The value of a degree (Bachelors or Masters) largely depends on your career goals, industry expectations, and personal interest in continued learning. In programming, for instance, obtaining a broader set of skills and practical problem-solving can sometimes weigh more than advanced academic degrees. A Bachelor’s degree in Computer Science or related fields provides foundational programming skills, while a Master's degree allows for specialization in a certain area like data science or machine learning.

Many tech companies do value skills and experience over degrees. However, a Masters can provide a deeper understanding, potentially leading to higher level positions or jobs at specific companies that value a more formal education.

Still, it's essential to consider several factors such as the time and financial investment required for a Masters, the potential delay in gaining professional experience, and the balance between theoretical knowledge and practical skills. Ultimately, neither degree is categorically better; it depends on the individual and situation.

Neither a Computer Science degree nor a Data Science degree is inherently better than the other. The best choice largely depends on your career goals and interests.

Computer Science is a broad field that provides foundational knowledge in areas such as algorithms, data structures, software design, and computational theory. This makes a CS degree more versatile. It also gives opportunities to specialize in a wide variety of areas within computing, from artificial intelligence to systems architecture.

On the other hand, a Data Science degree focuses on extracting insights from large volumes of data. You'll learn statistical and computational methods, data visualization, machine learning, predictive modeling, and related areas. This is ideal if you're interested in roles like Data Analyst, Data Scientist, or Machine Learning Engineer.

Professionally, both degrees can lead to high paying jobs and have a high demand in the current job market. However, do note that many CS programs are richer in their offerings simply because the discipline has been around longer.

Before choosing one over the other, consider whether you are more interested in broad computing principles or in the specialized task of making large-scale data informative and actionable. Look into the curriculum of specific programs, talk to professionals in the field and consider your long-term career goals. Work experience, personal projects and continuous learning are also key components of success in both fields.

The value of a degree (bachelor's or master's) depends on your career goals, the field in which you plan to work, and your personal aspirations. In the realm of programming or Information Technology, practical skills, experience, adaptation to rapidly evolving technology and frameworks often weigh heavier than degrees. However, a master's degree can offer advanced knowledge, research opportunities, and potentially more prestige, which can be better if you're aiming for senior-level or specialised roles.

Generally, a bachelor's degree establishes foundational knowledge and a launching point into the field, while a master's degree provides an opportunity to specialise and delve deeper. But remember, the tech-industry values skills and experience, often more than formal education. So, the 'better' choice is entirely dependent on your individual career path and goals.

Remember to always keep learning - whether that is through a degree, online courses, or hands-on coding projects. Your goal should be to remain current, adaptable, and skilled.

Multithreading in Java is a feature that allows concurrent execution of two or more parts of a program for maximum utilization of CPU. Each part of such a program is called a thread, and they are lightweight sub-processes which share a common memory area, known as the process's heap memory.

Threads can exist in several states (New, Runnable, Waiting, etc.), and you can control them through several methods of the Thread class like start(), run(), sleep(), isAlive(), join(), etc.

Here is a simple way to create a thread in Java:

```java
// Step 1: Define a Thread
class MultithreadingDemo extends Thread{
public void run(){
try{
System.out.println ("Thread "+ Thread.currentThread().getId() + " is running");
} catch (Exception e){
System.out.println ("Exception is caught");
}
}
}

// Step 2: Using the defined Thread
public class Multithread{
public static void main(String[] args){
int n = 8; // Number of threads
for (int i=0; i<n; i++){
MultithreadingDemo object = new MultithreadingDemo();
object.start();
}
}
}
```
The `MultithreadingDemo` extends the java.lang.Thread class making it a Thread. Inside the `Multithread` class in the main method, we create an instance of `MultithreadingDemo` and start it with the `start()` call. This causes `run()` to be called in a thread separately, that prints out the thread ID.

However, remember that it's recommended to implement the Runnable interface over extending the Thread class, as Java doesn't support multiple inheritances.

Use Java Executor Framework for better control and management of threads; it provides thread pool management and scheduling capabilities. Using java.util.concurrent package, you can coordinate and control thread execution in concurrent Java applications.

Be careful with thread synchronization and communication to avoid thread interference and memory consistency errors. If threads are not properly synchronized, it may lead to a condition called race condition.

In order to connect a Java application with a MySQL database, you can use JDBC (Java Database Connectivity), which is a standard Java API for database-independent connectivity between the Java programming language and a wide range of databases.

Here are the steps you need to follow:

1. Add JDBC Library: First, you need to add the MySQL connector (JDBC driver) in your Java project. You can download it from the MySQL official site and add it to your project's classpath.

```java
//Example
import java.sql.*;

2. Load Driver: You need to load the MySQL JDBC driver using forName() method of the class named Class.

```java
//Example
Class.forName("com.mysql.jdbc.Driver");
```

3. Establish Connection: Now you can connect to your MySQL database using the method getConnection() from DriverManager class with the MySQL URL and your database credentials (username, password).

```java
//Example
Connection connection = DriverManager.getConnection(
"jdbc:mysql://localhost:3306/yourDatabaseName", "yourUsername", "yourPassword");
```

4. Execute Queries: Now, you can execute SQL queries (select, insert, update, etc.) using Statement or PreparedStatement.

```java
//Example
Statement stmt = connection.createStatement();
ResultSet rs = stmt.executeQuery("SELECT * FROM your_table_name");
While(rs.next()) {
System.out.println(rs.getString("your_column_name"));
}
```

5. Close Connection: Finally, remember to close the connection to the database once you're done.

