Search Results (20,442)

To address the coexistence of random measurement delays and intermittent data loss in multi-UAV cooperative navigation under weak communication scenarios, an adaptive cooperative localization method based on online diagnosis is proposed. A timestamp-driven diagnosis mechanism first identifies the physical reachability and temporal validity of cooperative measurements and classifies the channel state as normal, delayed, or lost. The estimator then adaptively switches between timestamp-diagnosed multi-step augmented filtering for delayed packets and Gray Wolf Optimizer (GWO)-optimized Gated Recurrent Unit (GRU) virtual measurement reconstruction for complete dropouts. In a four-UAV hybrid-anomaly simulation with continuous random delays and a 10 s communication blackout, the proposed method reduces the mean east and north RMSE by 69.1% and 75.2%, respectively, and lowers the mean horizontal-channel RMSE from 2.200 m to 0.608 m. Ablation experiments isolate the contribution of each module (diagnosis and multi-step delayed filtering and GWO-GRU virtual reconstruction), and 20 paired Monte Carlo runs with paired significance tests confirm the improvement. Relative to the strongest delay-aware baseline, the full-trajectory mean accuracy is comparable, and the main advantage of the proposed method is its robustness during complete communication outages and fast post-outage recovery. The simulation scenarios are driven by flight data collected with the DJI Matrice 350 RTK platform; the communication anomalies are included in the simulation, and all evaluations are performed offline. These results indicate that the proposed diagnosis-driven scheduling strategy can improve cooperative localization robustness when delay and data loss occur simultaneously. Full article

Geographical authentication of medicinal plant materials remains challenging because multispectral variables are often highly collinear and sample grouping can complicate reliable model validation. Existing correlation-based feature-selection strategies also require careful adaptation to multiclass problems to avoid artificial ordering of class labels and information leakage during model development. Therefore, this study aimed to develop a compact and leakage-controlled multispectral learning framework for geographical-origin discrimination. This study analyzed 800 physical Pinellia ternata samples from Gansu Xihe, Sichuan Neijiang, Sichuan Chengdu, and Chongqing Dianjiang (200 samples per origin). Each physical sample was represented by 31 mean grayscale intensities calculated from Otsu-segmented multispectral regions of interest. A Pearson-correlation-guided deep multilayer perceptron (PCG-DeepMLP) was constructed by estimating one-vs-rest band relevance and inter-band redundancy only within the training data. The key methodological innovation is a unified multiclass-aware, relevance–redundancy spectral-learning framework in which class-specific one-vs-rest Pearson relevance is coupled with inter-band redundancy control and embedded within leakage-controlled grouped model development. By learning the spectral subset exclusively from each training partition before nonlinear classification, the framework produces compact and complementary multispectral signatures while preserving multiclass structure and strict independence of held-out groups. Model and feature-selection settings were chosen by three-fold grouped cross-validation within each training partition. PCG-DeepMLP retained 9–21 bands and achieved the highest mean accuracy (0.9812 ± 0.0135), macro-F1 (0.9812 ± 0.0135), Matthews correlation coefficient (MCC; 0.9752 ± 0.0179), and macro-AUC (0.9994 ± 0.0006) among seven models. Its macro-F1 was higher than that of 1D-CNN, 1D-ResNet, full-band MLP, PLS-DA, and random forest after Holm correction. Performance was estimated through a strict nested group-wise internal validation scheme, with every outer test fold remaining isolated from feature selection, preprocessing, and model optimization. These findings demonstrate that multiclass-aware relevance–redundancy learning can retain complementary Pinellia ternata origin-discriminative information in a compact and stable spectral representation, enabling accurate geographical-origin authentication while providing a principled basis for reduced-channel acquisition and future independent multi-batch validation. Full article

