By applying external pressure, PbSe obtained a ZT value of approximately 1.7 at room temperature and 3 GPa, driven by the pressure-induced topological phase transition, with a dramatically enhanced PF and a slightly increased thermal conductivity [10]. Among these studies, the PF values were ...
The solution I used is to “walk” through the vector by step larger than 1, in order to retain only one value even when the values are very noisy (see the picture at the end of the post). It goes like this : findpeaks <- function(vec,bw=1,x.coo=c(1:length(vec))) { pos....
By the way, I do not understand why you say that you do not know the years ahead of plotting because this is your data ! You can always calculate the number of data in a range using cut or table... You can also simply round the min and max of your x-data to be...
Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue. We present the R pa
regimechannel regimedepth regimedischarge regimeflow regimeofundergroundwa regimevalues regimewidth reginald regin our footing regin their footing regioalhypothesis regioanalis regioantebrachialisan regiocervicalisanteri regiocervicalislatera regio colli ventralis regio cruris anterior regiofaciesbrachialis regiofac...
ranganatha range blanking range coding range energy curve range from sthto sthr range fruit range hole range needs changing range of body movemen range of neutron velo range of regulationra range of speedrange o range of swing range particle spectr range period range rata range sound spectrome ...
As a result, the pre-trained BERT model can be fine-tuned with just one additional output layer to create state-of-the-art models for a wide range of tasks, such as question answering and language inference, without substantial task-specific architecture modifications. BERT is conceptually ...
Replacing NA's within a set of similar values I have a column in a dataset looking like this: cluster_id 1 1 1 1 NA 1 NA NA 2 NA 2 NA 3 NA NA 3 cluster_id <- c("1","1","1","1","NA","1&... r dataframe na ...
> range(spe) ## Overall distribution of abundances (dominance codes) # Minimum and maximum of abundance values in the whole data set [1] 0 5 > apply(spe, 2, range) Cogo Satr Phph Babl Thth Teso Chna Pato Lele Sqce Baba Albi Gogo Eslu Pefl Rham Legi Scer Cyca Titi Abbr Icme ...
How to create random values in R up to a range of values starting from 1 - Random sampling is a technique used by almost every researcher, analyst, financial analyst, data scientist, or even a leader and if we way that almost everyone uses it at least on