Search results for "Prediction."

Implementation of non-local boundary layer schemes in the Regional Atmospheric Modeling System and its impact on simulated mesoscale circulations

2016

This paper proposes the implementation of different non-local Planetary Boundary Layer schemes within the Regional Atmospheric Modeling System (RAMS) model. The two selected PBL parameterizations are the Medium-Range Forecast (MRF) PBL and its updated version, known as the Yonsei University (YSU) PBL. YSU is a first-order scheme that uses non-local eddy diffusivity coefficients to compute turbulent fluxes. It is based on the MRF, and improves it with an explicit treatment of the entrainment. With the aim of evaluating the RAMS results for these PBL parameterizations, a series of numerical simulations have been performed and contrasted with the results obtained using the Mellor and Yamada (M…

A nonlinear mixed model approach to predict energy expenditure from heart rate.

2021

Abstract Objective. Heart rate (HR) monitoring provides a convenient and inexpensive way to predict energy expenditure (EE) during physical activity. However, there is a lot of variation among individuals in the EE-HR relationship, which should be taken into account in predictions. The objective is to develop a model that allows the prediction of EE based on HR as accurately as possible and allows an improvement of the prediction using calibration measurements from the target individual. Approach. We propose a nonlinear (logistic) mixed model for EE and HR measurements and an approach to calibrate the model for a new person who does not belong to the dataset used to estimate the model. The …

Protein structure prediction assisted with sparse NMR data in CASP13

2019

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and 15 N-1 H residual dipolar coupling data, typical of that obtained for 15 N,13 C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CAS…

Predicting Skin Permeability by Means of Computational Approaches: Reliability and Caveats in Pharmaceutical Studies

2019

The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experim…

CORPORATE BANKRUPTCY AND INSOLVENCY PREDICTION MODEL

2021

In any competitive economy, the risk of bankruptcy is pervasive. The research aims to contribute in improving the predictive power of bankruptcy and insolvency risk among companies by introducing new methods of processing and validation. This paper investigates the extensive application of the Z score model for predicting the economic-financial stability of Romanian companies in the manufacturing and extractive industries. A list of 37 financial indicators determined on the basis of the balance sheet data of 80 companies for the period 2015–2018 was used. Stepwise Least Squares Estimation through the Forward method allowed the identification of the most relevant ones. Canonical discriminant…

Life Cycle Study of a Diabatic Rossby Wave as a Precursor to Rapid Cyclogenesis in the North Atlantic—Dynamics and Forecast Performance

2011

Monthly Weather Review, 139 (6)

Half-lives and delayed neutron emission probabilities of short-lived Rb and Cs precursors

1979

Half-lives and delayed-neutron emission probabilities (P n ) of short-lived Rb and Cs precursors in the mass chains 94–98 and 143–147 were measured. Sources of isotope separated nuclides were obtained from the on-line mass-separator OSTIS installed at the Grenoble high-flux reactor.

The reliability of nuclear model predictions of?-decay properties of nuclei far from stability

1983

Simulation of Sediment transport and flow characteristics downstream of a hydraulic structure

2016

The presence of a hydraulic structure (such as a dam) in a given river reach determines “constrained” sediment boundary conditions and thus transient transport phenomena. Many predictive mobile-bed one-dimensional models have been developed in or-der to predict sediment transport during transients but, even today, they have not attained a high degree of efficacy. This is because these models are confronted with some difficulties such as the reliable prediction of bed roughness or/and to the presence of flexible vegetation, of hydraulic sorting, of water-bed sediment interchanges in no-equilibrium situations. In the present work, with the aid of a 1-D numerical model previously developed (Te…

Multimodal Deep Learning for Prognosis Prediction in Renal Cancer

2021

BackgroundClear-cell renal cell carcinoma (ccRCC) is common and associated with substantial mortality. TNM stage and histopathological grading have been the sole determinants of a patient’s prognosis for decades and there are few prognostic biomarkers used in clinical routine. Management of ccRCC involves multiple disciplines such as urology, radiology, oncology, and pathology and each of these specialties generates highly complex medical data. Here, artificial intelligence (AI) could prove extremely powerful to extract meaningful information to benefit patients.ObjectiveIn the study, we developed and evaluated a multimodal deep learning model (MMDLM) for prognosis prediction in ccRCC.Desig…