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32 pages, 13931 KiB

Open AccessArticle

Alisertib and Barasertib Induce Cell Cycle Arrest and Mitochondria-Related Cell Death in Multiple Myeloma with Enhanced Efficacy Through Sequential Combination with BH3-Mimetics and Panobinostat

by Andrea Benedi, Manuel Beltrán-Visiedo, Nelia Jiménez-Alduán, Alfonso Serrano-Del Valle, Alberto Anel, Javier Naval and Isabel Marzo

Cancers 2025, 17(14), 2290; https://doi.org/10.3390/cancers17142290 (registering DOI) - 9 Jul 2025

Abstract

Background: The treatment landscape for multiple myeloma (MM) has significantly evolved in recent decades with novel therapies like proteasome inhibitors, immunomodulatory drugs and monoclonal antibodies. However, MM remains incurable, necessitating new pharmacological strategies. Mitotic kinases, such as Aurora proteins, have emerged as potential [...] Read more.

Background: The treatment landscape for multiple myeloma (MM) has significantly evolved in recent decades with novel therapies like proteasome inhibitors, immunomodulatory drugs and monoclonal antibodies. However, MM remains incurable, necessitating new pharmacological strategies. Mitotic kinases, such as Aurora proteins, have emerged as potential targets. Selective inhibitors of Aurora A and B,- alisertib (MLN8237) and barasertib (AZD1152), respectively, have shown anti-myeloma activity in preclinical studies, with alisertib demonstrating modest efficacy in early clinical trials. Methods and Results: This study investigated the mechanisms of action of alisertib and barasertib and their combination with antitumor agents in a panel of five MM cells lines. Both drugs induced cell cycle arrest phase and abnormal nuclear morphologies. Alisertib caused prolonged mitotic arrest, whereas barasertib induced transient arrest, both resulting in the activation of mitotic catastrophe. These findings revealed three potential outcomes: cell death, senescence, or polyploidy. High mitochondrial reactive oxygen species (mROS) were identified as possible drivers of cell death. Caspase inhibition reduced caspase-3 activation but did not prevent cell death. Interestingly, alisertib at low doses remained toxic to Bax/Bak^DKO cells, although mitochondrial potential disruption and cytochrome c release were observed. Sequential combinations of high-dose Aurora kinase inhibitors with BH3-mimetics, and in specific cases with panobinostat, showed a synergistic effect. Conversely, the simultaneous combination of alisertib and barasertib showed mostly antagonistic effects. Conclusions: Alisertib and barasertib emerge as potential in vitro candidates against MM, although further studies are needed to validate their efficacy and to find the best combinations with other molecules. Full article

(This article belongs to the Special Issue Advances in Molecular Oncology and Therapeutics)

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65 pages, 2945 KiB

Open AccessReview

Carbon Nanotubes as Excellent Adjuvants for Anticancer Therapeutics and Cancer Diagnosis: A Plethora of Laboratory Studies Versus Few Clinical Trials

by Silvana Alfei, Caterina Reggio and Guendalina Zuccari

Cells 2025, 14(14), 1052; https://doi.org/10.3390/cells14141052 (registering DOI) - 9 Jul 2025

Abstract

Encouraging discoveries and excellent advances in the fight against cancer have led to innovative therapies such as photothermal therapy (PTT), photodynamic therapy (PDT), drug targeting (DT), gene therapy (GT), immunotherapy (IT), and therapies that combine these treatments with conventional chemotherapy (CT). Furthermore, 2,041,910 [...] Read more.

Encouraging discoveries and excellent advances in the fight against cancer have led to innovative therapies such as photothermal therapy (PTT), photodynamic therapy (PDT), drug targeting (DT), gene therapy (GT), immunotherapy (IT), and therapies that combine these treatments with conventional chemotherapy (CT). Furthermore, 2,041,910 new cancer cases and 618,120 cancer deaths have been estimated in the United States for the year 2025. The low survival rate (<50%) and poor prognosis of several cancers, despite aggressive treatments, are due to therapy-induced secondary tumorigenesis and the emergence of drug resistance. Moreover, serious adverse effects and/or great pain usually arise during treatments and/or in survivors, thus lowering the overall effectiveness of these cures. Although prevention is of paramount importance, novel anticancer approaches are urgently needed to address these issues. In the field of anticancer nanomedicine, carbon nanotubes (CNTs) could be of exceptional help due to their intrinsic, unprecedented features, easy functionalization, and large surface area, allowing excellent drug loading. CNTs can serve as drug carriers and as ingredients to engineer multifunctional platforms associated with diverse treatments for both anticancer therapy and diagnosis. The present review debates the most relevant advancements about the adjuvant role that CNTs could have in cancer diagnosis and therapy if associated with PTT, PDT, DT, GT, CT, and IT. Numerous sensing strategies utilising various CNT-based sensors for cancer diagnosis have been discussed in detail, never forgetting the still not fully clarified toxicological aspects that may derive from their extensive use. The unsolved challenges that still hamper the possible translation of CNT-based material in clinics, including regulatory hurdles, have been discussed to push scientists to focus on the development of advanced synthetic and purification work-up procedures, thus achieving more perfect CNTs for their safer real-life clinical use. Full article

(This article belongs to the Special Issue New Advances in Anticancer Therapy)

23 pages, 816 KiB

Open AccessArticle

Large Angular Momentum

by Kenichi Konishi and Roberto Menta

Magnetism 2025, 5(3), 16; https://doi.org/10.3390/magnetism5030016 (registering DOI) - 9 Jul 2025

Abstract

The quantum states of a spin

\frac{1}{2}

(a qubit) are parametrized by the space

{CP}^{1} \sim S^{2}

, the Bloch sphere. A spin j for a generic j (a

2 j + 1

-state system) is represented instead by a [...] Read more.

The quantum states of a spin

\frac{1}{2}

(a qubit) are parametrized by the space

{CP}^{1} \sim S^{2}

, the Bloch sphere. A spin j for a generic j (a

2 j + 1

-state system) is represented instead by a point in a larger space,

{CP}^{2 j}

. Here we study the state of a single angular momentum/spin in the limit

j \to \infty

. A special class of states,

| j, n ⟩ \in {CP}^{2 j}

, with spin oriented towards definite spatial directions,

n \in S^{2}

, i.e.,

(\hat{J} \cdot n) | j, n ⟩ = j | j, n ⟩

, are found to behave as classical angular momenta,

j n

, in this limit. Vice versa, general spin states in

{CP}^{2 j}

do not become classical, even at a large j. We study these questions by analyzing the Stern–Gerlach processes, the angular momentum composition rule, and the rotation matrix. Our observations help to better clarify how classical mechanics emerges from quantum mechanics in this context (e.g., with the unique trajectories of a particle carrying a large spin in an inhomogeneous magnetic field) and to make the widespread idea that large spins somehow become classical more precise. Full article

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20 pages, 556 KiB

Open AccessArticle

Structural Conditions of Income Inequality Convergence Within the European Union

by Magdalena Cyrek

Sustainability 2025, 17(14), 6318; https://doi.org/10.3390/su17146318 (registering DOI) - 9 Jul 2025

Abstract

European integration aims to achieve spatially sustainable development across the member states. However, the success of socio-economic integration is conditioned by structural features of the economies, which, hitherto, appear highly diversified across the EU countries. The paper focuses on the structural conditions of [...] Read more.

