Java虚拟机体系结构

转自：http://www.cnblogs.com/java-my-life/archive/2012/08/01/2615221.html

JAVA虚拟机的生命周期

　　一个运行时的Java虚拟机实例的天职是：负责运行一个java程序。当启动一个Java程序时，一个虚拟机实例也就诞生了。当该程序关闭退出，这个虚拟机实例也就随之消亡。如果同一台计算机上同时运行三个Java程序，将得到三个Java虚拟机实例。每个Java程序都运行于它自己的Java虚拟机实例中。

　　Java虚拟机实例通过调用某个初始类的main()方法来运行一个Java程序。而这个main()方法必须是共有的(public)、静态的(static)、返回值为void，并且接受一个字符串数组作为参数。任何拥有这样一个main()方法的类都可以作为Java程序运行的起点。

public class Test {

    public static void main(String[] args) {
        // TODO Auto-generated method stub
        System.out.println("Hello World");
    }

}

　　在上面的例子中，Java程序初始类中的main()方法，将作为该程序初始线程的起点，任何其他的线程都是由这个初始线程启动的。

　　在Java虚拟机内部有两种线程：守护线程和非守护线程。守护线程通常是由虚拟机自己使用的，比如执行垃圾收集任务的线程。但是，Java程序也可以把它创建的任何线程标记为守护线程。而Java程序中的初始线程——就是开始于main()的那个，是非守护线程。

　　只要还有任何非守护线程在运行，那么这个Java程序也在继续运行。当该程序中所有的非守护线程都终止时，虚拟机实例将自动退出。假若安全管理器允许，程序本身也能够通过调用Runtime类或者System类的exit()方法来退出。

JAVA虚拟机的体系结构

　　下图是JAVA虚拟机的结构图，每个Java虚拟机都有一个类装载子系统，它根据给定的全限定名来装入类型（类或接口）。同样，每个Java虚拟机都有一个执行引擎，它负责执行那些包含在被装载类的方法中的指令。

　　

　　当JAVA虚拟机运行一个程序时，它需要内存来存储许多东西，例如：字节码、从已装载的class文件中得到的其他信息、程序创建的对象、传递给方法的参数，返回值、局部变量等等。Java虚拟机把这些东西都组织到几个“运行时数据区”中，以便于管理。

　　某些运行时数据区是由程序中所有线程共享的，还有一些则只能由一个线程拥有。每个Java虚拟机实例都有一个方法区以及一个堆，它们是由该虚拟机实例中所有的线程共享的。当虚拟机装载一个class文件时，它会从这个class文件包含的二进制数据中解析类型信息，然后把这些类型信息放到方法区中，当程序运行时，虚拟机会把所有该程序在运行时创建的对象都放到堆中。

　　

　　当每一个新线程被创建时，它都将得到它自己的PC寄存器（程序计数器）以及一个Java栈，如果线程正在执行的是一个Java方法（非本地方法），那么PC寄存器的值将总是指向下一条将被执行的指令，而它的Java栈则总是存储该线程中Java方法调用的状态——包括它的局部变量，被调用时传进来的参数、返回值，以及运算的中间结果等等。而本地方法调用的状态，则是以某种依赖于具体实现的方法存储在本地方法栈中，也可能是在寄存器或者其他某些与特定实现相关的内存区中。

　　Java栈是由许多栈帧（stack frame）组成的，一个栈帧包含一个Java方法调用的状态。当线程调用一个Java方法时，虚拟机压入一个新的栈帧到该线程的Java栈中，当该方法返回时，这个栈帧被从Java栈中弹出并抛弃。

　　Java虚拟机没有寄存器，其指令集使用Java栈来存储中间数据。这样设计的原因是为了保持Java虚拟机的指令集尽量紧凑、同时也便于Java虚拟机在那些只有很少通用寄存器的平台上实现。另外，Java虚拟机这种基于栈的体系结构，也有助于运行时某些虚拟机实现的动态编译器和即时编译器的代码优化。

　　下图描绘了Java虚拟机为每一个线程创建的内存区，这些内存区域是私有的，任何线程都不能访问另一个线程的PC寄存器或者Java栈。

　　

　　上图展示了一个虚拟机实例的快照，它有三个线程正在执行。线程1和线程2都是正在执行的Java方法，而线程3则正在执行的另一个本地方法。

　　Java栈都是向下生长的，而栈顶都显示在图的底部。当前正在执行方法的栈帧则以浅色表示，对于一个正在运行Java方法的线程而言，它的PC寄存器总是指向下一条将被执行的指令。比如线程1和线程2都是以浅色显示的，由于线程3表示当前正在执行的一个本地方法，因此，它的PC寄存器——以深色显示的那个，其值是不确定的。

数据类型

　　Java虚拟机是通过某些数据类型来执行计算的，数据类型可以分为两种：基本类型和引用类型，基本类型的变量持有原始值，而引用类型的变量持有引用值。

　　

　　Java语言中的所有基本类型同样也都是Java虚拟机中的基本类型。但是boolean有点特别，虽然Java虚拟机也把boolean看做基本类型，但是指令集对boolean只有很有限的支持，当编译器把Java源代码编译为字节码时，它会用int或者byte来表示boolean。在Java虚拟机中，false是由整数零来表示的，所有非零整数都表示true，涉及boolean值的操作则会使用int。另外，boolean数组是当做byte数组来访问的，但是在“堆”区，它也可以被表示为位域。

　　Java虚拟机还有一个只在内部使用的基本类型：returnAddress，Java程序员不能使用这个类型，这个基本类型被用来实现Java程序中的finally子句。该类型是jsr, ret以及jsr_w指令需要使用到的，它的值是JVM指令的操作码的指针。returnAddress类型不是简单意义上的数值，不属于任何一种基本类型，并且它的值是不能被运行中的程序所修改的。

　　Java虚拟机的引用类型被统称为“引用（reference）”，有三种引用类型：类类型、接口类型、以及数组类型，它们的值都是对动态创建对象的引用。类类型的值是对类实例的引用；数组类型的值是对数组对象的引用，在Java虚拟机中，数组是个真正的对象；而接口类型的值，则是对实现了该接口的某个类实例的引用。还有一种特殊的引用值是null，它表示该引用变量没有引用任何对象。

　　JAVA中方法参数的引用传递

　　java中参数的传递有两种，分别是按值传递和按引用传递。按值传递不必多说，下面就说一下按引用传递。

　　“当一个对象被当作参数传递到一个方法”，这就是所谓的按引用传递。

public class User {

    private String name;

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

}

public class Test {

    public void set(User user){
        user.setName("hello world");
    }

    public static void main(String[] args) {

        Test test = new Test();
        User user = new User();
        test.set(user);
        System.out.println(user.getName());
    }
}

　　上面代码的输出结果是“hello world”，这不必多说，那如果将set方法改为如下，结果会是多少呢？

    public void set(User user){
        user.setName("hello world");
        user = new User();
        user.setName("change");
    }

　　答案依然是“hello world”，下面就让我们来分析一下如上代码。

　　首先

User user = new User();

　　是在堆中创建了一个对象，并在栈中创建了一个引用，此引用指向该对象，如下图：

test.set(user);

　　是将引用user作为参数传递到set方法，注意：这里传递的并不是引用本身，而是一个引用的拷贝。也就是说这时有两个引用（引用和引用的拷贝）同时指向堆中的对象，如下图：

user.setName("hello world");

　　在set()方法中，“user引用的拷贝”操作堆中的User对象，给name属性设置字符串"hello world"。如下图：

　　

user = new User();

　　在set()方法中，又创建了一个User对象，并将“user引用的拷贝”指向这个在堆中新创建的对象，如下图：

　　

user.setName("change");

　　在set()方法中，“user引用的拷贝”操作的是堆中新创建的User对象。

　　set()方法执行完毕，目光再回到mian()方法

System.out.println(user.getName());

　　因为之前，"user引用的拷贝"已经将堆中的User对象的name属性设置为了"hello world"，所以当main()方法中的user调用getName()时，打印的结果就是"hello world"。如下图：

　　

类装载子系统

　　在JAVA虚拟机中，负责查找并装载类型的那部分被称为类装载子系统。

　　JAVA虚拟机有两种类装载器：启动类装载器和用户自定义类装载器。前者是JAVA虚拟机实现的一部分，后者则是Java程序的一部分。由不同的类装载器装载的类将被放在虚拟机内部的不同命名空间中。

　　类装载器子系统涉及Java虚拟机的其他几个组成部分，以及几个来自java.lang库的类。比如，用户自定义的类装载器是普通的Java对象，它的类必须派生自java.lang.ClassLoader类。ClassLoader中定义的方法为程序提供了访问类装载器机制的接口。此外，对于每一个被装载的类型，JAVA虚拟机都会为它创建一个java.lang.Class类的实例来代表该类型。和所有其他对象一样，用户自定义的类装载器以及Class类的实例都放在内存中的堆区，而装载的类型信息则都位于方法区。

　　类装载器子系统除了要定位和导入二进制class文件外，还必须负责验证被导入类的正确性，为类变量分配并初始化内存，以及帮助解析符号引用。这些动作必须严格按以下顺序进行：

　　（1）装载——查找并装载类型的二进制数据。

　　（2）连接——指向验证、准备、以及解析（可选）。

　　　　●　验证　　确保被导入类型的正确性。

　　　　●　准备　　为类变量分配内存，并将其初始化为默认值。

　　　　●　解析　　把类型中的符号引用转换为直接引用。

　　（3）初始化——把类变量初始化为正确初始值。

　　每个JAVA虚拟机实现都必须有一个启动类装载器，它知道怎么装载受信任的类。

　　每个类装载器都有自己的命名空间，其中维护着由它装载的类型。所以一个Java程序可以多次装载具有同一个全限定名的多个类型。这样一个类型的全限定名就不足以确定在一个Java虚拟机中的唯一性。因此，当多个类装载器都装载了同名的类型时，为了惟一地标识该类型，还要在类型名称前加上装载该类型（指出它所位于的命名空间）的类装载器标识。

　方法区

　　在Java虚拟机中，关于被装载类型的信息存储在一个逻辑上被称为方法区的内存中。当虚拟机装载某个类型时，它使用类装载器定位相应的class文件，然后读入这个class文件——1个线性二进制数据流，然后它传输到虚拟机中，紧接着虚拟机提取其中的类型信息，并将这些信息存储到方法区。该类型中的类（静态）变量同样也是存储在方法区中。

　　JAVA虚拟机在内部如何存储类型信息，这是由具体实现的设计者来决定的。

　　当虚拟机运行Java程序时，它会查找使用存储在方法区中的类型信息。由于所有线程都共享方法区，因此它们对方法区数据的访问必须被设计为是线程安全的。比如，假设同时有两个线程都企图访问一个名为Lava的类，而这个类还没有被装入虚拟机，那么，这时只应该有一个线程去装载它，而另一个线程则只能等待。

　　对于每个装载的类型，虚拟机都会在方法区中存储以下类型信息：

　　●　这个类型的全限定名

　　●　这个类型的直接超类的全限定名（除非这个类型是java.lang.Object，它没有超类）

　　●　这个类型是类类型还是接口类型

　　●　这个类型的访问修饰符（public、abstract或final的某个子集）

　　●　任何直接超接口的全限定名的有序列表

　　除了上面列出的基本类型信息外，虚拟机还得为每个被装载的类型存储以下信息：

　　●　该类型的常量池

　　●　字段信息

　　●　方法信息

　　●　除了常量以外的所有类（静态）变量

　　●　一个到类ClassLoader的引用

　　●　一个到Class类的引用

　　常量池

　　虚拟机必须为每个被装载的类型维护一个常量池。常量池就是该类型所用常量的一个有序集合，包括直接常量和对其他类型、字段和方法的符号引用。池中的数据项就像数组一样是通过索引访问的。因为常量池存储了相应类型所用到的所有类型、字段和方法的符号引用，所以它在Java程序的动态连接中起着核心的作用。

