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Transaction

4/7/2026 07:20:01 AM
ID: 6828e96b0f...201f
Inputs (3)
#0
577dee8aa66f...856e
Spent
Address:
P5a4t5sSNrmz...i82H
Output transaction:
0097df6497c6...5853
Settlement height:
1,757,945
Value:
0.07 ERG
Tokens:
Borrow Token QUACKS - Beta-2.0
0
#1
bbf25ecfe355...286e
Spent
Address:
2GHGXUgJzMYF...z4aL
Output transaction:
0097df6497c6...5853
Settlement height:
1,757,945
Value:
0.001 ERG
Tokens:
Loading assets...
#2
f7583711dd2f...9d76
Spent
Address:
9gSsDJixycev...7zSy
Output transaction:
2341ff55fafa...c5a9
Settlement height:
1,757,885
Value:
100.8 ERG
Tokens:
Loading assets...
Outputs (5)
#0
490473a27939...e374
Spent
Address:
P5a4t5sSNrmz...i82H
Spent in transaction:
4794ca3fda59...63ac
Settlement height:
1,758,719
Value:
0.064 ERG
Tokens:
Borrow Token QUACKS - Beta-2.0
0
#1
74b2c7fa33d1...d5c6
Spent
Address:
2GHGXUgJzMYF...z4aL
Spent in transaction:
4794ca3fda59...63ac
Settlement height:
1,758,719
Value:
0.001 ERG
Tokens:
Loading assets...
#2
cd18e1fe2b75...c687
Spent
Address:
9gSsDJixycev...7zSy
Spent in transaction:
f5e1606d93e5...265d
Settlement height:
1,758,719
Value:
100.8 ERG
Tokens:
Loading assets...
#3
b9cda504861f...5555
Spent
Address:
9gSsDJixycev...7zSy
Spent in transaction:
40f070b09b91...9c5f
Settlement height:
1,758,719
Value:
0.007 ERG
#4
49a86b62eb55...df18
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
1c392d40c0a7...f2d6
Settlement height:
1,758,719
Value:
0.002 ERG
Transaction Details
Status: Confirmed
Size: 7.82 KB
Received time: 4/7/2026 07:20:01 AM
Included in blocks: 1,758,719
Confirmations: 16,729
Total coins transferred: 100.87 ERG
Fees: 0.002 ERG
Fees per byte: 0.00000025 ERG
Raw Transaction Data
{
  "id": "6828e96b0f5a48ac059d5b444fda68c72c2c29e71e2408764877f5dfe3a4201f",
  "blockId": "0298f1ad7cdc91f99907f028570b4da77bd3a65a1b7a7ddb2d3f684b4f9b27f6",
  "inclusionHeight": 1758719,
  "timestamp": 1775546401492,
  "index": 4,
  "globalIndex": 10561380,
  "numConfirmations": 16729,
  "inputs": [
    {
      "boxId": "577dee8aa66f7a10b9c26d4e5a82fd651365e94793f5578aa29764f1f51f856e",
      "value": 70000000,
      "index": 0,
      "spendingProof": "51ced318a5818a8f9c88884874c797ab93cb0d6bf27a36e38c5623f72e813c27e2d1d71f58843ef215deb52fd68b02b940e10c0b3543d62e",
      "outputBlockId": "ffcc5a1b0521dc1ac7387c3871be873442acd2994a8050281820768022c63e70",
      "outputTransactionId": "0097df6497c68b6a2da29018d84926b0badfb5468626945838288c62445d5853",
      "outputIndex": 0,
      "outputGlobalIndex": 54561863,
      "outputCreatedAt": 1757944,
      "outputSettledAt": 1757945,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-80,-96,89,91,-62,-43,-103,63,48,29,93,-40,94,-114,23,64,61,77,-10,52,-73,-77,30,91,62,68,6,103,36,-21,86,109)\n3: 0\n4: 3\n5: 0\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(53,10,46,3,-60,3,80,-117,18,-119,93,-84,-8,51,-32,56,-96,-42,-109,18,-124,-123,82,47,-72,-124,-54,-21,35,-43,-103,13)\n12: 0\n13: 1\n14: 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)\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: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 8\n40: 0\n41: 8\n42: 0\n43: 1\n44: 10000000\n45: 1\n46: 1000000\n47: 1000\n48: 1000\n49: 0\n50: 0\n51: 0\n52: 1000000\n53: 10000000\n54: 5\n55: 1000000\n56: 10000000\n57: 100000000\n58: 100000000\n59: 100000000\n60: 0\n61: 1\n62: 3\n63: 2\n64: 3\n65: 5\n66: 6\n67: 7\n68: 1000\n69: 1\n70: 1\n71: 980000\n72: 1000000\n73: CBigInt(1)\n74: 0\n75: 0\n76: 0\n77: 0\n78: -1\n79: 1\n80: 1\n81: 2000000\n82: 0\n83: 0\n84: 0\n85: true\n86: 0\n87: 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 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n  val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n  val coll7 = SELF.R9[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](4))\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](5))\n  val coll11 = tuple10._1\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val ge13 = SELF.R5[GroupElement].get\n  val l14 = SELF.R6[Long].get\n  val coll15 = SELF.R8[Coll[Byte]].get\n  val l16 = SELF.value\n  val func17 = {(box17: Box) =>\n    val coll19 = box17.propositionBytes\n    val bool20 = coll19 == coll3\n    bool20\n  }\n  val coll18 = OUTPUTS.filter(func17)\n  val box19 = coll18.getOrElse(i6, SELF)\n  val coll20 = box19.tokens\n  val tuple21 = coll20(placeholder[Int](6))\n  val l22 = tuple21._2\n  val i23 = INPUTS.indexOf(SELF, placeholder[Int](7))\n  val bi24 = placeholder[BigInt](8)\n  val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n      val coll27 = box25.tokens\n      (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n    })(placeholder[Int](12)).R5[BigInt].get\n  val l26 = tuple10._2\n  