Search results for "forecasting"
showing 10 items of 329 documents
An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian Regions
2020
Abstract The availability of intensive care beds during the COVID‐19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short‐term prediction of COVID‐19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area‐specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave‐last‐out rationale. The approach has been set up and validated during t…
KFAS : Exponential Family State Space Models in R
2017
State space modelling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes an R package KFAS for state space modelling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modelling is presented.
Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer
2023
Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of colorectal cancer. The method is based on convolutional neural networks which were trained to classify colorectal cancer tissue in hematoxylin-eosin stained samples into three classes: stroma, tumor and other. The models were trained using a data set that consists of 1343 whole slide images. Three different training setups were applied with a transfer learning approach using domain-specific data i.e. an external colorectal cancer histopathological data set. The three most accurate models were chosen as a classifie…
Corporate Investment, Debt and Liquidity Choices in the Light of Financial Constraints and Hedging Needs
2015
We examine firms' simultaneous choice of investment, debt financing and liquidity in a large sample of US corporates between 1980 and 2014. We partition the sample according to the firms' financial constraints and their needs to hedge against future shortfalls in operating income. In contrast to earlier work, our joint estimation approach shows that cash flows affect the corporate decisions of unconstrained firms more strongly than those of constrained firms. Investment-cash flow sensitivities are particularly intense for unconstrained firms with high hedging needs. Investment opportunities (as proxied by Q), however, play a larger role for constrained firms with the effects being strongest…
Financial constraints and cash–cash flow sensitivity
2014
This article explores the cash–cash flow relationship by comparing financially constrained and financially unconstrained companies. Unlike previous research, we test the sensitivity of cash to cash flow by considering unlisted firms as constrained and listed firms as unconstrained. Our empirical evidence is based on findings from Spanish firms and is consistent with the core rationale that unlisted firms face more difficulties than their listed counterparts when looking for funding from external markets. As a result, unlisted firms tend to hoard significant amounts of cash out of the generated cash flow, while listed firms do not. Our findings are robust to a number of additional empirical …
Wave Energy Assessment around the Aegadian Islands (Sicily)
2019
This paper presents the estimation of the wave energy potential around the Aegadian islands (Italy), carried out on the basis of high resolution wave hindcast. This reanalysis was developed employing Weather Research and Forecast (WRF) and WAVEWATCH III ® models for the modelling of the atmosphere and the waves, respectively. Wave climate has been determined using the above-mentioned 32-year dataset covering the years from 1979 to 2010. To improve the information about wave characteristics regarding spatial details, i.e., increasing wave model resolution, especially in the nearshore region around the islands, a SWAN (Simulating WAves Nearshore) wave propagation model was used. Results obtai…
An improved perspective in the representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution product
2018
Abstract. This study uses the synergy of multiresolution soil moisture (SM) satellite estimates from the Soil Moisture Ocean Salinity (SMOS) mission, a dense network of ground-based SM measurements, and a Soil Vegetation Atmosphere Transfer (SVAT) model, SURFEX (Externalized Surface) – module ISBA (Interactions between Soil-Biosphere-Atmosphere), to examine, i) the comparison and suitability of different operational SMOS SM products to provide realistic information on the water content of the soil as well as the added value of the newly released SMOS Level 4 3.0 all weather disaggregated ~ 1 km SM (SMOS_L4 3.0 ), and ii) its potential impact for improving uncertainty associated to SM initia…
Predicting who fails to meet the physical activity guideline in pregnancy: a prospective study of objectively recorded physical activity in a populat…
2016
Background A low physical activity (PA) level in pregnancy is associated with several adverse health outcomes. Early identification of pregnant women at risk of physical inactivity could inform strategies to promote PA, but no studies so far have presented attempts to develop prognostic models for low PA in pregnancy. Based on moderate-to-vigorous intensity PA (MVPA) objectively recorded in mid/late pregnancy, our objectives were to describe MVPA levels and compliance with the PA guideline (≥150 MVPA minutes/week), and to develop a prognostic model for non-compliance with the PA guideline. Methods From a multi-ethnic population-based cohort, we analysed data from 555 women with MVPA recorde…
Oxidation of organics in water in microfluidic electrochemical reactors: Theoretical model and experiments
2011
The electrochemical oxidation of organics in water performed in micro reactors on boron doped diamond (BDD) anode was investigated both theoretically and experimentally in order to find the influence of various operative parameters on the conversion and the current efficiency CE of the process. The electrochemical oxidation of formic acid (FA) was selected as a model case. High conversions for a single passage of the electrolytic solution inside the cell were obtained by operating with proper residence times and low distances between cathode and anode. The effect of initial concentration, flow rate and current density was investigated in detail. Theoretical predictions were in very good agr…
Immunotherapy in gastrointestinal cancer: Recent results, current studies and future perspectives
2016
The new therapeutic approach of using immune checkpoint inhibitors as anticancer agents is a landmark innovation. Early studies suggest that immune checkpoint inhibition might also be effective in patients with gastrointestinal cancer. To improve the efficacy of immunotherapy, different strategies are currently under evaluation. This review summarises the discussion during the European Organisation for Research and Treatment of Cancer Gastrointestinal Tract Cancer Translational Research Meeting in Mainz in November 2014 and provides an update on the most recent results of immune therapy in gastrointestinal cancers. Knowledge of potential relationships between tumour cells and their microenv…