結果

問題 No.2290 UnUnion Find
ユーザー rsk0315rsk0315
提出日時 2023-05-06 23:58:53
言語 Rust
(1.77.0 + proconio)
結果
WA  
実行時間 -
コード長 31,349 bytes
コンパイル時間 13,347 ms
コンパイル使用メモリ 379,112 KB
実行使用メモリ 16,472 KB
最終ジャッジ日時 2024-05-03 06:22:31
合計ジャッジ時間 20,106 ms
ジャッジサーバーID
(参考情報)
judge1 / judge5
このコードへのチャレンジ
(要ログイン)

テストケース

テストケース表示
入力 結果 実行時間
実行使用メモリ
testcase_00 WA -
testcase_01 WA -
testcase_02 AC 18 ms
10,368 KB
testcase_03 AC 28 ms
13,180 KB
testcase_04 WA -
testcase_05 WA -
testcase_06 WA -
testcase_07 WA -
testcase_08 WA -
testcase_09 WA -
testcase_10 WA -
testcase_11 WA -
testcase_12 WA -
testcase_13 WA -
testcase_14 WA -
testcase_15 WA -
testcase_16 WA -
testcase_17 WA -
testcase_18 WA -
testcase_19 WA -
testcase_20 WA -
testcase_21 WA -
testcase_22 WA -
testcase_23 WA -
testcase_24 WA -
testcase_25 WA -
testcase_26 WA -
testcase_27 WA -
testcase_28 WA -
testcase_29 WA -
testcase_30 WA -
testcase_31 WA -
testcase_32 WA -
testcase_33 WA -
testcase_34 WA -
testcase_35 WA -
testcase_36 WA -
testcase_37 WA -
testcase_38 WA -
testcase_39 WA -
testcase_40 WA -
testcase_41 WA -
testcase_42 WA -
testcase_43 WA -
testcase_44 WA -
testcase_45 WA -
testcase_46 WA -
権限があれば一括ダウンロードができます

ソースコード

diff #

// This code is generated by [rsk0315/cargo-atcoder](https://github.com/rsk0315/cargo-atcoder) forked from [tanakh/cargo-atcoder](https://github.com/tanakh/cargo-atcoder).
// Original source code:
const _: &str = r#"
use std::io::BufRead;

use proconio::{
    fastout, input,
    marker::Usize1,
    source::{Readable, Source},
};

use nekolib::{ds::UnionFind, traits::DisjointSet};

#[derive(Clone, Copy, Eq, PartialEq)]
enum Query {
    Q1(usize, usize),
    Q2(usize),
}

use Query::{Q1, Q2};

impl Readable for Query {
    type Output = Query;
    fn read<R: BufRead, S: Source<R>>(source: &mut S) -> Self::Output {
        let ty: u32 = source.next_token_unwrap().parse().unwrap();
        if ty == 1 {
            input! {
                from source,
                x: Usize1,
                y: Usize1,
            }
            Q1(x, y)
        } else if ty == 2 {
            input! {
                from source,
                x: Usize1,
            }
            Q2(x)
        } else {
            unreachable!()
        }
    }
}

#[fastout]
fn main() {
    input! {
        n: usize,
        query: [Query],
    }

    let mut next: Vec<_> = (0..n).map(|i| (i + 1) % n).collect();
    let mut prev: Vec<_> = (0..n).map(|i| (i + n - 1) % n).collect();
    let mut uf = UnionFind::new(n);

    let mut res = vec![];
    for &q in &query {
        match q {
            Q1(u, v) => {
                let ru = uf.repr(u);
                let rv = uf.repr(v);
                if ru == rv {
                    continue;
                }

                uf.unite(u, v);
                let new = uf.repr(u);
                assert!([ru, rv].contains(&new));
                let old = ru ^ rv ^ new;
                next[prev[old]] = next[old];
                prev[next[old]] = prev[old];
            }
            Q2(u) => res.push((uf.count(u) < n).then(|| next[u])),
        }
    }

    for res in res {
        if let Some(res) = res {
            println!("0");
        } else {
            println!("-1");
        }
    }
}
"#;

fn main() {
    let exe = std::env::temp_dir().join("binA4532D7D");
    std::io::Write::write_all(&mut std::fs::File::create(&exe).unwrap(), &decode(BIN)).unwrap();
    #[cfg(unix)]
    fn executable(exe: &std::path::Path) {
        std::fs::set_permissions(exe, std::os::unix::fs::PermissionsExt::from_mode(0o755)).unwrap();
    }
    #[cfg(not(unix))]
    fn executable(_: &std::path::Path) {}
    executable(&exe);
    std::process::exit(std::process::Command::new(&exe).status().unwrap().code().unwrap())
}

fn decode(v: &str) -> Vec<u8> {
    let mut ret = vec![];
    let mut buf = 0;
    let mut tbl = vec![64; 256];
    for i in 0..64 { tbl[TBL[i] as usize] = i as u8; }
    for (i, c) in v.bytes().filter_map(|c| { let c = tbl[c as usize]; if c < 64 { Some(c) } else { None } }).enumerate() {
        match i % 4 {
            0 => buf = c << 2,
            1 => { ret.push(buf | c >> 4); buf = c << 4; }
            2 => { ret.push(buf | c >> 2); buf = c << 6; }
            3 => ret.push(buf | c),
            _ => unreachable!(),
        }
    }
    ret
}

