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.

Functional dependency and transitive dependency are fundamental concepts in database normalization. Functional dependency refers to a situation where the value of one attribute uniquely determines the value of another attribute in a database table. For example, in a table of employees, if the employee ID uniquely determines the employee's email address, we say there is a functional dependency between ID and email. Transitive dependency, on the other hand, occurs when a non-key attribute determines another non-key attribute. For instance, if in the same employee table, the department name is determined by the manager's name, which in turn is determined by the employee ID, then we have a transitive dependency. The goal of normalization is to minimize or eliminate such dependencies to ensure data integrity and reduce redundancy.

SQL injection attacks occur when malicious code is inserted into SQL statements, exploiting vulnerabilities to manipulate the database. To prevent SQL injection, input data should be sanitized to remove any malicious code. Using stored procedures and encrypting database connections also enhance security but may not directly prevent SQL injection attacks.

When deciding between virtual machines (VMs) and containers for cloud migration, factors such as operating system dependencies and resource utilization play a crucial role. Virtual machines offer strong isolation and can run multiple operating systems, making them suitable for legacy applications with diverse OS requirements. Containers, on the other hand, are lightweight and share the host OS, leading to better resource utilization but may face challenges with legacy applications and persistent storage needs. Hence, understanding the specific needs of the applications in terms of OS dependencies and resource utilization is key to making an informed decision.

Stacks and queues find numerous real-world applications. For instance, in a text editor, a stack can be used to implement undo operations efficiently. Similarly, a queue can manage requests in a web server, ensuring fair handling based on arrival order.

The "D" in ACID stands for Durability, which ensures that once a transaction is committed, it will persist even in the face of system failures such as power outages or crashes. This is crucial for maintaining the reliability and resilience of a database system, as it guarantees that data modifications made by transactions are permanent and will not be lost due to unforeseen circumstances. Without durability, data could be lost or corrupted, leading to inconsistencies and potential data loss. Therefore, the importance of durability in ACID properties cannot be overstated, as it forms the backbone of data persistence and reliability in database management systems.

Cross-Origin Resource Sharing (CORS) is a crucial security mechanism that prevents malicious websites from accessing resources across different domains. By allowing servers to specify which origins can access their resources, CORS helps mitigate risks associated with cross-domain requests, such as cross-site scripting (XSS) and cross-site request forgery (CSRF). It enhances web security by enforcing browser restrictions and ensuring that only authorized domains can interact with sensitive data.

Resource preemption involves forcefully taking resources from processes that are deadlocked to break the deadlock situation. This is a technique used in deadlock handling in operating systems.

Demand paging is a virtual memory management technique where pages are loaded into memory only when they are required, thus optimizing memory utilization. When a process is initiated, only essential pages are loaded initially. As the process executes and requires more pages, they are fetched from secondary storage. This approach minimizes initial load time and allows for more efficient use of available memory.