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Neonicotinoids are synthetic, nicotine-derived insecticides used worldwide to protect crops and domestic animals from pest insects. The reported evidence shows that they are also able to interact with mammalian nicotine receptors (nAChRs), triggering detrimental responses in cultured neurons. Exposure to high neonicotinoid levels during the fetal period induces neurotoxicity in animal models. Considering the persistent exposure to these insecticides and the key role of nAChRs in brain development, their potential neurotoxicity on mammal central nervous system (CNS) needs further investigations. We studied here the neurodevelopmental effects of different generations of neonicotinoids on CNS cells in mouse fetal brain and primary cultures and in neuronal cells and organoids obtained from human induced pluripotent stem cells (iPSC). Neonicotinoids significantly affect neuron viability, with imidacloprid (IMI) inducing relevant alterations in synaptic protein expression, neurofilament structures, and microglia activation in vitro, and in the brain of prenatally exposed mouse fetuses. IMI induces neurotoxic effects also on developing human iPSC-derived neurons and cortical organoids. Collectively, the current findings show that neonicotinoids might induce impairment during neuro/immune-development in mouse and human CNS cells and provide new insights in the characterization of risk for the exposure to this class of pesticides. Full article

(This article belongs to the Section Cells of the Nervous System)

14 pages, 482 KiB

Open AccessArticle

Using Role Models and Game-Based Learning to Attract Adolescent Girls to STEM

by Ioanna Vekiri, Maria Meletiou-Mavrotheris and Oliver Mannay

Educ. Sci. 2024, 14(8), 836; https://doi.org/10.3390/educsci14080836 (registering DOI) - 31 Jul 2024

Abstract

Various pedagogical approaches have been proposed to attract more female students to STEM (science, technology, engineering, and mathematics), targeting student beliefs and perceptions that are linked to STEM study intentions. The current study, which took place in a secondary school in Cyprus and employed a quasi-experimental design, aims at contributing to this literature. Responses to pre- and post-questionnaires by 69 experimental and 27 control students show that students in the experimental group, who participated in an intervention in which they learned about the lives and accomplishments of STEM/STEAM role models via a game-based learning approach, improved their STEM ability perceptions compared to control group students, who reported similar pre-post survey levels of STEM ability perceptions. Female students benefited more compared to their male counterparts, and using a game-based learning approach contributed significantly to the effectiveness of students’ exposure to the role models. Taken together, study findings support the use of role models and learning games as tools to attract more female students to STEM. Full article

(This article belongs to the Section STEM Education)

26 pages, 2996 KiB

Open AccessArticle

Linear and Non-Linear Regression Methods for the Prediction of Lower Facial Measurements from Upper Facial Measurements

by Jacques Terblanche, Johan van der Merwe and Ryno Laubscher

Math. Comput. Appl. 2024, 29(4), 61; https://doi.org/10.3390/mca29040061 (registering DOI) - 31 Jul 2024

Abstract

Accurate assessment and prediction of mandible shape are fundamental prerequisites for successful orthognathic surgery. Previous studies have predominantly used linear models to predict lower facial structures from facial landmarks or measurements; the prediction errors for this did not meet clinical tolerances. This paper compared non-linear models, namely a Multilayer Perceptron (MLP), a Mixture Density Network (MDN), and a Random Forest (RF) model, with a Linear Regression (LR) model in an attempt to improve prediction accuracy. The models were fitted to a dataset of measurements from 155 subjects. The test-set mean absolute errors (MAEs) for distance-based target features for the MLP, MDN, RF, and LR models were respectively 2.77 mm, 2.79 mm, 2.95 mm, and 2.91 mm. Similarly, the MAEs for angle-based features were 3.09°, 3.11°, 3.07°, and 3.12° for each model, respectively. All models had comparable performance, with neural network-based methods having marginally fewer errors outside of clinical specifications. Therefore, while non-linear methods have the potential to outperform linear models in the prediction of lower facial measurements from upper facial measurements, current results suggest that further refinement is necessary prior to clinical use. Full article

(This article belongs to the Special Issue Current Problems and Advances in Computational and Applied Mechanics (AfriComp6))

