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  1. Book ; Online: Computational Intelligence in Photovoltaic Systems

    Ogliari , Emanuele / Leva, Sonia

    2019  

    Abstract: Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as ... ...

    Abstract Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant production, storage sizing, modeling, and control optimization of photovoltaic systems. Computational intelligence algorithms (evolutionary optimization, neural networks, fuzzy logic, et cetera) have become more and more popular as alternative approaches to conventional techniques for solving problems such as modeling, identification, optimization, availability prediction, forecasting, sizing, and control of stand-alone, grid-connected, and hybrid photovoltaic systems. This Special Issue will investigate the most recent developments and research on solar power systems. This Special Issue "Computational Intelligence in Photovoltaic Systems" is highly recommended for readers with an interest in the various aspects of solar power systems, and includes 10 original research papers covering relevant progress in the following (non-exhaustive) fields: Forecasting techniques (deterministic, stochastic, et cetera); DC/AC converter control and maximum power point tracking techniques; Sizing and optimization of photovoltaic system components; Photovoltaics modeling and parameter estimation; Maintenance and reliability modeling; Decision processes for grid operators
    Keywords Technology (General) ; Engineering (General). Civil engineering (General)
    Size 1 electronic resource (180 pages)
    Publisher MDPI - Multidisciplinary Digital Publishing Institute
    Document type Book ; Online
    Note eng ; Open Access
    HBZ-ID HT020324143
    ISBN 9783039210985 ; 9783039210992 ; 303921098X ; 3039210998
    DOI 10.3390/books978-3-03921-099-2
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article: Real-World Outcomes of Lip Augmentation Using a Hyaluronic Acid-Based Filler With Low 1,4-Butanediol Diglycidyl Ether Content: A Prospective, Open-Label, Multicenter, Post-marketing Study.

    Massidda, Enrico / Ciampa, Sonia / Iozzo, Ivano / Emanuele, Enzo / Minoretti, Piercarlo

    Cureus

    2024  Volume 16, Issue 2, Page(s) e53513

    Abstract: Background 1,4-butanediol diglycidyl ether (BDDE) is the most common cross-linker used to produce hyaluronic acid (HA)-based dermal fillers. However, BDDE may have cytotoxic and potentially mutagenic effects, raising safety concerns. Consequently, ... ...

    Abstract Background 1,4-butanediol diglycidyl ether (BDDE) is the most common cross-linker used to produce hyaluronic acid (HA)-based dermal fillers. However, BDDE may have cytotoxic and potentially mutagenic effects, raising safety concerns. Consequently, manufacturers are developing new HA filler formulations with reduced BDDE levels to mitigate potential biological risks. Here, we sought to evaluate the clinical outcomes of lip augmentation performed using an HA-based filler with a reduced BDDE content (Agex Fill Volume
    Language English
    Publishing date 2024-02-03
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.53513
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Data-Driven Methods for the State of Charge Estimation of Lithium-Ion Batteries

    Panagiotis Eleftheriadis / Spyridon Giazitzis / Sonia Leva / Emanuele Ogliari

    Forecasting, Vol 5, Iss 32, Pp 576-

    An Overview

    2023  Volume 599

    Abstract: In recent years, there has been a noticeable shift towards electric mobility and an increasing emphasis on integrating renewable energy sources. Consequently, batteries and their management have been prominent in this context. A vital aspect of the BMS ... ...

    Abstract In recent years, there has been a noticeable shift towards electric mobility and an increasing emphasis on integrating renewable energy sources. Consequently, batteries and their management have been prominent in this context. A vital aspect of the BMS revolves around accurately determining the battery pack’s SOC. Notably, the advent of advanced microcontrollers and the availability of extensive datasets have contributed to the growing popularity and practicality of data-driven methodologies. This study examines the developments in SOC estimation over the past half-decade, explicitly focusing on data-driven estimation techniques. It comprehensively assesses the performance of each algorithm, considering the type of battery and various operational conditions. Additionally, intricate details concerning the models’ hyperparameters, including the number of layers, type of optimiser, and neuron, are provided for thorough examination. Most of the models analysed in the paper demonstrate strong performance, with both the MAE and RMSE for the estimation of SOC hovering around 2% or even lower.
    Keywords lithium batteries ; estimation ; data-driven ; machine learning ; state of charge ; Science (General) ; Q1-390 ; Mathematics ; QA1-939
    Language English
    Publishing date 2023-09-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Dual Function Molecules and Processes in Cell Fate Decision: A Preface to the Special Issue.