European integration aims to achieve spatially sustainable development across the member states. However, the success of socio-economic integration is conditioned by structural features of the economies, which, hitherto, appear highly diversified across the EU countries. The paper focuses on the structural conditions of the process of income inequality convergence. It aims to identify differences in the convergence regarding the structural conditions of the economies. To fulfil the research tasks the paper classifies the 27 European member states according to their sectional employment structures using the Ward method. It then tests the appearance of beta convergence using FE panel models for the specified clusters of economies. It also considers structural change, measured by the NAV (norm of absolute value), as a determinant of income inequality convergence. The main research period covers 2009–2021. The findings of the paper confirm that income inequality convergence occurs within the groups of economies specified by different structural conditions. Importantly, the clustering according to the similarity of the employment structure overlaps with the division along the lines of the ‘new’ and ‘old’ member states, which proves the importance of historically shaped institutions for development. However, the observed convergence does not lead to improved social cohesion. Social policy, especially in the ‘new’ member states, is not able to offset the growth in market income inequality additionally stimulated by the structural changes. It can be concluded that an urgent need to design new solutions for social policy concerning structural transformation in employment in the EU emerges. Full article

23 pages, 8690 KiB

Open AccessArticle

Dynamically Triggered Damage Around Rock Tunnels: An Experimental and Theoretical Investigation

by Wanlu Wang, Ming Tao, Wenjun Ding and Rui Zhao

Appl. Sci. 2025, 15(14), 7716; https://doi.org/10.3390/app15147716 (registering DOI) - 9 Jul 2025

Abstract

Dynamic impact experiments based on high-speed photography and digital image correlation (DIC) techniques were carried out on sandstone specimens containing arched holes to investigate the effect of the incident angle. In addition, the complex function method based on conformal mapping was used to [...] Read more.

Dynamic impact experiments based on high-speed photography and digital image correlation (DIC) techniques were carried out on sandstone specimens containing arched holes to investigate the effect of the incident angle. In addition, the complex function method based on conformal mapping was used to theoretically calculate the transient dynamic stress distributions around the arched holes. The test results indicated that the strength and modulus of elasticity of the specimens under dynamic impact decreased and then increased with the increase of the inclination angle of the holes from 0 to 90° at intervals of 15°, reaching a minimum value at 60°, due to the large stress concentration at this angle leading to the shear failure of the specimen. During the experiment, rock debris ejections, spalling, and heaving were observed around the holes, and the rock debris ejections served as an indicator to identify the early fracture. The damage mechanism around the holes was revealed theoretically, i.e., the considerable compressive stress concentration in the perpendicular incidence direction around the arched hole and the tensile stress concentration on the incidence side led to the initiation of the damage around the cavity, and the theoretical results were in satisfactory agreement with the experimental results. In addition, the effect of the initial stress on the dynamic response of the arched tunnel was discussed. Full article

(This article belongs to the Special Issue Advances in Failure Mechanism and Numerical Methods for Geomaterials)

16 pages, 634 KiB

Open AccessArticle

Content of Phytomelatonin in Acorns (Quercus sp.) in Its Possible Use as a Phytogenic in Animal Nutrition

by Soundouss Kaabi, Brahim El Bouzdoudi, Mohammed L’bachir El Kbiach, Antonio Cano, Josefa Hernández-Ruiz and Marino B. Arnao

Processes 2025, 13(7), 2202; https://doi.org/10.3390/pr13072202 (registering DOI) - 9 Jul 2025

Abstract

Phytogenics are functional compounds with a growing interest in animal nutrition. These plant-derived compounds are often used to improve health and behavioral aspects in livestock, and used as antipathogenic agents. Melatonin, an indolic hormonal compound, has been studied as an interesting phytogenic in [...] Read more.

Phytogenics are functional compounds with a growing interest in animal nutrition. These plant-derived compounds are often used to improve health and behavioral aspects in livestock, and used as antipathogenic agents. Melatonin, an indolic hormonal compound, has been studied as an interesting phytogenic in animal nutrition. This study analyzes the possibilities of acorn-fed flour as a phytomelatonin contributor and its beneficial roles for health. The fruits of two varieties of acorns (Quercus suber var. Maamora and var. Bouhachem), recollected in two different regions of Morocco, have been studied according to their eco-physiological origin. The content in phytomelatonin was analyzed using a solid extractive method and determined by liquid chromatography with fluorescence detection. The results show great morphological differences between the two varieties, and also significant differences in their phytomelatonin content. It is concluded that acorn-fed flour can be an interesting raw material as a phytomelatonin contributor for the functionality of certain feeds and animals. More specific studies using phytomelatonin-rich plants as feed have been proposed to implement specific functionalities in livestock. Full article

(This article belongs to the Special Issue Advanced Natural Product Technology: Extraction, Separation, and Analysis)

20 pages, 1383 KiB

Open AccessArticle

Corrected Correlation for Turbulent Convective Heat Transfer in Concentric Annular Pipes

by Jinping Xu, Zhiyun Wang and Mo Yang

Energies 2025, 18(14), 3643; https://doi.org/10.3390/en18143643 (registering DOI) - 9 Jul 2025

Abstract

This paper addresses the errors that arise when calculating the convective heat transfer in concentric annular pipes by using the equivalent diameter and turbulent heat transfer formula for circular pipes. This approach employs numerical simulations to solve the Reynolds-averaged Navier–Stokes equations and uses [...] Read more.