val bi27 = l26.toBigInt\n  val coll28 = coll9.slice(placeholder[Int](13), coll9.size)\n  val coll29 = placeholder[Coll[Byte]](14)\n  val func30 = {(box30: Box) =>\n    val coll32 = box30.propositionBytes\n    val coll33 = blake2b256(coll32)\n    val bool34 = coll33 == coll4\n    bool34\n  }\n  val coll31 = OUTPUTS.filter(func30)\n  val box32 = coll31.getOrElse(i23, SELF)\n  val coll33 = box32.tokens\n  val tuple34 = coll33(placeholder[Int](15))\n  val l35 = coll7(placeholder[Int](16))\n  val i36 = coll5.size\n  val bool37 = i36 == placeholder[Int](17)\n  val l38 = HEIGHT.toLong\n  val l39 = coll7(placeholder[Int](18))\n  val l40 = coll7(placeholder[Int](19))\n  val l41 = l39 + l40\n  val l42 = coll7(placeholder[Int](20))\n  val coll43 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n  val coll44 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n  val l45 = coll7(placeholder[Int](25))\n  val bi46 = bi27 * bi25 / bi24\n  val bi47 = if (l38 < l41) {(\n    val i47 = placeholder[Int](26)\n    bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n  )} else { bi46 }\n  val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n  val coll49 = box48.tokens\n  val tuple50 = coll49(placeholder[Int](28))\n  val func51 = {(box51: Box) =>\n    val coll53 = box51.propositionBytes\n    val coll54 = blake2b256(coll53)\n    val bool55 = coll54 == coll4\n    bool55\n  }\n  val coll52 = OUTPUTS.filter(func51)\n  val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n  val coll54 = box53.tokens\n  val tuple55 = coll54(placeholder[Int](30))\n  if (coll2.size > placeholder[Int](31)) {(\n    val func56 = func17\n    val coll57 = coll18\n    val i58 = coll57.size\n    val func59 = func30\n    val coll60 = coll31\n    val box61 = coll2.getOrElse(i6, SELF)\n    val coll62 = box61.R4[Coll[Long]].get\n    val l63 = coll62(placeholder[Int](32))\n    val l64 = coll62(placeholder[Int](33))\n    if (i58 > placeholder[Int](34)) {(\n      val box65 = box19\n      val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n        placeholder[Int](36)\n      ) - placeholder[Int](37)\n      val l67 = box65.value\n      val coll68 = coll20\n      val tuple69 = tuple21\n      val coll70 = box65.R4[Coll[Byte]].get\n      val ge71 = box65.R5[GroupElement].get\n      val coll72 = box65.R7[Coll[Byte]].get\n      val bool73 = ((((l67 >= l8) && (tuple69._1 == coll11)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)\n      val coll74 = box65.R8[Coll[Byte]].get\n      val l75 = box65.R6[Long].get\n      val coll76 = box65.R9[Coll[Long]].get\n      val bool77 = coll76.slice(placeholder[Int](38), placeholder[Int](39)) == coll7.slice(placeholder[Int](40), placeholder[Int](41))\n      if (coll60.size > placeholder[Int](42)) {(\n        val bi78 = l22.toBigInt\n        val box79 = box32\n        val coll80 = coll33\n        val tuple81 = coll80(placeholder[Int](43))\n        val tuple82 = tuple34\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16)) && (l67 <= l16 + placeholder[Long](44))) && (\n                            bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n                          )\n                        ) && (coll68.slice(placeholder[Int](45), coll68.size) == coll28)\n                      ) && (l75 == l14)\n                    ) && bool77\n                  ) && (((box79.value >= placeholder[Long](46)) && (tuple82._1 == coll11)) && (tuple81._1 == coll29))\n                ) && (tuple82._2 == l26 - l22)\n              ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](47).toBigInt)\n            ) && bool37\n          ) && (l38 >= l41)\n        )\n      )} else {(\n        val bi78 = l63.toBigInt\n        val i79 = placeholder[Int](48)\n        val bi80 = l22.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n        val bool81 = bi78 >= bi80\n        val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n              val coll84 = box82.tokens\n              ((coll84.size > placeholder[Int](49)) && (coll84(placeholder[Int](50))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n            }).size > placeholder[Int](51)) || proveDlog(ge13)\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](52))) && (l67 <= l16 + placeholder[Long](53))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l75 > l38 + l42)\n                ) && (l75 < l38 + l42 + placeholder[Long](54))\n              ) && (bi78 < bi80)\n            ) && bool77\n          ) && bool37\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](55))) && (l67 <= l16 + placeholder[Long](56))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l14 != placeholder[Long](57))\n                ) && (l75 == placeholder[Long](58))\n              ) && bool81\n            ) && bool77\n          ) && bool37\n        ) || prop82 && sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple10)) && (\n                            l75 == placeholder[Long](59)\n                          )\n                        ) && bool81\n                      ) && ((coll76(placeholder[Int](60)) == l64) && (coll76(placeholder[Int](61)) == coll62(placeholder[Int](62))))\n                    ) && (i36 == i58)\n                  ) && (coll76(placeholder[Int](63)) == l42)\n                ) && (coll76(placeholder[Int](64)) == l8)\n              ) && (coll76(placeholder[Int](65)) == l39)\n            ) && (coll76(placeholder[Int](66)) == l45)\n          ) && (coll76(placeholder[Int](67)) == l40)\n        ) || prop82 && sigmaProp(\n          ((((((bool73 && (l67 == l16)) && (coll68 == coll9)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)) && (coll76 == coll7)) && (\n            i36 == i58\n          )\n        )\n      )}\n    )} else {(\n      val bi65 = l63.toBigInt\n      val i66 = placeholder[Int](68)\n      val box67 = box48\n      val coll68 = coll49\n      val tuple69 = tuple50\n      val tuple70 = coll68(placeholder[Int](69))\n      val coll71 = SELF.id\n      val bi72 = bi65 - bi47\n      val bi73 = coll7(placeholder[Int](70)).toBigInt\n      val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n      val l75 = tuple70._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l14)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](71))) && (\n                  (((box67.value >= placeholder[Long](72)) && (tuple69._1 == coll11)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n                )\n              ) && (tuple69._2 == l26)\n            ) && if (bi74 < placeholder[BigInt](73)) { l75.toBigInt >= bi65 } else {(\n              val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll12 }).getOrElse(placeholder[Int](74), SELF)\n              val tuple77 = box76.tokens(placeholder[Int](75))\n              (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n            )}\n          ) && (\n            INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](76)) == box61.R9[Coll[Int]].get(placeholder[Int](77)) * placeholder[Int](\n              78\n            ) - placeholder[Int](79)\n          )\n        ) && bool37\n      )\n    )}\n  )} else {(\n    val func56 = func51\n    val coll57 = coll52\n    val box58 = box53\n    val coll59 = coll54\n    val tuple60 = tuple55\n    val tuple61 = coll59(placeholder[Int](80))\n    sigmaProp(\n      (\n        (\n          (\n            ((((box58.value >= placeholder[Long](81)) && (tuple60._1 == coll11)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n          ) && (tuple61._2.toBigInt > bi47)\n        ) && if (INPUTS.filter({(box62: Box) =>\n            val coll64 = box62.tokens\n            ((coll64.size > placeholder[Int](82)) && (coll64(placeholder[Int](83))._1 == coll43)) && (box62.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n          }).size > placeholder[Int](84)) { placeholder[Boolean](85) } else {(\n          val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll12 }).getOrElse(placeholder[Int](86), SELF)\n          ((box62.value >= l16 - placeholder[Long](87)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n        )}\n      ) && bool37\n    )\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "1eaf32e2dafc2706e6d5641903eb612637af6a4d970700d452b08e2612b32b39",
          "index": 0,
          "amount": 3000000,
          "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": "0e500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000"
        },
        "R7": {
          "serializedValue": "0e2034182b1fdad3b8fc3cdc74cef055ae00dd3b0c6ccf5b9612d68bfc3ae06e928e",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "34182b1fdad3b8fc3cdc74cef055ae00dd3b0c6ccf5b9612d68bfc3ae06e928e"
        },
        "R9": {
          "serializedValue": "1108c6173c108087a70e00aacbd601641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1507,30,8,15000000,0,1757909,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      }
    },
    {
      "boxId": "bbf25ecfe35556ca6ef3c8d33c23e20ecc9f17c0261be8e0fe5442e9cc48286e",
      "value": 1000000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "ffcc5a1b0521dc1ac7387c3871be873442acd2994a8050281820768022c63e70",
      "outputTransactionId": "0097df6497c68b6a2da29018d84926b0badfb5468626945838288c62445d5853",
      "outputIndex": 1,
      "outputGlobalIndex": 54561864,
      "outputCreatedAt": 1757944,
      "outputSettledAt": 1757945,
