We introduce a new class of nonstationary covariance functions for spatial modelling. Nonstationary covariance functions allow the model to adapt to spatial surfaces whose variability changes with location. The class includes a nonstationary version of the Matérn stationary covariance, in which the differentiability of the spatial surface is controlled by a parameter, freeing one from fixing th...

A robust screen for compound interaction with P-glycoprotein (P-gp) has some obvious requirements, such as a cell line expressing P-gp and a probe substrate that is transported solely by P-gp and passive permeability. It is actually difficult to prove that a particular probe substrate interacts only with P-gp in the chosen cell line. Using a confluent monolayer of MDCKII-hMDR1 cells, we have de...

In this paper, the process of forecasting household energy consumption is studied within framework nonparametric Gaussian Process (GP), using multiple short time series data. As we begin to use smart meter data paint a clearer picture residential electricity use, it becomes increasingly apparent that must also construct detailed and understanding consumer’s complex relationship with gas consump...

Taking advantage of Gaussian process (GP), we obtain an improved estimate the Hubble constant, $H_0=70.41\pm1.58$ km s$^{-1}$ Mpc$^{-1}$, using parameter [$H(z)$] from cosmic chronometers (CCH) and expansion rate function [$E(z)$], extracted type Ia supernovae, data. We also use CCH data, including ones with full covariance matrix, $E(z)$ data to a determination $H_0=72.34_{-1.92}^{+1.90}$ whic...

Abstract Signomial Programming (SP) has proven to be a powerful tool for engineering design optimization, striking balance between the computational efficiency of Geometric (GP) and extensibility more general methods optimization. While techniques exist fitting GP compatible models data, no have been proposed that take advantage increased modeling flexibility available in SP. Here, new Differen...

We first report on computations made using the GP/PARI package that show that the error term Δ(x) in the divisor problem is = M (x, 4)+ O∗(0.35x1/4 log x) when x ranges [1 081 080, 1010], where M (x, 4) is a smooth approximation. The remaining part (and in fact most) of the paper is devoted to showing that |Δ(x)| ≤ 0.397x1/2 when x ≥ 5 560 and that |Δ(x)| ≤ 0.764x1/3 log x when x ≥ 9 995. Sever...

Abstract A natural extension to standard Gaussian process (GP) regression is the use of non-stationary processes, an approach where parameters covariance kernel are allowed vary in time or space. The GP a flexible model that relaxes strong prior assumption regression, properties inferred functions constant across input Non-stationary GPs typically varying as further lower-level GPs, thereby ena...

The delivery method of [continuous (CONT) vs. every other day or intermittent (INT)] a glucogenic precursor (GP) which was contained glycerin (500 g/kg), mono-propylene glycol (250 g/kg), calcium propionate (150 g/kg), niacin (1 g/kg) and sulfate-Co (350 mg/kg) on performance, selected blood metabolites and liver enzymes were evaluated. Twenty-four multiparous Holstein fresh cows were ...

Active learning is a machine paradigm allowing to decide which inputs use for training. It introduced Genetic Programming (GP) essentially thanks the dynamic data sampling, used address some known issues such as computational cost, over-fitting problem and imbalanced databases. The traditional sampling GP gives algorithm new sample periodically, often each generation, without considering state ...

We present the structure of the surface Ebola virus (EBOV) trimeric glycoprotein (GP) spike at 11 Å resolution, in situ within the viral plasma membrane of purified virus particles. GP functions in cellular attachment, endosomal entry, and membrane fusion to initiate infection, and is a key therapeutic target. Nevertheless, only about half of the GP molecule has yet been solved to atomic resolu...