This paper addresses the errors that arise when calculating the convective heat transfer in concentric annular pipes by using the equivalent diameter and turbulent heat transfer formula for circular pipes. This approach employs numerical simulations to solve the Reynolds-averaged Navier–Stokes equations and uses the realizable k–ε turbulence model and a low Reynolds number model near a wall. This study conducts numerical simulations of turbulent convective heat transfer within a concentric annular pipe. The results show that the shear stress on the inner wall surface of the concentric annular pipe and the heat transfer Nusselt number are significantly higher than those on the outer wall surface. At the same Reynolds number, both the entrance length and the peak velocity increase upon increasing the inner-to-outer diameter ratio. A correction factor for the inner-to-outer diameter ratio is proposed to achieve differentiated and accurate predictions for the inner and outer wall surfaces. The results clearly demonstrate the effect of the inner-to-outer diameter ratio on heat transfer. Full article

21 pages, 2856 KiB

Open AccessArticle

Taraxacum mongolicum Ameliorates DNCB-Induced Atopic Dermatitis-like Symptoms in Mice by Regulating Oxidative Stress, Inflammation, MAPK, and JAK/STAT/TSLP Signaling Pathways

by Wen-Ping Jiang, Hsi-Pin Hung, Jaung-Geng Lin, Ling-Huei Chang, Atsushi Inose and Guan-Jhong Huang

Int. J. Mol. Sci. 2025, 26(14), 6601; https://doi.org/10.3390/ijms26146601 (registering DOI) - 9 Jul 2025

Abstract

Atopic dermatitis (AD) is a chronic inflammatory skin disease stemming from genetic susceptibility and environmental factors. It is characterized by immune dysregulation, increased mast cell activity, elevated levels of immunoglobulin E (IgE), and excessive proinflammatory mediator expression. These factors contribute to hallmark symptoms [...] Read more.

Atopic dermatitis (AD) is a chronic inflammatory skin disease stemming from genetic susceptibility and environmental factors. It is characterized by immune dysregulation, increased mast cell activity, elevated levels of immunoglobulin E (IgE), and excessive proinflammatory mediator expression. These factors contribute to hallmark symptoms such as pruritus, erythema, and skin barrier dysfunction. In this study, we investigated the antioxidant and anti-inflammatory effects of Taraxacum mongolicum (WTM) water extract, as well as its skin barrier regulation and immune functions in AD. In the present study, we explored the therapeutic efficacy and underlying mechanisms of WTM in a BALB/c mouse model of AD induced by 2,4-dinitrochlorobenzene (DNCB). Mice were administered WTM orally or topically for 14 consecutive days. The results demonstrated that WTM treatment significantly alleviated clinical severity, showing reductions in skin lesion scores, epidermal thickness, mast cell infiltration, and scratching behavior, compared to the DNCB-treated group. Mechanistically, WTM reduced serum levels of IgE and proinflammatory cytokines (IL-4, IL-6, IL-1β, TNF-α, and IL-31) while suppressing the expression of the JAK/STAT/TSLP signaling pathway in skin tissues. Furthermore, WTM inhibited the TLR4/NF-κB and MAPK pathways and enhanced antioxidant defense by elevating superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPx) activities. These findings indicate that WTM attenuates DNCB-induced AD progression in mice, likely through the dual modulation of inflammatory signaling and oxidative stress. These findings suggest that WTM may modulate the immune response and alleviate AD symptoms by inhibiting the TLR4/NF-κB, MAPK, and JAK/STAT/TSLP pathways. Full article

(This article belongs to the Special Issue Molecular Research and Potential Effects of Medicinal Plants)

20 pages, 3166 KiB

Open AccessArticle

Engineered Cu₀.₅Ni₀.₅Al₂O₄/GCN Spinel Nanostructures for Dual-Functional Energy Storage and Electrocatalytic Water Splitting

by Abdus Sami, Sohail Ahmad, Ai-Dang Shan, Sijie Zhang, Liming Fu, Saima Farooq, Salam K. Al-Dawery, Hamed N. Harharah, Ramzi H. Harharah and Gasim Hayder

Processes 2025, 13(7), 2200; https://doi.org/10.3390/pr13072200 (registering DOI) - 9 Jul 2025

Abstract

The rapid growth in population and industrialization have significantly increased global energy demand, placing immense pressure on finite and environmentally harmful conventional fossil fuel-based energy sources. In this context, the development of hybrid electrocatalysts presents a crucial solution for energy conversion and storage, [...] Read more.

The rapid growth in population and industrialization have significantly increased global energy demand, placing immense pressure on finite and environmentally harmful conventional fossil fuel-based energy sources. In this context, the development of hybrid electrocatalysts presents a crucial solution for energy conversion and storage, addressing environmental challenges while meeting rising energy needs. In this study, the fabrication of a novel bifunctional catalyst, copper nickel aluminum spinel (Cu_0.5Ni_0.5Al₂O₄) supported on graphitic carbon nitride (GCN), using a solid-state synthesis process is reported. Because of its effective interface design and spinel cubic structure, the Cu_0.5Ni_0.5Al₂O₄/GCN nanocomposite, as synthesized, performs exceptionally well in electrochemical energy conversion, such as the oxygen evolution reaction (OER), the hydrogen evolution reaction (HER), and energy storage. In particular, compared to noble metals, Pt/C- and IrO₂-based water-splitting cells require higher voltages (1.70 V), while for the Cu_0.5Ni_0.5Al₂O₄/GCN nanocomposite, a voltage of 1.49 V is sufficient to generate a current density of 10 mA cm⁻² in an alkaline solution. When used as supercapacitor electrode materials, Cu_0.5Ni_0.5Al₂O₄/GCN nanocomposites show a specific capacitance of 1290 F g⁻¹ at a current density of 1 A g⁻¹ and maintain a specific capacitance of 609 F g⁻¹ even at a higher current density of 5 A g⁻¹, suggesting exceptional rate performance and charge storage capacity. The electrode’s exceptional capacitive properties were further confirmed through the determination of the roughness factor (Rf), which represents surface heterogeneity and active area enhancement, with a value of 345.5. These distinctive characteristics render the Cu_0.5Ni_0.5Al₂O₄/GCN composite a compelling alternative to fossil fuels in the ongoing quest for a viable replacement. Undoubtedly, the creation of the Cu_0.5Ni_0.5Al₂O₄/GCN composite represents a significant breakthrough in addressing the energy crisis and environmental concerns. Owing to its unique composition and electrocatalytic characteristics, it is considered a feasible choice in the pursuit of ecologically sustainable alternatives to fossil fuels. Full article

(This article belongs to the Special Issue Advances in Electrochemical Energy Storage and Conversion Technologies)

17 pages, 5613 KiB

Open AccessArticle

Single-Pixel Imaging Based on Enhanced Multi-Network Prior

by Jia Feng, Qianxi Li, Jiawei Dong, Qing Zhao and Hao Wang

Appl. Sci. 2025, 15(14), 7717; https://doi.org/10.3390/app15147717 (registering DOI) - 9 Jul 2025

Abstract

Single-pixel imaging (SPI) is a significant branch of computational imaging. Owing to the high sensitivity, low cost, and wide spectrum, it acquires extensive applications across various domains. Nevertheless, multiple measurements and long reconstruction time constrain its application. The application of neural networks has [...] Read more.

