Question: When was the response deadline?
About the article "Nanking Massacre", section "Assault and capture of Nanking".

Candidate passages:
The deadline for voting was 15 November 2013.
However, on 20 November 2013, FIFA announced that voting was extended to 29 November 2013 for "after receiving a response of less than 50% from eligible voters before the original deadline."
It was also announced that any vote cast before the first deadline can be changed to "take into account recent performances."
The winners were announced on 13 January 2014. 
Deadline(s) or The Deadline(s) may refer to: Time limit  
The deadline for teams to complete trades was Wednesday October 9 at 3:59pm EDT. 
A system that correctly perceives the serialization and timing constraints associated with transactions with soft or firm deadlines, takes advantage of absolute consistency.
Another way of making sure that data is absolute is using relative constraints.
Relative constraints ensure transactions enter into the system at the same time as the rest of the group that the data transaction is associated with.
Using the mechanisms of absolute and relative constraints greatly ensures the accuracy of data.
An additional way of dealing with conflict resolution in a real-time database system besides deadlines is a wait policy method.
This process helps ensure the latest information in time critical systems.
The policy avoids conflict by asking all non-requesting blocks to wait until the most essential block of data is processed.
While studies in labs have found that data-deadline based policies do not improve performance significantly, the forced wait policy can improve performance by 50 percent.
The forced wait policy may involve waiting for higher priority transactions to process in order to prevent deadlock.
Another example of when data can be delayed is when a block of data is about to expire.
The forced wait policy delays processing until the data is updated using new input data.
The latter method helps increase the accuracy of the system and can cut down on the number of necessary processes that are aborted.
Generally relying on wait policies is a not optimal.
It is necessary to discuss the formation of deadlines.
Deadlines are the constraints for soon-to-be replaced data accessed by the transaction.
Deadlines can be either observant or predictive.
In an observant deadline system, all unfinished transactions are examined and the processor determines whether any had met its deadline.
Problems arise in this method because of variations caused by seek time variations, buffer management and page faults (An Overview of Real-Time Database Systems).
A more stable way of organizing deadlines is the predictive method.
It builds a candidate schedule and determines if a transaction would miss its deadline under the schedule.
The type of response to a missed deadline depends on whether the deadline is hard, soft, or firm.
Hard deadlines require that each data packet reach its destination before the packet has expired and if not, the process could be lost, causing a possible problem.
Problems like these are not very common because omnipotence of the system is required before assigning deadlines to determine worst case.
This is very hard to do and if something unexpected happens to the system such as a minute hardware glitch, it could throw the data off.
For soft or firm deadlines, missing a deadline can lead to a degraded performance but not a catastrophe.
A soft deadline meets as many deadlines as possible.
However, no guarantee exists that the system can meet all deadlines.
Should a transaction miss its deadline, the system has more flexibility and the transaction may increase in importance.
Below is a description of these responses:Hard deadline: If not meeting deadlines creates problems, a hard deadline is best.
It is periodic, meaning that it enters the database on a regular rhythmic pattern.
An example is data gathered by a sensor.
These are often used in life critical systems.
Firm deadline: Firm deadlines appear to be similar to hard deadlines yet they differ from hard deadlines because firm deadlines measure how important it is to complete the transaction at some point after the transaction arrives.
Sometimes completing a transaction after its deadline has expired may be harmful or not helpful, and both the firm and hard deadlines consider this.
An example of a firm deadline is an autopilot system.
Soft deadline: If meeting time constrains is desirable but missing deadlines do not cause serious damage, a soft deadline may be best.
It operates on an aperiodic or irregular schedule.
In fact, the arrival of each time for each task is unknown.
An example is an operator switchboard for a telephone.
Hard deadline processes abort transactions that have passed the deadline, improving the system by cleaning out clutter that needs to be processed.
Processes can clear out not only the transactions with expired deadlines but also transactions with the longest deadlines, assuming that once they reach the processor they would be obsolete.
This means other transactions should be of higher priority.
In addition, a system can remove the least critical transactions.
When I was pre-selecting classes on during a high traffic period, a field in the database can become so busy with registration requests that it was unavailable for a while and the result of my transaction was a display of the SQL query sent and a message that said that the data is currently unavailable.
This error is caused by the checker, a mechanism that checks the condition of the rules, and the rule that occurred before it.
The goal of scheduling periods and deadlines is to update transactions guaranteed to complete before their deadline in such a way that the workload is minimal.
With large real-time databases, buffering functions can help improve performance tremendously.
A buffer is part of the database that is stored in main memory to reduce transaction response time.
In order to reduce disk input and output transactions, a certain number of buffers should be allocated.
Sometimes multiversions are stored in buffers when the data block the transaction needs is currently in use.
Later, the database has the data appended to it.
Different strategies allocate buffers and must balance between taking an excessive amount of memory and having everything in one buffer that it has to search for.
The goal is to eliminate search time and distribute the resources between buffer frames in order to access data quickly.
A buffer manager is capable of allocating more memory, if necessary, to improve response time.
The buffer manager can even determine whether a transaction that it has should advance.
Buffering can improve speed in real-time systems. 
Detroit acquired Lynn for their pennant drive, which also proved unsuccessful.
There was some initial controversy with this trade; though the trade was made on the day of the trading deadline, while Lynn was en route to Detroit, he was technically not in "Detroit airspace" when the deadline passed, so he was ruled ineligible for the postseason.
MLB Commissioner Fay Vincent later overruled this decision, declaring that as long as the transaction was completed by the deadline, the player need not physically be in the new team's city to be eligible to play in the playoffs.
Following a disappointing season, Lynn ended his career with one season in San Diego (), retiring at the age of 38.