const TBL: &[u8] = b"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
const BIN: &str = "
f0VMRgIBAQAAAAAAAAAAAAMAPgABAAAAIPwAAAAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAEAAOAADAAAA
AAAAAAEAAAAGAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAABIsQAAAAAAAAAQAAAAAAAA
AQAAAAUAAAAAAAAAAAAAAADAAAAAAAAAAMAAAAAAAAC/TgAAAAAAAL9OAAAAAAAAABAAAAAAAABR5XRk
BgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAK8mgKpVUFgh
rBIOFgAAAADwqAAANmkAAOACAACvAAAADgAAABoDAD+RRYRoPYmm2orhgzJO2QlKPWzn6t5gqkdhpzQY
JQvAkJGxYPcNRvlgaGepVpt7Je4YmqEYXdT4tKcG6oKstq1GKCDEJz3EAvEmHT3nxRFSDUpMUzSJ/+U0
IsYCqsWSzx39YxolS8ggFj3a0D4mTrCdXltmVx6i3rJ+e19aVQaTI7IuKjJOJH710djaiKPJm0OzKPMZ
8mMw/5Xm/2j3oOe4EDaJQGRdaPOGH+AADwAATwMAAA4AAAAaAwAXmwkmM3GmCYALHTJPNRq/liYhnSgP
FX2WO3CstB0TYQRuPnDn/eIVCsd0PzwJH8GA1GBgnAQYAAKY6CCNGYYh6yMwpx9YZxyFkuCrC9gfyW0k
s3NWuLF3lzbZQIF0gONhuDuE3/5n1x6k+bBRezYhS3+A4d6tf5gz7mjD+PQt6CZa4mP4DytGORXOAtDi
Czxh+5NpmvJgmDFJS/oYAr+vmUGmhECDEOA+aNf6Vvyyl7Q/lwjWmRbRSGUz1SdTeulF8CNVeYEKAG4g
wqrfMDkj2Mc2FL4dcUDNJfeYJ05iwlX8JoMH6AOFPZq5t9sz/5+XmrpZi+zZLa+Y596pMJ5oZWZoCtF9
DUT0eklntBwlKog3SQgVvhxzHLwV9pMvLDzqRJOYiMLzHbu6KqVjtlHyJIoHSbA7NAJG5fmHs0wcWh2q
v5011+J51TrGEyAYKrEDFoQAAdvkCSACMoXBNl1Hmgx8sHYxOweL30UKHHoXbviWyKrhudQ5wtS5Y9gL
YT1dUIQV9LZovZ33UF3KUj8MiJq4/LafBHiC6V9ZihI1wG5C6uMTxWsx5g78f/v9shY8YMul6v26SJaK
Cdj0BkEu6qtigL50u4hnvIVHVPpgtXJxa44AuGfqsEvvknYxwZn5jDMb9n4D4kmeVh2gcc3XZpDWuwXv
4boeXKTyaAIbBu8ZQstiggSt3mRtBdkeP+AMtLc4HUiRBT729O33dtywP0pejRDZ10nzvozEqZThiyX2
BTdHEyxxPObag0UbG/H2kxPBWB2DS8xP0uU/sjMLnBaDNmVac68OoR7k+zUzcJq5NeeAy03jYuQ66TZ+
A72+pseTtwfvJ7Ekl8bArp/gXTfhnag1R1TgB0DTdrZrlo+pHmNLBXGIJlroT79xDOodshRSkw0bT12j
GApKafySvgMVW3YEfSpHZWbr6u/aRWALz6bLAeai6b9MJNNMHXk4EbIvPH0HDnZLDfqPjBI8vOZ8TTwu
FijV/Lg7ehkDGI7NAzUaeDrt1FbC2W2A2puOIuNcK18jmRiTSotpSO4LZ0TICg5odoLfaagCHJfjLRHT
eKDiN93Bam/bcG69DZQZh79I9E8intebEO4Wz7nxNsN/dpkGpT+b8eZYNmkAANQyAAAOSQEAGgMAJCDZ
gIJasTzXfX6qes5l8V6R5rRNH+1vUQlflUUfDmKbSbOwnfquYC+LGdBJXFkdPL5gjrvQxK2lC7XAXqwN
9y+57Zf8CsGt0tUThWiBm2BEkdOZujmSN1rYrcOcHT7w3U1z9AXI9vcnGydLyz6sZEZ4xIqm0AsalGmX
JXKfBkwX2ziGJHIOmuW2xZiA3JzeoB5YIKQGzQ2N7e/J4DahmeQ+jbUJZnQ6If6MWrzKYmEUrHUSKCNY
/eGD7+9nchH6W996vcxjQ/7+sG+6/3nL1ES7kI5BC3xXvz0At0VJknCMHL0o/t8IPAkVYgsQpRcOYot/
kbuRBIwR1B/4mVwFwCukExYq4Fnb8NqoZZiqDWHeQ5y8ml7lUGyK7GY4oOy5mfFO7A5EJUPxCSo9EECi
tBaQRAIqBJ0ZKe7IKaRoMQZx+ZNzA+9pDBBuTwR0ArrHO0ED2gN249LaKGOa8aaRj9uwbx3L/daZP1A5
Ezrca3JgPsBCKjMqBmiULmHs9sI5kyWOaaUxVZ96g/iUgS10D9leuwb74NsAnWo72GDYfFdS9YJrbqbo
ocqD7vVM71R4ITprGAjOC7+sVKl1u3LuE0//HEZH+gvBQ1odJPkcO1MzxxpV9z8zTQ0huBSKKem6AkU+
lG31VbOVp6xbC5us8rIu/cM6PnqoXGr+xIGc8qrXq6ZQhe5kQEFkuKDQkoh1kAvx8PU6Z9aQCNzz0FRb
TLaXPsqPicwDQBRtW5nvgCw7a9ih0aNBu13xYbl0jUHSZdjFQaI+KlT4QT39Bx4GhZ68EQI+sndBfkse
ygmA/D/yPOWygeP3pGPpo8C8mei1JTcvEqLAFlE0oVGfkF883AXMA3Rrd2qJpXaWHPk8vnhH579laon3
9KHa+Jbt2PAwR58t7RL7qI1Ep9wHLMwZBCKVlQtRfe+Dy81rswCS0Y6p8pSuZj2PUh9fokqlDeVogE2v
K1RkZRjMloW0wTmi8GUwYkZO0fmnIx9TAbRygNfzdsTrNdOughZONsP/QOJ6cD3aqAmqzx+fFZLim1nj
2/E7Ix8phm9PwYxRm+3zQENvBwBLfTcbSsyXAZbQ5FeSbcV0uZs3v/hQh0AKrE1NYx2kzz34zmdRZwzO
qQVjNBtU6go08Pu0kVTYbB4wyJsazNINjwq4Ej3P558V3u3NeXNWEKdQrIZo7nQmPtGSaVjc7AUrIH30
NJcGe/TeOShWO4LMLoVwtCF3tMnSzYlyht+JY+yJUExna02rakCNXm3aJ0zMetM/2uesNQmPkIsQ45zb
3AUjvsvwSk/ECf+5ScjBivTWHyQ32n0roAmaMBs0RInm1KCpmB5JYoCDbA+tCKXd9hycoZpfIKd6C3rD
sekWhPKyxq0kOv9z7aQ3LdyITJf0mwiMaUyErsKjLypAaLBcn4bmh9XhdRlrXloCgJOrUevxZyKUbajg
TB6OEsmbqnIpBfdUt5z51bLaoaYW362qnv1ciOIbXZPwu97Lmq9Mccve3r3JSJWLSQfC2ldwYSW9E2fF
s1frNDtD4jgEvefzJyYhRwW8SwvMK4auZiFCfVL04bDoJj1amb81daiVnKzh0a//LznZ132hswAePMHs
uCUZ83ZAMILsNYpWs/D1xYclrQULNFWicSqfTXHScVg62p43qjlRf32ATGC5ztD+vvOHZ8rZWHKYI5eE
sVz1UDoNUovXTymJByq3X2fSiOy+1MWSKMOcB5pWt88H69MHY+AZl8iQwX7Oh2FvsuKu2uvMxyTCtfpZ
j6UxXSXfi4DntBzE73gZ+RpI/X9N4IgruHq/uWY+umc5Xra3fnEei9Mkd7SRqBewhUznYrcyM22uagtP
8Fu2EiDva++VJ1X9NNkmPJt2T7AMdLoI9NhMsy2mCQD/w5+/jH3sTem1oos9rOCQVJbV2A7qcPmCqIKF
9ksrBVjWhd9AXP/hgid4KV0pE7FCgagCWIWmO4B8qJtOY7s6PZz80ZVuNlbxNoXRb54wSF9PjEZsSX2W
mznczjTyBijjlEdCMTnGArnYg6EhMpjNJBszu7uGpmpYuXg0NRRCkYd1PX4fGnvf/3m/8sGehtBLY+ya