Single-pixel imaging (SPI) is a significant branch of computational imaging. Owing to the high sensitivity, low cost, and wide spectrum, it acquires extensive applications across various domains. Nevertheless, multiple measurements and long reconstruction time constrain its application. The application of neural networks has significantly improved the quality of reconstruction, but there is still a huge space for improvement in performance. SAE and Unet have different advantages in the field of SPI. However, there is no method that combines the advantages of these two networks for SPI reconstruction. Therefore, we propose the EMNP-SPI method for SPI reconstruction using SAE and Unet networks. The SAE makes use of the measurement dimension information and uses the group inverse to obtain the decoding matrix to enhance its generalization. The Unet uses different size convolution kernels and attention mechanisms to enhance feature extraction capabilities. Simulations and experiments confirm that our proposed enhanced multi-network prior method can significantly improve the quality of image reconstruction at low measurement rates. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

15 pages, 2579 KiB

Open AccessArticle

Photo-Scanning Capacitance Microscopy and Spectroscopy Study of Epitaxial GaAsN Layers and GaAsN P-I-N Solar Cell Structures

by Adam Szyszka, Wojciech Dawidowski, Damian Radziewicz and Beata Ściana

Nanomaterials 2025, 15(14), 1066; https://doi.org/10.3390/nano15141066 (registering DOI) - 9 Jul 2025

Abstract

This work presents a novel approach to investigating epitaxial GaAsN layers and GaAsN-based p-i-n solar cell structures using light-assisted scanning capacitance microscopy (SCM) and spectroscopy. Due to the technological challenges in growing high-quality GaAsN with controlled nitrogen incorporation, the epitaxial layers often exhibit [...] Read more.

This work presents a novel approach to investigating epitaxial GaAsN layers and GaAsN-based p-i-n solar cell structures using light-assisted scanning capacitance microscopy (SCM) and spectroscopy. Due to the technological challenges in growing high-quality GaAsN with controlled nitrogen incorporation, the epitaxial layers often exhibit inhomogeneity in their opto-electrical properties. By combining localized cross-section SCM measurements with wavelength-tunable optical excitation (800–1600 nm), we resolved carrier concentration profiles, internal electric fields, and deep-level transitions across the device structure at a nanoscale resolution. A comparative analysis between electrochemical capacitance–voltage (EC-V) profiling and photoluminescence spectroscopy confirmed multiple localized transitions, attributed to compositional fluctuations and nitrogen-induced defects within GaAsN. The SCM method revealed spatial variations in energy states, including discrete nitrogen-rich regions and gradual variations in the nitrogen content throughout the layer depth, which are not recognizable using standard characterization methods. Our results demonstrate the unique capability of the photo-scanning capacitance microscopy and spectroscopy technique to provide spatially resolved insights into complex dilute nitride structures, offering a universal and accessible tool for semiconductor structures and optoelectronic devices evaluation. Full article

(This article belongs to the Special Issue Spectroscopy and Microscopy Study of Nanomaterials)

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20 pages, 1491 KiB

Open AccessArticle

Performance Analysis of Stellar Refraction Autonomous Navigation for Cross-Domain Vehicles

by Yuchang Xu, Yang Zhang, Xiaokang Wang, Guanbing Zhang, Guang Yang and Hong Yuan

Remote Sens. 2025, 17(14), 2367; https://doi.org/10.3390/rs17142367 (registering DOI) - 9 Jul 2025

Abstract

Stellar refraction autonomous navigation provides a promising alternative for cross-domain vehicles, particularly in near-space environments where traditional inertial and satellite navigation methods face limitations. This study develops a stellar refraction navigation system that utilizes stellar refraction angle observations and the Implicit Unscented Kalman [...] Read more.

Stellar refraction autonomous navigation provides a promising alternative for cross-domain vehicles, particularly in near-space environments where traditional inertial and satellite navigation methods face limitations. This study develops a stellar refraction navigation system that utilizes stellar refraction angle observations and the Implicit Unscented Kalman Filter (IUKF) for state estimation. A representative orbit with altitudes ranging from 60 km to 200 km is designed to simulate cross-domain flight conditions. The navigation performance is analyzed under varying conditions, including orbital altitude, as well as star sensor design parameters, such as limiting magnitude, field of view (FOV) value, and measurement error, along with different sampling intervals. The simulation results show that increasing the limiting magnitude from 5 to 8 reduced the position error from 705.19 m to below 1 m, with optimal accuracy reaching 0.89 m when using a 20° × 20° field of view and a 3 s sampling interval. In addition, shorter sampling intervals improved accuracy and filter stability, while longer intervals introduced greater integration drift. When the sampling interval reached 100 s, position error grew to the kilometer level. These findings validate the feasibility of using stellar refraction for autonomous navigation in cross-domain scenarios and provide design guidance for optimizing star sensor configurations and sampling strategies in future near-space navigation systems. Full article

(This article belongs to the Special Issue Autonomous Space Navigation (Second Edition))

22 pages, 1295 KiB

Open AccessArticle

Machine Learning Prediction of Airfoil Aerodynamic Performance Using Neural Network Ensembles

by Diana-Andreea Sterpu, Daniel Măriuța, Grigore Cican, Ciprian-Marius Larco and Lucian-Teodor Grigorie

Appl. Sci. 2025, 15(14), 7720; https://doi.org/10.3390/app15147720 (registering DOI) - 9 Jul 2025

Abstract

Reliable aerodynamic performance estimation is essential for both preliminary design and optimization in various aeronautical applications. In this study, a hybrid deep learning model is proposed, combining convolutional neural networks (CNNs) and operating directly on raw airfoil geometry, with parallel branches of fully [...] Read more.

Reliable aerodynamic performance estimation is essential for both preliminary design and optimization in various aeronautical applications. In this study, a hybrid deep learning model is proposed, combining convolutional neural networks (CNNs) and operating directly on raw airfoil geometry, with parallel branches of fully connected deep neural networks (DNNs) that process operational parameters and engineered features. The model is trained on an extensive database of NACA four-digit airfoils, covering angles of attack ranging from −5° to 14° and ten Reynolds numbers increasing in steps of 500,000 from 500,000 up to 5,000,000. As a novel contribution, this work investigates the impact of random seed initialization on model accuracy and reproducibility and introduces a seed-based ensemble strategy to enhance generalization. The best-performing single-seed model tested (seed 0) achieves a mean absolute percentage error (MAPE) of 1.1% with an R² of 0.9998 for the lift coefficient prediction and 0.57% with an R²of 0.9954 for the drag coefficient prediction. In comparison, the best ensemble model tested (seeds 610, 987, and 75025) achieves a lift coefficient MAPE of 1.43%, corresponding to R²0.9999, and a drag coefficient MAPE of 1.19%, corresponding to R² = 0.9968. All the tested seed dependencies in this paper (ten single seeds and five ensembles) demonstrate an overall R² greater than 0.97, which reflects the model architecture’s strong foundation. The novelty of this study lies in the demonstration that the same machine learning model, trained on identical data and architecture, can exhibit up to 250% variation in prediction error solely due to differences in random seed selection. This finding highlights the often-overlooked impact of seed initialization on model performance and highlights the necessity of treating seed choice as an active design parameter in ML aerodynamic predictions. Full article

