Search results for "Prediction."

Estimation of recombinant protein production in Pichia pastoris base don a constraint-based model

2012

[EN] A previously validated constraint based model and possibilistic MFA have been used to design a simple estimator of protein production rate in Pichia pastoris cultures. A structured model of the yeast P. pastoris metabolism is used to predict the balance of key energetic equivalents such as ATP from available measurements, mainly substrate consumption, gases exchange rates and biomass specific growth. It has been shown that ATP flux can be related to biomass growth and protein productivity specific rates by linear regression. Cross-validation has been applied for robust parameter fitting on the basis of chemostat, steady-state experimental conditions. In this way, protein estimation can…

Forecasting Electricity Consumption and Production in Smart Homes through Statistical Methods

2022

Abstract Over the last years, a steady increase in both domestic electricity consumption and in the adoption of personal clean energy production systems has been observed worldwide. By analyzing energy consumption and production on photovoltaic panels mounted in a house, this work focuses on finding patterns in electrical energy consumption and devising a predictive model. Our goal is to find an accurate method to predict electrical energy consumption and production. Being able to anticipate how consumers will use energy in the near future, homeowners, companies and governments may optimize their behavior and the import and export of electricity. We evaluated the ARIMA and TBATS statistical…

2021

Abstract. The formation of ice in clouds is an important processes in mixed-phase and ice-phase clouds. Yet, the representation of ice formation in numerical models is highly uncertain. In the last decade, several new parameterizations for heterogeneous freezing have been proposed. However, it is currently unclear what the effect of choosing one parameterization over another is in the context of numerical weather prediction. We conducted high-resolution simulations (Δx=250 m) of moderately deep convective clouds (cloud top ∼-18 ∘C) over the southwestern United Kingdom using several formulations of ice formation and compared the resulting changes in cloud field properties to the spread of an…

Sea breeze thunderstorms in the eastern Iberian Peninsula. Neighborhood verification of HIRLAM and HARMONIE precipitation forecasts

2014

In this study we investigated sea breeze thunderstorms with intense convective activity (i.e., heavy rainfall, hail and gusty winds) that occurred over the eastern Iberian Peninsula (Spain) and were missed by the operational HIRLAM model. We used two grid-spacing setups (5.0. km and 2.5. km) of the hydrostatic HIRLAM model, and the non-hydrostatic spectral HARMONIE suite (2.5. km), to simulate isolated convection associated with sea breezes. The overall aim is to estimate the ability of these three experimental setups, in particular the HARMONIE model as the forthcoming operational numerical weather prediction in most European Weather Services, to correctly simulate convective precipitation…

Classification of precipitation events with a convective response timescale and their forecasting characteristics

2011

[1] The convective timescale τc, which is mainly determined by the ratio of CAPE and precipitation rate, provides a physically-based measure to distinguish equilibrium and non-equilibrium convection. A statistical analysis of this timescale, based upon observational data from radiosonde ascents, rain gauges, and radar for seven warm seasons in Germany, reveals that the equilibrium and non-equilibrium regimes can be regarded as extremes of a continuous distribution. The two regimes characterize very different interactions between the large-scale flow and convection. The quality of precipitation forecasts from a non-hydrostatic regional weather prediction model with parameterized convection d…

Improving protein secondary structure predictions by prediction fusion

2009

Protein secondary structure prediction is still a challenging problem at today. Even if a number of prediction methods have been presented in the literature, the various prediction tools that are available on-line produce results whose quality is not always fully satisfactory. Therefore, a user has to know which predictor to use for a given protein to be analyzed. In this paper, we propose a server implementing a method to improve the accuracy in protein secondary structure prediction. The method is based on integrating the prediction results computed by some available on-line prediction tools to obtain a combined prediction of higher quality. Given an input protein p whose secondary struct…

Connectivity Influences on Nonlinear Dynamics in Weakly-Synchronized Networks: Insights from Rössler Systems, Electronic Chaotic Oscillators, Model a…

2019

Natural and engineered networks, such as interconnected neurons, ecological and social networks, coupled oscillators, wireless terminals and power loads, are characterized by an appreciable heterogeneity in the local connectivity around each node. For instance, in both elementary structures such as stars and complex graphs having scale-free topology, a minority of elements are linked to the rest of the network disproportionately strongly. While the effect of the arrangement of structural connections on the emergent synchronization pattern has been studied extensively, considerably less is known about its influence on the temporal dynamics unfolding within each node. Here, we present a compr…

Next-Day Bitcoin Price Forecast

2019

This study analyzes forecasts of Bitcoin price using the autoregressive integrated moving average (ARIMA) and neural network autoregression (NNAR) models. Employing the static forecast approach, we forecast next-day Bitcoin price both with and without re-estimation of the forecast model for each step. For cross-validation of forecast results, we consider two different training and test samples. In the first training-sample, NNAR performs better than ARIMA, while ARIMA outperforms NNAR in the second training-sample. Additionally, ARIMA with model re-estimation at each step outperforms NNAR in the two test-sample forecast periods. The Diebold Mariano test confirms the superiority of forecast …

Modification of Dzyaloshinskii-Moriya-Interaction-Stabilized Domain Wall Chirality by Driving Currents

2018

We measure and analyze the chirality of Dzyaloshinskii-Moriya-interaction (DMI) stabilized spin textures in multilayers of $\mathrm{Ta}|{\mathrm{Co}}_{20}{\mathrm{F}}_{60}{\mathrm{B}}_{20}|\mathrm{MgO}$. The effective DMI is measured experimentally using domain wall motion measurements, both in the presence (using spin-orbit torques) and absence of driving currents (using magnetic fields). We observe that the current-induced domain wall motion yields a change in effective DMI magnitude and opposite domain wall chirality when compared to field-induced domain wall motion (without current). We explore this effect, which we refer to as current-induced DMI, by providing possible explanations for…

#EEGManyLabs

2021

There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalog-raphy (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound in-fluence on our understanding of human cognition, but there is limited evid…