eigQpzWKe3aePnkfR8igulduXegVgjcCoXwOdKBdPEei6q4+LWd9wnWEUUGCEfEnldg85FuzYSWkvz8q
A+3GMqFeJ5MISPXC6oR05MtZ/PeR0ZHYGBC591mcVrrTaWldVAyRWYLuWMGyjpVJa4ry8DofYeKk9x1J
f3bdsdb2+QbXTeMhWs5HVXzzImKEz33f3nS4gCzY7hcUboLtgYH2o1yd7oMlTCeAiZeJ0c3aw1rYQJiJ
VhKJrfTm3tsuTjFNfRw7Nt+8u1YUWJcUcQAI5/Hpry+Erx6aa4xjG4yW/J2Hv+8oiZmY9/ExlTlAzoKU
BWDq8FS0HbyvnSBW1hlYYnmhdorYgP1AdmgJJS35LhZ6zQWONQaTaLLIjPRVBc/Dx5hlxX33ijIfum+i
NkmH8877lQRR4OzTlDukoVwISWHkZShTs5k0ohVAcv2D9vrRptvHr7M74RBnQ6ngIUSneEpoWq36t6nC
Y40VmZGyQ6pHKvhAxb/7iudqF9VoinEh9eJ1OVtwCmgDQ0DDT4JmavbHvY2aMnDhDvVZkhEIm4+UwOeh
u3lARPo9d1g0vYARGO7GQXyRf8VrEoBjiKJCvW/gYc7hzD941U7bA34w8fepeilfjClbBOkiTwHOCMYi
/LHRRyeuQK240vW2bDoDnPhmcj8UZwxT3oACk08YRJ8DMeyRMtxxHS8f11y9G0fmDrDU6WET2Kj1QfEA
kCG35MTMo+UqpLH5PDJv9afnEH1PYgyQAC7SEJsfPfYsgCkK4cxA5ka19rvul9cMw41ShroXU/OlQwPO
BHE9+KUodDiNcmR8YurJv1tWyl0S+Xms/FpKRi0ehYHIYIji60+FPHNKtlEVLs4cAYhkm8t7zcNitWTQ
aaEZYfV8aIrvRxHNe3zKfUSSGNBxZeE5X3vbo4ZXp8bCbSYa65SodG7mFpY5ZktQsphwiHLsvn/n8mcn
PP0MyR35ilHIt06RvJzIr90t197gA2TZ/r20Zikv97R+QF5/Y9kg+xQvoKURyAkDjtB5OwTyCDIlKFV1
4EZUNFLVB+4i1FMxK+H6l/6u3TcSdI00mF/7kj07fcG35gZqvSnkAxDB3J0uF/PclWXhhCIP2kWv+80Q
TzXLn3EaPde0XbOx4ugG7XfhJtlX6964+g9aHzAAo4VVePrjfm3kxU2gpGxgtuS5nuYM9LrdTIoJtFZk
Vt8tl28ymeBhneFtGZlLtJBQ7jrXGB20kVQc2Yh9euBznWypdCJr5jdpgbzndHp0ytM4KW6lIWkykJnx
Xld58PyC+PyQgZIsCfL0fib0yfwmevQfOhhGpoq3nlLJa67D4eQNgojkBCHCJqBu1P40q3u+w0MTSh8q
XAzD46wPoSIkxcMcRxLge3cFOIpWHiZVbDtDEsrZtqnRvS62upJaA6o2PK1coF3gDz5N2RQos9+nLWEg
1vg1CMOyP8JfCqeTbep5Vck1ppNj7cogsJ0jPyGA2iZjBFZj6//4gO6XELGfYbg8b5ONS+4iKnmpztIp
Rnw054z8JjuVBc01iufLxxwGrmBfPe4ucYNk0X6O8ROYd227iKyRZ5s7FdX6nAQh4eOAO7FlRiNijARM
iUHLmICe/KI0E1MQvDa9kPIvpWDy2Fj8FySiiUUJH6rIFyAEXCXA76PZVJiZCKeK/s8to97QoU1qODL+
gRJTXelb7zrw+lz/k6BrSm3DhHUFpiyFRDFX8A6itcsBSjYJQv4X9yhtexJTLdZOm4W53FxDd3Dh6vSv
QAcPwU2tO02RnCRZbKWkW0yCxE0KSH4LhIrvia/9NpbCWCGSK1YZtq/jBdMXRSRe5TRLPsj78A5k+UD2
Ygf+1VqehVKmBY2BDxfCGepRz1jO2of581n54APtapWA8L4WTGaOIKtJyPfcii+PeOJ79Ks8+wYmtu0N
0Uc4jHf7KT7QqO8b+d2QtsJmAQOnsjsi0zYVtCAdCaKoYOdXL5j3/P9lXMJ+JYA8nAhQ+J8D/5pxUhSa
xaAnDnlo9kRfnqT7U/7UTGRfXnCDaTl/c1rmw2U5Mq+Dm0Qh9Xn0HPHx/QmMfj0q4sNQ3MEJmtzznaty
lPmet80kzZ1MZwiUw9+IB8E7TQkIJrO47e6QL70yQDBbxFkAhS7QITPU3iLYvGgQyayTwg6SBub1goFX
7ixgxRcweeAF0vdIxy+ZsGRuIrDFqqYw5hZ2MsJhVWYXwY42sCoo5qKU4lysdU0IgiCFIiYByh/+u1J6
cN/8KSSbvIOv/AxGbBml80/i6CEpfW2x0Z+zKXwZy/mPsum2ML7apczGmxzuF/tTYA39tRClly7scWHy
JVaXYYUaNWe+x6ANYeA7bIM+5QLltlPz5FIDLwOzWsLitIT7IraaeGfQ/KxXUOU8aaOMNiVWvFMaoWYa
8RZB0osWKDu1ZO47AKR1pGyo8daxlYIeS4C9kiVLPqHUAq2yo721S0Z16Mmj7st4zaMyEpyBBeb05bSb
QTDmxDnasXQnqchhGerMhmE3rVCglafU1C1SkdXbB6g5frpLFVkVEfqWjQljV2RMP4m4bdV0ABKN4CkO
ETKGxssY00JIXJ+ahnBKRqcjVTZRHlXQs3PqDTFPIHv0+nfQWAv4Fi0819lZkMjgAmmcALnbnTkJjjPr
rhdGRGN5uQH+z3z1a2fX0tAbp7ojVskGjeQditUoqCLLolxfOi4U2S0W+ZnlE05K69g8ukeFaSksYaO7
lKDlOEmx+4oLjWpwKqjDxQLyqcN3nWCTOEKfU7rWuu5b3KcgnjW0QxKgB2rW2eyXkIro6EQ+jaREbO5y
z0lIhy5pIp9GeXNAfuy+wt2oiP/b3AtLU1Qaq0P2fQXWbDpHFmz4YStRBRYaA0s+QucO8hPHp+5vB7hk
qXhiVqgK8kidxGhCDWdhzKYJ+seDl/rHx4ICqKXHnviw/sRzQU4qBkhM2LLzhHVeSTvJ+gIb31AaJJ2t
iH1Y3ffX27HekSkjsuNoIxAaFp6jcMtifrRNnkB8JzenK4Ble5E4BCP43gsJguPvsvQgV8XSFCm86vFn
muVpSfwZni9cbX13DnSTBxZjpz4DC/YERwJx89V2NMMr41mF1JWE1PlViCr3m4OGWX3TOMsX8WFpwh1j
vGx0TBDUko3Ao1KScj+5feaP5B3CA8PcFviJz+fXLAOb6Rxe8vPmezAo+t/Ts2AiLxI2lHNoN8VokLtY
XSd3cjDgRnyPA0nq8czuD5GQ/Nty42kibCXVKDEVifXOx1YLGJGSLhaygS5FDyF5eW+B9cACLy7Vj/wQ
os19qbjjY880Dyw0zcESqKh0D+ZWprZ5k2NFWbDAL6dFCViRiichZcBJc41rca2LQjdLh3WMmVmuoe4F
fyXlAHdB0DlEEaDeh1Lsqk1OOGEt3IU7QnLH2WRY/uCcvLVC41otJB7+LpKHJeD+cccOfwfMroaleRqp
1xNlP12s2h06LFcBXjC4eOXowknJLridnac3sqqfpHKXmRxLUUcIH1CYgH/wKZI61uoA/nOWEal6Y4QS
CUFGTJ5MXllIH/B6sGKCHI2xfviFdSaVvQ/XHcYA4SigUC31AHBB6IwXF+oVU1oaXRDFbY0RjoamxuUC
XbsFUEWIDjMOg+FYSM4Oe+ALyWLF92BpQ75Y08a4s2gItnBNdupVpJvIXeqUOU7L3jtUvfmPj8DomAcI
aCnlTEzJtHKpDg+mkalZGIdTDEZK7EwbPlqqoyqjE4gZ+mZIsfj9TNBwszHw9vZeMLw8uVe0uZo7NBUN
lDFXxw7+2J/LpvjvQ7i/hAGZWbRudxYyFHZfsAjBUtKtXpbJ7ifHeymERmGM/6/O/Zwr2Z+nKcQNXWyF
ZmrVq7AVRX2d3bg7yPtfDGQqBDt3EJacFjkW+EASo+ypiulY0v3LSUVfwgebdXz5fTxbZb+qSXF+DC4M
ftNkBB/wf+KLTowejCUzNXLuHX7TMe91gYKKjqKdm1w0LW0tZO4zBhSgM18rPyGKPufoeRCVE5NurS5m