　　字段信息

　　对于类型中声明的每一个字段。方法区中必须保存下面的信息。除此之外，这些字段在类或者接口中的声明顺序也必须保存。

　　○　字段名

　　○　字段的类型

　　○　字段的修饰符（public、private、protected、static、final、volatile、transient的某个子集）

　　方法信息

　　对于类型中声明的每一个方法，方法区中必须保存下面的信息。和字段一样，这些方法在类或者接口中的声明顺序也必须保存。

　　○　方法名

　　○　方法的返回类型（或void）

　　○　方法参数的数量和类型（按声明顺序）

　　○　方法的修饰符（public、private、protected、static、final、synchronized、native、abstract的某个子集）

　　除了上面清单中列出的条目之外，如果某个方法不是抽象的和本地的，它还必须保存下列信息：

　　○　方法的字节码（bytecodes）

　　○　操作数栈和该方法的栈帧中的局部变量区的大小

　　○　异常表

　　类（静态）变量

　　类变量是由所有类实例共享的，但是即使没有任何类实例，它也可以被访问。这些变量只与类有关——而非类的实例，因此它们总是作为类型信息的一部分而存储在方法区。除了在类中声明的编译时常量外，虚拟机在使用某个类之前，必须在方法区中为这些类变量分配空间。

　　而编译时常量（就是那些用final声明以及用编译时已知的值初始化的类变量）则和一般的类变量处理方式不同，每个使用编译时常量的类型都会复制它的所有常量到自己的常量池中，或嵌入到它的字节码流中。作为常量池或字节码流的一部分，编译时常量保存在方法区中——就和一般的类变量一样。但是当一般的类变量作为声明它们的类型的一部分数据面保存的时候，编译时常量作为使用它们的类型的一部分而保存。

　　指向ClassLoader类的引用

　　每个类型被装载的时候，虚拟机必须跟踪它是由启动类装载器还是由用户自定义类装载器装载的。如果是用户自定义类装载器装载的，那么虚拟机必须在类型信息中存储对该装载器的引用。这是作为方法表中的类型数据的一部分保存的。

　　虚拟机会在动态连接期间使用这个信息。当某个类型引用另一个类型的时候，虚拟机会请求装载发起引用类型的类装载器来装载被引用的类型。这个动态连接的过程，对于虚拟机分离命名空间的方式也是至关重要的。为了能够正确地执行动态连接以及维护多个命名空间，虚拟机需要在方法表中得知每个类都是由哪个类装载器装载的。

　　指向Class类的引用

　　对于每一个被装载的类型（不管是类还是接口），虚拟机都会相应地为它创建一个java.lang.Class类的实例，而且虚拟机还必须以某种方式把这个实例和存储在方法区中的类型数据关联起来。

　　在Java程序中，你可以得到并使用指向Class对象的引用。Class类中的一个静态方法可以让用户得到任何已装载的类的Class实例的引用。

public static Class<?> forName(String className)

　　比如，如果调用forName("java.lang.Object")，那么将得到一个代表java.lang.Object的Class对象的引用。可以使用forName()来得到代表任何包中任何类型的Class对象的引用，只要这个类型可以被（或者已经被）装载到当前命名空间中。如果虚拟机无法把请求的类型装载到当前命名空间，那么会抛出ClassNotFoundException异常。

　　另一个得到Class对象引用的方法是，可以调用任何对象引用的getClass()方法。这个方法被来自Object类本身的所有对象继承：

public final native Class<?> getClass();

　　比如，如果你有一个到java.lang.Integer类的对象的引用，那么你只需简单地调用Integer对象引用的getClass()方法，就可以得到表示java.lang.Integer类的Class对象。

　　方法区使用实例

　　为了展示虚拟机如何使用方法区中的信息，下面来举例说明：

class Lava {

    private int speed = 5;
    void flow(){

    }
}

public class Volcano {

    public static void main(String[] args){
        Lava lava = new Lava();
        lava.flow();
    }
}

　　不同的虚拟机实现可能会用完全不同的方法来操作，下面描述的只是其中一种可能——但并不是仅有的一种。

　　要运行Volcano程序，首先得以某种“依赖于实现的”方式告诉虚拟机“Volcano”这个名字。之后，虚拟机将找到并读入相应的class文件“Volcano.class”，然后它会从导入的class文件里的二进制数据中提取类型信息并放到方法区中。通过执行保存在方法区中的字节码，虚拟机开始执行main()方法，在执行时，它会一直持有指向当前类（Volcano类）的常量池（方法区中的一个数据结构）的指针。

　　注意：虚拟机开始执行Volcano类中main()方法的字节码的时候，尽管Lava类还没被装载，但是和大多数（也许所有）虚拟机实现一样，它不会等到把程序中用到的所有类都装载后才开始运行。恰好相反，它只会需要时才装载相应的类。

　　main()的第一条指令告知虚拟机为列在常量池第一项的类分配足够的内存。所以虚拟机使用指向Volcano常量池的指针找到第一项，发现它是一个对Lava类的符号引用，然后它就检查方法区，看Lava类是否已经被加载了。

　　这个符号引用仅仅是一个给出了类Lava的全限定名“Lava”的字符串。为了能让虚拟机尽可能快地从一个名称找到类，虚拟机的设计者应当选择最佳的数据结构和算法。

　　当虚拟机发现还没有装载过名为“Lava”的类时，它就开始查找并装载文件“Lava.class”，并把从读入的二进制数据中提取的类型信息放在方法区中。

　　紧接着，虚拟机以一个直接指向方法区Lava类数据的指针来替换常量池第一项（就是那个字符串“Lava”），以后就可以用这个指针来快速地访问Lava类了。这个替换过程称为常量池解析，即把常量池中的符号引用替换为直接引用。

　　终于，虚拟机准备为一个新的Lava对象分配内存。此时它又需要方法区中的信息。还记得刚刚放到Volcano类常量池第一项的指针吗？现在虚拟机用它来访问Lava类型信息，找出其中记录的这样一条信息：一个Lava对象需要分配多少堆空间。

　　JAVA虚拟机总能够通过存储与方法区的类型信息来确定一个对象需要多少内存，当JAVA虚拟机确定了一个Lava对象的大小后，它就在堆上分配这么大的空间，并把这个对象实例的变量speed初始化为默认初始值0。

　　当把新生成的Lava对象的引用压到栈中，main()方法的第一条指令也完成了。接下来的指令通过这个引用调用Java代码（该代码把speed变量初始化为正确初始值5）。另一条指令将用这个引用调用Lava对象引用的flow()方法。

　堆

　　Java程序在运行时创建的所有类实例或数组都放在同一个堆中。而一个JAVA虚拟机实例中只存在一个堆空间，因此所有线程都将共享这个堆。又由于一个Java程序独占一个JAVA虚拟机实例，因而每个Java程序都有它自己的堆空间——它们不会彼此干扰。但是同一个Java程序的多个线程却共享着同一个堆空间，在这种情况下，就得考虑多线程访问对象（堆数据）的同步问题了。

　　JAVA虚拟机有一条在堆中分配新对象的指令，却没有释放内存的指令，正如你无法用Java代码区明确释放一个对象一样。虚拟机自己负责决定如何以及何时释放不再被运行的程序引用的对象所占据的内存。通常，虚拟机把这个任务交给垃圾收集器。

　　数组的内部表示

　　在Java中，数组是真正的对象。和其他对象一样，数组总是存储在堆中。同样，数组也拥有一个与它们的类相关联的Class实例，所有具有相同维度和类型的数组都是同一个类的实例，而不管数组的长度（多维数组每一维的长度）是多少。例如一个包含3个int整数的数组和一个包含300个整数的数组拥有同一个类。数组的长度只与实例数据有关。

　　数组类的名称由两部分组成：每一维用一个方括号“[”表示，用字符或字符串表示元素类型。比如，元素类型为int整数的、一维数组的类名为“[I”，元素类型为byte的三维数组为“[[[B”，元素类型为Object的二维数组为“[[Ljava/lang/Object”。

　　多维数组被表示为数组的数组。比如，int类型的二维数组，将表示为一个一维数组，其中的每一个元素是一个一维int数组的引用，如下图：

　　aaarticlea/png;base64,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" alt="" />

　　在堆中的每个数组对象还必须保存的数据时数组的长度、数组数据，以及某些指向数组的类数据的引用。虚拟机必须能够通过一个数组对象的引用得到此数组的长度，通过索引访问其元素（期间要检查数组边界是否越界），调用所有数组的直接超类Object声明的方法等等。

　程序计数器

　　对于一个运行中的Java程序而言，其中的每一个线程都有它自己的PC（程序计数器）寄存器，它是在该线程启动时创建的，PC寄存器的大小是一个字长，因此它既能够持有一个本地指针，也能够持有一个returnAddress。当线程执行某个Java方法时，PC寄存器的内容总是下一条将被执行指令的“地址”，这里的“地址”可以是一个本地指针，也可以是在方法字节码中相对于该方法起始指令的偏移量。如果该线程正在执行一个本地方法，那么此时PC寄存器的值是“undefined”。

　Java栈

　　每当启动一个新线程时，Java虚拟机都会为它分配一个Java栈。Java栈以帧为单位保存线程的运行状态。虚拟机只会直接对Java栈执行两种操作：以帧为单位的压栈和出栈。

　　某个线程正在执行的方法被称为该线程的当前方法，当前方法使用的栈帧称为当前帧，当前方法所属的类称为当前类，当前类的常量池称为当前常量池。在线程执行一个方法时，它会跟踪当前类和当前常量池。此外，当虚拟机遇到栈内操作指令时，它对当前帧内数据执行操作。

　　每当线程调用一个Java方法时，虚拟机都会在该线程的Java栈中压入一个新帧。而这个新帧自然就成为了当前帧。在执行这个方法时，它使用这个帧来存储参数、局部变量、中间运算结果等数据。

　　Java方法可以以两种方式完成。一种通过return返回的，称为正常返回；一种是通过抛出异常而异常终止的。不管以哪种方式返回，虚拟机都会将当前帧弹出Java栈然后释放掉，这样上一个方法的帧就成为当前帧了。

　　Java帧上的所有数据都是此线程私有的。任何线程都不能访问另一个线程的栈数据，因此我们不需要考虑多线程情况下栈数据的访问同步问题。当一个线程调用一个方法时，方法的的局部变量保存在调用线程Java栈的帧中。只有一个线程能总是访问那些局部变量，即调用方法的线程。

　本地方法栈

　　前面提到的所有运行时数据区都是Java虚拟机规范中明确定义的，除此之外，对于一个运行中的Java程序而言，它还可能会用到一些跟本地方法相关的数据区。当某个线程调用一个本地方法时，它就进入了一个全新的并且不再受虚拟机限制的世界。本地方法可以通过本地方法接口来访问虚拟机的运行时数据区，但不止如此，它还可以做任何它想做的事情。

　　本地方法本质上时依赖于实现的，虚拟机实现的设计者们可以自由地决定使用怎样的机制来让Java程序调用本地方法。

　　任何本地方法接口都会使用某种本地方法栈。当线程调用Java方法时，虚拟机会创建一个新的栈帧并压入Java栈。然而当它调用的是本地方法时，虚拟机会保持Java栈不变，不再在线程的Java栈中压入新的帧，虚拟机只是简单地动态连接并直接调用指定的本地方法。

　　如果某个虚拟机实现的本地方法接口是使用C连接模型的话，那么它的本地方法栈就是C栈。当C程序调用一个C函数时，其栈操作都是确定的。传递给该函数的参数以某个确定的顺序压入栈，它的返回值也以确定的方式传回调用者。同样，这就是虚拟机实现中本地方法栈的行为。

