Short-term solar irradiation forecasting based on dynamic harmonic regression

Solar power generation is a crucial research area for countries that have high dependency on fossil energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate the electricity generated by solar energy into the grid, solar irradiation must be reasonably well forecasted, where deviations of the forecasted value from the actual measured value involve significant costs. The present paper proposes a univariate Dynamic Harmonic Regression model set up in a State Space framework for short-term (1 to 24 hours) solar irradiation forecasting. Time series hourly aggregated as the Global Horizontal Irradiation and the Direct Normal Irradiation will be used to illustrate the proposed approach. This method provides a fast automatic identification and estimation procedure based on the frequency domain. Furthermore, the recursive algorithms applied offer adaptive predictions. The good forecasting performance is illustrated with solar irradiance measurements collected from ground-based weather stations located in Spain. The results show that the Dynamic Harmonic Regression achieves the lowest relative Root Mean Squared Error; about 30% and 47% for the Global and Direct irradiation components, respectively, for a forecast horizon of 24 hours ahead

Non-Linear Identification of Judgmental Forecasts Effects at SKU-Level

Prediction of demand is a key component within supply chain management. Im- proved accuracy in forecasts affects directly all levels of the supply chain, reduc- ing stock costs and increasing customer satisfaction. In many application areas, demand prediction relies on statistical software which provides an initial forecast subsequently modified by the expert’s judgment. This paper outlines a new method- ology based on State Dependent Parameter (SDP) estimation techniques to identify the non-linear behaviour of such managerial adjustments. This non-parametric SDP estimate is used as a guideline to propose a non-linear model that corrects the bias introduced by the managerial adjustments. One-step-ahead forecasts of SKU sales sampled monthly from a manufacturing company are utilized to test the proposed methodology. The results indicate that adjustments introduce a non-linear pattern undermining accuracy. This understanding can be used to enhance the design of the Forecasting Support System in order to help forecasters towards more efficient judgmental adjustments

Caracterización morfológica y cultural de aislados de "Colletotrichum" spp. causantes de la Antracnosis del olivo

La Antracnosis del olivo, causada por especies fúngicas del género Colletotrichum, es una enfermedad grave ampliamente distribuida en todas la regiones del mundo donde se cultiva el olivo. La incidencia de la enfermedad varia marcadamente en función de la susceptibilidad varietal, las condiciones climáticas y la virulencia del patógeno. Uno de los aspectos menos conocido de la enfermedad es la identificación del patógeno. Recientemente, se ha indicado que son dos las especies de Colletotrichum (C. acutatum y C. gloeosporioides) responsables de la Antracnosis del olivo, en lugar de una única especie (C. gloeosporioides = Gloeosporium olivarum) como se había considerado hasta ahora. En este trabajo se presentan los resultados de la caracterización morfológica y cultural de una colección de aislados de Colletotrichum obtenidos de olivos afectados de Antracnosis en varias comarcas olivareras de Andalucía. Aunque se han estudiado numerosos caracteres morfológicos y culturales, ninguno permitió una separación clara entre grupos de aislados o especies. No obstante, la forma de los extremos de las conidias fue el carácter más importante para su diferenciación. Casi todos los aislados de Colletotrichum de olivo (96%) tuvieron la mayoría de las conidias con un extremo redondeado y el otro agudo, diferenciándose de las conidias de C. gloeosporioides, con los dos extremos redondeados, y de las de C. acutatum, con los dos extremos agudos. Otras características estudiadas, como la coloración y el crecimiento de la colonia, la presencia de setas en los acérvulos, la presencia y morfología de las clamidosporas, la longitud y anchura de las conidias, o la formación de apresónos y conidias secundarias, mostraron una amplia variabilidad. Atendiendo a los resultados obtenidos, los aislados de Colletotrichum causantes de la Antracnosis del olivo en Andalucía se clasificarían dentro del complejo C. acutatum / C. gloeosporioides. Si bien, han mostrado características morfológicas y culturales más próximas a la especie C. acutatum. Su identificación definitiva requerirá de estudios adicionales para la caracterización fisiológica, molecular y patogénica de los aislados

