Search Results (495)

Granular collapse-induced wave generation is a critical process in coastal engineering and natural hazards, yet its rapid and complex fluid–solid coupling mechanism poses significant challenges for numerical modeling. This paper presents a comprehensive validations and performance benchmarking study of non-spherical granular collapse-induced wave generation using a GPU-accelerated resolved SPH-DEM coupling framework. Through three benchmark cases with increasing complexity, the numerical accuracy and robustness of the model are thoroughly verified with respect to free-surface flows, multi-body collisions, and intense fluid–solid interactions. Subsequently, the influence of SPH resolution and particle shape on computational efficiency is quantitatively assessed. It is found that the total runtime is dominated by the number of SPH particles, while the GPU acceleration advantage becomes more pronounced as the number of DEM faces increases. Furthermore, in the granular collapse-induced wave case, the temporal evolution of the leading wave amplitude and the difference in granular runout distance under dry and wet conditions are analyzed, revealing from the particle scale how fluid resistance modulates the coupling between wave generation and granular motion. This study not only validates the capability of the model to capture complex particle–wave interactions, but also provides quantifiable performance benchmarks and physical insights for its engineering applications. Full article

Deep Cretaceous clastic reservoirs in the Kuqa Depression are major targets for natural gas exploration in the Tarim Basin. Recent exploration of the Yageliemu Formation in the Ketan area has revealed considerable resource potential, although reservoir performance is strongly affected by deep burial, compaction, repeated fluid–rock interaction, and pronounced pore-system heterogeneity. Core descriptions, epoxy-impregnated thin sections, cathodoluminescence, scanning electron microscopy, conventional petrophysical measurements, mercury intrusion capillary pressure, and nuclear magnetic resonance data were integrated to evaluate sedimentary fabric, reservoir-space types, pore-throat characteristics, and diagenetic modification. The succession was deposited mainly in a braided river delta plain setting and is dominated by medium sandstone, pebbly sandstone, and fine conglomerate. Overall reservoir quality is poor, with an average porosity of 3.4% and permeability commonly between 0.01 and 0.5 mD. MICP and NMR data distinguish four pore-structure types. From Type I to Type IV, average displacement pressure rises from 0.89 to 11.02 MPa, whereas median throat radius and movable-fluid porosity decline from 0.17 to 0.01 μm and from 2.00% to 0.72%, respectively. Residual intergranular pores constitute the main storage space, while feldspar- and lithic-fragment-dissolution pores provide additional local storage. Fractures contribute little pore volume but can markedly improve connectivity where they remain open or only weakly cemented. The present reservoir heterogeneity reflects the combined effects of sand-body stacking, sandstone–mudstone arrangement, fault-related fracturing, and multistage diagenesis. The most favorable intervals occur in thick, relatively clean stacked sand bodies where residual pores are preserved, dissolution pores remain connected to the throat network, and fractures have undergone limited late-stage filling. Full article

Proteomics has emerged as a powerful tool for advancing our understanding of brain disorders by enabling large-scale characterization of protein expression, post-translational modifications, and interaction networks. Neurological conditions are often characterized by complex and dynamic molecular changes that are not fully captured by traditional diagnostic approaches. Proteomic technologies, particularly mass spectrometry-based and affinity-based methods, offer the ability to identify disease-specific protein signatures and elucidate underlying pathophysiological mechanisms, including neurodegeneration, neurodevelopment and neuroinflammation and alterations happening to the extracellular matrix and body fluid homeostasis. In recent years, artificial intelligence has emerged as a powerful tool to proteomics, enabling improved analysis of complex biological datasets. This integration has significantly enhanced the discovery of biomarkers for early diagnosis, disease stratification, and monitoring of therapeutic responses. Thus, cerebrospinal fluid and blood-based proteomic analyses have revealed promising candidates for neurological diseases. This review summarizes current advances in proteomics across a range of brain disorders, highlighting key molecular pathways, biomarker discovery efforts, and evolving clinical applications. Furthermore, it outlines future directions, including the application of machine learning for improved biomarker identification and precision medicine. Full article