(This article belongs to the Special Issue 5th Anniversary of Aerospace Science and Engineering Section—Recent Advances in Aerospace)

14 pages, 273 KiB

Open AccessReview

Artificial Intelligence Tools in Surgical Research: A Narrative Review of Current Applications and Ethical Challenges

by Bryan Lim, Ishith Seth, Jevan Cevik, Xin Mu, Foti Sofiadellis, Roberto Cuomo and Warren M. Rozen

Surgeries 2025, 6(3), 55; https://doi.org/10.3390/surgeries6030055 (registering DOI) - 9 Jul 2025

Abstract

Background/Objectives: Artificial intelligence (AI) holds great potential to reshape the academic paradigm. They can process large volumes of information, assist in academic literature reviews, and augment the overall quality of scientific discourse. This narrative review examines the application of various AI tools in [...] Read more.

Background/Objectives: Artificial intelligence (AI) holds great potential to reshape the academic paradigm. They can process large volumes of information, assist in academic literature reviews, and augment the overall quality of scientific discourse. This narrative review examines the application of various AI tools in surgical research, its present capabilities, future directions, and potential challenges. Methods: A search was performed by two independent authors for relevant studies on PubMed, Cochrane Library, Web of Science, and EMBASE databases from January 1901 until March 2025. Studies were included if they were written in English and discussed the use of AI tools in surgical research. They were excluded if they were not in English and discussed the use of AI tools in medical research. Results: Forty-two articles were included in this review. The findings underscore a range of AI tools such as writing enhancers, LLMs, search engine optimizers, image interpreters and generators, content organization and search systems, and audio analysis tools, along with their influence on medical research. Despite the multitude of benefits presented by AI tools, risks such as data security, inherent biases, accuracy, and ethical dilemmas are of concern and warrant attention. Conclusions: AI could offer significant contributions to medical research in the form of superior data analysis, predictive abilities, personalized treatment strategies, enhanced diagnostic accuracy, amplified research, educational, and publication processes. However, to unlock the full potential of AI in surgical research, we must institute robust frameworks and ethical guidelines. Full article

20 pages, 2037 KiB

Open AccessArticle

A UNet++-Based Approach for Delamination Imaging in CFRP Laminates Using Full Wavefield

by Yitian Yan, Kang Yang, Yaxun Gou, Zhifeng Tang, Fuzai Lv, Zhoumo Zeng, Jian Li and Yang Liu

Sensors 2025, 25(14), 4292; https://doi.org/10.3390/s25144292 (registering DOI) - 9 Jul 2025

Abstract

The timely detection of delamination is essential for preventing catastrophic failures and extending the service life of carbon fiber-reinforced polymers (CFRP). Full wavefields in CFRP encapsulate extensive information on the interaction between guided waves and structural damage, making them a widely utilized tool [...] Read more.

The timely detection of delamination is essential for preventing catastrophic failures and extending the service life of carbon fiber-reinforced polymers (CFRP). Full wavefields in CFRP encapsulate extensive information on the interaction between guided waves and structural damage, making them a widely utilized tool for damage mapping. However, due to the multimodal and dispersive nature of guided waves, interpreting full wavefields remains a significant challenge. This study proposes an end-to-end delamination imaging approach based on UNet++ using 2D frequency domain spectra (FDS) derived from full wavefield data. The proposed method is validated through a self-constructed simulation dataset, experimental data collected using Scanning Laser Doppler Vibrometry, and a publicly available dataset created by Kudela and Ijjeh. The results on the simulated data show that UNet++, trained with multi-frequency FDS, can accurately predict the location, shape, and size of delamination while effectively handling frequency offsets and noise interference in the input FDS. Experimental results further indicate that the model, trained exclusively on simulated data, can be directly applied to real-world scenarios, delivering artifact-free delamination imaging. Full article

(This article belongs to the Section Sensing and Imaging)

23 pages, 11832 KiB

Open AccessArticle

Investigation of Flexibility Enhancement Mechanisms and Microstructural Characteristics in Emulsified Asphalt and Latex-Modified Cement

by Wen Liu, Yong Huang, Yulin He, Hanyu Wei, Ruyun Bai, Huan Li, Qiushuang Cui and Sining Li

Sustainability 2025, 17(14), 6317; https://doi.org/10.3390/su17146317 (registering DOI) - 9 Jul 2025

Abstract

The inherent limitations of ordinary cement mortar—characterized by its high brittleness and low flexibility—result in a diminished load-bearing capacity, predisposing concrete pavements to cracking. A novel approach has been proposed to enhance material performance by incorporating emulsified asphalt and latex into ordinary cement [...] Read more.

The inherent limitations of ordinary cement mortar—characterized by its high brittleness and low flexibility—result in a diminished load-bearing capacity, predisposing concrete pavements to cracking. A novel approach has been proposed to enhance material performance by incorporating emulsified asphalt and latex into ordinary cement mortar, aiming to improve the flexibility and durability of concrete pavements effectively. To further validate the feasibility of this proposed approach, a series of comprehensive experimental investigations were conducted, with corresponding conclusions detailed herein. As outlined below, the flexibility properties of the modified cement mortar were systematically evaluated at curing durations of 3, 7, and 28 days. The ratio of flexural to compressive strength can be increased by up to 38.9% at 8% emulsified asphalt content at the age of 28 days, and by up to 50% at 8% latex content. The mechanism of emulsified asphalt and latex-modified cement mortar was systematically investigated using a suite of analytical techniques: X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TG-DTG), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). Through comprehensive analyses of microscopic morphology, hydration products, and elemental distribution, the enhancement in cement mortar toughness can be attributed to two primary mechanisms. First, Ca²⁺ ions combine with the carbonyl groups of emulsified asphalt to form a flexible film structure during cement hydration, thereby reducing the formation of brittle hydrates. Second, active functional groups in latex form a three-dimensional network, regulating internal expansion-contraction tension in the modified mortar and extending its service life. Full article

(This article belongs to the Special Issue Advances in Cement-Based Materials and Applications for Sustainable Building and Civil Engineering)

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24 pages, 5988 KiB

Open AccessArticle

Research on Construction Sequencing and Deformation Control for Foundation Pit Groups

by Ziwei Yin, Ruizhe Jin, Shouye Guan, Zhiwei Chen, Guoliang Dai and Wenbo Zhu

Appl. Sci. 2025, 15(14), 7719; https://doi.org/10.3390/app15147719 (registering DOI) - 9 Jul 2025

Abstract

With the rapid urbanization and increasing development of underground spaces, foundation pit groups in complex geological environments encounter considerable challenges in deformation control. These challenges are especially prominent in cases of adjacent constructions, complex geology, and environmentally sensitive areas. Nevertheless, existing research is [...] Read more.

