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Introduction and Problem Statement: Landslides represent a significant geological hazard worldwide. One of the primary triggers for these landslides is rainfall, which is becoming more intense as a result of climate change. The available literature has produced extensive research. However, this largely overlooks the use of mixed methodologies. Furthermore, a comprehensive review combining empirical, physically based, deterministic, and phenomenological models is still rare. Objective and Method: This study (Part I of a two-part review) addresses this gap by employing a mixed review that integrates quantitative scientometric analysis with a qualitative systematic review. The primary objective of Part I is to deliver a critical assessment, focusing on empirical and physically based causative threshold models. Main Results and Validation: Macroscopically, our analysis reveals that antecedent rainfall is a more robust indicator than classical intensity–duration (I-D) thresholds, though the latter remains widely used due to its simplicity. Physically based models provide a critical bridge when geotechnical data is scarce, correlating rainfall with internal slope responses like displacement. At a microscopic level, hybrid artificial intelligence (AI) models consistently demonstrate superior predictive accuracy by capturing complex, nonlinear relationships missed by simpler models. These findings are validated through a systematic evaluation of performance metrics across the reviewed literature. Main Conclusions and Significance: We conclude that while empirical thresholds offer operational simplicity, the future of accurate prediction lies in sophisticated hybrid AI models trained on extensive monitoring data. This review synthesizes fragmented knowledge into a unified framework, providing a clear roadmap for model selection. Full article

(This article belongs to the Special Issue Rainfall-Induced Landslides: Influencing, Modelling and Hazard Assessment: 2nd Edition)

32 pages, 5347 KB

Open AccessArticle

Simultaneous Reversible Data Hiding and Quality Enhancement for VQ-Compressed Images via Quality Improvement Codes

by Chun-Hsiu Yeh, Chung-Wei Kuo, Xian-Zhong Lin, Wei-Cheng Shen and Chin-Wei Liao

Electronics 2025, 14(22), 4463; https://doi.org/10.3390/electronics14224463 (registering DOI) - 16 Nov 2025

Abstract

With the rapid proliferation of digital multimedia in resource-constrained Internet of Things (IoT) environments, there is growing demand for efficient image compression combined with secure data embedding. Existing Vector Quantization (VQ)-based Reversible Data Hiding (RDH) methods prioritize embedding capacity while neglecting reconstruction fidelity, often introducing noticeable quality degradation in edge regions—unacceptable for high-fidelity applications such as medical imaging and forensic analysis. This paper proposes a lightweight RDH framework with a once-offline trained VQ codebook that simultaneously performs secure data embedding and visual quality enhancement for VQ-compressed images. Quality Improvement Codes (QIC) are generated from pixel-wise residuals between original and VQ-decompressed images and embedded into the VQ index table using a novel Recoding Index Value (RIV) mechanism without additional transmission overhead. Sobel edge detection identifies perceptually sensitive blocks for targeted enhancement. Comprehensive experiments on ten standard test images across multiple resolutions (256 × 256, 512 × 512) and codebook sizes (64–1024) demonstrate Peak Signal-to-Noise Ratio (PSNR) gains of +4 to +5.39 dB and Structural Similarity Index Measure (SSIM) improvements of +4.12% to +9.86%, with embedding capacities approaching 100 Kbits. The proposed approach consistently outperforms existing methods in both image quality and payload capacity while eliminating computational overhead of deep learning models, making it highly suitable for resource-constrained edge devices and real-time multimedia security applications. Full article

25 pages, 4889 KB

Open AccessArticle

Multi-Property Infrared Sensor Array for Intelligent Human Tracking in Privacy-Preserving Ambient Assisted Living

by Qingwei Song, Masahiko Kuwano, Takenori Obo and Naoyuki Kubota

Appl. Sci. 2025, 15(22), 12144; https://doi.org/10.3390/app152212144 (registering DOI) - 16 Nov 2025

Abstract

This paper deals with a privacy-preserving human tracking system that uses multi-property infrared sensor arrays. In the growing field of intelligent elderly care, there is a critical need for monitoring systems that ensure safety without compromising personal privacy. While traditional camera-based systems offer detailed activity recognition, privacy-related concerns often limit their practical application and user acceptance. Consequently, approaches that protect privacy at the sensor level have gained increasing attention. The privacy-preserving human tracking system proposed in this paper protects privacy at the sensor level by fusing data from an ultra-low-resolution

8 \times 8

(64-pixel) passive thermal infrared (IR) sensor array and a similarly low-resolution