Building on previous work to understand mental transformation of solid objects, our work aims to contribute to theory on how individuals visualize fluid transformation. Working at the intersection of discipline-based research in fluid-Earth sciences (oceanography and atmospheric science) and cognitive science, we began by characterizing students’ mental models of fluids in solid body rotation. Using a common pedagogical tool of oceanography and atmospheric science instructors—large water filled rotating tanks—we conducted semi-structured, interactive interviews in conjunction with demonstrations of solid body fluid rotation to elicit participants’ sketched predictions and explanations of their reasoning. We used emergent coding to analyze the data and found that participants confidently predicted fluid behavior; however, their predictions were highly inaccurate, much to the participants’ surprise. These results suggest that the behavior of rotating fluids is unintuitive, and that the mind adopts prior experiences with fluids to fill the gap. We suggest that a better understanding of how humans reason about fluids can inform the cognitive science of event processing and suggest that framing mental transformation using an event perspective may be a productive approach. Full article

Aim: While voluntary Islamic intermittent fasting (IF) of three consecutive days (mimicking practices such as Ayyam al-Bid) may be observed by Muslim athletes, its short-term effects on cognitive function and sleep quality in adolescent team-sport athletes remain unexamined. This study investigated the impact of three successive days of dawn-to-sunset IF on memory, attention, psychomotor vigilance, and subjective sleep quality in young male soccer players. Methods: A quasi-experimental, parallel-group design was employed. Thirty-five male soccer players (age: 15.6 ± 0.8 years; body mass: 55.07 ± 6.53 kg) were allocated to an IF group (n = 17) or a non-fasting control group (n = 18). The fasting protocol comprised approximately 14 consecutive hours of complete food and fluid abstinence per day (from 04:40 to 18:36, with daily variations of −3 min for the dawn and +2 min for the sunset, local time). Cognitive function was assessed using the CogniFit Cognitive Assessment Battery (CAB) and the Psychomotor Vigilance Test (PVT), and subjective well-being was quantified via the Hooper Index. Both assessment sessions were conducted between 14:00 and 17:00 to control for diurnal variation. Results: The Group × Time interaction for single-item subjective sleep quality reached nominal significance at the unadjusted threshold (Z = 2.18, p = 0.029, r = 0.37) but did not survive Bonferroni correction for the four Hooper Index comparisons (α = 0.0125); this result is therefore interpreted as hypothesis-generating only, reflecting a within-group deterioration in the control group (p < 0.05) alongside a non-significant marginal improvement in the fasting group. No statistically significant Group × Time interaction was detected for any memory subdomain (all p ≥ 0.419, r ≤ 0.14), attention component (all p > 0.176, r ≤ 0.23), or PVT parameter (all p > 0.192, η²p/r ≤ 0.22) under the present study conditions. Within-group improvements in memory and attention observed in both groups were consistent with test–retest learning effects. Conclusions: No statistically significant Group × Time interaction was detected for memory, attention-related executive functions, or psychomotor vigilance in young male soccer players under the present study conditions; the study was not designed as an equivalence or non-inferiority trial and cannot exclude effects smaller than the targeted medium magnitude, alongside a nominally divergent but statistically uncorrected sleep quality trajectory relative to non-fasting controls, which should be interpreted as hypothesis-generating pending replication. These findings provide preliminary, hypothesis-generating evidence that no statistically significant cognitive or psychomotor impairment was detected under the present study conditions; because the study was not designed as an equivalence or non-inferiority trial, compatibility between short-term voluntary IF and adolescent athletic training cannot be inferred from the absence of a significant interaction alone. Full article