Cost-effectiveness of Alzheimer's disease CSF biomarkers and amyloid-PET in early-onset cognitive impairment diagnosis

This study aimed at determining the cost-effectiveness of amyloid-positron emission tomography (PET) compared to Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers (amyloid-?42, total-Tau and phosphorylated-Tau) for the diagnosis of AD in patients with early-onset cognitive impairment. A decision tree model using a national health care perspective was developed to compare the costs and effectiveness associated with Amyloid-PET and AD CSF biomarkers. Available evidence from the literature and primary data from Hospital Clínic de Barcelona were used to inform the model and calculate the efficiency of these diagnostic alternatives. Medical visits and diagnostic procedures were considered and reported in €2020. We calculated the incremental cost-effectiveness ratio to measure the cost per % of correct diagnoses detected and we perform one-way deterministic and probabilistic sensitivity analyses to assess the uncertainty of these results. Compared with AD CSF biomarkers, Amyloid-PET resulted in 7.40% more correctly diagnosed cases of AD, with an incremental total mean cost of €146,854.80 per 100 cases. We found a 50% of probability that Amyloid-PET was cost-effective for a willingness to pay (WTP) of €19,840.39 per correct case detected. Using a WTP of €75,000, the probability that it is cost-effective reached a maximum of 76.9%, thus leading to a conclusion that Amyloid-PET is not a cost-effective technique compared to AD CSF biomarkers, unless the funder is willing to pay a minimum of €19,840.39 to detect one more correct case. Furthermore, obtaining CSF provides simultaneous information on amyloid ? and tau biomarkers and allows other biomarkers to be analyzed at a relatively low cost.© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany

EQUIPT: protocol of a comparative effectiveness research study evaluating cross-context transferability of economic evidence on tobacco control

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.This article has been made available through the Brunel Open Access Publishing Fund.Tobacco smoking claims 700 000 lives every year in Europe and the cost of tobacco smoking in the EU is estimated between €98 and €130 billion annually; direct medical care costs and indirect costs such as workday losses each represent half of this amount. Policymakers all across Europe are in need of bespoke information on the economic and wider returns of investing in evidence-based tobacco control, including smoking cessation agendas. EQUIPT is designed to test the transferability of one such economic evidence base-the English Tobacco Return on Investment (ROI) tool-to other EU member states

On the use of multi-step cost functions for generating forecasts

Accurate forecasts are of principal importance for operations. Exponential smoothing is widely used due to its simplicity, relatively good forecast accuracy, ease of implementation and automation. The literature has continuously improved upon many of its initial limitations, yet novel applications of exponential smoothing have brought new forecasting challenges that have revealed additional pitfalls in its use. In this work, we examine potential reasons for these issues and argue that special attention should be drawn to the cost function used to estimate model parameters. Conventional cost functions assume that the postulated model is an accurate reflection of underlying demand, which is not the case for the majority of real applications. We propose the use of alternative cost functions based on multi-step ahead predictions and trace forecasts. We show that these are univariate shrinkage estimators. We describe the nature of shrinkage and show that it differs from established shrinkage approaches, such as ridge and LASSO regression, offering new modelling capabilities. Using retailing sales, we construct forecasts and empirically demonstrate this shrinkage, validate our theoretical understanding, and provide evidence of both economic and forecast accuracy gains. We discuss implications for practice and limitations of the shrinkage caused by the multi-step cost functions

Optimising forecasting models for inventory planning

Inaccurate forecasts can be costly for company operations, in terms of stock-outs and lost sales, or over-stocking, while not meeting service level targets. The forecasting literature, often disjoint from the needs of the forecast users, has focused on providing optimal models in terms of likelihood and various accuracy metrics. However, there is evidence that this does not always lead to better inventory performance, as often the translation between forecast errors and inventory results is not linear. In this study, we consider an approach to parametrising forecasting models by directly considering appropriate inventory metrics and the current inventory policy. We propose a way to combine the competing multiple inventory objectives, i.e. meeting demand, while eliminating excessive stock, and use the resulting cost function to identify inventory optimal parameters for forecasting models. We evaluate the proposed parametrisation against established alternatives and demonstrate its performance on real data. Furthermore, we explore the connection between forecast accuracy and inventory performance and discuss the extent to which the former is an appropriate proxy of the latter

