Encapsulation is one of the main principles of Object-Oriented Programming (OOP). It refers to the bundling of data (attributes) and methods (functions) that operate on the data into a single unit or class. Encapsulation helps in hiding the internal complexities of an object and allows access to only the necessary parts through well-defined interfaces. This concept promotes modularity, reusability, and easier maintenance of code in OOP.

A clustered index stores a copy of the indexed columns along with the index data structure itself. This arrangement of data storage directly corresponds to the order of the indexed columns, making retrieval of data faster when queries align with the index order. However, it's important to note that a table can only have one clustered index, typically on the primary key column.

Hashing is used to ensure data integrity by generating a fixed-size hash value for a given input data. This hash value can be compared to verify data integrity during transmission or storage.

802.11a operates in the 5 GHz band, providing faster data rates but shorter range. 802.11b operates in the 2.4 GHz band with slower speeds but better range. 802.11g combines elements of both for improved speed and range.

Regression testing involves re-running test cases to ensure that new changes haven't adversely affected existing functionalities. It verifies that the code behavior remains unchanged post-modifications. This is crucial in software development to catch bugs introduced inadvertently during updates and to maintain overall system reliability and stability. It also helps in ensuring that new features don't break existing functionalities.

The Adapter design pattern allows objects with incompatible interfaces to work together. It acts as a bridge between the client and the target class, enabling communication and interaction. This pattern is useful when integrating existing systems that have incompatible interfaces or when designing reusable libraries that need to work with multiple interfaces.

Graph databases are ideal for handling complex relationships as they excel in managing interconnected data. Nodes represent entities like users, and edges represent relationships between them. This structure is well-suited for social networks where users have varied connections. Document databases are better suited for semi-structured data and may not handle complex relationships as effectively as graph databases. Columnar databases are optimized for analytical queries, not for complex relationship handling. Key-value databases are efficient for simple data retrieval but lack the structure needed for complex relationships.

Data normalization involves structuring data in a database to reduce redundancy and dependency. This process ensures that each piece of data is stored in only one place and eliminates the potential for inconsistent information. It helps improve data integrity, reduce storage space, and streamline data retrieval and manipulation processes.

The Transport layer in the OSI Model is responsible for segmenting and reassembling data packets to ensure reliable and efficient communication between end systems. It also handles flow control, error checking, and data integrity to guarantee that information is delivered accurately.

Server-side rendering (SSR) offers advantages like improved performance and SEO, but it also comes with challenges such as setup complexity and resource requirements. Both React and Angular support SSR, and developers must weigh the pros and cons carefully based on project requirements and their team's expertise to decide whether to implement SSR in their applications.