The rapid advancement of autonomous agricultural systems (AASs) is transforming modern agriculture, where labor shortages, sustainability imperatives, and demands for precision farming are driving the adoption of intelligent agricultural platforms. Agricultural production environments present uniquely challenging conditions for autonomous agricultural systems, including unstructured and dynamically changing terrain, biologically variable targets, unpredictable illumination and weather conditions, and safe human–machine coexistence. This review systematically investigates three cornerstone technologies: multi-source perception, intelligent decision-making, and precision control. Furthermore, typical agricultural operations, including soil tillage, planting, irrigation and drainage, fertilization, plant protection, harvesting, and agricultural product processing, are reviewed to illustrate their applications. Based on representative operational scenarios, the research progress and application characteristics of intelligent equipment in environmental perception, operational optimization, and control execution are summarized. Specifically, multi-source perception is evolving from isolated sensor-based acquisition toward multimodal and deep learning-enabled semantic scene understanding. Intelligent decision-making has evolved from experience-driven approaches toward physics-informed, data-driven, and knowledge-enhanced frameworks for adaptive operational optimization. Precision control has progressed from conventional PID control toward adaptive, learning-based, and digital twin-enabled control strategies, achieving robust high-precision closed-loop regulation. However, several critical challenges persist: limited cross-domain generalization and robustness of perception models under environmental distribution shift, constrained interpretability and trustworthiness of data-driven decision systems, and insufficient adaptability of control architectures under multi-disturbance coupled field conditions. To address these gaps, future research should prioritize multi-source heterogeneous data fusion and standardization, collaborative control frameworks integrating mechanistic knowledge with data-driven learning, and explainable artificial intelligence combined with agricultural domain expertise—advancing toward genuinely autonomous, trustworthy, and resilient agricultural systems. Full article

High-precision, multi-tier categorical soil classification faces critical bottlenecks, including the neglect of spatial context by conventional pixel-based models, the error cascade propagation phenomenon in multi-level classification networks, and the disruption of geophysical directional anisotropy by traditional geometric data augmentation. To address these challenges, in this study, we propose a multi-level soil classification model based on MTSC-ResNet-Trans, which organically couples residual convolutional blocks with a 3-layer Transformer encoder to model long-range spatial dependencies. The framework integrates a geospatial-safe data augmentation pipeline to preserve the topological fidelity of absolute geographic coordinates alongside four decoupled parallel multi-task classification heads to substantially suppress inter-level error propagation. Evaluated in the Southern Foothills of Qilian Mountains using 18 environmental covariates, the framework achieves an Overall Accuracy of 0.8931 at the Great Group level under conventional random splitting. Under a distance-stratified spatial evaluation—which isolates the contribution of spatial autocorrelation to accuracy estimates—the framework maintains robust performance, with MTSC-ResNet-Trans consistently outperforming pixel-based baselines (Random Forest) by approximately 3.7 percentage points even at spatial separation distances exceeding 400 m. This protocol transparently decomposes predictive accuracy into a component attributable to spatial proximity and a component reflecting reduced spatial proximity performance. Across the four taxonomic levels, accuracy decay is suppressed to 5.11%. Although spatial-block cross-validation indicates a lower regional extrapolation accuracy (OA = 0.7389 ± 0.0671), the decoupled parallel framework provides an effective and robust baseline for high-resolution regional digital soil mapping. Full article

Background/Objectives: Precise genetic access to the zebrafish habenula remains limited by a scarcity of compact, sequence-defined cis-regulatory elements (CREs). Here, we integrated developmental expression mapping, deep-learning predictions on long-range sequences, and in vivo reporter assays to identify compact regulatory sequences driving habenular expression. Methods: Using a transgenic zebrafish line enriched for habenular reporter expression, we isolated GFP-positive cells from larval brains and profiled their transcriptomes via microarray. A subset of candidate genes enriched in this dataset was validated using whole-mount in situ hybridization across two developmental stages. This analysis identified genes with highly reproducible habenular expression, leading to the selection of the gng8 and ano2 loci for subsequent CRE characterization. We developed ZEN-former (Zebrafish EN-former), an Enformer-based sequence-to-function model trained on neuronal subclass chromatin accessibility profiles from the adult mouse brain. Results: The model demonstrated strong correlation between predicted and experimentally measured signals across held-out genomic regions. To prioritize regulatory candidates, we integrated ZEN-former predictions with available zebrafish ATAC-seq data, RepeatMasker annotations, and gene models, identifying two ~600 bp intervals at each gene locus. These selected intervals were combined to generate ~1.2 kb reporter constructs for gng8 and ano2 loci, which were then evaluated using Tol2 transposon mediated transgenesis assays in zebrafish. In transiently injected larvae, both constructs successfully drove reporter expression in the habenular region. Furthermore, the resulting stable transgenic lines displayed highly specific and reproducible habenular expression. Quantitative confocal analysis showed mean habenular labeling completeness values of 84.5% and 96.2% for the gng8- and ano2-derived lines, respectively. Conclusions: Together, these findings provide a proof of concept that sequence features learned from mammalian chromatin accessibility datasets can effectively guide the prioritization of functional regulatory elements across species in zebrafish. The compact regulatory constructs and stable transgenic lines generated here offer robust genetic tools for investigating habenular circuitry. Full article