    Emanuele, Sonia / Giuliano, Michela

    International journal of molecular sciences

    2020  Volume 21, Issue 24

    Abstract: A lot of water has passed under the bridge since 1999, when C [ ... ]. ...

    Abstract A lot of water has passed under the bridge since 1999, when C [...].
    MeSH term(s) Animals ; Cell Differentiation ; Gene Expression Regulation, Developmental ; Humans ; Signal Transduction
    Language English
    Publishing date 2020-12-16
    Publishing country Switzerland
    Document type Editorial ; Introductory Journal Article
    ZDB-ID 2019364-6
    ISSN 1422-0067 ; 1422-0067 ; 1661-6596
    ISSN (online) 1422-0067
    ISSN 1422-0067 ; 1661-6596
    DOI 10.3390/ijms21249601
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Long non-coding RNA H19 enhances the pro-apoptotic activity of ITF2357 (a histone deacetylase inhibitor) in colorectal cancer cells.

    Zichittella, Chiara / Loria, Marco / Celesia, Adriana / Di Liberto, Diana / Corrado, Chiara / Alessandro, Riccardo / Emanuele, Sonia / Conigliaro, Alice

    Frontiers in pharmacology

    2023  Volume 14, Page(s) 1275833

    Abstract: Introduction: ...

    Abstract Introduction:
    Language English
    Publishing date 2023-09-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2587355-6
    ISSN 1663-9812
    ISSN 1663-9812
    DOI 10.3389/fphar.2023.1275833
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Day Ahead Electric Load Forecast

    Michael Wood / Emanuele Ogliari / Alfredo Nespoli / Travis Simpkins / Sonia Leva

    Forecasting, Vol 5, Iss 16, Pp 297-

    A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies

    2023  Volume 314

    Abstract: Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics and ...

    Abstract Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics and behavior. There are many promising machine learning techniques in the literature, but black box models lack explainability and therefore confidence in the models’ robustness can’t be achieved without thorough testing on data sets with varying and representative statistical properties. Therefore this work adopts and builds on some of the highest-performing load forecasting tools in the literature, which are Long Short-Term Memory recurrent networks, Empirical Mode Decomposition for feature engineering, and k-means clustering for outlier detection, and tests a combined methodology on seven different load data sets from six different load sectors. Forecast test set results are benchmarked against a seasonal naive model and SARIMA. The resultant skill scores range from −6.3% to 73%, indicating that the methodology adopted is often but not exclusively effective relative to the benchmarks.
    Keywords electric load ; forecasting ; neural networks ; LSTM ; EMD ; industrial ; Science (General) ; Q1-390 ; Mathematics ; QA1-939
    Language English
    Publishing date 2023-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Dual Function Molecules and Processes in Cell Fate Decision

    Sonia Emanuele / Michela Giuliano

    International Journal of Molecular Sciences, Vol 21, Iss 9601, p

    A Preface to the Special Issue

    2020  Volume 9601

    Abstract: A lot of water has passed under the bridge since 1999, when C.J. Jeffery stated in a pioneering review that “the idea of one gene-one protein-one function has become too simple” [.] ...

    Abstract A lot of water has passed under the bridge since 1999, when C.J. Jeffery stated in a pioneering review that “the idea of one gene-one protein-one function has become too simple” [.]
    Keywords n/a ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
    Language English
    Publishing date 2020-12-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Computational Intelligence in Photovoltaic Systems

    Sonia Leva / Emanuele Ogliari

    Applied Sciences, Vol 9, Iss 9, p

    2019  Volume 1826

    Abstract: Photovoltaics, among renewable energy sources (RES), has become more popular [.] ...