Estudio de viabilidad económica de la implantación de bioceldas en una planta de tratamiento de aguas residuales

Las aguas residuales generadas en la industria de los zumos se caracterizan entre otras cosas por presentar altas concentraciones de materia orgánica, la cual es muy costosa de eliminar con los tratamientos que existen actualmente.En los últimos años están surgiendo numerosos estudios en torno al uso de celdas de combustible microbiológicas o bioceldas como método de tratamiento de aguas residuales. En este artículo se ha realizado un estudio de viabilidad económica de la implantación de 10 bioceldas para tratar las aguas residuales generadas en una industria de este tipo. Para ello, se analizaron tres posibles escenarios que podrían darse utilizando estos sistemas y se compararon los resultados obtenidos con el uso de un reactor convencional de fangos activos. Los resultados obtenidos para el VAN mostraron que la utilizaciónde bioceldas podría proporcionar un ahorro comprendido entre un 10 y 20 % aproximadamente dependiendo de si es un escenario pesimista u optimista, respectivamente, teniendo en cuenta un tiempo de vida de la planta de 15 años. El área de electrodo por celda considerada en este estudio fue de 0,36 m2, la cual dio lugar a densidades de potencia algo más altas que las encontradas en la bibliografía. Por ello, se decidió realizar un análisis de sensibilidad considerando áreas de electrodo de 0,5 m2 y 0,8 m2 en las bioceldas. Se encontró que aún utilizandoáreas de 0,5 m2 el VAN seguiría siendo positivo en todos los escenarios considerados y para el valor de 0,8 m2 se obtuvieron también resultados favorables en el escenario optimista. Estos resultados muestran que siempre que se cumplan los criterios establecidos en este estudio, la depuración mediante bioceldas en una industria de este tipo podría ser una alternativa más rentable que la depuración convencional mediante fangos activos

Genetic diversity and population structure of Ascochyta rabiei from the western Iranian Ilam and Kermanshah provinces using MAT and SSR markers

Knowledge of genetic diversity in A. rabiei provides different levels of information that are important in the management of crop germplasm resources. Gene flow on a regional level indicates a significant potential risk for the regional spread of novel alleles that might contribute to fungicide resistance or the breakdown of resistance genes. Simple sequence repeat (SSR) and mating type (MAT) markers were used to determine the genetic structure, and estimate genetic diversity and the prevalence of mating types in 103 Ascochyta rabiei isolates from seven counties in the Ilam and Kermanshah provinces of western Iran (Ilam, Aseman abad, Holaylan, Chardavol, Dareh shahr, Gilangharb, and Sarpul). A set of 3 microsatellite primer pairs revealed a total of 75 alleles; the number of alleles varied from 15 to 34 for each marker. A high level of genetic variability was observed among A. rabiei isolates in the region. Genetic diversity was high (He = 0.788) within populations with corresponding high average gene flow and low genetic distances between populations. The smallest genetic distance was observed between isolates from Ilam and Chardavol. Both mating types were present in all populations, with the majority of the isolates belonging to Mat1-1 (64%), but within populations the proportions of each mating type were not significantly different from 50%. Results from this study will be useful in breeding for Ascochyta blight-resistant cultivars and developing necessary control measures

Far Ultraviolet Absolute Flux of alpha Virginis

We present the far ultraviolet spectrum of alpha Virginis taken with EURD spectrograph on-board MINISAT-01. The spectral range covered is from ~900 to 1080 A with 5 A spectral resolution. We have fitted Kurucz models to IUE spectra of alpha Vir and compared the extension of the model to our wavelengths with EURD data. This comparison shows that EURD fluxes are consistent with the prediction of the model within 20-30%, depending on the reddening assumed. EURD fluxes are consistent with Voyager observations but are ~60% higher than most previous rocket observations of alpha Vir.Comment: 13 pages, 4 figures. Submitted to The Astrophysical Journa