8 \times 8

active Time-of-Flight (ToF) sensor. The thermal sensor identifies human presence based on heat signature, while the ToF sensor provides a depth map of the environment. By integrating these complementary modalities through a convolutional neural network (CNN) enhanced with a cross-attention mechanism, our system achieves real-time three-dimensional human tracking. Compared to previous methods using ultra-low-resolution IR sensors, which mostly only obtained two-dimensional coordinates, the acquisition of the Z coordinate enables the system to analyze changes in a person’s vertical position. This allows for the detection and differentiation of critical events such as falls, sitting, and lying down, which are ambiguous to 2D systems. With a demonstrated mean absolute error (MAE) of 0.172 m in indoor tracking, our system provides the data required for privacy-preserving Ambient Assisted Living (AAL) applications. Full article

(This article belongs to the Section Applied Physics General)

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22 pages, 4592 KB

Open AccessArticle

From Fracture Connectivity to Intelligent Prediction: A Hybrid GA-DBN-SE Framework for Cement Intake Forecasting

by Zongxian Liu, Xiang Lu, Mengjie Yuan, Chaofeng Zhang and Jiankang Chen

Buildings 2025, 15(22), 4122; https://doi.org/10.3390/buildings15224122 (registering DOI) - 16 Nov 2025

Abstract

Curtain grouting is widely used to reduce the permeability of dam foundations, yet forecasting cement intake remains challenging because flow pathways are governed by the three-dimensional connectivity of rock fractures. We develop a hybrid framework that explicitly embeds 3D fracture connectivity into data-driven prediction. A discrete fracture network (DFN) is constructed and traversed using depth-first search (DFS) from each grouting hole segment to capture both direct and multistep connections. Six connectivity descriptors are computed—the number of reachable fractures (N), average inclination (I), average dip angle (D), cumulative connected volume (V), average radius (r), and average width (w)—and combined with construction parameters as model inputs. Cement intake is predicted using an integrated model that combines a Restricted Boltzmann Machine (RBM)-pretrained multilayer perceptron with channel-wise squeeze-and-excitation (SE) attention, where key hyperparameters are optimized via a genetic algorithm (GA). Applied to a curtain-grouting project (448 segments), the connectivity-aware model improves agreement with observations over a no-connectivity baseline: the correlation coefficient (R) increases from 0.938 to 0.972, while mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) decrease by 27.1%, 12.2%, and 32.8%, respectively. Ablation studies validate the contributions of each component, confirming that RBM pretraining enhances generalization, SE attention improves feature selection, and ensemble aggregation stabilizes predictions. Compared to four optimized baseline models (SVR, RF, ELM, and LSTM), the proposed integrated method achieves improvements of 3–34% in R and reductions of 22–55% in MAE, 31–66% in RMSE, and 2–48% in MAPE on the held-out test set. This model provides engineers with a simple, cost-effective tool for accurate predictions to support better decision-making in grouting. Full article

(This article belongs to the Section Building Structures)

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11 pages, 1210 KB

Open AccessArticle

A Class-F High-Power Rectifier Circuit Based on Admittance Matching

by Xiao-Ning Li, Long-Feng Tian, Lin-Feng Du, Tong Wu, Guang-Chuan Zhai and Yong-Qiang Chen

Electronics 2025, 14(22), 4461; https://doi.org/10.3390/electronics14224461 (registering DOI) - 16 Nov 2025

Abstract

This paper proposes a novel high-efficiency microwave rectifier circuit with a three-stage harmonic control network based on admittance matching technology. The microwave rectifier circuit is mainly composed of a three-stage Class-F harmonic control network, an admittance matching structure, and a DC filtering structure. The three-stage Class-F harmonic control network, featuring a simple structure, not only achieves the control of the second and third harmonics but also performs impedance control on the fourth harmonic to further improve efficiency, while also realizing the impedance matching function. The DC filtering structure eliminates traditional LC components to reduce losses; meanwhile, it uses fan-shaped microstrip lines to achieve filtering and completes admittance matching with the three-stage harmonic control network. This paper presents the simulation, fabrication and measurement of a high-power rectifier circuit. The results of the measurement show that at 2.55 GHz, with an input power of 32.5 dBm, the rectifier circuit achieves a maximum rectification efficiency of 76.9%, exhibiting excellent high-power performance. Additionally, it addresses the difficulty of impedance-matching technology being relatively complex for parallel circuits. The use of admittance for matching provides valuable reference significance for reducing the complexity of parallel circuit matching and enhancing the intuitiveness of matching in related research. Full article

