Output data (predicted pond temperature) was compared to measured pond temperature collected from the warmwater ponds at the Louisiana State University Agricultural Center Aquaculture Research Station, Baton Rouge, Louisiana.
Comparing these results with the available data for pond ash reported by Jakka et al. [12], it can be observed that Panki and Panipat pond ash shows higher compressibility value.
We obtained these data by pond edge surveys during daylight hours, approximately every two weeks throughout the duration of the breeding and emergence season.
Additional data on pond dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data.
Metagenomics data from pond sediment and recently surveyed HCH adulterated soils revealed the in situ enrichment of integron associated transposase gene (TnpA6100) across increasing HCH contamination (0.7 to 450 mg HCH g−1 of soil).
Tests on simulated data (S.L.K. Pond and S.D.W. Frost, methods available in [ 59]) show that p values less than or equal to 0.1 identify nearly all true positives with a false positive rate generally below the nominal p value; for actual data, the number of true positives at a given false positive rate is lower.
While we were able to infer the presence of additive genetic variance for morphometric traits from two generations of pond data, more stringent analyses including F2 and F3 are planned although data are not yet available due to the relatively long generation time (approximately 2.5 years).
However, because deep learning models drink data by the pond rather than the gallon, the company pushed out an additional 183GB of driving data.
They also used pond data collected during the International Biological Program in the 1970s, including areal extent estimates, water depths, and pond depths, and compared those with field data collected from 2011 to 2013.
These adults were allowed to spawn freely and, together with their offspring, comprise the Pond data set.