      "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": "34182b1fdad3b8fc3cdc74cef055ae00dd3b0c6ccf5b9612d68bfc3ae06e928e",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT QUACKS - Beta-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "1a062046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1209916d75132593c8b07fe18bd8d583bda1652eed7565cf41a4738ddd90fc992ec201d5afc59838920bb5ef2a8f9d63825a55b1d48e269d7cecee335d637c3ff5f3f201b694b15467c62f0cd4525e368dbdea2329c713aa200b73df4a622e950551b4020ae97c5eccd59a065cd973a8d6afb8bb79f9cc70368a7dcdf73aaeab1cedf6f6b2047a811c68e49f6bfa6629602037ee65f8d175ddbc7b64bdb65ad40599b812fd0",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,9916d75132593c8b07fe18bd8d583bda1652eed7565cf41a4738ddd90fc992ec,1d5afc59838920bb5ef2a8f9d63825a55b1d48e269d7cecee335d637c3ff5f3f,1b694b15467c62f0cd4525e368dbdea2329c713aa200b73df4a622e950551b40,ae97c5eccd59a065cd973a8d6afb8bb79f9cc70368a7dcdf73aaeab1cedf6f6b,47a811c68e49f6bfa6629602037ee65f8d175ddbc7b64bdb65ad40599b812fd0]"
        },
        "R6": {
          "serializedValue": "1106f015c413f015f015f015a814",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1250,1400,1400,1400,1300]"
        },
        "R8": {
          "serializedValue": "1a052003faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf0420003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0208b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b20e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297207a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04,003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0,8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b,e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297,7a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0]"
        },
        "R7": {
          "serializedValue": "11050000000000",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[0,0,0,0,0]"
        },
        "R9": {
          "serializedValue": "10020202",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[1,1]"
        },
        "R4": {
          "serializedValue": "110a80a0b787e905a4aaf104c6173c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,5122706,1507,30,15000000,8,0,50,15,20000000]"
        }
      }
    },
    {
      "boxId": "f7583711dd2fda2c669c7cd243b9bed18c59ec0107404f8f08b9f7a7b92a9d76",
      "value": 100801082521,
      "index": 2,
      "spendingProof": "1be19f25a0b4721259a06eadcc4154d7ce09e3f283bcd3521545518fe8b7f570a2c9bad5214fbe1b1d724c40997aeba839f5ceff55f4a320",
      "outputBlockId": "6e53b1694145e9a31f2084c0de18cf9492604c72e43ef776be3ad199da3b9a94",
      "outputTransactionId": "2341ff55fafa8ca802153183b5e065d81b9d3c68a4700ec11d1c3c4bc750c5a9",
      "outputIndex": 1,
      "outputGlobalIndex": 54560111,
      "outputCreatedAt": 1757883,
      "outputSettledAt": 1757885,
      "ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
      "address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
      "assets": [
        {
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          "index": 0,
          "amount": 1983796,
          "name": "QUACKS",
          "decimals": 6,
          "type": "EIP-004"
        },
        {
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          "name": "CzechErgo",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "amount": 64760,
          "name": "SigRSV",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "name": "$ERG Lend token NFT - 01",
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        },
        {
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        },
        {
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          "name": "fCounter",
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          "type": "EIP-004"
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        {
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        {
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        {
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        {
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        {
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        {
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        },
        {
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        },
        {
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        },
        {
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        },
        {
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        },
        {
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        },
        {
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        {
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        },
        {
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          "amount": 33032865,
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          "type": "EIP-004"