UJ8wZY5LDY/sWs4uyv7CTSj1M6YF/BX8fGLYym1RQpLsFUlKxdwmi5rbtvKzVH2Ar21eJq3sEuJ/njnU
HizGa1+3cEe53VQT372mdf4n3iGSCwlTGqCaAVA0maXjXBbF8wSui5uTykO9w3DgtLS5/zbgIym+NXYN
O0ybbXaQrpDTZA7Go/8Vd8knDGmmARH/eXVj95VF1runbWxDMXHrCIRfGS5m6LQ/Hvd09mH2NOXY2YDH
x5dGMITnelnL8wREe+qDWMJnbwYDBlGen4wQ+fp1gG+t9A5ySb7I46pP8AyQvI+HMSJTnwfxC76XhMcc
Wd2w7x1kIpQqO9aeXdkqgcKGWa5KAFIuujCBZ/qfSIElj3hpLt77GZP1WT+kxyDKWM0cw2T4VqSMVJwS
7+KQbtSszTYBIMiO1SyNhyYW1AbCIn0OzewNU33ZwO5aQ1j1e0qEoIdbChvMSU17IgW0QWH6tD0BZGTM
RBbhfXkh0LEfZ5+65kPZjPV/Cv3axx6KBWMyniH/846cOCK2s0WWPlnJe8J5JXxvuVUatwbn1WK5UAKc
p+vo5jTwH1fcxKOttLFaRD/CVo36lZvVjkB0D5KZVEofc34nfIhBa4ez6cHsNCDi8/FcCzSkaHC9CY9E
YcZHfKU2DLc1jeGmcPlJ0teiamb2f0To5ofg9UbGJ+DCvZ90tYWKAbxqEIpmQCEj9LjsizUhB/LzmDHu
U8WQ75g0ClPP//V82FWyae1xkdOwkIewVq2wC3NiXncBWmGNH0hb7OFgH4D/WM+ME+4KorOT98xw9cPi
oNO33yU13r6dRurUYLrS8xdM803FvQELEUg5RVQHO6Us6+vHmq5AHM17kvJDmyE7ZopGAzxCabiEFKDY
5Nsd+mZmGCYk+X3twpzTrBWAlvUh+jX4Cko19iziUNhRaEPzy6ADy1x84D/Dp5q/4SqAEJu0rj2thauX
dM3gFmtlcBbm41yT/gPnCZ+TqRcbQroYZd5LlPfaYyhD78mtm9dymqb5QM2Y5NZrdwAo7+xEA6+lMJXU
vuLIjj5CwNo59YKLDtedujaP9hkWWCHgC6SM63KXQEHRZzlq5PcShPAxX+Bv9IatQzOOLwSCIALFN55u
eMHWpjpUtSSFlvaObA+Tigjy9AjtnLPxgfS10lvKeEHImBMpvUeniEy68wY2SKB93yrEaeryK6pHwEnQ
CvJ+YtJV8OqAQytJ6SZsVqWnz86tN+VTzVG/g0EQ3v8aW92KPZgA8QaLcKBeKaRbaJD8kl3bA19OqPpb
tb+mO7Zfet05trcuX+6cz81bdKXuvSq9Xjw1FQwIDTb+BvKtko/Py6re3FfkJE0PGoUky/T/gAidglYx
ItHOjjBgyZjHoFzGXAFALuSdHUoY3fzcnDOZR6OoUW+9R4HXXR8PZKFoyf2EwtPx7yz4qbvai+efOHOH
3FauwvRnsyjzeqWmwSJGBHPi7U1cbfF3ds45BnlCbEjpiHpQlElf9SsS725XhxKN00hxb+DjruZfEEEv
0eUOz+skbLh1ufIawKudYwwDuCDtXYzX5jcB3qfhF+mWKwguVgi/XJGzhfPIU0fvsvsG9Bua4pHeeF3p
R9r6wI7c1E6aOgFvt07Lf72RjKkh1u5RJn7GUNdWlzzueK0qYmErcIoSn676KslMLaXEKHihilMHPYao
lzx/7RTAqUnMQbjL01h81ipU33/RO1n5fQbPuPFsgBkRwcd60TTBt80uIX5aJZv1NgkWCo/3j2c64Vmu
kPUWvs0G5MMfxZxHng0phZ4bF2QjecPcNQA1gITyh3g6uS4eSSnoyYT7nEpNWd07JsB34imw+sM088cQ
0g8TqFc9fhd8pXzmWTbh6tOCU9na9Wc6cRYvvAm8XXCJhaB0b8dL1bp7qAXIHcWfX/zahAGajTL3dQQi
4P+tZ+CxAEMlRaP79/ii8Uksp0m2+CHkeol6ssWiW8BXm4TCzPOOq6rs+ty5dm7PtDt0KnqizsVQcTR3
1g+EhwT58jU/BrPbQpMJmIZG5KFox3cp60XeA90XIbsbIO0Ww1ZADxLfVYRcIdo8hTIkmKjpJuXoAs/R
+FDN0a7ZeKtQL+i6Of4VFLGXFmBt/by2eVQWz3BBaPPDNoI8bVD/s81jePxdD3c3UyiwNPk36SP7/sQd
BGjeOjszgMC/OTi4OrA+1keTwf1YML5usbs+yeCE2US4o3OyOJN/qT8JvDR8Nu4W7ov8MW5RQZNOoK9H
4K/1Y76MeKP1/Ntr6Wo6/99RCzT0bD6hou8zDVkfuOq/RLBMoBkEmnrVIQ5CrxWX9N2XrkiqKqFN4FYU
BnOacjVlfn8SESty7e8+Ns7d0oX5jyvubq6D+wC2o7bZQgNqKTWfpDBZCf+RbqhKNAxHbQC9A1M50Ar7
BsIC0z3HmOmkBQMB8fHspkFb17tWLNufbiEa9vvIbzrKYlzAvjzmZyyAKpCaK42V/JKmMThOsDNhIrSj
powK8K06Cirv7GWmf9ku4AZU/zWVnwLnbuIEynWS2DsKuj4RrEulAAjwBAiuMoVF82e7XuYcZ4o3Gj+G
6l5bZ/s0CBNEWkFxlI9DI/Pxkv23g4n0PAUacBHMgipfW7z4L4hswsT7JipLEbbCDg0YQGNYnLNtStCS
8l/aFRHL1zwPmNEBBVF//Eve3N9gc6tYHh0ADMq6nfODCrDYBc3twwSbqz4MqlvhAXBVN4jtDpadXm/8
t1mzGsjqF5vwHfGLNGmzjET+LFyfsC5LGC5Qcod+6dHB00+Jr39SgZXJklCM9vXuBHuzAYFw62QDDNd5
PO6a2pqddYFcXwJ5U5VEnGF/VsJD1mKruiTe0AIWC4rArFohzf0UCs6QTOQPAb9jC+DBOFFhbSHIeoKO
7idDjClD7FXNNcwkkWF23GCMlnC4vBTJ2aprs65k4fs46E/ay49BKKY1JDlHOBLBbOsXsi+mgiF41rGq
Z4JrmDa8oWn4U5UADztBKIz5MW00/sVvAtLZqixoV/SZSwwYtY7++szg5RNb385laTTgyod0CTJjwC5b
L15kNrzu84I7aQ5ACC6/cyt9zJy9cMtDfZ3rN/B5ogym8dhr0SrAyQS5TluDDacXx0Kf1lJuslz7wGKJ
rAS8OGxi+BJJS5hBtvFJEfE9KnFEf5t9nqNchmJeCW+D4GZaqCdQDn55KtN7gyWk8vM6lAxU/hr+aOtt
AJlBoSkL/y13rbVxKgN1suenJSbHpipBV5dcbpVHREu6i5mernsIYPX5+8oZw3sAyDVkAPkN8aMMQKQr
XbB8eT7yvS/mvlgkj5vzPJwtpTcEcS2OSuF6PNLIG1Rn+ZofA9d396deqkzQIsE1CY1tmYiqM2e9GoDT
0lD4kbpQh4Im2lqlgjs2JdEYSXUtKoqrsug6hrw0mnLVsq3hkoEOP1ThKTI45APT0ijVtM9JWDQ32Q10
fiN+gfMHXhR8i1Kt9+eubMozXkGjLpAwsaLqlWfTXiHpI1/2rIifiEFhWuCKscdZpesgkA7m8Du8eF2b
WMCxafakWFecGwqW2xO6aGIpn54CBEQXOxrCTqV2RBdSapU5OZK6rm+Umk+HLNxkP71ksXjX+XrLrpMr
tUHsJQf4RWrWQdn2aidFDYhWe8S+2lfjeKZNF2RPlpV5x4ZBfjjt2nc1sTAGapt6epPoIYLM4R47ux64
ajSg6kv4gXAranoDTNFakyKx69egLq0u05n0WXl1f5LumVQlgLHrHEhRbERVD89I8eadpZt6gwSPuDsP
EL7Ymtrx83y9TMzdcgUyXWePNreaCkoYNUQzzWF/DdqA1UnTDlhz0htBV/2LmouIHuiKmN7664UJuBzP
uindnuhYQkuU3JZ0DL6RtbrZwqVS7Tq+j+lqzLjeEH22YXZs9TO53ez7DFZ9yHt1dyRqnlH/YBp0YXYt
Fl7Bll5Zv/9JJe7QukATxHIgPTqpUilG/ndT9RcgynFt2tPfqRQ59Ur546NB8eXZSZE5I17Ou6tEfUwm