　　很可能本地方法接口需要回调Java虚拟机中的Java方法，在这种情况下，该线程会保存本地方法栈的状态并进入到另一个Java栈。

　　下图描绘了这样一个情景，就是当一个线程调用一个本地方法时，本地方法又回调虚拟机中的另一个Java方法。这幅图展示了JAVA虚拟机内部线程运行的全景图。一个线程可能在整个生命周期中都执行Java方法，操作它的Java栈；或者它可能毫无障碍地在Java栈和本地方法栈之间跳转。　　aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAn4AAAGvCAIAAABKOE8gAAAgAElEQVR4nO29f3AU933/f/9a/0SZQZ5JnHHCSVu3bpnWieOT8MZZIFVbSZis0qlUxVJxVjM1SsACX6gtAwYlB0rAApxNJlZsa+wrIyf418UwuHLg4EPAITmGmoaGC7WN+HFCDnLAZ9dW3Ga/f7x67++b3feuTvfjfbvH8zHv0Zz29nb3ve+712PfP/a9IQsAAAAAEglV+gAAAACA6wuoFwAAAJAK1AsAAABIBeoFAAAApAL1AgAAAFKBegEAAACpQL0AAACAVKBeAAAAQCpQLwAAACAVqBcAAACQCtQLAAAASAXqBQAAAKQC9VaYbDabyWRKsqlkMlmS7QA/U8IvTGGk0+kK7r1MpFKpUm1KTungxx50oN4KE4vFFEWJxWJz+pSu687fnqqqqqrG4/FsNpvndjKZjGEYtHePH7Mz2iYSiUQiwS/Jf6f8Zm0b8SAWiwU03KiqOqfyjcfjHjlNpVKKohiGMdcTnslkdF0vXgzsa5bn+slk0sPWqqoahjHXozIMY06fSqVS3gesKIqu6yURsKqquq57X6CkUim3c6goSj7n1q0UCggmoCJAvRVGUZRQKGQYRv4fyWQy9ClbpIhGo6FQyDRNXddVVTVN020L6XTaNE1VVWk7iqJkMhn6Mccc0Gq2faXTaYpWTACxWEzXdefHCTok22GkUqlQKKTmRygUCoVCQbRvMpmkk5xnfZHW9/hKKIriPJkexONxXdeprHVdz/+DQqgs8v/GxmIxj/3St2uuNelsNqsoSp6WYuurquq2I+GXvDDoZxiNRj3WMU2Tvvm25VT0+XzPqRScv3Eq5Xg8Ttc0Qfy9XCdAvZWERaU5RR/6lPPalpZT+KBfpu23TfUeJQcFiFQqxT5Cl8w2aGXnbzgej/O7oL1Ho1H2Kd7EtDtbHZfUy46BoM3aFlJVb06+8RUUjvPXnreuZq3ZpFKpWCxmGAYraKoox2IxKmvnx+PxeJ7ioa9W/paivPBFz9dW6VuX56Z4EokE5SvP9dkFkPBdurzz+HgsFuMPOx6PuxUB/zN0g4rG2W5hGIbwpy08YOFe2M+ELqZLcrEFygHUWzHYlXsmk6E6aJ4f5CXEC9v2mxcGNRY+nAHCLQh6BEf6bdMxCPfODk+4EVKvLdAIF1pzr+r5CmqoEIZUwzDcGh7pjDnb5G2bcra70uUOXbKQ9W27po3bGhXoqzhrXjzUK/y48JvGmmQLVi/bjnN5PB4XVsp1XaevK2HblPe3i46Tv2x1c6SHetlO+fo6f1HLCn1WZlWvlfvWFXx6QVmBeiuG7Qp31h8/QZVCCsfxeJz/Ddt+89Qm7NYiVxL1JhIJ1rDmJn46gDKpN5FIkGaEHZ+szu3slqblbm3ybu+6bZDfphtU6XQupCDuLKZ4PE57UVU1mUzaGgBYq0AikaB/hRmxXNpI6GQW1qjgFvSpJudc7vZNoyKzfTFsRvQ+pdFolLWy8AvplDrtm06n6TwYhmGaJp99+vXZ/rXlmj9OPgse+bUVaywWo8JizUv0BaDVqF7Ot/dQ4QovI1gp2C4jbK6lH0hVjowLOlBvZaDOHv6anUw5a/ijLhx6TVfx7F/6zVPLYTweZzFIaF8+QPANzsI95nPhTBs0DIPCFmvnpGhSJvWyPmBnxKczTDh3zQ7PmZF0Ok2fstWovDdouXuCoqG3RWIuI92om5ausWw1VFtfuFsLp029VDF1nkzbEgr6QtgZcEN4AG4XefxrZ3MrtesKTynfu+FGNptNp9O2ujjVBdnVBvu6Ok8pf+0lVK9wp/SrjEajlB1+I7FrO2XYyvQTpte2Y6BTTV8M/vJOyY0RsRUcK4JMJsMuIxRFyX88I5AD1FsB+EpGKpVio1VZ76nbVSqJjV7TNbItdrAl7CfKunItyzJNUxggKBK5RROPNiv+epxFWKpPqLlxK/zv33keiuzr9VAve4uwWY2yL7wucbtk8d6gBx4n0IZpmrYoKRzKruTR18tgo37om0Z1tVnVa7m0HrNqupr3IGf2xRD2PtBrdsUWEg0dcuJW83ZCV7T86YrFYs5GAmc117mCUL2qqtquANgvi78CsJ0K/mBoCf2cY6LLUP7AbOple+HjALswoiWsuaWAexBA+YB6y4VbaCaLKLmmOfp1KbluNhKPMLZS1DMMg1UiKYyyHTl/2Na19/wkk0n2U7T9dGlIZD7qpW5p9iNXrx1mlRI1OHur11nbcFuYv3pZzZWtYGu1o/PsrNpaLhXiWTfoQf7qtbhStnLaEG7QW700npydN9v5dFaVrPy60tnQ+lBuDK3HyqwvgFXs2C7UXGst1eaVXLeI8AsshLaQ581FtuHEimhIY2HqFa7pkQsP9eq67vwqOtXLUK69xyGdTvM/NFjW/0C9pYfGFiqifq9kMkkBiP02nL8uikcULqmyQsvpV6qqKlVeQ44Bw7SQrzSQ5t1G8diigK7rQp2YpmnbAnU9UnWKHQM7PJuYWdx3U6/wSt+pljnVeunYKMgKVWrNplhbHMxng24Ij9xtKBAbfGfl7l4VbtBbvc7sxER9vbMepA2+bppyvzOVoF+BYRi2WiBd/9F3I5a7dY0+Mlf12haSwITr0zFQm4qw4ApWr3NkeAHqpd5f58U6/Rac3wF2DeSsvtMXld8F/VQ9sgYqAtQ7CxRqC8Y2AtkZNIUXthTXWH2FBTh6QT885w+SbregW3ooSrLDsAUCdvugmpvtIeUOdfs544ItjsRyfYq2ASyzNjiXQ70KVyNnbcv5tDmzDl2bVPLZoBBWs7chNCJBZUcOFu7C+S1yE7lb+3AB6qXvDFV2eY3NWsFi35NMJmNrsLGuVVr+6lW4ZlXbWXUb86woCt1cJzznTvXaRM4uItmO6LDpYtrZoTsn9dIvlFoIbMcg/JKwbykdtnODdEFA1+jK3GcOABKAemen+AmAWEuvc1MebUrCTimLCxPpdJpVMSl0MvUy5wmPhx9YSx+kn6izzsrgZ89gh+dUL11is2zG4/GyjnAWqpdV9SggsrZltzZnfjmLsPyaeW5QCEVJ4axDzhNi+yDF9Pyv82wnjd1bEuLae6mVogD1sm+dyvWzqi639/DQFyOZTMZyg8ZVR18vv+as6qXicJ5871ZoGnKlKIpwBJlQ5IqisNx5NDjzfQTeueC9yPfEs5VtpeD2W2Bfe5YXihUq19er5rqWqOUMg5z9BtQrA95GNjzUK8R2Mz67BcXKhVq2KboeF4YA5mkaeuOMFB5dWQw39fK1bVY7FG7QY2hJMepljcPsnCv5tTmzdjxbWM9/g05oDhNb6ZM8ZlUdXXjZ4iZ9AfIZ4kRrsvt6WVNHSjRmzVu9tCl2Jy474bNOvGXNZYRznuot+GqGjVJMp9P8XugC1LtV1kO97GsjvMGdx9Ypw0xp+xGxIxH+FtitEKFcJzE1adAFNzV9sRLJp4BARYB6K0z+6qX5lilG8GMa+R5fFkCpuVLY/sYCDWsGdK5TmHqV3ISUfGBlVSXnBllrWz5VEOFZEqrXubLbeGZb0zGrztqaefPfoBOh0lK5od1un6IjcdZUWEV2Vj+xyxrWEcA2O1f10qdYTtVrRxfTF8kjuJdcvW5fTu+rBzp1wuHTlCPvovRQb/658BhmRf/arsmE6qURAKwUnNOD8OdBzc36iYFXfgPqrTD5q5fVWkK5wVbOmjRrc2M/Oed22PyOHmGODyXUC+Vch98CNSfSR+aqXtsxFFnrZWeJn8aSmdJ2kWFrOqbVbMc5pw0KM+iM6bwOeag2xubTdm6Q9pvPPZpsC7Z90YnKX73sXi9+y06VhtxviptVvSFuIN6s6nWrxrn9jrLZLJ1SumwVzvzlfRnkPGbnv/wjIopRr2VZCnd3mfN7QhcQ7Acu3As7Ntt9/8BXQL0VZk4NzjRe1KPbhtUjbY1O7CPUCm05fvPZbNbZDsa/doZ7tgUaeiO0rLd6hQuLVC/rxhbi0ebM2glsoWquG5z1mC3RMFQilruVS3gGqKGVHR7NmiLcL3//t1DzeaqXvGs7IXzQp68N3W8Wys0U7ZyRis8su42NbY1OPp1nVVWpE0SYL8ulAd9y6bywcsMs3FpNbPPYeDzcyVu9Hvn1fsv7CthZdnRvoeV5ZzO7mQre9TNQb4WZa1+vjUwmk0wmWQMp9fSErr3FSOXGQKq5OXqcv/lEIsEmLFSvnRBDOEyDvy8ilXuSnXXtWFCWNWGo8miMLVi9CjfMxHkx4ayDsvorm0lD2Nqc/wYZtEHhEGWVm/vaibD3XTisnRRr247tjls39YaubdV3fgnZNKXsgoCtGXL0CLCRzwo3NIk/ANM0qd7Jxt6zI2Gv2Sg2t58Dfb092mDcpuMgGwnHKwlz7bzQZDV7Vvry1UuXEfzxCD/I7n/jr8ycwyRBZYF6K8xc1ZtOp6l1l/3+WT2DDXe0xSAl1zXI34KSf4OzG7QF2hf1UZFmbHUa5mPbBukjzliZj3qj0SjdbcxMQGeANQ47q4Psfgy3NmdFNHKqgA3ymxVKwpptQJCwaFRuAlHbcoUbdeXsuS+s1kvDZYUXBx5BP+aYMolXciz38B/+yyCsJQt/Duw5lc63LO7OXeG7bp2mwh3RpY+txG0XozJrvXxPMH88wg+ywRa2LMz6cwaSgXorTP7qZY9cDeVm22A/RerKYu11KjchH8kj5XhUXPHq5XuSbC2crKrHArFzg1Rddm42H/Wyyi7BlrPGYWddkw1DdTZXsrMacm9tntMG+TYAtjJ7PevwZltUZXNTWNzEvATdOqK49AgQbuq1OYx/tiu7JSyfw3ODHZjiuOvJ+9tFlWxnFc1WQ3UW4qxXM7aWWzU3sw1/Svl7YW093Pz2dV13a+2fVb3OOZw9foZu7wrfootvVVXZvCWx3F37UK/fgHorTP7qpUqerZbAxo+o3JwJ9Esjkbj9tuekXmH9gO4qptfCNrp0Os3mj3VGRsVluCmvXjZpJWvuo3VYWGdXG/xhu0UZ9qxiZ5szazi1KbaADQrvVKE12dB0p+NtZyYkakJnTRr0Qs3NHsyuuoRbE6o3n3mS3chTvXRp4nZjOp20lAMai2A7P3Q16ZxfTMk9hNj7DFi5y0R2Eth4OucpZffC2ppADJdnO/JHqObujy9GvexIWGuBcI+2UqDOcv6Es0tDukqAev0G1Fth5tTgbLvSJyPy1V9+Tb5q6K1e3j0euF3m0zMYhG+Zpsk6U20dkG4th3TdwNzArt9DjqGewh7oykLttMIKKE2OwRotPOZpYd3n9C95hTRDM4U5P6K4PFrOch9NXTB5qtdyn4uGKmchdxRuGji6lBEeP//d8Kj3sz2yjbCZ0tn8M86P0P2ys+aRkcrdIu/hS2GDs+KYU5rvSXH70fGlQBtxztiTzWbZry/PIgPSgHorDJmmsMg46zRb/EMRbG9R9av4ibqo2p3PYfC/fJWbxdpGNpsV3jTl/3lo3SYpZFBI9R6j7oRG0nmv42EdqsMVX9AM1utZ5HacVV4GW4dqtB4Hz6aRmetD8Wa9Idt5v2w+0DWl2wedLfluvwK6qvBu9idne/cOWJaVSCRYo0seOQCSgHqrn0wm4/yFV3a4IwZbBpf8n5YIykcJr6VARYB6AQAAAKlAvQAAAIBUoF4AAABAKlAvAAAAIBWoFwAAAJAK1AsAAABIBeoFAAAApAL1AgAAAFKBegEAAACpQL0AAACAVKBeAAAAQCpQLwAAACAVqBcAAACQCtQLAAAASAXqBQAAAKQC9QIAAABSgXoBAAAAqUC9AAAAgFSgXgAAAEAqUC8AAAAgFagXAAAAkArUCwAAAEgF6gUAAACkAvUCAAAAUoF6AQAAAKlAvQAAAIBUoF4AAABAKlAvAAAAIBWoFwAAAJAK1AsAAABIBeoFAAAApAL1AgAAAFKBegEAAACpQL0AAACAVKBeAAAAQCpQLwAAACAVqBcAAACQCtQLAAAASAXqBQAAAKQC9QIxvb29Gig/vb29KN8qplLlC3wO1AvEaJpW6UO4LqjUeUb5ygHnGQiBeoEYhAw5aJqWyWR+97vfyd+v5D1en1SqfIHPgXqBGIRmOVBozmQy8vcreY/XJ5UqX+BzoF4gBqFZDlBvdQP1AiFQLxCD0CwHqLe6gXqBEKgXiEFolgPUW91AvUAI1AvEIDTLAeqtbqBeIATqBWIQmuUA9VY3UC8QAvUCMQjNcoB6qxuoFwiBeoEYTdP+CMpPBdVb6axfF0C9QAjUC8QgNMsB6q1uoF4gBOoFYhCa5QD1VjdQLxAC9QIxCM1ygHqrG6gXCIF6gRiEZjlAvdUN1AuEQL1ADEKzHKDe6gbqBUKgXiAGoVkOUG91A/UCIVAvEIPQLAeot7qBeoEQqBeIQWiWA9Rb3UC9QAjUC8QgNMsB6q1uoF4gBOoFYmSG5uVfXqL5id7eXml516DeqqZS5Qt8DtQLxMgMzZqmvf39L/snSc471FvFQL1ACNQLxEhX7zL/JE3TLl68+Pbbb8vJO9RbxUC9QAjUC8RAvRcvXpSTd6i3ioF6gRCoF4iRrV7zbv8kqBeUCqgXCIF6gRioF+oFxQP1AiFQLxAD9UK9oHigXiAE6gViJKt36ntL/ZOgXlAqoF4gBOoFYqSrt80/CeoFpQLqBUKgXiAG6oV6QfFAvUAI1AvEyFbvY63+SVAvKBVQLxAC9QIx0tXb4p8E9YJSAfUCIVAvEKNp2v/KwrfqlZP3SqlXQu4A1AuEQL1ADNQL9YLigXqBEKgXiJGt3p1/558E9YJSAfUCIVAvEAP1Qr2geKBeIATqBWKkq/dv/ZOgXlAqoF4gBOoFYmSrd8ffeKejD6sDrQr7d6BVOTno+qmuxk/x79o+O2uCekGpgHqBEKgXiPGbescfaArX1bB/I+GPdzV+aqBVsVmWUriu5sVvfJ7/bCT8cXrNL4d6QbmBeoEQqBeIka7eZu80/kBjJFzL/u1qvGmgVeFfUHrzO0umdjSH62rGH2g8OfhF9tlwXU3f4s/0Lf5MJFz7TO9t3vuCekGpgHqBEHnqzWazkr9/6XR6Tusnk8myHmE2my3fxkuObPVub3ZLbw4tGV/T+P2vLoiEa7d85c9e/PrtU9ubB1qVgVaF3u1qvGl8TSOtHAnXdjXeFAqF6O/3v7pganvz+JrGSLiWVvbYEUtQLygVUC8QUkb16rqeTCb5JaqqJhKJ8u3RhmEYuq67vRuNRk3T5JfEYjFVVZ1rZjIZXddJ5NFoNJlMpjii0SjveF3XYy4oihKgX6B09f61Wzq56a6B1oauxpvCdTUDrQ0DrQ0tC26MhGvDdTVdjTfRkvE1EVo5Eq4dXxMJ19XQ35YFN7YsuLGr8aaWBTf2Lfp0JFzbt+jTHvuiBPWCUgH1AiFlVG8ymVQUhV8Si8VSqZRlWWSs8u2aoSgK70X+UiCbzSqKkkqlWGWUBCncDrOyqqrxeDyVSqmqapomveA3q6oq5dG2wVQqZTsbPsc/6qXUt+jT4bqak5vuon+3fOVPI+Faev2M8VdsNad6B1ob3hxa/OLXb2fvQr2Sy/d6BuoFQsrb4EzVSjKQYRiKovC1QOY8qimWZHe2imY0GuVfK4rCKz+RSGQyGcMwaAVd1+lIotGoYRi2jVN93abeeDzOu9aCegsNT1PDX/JO4bqayPzacF3NlvZbxtfcsaX9FlapjcyvHWipp9Ui82vH19wRrquhvy0LbqS3wnU1Jzd+gd6ddV9QLygVUC8QIq+vV1VV8lk8Hud7PVOpVCgUErb0FglVaoVvGYZBPwbTNNPpNGs6jkajrCWZX59VnUm91HpMXneql9xs22A8Hod6PcKTtwtf7PscU+xAS/2W9lueMf4yXFczNfyl8TV3RObXsjWF6j258Qu0MtRbkfK9ngmQep0Hmedhx+PxMhzONaRSKf5gytpxKWdQTlnUm81mqe7IhGoYBtWAqZmXLyqbelOpFFUW2Ynm24RJk/Q6mUzGYjFbfy0P37dqG3KVSCToXb4zWNjgHI/HdV2n+rrlqPUahgH1liQ8TQ0v8UgtC+pe7PtsZH4tvzBcV0ML+xbdzBYy9fYtujlcV9MV+eRAS31Oz0ty9WOvfU0NL4F6QakIkHpN07QNjqFo5v0pimxulRw3Ui6Ypmk7V7FYjMK+qqrZbJbqb6qqOrssgzUop4y1XtY/Go/HQ6GQoii6rrO6L4NXL0lOVVVFURRFSSaT6XQ6FAqxj9By9kJVVdqyc++ZTIb2SNBrfgVd1xOJBF/N5U1JjclsZeZXVVVjsVgikWCfQoNzScLTpUeXuKUX+j67pf2W8dV3RObX8su7Ip8Mz6vp026+9OiSIw82sYWvP6KG59Vsab+lT7v5oZb6h1rqza4/b1lQd+nRJZH5tVvab/HYFyWoF5SKAKnXsixbvYgqHvTaLQtkQWcPnTeJRMLpPArUNqfSmKFkMkmxl3bkFksDNChHhnqtXKWT8m9ZlmEY7Pzy6qXOV3oRCoXodDDdkobpg+z7EY1GQ6GQ85qLemHZv8LLN7pE4i92bJdC/MeZeikXdBmRSCSg3pKEp0uPLnZLL/TddunRxeOrPx+ZX8sW0r/heTXjqz9/6dHFLQvq+I+w5W9s/uKlRxdH5teaXbf2aTf3aTd77IglqBeUimCplxpyeS+y4TI2KxMsyFMToNs2KVpGo1G385DJZMjfwhUMwyD1RqPReDwej8fZvqhB0ZkF/w/KkaReK+fddDpta6CwNTizVlymXpIrOZJeWJaVyWTYVZJQvbqu823RziYRdh1ApNNpj2YTm3qpbJiG+U+xPmB+3BYb5DXXc1hBpKt3kXcaX317ZP7H6PWW9j9pWVB35MGI2XVreN4NZtet7C1K4Xk3jK++nV53RT7RFfkEvW5ZUGdbU5igXlAqgqVe1rXHH7BbszPVRymkW5ZlGIbTvoZhUMMktWWykEuCjEajtEeKvdT0yHe1ptNpGgZLFTCKpVTz4QMsvz5/zH4elFN29VLfLfUiZLNZ8hZ/CpwNziQqpl5W2aXCo09RKdLZd6qXPMovsf1LO+LdzL5eMW7oNf9uMpmkT1FTNpOuU738GUCtN8/wdGnbIu803n97ZP7HXlhxW9cdnzD/8Va2/Ol7F0Tmfyw87wZ+5fC8G8b7b39hxW0tf1H39L0L2PI3YneF593w+oY7vfcF9YJSERT1UixlHYKxWIw1zwr7PvnQxyrEqqrynk4mkxTbWURlw6NoNfIcDQDKZrMU0mOO+RWolZRiPrWBU1zlA2zgBuWUV73UhBuNRumM04mgDnBah84+681ll0V8g7OVa3Nm3QBka75ObFOvbe4Oofb4kqB2DHqdyWRshUQrs/4GOh7KHS1hK/NdIxbUO5fwdGnb7On1DQvd3hrv/5zzX4/1vRPUC0pFUNRL8CGLOlaF/bgkMyZUvjZFgVFVVWpDDoVCwhoz345I6jUMg+qsts4+Cs6pVErXdYqiVAuiz9qG2QZoUE7Z1cu+c3QtQyeXjU+j5uJQKESmpCosG2bFTgcVIWtttrhhVrQyf04Nw6DCTqfT5HjnZZTFfV2i0aiti5e2aRsOZ5omG3tFm+WboNlqfE8+K1GZF1OlwofqlZagXlAqgqtey7JM02TBmV/HNk2hLQKzzFK/obAXj4XNdDpN4Z119Nr0T3GYdSDSrkm9zi7CAA3KKe99vYlEIpvNUmszf+1DbbaWZaXTabqzlr2VTCZpfHk6nbbd/ms7y1RjtnIKpM0ahsF/UUzTJLsLx1ixQmJ1cXYkzlkwLcuyXf2RpPnuZ9vYvFju3if6bnnMaulDZKt36xf9k6BeUCoCrV4KjMIBVjxuo2S81Uujpaj2TFugHfHHQEO0WJWMVGpZFsV5j7ZM/w/KKfuUGm5PTSjHd1F4n7Vpmk6J8uR5A7XbamynbkO0CO9j8CGapv2PLDRNu7T1Lv8kTdMuXLhw4cIFOXmvlHol5A4EVL3pdJpuv7Ryd4d6zGLhpl4aGBsTzVRIncp8l6KVG7dFRuRXZkuotdnK3UzsbAkP0KAcPDQQiIF6oV5QPAFSLw1VoemPbDcCOXXI46Zekh/VZVOpVDKZZO2CTIQ0GIjZjt3tyW+HDQFTuZmXbONk2WaDMigH6gViZKv3u1/wT4J6QakIinppDLCVmxGBpqHgocmhhI1/HrdlUvU0lIPVU3kRsrkOCad6Lcui0V70IADyKG3ZtmaABuVAvUAM1Av1guIJinqta/vUTNNkw10ZbrP2eqiXoBE8toGr/LNteKjnlVZjU20wU7LuYStXQ6XR1PzuAjEoB+oFYqBeqBcUT4DUWzClfXxCMplkp8s2975zhmcnQRmUA/UCMdLVq/onQb2gVFwP6gUFEAD18vduz7qmx1fc+VY8Hvf+SWSzWe8LOufH+QlDAo1s9X7nTv8kqBeUCqgXCPG7eml8mncTAcOjN8ISPWfKORmKEzb6QIhtBtE8tylkaGjo2LFjBXywTEC9UC8onkCo98SJE8PDw5U+iusLX6uXPdw3z35vt0lVCJpazLKsVCrFHvo4q9RpXkl+Ce9aNjcIP4FLnhcKNiYnJ9euXbt27drp6ekCPl5ypKt3oX8S1AtKhc/VOzk5uW7duv7+/omJiUofy/WFr9XLHoXB7tPiyWaztqFx/AQlzklYePWquWc60nB5ZtNsNhvloCovTWRK0O1lfL02k8nE43F6iz1vmD0ka65ZPnbsWGdn565du+Z+tkqMZPVODjX5J0G9oFT4Vr0zMzOjo6M9PT2HDx+u9LFcj/hXvTS6PZvNUg9ujJsCmsH/S0+noucjCTfIT6jN1Gu7oduGx+3VmUyGHvdr5SYUZXsprNbLmJmZGRkZ6enpOXHiRDHbKRKoF+oFxeNP9e7fv7+zs3N0dHRmZiaf9Z0xLZvNesxvNScMwygyZs4KGcTKjX+Ox+OlOviC8YV62ZMoGDTtM71mk4eRI4XlxE+b4rwdmyYCZYTU97kAACAASURBVE9cYPVj1kDtoV5SKWHbMk0QTc+cYguLVy8xMTHR398/NDRUqfZnqBfqBcXjN/WeOXOmv79/cHBwToFFyT0rl0HxM88BsB7QgwU9psoSkkgkhPcEO2fdoiZJygI9lzCZTAofLSwZSeo1TVN4pnjoMiSTydgmN+F7cKnl2dmQS08rojVZZdQGfZBaj/kGZ8tdvVTz5hu0bUOoaAZwPnd8o7ft2YUFsG/fvp6enopcoMlW75ZG/ySoF5QK/6g3m80ODw/39vYW0JzmjJCs7bBIqN2RHpc7pw+mHNDVgNMOiqLQsxYoXNMSoSNk4otaL49TM7OOcGbjsGjNdDrNP5yZ4dbXa7mrlz2pih2JbQU2CIvNtUZ6Zt+G4guYfjB9fX2nTp0qclNzAuqFekHx+ES9u3fv7uzsLPgivkzqpbqNZVlUHxXGeWpctD1G1kYikaCHMTjPM7VWUmSmehfNlEnxmRpEi8xFYfhOvU681UvVXNuasdyU2fyaQvXS3UFu6lW45w07+33T6bStgi58rHRJOHXqVF9fn2maxbfw5Il09Ub8k6BeUCoqrt5jx4719PQUGTqEDc5FqpciKkXRZDJJdrRdHNDMjhS6aQJnWk7Po4vlJoCk9kWqdLHHtBP05AaaFDMWi9HtLfTEWObgYnJRMMFWL3nX1thL3wnnqCsqP2pz4Gu91D7sbKagTbF/naOsqX2D/aj4Fbwn9yiY3bt39/T07N+/v+RbdiIzNLe1tWl+oqWlBeoFJaFS5WtZ1sTEBN2vWPyNQxTZqBONzZ88pw5a6hNk//KPEmJ9iNRpSM82oKfNUmWXxXB2GlnEpmZk9qxAanHkw7KVezwD1XrpPhSPG2ekEWD1Ug+rZVnpdJpaD9jTqeiWoUQiwQqAFSq7CLKubdy2NTs4SyUWizmbJthVWDab5d9Np9POandJmJ6eHhwclHAfnvzQfKFotFxttVRIyDXUW91UpHyz2axpmj09PcXP0sOiK9VS+GGn8Xict6nb4xB4SKK2qg5rj7Ryd44YhpFOp+k5wcJbNGlr9IJ6/XRdp5NsawmnFmbWM2gYBmtkppp0keenYAKsXmf7idua7LKI/iUv8v3z1AnPTMyPuKZHUFFx2sZYsSZoujqjx0myqyr2uOaiMu/CiRMnent7R0ZG8rw3oADkh+ZMJlOkKUur3kwmIyHXUG91I798qVt39+7dJdkatesSFNz4fwt4vh5fIyJ49fLEYjG3wc9MvfQMYKpW2foT6TWNtqF5F6zc0xGi0Wg6nbYN5ZFMgNVbzJp0+cbDLn9YoTLo4kvYNME/fpI6EoTvloOZmZldu3aV7474IIbmgB4z1FvFyCzfknTremBzlbCfrgDc1Guapod6+aZjqotTTyLfYEl1aF3XKYBTj282m2XCrmAffADUm//ZKcmzq4S7q1RX/KyweeDOnDlT2i0HMTQH9Jih3ipGTvmWsFvXA5urnLWUwnBTbzqddqvzkPVZwOe7jdmoaQa7BYY6HFleKjW2mQiAesGsUPvz8PBwCa92gxiaA3rMUG8VU+7yLWG3rjd0Z45tSVnVa1kWVVhZKzdzKt/Xq6pqKBRit3E673pKp9M0CJdNLUx9hRUcY2VBvdVEIpEoYR+PpmkfBY2AHnOl1FvprF8XlLV8S9ut6wbN5su6z2jSezastfjte6jXsizqUQ6FQjREmRbSdQCN1DFNk71mtwzxW6BpmuhxrjSamm+grtSMklBvVVHCS+AghuaAHjPUW8WUqXz37dvX2dlZ7hv9ybJ03y2/nO7BLVWt0Vu9hK3LjwZXOye0IvWywV9003A0GqXzn8lkbDNNkoYr8oR1qLcKYR0/k5OTBW8kiKE5oMcM9VYxJS9fku7Q0FAxv+488fB6CXMk7ctf8ckjeaDeqoWGO46MjBR2XRzE0BzQY4Z6q5gSlq9M6YJyA/VWM+wGpAL6MwIRmqempvh/bcf8/vvvyz2cQoB6q5uSlC+kW31AvdXP9PR0AQ9gCERonpqa6ujo2LZtG3XzaJp28uTJVCr15JNPdnd328TsT6De6qbI8oV0qxWo93qBHsCQ/3M6gxKaH3vsMeE8zI899lilDy0vqk+9//CPS+c+bXaFMQyjTGdDK7R8Id3qBuq9vti/f39nZ+fo6OisM1BqAVHv1NRUc3OzLZI2NzcHosr7UTWqV9O0nx4aDFYq69mYa/lCutcDUO91x8zMzOjo6KxPQAqKej8SVXyDUuX9COr1R9I07cKFC+W4XJtT+UK61w9Q73XK5OTk4OBgb2/viRMnhCsESL22im+AqrwfQb3+SFruwRvlOBv5lO/hw4d7enog3esHqPe65syZM/39/cKpXwOk3o+urfgGqMr7UdWqd1OwUgXVe+LEib6+vnXr1pX7MaDAV0C94P/uAB4eHuZHYAVLvaziG6wq70dQrz9SRdRLF779/f1zuvUAVAdQL/g/aAro0dFRmoIjWOr9KFfxDVaV9yOo1x9JsnrpgWMe3T2g6oF6wf8PG4GVSCQCp96pqam2trZgVXk/qlL1Jg5uDFaSpt7p6emhoaHOzs4yPWYbBAWoF9ihKTg0TTt48GDJI5GQ5V9eMod7MMtP+e7ydKJVp3ofCVbSyq9eerRJZ2fnvn37JJc18CFQLxCjadrDDz98//33nzx5suTxyBme3v7+l/2TyqclYd6h3oqnsqr3v/7rv773ve/R0/1mvZ8eXCdAvUAMheZUKrVixYpNmzaVIyrx4ent7y/zT9LKdpenMO/Vp96XDm4IViqTet9//31N07q6ur73ve+V9el+IHBAvUAMH5rHx8e7u7sfe+yx3//+96WNTYQ/1VvWqw0+71BvxVM5Snzv3r3d3d2apv3nf/6n/PIFPgfqBWI0x1OAfvzjH3d0dMTj8ZI/EUjTtLfNu/2ToN4ic1RxlVZQve+///7evXs7Ojo2b9584cKFSpUv8DlQLxAjDM2///3vf/jDH3Z3dx89erT4IMWAeqHeKlDv1NTUk08+yaTLzgbUC5xAvUCMR2i+cOHCN7/5zW9+85ulkhPUW2XqfTG5PlipyBK/cOHC5s2bOzo6nnzySeczpKFe4ATqBWJmDc1Hjx7t7u5+8skni29/1jRt6ntL/ZOg3iJzVHGVlkS9+XyxU6nUww8/3NHRsXfvXuH6UC8QAvUCMZqm/WE23nvvPXoo/ZEjR2Zd2QNN06a+1+afpGna+fPnz58/X0ym8s97pdRbvhxVXKUFqNdW4m+88ca2bds8srlnzx7DMO6///6DBw96nw2oFziBeoGY/EPz+fPnqf25YFdBvVWn3nXBSrYSf+edd7q7uzdu3OjM3TvvvPPss89Sh+5vfvObfM4G1AucQL1AzFxD85EjR6j9+b333pvTByk8TT3W6p8E9RaZo4qrtEj1DgwMaJq2YsUKPl/nz59/7LHHOjo6Hnvssfy/G1AvEAL1AjEFhOY8259/9atfOcPT1GMt/klQrzfvvPOOd45eTD4crMSX+LPPPkvziTY3N1NOf/Ob39AoqmeffdY77/4pX+BzoF4gpuDQPGv7c3Nz8xtvvGELTxXXLdSbP9Qeu2fPHrccvXDg4WAlVuK/+tWv+Nm8d+zYcf/99xuG4ZZZ35Yv8DlQLxBTZIOkW/vzG2+84WzKg3qDpd4//OEPGzdu1DSto6PD6SRN0144MBCsRCX+61//ur29nVdva2vra6+9VsyJgnqBEKgXiCm+L1DY/rxnzx4Kas888wwfnqZ2/p1/EtQ7Ky+88ALzk03AAVXvm2++2dvbqzl49tlng1i+wOdAvUBMqYbh2Nqf77//ftaRxpqdod7AqffIkSM2RTEBa5r2/IGHgpU0TRsaGnJ6l76o+Yxk9lv5Ap8D9QIxpVIvQe3PO3fu5IMaa3bWNG1q59/6JwlDMMiHjo4OLZjq3blz586dO58U8eyzz166dKmwb74G9QIRUC8Qo5X65pP33nvv7//+722RmpqdNU2b2vE33unow+pAq8L+HWhVTg66fqqr8VP8u7bPzpo01Hpn4/XXX3d6d/PmzefPnw+oestU4lAvEAL1AjElV+8Pf/hDZ7CmZud81Dv+QFO4rob9Gwl/vKvxUwOtis2ylMJ1NS9+4/P8ZyPhj9NrfjnUWzDj4+NO6bIcPbf/wWAlqBdIBuoFYkqr3ieffNKtiXLFihWapk3taPZO4w80RsK17N+uxpsGWhX+BaU3v7NkakdzuK5m/IHGk4NfZJ8N19X0Lf5M3+LPRMK1z/Te5r0vqHdW2IUUL12Wo4qrFOoFPgfqBWJKqN7z588Lu9AYmqZNbW92S28OLRlf0/j9ry6IhGu3fOXPXvz67VPbmwdalYFWhd7tarxpfE0jrRwJ13Y13hQKhejv97+6YGp78/iaxki4llb22BFLUO+stLe3O6XLclRxlUK9wOdAvUBMyRucvcPT1Pa/dksnN9010NrQ1XhTuK5moLVhoLWhZcGNkXBtuK6mq/EmWjK+JkIrR8K142si4boa+tuy4MaWBTd2Nd7UsuDGvkWfjoRr+xZ92mNflKBeby5duuRxcjRNe+5n/xKsBPUCyUC9QIx/1Eupb9Gnw3U1JzfdRf9u+cqfRsK19PoZ46/Yak71DrQ2vDm0+MWv387ehXrLWr5Qr+1sQL3ACdQLxMhW7/CXvFO4riYyvzZcV7Ol/ZbxNXdsab+FVWoj82sHWupptcj82vE1d4Trauhvy4Ib6a1wXc3JjV+gd2fdF9RbZI4qrlKoF/gcqBeI8ZV6X+z7HFPsQEv9lvZbnjH+MlxXMzX8pfE1d0Tm17I1heo9ufELtDLUK6F8NU3b/bO1wUpQL5AM1AvESFfvEo/UsqDuxb7PRubX8gvDdTW0sG/RzWwhU2/fopvDdTVdkU8OtNTn9LwkVz/22tfU8BKot8gc7f7ZN4OVoF4gGagXiJGs3kuPLnFLL/R9dkv7LeOr74jMr+WXd0U+GZ5X06fdfOnRJUcebGILX39EDc+r2dJ+S59280Mt9Q+11Jtdf96yoO7So0si82u3tN/isS9KUG+ROaq4SqFe4HOgXiBGunoXu6UX+m679Oji8dWfj8yvZQvp3/C8mvHVn7/06OKWBXX8R9jyNzZ/8dKjiyPza82uW/u0m/u0mz12xBLUW2SOfvJqNFgJ6gWSgXqBGOnqXeSdxlffHpn/MXq9pf1PWhbUHXkwYnbdGp53g9l1K3uLUnjeDeOrb6fXXZFPdEU+Qa9bFtTZ1hQmqLfIHFVcpVAv8DlQLxCjadqMLDRNu7RtkXca7789Mv9jL6y4reuOT5j/eCtb/vS9CyLzPxaedwO/cnjeDeP9t7+w4raWv6h7+t4FbPkbsbvC8254fcOd3vtigVhO3iul3vLlqOIqLVi95TgbUC9wAvUCMdLVO3t6fcNCt7fG+z/n/Ndjfe8E9RaZo4qrFOoFPgfqBWJ8qF5pCeotMkc/fvWBYCWoF0gG6gViZKt36xf9k6DeInNUcZVCvcDnQL1AjHT13uWfBPUWmaOKqxTqBT4H6gVioF6ot+Ac/Xh8TbAS1AskA/UCMbLV+90v+CdBvUXmqOIqhXqBz4F6gRioF+otOEc/Hl8drAT1AslAvUAM1Av1FpyjZ8dXBytBvUAyUC8QI129qn8S1Ftkjp4d7w9WgnqBZKBeIEa2er9zp38S1FtkjiquUqgX+ByoF4iBeqHewui+V9dyPLTp3pf/37coPbTpXk2EH9ZZvHgx1AtkAvUCMdLVu9A/CeotMkc/PTQYrIRaL5AM1AvESFbv5FCTfxLUW2SOKq7SAtR7+vTpt956qxxnA+oFTqBeIAbqhXoLztFPD20KVkKtF0gG6gVioF6ot+Ac/fTQxmClnTt3Qr1AJlAvECNbvVsa/ZOg3iJzlDj4SLDS+RzlOBtQL3AC9QIxUC/UW3COKq5SqBf4HKgXiJGu3oh/EtRbZI5eOrghWAnqBZKBeoEYmepta2sT3oVZKVpaWqDegnlw4z9VXKVzTejrBZKBeoGY8oVmN877Dwm5rj71vphcH7ikYYQzkAvUC8RomvahXC5cuHDOT1y4cEFCriuo3jLlqOIeLUy9586dm56eLvnZgHqBEKgXiJGv3uuTalTvusAlUm85zgbUC4RAvUAM1CuH6lPvvzzSU3GVQr3A50C9QAzUK4fqU6+maS8ceDhYCeoFkoF6gRioVw5Vqt6BYCX09QLJQL1ADNQrh6pU7/MHHgpWIvWWo+IL9QIhUC8QA/XKocrU+/LLLwdRvYODgzt37ty5c+cTLkxMTBR2QqBeIATqBWKgXjlUh3rffffd559/vqOjIxaLBVG9586dW7FihdsUK0888UTgyhf4HKgXiIF65RB09V6+fHlsbKyjo2Pr1q1UNdQ07bn9DwYrnTt37j/+4z+WLVvm9O7GjRuDWL7A50C9QAzUK4fgqvfy5ctPPPFER0fHzp07Jycn+RxVXKUFqPfcuXMHDhxobm7mvbtkyZKCm5orW77A50C9QAzUK4cgqndycnLnzp0dHR1PPPHE5cuXbe+u3fDV5372L8FKO3fuJPuOjY3x6r3vvvt0XX/iiSf4a4tAlC/wOVAvEAP1yiFY6p2YmNi6dWtHR8fY2JhTusRzP1sbuMSPcN64cSNT75kzZ1jlnrWoB6J8gc+BeoEYqFcOQVHvxMRELBbr6Oh4/vnn3333XY81d//sm4FL/H297777bnd3t6Zp3d3dLFNsHNnGjRtPnTrl//IFPgfqBWKgXjn4X72nTp0aGBjo6Oh4+eWX81m/4h4tWL0sC2fOnGlraxsYGHDm7pVXXjEMY9WqVT//+c/9XL7A50C9QAzUKwc/q/eXv/xlNBo1DOPAgQP55+ib67t+8mo0WMk5keSBAwdisdisZ2bWyxGoFwiBeoEYqFcO/lTvz3/+81WrVuVft7PlqOIqLV69H3744ZkzZ7xzeurUKWqEHxsbc2uEh3qBEKgXiIF65eA39R44cMAwjGg0+stf/rLgHP341QeClbQi5nCemJjYuXOn20BoqBcIgXqBGKhXDv5R78svv9zR0TEwMDCnYUTCHFVcpYWpt5g5nN0GQkO9QAjUC8RAvXLwg3pJurFYrMjpI1iOfjy+JliJ3ddbZN6dA6GhXiAE6gVioF45VFa9pZUuy1HFVTrXdC5HqU4CGwgN9QIhUC8QA/XKoYLqLbl0WY6eHV8drFRy9RK//OUvNU37p3/6p7GxMcnlC3wO1AvEQL1ykK/effv2dXZ2appWcumyHD073h+sVCb10tl47bXXHnnkkc7Ozn379kkrZeBzoF4gBuqVg0z1knSHhoYmJyfLV77t7e2apm3evHnz5s2GYTifBaRpmmEYm3P4YZ1vfOMb5VMvle/k5OTQ0FBnZ+f+/fsllDXwOVAvEAP1ykGOennplrt8NU374x//eDFQbN68udzqpdM+OTk5ODjY29t7+PDhspY48DlQLxAD9cqh3Op1Srfc5UvqnZycFEru6tWrf8xx9epVn6yjadq5c+fOnj1bjrPhLN8zZ86sW7eur6/vxIkTZSp34HOgXiAG6pVD+dTrJt1yly+pN1hoRd/X63E23Mr31KlT/f39/f39EPB1CNQLxEC9ciiHer2lW+7y1TTtf4NGRdRLnDhxor+/f926dWfOnCnhdwD4HKgXiIF65VBa9eYj3XKXL9RrOxv5lO/hw4d7e3vXrVs3a8GB6gDqBWKgXjmUSr35S7fc5Qv12s5G/uV7+PDhORUiCC5QLxAD9cqhSPXOzMwkEokC4nVZ1fs/QcMn6iXoKso0zenp6bl/I0AwgHqBGKhXDgWrd3p6emRkpL29fXh4uIBKEtTL4yv1Ert37yYBZ7PZuX4W+B+oF4iBeuVQQGg+derU0NBQe3v7rl27Co7LUC+PD9VrWdbMzAwJeHR0FAKuMqBeIAbqlcOcQvP+/fv7+vr6+vqKn5KwrOr9KGj4U71ENpsdHR3t7OzctWvXzMxMkeUOfALUC8RAvXLIJzRns1mq/QwODp46dcrn5Qv12s5GSYbRZbPZkZGRzs7O3bt3Q8BVANQLxMhU7/IvLxHOrFspDMOQlnfNMzRPTk4ODw9Tn19pR71qUC+H5nv1EtPT06Zp9vT04EkMQQfqBWLKF5qF4ent73/ZP0ly3oWh+cSJE+vWrevs7EwkEuXo54N6eYKiXoKexNDb23vs2LESbhbIBOoFYqSrd5l/EgXiyclJOXm3heZ9+/b19vb29/eXdYb9sqr3D0EjWOolzpw5s3bt2v7+fkyDFUSgXiAG6i1HIBbmnULz9PT06Ohoe3v70NCQhGAK9fIEUb3EiRMnent7BwcHMQtHsIB6gRjZ6jXv9k+SrN5UKkWPUh8dHZU2iwLUyxNc9RL79+/HLBzBAuoFYqBeCer9+c9/rmlaV1fX2NiY5GGrZVXvTNAIunqJ3bt39/T0jI6OzmAItO+BeoEYqLd86r18+fLzzz/f0dERjUZlhmY55Qv12s6GzPJlNwEnEgk5ewSFAfUCMZLVO/W9pf5J5QvE//7v/x6LxXRd37p168TExIfSQ7OE8oV6bWdDfvlOT0/TPWllHakHigHqBWKkq7fNP6nkgZiqud3d3ffdd9/LL7/87rvv8nmvPvWWacvlo8rUS0xOTq5bt66vr+/EiRN5fsR5nHkeeTwen9vBzZ1UKsUfTFmr9RKm7YR6gRhN0z6QhW/VW3zWfvvb327durWjo2Pr1q2//e1vhXmvlHqLz52QQKu3HGejUuolTp061d/fv27duomJiVlXNk1T13V+iaqqs2o1Ho8ripJKpeZ0YCkXTNO0na5YLJZOp1OplKqq2WzWMAw6sGg0attmJpPRdT2dTluWFY1Gk8kkv+VoNEpvEbqux1xQFKXcRQb1AjGy1ftYq39S8YH46tWrP/3pT++7777u7u7nnnvu8uXLHnmHeitOFauXOHz4cE9Pz9DQ0KxDoBVF4V0bj8eZjN1yQRYkI+ZPIpFwOk/XdUVRbE5NJpOKoiSTSVVVY7EY7UhRFOFmY7GYqqpW7qKBhG2aJr1IJpP8YbPLBdo7vU6lUm4bLyFQLxAjXb0t/knFBOKzZ89u3bqVLqhPnDiRT96h3opT9eol6EnAIyMjHg2q1JDLezEajbK6oLMGzFRnmqabfROJhK7rZGi3U5HJZMjfwhUMwyD1RqPReDwej8fZvlKplO2oKAs29cbjcd61FtQL/AnUawvEx44d887FK6+8Eo1GOzo6vKu5zrxDvRXnOlGvZVkzMzO7du3yeAwDszJ/zG7NzlQfTafT9K5hGE77GoYRCoUURVFVlf7SchJkNBqlPVKTNTUL81cG6XTaMAwSv6Io5EhVVenqVtd1esGvzx8zfZCuHpzqJTfTTqPRKL2m9vP8T2lhQL1ADNTLB+Jjx47pui48+LNnz/7gBz/Qdf2RRx45fPhwAXmHeivO9aNeIpvNmqa5du1afiGZTFVV0mcsFmPNs8K+T6pQksxYhVhVVd7TyWQyFApRHy0tYcOjaDXyXDabpb/UpMxq0gzDMKLRKJmb2sBJt3xtlZaTni1HrdcwDKgXBADZ6t35d/5JtkD829/+trW11XlCDh8+TNXcp59+OpPJFJz36lNvmbZcPq439XrAy4w6VoX9uCQzJlR+mBVVNFVVpTbkUCgkrDEzEZKYFUUxDIPqrPwxWJZFjcypVErXdWoNTiaT1ANNWnXbbCwWSyQSbJgVGpxBAIB6KRBnMpmOjg56mOCpU6doydNPP00TYhRQzXXmHeqtOFAvw6Y90zRDoZDtTh6+QkzYRjiz/KqqGgqFhIOfmfnS6TQZmnX02vRPPtZ1nSxLuyb1OkdW8+ol3VJVPpFIQL0gAEhX79/6J7FAfPXq1a997Wtajlgs9sgjj+i6/oMf/ODs2bOlyjvUW3GgXoZNvTSySTjAisft5iJv9dJoKao90xZoR/wx0BAtXdep4ZpUalmWYRiJRMLpSJt6aQWmYf5IWB8w32dMw8qgXlAxZKt3x994p6MPqwOtCvt3oFU5Oej6qa7GT/Hv2j