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14 pages, 6209 KB

Open AccessArticle

Biomechanical and Bio-Inspired Perspectives on Root Amputation in Maxillary Molars: An FEA Study

by Öznur Küçük Keleş and Öznur Eraslan

Biomimetics 2025, 10(11), 778; https://doi.org/10.3390/biomimetics10110778 (registering DOI) - 15 Nov 2025

Abstract

This study aimed to evaluate the biomechanics of maxillary first molar teeth following palatal, disto-buccal, and mesio-buccal root amputation. An intact maxillary molar underwent root canal treatment using Reciproc R25 files (VDW, Munich, Germany). The canals were obturated with gutta-percha (DiaDent, Seoul, Republic of Korea) and 2Seal sealer (VDW, Munich, Germany), and the access cavity was restored with composite resin. A high-resolution CBCT scan of an intact maxillary first molar was obtained using a Planmeca Promax 3D Max system (Planmeca Oy, Helsinki, Finland) at 75 kVp and 10 mA. The acquired data were processed in 3D Slicer software (v5.8.0, BSD license, Boston, MA, USA) to segment enamel, dentin, and pulp based on pixel density variations using the three-point cloud method. A baseline intact model and three root-resected models (palatal, disto-buccal, mesio-buccal) were reconstructed in SolidWorks 2021, with resected roots simulated as being sealed with MTA. Finite element analysis was conducted in CosmosWorks to evaluate von Mises stress distribution under a 300 N static occlusal load. Maximum von Mises stresses were detected at occlusal force application sites. Among root dentin tissues, stress values ranked highest after palatal root resection, followed by the mesio-buccal, disto-buccal, and non-resected models. Conclusions: Palatal root amputation of maxillary first molars generated the highest von Mises stresses in root dentin, suggesting a higher biomechanical risk than disto-buccal or mesio-buccal resections. Full article

(This article belongs to the Section Development of Biomimetic Methodology)

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21 pages, 14137 KB

Open AccessArticle

Stability Analysis of Loess Slope Under Heavy Rainfall Considering Joint Effect—Case Study of Jianxi Landslide, China

by Jiahao Wang, Lei Zhang, Shi Zhao, Guoji Li and Haipeng Guo

Water 2025, 17(22), 3271; https://doi.org/10.3390/w17223271 (registering DOI) - 15 Nov 2025

Abstract

Loess exhibits a pronounced reduction in strength under rainfall infiltration, making loess slopes highly susceptible to instability and failure during rainfall events. Although numerous studies have investigated the failure mechanisms of loess slopes under rainfall, most have overlooked the role of joints, which are intrinsic structural features of loess. To address this gap, this study selected the Jianxi landslide, located in Lingbao city of Henan province, as a representative case and employed a numerical simulation method to examine the influence of joints on the moisture fields and stability conditions of the Jianxi landslide. The results elucidate that the safety factor of the Jianxi landslide considering joints is 15.7% lower than the one measured without considering joints and identify the critical rainfall threshold leading to landslide instability to be 100 mm/d. Furthermore, when joints are considered, the sliding zone becomes deeper, indicating a larger landslide volume and more severe potential damage. This work provides new insights into the failure mechanism of loess landslides and offers a scientific basis for early warning. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

13 pages, 3846 KB

Open AccessArticle

Novel 2D Porous Metal–Organic Frameworks: Synthesis, X-Ray Structure, Thermal, and Hirshfeld Surface Analyses

by Rupam Sen, Mahananda Roy, Sriparna Sanyal, Arpan Dolui, Paula Brandão and Zhi Lin

Crystals 2025, 15(11), 989; https://doi.org/10.3390/cryst15110989 (registering DOI) - 15 Nov 2025

Abstract

In the present study, we have developed a series of compounds [M(tcm)₂(bix)₄]_n [where M = Co (1), Ni (2), and Cu (3)] using tricyanomethanide (tcm) and 1,4-bis(imidazol-1-ylmethyl)benzene (bix) ligands. The compounds were characterized by elemental analysis, PXRD, FT-IR and single-crystal X-ray crystallography. Single-crystal X-ray investigation of compounds 1, 2, and 3 shows the formation of the porous 2D structure. These 2D structures are further stacked to create a 3D network in the crystallographic space. All the compounds are thermally stable up to 300 °C, as revealed by the TGA. Hirshfeld surface analysis was carried out, and it reveals the existence of short intermolecular interactions between the layers. Full article

