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Hypoxic zones can occur naturally, but scientists are concerned about the areas created or enhanced by human activity. There are many physical, chemical, and biological factors that combine to create dead zones, but nutrient pollution is the primary cause of those zones created by humans. Excess nutrients that run off land or are piped as wastewater into rivers and coasts can stimulate an overgrowth of algae, which then sinks and decomposes in the water. The decomposition process consumes oxygen and depletes the supply available to healthy marine life.

Property owners are responsible for removing dead animals on their property. Do not bury dead animals. If you find a dead animal, you can put the animal in a sealed trash bag and place it in the trash. You can also bring the dead animal to ACCT Philly for disposal.

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The "dead-donor rule" requires patients to be declared dead before the removal of life-sustaining organs for transplantation. The concept of brain death was developed, in part, to allow patients with devastating neurologic injury to be declared dead before the occurrence of cardiopulmonary arrest. Brain death is essential to current practices of organ retrieval because it legitimates organ removal from bodies that continue to have circulation and respiration, thereby avoiding ischemic injury to the organs. The concept of brain death has long been recognized, however, to be plagued with serious inconsistencies and contradictions. Indeed, the concept fails to correspond to any coherent biological or philosophical understanding of death. We review the evidence and arguments that expose these problems and present an alternative ethical framework to guide the procurement of transplantable organs. This alternative is based not on brain death and the dead-donor rule, but on the ethical principles of nonmaleficence (the duty not to harm, or primum non nocere) and respect for persons. We propose that individuals who desire to donate their organs and who are either neurologically devastated or imminently dying should be allowed to donate their organs, without first being declared dead. Advantages of this approach are that (unlike the dead-donor rule) it focuses on the most salient ethical issues at stake, and (unlike the concept of brain death) it avoids conceptual confusion and inconsistencies. Finally, we point out parallel developments, both domestically and abroad, that reflect both implicit and explicit support for our proposal.

A dead ball is a ball that is out of play. The ruling of a dead ball halts the game and no plays can legally occur until the umpire resumes the game, though baserunners can advance as the result of acts that occurred while the ball was live. Dead balls are frequent occurrences during a game, and the dead-ball period typically does not last long before the ball is put back into play.

Dead balls most frequently occur when a batted ball becomes a foul ball or a fair ball is hit out of the playing field. Other common instances in which the ball is ruled dead include a batter being hit by a pitch, a balk, an illegal collision at home plate, obstruction of a baserunner, interference with a fielder's right of way, spectator interference, a batter or runner being granted time out by the umpire and a fair batted ball striking an umpire or runner.

If a fair ball gets lodged in the outfield wall padding -- or the ivy, in the case of Wrigley Field -- it is a ground-rule double. On all ground-rule doubles, the ball is dead, the batter-runner goes to second and all additional runners are permitted to move up two bases from the one they occupied at the time of the pitch.

Amazon SQS supports dead-letter queues (DLQ), which other queues (source queues) can target for messages that can't be processed (consumed) successfully. Dead-letter queues are useful for debugging your application or messaging system because they let you isolate unconsumed messages to determine why their processing didn't succeed. For information about configuring a dead-letter queue using the Amazon SQS console, see Configuring a dead-letter queue(console). Once you have debugged the consumer application or the consumer application is available to consume the message, you can use the dead-letter queue redrive capability to move the messages back to the source queue.

Sometimes, messages can't be processed because of a variety of possible issues, such as erroneous conditions within the producer or consumer application or an unexpected state change that causes an issue with your application code. For example, if a user places a web order with a particular product ID, but the product ID is deleted, the web store's code fails and displays an error, and the message with the order request is sent to a dead-letter queue.