47a2KBmCZ6ZLS0tLzyyislz3v1qfe/gwbUy2DaS6fTuq5TfTcejzvrvjxu6o3FYqFQiHc5gzqV2VtkOxq3RUbkV2ZLqLXZyt1M7GwJpzuIqNM3k8nQgbmp15lrC7VeUFn8pt7xB5rCdTXs30j4412NnxpoVWyWpRSuq3nxG5/nPxsJf5xe88u91Ts4OKg5OHDgQMnzDvVWHKiXoJFKhmGYpmm7EcipQx439ZL8qC6bSqWSySS7Z5eJUNd1vqKZTqdtNW+LGwLGhl+RIG0dvbRZdhMwHRj1PdMSdpD8/coW1Av8g3T1Nnun8QcaI+Fa9m9X400DrQr/gtKb31kytaM5XFcz/kDjycEvss+G62r6Fn+mb/FnIuHaZ3pv896Xpmk/+MEPnN7VNE3X9fxvHMoz71BvxYF6LcuiMcCWZdEtsDQNBQ9NDiW8J9hjNiuqnoZysHoqL0KSPfuIU72WZdFoL8MwmEdpy7Y1qUuYbuS1ch3DfBM0W43vrmZ7xAhnUGFkq3d7s1t6c2jJ+JrG7391QSRcu+Urf/bi12+f2t480KoMtCr0blfjTeNrGmnlSLi2q/GmUChEf7//1QVT25vH1zRGwrW0sseOWNI0bcWKFStWrKCBzTZWrVp19erVEua9+tT7ftCAegleq6ZpUg2Sx1nLJGadSDKZTJqmaZvHkXW12qCeV1qNTbXBTMm6h61cDZVGU/O7szVE091KoVCIDoC2aVuBskYDvmyzaZYDqBeIka7ev3ZLJzfdNdDa0NV4U7iuZqC1YaC1oWXBjZFwbbiupqvxJloyviZCK0fCteNrIuG6GvrbsuDGlgU3djXe1LLgxr5Fn46Ea/sWfdpjX5ScgfjYsWPHjh07cODAj370ox/96EezTq8xp7xDvRUH6i2SIev12QAAG8VJREFU0j4+IZlMsjPG29qyLOcMz07c5upifdWzXiXkeZzFAPUCMf5RL6W+RZ8O19Wc3HQX/bvlK38aCdfS62eMv2KrOdU70Nrw5tDiF79+O3u3APWWNe9Qb8WBeoFkoF4gRrZ6h7/kncJ1NZH5teG6mi3tt4yvuWNL+y2sUhuZXzvQUk+rRebXjq+5I1xXQ39bFtxIb4Xrak5u/AK9O+u+oN4ic/Re0IB6gWSgXiDGV+p9se9zTLEDLfVb2m95xvjLcF3N1PCXxtfcEZlfy9YUqvfkxi/QylCvhPKFem1nA+oFTqBeIEa6epd4pJYFdS/2fTYyv5ZfGK6roYV9i25mC5l6+xbdHK6r6Yp8cqClPqfnJbn6sde+poaXQL1F5qjSJp0zUC+QDNQLxEhW76VHl7ilF/o+u6X9lvHVd0Tm1/LLuyKfDM+r6dNuvvTokiMPNrGFrz+ihufVbGm/pU+7+aGW+oda6s2uP29ZUHfp0SWR+bVb2m/x2BclqLfIHFXapHMG6gWSgXqBGOnqXeyWXui77dKji8dXfz4yv5YtpH/D82rGV3/+0qOLWxbU8R9hy9/Y/MVLjy6OzK81u27t027u02722BFLUG+ROcoGDai3tBiG4T2KuBy43fhEZB3DnmnujnIekRdQLxAjXb2LvNP46tsj8z9Gr7e0/0nLgrojD0bMrlvD824wu25lb1EKz7thfPXt9Lor8omuyCfodcuCOtuawgT1FpmjSpt0zkC9JYQeFCjfaqZpCh9uyI5KVVX+ViU5s1a5AfUCMbLVu22Rdxrvvz0y/2MvrLit645PmP94K1v+9L0LIvM/Fp53A79yeN4N4/23v7Ditpa/qHv63gVs+Ruxu8Lzbnh9w53e+4J6i8xRpU06Z6DeEkJzZdDjbyXv2ja3hk3/NGU0Oyqa1ZleZ11uBS4fUC8QI129s6fXNyx0e2u8/3POfz3W905Qb5E5ejdoQL2lgubAsiwrm83aHldA0KzOzsceFAA9ZYhBz2Ng/9K8mLQj3qx6Dpqri14rimKbu6PcQL1AjMyZePNUr7SkadrExMTExIScvFdKveXLUaVNOmfKV+LXlXqpCTedTtO8j/QYItvzjlKpFD3+r+R795jMkj37IZlMsom3+FqvfKBeIEa2erd+0T8J6i0yR5U26ZyBegvAMAx+/kj+0UD0lF8r9+wEelZBNjfrMq9e0zSpAsoah9l0yrTNWCyWzWbpkUf0sF63iR7psQr0pAd69oPtXdoXWwL1Aj8iXb13+SdBvUXm6GrQgHqFuD3egIeESm2/7IO8SjOZDD2IkFp0efXS4/zocQjsoUb0nAb6LDUF00LSOb3rPJ/pdJqeYkSQ7/kVEokEPceXrUNbY68laxjqBWKgXqi34BxV2qRzBuothkQiYcsgr14bbg3OJFcr9+wgqrMyg7Lt8+/y2Gq0qqo6K8fUDJ5Op6lmTJ3B/FMR55jvooB6gRjZ6v3uF/yToN4ic1Rpk84ZqLe05K9e8h890JcWptPpUCgUjUbpJiVq004kEuwJhkL10uN72b+2fl/SLX8rEY32kj8GmwH1AjFQL9RbGMKHHPuclpYWqLeE5Kleeu59IpFgj92ldUix9K7FDYpOpVLCWi+JmV9iu2GXVuCHVeu6zqTuPRdHmYB6gRgN6oV6i2AimJT8PEC9PHTzD1VqaTXquKWx0EyftA5rbSZb00eoV5hXL93FNOtcGdSny17zVWTqbC5JxvMH6gVipKtX9U+Ceovn/PnzlZVoAZw/f77k5wHq5aHmYnYTbSKRUHIYhsE6a2nMlKIoTJA03opVhZl6aQwX/Ut1YurEtY2x4g+JRlepqkrjpaPRKG2cHyYmAagXiJGt3u/c6Z8E9YJSAfXacM5ckWeHq/M0JhIJwzD4hVTfpbuMbB9PJBIkctM06bYo/oOJRMJ2/3G5gXqBGKgX6gXFc32qV05+hXuRPClVwUC9QIx09S70T4J6Qam4PtULZgXqBWIkq3dyqMk/CeoFpQLqBUKgXiAG6oV6QfFAvUAI1AvEQL1QLygeqBcIgXqBGNnq3dLonwT1glIB9QIhUC8QA/VCvaB4oF4gBOoFYqSrN+KfBPWCUgH1AiFQLxAjMzT7bdbf8s3o60SDequaSpUv8DlQLxAjPzQXPxGglqutlgoJuYZ6qxuoFwiBeoEY+aG5+Fl/S6vecszo6wTqrW6gXiAE6gVighiaA3rMUG8VA/UCIVAvEKNp2vtBI6DHXCn1Vjrr1wVQLxAC9QIxQQzNAT1mqLeKgXqBEKgXiAliaA7oMUO9VQzUC4RAvUBMEENzQI8Z6q1ioF4gBOoFYoIYmgN6zFBvFQP1AiFQLxATxNAc0GOGeqsYqBcIgXqBmECE5gsXLvD/2o7597//vdzDKQSot7qBeoEQqBeICURovnDhQkdHx3e/+91f/OIXv/jFLzRNO378+C9+8YuRkZF77rnHJmZ/AvVWN1AvEAL1AjFBCc07duwQzsO8Y8eOSh9aXkC91Q3UC4QET73ZbDaZTHqvk06n+XUSiYTwI/F4PB6Ps39jsZjHBm3v2j5bfQQlNF+4cKG5udnm3ebm5kBUed+HeqsdqBcICYZ6U6kU++6mUilFUdLptGVZyWSSXjhRFIWpUdd1wzCc68RiMX65oiimaeq67nQw7dT22Wg0Sq9nvRQIIgEKzc6Kb1CqvO9DvdUO1AuEBEO9lmWpqkpG5C2oqqqu69ls1rl+NBolrSaTSebXaDSaSqXYOrFYjLesoij0rqqq/Gr8TtlPKBaLqapKe1FVtfp+WgEKzbaKb4CqvO9DvdUO1AuEBEa96XSa1MgsaKuzWpaVSCQMw4i5EI1GY7GYaZq0tVQqFc1B8mbGTaVSttqwYRihUMgwDFbhZtqu1h9VsEIzX/ENUJX3fai32oF6gZDAqNeyLGpAJvWSOGk5/7WmTlkytK7r6XQ6m83SCqzebFlWMpmkais1L1PlVVEUqsiSVlllmnbH/qqqahiGruu6rkejUUVREomE1BMhhWCFZlbxDVaV932ot9qBeoGQYKiXqU7XdVVVFUWx/cs0mUqlqPLKv6BasrMZmSTK/uV7efkhVE71plKpdDpNPydbH3DVELjQTBXfYFV534d6qx2oFwgJhno9oMor+1eoXlrBpt5MJkMKV1U1kUhQIzNvdFaXFaqXbRbq9QkXLlxobW0NVpX3fai32oF6gZAqVK+iKNRizPqGheqNxWJUzdV13TTNeDxumiataZqmra/Xqd54PO5U79DQ0PDw8LFjxyRkvNzIDM29vb3Ce3Mrxde+9jVpedeg3qqmUuULfE5g1Os2eIpqqGw1Jlor51o39ZJ3+RHOVA8mv/Ldt2wh6w9OpVLs5iI2LtqyrMnJyUQisXbt2ra2tsHBwf379wtHXwcCmaFZ07Q/+gnJeYd6qxioFwgJjHrdHFZYrTcWi9GALNstvIqisBuC2R3Duq7TZqlyTNuhodT0Eee9xdlsdv/+/YODg21tbWvXrk0kEpOTk6U5EbK4ztU7MTFx8eJFOXmHeqsYqBcICYx63RD29dJrj2FWNAmGTb3xeJwqtfQv3+bM30xMPyTyumEYdLeSB8eOHRseHu7s7Ozt7R0dHZ2YmCgux5KAeicmJuTkHeqtYqBeICQA6s1ms26tzR4Nzqx31rKsWCyWSCT4lmGCVy+bgoOmyDBNk928ZF2r3mw2q6oq1Yyz2ayiKPyaHpw5c2Z0dLSnp6ezs9M0zRMnThRzWsqNZPX+r5+AekGpgHqBkACo17KslDvRaFTXdX5N+pf6ZWlhOp1WVZU3NEHqJcvyk0FSY7WzHduyrHg8TrcLs7eSyaRzy95MTk7u3r27v7+/ra1taGho//79MzMzc9qCBDRNe08WPlTv2bNnz549KyfvlVKvhNwBqBcICYZ6PchzHJNwNe/P8lVkNi9HaX9C2Wx23759g4ODzc3N69atSyQS09PTJdx+MUC9UC8oHqgXCAm8equGw4cPDw8Pt7e39/b27t69u+JdwpLV+z9+AuoFpQLqBUKgXt9x5swZ0zR7enp6enpM0zx16lRFDgPqhXpB8UC9QAjU618mJiZ2797d19fX3t4+NDR0+PBhmV3CUC/UC4oH6gVCoN4AMD09vW/fvnXr1rW1ta1bt27fvn0SuoQlq/cjPwH1glIB9QIhUG+QmJmZOXz48NDQUHt7e39//+7du8s3UwfUC/WC4oF6gRCoN6icOHHCNM3Ozs6enp6RkZEzZ86UdvtQL9QLigfqBUKg3sAzMTGxa9eu3t7e9vb24eHhw4cPl2SzUC/UC4oH6gVCoN7qYXp6OpFIrFu3rrm5eXBwcN++fcU8vEGyev/gJ6BeUCqgXiAE6q1CZmZm9u/fPzQ0VMzDG6BeqBcUD9QLhEC