Article
Construction & Building Technology
S. N. Londhe, P. S. Kulkarni, P. R. Dixit, A. Silva, R. Neves, J. de Brito
Summary: Concrete carbonation is an important issue in Civil Engineering and Material Science fields. This study used statistical modeling and Soft Computing techniques like Artificial Neural Networks and Genetic Programming to predict the carbonation coefficient in concrete, showing that these models perform better than Multiple Linear Regression in handling the nonlinear influence of relative humidity on concrete carbonation.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Chemistry, Physical
Daniel Dinculescu, Cristiana Luminit Gijiu, Manuela Rossemary Apetroaei, Raluca Isopescu, Ileana Rau, Verginica Schroder
Summary: This study focuses on utilizing waste egg capsules of Rapana venosa as raw material to extract chitosan oligomers, with the aim of optimizing the extraction process. By using experimental design and neural modeling, a maximum yield of 7.05% was achieved with a NaOH concentration of 6.47%, temperature of 90 degrees C, and extraction duration of 120 min.
Article
Biology
Steven A. Frank
Summary: This article introduces a computational method to optimize transcription factor (TF) networks and discusses the role of TFs in cellular function and how cells process information through their TF networks.
Article
Multidisciplinary Sciences
Zhengcai Li, Xinmin Hu, Chun Chen, Chenyang Liu, Yalu Han, Yuanfeng Yu, Lizhi Du
Summary: This paper investigates the optimization algorithms based on machine learning for settlement prediction. By comparing the performance of different algorithms, the study finds that Sparrow Search Algorithm (SSA) significantly improves the optimization effect of the gradient descent model and enhances its stability to a certain degree.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Interdisciplinary Applications
Marco Langiu, Manuel Dahmen, Alexander Mitsos
Summary: This paper optimizes the design and operation of an air-cooled geothermal organic Rankine cycle, considering multiple operating scenarios and maximizing the total annual return. The study incorporates component models and artificial neural networks to accurately capture the realistic off-design behavior. The research demonstrates the importance of considering multiple operating conditions and proposes a methodology for solving such problems globally.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Review
Computer Science, Artificial Intelligence
Hamit Taner Unal, Fatih Basciftci
Summary: The review provides a comprehensive overview of the evolutionary design of neural network architectures, focusing on the adoption of evolutionary computation techniques and encoding strategies. It analyzes the historical progress, common challenges, and divides the timeframe into three periods, covering the optimization of simple ANN architectures, rise of powerful methods, and the Deep Learning Era towards configuring advanced models of deep neural networks. The study aims to guide researchers towards promising directions in the field of neural architecture search and provide insights for fully automated machine learning.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Materials Science, Multidisciplinary
Edgar O. Resendiz-Flores, Gerardo Altamirano-Guerrero, Patricia S. Costa, Antonio E. Salas-Reyes, Armando Salinas-Rodriguez, Frank Goodwin
Summary: This study applies a non-linear back-propagation artificial neural network to optimize the processing of hot-dip galvanized dual-phase steels, obtaining the best parameters through an evolutionary approach and achieving outstanding mechanical properties of GDP steels. This method is used for the first time in the design of an actual manufacturing process.
Article
Computer Science, Interdisciplinary Applications
Hasan Sildir, Sahin Sarrafi, Erdal Aydin
Summary: This study focuses on the development of a superstructure-oriented feedforward ANN design and training algorithm, which achieves reduced over-fitting and improved prediction performance by reducing connections and the number of inputs.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Fan Zhang, Jianshen Zhu, Rachaya Chiewvanichakorn, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu
Summary: The paper introduces a method for computer-aided drug design using intelligent systems, with a focus on the inverse QSAR/QSPR approach. It presents the two phases of the method, forward prediction and inverse inference, and proposes a new method for inferring acyclic chemical compounds. Computational experiments show that the proposed method outperforms existing methods.
APPLIED INTELLIGENCE
(2022)
Article
Mechanics
Xiaoyang Liu, Jian Qin, Kai Zhao, Carol A. Featherston, David Kennedy, Yucai Jing, Guotao Yang
Summary: This paper proposes an efficient method for minimum weight optimization of composite laminates using artificial neural network (ANN) based surrogate models. By predicting the buckling loads of the laminates using ANN, the need for time-consuming buckling evaluations in the optimization process is eliminated. The use of lamination parameters and other dimensional inputs significantly reduces the number of required models and computational cost.
COMPOSITE STRUCTURES
(2023)
Article
Energy & Fuels
Minwoong Kang, Stefan Elbel
Summary: This study proposes a new type of regenerator with high heat transfer rate for the caloric cycle using additive manufacturing. The regenerator is optimized through an artificial neural network - genetic algorithm method, resulting in improved system efficiency and cooling capacity. This contributes to the development and energy saving of magnetic refrigeration cycle and may also enhance the performance of other caloric cycles.