25 pages, 48174 KiB

Open AccessArticle

Time-Series Explanatory Fault Prediction Framework for Marine Main Engine Using Explainable Artificial Intelligence

by Hong Je-Gal, Young-Seo Park, Seong-Ho Park, Ji-Uk Kim, Jung-Hee Yang, Sewon Kim and Hyun-Suk Lee

J. Mar. Sci. Eng. 2024, 12(8), 1296; https://doi.org/10.3390/jmse12081296 (registering DOI) - 31 Jul 2024

Abstract

As engine monitoring data has become more complex with an increasing number of sensors, fault prediction based on artificial intelligence (AI) has emerged. Existing fault prediction models using AI significantly improve the accuracy of predictions by effectively handling such complex data, but at the same time, the problem arises that the AI-based models cannot explain the rationale of their predictions to users. To address this issue, we propose a time-series explanatory fault prediction framework to provide an explainability even when using AI-based fault prediction models. It consists of a data feature reduction process, a fault prediction model training process using long short-term memory, and an interpretation process of the fault prediction model via an explainable AI method. In particular, the proposed framework can explain a fault prediction based on time-series data. Therefore, it indicates which part of the data was significant for the fault prediction not only in terms of sensor type but also in terms of time. Through extensive experiments, we evaluate the proposed framework using various fault data by comparing the prediction performance of fault prediction and by assessing how well the main pre-symptoms of the fault are extracted when predicting a fault. Full article

(This article belongs to the Special Issue Recent Advances on Intelligent Maintenance and Health Management in Ocean Engineering)

82 pages, 4399 KiB

Open AccessReview

Statistical Dynamics and Subgrid Modelling of Turbulence: From Isotropic to Inhomogeneous

by Jorgen S. Frederiksen, Vassili Kitsios and Terence J. O’Kane

Atmosphere 2024, 15(8), 921; https://doi.org/10.3390/atmos15080921 (registering DOI) - 31 Jul 2024

Abstract

Turbulence is the most important, ubiquitous, and difficult problem of classical physics. Feynman viewed it as essentially unsolved, without a rigorous mathematical basis to describe the statistical dynamics of this most complex of fluid motion. However, the paradigm shift came in 1959, with the formulation of the Eulerian direct interaction approximation (DIA) closure by Kraichnan. It was based on renormalized perturbation theory, like quantum electrodynamics, and is a bare vertex theory that is manifestly realizable. Here, we review some of the subsequent exciting achievements in closure theory and subgrid modelling. We also document in some detail the progress that has been made in extending statistical dynamical turbulence theory to the real world of interactions with mean flows, waves and inhomogeneities such as topography. This includes numerically efficient inhomogeneous closures, like the realizable quasi-diagonal direct interaction approximation (QDIA), and even more efficient Markovian Inhomogeneous Closures (MICs). Recent developments include the formulation and testing of an eddy-damped Markovian anisotropic closure (EDMAC) that is realizable in interactions with transient waves but is as efficient as the eddy-damped quasi-normal Markovian (EDQNM). As a similarly efficient closure, the realizable eddy-damped Markovian inhomogeneous closure (EDMIC) has been developed. Moreover, we present subgrid models that cater to the complex interactions that occur in geophysical flows. Recent progress includes the determination of complete sets of subgrid terms for skilful large-eddy simulations of baroclinic inhomogeneous turbulent atmospheric and oceanic flows interacting with Rossby waves and topography. The success of these inhomogeneous closures has also led to further applications in data assimilation and ensemble prediction and generalization to quantum fields. Full article

(This article belongs to the Special Issue Isotropic Turbulence: Recent Advances and Current Challenges)

18 pages, 554 KiB

Open AccessArticle

Adopting the Materiality Principle in Sustainable Operations Management

by Michel Leseure and David Bennett

Sustainability 2024, 16(15), 6572; https://doi.org/10.3390/su16156572 (registering DOI) - 31 Jul 2024