(This article belongs to the Special Issue Synthesis, Crystal Structures and Hirshfeld Surface Analysis of Coordination Compounds (3rd Edition))

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23 pages, 7853 KB

Open AccessArticle

A Stereolithography Appearance-Based Ultra-Wideband Wide-Beam Dielectric Resonator Antenna

by Chenyang Song, Yubing Yuan, Shengbo Ye, Zihao Wang, Qunying Zhang, Xiaojun Liu and Guangyou Fang

Sensors 2025, 25(22), 6989; https://doi.org/10.3390/s25226989 (registering DOI) - 15 Nov 2025

Abstract

This paper presents a comprehensive study on the design, fabrication, and characterization of ultra-wideband (UWB) wide-beam dielectric resonator antennas (DRAs) using stereolithography (SLA)-based 3D printing technology. High-purity alumina ceramics were successfully fabricated through an optimized SLA process involving 80 wt.% solid loading and sintering. The proposed DRA design incorporates a vertical ground plane to achieve a compact footprint of 0.598λ₀ × 0.491λ₀ × 0.069λ₀ (where λ₀ is the wavelength corresponding to the center operating frequency of 4.15 GHz) while demonstrating an exceptional 70.59% relative bandwidth (2.75–5.75 GHz). A novel slot-loading technique was developed to correct radiation pattern distortions caused by higher-order modes, validated through both simulation and measurement. The antenna exhibits stable unidirectional radiation patterns with a wide half-power beamwidth in both the E-plane and H-plane and a gain of 2.5–5.5 dB across the operating band. This work establishes SLA as a viable manufacturing approach for high-performance RF components. Full article

(This article belongs to the Section Communications)

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26 pages, 6764 KB

Open AccessArticle

Integrative Transcriptome Analysis Across Follicles Highlights Key Regulatory Pathways in Low and High-Egg-Laying Hens

by Armughan Ahmed Wadood, Farhad Bordbar and Xiquan Zhang

Animals 2025, 15(22), 3300; https://doi.org/10.3390/ani15223300 (registering DOI) - 15 Nov 2025

Abstract

Egg-laying performance in hens is regulated by complex molecular mechanisms within the hypothalamic–pituitary–gonadal (HPG) axis and ovarian follicles. This study employed integrative transcriptome profiling of primordial (PR), primary (PM), small white (SW), and small yellow (SY) follicles in hens with low and high egg-laying capacities to explain regulatory pathways influencing reproductive outcomes. Specific gene expression patterns were observed that correlated with follicular growth, steroidogenesis, and granulosa cell proliferation. Heatmap clustering and principal component analysis revealed transcriptional divergence between low- and high-laying hens, suggesting that coordinated changes in signaling pathways influence egg-laying performance. High-laying hens intricated an upregulation of the PI3K-AKT-FOXO3, TGF-β, and Wnt/β-catenin pathways, which facilitate early follicular development, granulosa cell proliferation, and folliculogenesis. Higher phosphorylation of AKT and reduced nuclear FOXO3 activity were associated with enhanced primordial follicle growth. Increased TGF-β signaling, as demonstrated by higher levels of SMAD2/3/4 and cell cycle regulators, promoted granulosa cell proliferation in primary follicles (PMF). In SWF, higher levels of β-catenin and its downstream genes, such as c-Myc and cyclin D1, promoted follicle development. High-laying hens revealed increased expression of FSHR, CYP19A1, 17β-HSD, CYP1A1, and CYP1B1 in SYF, signifying enhanced FSH level and steroidogenesis. Similarly, low-laying hens exhibited downregulation of key genes, suggesting reduced follicular development and hormone signaling. These findings identify key regulatory networks and molecular markers associated with reproductive performance, providing targets for genetic selection and interventions to enhance egg production while reducing the risk of hormonal overstimulation. Full article

(This article belongs to the Special Issue Advances in Genetic Analysis of Important Traits in Poultry)

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16 pages, 2615 KB

Open AccessArticle

A Novel High-Performance 2-to-4 Decoder Design Utilizing a Plasmonic Well and Suspended Graphene Nanoribbon

by Mohammad Javad Maleki and Mohammad Soroosh

Crystals 2025, 15(11), 988; https://doi.org/10.3390/cryst15110988 (registering DOI) - 15 Nov 2025