To meet the demands for high-density integration and broadband RF performance in next-generation electronic equipment, this paper investigates the structural design and process sensitivity of vertical interconnects in three-dimensional stacked system-in-package (3D-SiP). Based on quasi-coaxial matching and low-impedance compensation techniques, three typical vertical interconnect structures are designed: the PCB-BGA-SiP microstrip structure achieves S₁₁ better than −15 dB and S₂₁ < 0.3 dB within 2–20 GHz; the lower stripline–BGA–upper microstrip structure achieves S₁₁ better than −27 dB; the lower microstrip–BGA–upper microstrip structure achieves S₁₁ better than −18 dB within 1–23 GHz. Isolation simulation shows that the isolation between adjacent channels exceeds 55 dB within 25 GHz. For process sensitivity evaluation, physical samples of gold wire bonding parameters (length, diameter, number) were fabricated and tested for S₁₁, confirming that the dual-wire topology extends the effective bandwidth to 2–20 GHz (a 54% improvement over single wire), the third-wire marginal gain is only ~5%, and 25 μm diameter offers the best overall performance. For BGA ball radius and pad pitch, parametric sensitivity analysis via Ansys HFSS was performed (not experimentally validated process variation results), identifying the optimal BGA radius as 0.245 mm with an allowable variation of ±0.015 mm, and the pad center-to-center distance should be controlled near 0.8 mm. Based on these findings, process control strategies are proposed: low-loop wire bonding (loop height < 50–80 μm) with statistical process control; substrate warpage controlled through symmetric copper filling, a thick-middle dielectric stack-up, and distributed symmetric cavity layout, combined with eutectic pressure of 1.5 kPa, validated on 10 fabricated substrates with peak warpage consistently < 80 μm, void rate 4.75%, and solder overflow 94%; and BGA soldering using high-precision vision alignment and controlled collapse (20–35%). This work provides a theoretical basis and practical process pathway for transitioning 3D-SiP vertical interconnects from ideal design to mass production. Full article

The cyanobacterial genus Aliterella (Chroococcidiopsidales) comprises coccoid taxa with a broad geographic and ecological distribution, occurring in habitats ranging from polar environments to arid deserts and tropical regions. In this study, we describe two novel species isolated from phototrophic biofilms colonizing the columns of the portico of Villa Poppea at the archaeological site of Oplontis (Naples, Italy), representing the first record of the genus from the Mediterranean Basin. The strains were investigated using a polyphasic approach combining morphological observations, transmission electron microscopy (TEM), 16S rRNA gene and 16S–23S ITS sequencing, phylogenetic analyses, and comparative ITS secondary structure reconstruction. The results support the establishment of Aliterella oplontina sp. nov. and Aliterella pliniana sp. nov. Aliterella oplontina is characterized by irregular colonies emb edded in a thick mucilaginous sheath, small oval cells, and a phylogenetic position closely related to A. antarctica. Aliterella pliniana forms compact colonies composed of cylindrical cells and occupies a distinct evolutionary lineage closely associated with A. diffluens and A. bergstromii. Genetic distance analyses based on the 16S rRNA gene confirm the placement of both taxa within Aliterella while supporting their recognition as separate species. Comparative analyses of the D1D1′ and Box-B secondary structures of the ITS region provided additional diagnostic characters and revealed shared structural patterns among species groups within the genus. Aliterella oplontina possesses a unique combination of ITS features, whereas A. pliniana shares several structural affinities with A. diffluens and A. bergstromii. These findings significantly expand current knowledge of the diversity, phylogenetic relationships, and biogeographical distribution of Aliterella, while further demonstrating the value of an integrative polyphasic approach for cyanobacterial taxonomy. Full article