Abstract

This paper argues that operations management needs a commonly understood materiality principle to truly contribute to sustainability. A framework initially developed in international finance is generalized and used to model firms as borrowing resources from a common creditor, the environment, and to establish when a sustainable initiative is material in terms of impact. Our framework also solves the long-standing challenge of measuring impact at the level of an operations unit of analysis. Full article

(This article belongs to the Special Issue Sustainable Operations: Advancing Industry Practices for a Greener Future)

14 pages, 591 KiB

Open AccessArticle

Breeding Value Estimation Based on Morphological Evaluation of the Maremmano Horse Population through Factor Analysis

by Andrea Giontella, Maurizio Silvestrelli, Alessandro Cocciolone, Camillo Pieramati and Francesca Maria Sarti

Animals 2024, 14(15), 2232; https://doi.org/10.3390/ani14152232 (registering DOI) - 31 Jul 2024

Abstract

Morphological scoring is a common evaluation method for domestic animals. The National Association of Maremmano Breeders (ANAM) has provided a dataset containing the records of 600 horses, four metric measurements (cm) and 24 traits with a continuous evaluation scale, each one with 15 classes. Moreover, a body condition score (BCS) with five classes is included. In this study, factor analysis was conducted to create a small number of informative factors (3) obtained from these traits, and a new BLUP-AM-MT index was established. The New Estimated Breeding Value (NEBV1) of each horse was computed by adding the genetic indexes of the three factors, with each one multiplied using a coefficient indicated by ANAM. The practical feasibility of the NEBV1 was evaluated through Spearman correlations between the rankings of the NEBV1 and the rankings of the BLUP-AM-MT, estimated through the four biometric measures and the morphological score (MS) assigned to each horse by the ANAM judges. The factorial analysis was used to estimate three factors: the “Trunk Dimension”, “Legs” and “Length”. As the explained variance was only 32%, the model was rotated, and the heritability of the three factors were 0.51, 0.05 and 0.41, respectively. After rotation, the estimated correlations between the new NEBV1 and the biometric measures were improved. These results should encourage breeders to adopt a breeding value index that takes into consideration the factors derived from all the variables observed in the morphological evaluation of the Maremmano. In this way, breeders can use it to select the best animals for breeding. Full article

(This article belongs to the Special Issue Advances in Equine Genetics and Breeding)

17 pages, 1229 KiB

Open AccessArticle

Periostracum Cicadae Extract and N-Acetyldopamine Regulate the Sleep-Related Neurotransmitters in PCPA‑Induced Insomnia Rats

by Dongge Wang, Tingjuan Wu, Jinghui Jin, Yanpo Si, Yushi Wang, Xiaojia Ding, Tao Guo and Wenjun Wei

Molecules 2024, 29(15), 3638; https://doi.org/10.3390/molecules29153638 (registering DOI) - 31 Jul 2024

Abstract

Insomnia is the second most prevalent mental illness worldwide. Periostracum cicadae (PC), as an animal traditional Chinese medicine with rich pharmacological effects, has been documented as a treatment for children’s night cries, and later extended to treat insomnia. This study aimed to investigate the effects of PC extract and N-acetyldopamine compounds in ameliorating insomnia. The UPLC-ESI-QTOF-MS analysis determined that PC extract mainly contained N-acetyldopamine components. Previously, we also isolated some acetyldopamine polymers from PC extract, among which acetyldopamine dimer A (NADA) was present in high content. Molecular docking and molecular dynamic simulations demonstrated that NADA could form stable complexes with 5-HT1A, BDNF, and D2R proteins, respectively. The effects of PC extract and NADA on insomnia were evaluated in the PCPA-induced insomnia model. The results indicated that PC extract and NADA could effectively ameliorate hypothalamic pathology of insomnia rats, increase the levels of 5-HT, GABA, and BDNF, and decrease the levels of DA, DOPAC, and HVA. Meanwhile, the PC extract and NADA also could significantly affect the expression of 5-HT1A, BDNF, and DARPP-32 proteins. This study proved that PC extract and acetyldopamine dimer A could effectively improve PCPA‑induced insomnia in rats. It is speculated that the main pharmacological substances of PC were acetyldopamine components. Full article