O2gXmTCHXvHjMaJdtSfW9sGADpYNeIeJNaloMYhz90wIkQwBgqHLTkLFs+PNufKVGaK59sBvy/bSqGjS
t/i4RIA7jOirdjGNhoSRetFc1a7BMFnEHODmNasIjVaugp2rM8nzYel4LgxXRxofOOrKPTmCBghaFhJ7
zk+h3RCXawzxl6e5YO5jYOBxdxVZ4RnH0lXELONKLVP2WXIu4lqQP575/FZX+NIJxiLNddOGz1gOy34k
u/fBhXU2sWGLOKhA0lxLmu9RbuDE2CR+qUp3g1E9x8FRHP6+OBh9jRS3B/BAyTFitwYqiJX+oM0k7Xfy
JeXvcLGCevK9ca5SZq4yUq2hNLsGcESLk8g1PcI1cTccPfs3kQVTmJd4tcIRsaiE9rhugPNO5Fcd4YqQ
6sbrL95L26ZxtYQkqbdO3yuQJsONAPfLf4uE5QNy9z+QqMhsWQHnIntgubqZXbcTtK83QCM2cYgrmiaj
TeOavNiETz51d3A7XKdzLqkZjWwHP2TaNezoYz3rWY9gV+MOROBVRYDw29rotCE4XN7AHpw58V2bi0iR
CZnx3CzYzKN2r7ochxtjj1iyNiwxXEdj/8iEdn6+ltBC8IOicJ4QS1MIPSd+CuBvtMJlFe0MZpo0qti5
uZHWD9vprQiKViQgVnsyVGtEXEitSzHfT+pghrABGfrWQsxQZ1fKdAkGZ+a/RRduqUGoyZ46UMOR90nz
j+1d8MyZVjmCUL8pz5rLXpdLP5nLHoaYa5VMBChs1LE3B+MZRQ0MinUC4DatGL5wPQaaiwExBk+R8WKV
7qcowQ3jHoUCZXNyecvGbFf4ml+MWgllqIeFBV2A/UGASR8bq0HrBhrCEq67jlgZ1eUotrbkRTKy1cPY
AtVMFaVdvgVQrDHIIIS6Xt/5tFsyqUc3Mn/S2b1ebX7hkiGVHkOpkdjecctAZfdhsdodJ7uduShBdG5l
ghG5+GytCzZ5hTnD1UMOV8Ai8Y0Cy7MX3FdUIRfppnEo/EV/9xXnwZuVTV3Sltr6YnNOHPzz/uyGp5kx
fq7MfowullWGsdlXHjbmVeLUst6t1Z8GheDWH1bYtC8zW+wxcjQN2tp5KwjsPfDKFkiEs6So4GH3sKPj
Oys55cNablI6zC6aAvBZNWd/kcBIXepWxY/BUN9MQAIVpxVhf/Tr82WebcXlcaYjFz2IHG7+KHvbDBNf
rJmBkeAYregNaYS9Xl2P8aXMd1x2VZKXYLftquhMLkNagSqH2pGuPYhwkI+GFow5t/u/Azn9wBbM2s7s
PePMJOIkVEllNPuGucdn54HcUTwMF0AwIhLx6KIk9nAtlhk09wr72AVVPcYhscTQvfHoibWaHM+ut4cT
0za4jfG1iCyZ0epsO/EUt6dxsDHhI7ue8fCMNQSruC71t2ImWd55wXPYIF+ZbzV09g0MWpZXS1x1IneL
E4aYApKjh2fDhxm2rdJs7lYRhl4UGKq3kX4jRct+6zHUBFVpGKaVIjz1SWGXyLfjywXXYQWDgzPd6I9d
GtO8inaFv7UzsDuhgNR/EMnIGWNhVcVYUqglb2ZuInYM4Pk4zy9of5UEuav4jNYYi5HlJJovzICJ07EG
BD/ivZeEW4ZV7yjbVrHQ2Urpspcfs2peR+sHnotEkB1hCQYOHjZAQRtkWcHj078CDw9VjCG3yIqktJwt
vsOyURRHakT7Fw92RP7TZsRdsVBRw6diJypjZr3KsnGUUfZxrFAjC6ZdRvc8eT8TH28EYJTdAs5hscoW
KkGQ4GblHVsuVPGCmY0K6SwFwX06m2SL7N7SKz46N1F1abO3hQWG2ZPAmXZ13LZQglLyovUF5y08pyzj
3c49TJf8FeAxZUIacZ3zevAwtY/rvQZJ9npvskHZvVOpD23S/5TArBnH72NzSFRwhEzNR8oCkC+7yCQJ
N6WOz2nvNypeX9AjYxWl8nkjuL5+ckU0KGk2xr6PJlc3fnDOR+4OZMmm5fBG4baskTURD5Mz/ECfl9KQ
zEzDcl97wVMNyFyAjPB6vyc3ZE5mtmUpnmUwZy00gLckcVmFAJys1jTPx6ax2UDWGKDLQSKB/NkZjhQS
gLLuJ+WAGaIY9XrL7ArigrPVRIvccqwvKHF9U4I9pHr0ZAySkPJbO4lWdGak0oKRGPAls1fLmp/8DUjn
RLu1d9NO1iOADAu9DGqSg7uAT5CbX64i60yUydceC6K+ggQqY1FwiurzCxzNCF+SRxQ4iQisg0yOwGbE
gYK3YL1FuryjZfj9RJVR3k9p6OKyufy7ItBrOcC1pqYV388+mx5Fqzz4PCf+nQ1Crd2orJMi2jzyKQP/
wTQnKxeISs2CD0KTue9QCwlsbSz1kV6XTf/wIjkTKuD5aNrgUP8GdoZzaunNSgoalg25RF9kyyaoWGZl
1IMyEONkSB1CzQV6yfiZUi/t4Q8BwkopykB+JhCHtrQPJ3ImMoMD8NydYReIQNOx+NRO/1K/2KiSJpAS
SpdgGrPuNhmEqaxoTuzmDK6IGo+E4L7CI4YAP192ZM2d2cbpylmuev630FnHKRNG+HJuUoEpd+Z97dGB
QrPo4xtFRQlNb+Z6Hb0IqnJbZNqWKbcBK519yoRAOPQCeIzs8dVfV2uoXu2542oq04Bd5Xcq4EwIbnmU
HoksFY4KBgoDXHXgt6TYHybw57piDyfBROu8oXy/w3sfKnT4Dw2wcsXWFRWf2QCVXS+x73ezpIp+1/6P
QRYSOU90c8PTT0s34SwAKm3+EFQsqOORN9hwT57wouIpJuSh0JgEdx1UiT3j9YyVXMZRf9naEe4/NuFt
WlTkzDckjNAlkkNOZl1ap4EiGhBP62taLnTk932xrutoS8XGLZdnjeIhAgBSCTKaht+5kVbkBySqIdCp
yEb6HAx6JAKsq+aVCwkrWZMe0zv3l3KbjEmko6RQbaFajHS6KseNCbFiSgrmLta8+uipn39IvfLKqFVG
JBt1e1tmCOy1XZSzoLdSD0Um6JQuOaT99vSNuVGSpx5Cl11hokGoxVYGhyRI7Bl/hslmPCIzCh7cf2Lz
nKBIG18nrnQ5HiANL9QrMsxTv+ZXixmXDhPm2XdHDRyc+lx4bDGqy0mNzQGpyfwFVVpE+gZk6AEqzMs+
xd9QZXiG639xBVhgkkP9+dtUOdZrgqs2dKegljxuITofXucY3a64Io23LAfPnFmmlpdiGW9Fsfye1qVP
g4A9Pl/BOmRTC/MHqtH391ptDLjAmxxefUf7X+AkxF7q2uSiEDqgzRhKm4jF/t5Ph50kJlqP0pR7B8PL
hczo9CB6YGgoBUSxQv1BPH2YpXaBm3hLCJiUyEPQmdQnvKKhAZtzPqKys3c/BifrEAMCYI1wiG/TBGbu
23JYn5OCDn9qByTsl6MHbdr0970x+zzTRQ+8S+jc440kdsgOqP16pHrDGwXG+ksCDzOdTYfiNG1937Do
m4QYvhPyNm/UY1kiAgy17hLYAvl+4o/9AAhK4aHD4j7ZFBDTpYdh9/gbD+Ftfv3WZ/r6+3yFz1AvyaWR
rnyPP2OiWTbroBmwNAa2iMJYBg81giTkYmsSMXEbQXt5yVkkeOyOkF11VuZKv96UNEQD6ABY3qAsS+4P
1954J1Crb+/BrfO6A/mjbr91nx/lP+RKEPX/o1MwbLf133JarNlmOcRkJ2hrn3xHct02Di2eCee3vKRI
c4GS4eyRvhZunDyfa5i+7aC//Xsaw9peXYrpMDUIVs9xVgCeKjAGXbFFDuVinY5x7mMUYcUT0S/MBLi2
nz0bseJejkCgOne3i4hqLfjyUqKQWWUi0d6D8+72qj6GR2ATlBesJE/ZHEEA+4oPfjYU+RI8eALynSJg
Ig3CKSv+7oGop3HhjQkBNwt0ln0Iotg/g8GJAH7HyI6M/uf2/TvtcPAN61LaxpDmx7Pd93cvhH+wk6So
6QhDpmSs0wSoLpAkPHsCs7BXjEB+2dchm5aA53Ff8kKBP2/v+IqpqNc3j4VjJii/Xowgtcjo0Og5HGYx