The redrive policy specifies the source queue, the dead-letter queue, and the conditions under which Amazon SQS moves messages from the former to the latter if the consumer of the source queue fails to process a message a specified number of times. The maxReceiveCount is the number of times a consumer tries receiving a message from a queue without deleting it before being moved to the dead-letter queue. Setting the maxReceiveCount to a low value such as 1 would result in any failure to receive a message to cause the message to be moved to the dead-letter queue. Such failures include network errors and client dependency errors. To ensure that your system is resilient against errors, set the maxReceiveCount high enough to allow for sufficient retries.

The redrive allow policy specifies which source queues can access the dead-letter queue. This policy applies to a potential dead-letter queue. You can choose whether to allow all source queues, allow specific source queues, or deny all source queues. The default is to allow all source queues to use the dead-letter queue. If you choose to allow specific queues (using the byQueue option), you can specify up to 10 source queues using the source queue Amazon Resource Name (ARN). If you specify denyAll, the queue cannot be used as a dead-letter queue.

To specify a dead-letter queue, you can use the console or the AWS SDKs. You must do this for each queue that sends messages to a dead-letter queue. Multiple queues of the same type can target a single dead-letter queue. For more information, see Configuring a dead-letter queue(console) and the RedrivePolicy and RedriveAllowPolicy attributes of the CreateQueue or SetQueueAttributes action.

You must use the same AWS account to create the dead-letter queue and the other queues that send messages to the dead-letter queue. Also, dead-letter queues must reside in the same region as the other queues that use the dead-letter queue. For example, if you create a queue in the US East (Ohio) region and you want to use a dead-letter queue with that queue, the second queue must also be in the US East (Ohio) region.

For standard queues, the expiration of a message is always based on its original enqueue timestamp. When a message is moved to a dead-letter queue, the enqueue timestamp is unchanged. The ApproximateAgeOfOldestMessage metric indicates when the message moved to the dead-letter queue, not when the message was originally sent. For example, assume that a message spends 1 day in the original queue before it's moved to a dead-letter queue. If the dead-letter queue's retention period is 4 days, the message is deleted from the dead-letter queue after 3 days and the ApproximateAgeOfOldestMessage is 3 days. Thus, it is a best practice to always set the retention period of a dead-letter queue to be longer than the retention period of the original queue.

For FIFO queues, the enqueue timestamp resets when the message is moved to a dead-letter queue. The ApproximateAgeOfOldestMessage metric indicates when the message moved to the dead-letter queue. In the same example above, the message is deleted from the dead-letter queue after 4 days and the ApproximateAgeOfOldestMessage is 4 days.

The main task of a dead-letter queue is to handle the lifecycle of unconsumed messages. A dead-letter queue lets you set aside and isolate messages that can't be processed correctly to determine why their processing didn't succeed. Setting up a dead-letter queue allows you to do the following:

In a system that processes thousands of messages, having a large number of messages that the consumer repeatedly fails to acknowledge and delete might increase costs and place extra load on the hardware. Instead of trying to process failing messages until they expire, it is better to move them to a dead-letter queue after a few processing attempts.

Standard queues allow a high number of in flight messages. If the majority of your messages can't be consumed and aren't sent to a dead-letter queue, your rate of processing valid messages can slow down. Thus, to maintain the efficiency of your queue, make sure that your application correctly handles message processing.

FIFO queues provide exactly-once processing by consuming messages in sequence from a message group. Thus, although the consumer can continue to retrieve ordered messages from another message group, the first message group remains unavailable until the message blocking the queue is processed successfully or moved to a dead-letter queue.

Do use dead-letter queues with standard queues. You should always take advantage of dead-letter queues when your applications don't depend on ordering. Dead-letter queues can help you troubleshoot incorrect message transmission operations.

Don't use a dead-letter queue with standard queues when you want to be able to keep retrying the transmission of a message indefinitely. For example, don't use a dead-letter queue if your program must wait for a dependent process to become active or available.

Don't use a dead-letter queue with a FIFO queue if you don't want to break the exact order of messages or operations. For example, don't use a dead-letter queue with instructions in an Edit Decision List (EDL) for a video editing suite, where changing the order of edits changes the context of subsequent edits. be457b7860