Maid of the Mist, Niagara, U.S.A.

The description of the image is "(6) Majestically Grand - the Falls from the 'Maid of the Mist,' Niagara, U.S.A.". The reverse of the image reads "You are on the deck of the small but sturdy little steamer that runs along near the foot of the falls. At this moment you are pretty nearly mid-stream, looking south. The American shore are up over your left shoulder. That tall, dark cliff at the extreme left of what you see is Goat Island. The people up there outlined against the sky look like dolls and no wonder; they are more than 160 feet above your head. Some of them are looking off over the unspeakable grandeurs of the Horseshoe Fall there at the right; some are without doubt looking down at the very boat and remarking that the passengers look like dolls. It is an awesome experience to go so near that never-ceasing downpour of waters from the sky. The air is full of the roar and iridescent spray, and it seems as if the boat must be drawn in under the overwhelming floods never to rise again. Yet, curiously enough, the river right around the boat is not so madly excited as you might expect. It seems more like some great creature, dazed, bewildered, stunned by some incredible experience and not yet quite aware of what has happened. (When it gets down into the Whirlpool Rapids, two miles below here, it is dramatically alive to its situation!) The gigantic curve of the cliffs, reaching in up-stream straight ahead, makes a contour line of over 3000 feet before it comes up against the Canadian banks on the west (right). Geologists say that the Falls ages ago must have been at least seven miles farther down the river (behind you) and have gradually won their way back. Even now the curve of the Horseshoe is worn away from two to four feet in a year. No wonder; 12, 000, 000 cubic feet of water (about 375, 000 tons) sweep over the rocks in one minute, and the same the next minute and the next and the next. See Niagara through the Stereoscope, with special maps locating all the landmarks about the Falls.

Assessing the Reproducibility of Clustering of Molecular Dynamics Conformations on Self-Organizing Maps

The goal of most clustering algorithms is to find the optimal number of clusters (i.e. fewest number of clusters). However, analysis of molecular conformations of biological macromolecules obtained from computer simulations may benefit from a larger array of clusters. The Self-Organizing Map (SOM) clustering method has the advantage of generating large numbers of clusters, but often gives ambiguous results. In this work, SOMs have been shown to be reproducible when the same conformational dataset is independently clustered multiple times (~100), with the help of the Cramérs V-index (C_v). The ability of C_v to determine which SOMs are reproduced is generalizable across different SOM source codes. The conformational ensembles produced from MD (molecular dynamics) and REMD (replica exchange molecular dynamics) simulations of the penta peptide Met-enkephalin (MET) and the 34 amino acid protein human Parathyroid Hormone (hPTH) were used to evaluate SOM reproducibility. The training length for the SOM has a huge impact on the reproducibility. Analysis of MET conformational data definitively determined that toroidal SOMs cluster data better than bordered maps due to the fact that toroidal maps do not have an edge effect. For the source code from MATLAB, it was determined that the learning rate function should be LINEAR with an initial learning rate factor of 0.05 and the SOM should be trained by a sequential algorithm. The trained SOMs can be used as a supervised classification for another dataset. The toroidal 10×10 hexagonal SOMs produced from the MATLAB program for hPTH conformational data produced three sets of reproducible clusters (27%, 15%, and 13% of 100 independent runs) which find similar partitionings to those of smaller 6×6 SOMs. The χ^2 values produced as part of the C_v calculation were used to locate clusters with identical conformational memberships on independently trained SOMs, even those with different dimensions. The χ^2 values could relate the different SOM partitionings to each other.