4pzTyuDTJUtiXlClFvxK4rQ+Vbg68jBOGlocWaM/UQA9w516EzCRI58BKArbcgp1uig4yqAaJFNoybDd
ChduGe31Va4BtAfCOOeyQSDfma6Q0XcwsYAz9PjazmJUADNAQKtcRLKayk2qK0VBsu1Q3Alm4BnUJrwj
jH4YPALmMtbYe4hgEP4/zeVGJp1idJ3oGtGDiSZJXoVhfbunsWY3a3oqsfp/VTVxpwgnbPxBL73DE9CZ
BM46hMNrp34YZc75x1RNtAvVfcnQ8J711zU9A7ryKT2a5saCA9jO9YLxKFarKZttp0e5bl5GAExHY23I
ilJRpXyn/UzPkFH+e3dq8w6b8IOWEmy2ZsNWfiroOYde0Q7hZN6vT9rZvFgvsN3GKrfiTWVNNLwtaqZV
QPy/Q6gYfxaOFMn7o/1C+Uz2wNOTCH32iLp03aWjiqImsztKYrZpWkmhk8cN1q9kSaVS/LrvVj4tbo7H
IaZHbtHg6IQEWgpwR8lzszPjHQxpqAm69MvthlyMHTnmlOAhBjMSuTUEV9oKA9fYNo+O5ivRyw/xwBED
hvWcTEA6fMQvHmTIKgBrsKRKndB4Z6T/SSJarsMjyt/rIP2PFxn1NbKHLOUvx6oaRRjAs8tb0aw4x4/z
OOxcyiiaSQ/WGA1x2uNiE+JiWHJqdBCUTNB9YPM7rYN8SsdD5R1v4Zis2wc7CGO3NjvoV+zx3RqZvKR0
DbdUgFf7Tay3LRphZzpTzP1toUTVAaKAACn2DPfovvASARBxAE3Wgv8KAqmjgUDZ1lS9sZDc5hV/MXWa
Mk7mp4OEStSK48X+R4HgFyFVqzUlPl6NnfE64udzIvXEd5O55pKBCyrjmE6zjMc1cza9AFkIcXsY7zDm
z297xbWpPJrMZPpj7Dz+O8Fb+hkRLrP1hI4nybLh7ROcC0pAqG0YiZuYP/xV9FD/4wiq9CR5FNYxAYW9
mSTLPxkion1Wv8GokWDHltki9KDjx6Gmt5nvfkX2dP7YeLMQWLZN1zwQ6lwXTO24fEZTdr2EdlAhYZqy
QvCym/m45iCKeTSrk9si+USDXDVL+aFAzgNiWw0tsxMc8kJ1Fl0PUK4Aar+0XL5OFjm8lZC49jhgkR2p
qPdxeQYWSpiXNKwAbX/VveGTuRqzJ5in/KoFAHfR9sIPHaKImIs5X+3tZb83stbjIOEgapmZshkasC62
Ti4YggvZaO6eOh5La573g3PiGOuu+8hbEa/OIwgFaZnD772XN+TxABkZDSHHsjvhT+A3irpWYt4q3cPI
NRIjY0GLicHBj7PXIEHLcccFwlV/x5LEYD4ggNUdE/Jc+E15sAQcanqMB+I59pgUQfXXHJc2amQR5EBC
Peq/5lAE8JUikKjer7F9zUSfUCrcN3sWMUs3I8vwGtJ7QvDq4iV0mqL9+SF1xCY9gSmNlsAQEiLJksoq
x2pRP1nE5r87Pe2EdA/qDzLnetyCCMaCsQWK2UBb6zL86zX+g3gab08WRT4T7a3JI6E9Sw+N9Ao9mKPZ
sDHOzCsEbPKlYOz4E/wyF5+v4V5li+WdoWiYpj/Kyd/OyjpfWHSnSdONSBmPwjyUXixPQjt8tuOGmCa6
acSIGJpDbkpNn6MEQNc+IV7tdPeQwXYaYS6wtcT00eYFg+CPLoA6/z2d4zwAhRNj77M9oiS17i7Jb6YE
262M+rD+id3MnCA/xeMnjngGDON+So98PXk2NwlbDp8CisBul3cY6Mwptr3t/rG4NVLh6+JbW7sc+ju7
dANe5FbxFMtXPm9+hJoN3o/MqHrOG0lYUYSZ1rmYfA0oZCoEE585V5hpVqAYEZ+LtnR7CorpeeA5qL4I
9OHfUOvvFlJgetwamLNSBdN0jXnJ/kIRRuMDegufFpzFiCvkEEJUsGdQM3J3Fzbm7PA9ppTRc2Zyqu+P
XxCEpvx7H0Ehe6X5MrLwSAPcyO0/KKPs6Vkhb5WZW/IH6jaN/ksbTIH3UNT6JCUwdslsWeKwAxxujrGN
mkB1Tu6OATcTMsx7IKAyPldv9XyC3NlWNOaOoCL6lZn2mhC3NCrrb6k/DlpWiD6DKyCHVMTzETzAhoxo
OPtMfL83aQ7+5o52txHVRpOUWW/ozg6mIBJWXParYJ0jPwXOiCRztseanPJXGWvnGI5vQhlWTtDRR0Ec
HBTpoKaBDG2jq9J/D6lJbs5nZV/AFfmXtpJejUUaxvxWWDHQT9ytuAjDpYcYKbp4w+UJ3sReU6UGcw6l
VrNeqeZqDt4LEoR92rCfuOKyspfFTUlHrWB8Gzs6/m2T7voJD6X88SbyaMBkHnYzETxcPrAdktrYc6Yv
Awl5QPTKod//472WCp6F9g9jknMyHseO4cJs/uOhDNYKTwIiWqYXieXcPyTGeQZemrU+w6QBL/UF9pcI
UaO1WxSZebeQgY60jeE/WHJARYtyTPBrho87HducKqjhxPEV6hMAyH6PE34n27IOcmcuureLQ/vs0OHV
maizELStGGloAAsQK0eYZyrFvzjNcGdT8mDLkv8qmWRHwdnvRI6S+vZr/xz1mQqrldMhCPNduEHNPvIu
7+qEnn/1WZHEX+po8VVMDWL4IJSnE1TL+Yiqtp87RqQBXJAfWhoMTX0rLa9me2opdwGjqcKxN1z1eEa7
zO+jX0krV+PtUCuNVVKHR5RopA72NmIfIpxUzBov/VxpIu6ddKj+tJ4d2eLWc4iazUKA9Zm9nycDhOpa
bvcTzJs+4G+yZ1+jq9bHbWo3W0NbTLLje9ut2sAMHquptgcMESUSpcXoiTFPQ0pXYNafP4SCU0e5RCfr
Z3pwJlu/PcA6mlw5rV06sxXM1ZKV9hHSXWc/H5uwPBA6O6P5nnjd9uq6RKc1vvpZELd9GEqHYJqCAruz
ndu1IvPfXTd/uinPTwMZda7khCb29HcDQgn6QyRP4vCp8jH/lPUM0SGwwVGDtRBpfe/DSYjH4dASVDue
VludgBcin3VBPd55fQ0/KcmTz/DsFgFTSdVMHeXhW+8vocdwYcepqswd7KJfmuj7+O4B59Oj+ys6K4O6
s41lzDDtWrqCLK4Gs1Hsq6uM/c6qh88nJ2jX2Q/EdaoXxQNGMeJZXyfp/Z4w76SGZlsLCwW60v+KDooH
faGwurbFmxgEseoJHYfyywQmrFgVpPdD476g2WMfvKU/YX6Db+qblUVawt+6B8VOSARSqPozHXZZkCFM
DUMK68BOGin4GEU72l4ALQzHCfXccEwS6PxPu2afV9kj2/tf6MrLLe3WcpIcOpgIAAD5AgAADgAAABoD
AABqfrsUbxtBK5EbaYBdk+kQi1n5drS1UBv02vIKIxBSByz5enqjAUN7GoGrrMpHTo4SwZRHVzIyzWFX
EndQ79365W5wKS48j5X51mQY2pcgxJWgEm8DrvPbQYC2cgHCW5Xg5cGYE9sPcjiwnfyQ/Bm/NlH+D5JE
UPM/+goh/+RHTLnX6QASSF79q7yMfomheio5Mq2DeVJzgQ7ZKhT9JBuxngXL1AStDncD99ttCXr63VMZ
2Yt3hOqIsFQxlcMfoRknKcdwH6/GxRNiM6YTkcJQLsX5x0JS/5Cc69uoBU67J1dI+45/HAxM+akp+/sT
0InnxqW5bVkjf+mxVSxGALrIoLSoTDIzT0NcVErgZ6IrWxAzUMxK1D9wWQJKX7ciSs1H2PHhs52A9QU4
85WSkxjV3niYXKsDFLM64AiRYPiY7DXMV6ILNrJkilULfb6LDJHUUXG/uEiWxYZSdnrW8mtPIjMuUyQg
n7Clm+MXRRGpIouDIOGtxCDNACK8SLgdtFxAg/zJMTD079TeCd02cY6D1XPNaiaENjiMidF//uF55Rj/
1EFQMrSqmuevSrw68lLwXokdjsK9Bhx/HzIzalHM1Ibka0De99+N8E56c+adgOZPCe77q/IeVxjBOK0m
0xbiaWSwp3dMvcP65XLCjrbi87vfaFEqZMR5KJXzlYUAsk5gEdkEhiS/cWsTagZGcBxDec+ZsfPv8fcP