Web applications increasingly handle sensitive data in diverse use cases, but conventional encryption implementations apply a uniform level of cryptographic protection to all traffic, regardless of the associated risk. This static approach results in either excessive computational overhead when applying maximum encryption universally, or inadequate protection when using lightweight encryption to preserve performance. This paper proposes an Adaptive Encryption Framework (AEF) designed to bridge the gap between performance and security in web applications. Rather than relying on a static protocol, AEF dynamically adjusts encryption algorithms based on a real-time composite risk score (0–100). This score is derived from six weighted variables: network risk (25%), authentication strength (20%), behavioral risk (20%), device trust (15%), data sensitivity (15%), and temporal risk (5%). Depending on the calculated risk, the system automatically transitions between three distinct security tiers: GREEN (utilizing ChaCha20-Poly1305), YELLOW (AES-256-GCM), or RED (AES-256-GCM with per-request HKDF key derivation for key isolation). All three profiles use exclusively standardized cryptographic primitives. The proposed weighting distribution was evaluated through sensitivity analysis on 27 framework-executed scenarios and further calibrated using 40,000 labeled application requests. Within these experimental conditions, it achieved complete agreement with the expected scenario classifications, and no alternative weight configuration produced better held-out performance. Additional validation on 61,065 HTTP requests from the CSIC 2010 dataset yielded an area under the ROC curve (ROC AUC) of 0.860, with no attack request assigned to the lightweight profile under the evaluated operating conditions. Across three hardware platforms and four payload sizes, all encryption profiles maintained sub-millisecond latency. Extended load testing showed that a four-worker Node.js cluster sustained 4948 requests per second at 2000 concurrent connections, a 7.1-fold improvement over a single process. When hardware cryptographic acceleration was disabled, ChaCha20-Poly1305 became up to 9.1 times faster than AES-256-GCM, supporting its use as the lightweight profile. The framework proposed in this paper operationalizes the qualitative risk assessment guidelines from NIST SP 800-30 and SP 800-63 into a quantitative, automated encryption selection mechanism for web applications, evaluated under the hardware platforms, concurrency levels and traffic assumptions described in this study. Full article

Background: The vaginal microbiota of healthy women is predominantly composed of lactic acid bacteria (LAB), particularly species from the lactobacilli group, which contribute to the maintenance of vaginal health through multiple protective mechanisms. Objectives: In the present study, vaginal LAB isolated from healthy premenopausal Algerian women were evaluated for their probiotic potential. Methods: A total of 259 LAB isolates were initially screened for antimicrobial activity against vaginal pathogens, among which 164 strains exhibited inhibitory effects. Based on antimicrobial capacity and biofilm formation ability, 38 strains were selected for further characterization. A refined subset of 15 strains belonging to Lactiplantibacillus (Lpb.) plantarum, Limosilactobacillus (Lmb.) fermentum, and Ligilactobacillus (Lgb.) salivarius were subsequently identified according to their superior antimicrobial and probiotic-related properties. The selected strains were evaluated for several functional and safety characteristics, including antimicrobial activity, production of lactic acid and hydrogen peroxide (H₂O₂), biofilm formation, auto-aggregation, cell surface hydrophobicity, antibiotic susceptibility, hemolytic activity, and tolerance to acidic conditions. These studies were complemented with comparative genomics using the complete genome sequences of selected strains. Results: The isolates demonstrated significant inhibitory activity against vaginal pathogens associated with aerobic vaginitis, and vulvovaginal candidiasis. In addition, strong correlations were observed between metabolite production and antimicrobial activity. Several strains also exhibited enhanced biofilm formation, aggregation capacity, and favorable safety profiles. Among the tested isolates, Lmb. fermentum 70BJ2, Lpb. plantarum 87JG8, and Lpb.plantarum N17 emerged as particularly promising probiotic candidates due to their combined antimicrobial, metabolic, and adhesion-related properties. Conclusions: Overall, these findings demonstrate that the vaginal microbiota of healthy Algerian women represents a valuable source of potential probiotic strains and provide a strong basis for future in vivo validation and clinical application in the prevention and management of vaginal infections. Full article