        },
        {
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          "amount": 9999999,
          "name": "Lend Token QUACKS - Beta-2.0",
          "decimals": 2,
          "type": "EIP-004"
        },
        {
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          "name": "Lend Token QUACKS - Beta-2.0",
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          "type": "EIP-004"
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        {
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          "name": "Lend Token QUACKS - Beta-2.0",
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        },
        {
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          "amount": 9999999,
          "name": "Lend Token QUACKS - Beta-2.0",
          "decimals": 2,
          "type": "EIP-004"
        },
        {
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        "R4": {
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          "sigmaType": "SInt",
          "renderedValue": "990"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "490473a279392825668a00665afaf1db442c75245d78740ddb4d34bbaacce374",
      "transactionId": "6828e96b0f5a48ac059d5b444fda68c72c2c29e71e2408764877f5dfe3a4201f",
      "blockId": "0298f1ad7cdc91f99907f028570b4da77bd3a65a1b7a7ddb2d3f684b4f9b27f6",
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      "index": 0,
      "globalIndex": 54586826,
      "creationHeight": 1758718,
      "settlementHeight": 1758719,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-80,-96,89,91,-62,-43,-103,63,48,29,93,-40,94,-114,23,64,61,77,-10,52,-73,-77,30,91,62,68,6,103,36,-21,86,109)\n3: 0\n4: 3\n5: 0\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(53,10,46,3,-60,3,80,-117,18,-119,93,-84,-8,51,-32,56,-96,-42,-109,18,-124,-123,82,47,-72,-124,-54,-21,35,-43,-103,13)\n12: 0\n13: 1\n14: 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)\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: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 8\n40: 0\n41: 8\n42: 0\n43: 1\n44: 10000000\n45: 1\n46: 1000000\n47: 1000\n48: 1000\n49: 0\n50: 0\n51: 0\n52: 1000000\n53: 10000000\n54: 5\n55: 1000000\n56: 10000000\n57: 100000000\n58: 100000000\n59: 100000000\n60: 0\n61: 1\n62: 3\n63: 2\n64: 3\n65: 5\n66: 6\n67: 7\n68: 1000\n69: 1\n70: 1\n71: 980000\n72: 1000000\n73: CBigInt(1)\n74: 0\n75: 0\n76: 0\n77: 0\n78: -1\n79: 1\n80: 1\n81: 2000000\n82: 0\n83: 0\n84: 0\n85: true\n86: 0\n87: 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 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n  val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n  val coll7 = SELF.R9[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](4))\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](5))\n  val coll11 = tuple10._1\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val ge13 = SELF.R5[GroupElement].get\n  val l14 = SELF.R6[Long].get\n  val coll15 = SELF.R8[Coll[Byte]].get\n  val l16 = SELF.value\n  val func17 = {(box17: Box) =>\n    val coll19 = box17.propositionBytes\n    val bool20 = coll19 == coll3\n    bool20\n  }\n  val coll18 = OUTPUTS.filter(func17)\n  val box19 = coll18.getOrElse(i6, SELF)\n  val coll20 = box19.tokens\n  val tuple21 = coll20(placeholder[Int](6))\n  val l22 = tuple21._2\n  val i23 = INPUTS.indexOf(SELF, placeholder[Int](7))\n  val bi24 = placeholder[BigInt](8)\n  val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n      val coll27 = box25.tokens\n      (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n    })(placeholder[Int](12)).R5[BigInt].get\n  val l26 = tuple10._2\n  val bi27 = l26.toBigInt\n  val coll28 = coll9.slice(placeholder[Int](13), coll9.size)\n  val coll29 = placeholder[Coll[Byte]](14)\n  val func30 = {(box30: Box) =>\n    val coll32 = box30.propositionBytes\n    val coll33 = blake2b256(coll32)\n    val bool34 = coll33 == coll4\n    bool34\n  }\n  val coll31 = OUTPUTS.filter(func30)\n  val box32 = coll31.getOrElse(i23, SELF)\n  val coll33 = box32.tokens\n  val tuple34 = coll33(placeholder[Int](15))\n  val l35 = coll7(placeholder[Int](16))\n  val i36 = coll5.size\n  val bool37 = i36 == placeholder[Int](17)\n  val l38 = HEIGHT.toLong\n  val l39 = coll7(placeholder[Int](18))\n  val l40 = coll7(placeholder[Int](19))\n  val l41 = l39 + l40\n  val l42 = coll7(placeholder[Int](20))\n  val coll43 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n  val coll44 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n  val l45 = coll7(placeholder[Int](25))\n  val bi46 = bi27 * bi25 / bi24\n  val bi47 = if (l38 < l41) {(\n    val i47 = placeholder[Int](26)\n    bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n  )} else { bi46 }\n  val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n  val coll49 = box48.tokens\n  val tuple50 = coll49(placeholder[Int](28))\n  val func51 = {(box51: Box) =>\n    val coll53 = box51.propositionBytes\n    val coll54 = blake2b256(coll53)\n    val bool55 = coll54 == coll4\n    bool55\n  }\n  val coll52 = OUTPUTS.filter(func51)\n  val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n  val coll54 = box53.tokens\n  val tuple55 = coll54(placeholder[Int](30))\n  if (coll2.size > placeholder[Int](31)) {(\n    val func56 = func17\n    val coll57 = coll18\n    val i58 = coll57.size\n    val func59 = func30\n    val coll60 = coll31\n    val box61 = coll2.getOrElse(i6, SELF)\n    val coll62 = box61.R4[Coll[Long]].get\n    val l63 = coll62(placeholder[Int](32))\n    val l64 = coll62(placeholder[Int](33))\n    if (i58 > placeholder[Int](34)) {(\n      val box65 = box19\n      val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n        placeholder[Int](36)\n      ) - placeholder[Int](37)\n      val l67 = box65.value\n      val coll68 = coll20\n      val tuple69 = tuple21\n      val coll70 = box65.R4[Coll[Byte]].get\n      val ge71 = box65.R5[GroupElement].get\n      val coll72 = box65.R7[Coll[Byte]].get\n      val bool73 = ((((l67 >= l8) && (tuple69._1 == coll11)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)\n      val coll74 = box65.R8[Coll[Byte]].get\n      val l75 = box65.R6[Long].get\n      val coll76 = box65.R9[Coll[Long]].get\n      val bool77 = coll76.slice(placeholder[Int](38), placeholder[Int](39)) == coll7.slice(placeholder[Int](40), placeholder[Int](41))\n      if (coll60.size > placeholder[Int](42)) {(\n        val bi78 = l22.toBigInt\n        val box79 = box32\n        val coll80 = coll33\n        val tuple81 = coll80(placeholder[Int](43))\n        val tuple82 = tuple34\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16)) && (l67 <= l16 + placeholder[Long](44))) && (\n                            bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n                          )\n                        ) && (coll68.slice(placeholder[Int](45), coll68.size) == coll28)\n                      ) && (l75 == l14)\n                    ) && bool77\n                  ) && (((box79.value >= placeholder[Long](46)) && (tuple82._1 == coll11)) && (tuple81._1 == coll29))\n                ) && (tuple82._2 == l26 - l22)\n              ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](47).toBigInt)\n            ) && bool37\n          ) && (l38 >= l41)\n        )\n      )} else {(\n        val bi78 = l63.toBigInt\n        val i79 = placeholder[Int](48)\n        val bi80 = l22.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n        val bool81 = bi78 >= bi80\n        val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n              val coll84 = box82.tokens\n              ((coll84.size > placeholder[Int](49)) && (coll84(placeholder[Int](50))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n            }).size > placeholder[Int](51)) || proveDlog(ge13)\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](52))) && (l67 <= l16 + placeholder[Long](53))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l75 > l38 + l42)\n                ) && (l75 < l38 + l42 + placeholder[Long](54))\n              ) && (bi78 < bi80)\n            ) && bool77\n          ) && bool37\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](55))) && (l67 <= l16 + placeholder[Long](56))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l14 != placeholder[Long](57))\n                ) && (l75 == placeholder[Long](58))\n              ) && bool81\n            ) && bool77\n          ) && bool37\n        ) || prop82 && sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple10)) && (\n                            l75 == placeholder[Long](59)\n                          )\n                        ) && bool81\n                      ) && ((coll76(placeholder[Int](60)) == l64) && (coll76(placeholder[Int](61)) == coll62(placeholder[Int](62))))\n                    ) && (i36 == i58)\n                  ) && (coll76(placeholder[Int](63)) == l42)\n                ) && (coll76(placeholder[Int](64)) == l8)\n              ) && (coll76(placeholder[Int](65)) == l39)\n            ) && (coll76(placeholder[Int](66)) == l45)\n          ) && (coll76(placeholder[Int](67)) == l40)\n        ) || prop82 && sigmaProp(\n          ((((((bool73 && (l67 == l16)) && (coll68 == coll9)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)) && (coll76 == coll7)) && (\n            i36 == i58\n          )\n        )\n      )}\n    )} else {(\n      val bi65 = l63.toBigInt\n      val i66 = placeholder[Int](68)\n      val box67 = box48\n      