A framework to predict the price of energy for the end-users with applications to monetary and energy policies

Baratsas, Stefanos G.; Niziolek, Alexander M.; Onel, Onur; Matthews, Logan R.; Floudas, Christodoulos A.; Hallermann, Detlef R.; Sorescu, Sorin M.; Pistikopoulos, Efstratios N.

doi:10.1038/s41467-020-20203-2

Cited by 25 publications

(3 citation statements)

References 60 publications

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“…Reactive oxygen species (ROS)‐mediated photodynamic therapy (PDT) as another new modality against biofilm, [ 88 ] involves the combination of light with a photosensitizing drug in an oxygen‐rich environment. [ 89 ] The production of ROS can be divided into two types [ 90 ] :1) charge is transferred to the photosensitizer resulting in the generation of superoxide radicals (O 2 – ·) which can be converted to hydrogen peroxide (H 2 O 2 ) and free hydroxyl radicals (HO·); 2) energy is directly transferred to molecular oxygen ( 3 O 2 ), which can result in producing singlet oxygen ( 1 O 2 ).…”

Section: Progress In Surface Modifications For Anti‐biofilmmentioning

confidence: 99%

Surface Design for Antibacterial Materials: From Fundamentals to Advanced Strategies

et al. 2021

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Healthcare-acquired infections as well as increasing antimicrobial resistance have become an urgent global challenge, thus smart alternative solutions are needed to tackle bacterial infections. Antibacterial materials in biomedical applications and hospital hygiene have attracted great interest, in particular, the emergence of surface design strategies offer an effective alternative to antibiotics, thereby preventing the possible development of bacterial resistance. In this review, recent progress on advanced surface modifications to prevent bacterial infections are addressed comprehensively, starting with the key factors against bacterial adhesion, followed by varying strategies that can inhibit biofilm formation effectively. Furthermore, "super antibacterial systems" through pre-treatment defense and targeted bactericidal system, are proposed with increasing evidence of clinical potential. Finally, the advantages and future challenges of surface strategies to resist healthcare-associated infections are discussed, with promising prospects of developing novel antimicrobial materials.

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Section: Progress In Surface Modifications For Anti‐biofilmmentioning

confidence: 99%

Surface Design for Antibacterial Materials: From Fundamentals to Advanced Strategies

et al. 2021

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“…This situation is also relevant to mining companies as the price of energy influences every entity in the world and therefore it is important to determine two key factors, i.e. the overall demand for a product and final consumption (Baratsas et al, 2021;Polishchuk et al 2021;Hyránek et al 2021).…”

Section: Entrepreneurship and Sustainability Issuesmentioning

confidence: 99%

Alternative costs of equity of coal mining companies taking into account a context of the Russian Invasion into Ukraine

Matasová¹,

Vochоzka²,

Rowland³

2022

JESI

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The aim of work was to evaluate the alternative costs of equity of mining companies in the Czech Republic from 2011 to 2021 and to predict the development of costs structure of equity in the following five years. The calculation of Capital Asset Pricing Model (CAMP) model was selected to deal with the issue of alternative costs of equity in the monitored period and multi-layer perceptron networks were selected for the prediction of development. The achieved results clearly demonstrate the ratio of capital structure and its prediction in the future. The research is useful for energy enterprises and a possibility to use it in another sector is obvious.

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“…This encourages the research and development of renewable energies. As stated by the Energy Information Administration (EIA), renewable energy is a natural reservoir with a limited supply of energy (Baratsas et al, 2021). This energy comprises wind, bioenergy, solar, nuclear sources, geothermal, and water.…”

Section: Introductionmentioning

confidence: 99%

Appraising machine learning classifiers for discriminating rotor condition in 50W–12V operational wind turbine for maximizing wind energy production through feature extraction and selection process

Dhanraj

Alkhawaldeh

et al. 2022

Front. Energy Res.

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Wind energy is one of nature’s most valuable green energy assets, as well as one of the most reliable renewable energy supplies. Wind turbine blades convert wind energy into electric energy. Wind turbine blades range in size from 25 to 120 m, depending on the demands and efficiency necessary. Owing to ambient influences and wide structures, the blades are subject to various friction forces that might harm the blades. As a result, the generation of power and the shutdown of turbines are both affected. Downtimes are reduced when blades are detected on a regular basis, according to structural health management. On the 50-W, 12-V wind turbine, this research investigates the use of vibration signals to anticipate deterioration. The machine learning (ML) method establishes a nonlinear relationship between selected important damage features and the related uniqueness measures. The learning algorithm was trained and tested based on the excellent state of the edge. To forecast blade faults, classifier models, such as naive Bayes (NB), multilayer perceptron (MLP), linear support vector machine (linear_SVM), one-deep convolutional neural network (1DCNN), bagging, random forest (RF), XGBoosts, and decision tree J48 (DT) were used, and the results were compared according to their parameters to propose a better fault diagnostics model.

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A framework to predict the price of energy for the end-users with applications to monetary and energy policies

Cited by 25 publications

References 60 publications

Surface Design for Antibacterial Materials: From Fundamentals to Advanced Strategies

Surface Design for Antibacterial Materials: From Fundamentals to Advanced Strategies

Alternative costs of equity of coal mining companies taking into account a context of the Russian Invasion into Ukraine

Appraising machine learning classifiers for discriminating rotor condition in 50W–12V operational wind turbine for maximizing wind energy production through feature extraction and selection process

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