With the rapid urbanization and increasing development of underground spaces, foundation pit groups in complex geological environments encounter considerable challenges in deformation control. These challenges are especially prominent in cases of adjacent constructions, complex geology, and environmentally sensitive areas. Nevertheless, existing research is lacking in systematic analysis of construction sequencing and the interaction mechanisms between foundation pit groups. This results in gaps in comprehending stress redistribution and optimal excavation strategies for such configurations. To address these gaps, this study integrates physical model tests and PLAXIS 3D numerical simulations to explore the Nanjing Jiangbei New District Phase II pit groups. It concentrates on deformations in segmented and adjacent configurations under varying excavation sequences and spacing conditions. Key findings reveal that simultaneous excavation in segmented pit groups optimizes deformation control through symmetrical stress relief via bilateral unloading, reducing shared diaphragm wall displacement by 18–25% compared to sequential methods. Sequential excavations induce complex soil stress redistribution from asymmetric unloading, with deep-to-shallow sequencing minimizing exterior wall deformation (≤0.12%He). For adjacent foundation pit groups, simultaneous excavation achieves minimum displacement interference, while phased construction requires prioritizing large-section excavation first to mitigate cumulative deformations through optimized stress transfer. When the spacing-to-depth ratio (B/He) is below 1, horizontal displacements of retaining structures increase by 43% due to spacing effects. This study quantifies the effects of excavation sequences and spacing configurations on pit group deformation, establishing a theoretical framework for optimizing construction strategies and enhancing retaining structure stability. The findings are highly significant for underground engineering design and construction in complex urban geological settings, especially in high-density areas with spatial and geotechnical constraints. Full article

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22 pages, 2221 KiB

Open AccessArticle

Enhanced Pedestrian Navigation with Wearable IMU: Forward–Backward Navigation and RTS Smoothing Techniques

by Yilei Shen, Yiqing Yao, Chenxi Yang and Xiang Xu

Technologies 2025, 13(7), 296; https://doi.org/10.3390/technologies13070296 (registering DOI) - 9 Jul 2025

Abstract

Accurate and reliable pedestrian positioning service is essential for providing Indoor Location-Based Services (ILBSs). Zero-Velocity Update (ZUPT)-aided Strapdown Inertial Navigation System (SINS) based on foot-mounted wearable Inertial Measurement Units (IMUs) has shown great performance in pedestrian navigation systems. Though the velocity errors will [...] Read more.

Accurate and reliable pedestrian positioning service is essential for providing Indoor Location-Based Services (ILBSs). Zero-Velocity Update (ZUPT)-aided Strapdown Inertial Navigation System (SINS) based on foot-mounted wearable Inertial Measurement Units (IMUs) has shown great performance in pedestrian navigation systems. Though the velocity errors will be corrected once zero-velocity measurement is available, the navigation system errors accumulated during measurement outages are yet to be further optimized by utilizing historical data during both stance and swing phases of pedestrian gait. Thus, in this paper, a novel Forward–Backward navigation and Rauch–Tung–Striebel smoothing (FB-RTS) navigation scheme is proposed. First, to efficiently re-estimate past system state and reduce accumulated navigation error once zero-velocity measurement is available, both the forward and backward integration method and the corresponding error equations are constructed. Second, to further improve navigation accuracy and reliability by exploiting historical observation information, both backward and forward RTS algorithms are established, where the system model and observation model are built under the output correction mode. Finally, both navigation results are combined to achieve the final estimation of attitude and velocity, where the position is recalculated by the optimized data. Through simulation experiments and two sets of field tests, the FB-RTS algorithm demonstrated superior performance in reducing navigation errors and smoothing pedestrian trajectories compared to traditional ZUPT method and both the FB and the RTS method, whose advantage becomes more pronounced over longer navigation periods than the traditional methods, offering a robust solution for positioning applications in smart buildings, indoor wayfinding, and emergency response operations. Full article

(This article belongs to the Special Issue Wearable Vital Signs and Activities Detection: Systems and Applications)

17 pages, 1205 KiB

Open AccessArticle

Evaluating the Characteristics of Disaster Waste Management in Practice: Case Studies from Queensland and New South Wales, Australia

by Savindi Caldera, Chamari Jayarathna and Cheryl Desha

Sustainability 2025, 17(14), 6300; https://doi.org/10.3390/su17146300 (registering DOI) - 9 Jul 2025

Abstract

Disaster waste management (DWM) has gained much attention due to the issues associated with the enormous amount of disaster waste generated by natural disasters. However, moving beyond ad hoc and champion-based take-up by practitioners, there is generally a lack of momentum towards mainstreaming [...] Read more.

Disaster waste management (DWM) has gained much attention due to the issues associated with the enormous amount of disaster waste generated by natural disasters. However, moving beyond ad hoc and champion-based take-up by practitioners, there is generally a lack of momentum towards mainstreaming such DWM practices to achieve resilient outcomes. This study aims to explore the characteristics of DWM practices, drawing on the lived experiences of industry practitioners and government decision-makers. An interpretive case study method was used to investigate how local government organisations could readily engage in effective DWM processes using the “Resilient disaster management framework” previously established by the research team. Insights include a lack of documented plans for DWM and at best a moderate focus on recovery processes for disaster waste. With these issues counterproductive to community resilience outcomes, there is an urgent need to better manage disaster waste, which we propose can be enabled and supported through DWM plans. The extended ‘resilient DWM framework’ proposed in this study provides a useful reference to prepare practical, agile, and comprehensive DWM plans. Full article

(This article belongs to the Special Issue Municipal Solid Waste Management (2nd Edition)—Innovative Solutions and Sustainable Strategies)

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14 pages, 456 KiB

Open AccessArticle

The Cost-Effectiveness of Increased Yogurt Intake in Type 2 Diabetes in Japan

by Ryota Wakayama, Michihiro Araki, Mieko Nakamura and Nayu Ikeda

Nutrients 2025, 17(14), 2278; https://doi.org/10.3390/nu17142278 (registering DOI) - 9 Jul 2025

Abstract

Background/Objectives: A healthy diet helps prevent noncommunicable diseases, and dairy is an essential part of this diet. Multiple meta-analyses have shown an inverse association between yogurt intake and type 2 diabetes (T2D). This study aimed to develop a simulation model and evaluate [...] Read more.