    Abstract Photovoltaics, among renewable energy sources (RES), has become more popular [.]
    Keywords computational intelligence ; day-ahead forecast ; photovoltaics ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Language English
    Publishing date 2019-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Irradiance Nowcasting by Means of Deep-Learning Analysis of Infrared Images

    Alessandro Niccolai / Seyedamir Orooji / Andrea Matteri / Emanuele Ogliari / Sonia Leva

    Forecasting, Vol 4, Iss 19, Pp 338-

    2022  Volume 348

    Abstract: This work proposes and evaluates a method for the nowcasting of solar irradiance variability in multiple time horizons, namely 5, 10, and 15 min ahead. The method is based on a Convolutional Neural Network structure that exploits infrared sky images ... ...

    Abstract This work proposes and evaluates a method for the nowcasting of solar irradiance variability in multiple time horizons, namely 5, 10, and 15 min ahead. The method is based on a Convolutional Neural Network structure that exploits infrared sky images acquired through an All-Sky Imager to estimate the range of possible values that the Clear-Sky Index will possibly assume over a selected forecast horizon. All data available, from the infrared images to the measurements of Global Horizontal Irradiance (necessary in order to compute Clear-Sky Index), are acquired at SolarTech LAB in Politecnico di Milano. The proposed method demonstrated a discrete performance level, with an accuracy peak for the 5 min time horizon, where about 65% of the available samples are attributed to the correct range of Clear-Sky Index values.
    Keywords deep learning ; infrared sky images ; irradiance nowcasting ; PV production forecasting ; Science (General) ; Q1-390 ; Mathematics ; QA1-939
    Language English
    Publishing date 2022-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Tributyltin(IV) Butyrate: A Novel Epigenetic Modifier with ER Stress- and Apoptosis-Inducing Properties in Colon Cancer Cells.

    Giuliano, Michela / Pellerito, Claudia / Celesia, Adriana / Fiore, Tiziana / Emanuele, Sonia

    Molecules (Basel, Switzerland)

    2021  Volume 26, Issue 16

    Abstract: Organotin(IV) compounds are a class of non-platinum metallo-conjugates exhibiting antitumor activity. The effects of different organotin types has been related to several mechanisms, including their ability to modify acetylation protein status and to ... ...

    Abstract Organotin(IV) compounds are a class of non-platinum metallo-conjugates exhibiting antitumor activity. The effects of different organotin types has been related to several mechanisms, including their ability to modify acetylation protein status and to promote apoptosis. Here, we focus on triorganotin(IV) complexes of butyric acid, a well-known HDAC inhibitor with antitumor properties. The conjugated compounds were synthesized and characterised by FTIR spectroscopy, multi-nuclear (
    MeSH term(s) Acetylation/drug effects ; Apoptosis/drug effects ; Apoptosis/genetics ; Butyric Acid/chemistry ; Cell Line, Tumor ; Colonic Neoplasms/pathology ; Endoplasmic Reticulum Stress/drug effects ; Endoplasmic Reticulum Stress/genetics ; Epigenesis, Genetic/drug effects ; Histone Deacetylases/metabolism ; Humans ; Protein Processing, Post-Translational/drug effects ; Trialkyltin Compounds/chemistry ; Trialkyltin Compounds/pharmacology
    Chemical Substances Trialkyltin Compounds ; Butyric Acid (107-92-6) ; tributyltin (4XDX163P3D) ; Histone Deacetylases (EC 3.5.1.98)
    Language English
    Publishing date 2021-08-19
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 1413402-0
    ISSN 1420-3049 ; 1431-5165 ; 1420-3049
    ISSN (online) 1420-3049
    ISSN 1431-5165 ; 1420-3049
    DOI 10.3390/molecules26165010
    Database MEDical Literature Analysis and Retrieval System OnLINE

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