Imperial submitted a total of 1,257 staff across 14 units of assessment to the 2014 Research Excellence Framework (REF) assessment. In the REF results 46% of Imperial's submitted research was classified as 4*, 44% as 3*, 9% as 2* and 1% as 1*, giving an overall GPA of 3.36. In rankings produced by Times Higher Education based upon the REF results Imperial was ranked 2nd overall for GPA and 8th for "research power" (compared to 6th and 7th respectively in the equivalent rankings for the RAE 2008).
If it is possible to answer this question, answer it for me (else, reply "unanswerable"): How many staff were submitted over the 16 units of assessment?
Ah, so.. unanswerable

Over time, the relative power of these five nations fluctuated, which by the dawn of the 20th century had served to create an entirely different balance of power. Some, such as the United Kingdom and Prussia (as the founder of the newly formed German state), experienced continued economic growth and political power. Others, such as Russia and Austria-Hungary, stagnated. At the same time, other states were emerging and expanding in power, largely through the process of industrialization. These countries seeking to attain great power status were: Italy after the Risorgimento, Japan after the Meiji Restoration, and the United States after its civil war. By the dawn of the 20th century, the balance of world power had changed substantially since the Congress of Vienna. The Eight-Nation Alliance was a belligerent alliance of eight nations against the Boxer Rebellion in China. It formed in 1900 and consisted of the five Congress powers plus Italy, Japan, and the United States, representing the great powers at the beginning of 20th century.
If it is possible to answer this question, answer it for me (else, reply "unanswerable"): Which of the 5 powers were beginning to stagnate in early 20th century?
Ah, so.. Russia and Austria-Hungary

Genetics compression algorithms are the latest generation of lossless algorithms that compress data (typically sequences of nucleotides) using both conventional compression algorithms and genetic algorithms adapted to the specific datatype. In 2012, a team of scientists from Johns Hopkins University published a genetic compression algorithm that does not use a reference genome for compression. HAPZIPPER was tailored for HapMap data and achieves over 20-fold compression (95% reduction in file size), providing 2- to 4-fold better compression and in much faster time than the leading general-purpose compression utilities. For this, Chanda, Elhaik, and Bader introduced MAF based encoding (MAFE), which reduces the heterogeneity of the dataset by sorting SNPs by their minor allele frequency, thus homogenizing the dataset. Other algorithms in 2009 and 2013 (DNAZip and GenomeZip) have compression ratios of up to 1200-foldallowing 6 billion basepair diploid human genomes to be stored in 2.5 megabytes (relative to a reference genome or averaged over many genomes).
If it is possible to answer this question, answer it for me (else, reply "unanswerable"): What encoding reduces the heterogenelty of a dataset by sorting megabytes?
Ah, so..
unanswerable