val coll68 = coll49\n      val tuple69 = tuple50\n      val tuple70 = coll68(placeholder[Int](69))\n      val coll71 = SELF.id\n      val bi72 = bi65 - bi47\n      val bi73 = coll7(placeholder[Int](70)).toBigInt\n      val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n      val l75 = tuple70._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l14)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](71))) && (\n                  (((box67.value >= placeholder[Long](72)) && (tuple69._1 == coll11)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n                )\n              ) && (tuple69._2 == l26)\n            ) && if (bi74 < placeholder[BigInt](73)) { l75.toBigInt >= bi65 } else {(\n              val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll12 }).getOrElse(placeholder[Int](74), SELF)\n              val tuple77 = box76.tokens(placeholder[Int](75))\n              (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n            )}\n          ) && (\n            INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](76)) == box61.R9[Coll[Int]].get(placeholder[Int](77)) * placeholder[Int](\n              78\n            ) - placeholder[Int](79)\n          )\n        ) && bool37\n      )\n    )}\n  )} else {(\n    val func56 = func51\n    val coll57 = coll52\n    val box58 = box53\n    val coll59 = coll54\n    val tuple60 = tuple55\n    val tuple61 = coll59(placeholder[Int](80))\n    sigmaProp(\n      (\n        (\n          (\n            ((((box58.value >= placeholder[Long](81)) && (tuple60._1 == coll11)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n          ) && (tuple61._2.toBigInt > bi47)\n        ) && if (INPUTS.filter({(box62: Box) =>\n            val coll64 = box62.tokens\n            ((coll64.size > placeholder[Int](82)) && (coll64(placeholder[Int](83))._1 == coll43)) && (box62.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n          }).size > placeholder[Int](84)) { placeholder[Boolean](85) } else {(\n          val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll12 }).getOrElse(placeholder[Int](86), SELF)\n          ((box62.value >= l16 - placeholder[Long](87)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n        )}\n      ) && bool37\n    )\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "1eaf32e2dafc2706e6d5641903eb612637af6a4d970700d452b08e2612b32b39",
          "index": 0,
          "amount": 3000000,
          "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": "0e500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000"
        },
        "R7": {
          "serializedValue": "0e2034182b1fdad3b8fc3cdc74cef055ae00dd3b0c6ccf5b9612d68bfc3ae06e928e",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "34182b1fdad3b8fc3cdc74cef055ae00dd3b0c6ccf5b9612d68bfc3ae06e928e"
        },
        "R9": {
          "serializedValue": "1108dc173c108087a70e00aacbd601641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1518,30,8,15000000,0,1757909,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      },
      "spentTransactionId": "4794ca3fda5924b8ee70318405960899e3790dd081d9cd9f984ece55338863ac",
      "mainChain": true
    },
    {
      "boxId": "74b2c7fa33d1c3016657a72a3d7d343d9de6075e7d56987cda018483d58ad5c6",
      "transactionId": "6828e96b0f5a48ac059d5b444fda68c72c2c29e71e2408764877f5dfe3a4201f",
      "blockId": "0298f1ad7cdc91f99907f028570b4da77bd3a65a1b7a7ddb2d3f684b4f9b27f6",
      "value": 1000000,
      "index": 1,
      "globalIndex": 54586827,
      "creationHeight": 1758718,
      "settlementHeight": 1758719,
      "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": "34182b1fdad3b8fc3cdc74cef055ae00dd3b0c6ccf5b9612d68bfc3ae06e928e",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT QUACKS - Beta-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "1a062046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1209916d75132593c8b07fe18bd8d583bda1652eed7565cf41a4738ddd90fc992ec201d5afc59838920bb5ef2a8f9d63825a55b1d48e269d7cecee335d637c3ff5f3f201b694b15467c62f0cd4525e368dbdea2329c713aa200b73df4a622e950551b4020ae97c5eccd59a065cd973a8d6afb8bb79f9cc70368a7dcdf73aaeab1cedf6f6b2047a811c68e49f6bfa6629602037ee65f8d175ddbc7b64bdb65ad40599b812fd0",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,9916d75132593c8b07fe18bd8d583bda1652eed7565cf41a4738ddd90fc992ec,1d5afc59838920bb5ef2a8f9d63825a55b1d48e269d7cecee335d637c3ff5f3f,1b694b15467c62f0cd4525e368dbdea2329c713aa200b73df4a622e950551b40,ae97c5eccd59a065cd973a8d6afb8bb79f9cc70368a7dcdf73aaeab1cedf6f6b,47a811c68e49f6bfa6629602037ee65f8d175ddbc7b64bdb65ad40599b812fd0]"
        },
        "R6": {
          "serializedValue": "1106f015c413f015f015f015a814",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1250,1400,1400,1400,1300]"