bd4UZldNkCdPomvM0+TmuCb1QETyJ/hTFXzcTrjZandFiGVCD2JOep4Izk6sKLBaCZe/goSPI4t+eYv8
R1Y5jkYvls3elIhJTZprXX1yHk3gA0BQRlki47mCgOcaz/f2KcTeclJKtkPrn2/nZWdAm1gAvSVNYQGm
jvXsVFrlOFcMbcrG3kyBWSqYW1gHzOIIX2CWDxLWGNZx11kl2ZxV6W0Gqil/M0/gLg67j8hA/nRtNgeJ
k7nsfz6tMoWYxWXpCeUpG53Sx04XG07Rq0/rIDMPNJnAJIV5+4KgeAUAAAoBAAAOAAAAGgMAAG0+nQmj
fK49f+rt9nxIFV1jfNeU8XgkdvLP7/7C1jQsIDpgSTD2z0C7LsON2Yh0ZOU0i1GQYdSNed1QUwQInBGs
MNDr4YkHahrXJXt8ItXi70f/guk23md7p7Dc7lZboPvDJgo0GhlIzYc3S/RQYOb57upcwbVoYxsmMQpB
mn89ztEScmYLWyL4zk4W2nX0i3CPbWTr4PmC6bspjGg2/xyhKrUhqQg/K3J7xPnjmZIPOBkXC/YcM6Pu
sxAZnnXMur1D1MhCIbkIVFwR7TAOCAbuxd4N/Vb7zWIKlFKs+fOklnogSXKsGTfooX3qZ0RY7KZmKjiZ
+YQmOUOaV8JYyzGk9RZzsAAAAAAAAAAAAAEAABw8AABQUujtCwAAVVNRUkgB/lZBgPgOD4VnCgAAVUiJ
5USLCUmJ0EiJ8kiNdwJWigf/yojBJAfA6QNIx8MA/f//SNPjiMFIjZxciPH//0iD48BqAEg53HX5U0iN
ewiKTv//yohHAojIwOkEiE8BJA+IB0iNT/xQQVdIjUcERTH/QVZBvgEAAABBVUUx7UFUVVNIiUwk8EiJ
RCTYuAEAAABIiXQk+EyJRCToicNEiUwk5A+2TwLT44nZSItcJDj/yYlMJNQPtk8B0+BIi0wk8P/IiUQk
0A+2B8cBAAAAAMdEJMgAAAAAx0QkxAEAAADHRCTAAQAAAMdEJLwBAAAAxwMAAAAAiUQkzA+2TwEBwbgA
AwAA0+AxyY24NgcAAEE5/3MTSItcJNiJyP/BOflmxwRDAATr60iLfCT4idBFMdJBg8v/MdJJifxJAcRM
OecPhO8IAAAPtgdBweII/8JI/8dBCcKD+gR+40Q7fCTkD4PaCAAAi0Qk1EhjXCTISItUJNhEIfiJRCS4
SGNsJLhIidhIweAESAHoQYH7////AEyNDEJ3Gkw55w+ElggAAA+2B0HB4ghBweMISP/HQQnCQQ+3EUSJ
2MHoCw+3yg+vwUE5wg+DxQEAAEGJw7gACAAASItcJNgpyA+2TCTMvgEAAADB+AWNBAJBD7bVZkGJAYtE
JNBEIfjT4LkIAAAAK0wkzNP6AdBpwAADAACDfCTIBonATI2MQ2wOAAAPjrgAAABIi1Qk6ESJ+EQp8A+2
LAIB7Uhj1onrgeMAAQAAQYH7////AEhjw0mNBEFMjQRQdxpMOecPhNsHAAAPtgdBweIIQcHjCEj/x0EJ
wkEPt5AAAgAARInYwegLD7fKD6/BQTnCcyBBicO4AAgAAAH2KcjB+AWF240EAmZBiYAAAgAAdCHrLUEp
w0EpwonQZsHoBY10NgFmKcKF22ZBiZAAAgAAdA6B/v8AAAAPjmH////reIH+/wAAAH9wSGPGQYH7////
AE2NBEF3Gkw55w+EQwcAAA+2B0HB4ghBweMISP/HQQnCQQ+3EESJ2MHoCw+3yg+vwUE5wnMYQYnDuAAI
AAAB9inIwfgFjQQCZkGJAOuhQSnDQSnCidBmwegFjXQ2AWYpwmZBiRDriEiLTCToRIn4Qf/HQYn1QIg0
AYN8JMgDfw3HRCTIAAAAAOmmBgAAi1QkyItEJMiD6gOD6AaDfCTICQ9P0IlUJMjphwYAAEEpw0EpwonQ
ZsHoBWYpwkiLRCTYQYH7////AGZBiRFIjTRYdxpMOecPhHkGAAAPtgdBweIIQcHjCEj/x0EJwg+3loAB
AABEidjB6AsPt8oPr8FBOcJzTkGJw7gACAAATItMJNgpyItMJMREiXQkxMH4BY0EAotUJMCJTCTAZomG
gAEAADHAg3wkyAaJVCS8D5/ASYHBZAYAAI0EQIlEJMjpVAIAAEEpw0EpwonQZsHoBWYpwkGB+////wBm
iZaAAQAAdxpMOecPhNoFAAAPtgdBweIIQcHjCEj/x0EJwg+3lpgBAABEidjB6AsPt8oPr8FBOcIPg9AA
AABBuAAIAABBicNIweMFRInAKcjB+AWNBAJmiYaYAQAASItEJNhIAdhBgfv///8ASI00aHcaTDnnD4Rw
BQAAD7YHQcHiCEHB4whI/8dBCcIPt5bgAQAARInYwegLD7fKD6/BQTnCc09BKchBicNBwfgFRYX/Qo0E
AmaJhuABAAAPhCkFAAAxwIN8JMgGSItcJOgPn8CNRAAJiUQkyESJ+EQp8EQPtiwDRIn4Qf/HRIgsA+nY
BAAAQSnDQSnCidBmwegFZinCZomW4AEAAOkRAQAAQSnDQSnCidBmwegFZinCQYH7////AGaJlpgBAAB3
Gkw55w+EtQQAAA+2B0HB4ghBweMISP/HQQnCD7eWsAEAAESJ2MHoCw+3yg+vwUE5wnMgQYnDuAAIAAAp
yMH4BY0EAmaJhrABAACLRCTE6ZgAAABBKcNBKcKJ0GbB6AVmKcJBgfv///8AZomWsAEAAHcaTDnnD4RE
BAAAD7YHQcHiCEHB4whI/8dBCcIPt5bIAQAARInYwegLD7fKD6/BQTnCcx1BicO4AAgAACnIwfgFjQQC
ZomGyAEAAItEJMDrIkEpw0EpwonQZsHoBWYpwotEJLxmiZbIAQAAi1QkwIlUJLyLTCTEiUwkwESJdCTE
QYnGMcCDfCTIBkyLTCTYD5/ASYHBaAoAAI1EQAiJRCTIQYH7////AHcaTDnnD4ScAwAAD7YHQcHiCEHB
4whI/8dBCcJBD7cRRInYwegLD7fKD6/BQTnCcydBicO4AAgAAEUx7SnIwfgFjQQCZkGJAUhjRCS4SMHg
BE2NRAEE63hBKcNBKcKJ0GbB6AVmKcJBgfv///8AZkGJEXcaTDnnD4QqAwAAD7YHQcHiCEHB4whI/8dB
CcJBD7dRAkSJ2MHoCw+3yg+vwUE5wnM0QYnDuAAIAABBvQgAAAApyMH4BY0EAmZBiUECSGNEJLhIweAE
TY2EAQQBAABBuQMAAADrJ0Epw0EpwonQZsHoBU2NgQQCAABBvRAAAABmKcJmQYlRAkG5CAAAAESJy70B
AAAASGPFQYH7////AEmNNEB3Gkw55w+EhwIAAA+2B0HB4ghBweMISP/HQQnCD7cORInYwegLD7fRD6/C
QTnCcxdBicO4AAgAAAHtKdDB+AWNBAFmiQbrFkEpw0EpwonIZsHoBY1sLQFmKcFmiQ7/y3WRuAEAAABE
icnT4CnFRAHtg3wkyAMPj8IBAACDRCTIB7gDAAAAg/0ED0zFSItcJNhBuAEAAABImEjB4AdMjYwDYAMA
ALsGAAAASWPAQYH7////AEmNNEF3Gkw55w+E0AEAAA+2B0HB4ghBweMISP/HQQnCD7cWRInYwegLD7fK
D6/BQTnCcxhBicO4AAgAAEUBwCnIwfgFjQQCZokG6xdBKcNBKcKJ0GbB6AVHjUQAAWYpwmaJFv/LdY9B
g+hAQYP4A0WJxg+ODQEAAEGD5gFEicDR+EGDzgJBg/gNjXD/fyOJ8UiLXCTYSWPAQdPmSAHARInySI0U
U0gpwkyNil4FAADrUY1w+0GB+////wB3Gkw55w+EGQEAAA+2B0HB4ghBweMISP/HQQnCQdHrRQH2RTna
cgdFKdpBg84B/851x0yLTCTYQcHmBL4EAAAASYHBRAYAAEG9AQAAALsBAAAASGPDQYH7////AE2NBEF3