Background/Objectives: A healthy diet helps prevent noncommunicable diseases, and dairy is an essential part of this diet. Multiple meta-analyses have shown an inverse association between yogurt intake and type 2 diabetes (T2D). This study aimed to develop a simulation model and evaluate the medical and economic effects of increased yogurt intake on T2D. Methods: It predicted the T2D incidence rate, T2D mortality rate, and national healthcare expenditures (NHE) over 10 years using a Markov model for the Japanese population aged 40–79 years. Results: By increasing yogurt intake to 160 g/day or 80 g/day, the incidence rate of T2D decreased by 16.1% or 5.9%, the T2D-related mortality rate decreased by 1.6% or 0.6%, and the NHE was predicted to decrease by 2.4% and 0.9%, respectively. Conclusions: Increasing yogurt intake may be an effective strategy to prevent T2D and reduce NHE. Full article

(This article belongs to the Special Issue The Diabetes Diet: Making a Healthy Eating Plan)

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25 pages, 2823 KiB

Open AccessArticle

A Reflection on the Conservation of Waterlogged Wood: Do Original Artefacts Truly Belong in Public Museum Collections?

by Miran Erič, David Stopar, Enej Guček Puhar, Lidija Korat Bensa, Nuša Saje, Aleš Jaklič and Franc Solina

Heritage 2025, 8(7), 273; https://doi.org/10.3390/heritage8070273 (registering DOI) - 9 Jul 2025

Abstract

The last decade has seen a transformative advancement in computational technologies, enabling the precise creation, evaluation, visualization, and reproduction of high-fidelity three-dimensional (3D) models of archaeological sites and artefacts. With the advent of 3D printing, both small- and large-scale objects can now be [...] Read more.

The last decade has seen a transformative advancement in computational technologies, enabling the precise creation, evaluation, visualization, and reproduction of high-fidelity three-dimensional (3D) models of archaeological sites and artefacts. With the advent of 3D printing, both small- and large-scale objects can now be reproduced with remarkable accuracy and at customizable scales. Artefacts composed of organic materials—such as wood—are inherently susceptible to biological degradation and thus require extensive, long-term conservation employing costly methodologies. These procedures often raise environmental concerns and lead to irreversible alterations in the wood’s chemical composition, dimensional properties, and the intangible essence of the original artefact. In the context of public education and the dissemination of knowledge about historical technologies and objects, 3D replicas can effectively fulfill the same purpose as original artefacts, without compromising interpretative value or cultural significance. Furthermore, the digital data embedded in 3D surface and object models provides a wealth of supplementary information that cannot be captured, preserved, or documented through conventional techniques. Waterlogged wooden objects can now be thoroughly documented in 3D, enabling ongoing, non-invasive scientific analysis. Given these capabilities, it is imperative to revisit the philosophical and ethical foundations of preserving waterlogged wood and to adopt innovative strategies for the conservation and presentation of wooden artefacts. These new paradigms can serve educational, research, and outreach purposes—core functions of contemporary museums. Full article

18 pages, 1079 KiB

Open AccessArticle

Driver Clustering Based on Individual Curve Path Selection Preference

by Gergo Igneczi, Tamas Dobay, Erno Horvath and Krisztian Nyilas

Appl. Sci. 2025, 15(14), 7718; https://doi.org/10.3390/app15147718 (registering DOI) - 9 Jul 2025

Abstract

The development of Advanced Driver Assistance Systems (ADASs) has reached a stage where, in addition to the traditional challenges of path planning and control, there is an increasing focus on the behavior of these systems. Assistance functions shall be personalized to deliver a [...] Read more.

The development of Advanced Driver Assistance Systems (ADASs) has reached a stage where, in addition to the traditional challenges of path planning and control, there is an increasing focus on the behavior of these systems. Assistance functions shall be personalized to deliver a full user experience. Therefore, driver modeling is a key area of research for next-generation ADASs. One of the most common tasks in everyday driving is lane keeping. Drivers are assisted by lane-keeping systems to keep their vehicle in the center of the lane. However, human drivers often deviate from the center line. It has been shown that the driver’s choice to deviate from the center line can be modeled by a linear combination of preview curvature information. This model is called the Linear Driver Model. In this paper, we fit the LDM parameters to real driving data. The drivers are then clustered based on the individual parameters. It is shown that clusters are not only formed by the numerical similarity of the driver parameters, but the drivers in a cluster actually have similar behavior in terms of path selection. Finally, an Extended Kalman Filter (EKF) is proposed to learn the model parameters at run-time. Any new driver can be classified into one of the driver type groups. This information can be used to modify the behavior of the lane-keeping system to mimic human driving, resulting in a more personalized driving experience. Full article

(This article belongs to the Special Issue Sustainable Mobility and Transportation (SMTS 2025))

13 pages, 3158 KiB

Open AccessArticle

Process Safety Assessment of the Entire Nitration Process of Benzotriazole Ketone

by Yingxia Sheng, Qianjin Xiao, Hui Hu, Tianya Zhang and Guofeng Guan

Processes 2025, 13(7), 2201; https://doi.org/10.3390/pr13072201 (registering DOI) - 9 Jul 2025

Abstract

To ensure the inherent safety of fine chemical nitration processes, the nitration reaction of benzotriazole ketone was selected as the research object. The thermal decomposition and reaction characteristics of the nitration system were studied using a combination of differential scanning calorimetry (DSC), reaction [...] Read more.

To ensure the inherent safety of fine chemical nitration processes, the nitration reaction of benzotriazole ketone was selected as the research object. The thermal decomposition and reaction characteristics of the nitration system were studied using a combination of differential scanning calorimetry (DSC), reaction calorimetry (RC1), and accelerating rate calorimetry (ARC). The results showed that the nitration product released 455.77 kJ/kg of heat upon decomposition, significantly higher than the 306.86 kJ/kg of the original material, indicating increased thermal risk. Through process hazard analysis based on GB/T 42300-2022, key parameters such as the temperature at which the time to maximum rate is 24 h under adiabatic conditions (T_D24), maximum temperature of the synthesis reaction (MTSR), and maximum temperature for technical reason (MTT) were determined, and the reaction was classified as hazard level 5, suggesting a high risk of runaway and secondary explosion. Process intensification strategies were then proposed and verified by dynamic calorimetry: the adiabatic temperature increase (ΔT_ad) was reduced from 86.70 °C in the semi-batch reactor to 19.95 °C in the optimized continuous process, effectively improving thermal safety. These findings provide a reliable reference for the quantitative risk evaluation and safe design of nitration processes in fine chemical manufacturing. Full article

(This article belongs to the Special Issue Advances in Computational Fluid Dynamics (CFD) Simulation of Thermal Chemical Processes)

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30 pages, 2194 KiB

Open AccessArticle

Design and Validation of an Active Headrest System with Integrated Sensing in Rear-End Crash Scenarios

by Alexandru Ionut Radu, Bogdan Adrian Tolea, Horia Beles, Florin Bogdan Scurt and Adrian Nicolaie Tusinean

Sensors 2025, 25(14), 4291; https://doi.org/10.3390/s25144291 (registering DOI) - 9 Jul 2025

Abstract

Rear-end collisions represent a major concern in automotive safety, particularly due to the risk of whiplash injuries among vehicle occupants. The accurate simulation of occupant kinematics during such impacts is critical for the development of advanced safety systems. This paper presents an enhanced [...] Read more.