Article
Robotics
Gan Yu, Joel Reis, Carlos Silvestre
Summary: This letter presents an adaptive nonlinear controller design and experimental study for UAVs in the presence of unknown disturbances and model uncertainty. A neural network is used to approximate the unknown system, along with a simple controller for trajectory tracking. The weights of the neural network are determined online using an adaptive law based on the Lyapunov synthesis method. Simulation and experimental results validate and assess the proposed control solution.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Pharmacology & Pharmacy
Erno Benko, Ilija German Ilic, Katalin Kristo, Geza Regdon Jr, Ildiko Csoka, Klara Pintye-Hodi, Stane Srcic, Tamas Sovany
Summary: This study investigates the customization of drug release from implantable drug delivery systems through drug-carrier interactions. The results indicate that interactions significantly affect the release rate and amount of the released drug. Models based on artificial neural networks are used for prediction.
Review
Optics
Wei Ma, Zhaocheng Liu, Zhaxylyk A. Kudyshev, Alexandra Boltasseva, Wenshan Cai, Yongmin Liu
Summary: Innovative approaches and tools, particularly deep learning, are shaping the field of photonics by offering efficient means to design photonic structures and providing data-driven solutions complementary to traditional physics-based methods. The progress in deep-learning-based photonic design is promising, with various model architectures showing potential applications in specific photonic tasks.
Review
Computer Science, Artificial Intelligence
Sara Kaviani, Ki Jin Han, Insoo Sohn
Summary: In recent years, the improvement of medical images and the performance of deep learning networks have led to the application of deep learning approaches in medical image classification and segmentation. However, there are concerns about the security and accuracy of healthcare systems, as well as the vulnerability of medical deep learning networks to adversarial attacks. This paper reviews the proposed adversarial attack methods and defense techniques for medical imaging DNNs and discusses future directions for improving neural network's robustness.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Pharmacology & Pharmacy
Afroditi Kapourani, Kalliopi Eleftheriadou, Konstantinos. N. Kontogiannopoulos, Panagiotis Barmpalexis
Summary: The study evaluated the impact of molecular mobility and interactions on the physical stability of RIV-SOL ASDs, finding that hydrogen bonds and the presence of a separate drug-rich amorphous phase contributed to system stability. Molecular dynamics simulations revealed strong intermolecular hydrogen bonds between RIV and SOL, leading to the formation of a separate drug-rich phase.
EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES
(2021)
Article
Pharmacology & Pharmacy
Aikaterini-Theodora Chatzitaki, Konstantinos Tsongas, Emmanouil K. Tzimtzimis, Dimitrios Tzetzis, Nikolaos Bouropoulos, Panagiotis Barmpalexis, Georgios K. Eleftheriadis, Dimitrios G. Fatouros
Summary: Personalized drug delivery systems using 3D printing technology have the potential to counterbalance pharmacological effects. In this study, pressure-assisted microsyringes were utilized to fabricate lidocaine-loaded suppositories, with in vitro dissolution profiles showing delayed lidocaine release.
JOURNAL OF DRUG DELIVERY SCIENCE AND TECHNOLOGY
(2021)
Article
Polymer Science
Stavroula G. Nanaki, Evi Christodoulou, Nikolaos D. Bikiaris, Afroditi Kapourani, Konstantinos N. Kontogiannopoulos, Souzan Vergkizi-Nikolakaki, Panagiotis Barmpalexis
Summary: The aim of the study was to prepare a leflunomide sustained release transdermal delivery system for psoriasis treatment. Using SDAEM-modified CS resulted in improved wetting and solubilization properties, better in vitro dissolution profile characteristics, and enhanced antibacterial properties in the LFD-loaded NPs. Embedding the NPs in polymeric thin-film patches resulted in sustained drug release for up to approximately twelve days, with CS-SDAEM NPs showing the most promising formulation approach.
Article
Polymer Science
Afroditi Kapourani, Artemis Palamidi, Konstantinos N. Kontogiannopoulos, Nikolaos D. Bikiaris, Panagiotis Barmpalexis
Summary: This study aimed to evaluate the use of poly(propylene succinate) (PPSu) in the preparation of drug-loaded PVA-based amorphous solid dispersions to improve thermal properties and stability of the drug.
Article
Pharmacology & Pharmacy
Andreas Ouranidis, Christina Davidopoulou, Kyriakos Kachrimanis
Summary: This study explores the effects of nanosizing BCS II APIs and the use of a novel thermodynamic model to predict solubility enhancement in nanosuspensions. Traditional dissolution estimation equations are found inadequate for nanoparticle systems, leading to the proposal of a comprehensive analysis method to predict critical material quality attributes and process parameters.
Article
Biochemistry & Molecular Biology
Andreas Ouranidis, Theofanis Vavilis, Evdokia Mandala, Christina Davidopoulou, Eleni Stamoula, Catherine K. Markopoulou, Anna Karagianni, Kyriakos Kachrimanis
Summary: mRNA therapeutics, particularly mRNA vaccines, have become a prominent weapon in the fight against the SARS-CoV-2 pandemic. Their advantages include rapid production cycle, flexibility in target selection, avoidance of safety issues posed by DNA therapeutics, and precise control over translated peptides. However, the global demand for mRNA has also revealed shortcomings in industrial production, formulation, efficacy, and applicability, which require continuous research and improvement.