Online commercial sex platforms have become key environments in which potential indicators relevant to technology-facilitated sexual exploitation (TFSE) and technology-facilitated gender-based violence (TFGBV) may be observed. Current language models and computational approaches to identifying potential exploitation often assume that behavioural indicators (e.g., geographical mobility, pricing, and other linguistic markers) are easily accessible and comparable across online spaces and jurisdictions. This study challenges this assumption by showing that platform design largely shapes the variables and indicators that can be observed in these spaces. Drawing on a large-scale dataset of 1.9 million profiles (after cleaning) from two major online commercial-sex platforms, AdultWork (United Kingdom) and CallEscort (United States), the research examines how potential exploitation-related indicators may be identified and interpreted across platform architectures. Through cross-platform mapping, significant misalignments in data visibility and comparability were highlighted for demographic characteristics, mobility data, and services offered. To address comparability challenges, the study introduces a platform-mediated visibility framework to explain how platform design shapes the visibility, interpretation, and comparability of potential indicators relevant to TFSE and TFGBV. The framework provides a methodological basis for interpreting exploitation-related indicators across different platform architectures and underscores the value of platform-aware approaches to safeguarding and prevention. In collaboration with US and UK law enforcement and Non-Governmental Oranization (NGO) partners, the study advocates for proactive and tailored prevention strategies that account for platform architecture while recognising that coordinated activity and potential indicators do not, in isolation, establish exploitation, trafficking or criminal behaviour. Full article

Background: Epithelial ingrowth is an uncommon but potentially vision-threatening complication after keratorefractive lenticule extraction (KLEx). Although this complication is well described after flap-based refractive surgery, its occurrence after flapless lenticule extraction remains rare and is mainly reported in isolated cases. This narrative review summarizes the available literature on epithelial ingrowth after KLEx, with particular attention to proposed mechanisms, clinical presentation, imaging findings, and surgical management. An illustrative case of severe epithelial ingrowth managed with crocodile-forceps extraction is also presented. Methods: A literature search was performed to identify published reports describing epithelial ingrowth after SMILE/KLEx. Relevant articles were reviewed and compared with regard to onset, suspected mechanism, clinical severity, treatment strategy, anatomical outcome, visual recovery, and recurrence. Results: The affected eye developed extensive epithelial ingrowth associated with a postoperative tunnel laceration and marked visual deterioration during the first postoperative week. Surgical clearance through the original incision was performed using crocodile forceps followed by copious interface irrigation. Approximately one hour after treatment, AS-OCT demonstrated complete clearance of the hyperreflective interface material, corneal topography showed marked regularization, and wavefront aberrometry demonstrated a reduction in overall OPD RMS from 1.21 to 0.58 µm and higher-order RMS from 1.03 to 0.37 µm at a 4 mm pupil. Visual acuity subsequently improved over the following postoperative days, with no recurrence during 6-month follow-up. Conclusions: Severe epithelial ingrowth after KLEx may require prompt surgical intervention when rapid progression and visual deterioration occur. In this case, crocodile-forceps-assisted interface clearance through the original incision was feasible and was associated with rapid anatomical and optical recovery without cap-to-flap conversion or chemical adjuvants. Further cases are required to determine the reproducibility, safety, and long-term outcomes of this approach. Full article

Road safety is a fundamental component of sustainable urban mobility, requiring transportation systems that support safe, efficient, and evidence-based territorial planning. Although traffic safety is commonly evaluated using individual indicators, their isolated application often limits comprehensive territorial assessments and intervention prioritization. This study proposes a spatial decision-support framework for sustainable transportation planning based on composite risk indices, multicriteria weighting, and geographic analysis. Official traffic crash records from Ecuador for 2025 were analyzed at the cantonal level to develop three complementary indices representing crash severity, spatial risk, and hotspot concentration. The methodology integrated demographic exposure, territorial exposure, crash frequency, fatalities, injuries, victims, fatal crashes, nighttime crashes, and severity indicators. Variables were normalized using the Min–Max method and aggregated through theoretical and entropy-based weighting schemes. The robustness of the proposed framework was assessed through sensitivity analysis, Monte Carlo simulation with 1000 iterations, and Spearman rank correlation analysis. Results showed very high-ranking agreement between theoretical and entropy-based rankings (ρ = 0.993 for severity, ρ = 0.993 for spatial risk, and ρ = 0.965 for hotspot concentration), indicating the stability of territorial prioritization across alternative weighting schemes. The proposed framework provides a transferable tool for sustainable mobility planning and road safety management. Full article