Rear-end collisions represent a major concern in automotive safety, particularly due to the risk of whiplash injuries among vehicle occupants. The accurate simulation of occupant kinematics during such impacts is critical for the development of advanced safety systems. This paper presents an enhanced multibody simulation model specifically designed for rear-end crash scenarios, incorporating integrated active headrest mechanisms and sensor-based activation logic. The model combines detailed representations of vehicle structures, suspension systems, restraint systems, and occupant biomechanics, allowing for the precise prediction of crash dynamics and occupant responses. The system was developed using Simscape Multibody, with CAD-derived components interconnected through physical joints and validated using controlled experimental crash tests. Special attention was given to modelling contact forces, suspension behaviour, and actuator response times for the active headrest system. The model achieved a root mean square error (RMSE) of 4.19 m/s² and a mean absolute percentage error (MAPE) of 0.71% when comparing head acceleration in frontal collision tests, confirming its high accuracy. Validation results demonstrate that the model accurately reproduces occupant kinematics and head acceleration profiles, confirming its reliability and effectiveness as a predictive tool. This research highlights the critical role of integrated sensor-actuator systems in improving occupant safety and provides a flexible platform for future studies on intelligent vehicle safety technologies. Full article

(This article belongs to the Special Issue Intelligent Sensors for Smart and Autonomous Vehicles)

18 pages, 4891 KiB

Open AccessArticle

Functional Identification Reveals that TaTGA16-2D Promotes Drought and Heat Tolerance

by Jingna Ru, Jiamin Hao, Xiaoqian Ji, Bingqing Hao, Jiale Yang, Hongtao Wang, Baoquan Quan, Pengyan Guo, Jiping Zhao, Chao Wang, Huawei Shi and Zhaoshi Xu

Plants 2025, 14(14), 2125; https://doi.org/10.3390/plants14142125 (registering DOI) - 9 Jul 2025

Abstract

The TGACG motif-binding factor (TGA) family is an important group of basic region/leucine zipper (bZIP) transcription factors in plants, playing crucial roles in plant development and stress responses. This study conducted a comprehensive genome-wide analysis of the TGA transcription factor (TF) family in [...] Read more.

The TGACG motif-binding factor (TGA) family is an important group of basic region/leucine zipper (bZIP) transcription factors in plants, playing crucial roles in plant development and stress responses. This study conducted a comprehensive genome-wide analysis of the TGA transcription factor (TF) family in common wheat (Triticum aestivum L.). A total of 48 wheat TGAs were identified and classified into four subgroups. Collinearity analysis of the TGAs between wheat and other species identified multiple duplicated gene pairs and highlighted the presence of highly conserved TGAs in wheat. Whole-genome and segmental duplications were identified as the primary drivers of TaTGA expansion. Expression pattern analysis indicated that TaTGAs are involved in plant development and responses to abiotic stresses, including drought, heat, and cold treatment. Among these, TaTGA16-2D was significantly upregulated under both drought and heat stresses, showing more than a five-fold increase in expression. Subcellular localization confirmed its nucleus localization. Functional validation through ectopic expression in Arabidopsis demonstrated that transgenic lines overexpressing TaTGA16-2D exhibited significantly improved stress tolerance. Under heat stress, the survival rates of transgenic lines exceeded 34%, compared to less than 18% in wild-type plants. Overall, this study provides valuable insights into the evolution and functional roles of TaTGAs and identifies TaTGA16-2D as a promising candidate to enhance abiotic stress tolerance in wheat via molecular breeding. Full article

(This article belongs to the Section Plant Response to Abiotic Stress and Climate Change)

15 pages, 2181 KiB

Open AccessArticle

The Impact of Shifts in Both Precipitation Pattern and Temperature Changes on River Discharge in Central Japan

by Bing Zhang, Jingyan Han, Jianbo Liu and Yong Zhao

Hydrology 2025, 12(7), 187; https://doi.org/10.3390/hydrology12070187 (registering DOI) - 9 Jul 2025

Abstract

Rivers play a crucial role in the hydrological cycle and serve as essential freshwater resources for both human populations and ecosystems. Climate change significantly alters precipitation patterns and river discharge variability. However, the impact of precipitation patterns (rainfall and snowfall) and air temperature [...] Read more.

Rivers play a crucial role in the hydrological cycle and serve as essential freshwater resources for both human populations and ecosystems. Climate change significantly alters precipitation patterns and river discharge variability. However, the impact of precipitation patterns (rainfall and snowfall) and air temperature on river discharge in coastal zones remains inadequately understood. This study focused on Toyama Prefecture, located along the Sea of Japan, as a representative coastal area. We analyzed over 30 years of datasets, including air temperature, precipitation, snowfall, and river discharge, to assess the effects of climate change on river discharge. Trends in hydroclimatic datasets were assessed using the rescaled adjusted partial sums (RAPS) method and the Mann–Kendall (MK) non-parametric test. Furthermore, a correlation analysis and the Structural Equation Model (SEM) were applied to construct a relationship between precipitation, temperature, and river discharge. Our findings indicated a significant increase in air temperature at a rate of 0.2 °C per decade, with notable warming observed in late winter (January and February) and early spring (March). The average river fluxes for the Jinzu, Oyabe, Kurobe, Shou, and Joganji rivers were 182.52 m³/s, 60.37 m³/s, 41.40 m³/s, 38.33 m³/s, and 18.72 m³/s, respectively. The tipping point for snowfall decline occurred in 1992, marked by an obvious decrease in snowfall depth. The SEM showed that, although rainfall dominated the changes in river discharge (loading = 0.94), the transition from solid (snow) to liquid (rain) precipitation may alter the river discharge regime. The percentage of flood occurrence increased from 19% (1940–1992) to 41% (1993–2020). These changes highlight the urgent need to raise awareness about the impacts of climate change on river floods and freshwater resources in global coastal regions. Full article

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