Characterisation of large changes in wind power for the day-ahead market using a fuzzy logic approach

Wind power has become one of the renewable resources with a major growth in the electricity market. However, due to its inherent variability, forecasting techniques are necessary for the optimum scheduling of the electric grid, specially during ramp events. These large changes in wind power may not be captured by wind power point forecasts even with very high resolution Numerical Weather Prediction (NWP) models. In this paper, a fuzzy approach for wind power ramp characterisation is presented. The main benefit of this technique is that it avoids the binary definition of ramp event, allowing to identify changes in power out- put that can potentially turn into ramp events when the total percentage of change to be considered a ramp event is not met. To study the application of this technique, wind power forecasts were obtained and their corresponding error estimated using Genetic Programming (GP) and Quantile Regression Forests. The error distributions were incorporated into the characterisation process, which according to the results, improve significantly the ramp capture. Results are presented using colour maps, which provide a useful way to interpret the characteristics of the ramp events

Detectability of colorectal neoplasia with fluorine-18-2-fluoro-2-deoxy-D-glucose positron emission tomography and computed tomography (FDG-PET/CT)

The purpose of this study was to analyze the detectability of colorectal neoplasia with fluorine-18-2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (FDG-PET/CT). Data for a total of 492 patients who had undergone both PET/CT and colonoscopy were analyzed. After the findings of PET/CT and colonoscopy were determined independently, the results were compared in each of the six colonic sites examined in all patients. The efficacy of PET/CT was determined using colonoscopic examination as the gold standard. In all, 270 colorectal lesions 5 mm or more in size, including 70 pathologically confirmed malignant lesions, were found in 172 patients by colonoscopy. The sensitivity and specificity of PET/CT for detecting any of the colorectal lesions were 36 and 98%, respectively. For detecting lesions 11 mm or larger, the sensitivity was increased to 85%, with the specificity remaining consistent (97%). Moreover, the sensitivity for tumors 21 mm or larger was 96% (48/50). Tumors with malignant or high-grade pathology were likely to be positive with PET/CT. A size of 10 mm or smaller [odds ratio (OR) 44.14, 95% confidence interval (95% CI) 11.44-221.67] and flat morphology (OR 7.78, 95% CI 1.79-36.25) were significant factors that were associated with false-negative cases on PET/CT. The sensitivity of PET/CT for detecting colorectal lesions is acceptable, showing size- and pathology-dependence, suggesting, for the most part, that clinically relevant lesions are detectable with PET/CT. However, when considering PET/CT for screening purposes caution must be exercised because there are cases of false-negative results

Electron-Spin Excitation Coupling in an Electron Doped Copper Oxide Superconductor

High-temperature (high-Tc) superconductivity in the copper oxides arises from electron or hole doping of their antiferromagnetic (AF) insulating parent compounds. The evolution of the AF phase with doping and its spatial coexistence with superconductivity are governed by the nature of charge and spin correlations and provide clues to the mechanism of high-Tc superconductivity. Here we use a combined neutron scattering and scanning tunneling spectroscopy (STS) to study the Tc evolution of electron-doped superconducting Pr0.88LaCe0.12CuO4-delta obtained through the oxygen annealing process. We find that spin excitations detected by neutron scattering have two distinct modes that evolve with Tc in a remarkably similar fashion to the electron tunneling modes in STS. These results demonstrate that antiferromagnetism and superconductivity compete locally and coexist spatially on nanometer length scales, and the dominant electron-boson coupling at low energies originates from the electron-spin excitations.Comment: 30 pages, 12 figures, supplementary information include

Sunscreens - Which and what for?