9VY7t4Q35dwlDvVAvKB6oFwiBeq8X6OENvb29nZ2dw8PDx44d815fsnpnZuPXv/714OAg+3dwcHBiYsJt5XvvvZd/1/bZWYF6QamAeoEQqPe6Y3JyMpFIrF27tq2tbXBw0O3hDX5T72uvvdbQ0MD+vfPOO++9997BwUGbZYmGhoZXX32V/+ydd95Jr/nlUC8oN1AvEAL1Xr9ks9n9+/e7PbzBh+pl+pyZmSHv8i+I6elpUu9rr73GlEzaXr169erVq++8887nn38e6oV65QD1AiFQL7Csax/esGvXromJCcnq/dCdy5cvHz16dHR0dOHChTt27BgfH//www83bdq0adMmenf58uVHjx6llRcuXLh8+fJQKER/R0dHP/zww6NHjy5cuJBW9tgRA+oFpQLqBUKgXnANZ86cGRkZ6enp0TRt+/btr732mpzw5CHCs2fPbtq0afny5Q0NDWTcZcuWLVy4sKGhYfny5bSEV+/Ro0cbGhro77Jly5YtW7Z8+fJly5atXr164cKFq1evhnotqFcWUC8QAvUCMZqm7dq1a+XKla2trd/+9rdfffXVd955p3zhaVYdrl69uqGh4ezZs/Tvjh07qCL74YcfPvfcc2w1p3o3bdp0+fJlqivTu1CvBfXKAuoFQqBeIIaF5qmpqZdeeumhhx5qbW196KGHXnrppfPnz5c8PM2qw4aGBqrp7tix4+jRozt27GCV2oULF1Ljs5t66eNnz56Fep3lC8oK1AuEQL1AjDM0v/POO6+++uq3v/1tXdfvu+++Xbt2nT59ek5haGpqyi08ebtwfHycKXbTpk07dux47rnnGhoaPuT6cT3Ue/bsWVoZ6vUoX1AOoF4gBOoFYrxDcyqV2r59+z333HPPPfds3749lUrlE4Zeeumll156SRievF24bNmy8fFxXrEffvhhQ0MDLeS7b5l6qYGaOoOZnvn6MdQrIXcA6gVCoF4gJs/QfPr06V27dt133326rn/3u9999dVXPVZ+6aWXNE1z2lfTtA/c+bd/+7ft27eTPvnlNPCqv7//gw8+OHnyJFv41ltvNTQ0bN++vb+/n2rJTz311N133/3BBx8sXLhw+/btHvsioF5QKqBeIATqBWI0TcvOhXPnzv3kJz958MEHm5ubN2zY8NJLL126dMm2DqmX7Msvn1W9H3zwgU299C81LH/wwQdkVgZb/rvf/Y6M+9RTT/X395On81fvnM5AYVRQvRJyB6BeIATqBWIKDs3T09N79+791re+1draunLlyn/9139944036K3R0VEtB29fb/XyrqXX27dvv/vuu0+ePPnUU081NDQ89dRTtgoxU+8HH3ywfPny5cuX0+u7777btibUC8oK1AuEQL1ATElC89GjR7dv3/4P//AP99xzj2maa9as0TiYfTVN++/ZOHLkyMKFC1955ZXly5c/+eSTbPnu3bup+suv3NDQcOTIkVdeeeXuu+/evXs3W/722283NDS8+eab3vuCekGpgHqBEKgXiCltaP7Nb37zxBNPLFmyRLsWsm8+6v3v//5vD2UeOXLE+e+sioV6QbmBeoEQqBeIKXlo/slPfqKJoA7gwhxZJqBeUCqgXiAE6gViShuap6en77nnHqF6//mf/1nTtPf9BNQLSgXUC4RAvUBMaUPzt771LRKtrusrV658/PHH9+7d+/rrr7PwVGnbXgPUC0oF1AuEQL1ATAlD87lz50ZHR48ePeq83YiFp0rb9hqgXlAqoF4gBOoFYmSGZr9N7wD1glIB9QIhUC8QA/VCvaB4oF4gBOoFYqBeqBcUD9QLhEC9QAzUC/WC4oF6gRCoF4iRrF5p+8oHqBeUCqgXCIF6gRioF+oFxQP1AiFQLxAD9UK9oHigXiAE6gViJKv3XT8B9YJSAfUCIVAvEAP1Qr2geKBeIATqBWKgXqgXFA/UC4RAvUCMZPVe9RNQLygVUC8QAvUCMVAv1AuKB+oFQqBeIAbqhXpB8UC9QAjUC8TI7H9tbW0VPsq3UrS0tLz11ltvvfWWhLxrlVOvhNyBSpUv8DlQLxAjPzS/5T8k5BrqrW6gXiAE6gVi5IfmiYmJSqv2GiYmJiTkGuqtbqBeIATqBWIQmuUA9VY3UC8QAvUCMQjNcoB6qxuoFwiBeoEYhGY5QL3VDdQLhEC9QAxCsxyg3uoG6gVCoF4gBqFZDlBvdQP1AiFQLxCD0CwHqLe6gXqBEKgXiEFolgPUW91AvUAI1AvEIDTLAeqtbqBeIATqBWIQmuUA9VY3UC8QAvUCMQjNcoB6qxuoFwiBeoEYhGY5QL3VDdQLhEC9QAxCsxyg3uoG6gVCoF4gBqFZDlBvdQP1AiFQLxCD0CwHqLe6gXqBEKgXiEFolgPUW91AvUAI1AvEIDTLAeqtbqBeIATqBWIQmuUA9VY3UC8QAvUCMQjNcoB6qxuoFwiBeoEYTdOugvJTQfVWOuvXBVAvEAL1AjEIzXKAeqsbqBcIgXqBGIRmOUC91Q3UC4RAvUAMQrMcoN7qBuoFQqBeIAahWQ5Qb3UD9QIhUC8Qg9AsB6i3uoF6gRCoF4hBaJYD1FvdQL1ACNQLxCA0ywHqrW6gXiAE6gViEJrlAPVWN1AvEAL1AjEIzXKAeqsbqBcIgXqBGIRmOUC91Q3UC4RAvUAMQrMcoN7qBuoFQqBeIAahWQ5Qb3UD9QIhUC8QU02hecOGDT09PezfpUuXHjp0KJ1OV/CQGFWp3qamprGxMbd3nW/19PR4rH/16tV0Ot3T0+NRZCMjI7YlS5cu3bBhg3Bl/q1Dhw55b7lIoF4gBOoFYqpMvatWrWL/1tfXj42NrVq1aunSpZlMpoIHdrVK1Utn2O3dpqYm/kro6myqJjZs2FBfX+/2LpVmntvk3zp06FB9fX06nV66dKntqEoC1AuEQL1ATGXVm06nS1gR2bBhA18BampqOnTo0NVc9bdUeymMalUvf2JtVdKmpiYqjkOHDjU1NWUyGVYiHmQyGV6Nhw4dcro2k8ns3buX/UvbPH78uG1Ttt2R0ekw8s5ivkC9QAjUC8RUVr319fUeVZz8GRsb27Bhw9KlS5cuXcoCblNT08jIyKFDh8bGxpqampyhWSZVoN5MJrN06dJVOZYuXRoKhZqamujfnp6epqambdu2sfVt6r2ac+HY2BjfDrGBY9WqVfX19RscjI2NZTIZdpVGC6m46+vrm5qaqNyZs2mF+vp6OiraF10oHDp0aNu2bSW3L9QLhEC9QEx1qDeTyVD1aNWqVRRbKYj39PTs3buXAm7xeymGKlCvDVLv0qVLne0WVBzkQioRpl7q7nUrdGoWdtsjXUvRrvmFzsI9fvw4bYquvVatWkUmpoM5dOhQya/DoF4gBOoFYvyj3p6eHvqXddH19PSwIHv8+HGKvFSFpTVtnXb0WRZVe3p6qNZFbZiV7e6tMvXu3buXSmFsbMzZdXr8+HFSHV0MUclu2LCBadJbvayya+spIGePjY3Z6tZsHf4iIJ1O0zeElTtrHicZl+AscEC9QAjUC8T4RL1k1m3btlF4pYWrVq0KhULUq0evjx8/TsNk9u7d29PTEwqFWBQ+fvw4hVqq3FCgp6ZIVveqYE6rTL1NTU179+4lmbmNW2Zt0SMjI3yD81V39dIY9UM5nMO46AvAWpv5Bmd6zTr7t23bFgqF+BZsuhSg78OGDRtKeykG9QIhUC8Q4xP1MqhxkvmYoqdzzXQ6PTIyEgqFWKjt6emhkLphw4bjx4+n02mqH1+9tvZcKapJvSTUq7l6JA1cYuOeGG59vVfd1cualAnnaqRe/t/6+nrnrq9evcp6/VetWkUNIXRBxh9YCYF6gRCoF4jxj3qp1lJfXx8KhdhCWkKNhxTuR0ZG6nMw9dL9oLYRzvTxbdu20Rbk5sxO1ah3ZGSEtTCzJtwNGzbwl0GEUL1kxPr6emdvK5Uy+9fW75vJZGh4FO9mdueurXxHRkaoqs03dVAjOQ28KuoUiIB6gRCoF4jRNO1K5SCDXrlyZevWraFQaGxs7MqVK42NjbTwypUrK1euDIVC3d3doVAolUrRRxobG69cuXLw4MFQKLR+/Xpa7eLFi+vXr6d/GY2NjY2NjfTBxx9/XG7mrqGC6i1hLrZu3bpy5cru7u62tra2trZQKERnuL6+fuXKlVQ0p0+fppUbGxu7u7tpZSqyxsbGgwcPjo2N7dmzZ+XKlbaNt7W1bd26lf37+OOP06cY1BnBH0x3dze97u7upi8P+5ftji28ePFifX09vXXx4sU9e/aU4pT8H1AvEAL1AjGVUi+FY4rdV3LqXbly5eOPP858fOXKlVQqRZVgtoRej42NkY/JtRcvXrxy5YpNvRT06+vrDx48ePr0aWesl0kVqHf9+vU2XdG5Zf8y6R48eLC7u7u+vn79+vWnT58+ePAglTJb4cqVKzat8h4lyPG2Y2Bfgz179vDvnj59mnbHr8yr9+LFi42Njewi4PHHH4d6gQSgXiCmUupllSQWHClYNzY2Pv74421tbWxNCpcsqo6NjbFqVnd3N19PYurds2cPq0KRy6n6JS97DqpAvU5s6mWQeul66ArnRQY1ZrB2iPXr17PSodJfv359fX29raHi4MGDpN7Tp0+zC7K2trbu7m7abCgUstmdDo8q0OTa7u5ucnBpW0GgXiAE6gViKtvgXFrWr1+/devW9evX26IqmdhWzZLMdaVeJ2NjY+uvhZVRd3e3rQJKihVeKrFPrVy50rlrW7m3tbUdPHhw5cqVtu2TiUt7KQb1AiFQLxBTTer1M1WpXr6KeZ0D9QIhUC8QA/XKoSrVCxhQLxAC9QIxCM1ygHqrG6gXCIF6gRiEZjlAvdUN1AuEQL1ADEKzHKDe6gbqBUKgXiCmra1NA+WnpaWlIqEZ5SuHSpUv8DlQL/AiA2SB8q1uKlK+wLdAvcCLS5cuVTpkXRdcunQJ5VvFVKp8gW+BegEAAACpQL0AAACAVKBeAAAAQCpQLwAAACAVqBcAAACQCtQLAAAASAXqBQAAAKQC9QIAAABSgXoBAAAAqUC9AAAAgFSgXgAAAEAqUC8AAAAgFagXAAAAkMr/BzZxI6DO5BbIAAAAAElFTkSuQmCC" alt="" />

　　该线程首先调用了两个Java方法，而第二个Java方法又调用了一个本地方法，这样导致虚拟机使用了一个本地方法栈。假设这是一个C语言栈，其间有两个C函数，第一个C函数被第二个Java方法当做本地方法调用，而这个C函数又调用了第二个C函数。之后第二个C函数又通过本地方法接口回调了一个Java方法（第三个Java方法），最终这个Java方法又调用了一个Java方法（它成为图中的当前方法）。