20. Unseen Bits 3
Since the fall of the Berlin Wall, Europeans have seen a steady resurgence of Neo-Nazi and anti-immigrant activities. While a great deal of attention has been focused on racist "skinheads", particularly in the eastern half of Germany, Sweden, and in Russia, far less attention has been paid to a loosely defined grass-roots, ANTI-racism Movement that has surfaced across the continent. Activists are working largely unseen to counter the proponents of hate. It is their story that I report in this four-part series titled "Standing Up To Hate in Europe". Part One: In the Spirit of Martin Luther King, Jr. a German activist describes how MLK influenced her life and her life-long struggle against right-wing extremism and anti-Semitism. 7 min, 19 sec. Phillip Martin, Reporter.
20. Unseen Bits 3
I guess the thing that interests me, @Santalives, is the motivation. I've read all of your posts in this thread and I'm simply left with that one question: what motivates you here? Genuinely. Like a drowning man in a flooding river you grasp at bits of driftwood bobbing by, when the best advice all along was to stay away from the water because there was a flood coming.I've also seen a lot of this type of reasoning with regard to COVID 19. Remarkably so, in fact. Is this the bargaining stage of grief?
As you say, it is all about the unseen audience. The troll is partly aware of that too. Yet IMO the troll's greater motivation is to "act out", to vent his anger. Trolls are angry people. They don't all go to WUWT blogsite to vent their anger well, not full time anyway.
The manuscript " Not just contaminants: Uncovering unseen microbial biodiversity from plant DNA banks," by E M Datlof, A S Amend, K Earl, J Hayward, C W Morden, R Wade, G Zahn, N A Hynson, gives an innovative approach to the study of the microbial diversity of Hawaiian Island using samples collected from a germplasm bank.The current works presents several aspects that should be improved upon before publication.
We can use Topic Model for two major purposes.The basic one is to discover topics from a set of documents as a result of trained model,and the more advanced one is to infer topic distributions for unseen documents by using trained model.
We named the document in the former purpose (used for model training) as document in the model,and the document in the later purpose (unseen document during training) as document out of the model. 041b061a72