It is well established that sun exposure is the main cause for the development of skin cancer. Chronic continuous UV radiation is believed to induce malignant melanoma, whereas intermittent high-dose UV exposure contributes to the occurrence of actinic keratosis as precursor lesions of squamous cell carcinoma as well as basal cell carcinoma. Not only photocarcinogenesis but also the mechanisms of photoaging have recently become apparent. In this respect the use of sunscreens seemed to prove to be more and more important and popular within the last decades. However, there is still inconsistency about the usefulness of sunscreens. Several studies show that inadequate use and incomplete UV spectrum efficacy may compromise protection more than previously expected. The sunscreen market is crowded by numerous products. Inorganic sunscreens such as zinc oxide and titanium oxide have a wide spectral range of activity compared to most of the organic sunscreen products. It is not uncommon for organic sunscreens to cause photocontact allergy, but their cosmetic acceptability is still superior to the one given by inorganic sunscreens. Recently, modern galenic approaches such as micronization and encapsulation allow the development of high-quality inorganic sunscreens. The potential systemic toxicity of organic sunscreens has lately primarily been discussed controversially in public, and several studies show contradictory results. Although a matter of debate, at present the sun protection factor (SPF) is the most reliable information for the consumer as a measure of sunscreen filter efficacy. In this context additional tests have been introduced for the evaluation of not only the protective effect against erythema but also protection against UV-induced immunological and mutational effects. Recently, combinations of UV filters with agents active in DNA repair have been introduced in order to improve photoprotection. This article reviews the efficacy of sunscreens in the prevention of epithelial and nonepithelial skin cancer, the effect on immunosuppression and the value of the SPF as well as new developments on the sunscreen market. Copyright (C) 2005 S. Karger AG, Basel

Component-wise incremental LTL model checking

Efficient symbolic and explicit-state model checking approaches have been developed for the verification of linear time temporal logic (LTL) properties. Several attempts have been made to combine the advantages of the various algorithms. Model checking LTL properties usually poses two challenges: one must compute the synchronous product of the state space and the automaton model of the desired property, then look for counterexamples that is reduced to finding strongly connected components (SCCs) in the state space of the product. In case of concurrent systems, where the phenomenon of state space explosion often prevents the successful verification, the so-called saturation algorithm has proved its efficiency in state space exploration. This paper proposes a new approach that leverages the saturation algorithm both as an iteration strategy constructing the product directly, as well as in a new fixed-point computation algorithm to find strongly connected components on-the-fly by incrementally processing the components of the model. Complementing the search for SCCs, explicit techniques and component-wise abstractions are used to prove the absence of counterexamples. The resulting on-the-fly, incremental LTL model checking algorithm proved to scale well with the size of models, as the evaluation on models of the Model Checking Contest suggests

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Interactions between the Nse3 and Nse4 Components of the SMC5-6 Complex Identify Evolutionarily Conserved Interactions between MAGE and EID Families

The SMC5-6 protein complex is involved in the cellular response to DNA damage. It is composed of 6-8 polypeptides, of which Nse1, Nse3 and Nse4 form a tight sub-complex. MAGEG1, the mammalian ortholog of Nse3, is the founding member of the MAGE (melanoma-associated antigen) protein family and Nse4 is related to the EID (E1A-like inhibitor of differentiation) family of transcriptional repressors.Using site-directed mutagenesis, protein-protein interaction analyses and molecular modelling, we have identified a conserved hydrophobic surface on the C-terminal domain of Nse3 that interacts with Nse4 and identified residues in its N-terminal domain that are essential for interaction with Nse1. We show that these interactions are conserved in the human orthologs. Furthermore, interaction of MAGEG1, the mammalian ortholog of Nse3, with NSE4b, one of the mammalian orthologs of Nse4, results in transcriptional co-activation of the nuclear receptor, steroidogenic factor 1 (SF1). In an examination of the evolutionary conservation of the Nse3-Nse4 interactions, we find that several MAGE proteins can interact with at least one of the NSE4/EID proteins.We have found that, despite the evolutionary diversification of the MAGE family, the characteristic hydrophobic surface shared by all MAGE proteins from yeast to humans mediates its binding to NSE4/EID proteins. Our work provides new insights into the interactions, evolution and functions of the enigmatic MAGE proteins