(This article belongs to the Special Issue Isolation, Identification and Application of Biologically Active Natural Products—Second Edition)

15 pages, 5383 KiB

Open AccessArticle

Correlation between Discharge Noise and Flow Field Characteristics of Hydraulic Turbine

by Min Shi, Yu Wang and Xiaochun Lu

Water 2024, 16(15), 2176; https://doi.org/10.3390/w16152176 (registering DOI) - 31 Jul 2024

Abstract

The water flow within the turbine passage of a hydropower station exhibits high-speed closed-pressure flow. The flow field characteristics will directly affect the turbine’s operational efficiency and safety. To ensure the safe operation of the turbine and accurately monitor its flow state, the relationship between the flow characteristics in the turbine passage and its discharge noise must be established. In this study, the relationship between the flow field and the noise field of the turbine is explored using a combination of a model turbine passage discharge noise test and numerical simulation of flow field characteristics. Results show that the operating parameters are closely related to the discharge noise’s characteristics, in which the operating head and discharge of the unit’s operating parameters greatly influence the discharge noise in the flow passage. Hydrodynamic factors, such as fluctuation pressure and pressure in the flow field, show a strong correlation with the discharge noise characteristics. As the pressure and fluctuation pressure in the inlet area of the spiral case intensify, the sound pressure level (SPL) of the discharge noise increases and the main frequency decreases. A large-scale vortex easily forms in the spiral case and draft tube area, thereby causing low-frequency fluctuation and forming high-decibel noise. Also, the runner area is the main sound source region of the turbine passage. The research results will provide technical and theoretical support for the safe operation and accurate fault diagnosis of hydropower stations. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

16 pages, 1200 KiB

Open AccessArticle

Efficient Adsorption of Pollutants from Aqueous Solutions by Hydrochar-Based Hierarchical Porous Carbons

by Marija Ercegović, Jelena Petrović, Marija Koprivica, Marija Simić, Mirko Grubišić, Nikola Vuković and Jugoslav Krstić

Water 2024, 16(15), 2177; https://doi.org/10.3390/w16152177 (registering DOI) - 31 Jul 2024

Abstract

Three-dimensional hierarchical porous carbons (HPCs) created through hydrothermal carbonization and the subsequent chemical activation of miscanthus were tested as adsorbents of Pb²⁺ and methylene blue from the aqueous solution. The HPC pore structure was customized using various hydrochar precursors obtained through a longer reaction time and by adding acetic acid. HPC obtained from hydrochar derived from acetic acid’s addition exhibited the highest specific surface area due to a larger micropore volume. This adsorbent proved to be the most efficient in removing lead from aqueous solutions. The Langmuir isotherm best described the lead adsorption process onto HPC with q_m = 155.6 mg g⁻¹ and the pseudo-second-order kinetic model. HPC obtained from hydrochar produced with a longer reaction time exhibited improved methylene blue adsorption properties. The pseudo-second-order kinetic model and the Freundlich isotherm best described the experimental data. The theoretical maximum adsorption capacity for methylene blue was 316.0 mg g⁻¹. The type of hydrochar significantly impacted the yield and physical structure of HPCs, while having a lesser effect on the composition of surface functional groups. The results revealed the binding mechanism of each pollutant, highlighting the importance of biomass pretreatment on the structure of the resulting HPC and its effectiveness in water purification. Full article

(This article belongs to the Special Issue Membrane and Other Innovative Technologies for Water Purification: Design, Development, and Application)

18 pages, 8176 KiB

Open AccessArticle

Development of a Software Module for Studying Historical and Cultural Heritage Objects Using Non-Invasive Research Data

by Borys Chetverikov, Volodymyr Hlotov and Krzysztof Bakuła

Heritage 2024, 7(8), 4131-4148; https://doi.org/10.3390/heritage7080194 (registering DOI) - 31 Jul 2024