Low carbon-to-nitrogen (C/N) municipal wastewater often limits heterotrophic denitrification and increases external carbon addition. This study evaluated an exogenous denitrifying bioaugmentation (DEN) strategy for improving nitrogen removal per unit of external carbon added. The screened inoculant reached approximately 2.5 × 10⁹ CFU/mL, and maximum nitrate and nitrite reduction rates of 307.42 and 215.42 g N/(m³ h), respectively, were achieved by the selected isolates. Among the tested carbon sources, the highest denitrification rate was obtained with sodium acetate. Across wastewater samples from six municipal wastewater treatment plants (WWTPs), the apparent C/N requirement was reduced from 2.79–9.41 to 1.92–5.20 by DEN addition, corresponding to a 21–55% decrease in chemical oxygen demand (COD) required per unit total nitrogen (TN) removed. During full-scale validation at a 24,000 m³/d WWTP, effluent TN was maintained at approximately 10 mg/L through startup and adaptive maintenance dosing, while specific denitrification rate (SDNR) was increased by approximately 2.3-fold. Activated-sludge community restructuring was indicated by 16S rRNA sequencing, with an increase in the relative abundance of Pseudomonadota from 18.4% to 27.6% after dosing. Based on external carbon-source expenditure, the specific external carbon-source cost per unit TN removed decreased from 0.036 to 0.011 Chinese Yuan (CNY)/(t water·mg TN), corresponding to a 69.4% reduction in this cost indicator. Overall, DEN bioaugmentation was shown to be a practical engineering tool for carbon-efficient nitrogen removal from low-C/N municipal wastewater. Full article

The widespread presence of microplastics (MPs) and associated plastic-derived compounds, bisphenols (BPs), in the environment—originating from plastic production or adsorption of environmental pollutants—results in unavoidable human exposure. Therefore, assessing their occurrence in human biological samples is essential for understanding potential health risks. In this study, pyrolysis gas chromatography–mass spectrometry was used to analyse human intraocular fluids—aqueous humour (AH) and vitreous humour (VH)—to identify 11 microplastic polymer clusters. A method based on dansyl chloride derivatisation combined with ultra-performance liquid chromatography–tandem mass spectrometry was employed to screen for five bisphenols (BPs) in blood serum collected from the same patients. Potential MPs isolated from ocular samples were qualitatively assessed by stereomicroscopy. The number of particles ranged from 14 to 69 per gram in AH and from 21 to 34 per gram in VH. Among AH samples, the most frequently detected polymer clusters were C-PVC, C-PMMA, C-PET, and C-PP, with average levels ranging from 0.41 to 0.84 µg/g. The three VH samples contained only C-PMMA, with an average concentration of 0.55 ± 0.12 µg/g. Polymers such as C-PA66 (0.30 ± 0.21 µg/g) and C-PA6 (0.15 ± 0.44 µg/g) were occasionally observed in AH. Analysis of 13 human serum samples demonstrated exposure to bisphenol A (BPA; 4.05–5.18 ng/mL) and bisphenol AF (BPAF; 2.13–4.54 ng/mL), but no clear correlation was observed between serum BP levels and intraocular MPs within the limitations of the present dataset. These findings suggest the presence of MPs and BPs in human biological samples; however, the results should be interpreted with caution owing to potential background contamination and the pilot nature of the study. Full article

Water retention on the lunar surface is governed by water–mineral interactions, yet the atomic-scale transition from isolated adsorption to high-coverage water accumulation remains insufficiently understood. We perform spin-polarized first-principles calculations to investigate single- and multi-water adsorption on representative surfaces of four major lunar regolith minerals: CaAl₂Si₂O₈, MgFeSi₂O₆, FeTiO₃, and Mg₃FeSi₂O₈. Single-water adsorption reveals that H₂O preferentially anchors at exposed metal sites via O-M coordination, with Ti and Fe sites exhibiting stronger initial binding than Mg, Ca, or Al sites. The Hard–Soft Acid–Base (HSAB) principle provides a qualitative framework for this low-coverage site preference based on Lewis acidity. Specifically, the accessible d-orbitals and localized states of Ti/Fe centers introduce substantial covalent orbital coupling and interfacial polarization, which effectively reinforce the binding with the hard O-donor of water. However, as water coverage increases, the stabilization mechanism undergoes a fundamental transition. At low coverage, adsorption is localized and site-specific, governed by cation acidity. At high coverage, the formation of laterally connected hydrogen-bonded networks becomes the dominant stabilizing factor, and the overall adsorption behavior is increasingly dictated by surface topology and geometric compatibility for hydrogen-bond connectivity rather than by isolated cation acidity. This coverage-dependent evolution from electronic-driven anchoring to topology-driven network formation establishes a dual-stage cooperative mechanism for water accumulation on lunar mineral surfaces. Our findings suggest that models for volatile retention on airless bodies must account for both the electronic activity of surface cations and the structural topology of mineral surfaces. Full article