Abstract

This paper presents a compact and high-performance 2-to-4 optical decoder based on a plasmonic well structure incorporating suspended graphene nanoribbons. By exploiting the tunable graphene’s chemical potential, the propagation and confinement of surface plasmon polaritons are dynamically controlled, enabling efficient routing of optical signals toward the output ports. Finite-difference time-domain simulations are employed to analyze the influence of channel geometry and graphene chemical potential on surface plasmon polariton propagation, refractive index, and transmission loss. The designed structure, featuring a 30 nm wide and 10 nm high plasmonic well, achieves a low propagation loss of 0.188 dB/µm and a high figure of merit of 1950 at 40 THz. The designed decoder exhibits a contrast ratio of 36.93 dB and crosstalk suppression of −36.93 dB, while occupying a remarkably small area (0.05 µm²), demonstrating superior optical performance and compactness compared to previously reported designs. These results confirm the potential of the proposed plasmonic well-based decoder as a fundamental component for next-generation nanoscale optical and plasmonic computing systems. Full article

(This article belongs to the Special Issue Recent Advances in Graphene and Other Two-Dimensional Materials)

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39 pages, 2839 KB

Open AccessArticle

A Neuro-Symbolic Multi-Agent Architecture for Digital Transformation of Psychological Support Systems via Artificial Neurotransmitters and Archetypal Reasoning

by Gerardo Iovane, Iana Fominska and Raffaella Di Pasquale

Algorithms 2025, 18(11), 721; https://doi.org/10.3390/a18110721 (registering DOI) - 15 Nov 2025

Abstract

The digital transformation in the treatment of mental health and emotional disharmony requires artificial intelligence architectures that overcome the limitations of purely neural approaches, such as temporal inconsistency, opacity, and lack of theoretical foundations. Assuming the existence and use of generalist LLMs currently used in clinical settings and considering the appropriate limitations indicated by experts, this article aims to offer clinicians an alternative Neuro-symbolic-Psychological multi-agent architecture (NSPA-AI), which integrates archetypal symbolic reasoning with neurobiological modelling, based on our established framework of artificial neurotransmitters for the modelling and analysis of affective-emotional stimuli to enable interpretable AI-assisted psychological intervention. The system implements a hub-and-spoke topology that coordinates five specialized agents (symbolic, psychological, neurofunctional, decision fusion, learning) that process heterogeneous information via SPADE protocols. Seven archetypal constructs from Jungian psychology and narrative identity theory provide stable symbolic frameworks for longitudinal therapeutic consistency. An empirical study of 156 university students demonstrated significant improvements in depression (Cohen’s d = 1.03), stress (d = 0.89), and narrative identity integration (d = 0.75), which were maintained at a 12-week follow-up and superior to GPT-4 controls (d = 0.34). Neurofunctional correlations—downregulation of cortisol (r = 0.71 with stress reduction), increase in serotonin (r = −0.68 with depression improvement)—validated the neurobiological basis of the entropy-energy framework. Qualitative analysis revealed the following four mechanisms of improvement: symbolic emotional support (93%), increased self-awareness through neurotransmitter visualization (84%), non-judgmental AI interaction (98%), and archetypal narrative organization (87%). The results establish that neuro-symbolic architectures are viable alternatives to large language models for digital mental health, providing the interpretability and clinical validity essential for adoption in the healthcare sector. Full article

(This article belongs to the Special Issue Algorithms in Multi-Sensor Imaging and Fusion)

15 pages, 1027 KB

Open AccessArticle

CRISPR-Cas9-Mediated Knockout of MLO3 Confers Enhanced Resistance to Reniform Nematode in Upland Cotton

by Foster Kangben, Sonika Kumar, Anqi Xing, Li Wen, Wei Li, Stephen Parris, John Lawson, Zhigang Li, Lauren Carneal, Meredith Cobb, Robert L. Nichols, Christina Wells, Paula Agudelo, Churamani Khanal and Christopher A. Saski

Plants 2025, 14(22), 3491; https://doi.org/10.3390/plants14223491 (registering DOI) - 15 Nov 2025

