We focus our analysis in the southwestern Annapurna Range of the central Nepalese Himalaya where detailed geologic maps, topographic data, field observations, and aerial photographs are available. We identified knickzones in our study area from normalized river steepness indices (kvalues) extracted from...
We used the Normalized Difference Vegetation Index (NDVI), a graphical indication of the presence of green vegetation, as a proxy for food availability32. We found no significant relationship between the size and the average NDVI value of individual home ranges either overall (t = −0.95,...
Average True Range Normalized Average True Range True Range Time Period Execute IndicatorThe output start index for this execution was one with a total number of output elements of sixty. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Well...
Serum creatinine normalized to ≤1.2 mg/dl in 14 patients (78%). Partial recovery (defined as a >50% reduction of serum creatinine from initial presentation and serum creatinine >1.2 mg/dl at last follow-up) was seen in 3 of the remaining patients (14%) and ranged from 2.1 to 3.3 mg...
normalized = (x - mean) / tf.sqrt(variance + epsilon) dtype = x.dtype shape = x.get_shape().as_list()foriinsix.moves.range(len(shape)):ifinotinreduction_indicesornotper_element: shape[i] =1withtf.variable_scope(scopeor'layer_norm'):ifgainisNone: ...
Python QSlider.setRange - 60 examples found. These are the top rated real world Python examples of PyQt5.QtWidgets.QSlider.setRange extracted from open source projects. You can rate examples to help us improve the quality of examples.
Extraction of normalized counts #Export the count information normalized_counts <- counts(dds, normalized=TRUE) normalized_counts <- data.frame(normalized_counts) normalized_counts$Geneid <- rownames(normalized_counts) normalized_counts <- left_join(normalized_counts, FC1[,c(1,2)], by = "Gene...
They reveal the normalized resolution of our microscope as high as ≃0.15λ33, which depends (to some extent) on the optical properties of an imaged object34. Figure 2 Polarization-sensitive 0.6 THz (λ=500 µm) SI microscopy of test objects. (a–d) Photo, optical microscopy, and THz...
Extraction of normalized counts #Export the count information normalized_counts <- counts(dds, normalized=TRUE) normalized_counts <- data.frame(normalized_counts) normalized_counts$Geneid <- rownames(normalized_counts) normalized_counts <- left_join(normalized_counts, FC1[,c(1,2)], by = "Gene...
A peak in α-diversity at intermediate frequencies of disturbance was observed for all unweighted (0D, PD) and abundance-weighted (1D, 2D, PDW) indices evaluated in this study (Fig. 1A and Supplementary Figs. 2 and 3). Such a parabolic pattern was significant from d21 onwards for 2D (...