Gkw55w+EuQAAAA+2B0HB4ghBweMISP/HQQnCQQ+3EESJ2MHoCw+3yg+vwUE5wnMYQYnDuAAIAAAB2ynI
wfgFjQQCZkGJAOsaQSnDQSnCidBmwegFjVwbAUUJ7mYpwmZBiRBFAe3/znWIQf/GdECDxQJFOf53TUiL
VCToRIn4RCnwRA+2LAJEifhB/8f/zUSILAIPlcIxwEQ7fCTkD5LAhcJ100Q7fCTkD4JF9///QYH7////
AHcWTDnnuAEAAAB0I+sHuAEAAADrGkj/x4n4K0Qk+EiLTCTwSItcJDiJAUSJOzHAW11BXEFdQV5BX0iL
dfhIi30Qi0sESAHOixNIAdfJ6wJXXllIifBIKchaSCnXWYk5W13DaB4AAABa6MUAAABQUk9UX0VYRUN8
UFJPVF9XUklURSBmYWlsZWQuCgAKACRJbmZvOiBUaGlzIGZpbGUgaXMgcGFja2VkIHdpdGggdGhlIFVQ
WCBleGVjdXRhYmxlIHBhY2tlciBodHRwOi8vdXB4LnNmLm5ldCAkCgAkSWQ6IFVQWCA0LjAxIENvcHly
aWdodCAoQykgMTk5Ni0yMDIyIHRoZSBVUFggVGVhbS4gQWxsIFJpZ2h0cyBSZXNlcnZlZC4gJAoAkJCQ
ag5aV17rAV5qAl9qAVgPBWp/X2o8WA8FXyn2agJYDwWFwHjcUEiNtw8AAACtg+D+QYnGVluLFkiNjfX/
//9EizlMKflFKfdJAc5fUlBXUU0pyUGDyP9qIkFaUl5qA1op/2oJWA8FSIlEJBBQWlNerVBIieFJidWt
UK1BkEiJ917/1VlIi3QkGEiLfCQQagVaagpYDwVB/+Vd6Hr///8vcHJvYy9zZWxmL2V4ZQAAAQAAiggA
AIYGAAAOSQEAGgMAdBJ8Ggg2Ct9V9xgLKdkVSgc8lNrznlW1S45V2wl+X5UE/Md+tlQh0J2Q78Q0UpLE
kvMkEVOMvrWYHeWKwfCWH8VCvgC1J42rmOBud3GA7U8RabBaL9g6qcTHce3S8gKIFvfSA/cKOO+HXIuN
UdCDmrOa8ymHgcDoY340fNMBlzyOpUahlOIUj3wqfUmOmu0vq47s0wfaO5P0RssjvGN4xBPwg7YYM5aJ
ICKBEs+R93MkFN6KKj6VTMAsaSz4iVWXIu4K7rTy7/Wp7aArygughxW4PhrKLtAeCykomF+nXLyw9jIi
wGuT7gfvLDfIxJ91u/oQDEtq2B2Jg2GXeJRyiyj1uhTWkU58jq6F3M7XLUwNobzhFMZ2odgA0cu00VTv
aIdI9tLd62JQVDv+bEq/vBnLuDPrSzAYp4T7MQGqS5VBulBhryaxzRo3OU5npumW9RrgqWXV0NudUk/A
sMGz59quhLszskP+uQKQ9usm/Dybh5NBaRpmBK/whjPXuPeasCqosawPQMl3O/rl8wvSDQbbbJ1QE4lO
esdTtKiSjceNpXMM0cRwi4wzUUkJYEGz+FdM1lNFH/ddg8T5Ntt8qJa865ElSoT8BG0dd458cE1irdpS
iKZmploA22mw245aGY5uyWZ4rpZz9T9Pf0F3GosTDWiOFewCXnj+E83GqhKw7k7sP3IGYiyGGCb0cY8U
PZCR///kvVH/+1+i/sHIJejQHJtQ/hvfxW75xK+QIsjghCJPWJQM73F0SipRjCydGR8G2HCjXKQoc+9Z
8bIIecaVO4YpijXy3DrwYudwDktgQbRfds+sZf9Djx9ThozAFWrYn+ZmED9pwWChkQbKsT++Cv8vdij6
iguajUzjRCv5y4hGuPhTYsc2S3MSmkOGpyfu1a9XwLY/ZHiAm8fFbUR6MfdKXwA/8sAU1mmPhE04OGxS
sHLDV77RgxvSDue+rnrux8Zv6C67+nPck9oYYFh+fMhVrxD4r1wt+KAIB6M8GJVMVKmw+p3DzIOdyMff
mqIBB85egNwWV6okzn7wfWb2MyvNMOjQ6zm5JYZQ7SFihQeOmTmuYXLep1Y4ootMzk5cdaGeVbKqVdFT
kodVQ6cWElGzfIwM4rHT9FvYnjpRX+SXPO9v5qJ4trr97K0cb4/GKdak6xt1TJWgtbchLe9hwTIklezn
YFed0xE8sWIvLhVuYzlh3Pmf8pKGXxHpjBD7nItCfJtXEU44JigeMtfOKMuabQ0JXGnw7+jb3EIsYglZ
NgyLI5Dnq/49+oVPrbYKxnIjKWXnxEwehTGRF+4+WV/lq1G81IJFZ9WUrK1maDJxF4YHWvbFN7z8METG
gMITIbw6HYCSsjdDFrKX8StYFrnB+F4sBbzkJj39nU6ELR5FQLIq+oGCY7XtqZuiYmPttuNz33+EbrVJ
xVFf9DAF8aEt2ID6JXw5pzZb+YdkVl//Fk8t389P2h/inlKntamGTwaZ87fEi7+oJMmLxZsBSOtiztMx
UGioSbuKcoxwm5w0glzyCS1q4yDMazPcbfhNZYiOAlBXIc782gsmBXEW+7FldrN3Aay/+HhGqMKWlxVr
J+/S3Z/jmU0XC7PuO3Pl0nXGihButJ9RHZxVLZIbAYloM42FJGy6JCzHgAiU7+91p505cKnuZCiASNpg
MuFBZ/LBuRL0iz2Kyc3znZFuUcq1XvxEdJKHvPuxMwrlVMasLJet50rdt3EJCvc02OMWUaITg6Ft+oBs
6o9Z+Nzryr8ILu7UfUUm74lcKhcHZfLrf95IF0wGtS/NuBXmoiUgvcdKT+O9xcF1qpLCWWGZ9/xNvzQM
pTYYYN6HpuoABn9kBjLdrzca2NvHt7cMXc6eKc9C4Z63VrKb79vxvDAKhyT1AmGLTNLpvVLV3yxO0cgG
l/DnIteJhZ2s37KoReDkoXQl/kT6EiXpj7N2Zf6ueJOpiuQGGPH6+8EK9lYA7hTXW/mw96pMXS5Ukcl7
i0bddV1a2wAtxgQU48UsbUg7oSgCQDxsmpt8Ke6WJCi+14qpfPMGd6h74A/msBUzct7bWqlgLRgGBK/7
N7tI/KmpKfUZbjLFAi3C5GT6X8sBzI2C3YG0K72Cg4syBi80tB1qCVxhvumU8kSAN5CuNty70VhezdDn
RwZlMug5emzmKJ/AQ76G/W9ipGhW7azivTBOQfpmNF42IXAkagjH0yX7a1TArVr7eYhFUe3ZHI2Z5bIA
IA4AABwAAAAOAAAAGgMAAG/9//+jt/9HPkgVcjlhUbiSKOZt6fmQAMoGAAATAAAADgAAABoDAABv/f//
o7f/Rz5IBErWWQAQAgAACwAAAA4AAAAaAwAAb/3/QuXwANAIAAABAgAADgAAABoDACOQ7HQgFTs34gg2
Rv83Mg7hHhkJdcrKX1Adze79eb6wXGmxn2jnXiE2D1MkDTW7KPHYBkuDGatwO9oRoNx8dFLx+j13RkTD
2HHB5wFw/0ZkuKunUNOGxn2Tzuboa3fydNBhWwh2EeIThtzyorxSgOgX/mdotvYqHBFbROnPJj92yrwQ
9ouY+0pMcU4+ovAug/raL8TwRBQLOPWe/qDg2tP2+/MiprOkbF713cUfkx0fZuJlfTkUfrlbT7QGwTH/
4shLmzXGjII9ZN5L77Yknvd1ccIj415c2ctQkjhPekgRa6G0Df88XJF9zYTEVUKBIleqTBUhaEROmsX6
g4X6khEQFpj6hwQUIGnvkBXnFIJhE1Rq8iteCySmqEcu9BiJc6fLLe2pa1pT8Tfl577E4+R04gSdNyM4
jB2mlFsyF8xtZ9gCcYGZn8moRSQubJ1HhrNgapl1Jt1Evs4ldvGBssZNPP6abMBxlG3eqseCG8ixxtF5
qhGnYvPZteuc2RjZZ/+iaKVad8cwa/61C3ndIMGO00/8l4UZbUyhWApQOxPtWGn97923+u0ZaEVzctYz
xWNeRB4Q43chEqUNMl1PpaJAv5crDwKv5S63K9BQtMAupgmNGi8e2H6fVunY/3KasR7g+MFHmlZvHjCs
/c+i+FSovxqK8OggRka6syYnfwAAAABVUFghAAAAAABVUFghDhYOCmjQpkVJQV4u0AgAAAECAADwqAAA
SQEAUPQAAAA=
";
0