Abstract

Upland cotton (Gossypium hirsutum L.) is a major global commodity crop whose production is threatened by the reniform nematode (Rotylenchulus reniformis Linford and Oliveira), a plant-parasitic pest that causes substantial yield losses. Host-plant resistance offers a sustainable management strategy, but currently available resistant cotton cultivars provide only partial protection and often require supplemental control methods. In this study, Clustered Regularly Interspaced Palindromic Repeats (CRISPR)–CRISPR-associated 9 (Cas9) gene editing was used to generate targeted knockouts of Mildew Resistance Locus O (GhiMLO3) in cotton and assess its role in resistance to R. reniformis. Four independent knockout lines (A1, D3, E1, and P3) were developed, confirmed by sequencing, and evaluated for nematode resistance under controlled greenhouse conditions. Nematode reproduction was significantly reduced on lines D3 and E1, with lower egg counts and fewer vermiform life stages compared with the control genotypes, Coker 312 (WT), Delta Pearl, and Jin668. The edited lines also showed characteristic mesophyll cell-death phenotypes, suggesting potential pleiotropic effects associated with MLO-mediated resistance. Sequence analysis confirmed multiple homozygous and heterozygous mutations in MLO3 alleles from both the A and D subgenomes, with D3 and E1 lines displaying the strongest resistance profiles. These findings demonstrate that MLO3 gene editing is a promising approach for improving R. reniformis resistance in cotton. Full article

(This article belongs to the Special Issue New Strategies for the Control of Plant-Parasitic Nematodes)

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19 pages, 6776 KB

Open AccessArticle

Integrated Transcriptomic and Developmental Analyses Provide Insights into the Intrafloral Stamen Differentiation in Cassia fistula L.

by Zhonglai Luo, Tingting Duan, Xiaoyuan Li, Jianxuan Zhou, Qiankun Liu and Libo Jiang

Plants 2025, 14(22), 3490; https://doi.org/10.3390/plants14223490 (registering DOI) - 15 Nov 2025

Abstract

Selective pressure targeting male functions plays a crucial role in the evolution of floral morphological traits. In some angiosperm groups, flowers contain two or more sets of stamens that vary in size, color, and morphology, a phenomenon known as heteranthery. This reflects an evolutionary adaptation of stamens. However, the developmental basis and molecular mechanisms remain poorly understood. This study integrates transcriptomic and developmental approaches to elucidate the molecular and morphological mechanisms underlying intra-floral stamen differentiation in Cassia fistula L., an economic leguminous tree exhibiting heteranthery with three distinct stamen types: long stamens (LS), short stamens (SS), and degenerated stamens (St). We documented asynchronous stamen primordia initiation and development trajectories across stamen types. Transcriptomic profiling and protein–protein interaction analysis identified differentially expressed genes (DEGs) between filaments of the three stamen sets, with significant enrichment in brassinosteroid (BR) related pathways. CYP90D1 (Cf_f49903) and CYP90C1 (Cf_f56973) emerged as candidate genes related to stamen length differentiation in C. fistula. This study not only helped elucidate the developmental and genetic framework of heteranthery in C. fistula but also provided new insights for exploring floral organ evolution in leguminous plants. Full article

(This article belongs to the Special Issue Recent Advances in Horticultural Plant Genomics)

37 pages, 3646 KB

Open AccessReview

Fascinating Frontier, Nanoarchitectonics, as Method for Everything in Materials Science

by Katsuhiko Ariga

Materials 2025, 18(22), 5196; https://doi.org/10.3390/ma18225196 (registering DOI) - 15 Nov 2025

Abstract

Methodological fusion of materials chemistry, which enables us to create materials, with nanotechnology, which enables us to control nanostructures, could enable us to create advanced functional materials with well controlled nanostructures. Positioned as a post-nanotechnology concept, nanoarchitectonics will enable this purpose. This review paper highlights the broad scope of applications of the new concept of nanoarchitectonics, selecting and discussing recent papers that contain the term ‘nanoarchitectonics’ in their titles. Topics include controls of dopant atoms in solid electrolytes, transforming the framework of carbon materials, single-atom catalysts, nanorobots and microrobots, functional nanoparticles, nanotubular materials, 2D-organic nanosheets and MXene nanosheets, nanosheet assemblies, nitrogen-doped carbon, nanoporous and mesoporous materials, nanozymes, polymeric materials, covalent organic frameworks, vesicle structures from synthetic polymers, chirality- and topology-controlled structures, chiral helices, Langmuir monolayers, LB films, LbL assembly, nanocellulose, DNA, peptides bacterial cell components, biomimetic nanoparticles, lipid membranes of protocells, organization of living cells, and the encapsulation of living cells with exogenous substances. Not limited to these examples selected in this review article, the concept of nanoarchitectonics is applicable to diverse materials systems. Nanoarchitectonics represents a conceptual framework for creating materials at all levels and can be likened to a method for everything in materials science. Developing technology that can universally create materials with unexpected functions could represent the final frontier of materials science. Nanoarchitectonics will play a significant part in achieving this final frontier in materials science. Full article

(This article belongs to the Special Issue Nanoarchitectonics in Materials Science, Second Edition)

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