Article
Polymer Science
Afroditi Kapourani, Konstantinos N. N. Kontogiannopoulos, Alexandra-Eleftheria Manioudaki, Athanasios K. K. Poulopoulos, Lazaros Tsalikis, Andreana N. N. Assimopoulou, Panagiotis Barmpalexis
Summary: Xerostomia refers to the subjective sensation of oral dryness, which is multifactorial and commonly caused by the use of xerostomic medications, neck and head radiation, and systematic diseases. It is associated with increased incidence of dental caries, oral fungal infections, and difficulties in speaking and chewing/swallowing, ultimately affecting the oral health-related quality of life. Successful management of xerostomia is challenging due to the complexity of saliva, but polymers play a crucial role in various formulations, especially in saliva substitutes.
Review
Environmental Sciences
Georgios S. Chatzopoulos, Panagiotis Karakostas, Stefania Kavakloglou, Andreana Assimopoulou, Panagiotis Barmpalexis, Lazaros Tsalikis
Summary: In periodontitis patients, herbal oral care products used as adjuncts to conventional treatment showed superior clinical outcomes and may play a key role in managing the disease.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Review
Chemistry, Medicinal
Afroditi Kapourani, Konstantinos N. Kontogiannopoulos, Panagiotis Barmpalexis
Summary: Xerostomia is associated with dental caries, oral fungal infections, and difficulties in speaking and swallowing, impacting patients' quality of life. The use of pilocarpine, a parasympathomimetic agent, for treating xerostomia has been proven effective, but systemic administration can cause adverse effects. Thus, the development of topical pilocarpine delivery systems has emerged as a new strategy, offering comparable efficacy with improved patient tolerance and fewer adverse effects.
Article
Chemistry, Analytical
Maria S. Synaridou, Vasilis Tsamis, Eleni Tsanaktsidou, Andreas Ouranidis, Kyriakos Kachrimanis, Catherine K. Markopoulou
Summary: A new multivitamin supplement containing fat and water soluble vitamins, as well as nutrients for young athletes, was formulated and analyzed. A purification process was developed using freezing and liquid extraction, and an efficient liquid chromatography method was developed for sample analysis. The stability of the vitamins was validated and found to be stable for at least 1 year.
ANALYTICAL LETTERS
(2023)
Article
Polymer Science
Stavroula G. Nanaki, Konstantinos Spyrou, Pelagia Veneti, Niki Karouta, Dimitrios Gournis, Turki N. Baroud, Panagiotis Barmpalexis, Dimitrios N. Bikiaris
Summary: This study evaluates the use of thiolized chitosan conjugates (CS) combined with carbon dots (CDs) and hierarchical porous carbons (HPC) for the preparation of galantamine (GAL) nanoparticles (NPs) for intranasal drug delivery. The results show that the use of Cys-CS and CDs in the preparation of NPs leads to a more thermodynamically stable drug dispersion and achieves a zero-order release profile.
Article
Polymer Science
Maria Koromili, Afroditi Kapourani, Panagiotis Barmpalexis
Summary: Luteolin (LUT) is a flavonoid with various pharmacological properties, including antioxidant, antimicrobial, anti-allergic, cardio-protective, and anti-cancer activity. This study aims to prepare amorphous solid dispersions (ASD) to improve the solubility of LUT in saliva. The most promising polymeric matrix/carrier for LUT's ASDs was found to be PVP, which significantly enhanced LUT's dissolution profile in simulated saliva.
Article
Polymer Science
Afroditi Kapourani, Alexandra-Eleftheria Manioudaki, Konstantinos N. Kontogiannopoulos, Panagiotis Barmpalexis
Summary: This study focuses on enhancing the solubility of Dronedarone (DRN) through the use of amorphous solid dispersions (ASDs). Soluplus (R) was identified as the most promising carrier, and DRN ASDs were successfully prepared using the melt-quench method. The prepared systems exhibited physical stability and sustained drug supersaturation.
Article
Biochemistry & Molecular Biology
Konstantinos Theodoridis, Athanasios S. Arampatzis, Georgia Liasi, Lazaros Tsalikis, Panagiotis Barmpalexis, Dimitrios Christofilos, Andreana N. Assimopoulou
Summary: This study proposes a new approach for treating periodontitis by incorporating tetracycline hydrochloride into a 3D-printed scaffold made of poly(epsilon-caprolactone). The scaffold exhibits antibacterial properties against Staphylococcus aureus and promotes bone tissue regeneration.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Athanasios S. Arampatzis, Aspasia Pampori, Eleftheria Droutsa, Maria Laskari, Panagiotis Karakostas, Lazaros Tsalikis, Panagiotis Barmpalexis, Christos Dordas, Andreana N. Assimopoulou
Summary: Secondary metabolites called polyphenols, including the compound luteolin, are crucial for plant adaptation to different environments and defense against pathogens. Luteolin exhibits various biological activities and has been widely used in the food and biomedical industries. Understanding the extraction and detection methods, as well as the content of luteolin in Greek flora, is important for its potential applications.