        },
        "R8": {
          "serializedValue": "1a052003faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf0420003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0208b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b20e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297207a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04,003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0,8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b,e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297,7a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0]"
        },
        "R7": {
          "serializedValue": "11050000000000",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[0,0,0,0,0]"
        },
        "R9": {
          "serializedValue": "10020202",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[1,1]"
        },
        "R4": {
          "serializedValue": "110a80a0b787e905e6cdb704dc173c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,4649843,1518,30,15000000,8,0,50,15,20000000]"
        }
      },
      "spentTransactionId": "4794ca3fda5924b8ee70318405960899e3790dd081d9cd9f984ece55338863ac",
      "mainChain": true
    },
    {
      "boxId": "cd18e1fe2b7529a22805945b299d0080ccd94266d85cb725d52220bc61e9c687",
      "transactionId": "6828e96b0f5a48ac059d5b444fda68c72c2c29e71e2408764877f5dfe3a4201f",
      "blockId": "0298f1ad7cdc91f99907f028570b4da77bd3a65a1b7a7ddb2d3f684b4f9b27f6",
      "value": 100798082521,
      "index": 2,
      "globalIndex": 54586828,
      "creationHeight": 1758718,
      "settlementHeight": 1758719,
      "ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
      "address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
      "assets": [
        {
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          "index": 0,
          "amount": 1983796,
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          "decimals": 6,
          "type": "EIP-004"
        },
        {
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        {
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          "name": "SigRSV",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "amount": 465753768,
          "name": "$ERG Lend token NFT - 01",
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          "type": "EIP-004"
        },
        {
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          "type": "EIP-004"
        },
        {
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        },
        {
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          "name": "Lend Token QUACKS - Beta-2.0",
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        {
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        },
        {
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        {
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        {
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        },
        {
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        },
        {
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        },
        {
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          "name": "Lend Token QUACKS - Beta-2.0",
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        },
        {
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        },
        {
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        },
        {
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          "type": "EIP-004"
        },
        {
          "tokenId": "4408043559420b62d988f3dad1148ea43465ab15ab01be73a302d29ade0bd0a1",
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          "amount": 9999999,
          "name": "Lend Token QUACKS - Beta-2.0",
          "decimals": 2,
          "type": "EIP-004"
        },
        {
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          "amount": 9999999,
          "name": "Lend Token QUACKS - Beta-2.0",
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          "type": "EIP-004"
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        {
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          "name": "Lend Token QUACKS - Beta-2.0",
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        {
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          "name": "Lend Token QUACKS - Beta-2.0",
          "decimals": 2,
          "type": "EIP-004"
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        {
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          "name": "Lend Token QUACKS - Beta-2.0",
          "decimals": 2,
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