Abstract

This work proposes the development of a software module for studying historical and cultural heritage objects using remote and non-invasive research data. The module aims to integrate modern technologies such as image processing, data analysis, and visualization to provide access to heritage information for researchers, conservators, and the general public. Utilizing non-invasive data, such as geophysical surveys, enables the collection of information about heritage objects without causing damage. The module facilitates the analysis and visualization of this data as well as the creation of interactive object models, thereby promoting further research, preservation, and popularization of cultural heritage. The module consists of three blocks: defining areas for ground-based research using interferograms; constructing a comprehensive 3D model based on ground and underground research data; and refining the boundaries of historical-cultural heritage objects and establishing protective zones. The program is developed in the object-oriented programming language VisualBasic with additional modules. This developed module could become a significant tool for studying and preserving historical and cultural objects in the modern world. Full article

19 pages, 3331 KiB

Open AccessArticle

Senolytics and Senomorphics Targeting p38MAPK/NF-κB Pathway Protect Endothelial Cells from Oxidative Stress-Mediated Premature Senescence

by Jingyuan Ya and Ulvi Bayraktutan

Cells 2024, 13(15), 1292; https://doi.org/10.3390/cells13151292 (registering DOI) - 31 Jul 2024

Abstract

Oxidative stress is a prominent causal factor in the premature senescence of microvascular endothelial cells and the ensuing blood–brain barrier (BBB) dysfunction. Through the exposure of an in vitro model of human BBB, composed of brain microvascular endothelial cells (BMECs), astrocytes, and pericytes to H₂O₂, this study examined whether a specific targeting of the p38MAPK/NF-κB pathway and/or senescent cells could delay oxidative stress-mediated EC senescence and protect the BBB. Enlarged BMECs, displaying higher β-galactosidase activity, γH2AX staining, p16 expression, and impaired tubulogenic capacity, were regarded as senescent. The BBB established with senescent BMECs had reduced transendothelial electrical resistance and increased paracellular flux, which are markers of BBB integrity and function, respectively. Premature senescence disrupted plasma-membrane localization of the tight junction protein, zonula occludens-1, and elevated basement membrane-degrading matrix metalloproteinase-2 activity and pro-inflammatory cytokine release. Inhibition of p38MAPK by BIRB796 and NF-κB by QNZ and the elimination of senescent cells by a combination of dasatinib and quercetin attenuated the effects of H₂O₂ on senescence markers; suppressed release of the pro-inflammatory cytokines interleukin-8, monocyte chemoattractant protein-1, and intercellular adhesion molecule-1; restored tight junctional unity; and improved BBB function. In conclusion, therapeutic approaches that mitigate p38MAPK/NF-κB activity and senescent cell accumulation in the cerebrovasculature may successfully protect BBB from oxidative stress-induced BBB dysfunction. Full article

(This article belongs to the Section Cellular Aging)

15 pages, 985 KiB

Open AccessArticle

Biochemical Markers in The Prediction of Pregnancy Outcome in Gestational Diabetes Mellitus

by Vesna Mandić-Marković, Zorana Dobrijević, Dragana Robajac, Goran Miljuš, Miloš Šunderić, Ana Penezić, Olgica Nedić, Danijela Ardalić, Željko Miković, Ognjen Radojičić, Milica Mandić and Jelena Mitrović

Medicina 2024, 60(8), 1250; https://doi.org/10.3390/medicina60081250 (registering DOI) - 31 Jul 2024