```java
//Example
connection.close();
```

This is a simplified representation. In production-level code, it would be a good practice to handle SQL exceptions and any errors associated with database interactions. You can also use a connection pool, utility classes or frameworks like Hibernate to simplify database operations.

Remember, it's not advisable to hard-code sensitive data like your username and password. Consider storing them in a configuration file or environment variables.

A Java Bean is essentially a standard Java class which adheres to certain conventions. These conventions include:

1. It should have a no-arg constructor - a constructor with no arguments. This allows easy instantiation.

2. The class properties (or instance variables) must be private to ensure data encapsulation, and accessed via getter and setter methods that follow a naming convention. For instance, if the instance variable is "name", its getter method would be "getName" and setter would be "setName".

3. The class should be Serializable. This means the class should implement the java.io.Serializable interface, allowing the state of an object to be saved or transported.

Java Beans are commonly used in Java-based software components (JSP, Servlets, EJB etc.) because they can be easily reused and their properties, events, and methods can be manipulated in a standard way.

Here's a very simple example of a Java Bean:

```java
public class Employee implements Serializable {
private String name;
private int age;

// No-arg constructor
public Employee() { }

// Getter and setter for 'name'
public String getName() { return this.name; }
public void setName(String name) { this.name = name; }

// Getter and setter for 'age'
public int getAge() { return this.age; }
public void setAge(int age) { this.age = age; }
}
```

This class `Employee` is a Java Bean. It has a no arg-constructor, private instance variables `name` and `age` with the respective getter and setter methods, and it implements `Serializable`. Now, this bean can be reused and manipulated in various parts of your application.

In Python, you can emulate Java-like interfaces using abstract base classes (abc module). Here is a brief summary on how you can achieve this:

```python
from abc import ABC, abstractmethod

class MyInterface(ABC):
@abstractmethod
def method_to_implement(self):
pass
```

Here, we are declaring an abstract method `method_to_implement()`. An abstract method is a method declared in an abstract class but doesn't contain any implementation. Subclasses of this abstract class are generally expected to provide an implementation for this method.

Now, any class that subclasses `MyInterface` has to implement `method_to_implement()`. If it doesn't, Python will raise a `TypeError` when you try to instantiate it.

```python
class MyClass(MyInterface):
def method_to_implement(self):
return "Implemented method"
```

But remember, Python's philosophy is "we are all consenting adults here" which means the language trusts its users not to mess things up. The concept of interfaces is contrary to Python's dynamic typing system, but if you feel a necessity to strictly enforce interface patterns, this is how you can approach it.

Efficiency-cores, also known as "little cores" in ARM's big.LITTLE architecture, are designed to be more power-efficient, meaning they consume less energy to perform tasks. This is achieved through multiple means:

1. Lower Clock Speeds: Efficiency-cores typically run at lower clock speeds compared to performance cores, which are geared towards maximum processing power. Since power consumption is proportional to the square of the frequency, operating at a lower frequency greatly reduces power consumption.

2. Simpler Design: Efficiency-cores are generally simpler and smaller in design compared to performance-cores, reducing the amount of energy required to perform a computation.

3. Optimized for Common Tasks: These cores are optimized to efficiently carry out the most common, less-demanding tasks, such as background syncing, email, browsing etc.

This combination of performance and efficiency allows for better battery life without sacrificing usability. Devices can switch between performance cores and efficiency cores depending on the computational task at hand. For intensive tasks like gaming or video editing, a device might use more power-hungry performance cores. But for simpler tasks, the device will rely on the efficiency cores, thereby saving power.

No, not all Tesla models have a single motor per wheel. Tesla Model S and Model 3 typically come with either one motor (rear-wheel drive) or two motors (dual motor all-wheel drive). However, the new Tesla Roadster and Tesla Cybertruck are equipped with a tri-motor setup, one for each rear wheel and one for both front wheels. The Tesla Model S Plaid also has a three motor system. None of them, however, have a distinct motor for each wheel. The purpose of having these multiple motors is to provide better handling, traction, and acceleration performance. It's important to note that specific configurations may vary based on the model and options selected upon purchasing.

This error is often due to an incorrect installation or import of the Python Imaging Library (PIL) module. PIL.Image should indeed have an attribute called ANTIALIAS. The ‘ANTIALIAS’ is a resampling filter. It can be used for resizing images and is generally the highest quality resampling filter, but it may be slower than others.

Here are ways to fix this issue:

1. Ensure PIL is correctly installed: Uninstall it first with `pip uninstall PIL` and `pip uninstall Pillow`. Then, reinstall Pillow (which is an improved version of PIL) with `pip install Pillow`

2. Correct your import: When using Pillow, you should import modules in this way: `from PIL import Image`.

3. Use ANTIALIAS filter: After properly importing Image module from PIL, you can use ANTIALIAS filter as a parameter in resize method like this: `image = image.resize((width, height), Image.ANTIALIAS)`.

So your top part of the code should look something like this:

```python
from PIL import Image

image = Image.open('your-image-path.jpg')
image = image.resize((width, height), Image.ANTIALIAS)
```

4. If the issue persists, there may be some issues with your installation of Python or the way your environment is setup. Consider checking your system path, or possibly reinstalling Python and PIL again.

If you're not resizing images and still get this error, it could be linked to an entirely different issue, which we might need more details to diagnose.

Remember, always make sure to keep your libraries updated to the latest version. The current stable version for Pillow is 8.2.0, as of April 2021.