437317a250feb6264f",
"mainChain": true
}
],
"size": 4184,
"isUnconfirmed": false
}