Abstract

Background and Objectives: Gestational diabetes mellitus (GDM) may impact both maternal and fetal/neonatal health. The identification of prognostic indicators for GDM may improve risk assessment and selection of patient for intensive monitoring. The aim of this study was to find potential predictors of adverse pregnancy outcome in GDM and normoglycemic patients by comparing the levels of different biochemical parameters and the values of blood cell count (BCC) between GDM and normoglycemic patients and between patients with adverse and good outcome. Materials and Methods: Prospective clinical study included 49 patients with GDM (study group) and 44 healthy pregnant women (control group) who underwent oral glucose tolerance test (OGTT) at gestational age of 24–28 weeks. At the time of OGTT peripheral blood was taken for the determination of glucose levels, insulin, glycated hemoglobin, lipid status, homeostatic model assessment, BCC, iron and zinc metabolism, liver function, kidney function and inflammatory status. Each group was divided into two subgroups – normal and poor pregnancy outcome. Results: Higher RBC, hemoglobin concentration, hematocrit value, fasting glucose, uric acid and fibrinogen were found in GDM patients compared to control group. In GDM patients with poor pregnancy outcome values of fibrinogen, ALT, sedimentation rate, granulocyte and total leukocyte counts were elevated, while the serum level of zinc was significantly lower. Higher level of fibrinogen was found in normoglycemic patients with adverse pregnancy outcomes. ROC curve was constructed in order to assess fibrinogen’s biomarker potential. The established AUC value for diagnostic ROC was 0.816 (p < 0.001, 95% CI 0.691–0.941), while the AUC value for assessing fibrinogen’s potential to predict poor pregnancy outcome in GDM was 0.751 (p = 0.0096, 95% CI 0.561–0.941). Conclusions: The results of our study demonstrated that the best prognostic potential in GDM showed inflammation related parameters, identifying fibrinogen as a parameter with both diagnostic and prognostic ability. Full article

(This article belongs to the Section Obstetrics and Gynecology)

21 pages, 617 KiB

Open AccessArticle

Integration of CSR into the Marketing Mix for the Sustainable Development of Companies: A View from the Position of Financial Risk Management

by Abrorjon S. Kucharov, Anastasia A. Sozinova, Elena G. Popkova, Natalia M. Fomenko, Galina V. Vorontsova and Victoria N. Ostrovskaya

Risks 2024, 12(8), 121; https://doi.org/10.3390/risks12080121 (registering DOI) - 31 Jul 2024

Abstract

This paper is devoted to establishing the consequences of integrating CSR into the marketing mix for financial risks in modern companies. Based on the international statistics for 2023, we compiled a regression model of the dependence of financial risks on the integration of CSR into their marketing mix. Based on that, we developed a new system approach to managing companies’ sustainable development. Its features are marketing management of the sustainable development of companies, systemic management of social and financial risks to companies, and implementation of risk management through integrating CSR into the marketing mix. The main conclusion is that the sustainable development of companies in the Decade of Action requires a systemic integration of CSR into the marketing mix, for this will allow for the simultaneous reduction of social and financial risks. The theoretical significance of this conclusion consists in the disclosure of previously unknown cause-and-effect relationships between CSR and financial risks to companies, which are explained in this paper through the lens of the elements of the marketing mix in the 7P model. The originality of this research consists in developing novel marketing tools for the systemic management of social and financial risks for companies with the help of CSR. The practical significance relates to the fact that the offered recommendations on the more complete integration of CSR into their marketing mix will allow reducing financial risks and ensuring sustainable development of Russian companies in the Decade of Action (until 2030). The managerial significance is as follows: the developed system approach to managing companies’ sustainable development will improve the practice of risk management in companies due to previously unavailable joint management and the general reduction of social and financial risks. Full article

(This article belongs to the Special Issue Managing Financial Risks Based on Corporate Social Responsibility for Sustainable Development II)

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22 pages, 943 KiB

Open AccessArticle

Dupin Cyclides as a Subspace of Darboux Cyclides

by Jean Michel Menjanahary and Raimundas Vidunas

Mathematics 2024, 12(15), 2390; https://doi.org/10.3390/math12152390 (registering DOI) - 31 Jul 2024

Abstract

Dupin cyclides are interesting algebraic surfaces used in geometric design and architecture to join canal surfaces smoothly and to construct model surfaces. Dupin cyclides are special cases of Darboux cyclides, which in turn are rather general surfaces in

R^{3}

of degree 3 [...] Read more.

R^{3}

of degree 3 or 4. This article derives the algebraic conditions for the recognition of Dupin cyclides among the general implicit form of Darboux cyclides. We aim at practicable sets of algebraic equations on the coefficients of the implicit equation, each such set defining a complete intersection (of codimension 4) locally. Additionally, the article classifies all real surfaces and lower-dimensional degenerations defined by the implicit equation for Dupin cyclides. Full article

(This article belongs to the Special Issue New Trends in Algebraic Geometry and Its Applications, 2nd Edition)

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