Background: Skeletal muscle index (SMI, kg/m²) derived from bioelectrical impedance analysis (BIA) is widely used to assess muscle mass. However, SMI is influenced by extracellular fluid, potentially leading to inaccurate estimation in patients with fluid imbalance. Intracellular water normalized by height squared (ICW/height², L/m²) may reflect intracellular body cell volume and provide complementary information to BIA-derived SMI, particularly in patients with altered hydration or low nutritional reserve. Based on these considerations, we hypothesised that ICW/height² would demonstrate stronger correlations with BMI than SMI, that the SMI–ICW/height² correlation would differ significantly by sex, and that hydration status (ECW/TBW) would modulate this relationship. Objective: To compare ICW/height² with SMI and evaluate their relationships with nutritional status and hydration in hospitalized patients. Specifically, we tested the hypotheses that (1) ICW/height² correlates more strongly with BMI than SMI; (2) the SMI–ICW/height² correlation differs significantly between sexes; and (3) ECW/TBW and sex interact to modulate the SMI–ICW/height² relationship. Methods: This single-centre, retrospective, exploratory cross-sectional study included 477 hospitalized patients (232 men and 245 women) who underwent body composition assessment using BIA. SMI and ICW/height² were examined in relation to body mass index (BMI) and hydration status assessed by extracellular water to total body water ratio (ECW/TBW). Correlation analyses were performed overall and stratified by sex, BMI categories (<18.5, 18.5–24.9, ≥25 kg/m²), and ECW/TBW groups (<0.36, 0.36–0.40, >0.40). Results: ICW/height² showed a stronger correlation with BMI than SMI in both men (R² = 0.492 vs. 0.338) and women (R² = 0.354 vs. 0.121). A strong correlation between SMI and ICW/height² was observed in men (R² = 0.634), whereas the correlation was weaker in women (R² = 0.316). In BMI-stratified analyses, the correlation between SMI and ICW/height² increased with higher BMI in men (R² = 0.192, 0.467, 0.791), while in women it was markedly attenuated in the low BMI group (R² = 0.134). Stratification by ECW/TBW showed that in men, the correlation remained strong under normal hydration conditions but was attenuated in the high ECW/TBW group. In contrast, in women, the correlation was weak even within the normal ECW/TBW range (R² = 0.336) and particularly poor in the low ECW/TBW group (R² = 0.060). Among women with normal ECW/TBW, those with low BMI demonstrated clear discordance between SMI and ICW/height². Exploratory four-quadrant classification using sex-specific SMI and ICW/height² thresholds further demonstrated that patients with discordant SMI and ICW/height² values had distinct BMI profiles, and BMI differed significantly among the four groups in both men and women (Kruskal–Wallis test, p < 0.001). Conclusions: These exploratory findings suggest that ICW/height² and BIA-derived SMI may show systematic discordance under specific clinical conditions, particularly in underweight or fluid-imbalanced hospitalised patients. Prospective validation against reference-standard body-composition measures is required before any clinical application. Full article

Background: Postoperative hemoglobin (Hb) reduction reflects the physiologic extent of perioperative blood loss after total knee arthroplasty (TKA). Whereas previous studies have relied on transfusion as a binary endpoint, transfusion decisions are highly variable across institutions, obscuring the underlying hematologic trajectory. This study aimed to develop and interpret machine learning (ML) models to characterize and quantify the determinants of postoperative Hb reduction in a standardized cohort of non-transfused TKA patients. Methods: A retrospective cohort of 866 patients who underwent primary TKA under a standardized operative protocol—with identical cemented posterior-stabilized implants and uniform cementing technique—was analyzed (1 January 2014–31 March 2024). During the study period, a consistent 1 g intra-articular tranexamic acid (TXA) regimen administered through the drain was introduced and applied to a subset of patients, allowing TXA use to be modeled as a binary predictor. Four ML algorithms (Linear Regression, Random Forest, XGBoost, and Stacking Regressor) were trained using preoperative, demographic, and perioperative variables. Fivefold cross-validation assessed model performance, and SHapley Additive exPlanations (SHAP) values were used to identify influential predictors and enhance interpretability. Results: Across all ML models, preoperative Hb emerged as the strongest determinant of postoperative Hb reduction, followed by TXA use, body mass index (BMI), and platelet count. Ensemble models captured non-linear and interacting effects more effectively than linear regression. Test-set performance was modest (best R² = 0.330), consistent with the influence of unmeasured physiologic factors such as hidden blood loss, fluid dynamics, and inflammatory responses. Accordingly, the primary value of the framework lies in the exploratory and transparent assessment of determinant importance rather than in individual-level prediction. Conclusions: This study provides an interpretable, exploratory ML framework for identifying factors associated with percentage Hb reduction after TKA. Preoperative Hb was the dominant determinant, while TXA use and higher BMI were recurrently associated with smaller predicted percentage reductions. Given the modest test-set performance and the absence of external validation and clinical utility assessment, the models should not be interpreted as tools for individual-level prediction or clinical decision making. Full article

We have found for the first time several distinct, very large (1.25–1.69 megadaltons), stable protein–peptide complexes in various organs and tissues (upper body wall, gonads, respiratory trees, gut, and coelomic fluid) of the sea cucumber Eupentacta fraudatrix. It has been previously shown that complexes isolated from the whole organism are destroyed only under very harsh conditions. Here, for the first time, complexes were isolated from individual organs of the sea cucumber Eupentacta fraudatrix. According to gel filtration data, the molecular weights (MWs) of complexes from different organs are distinct but comparable (in kDa): 1690 ± 29 (coelomic fluid), 1650 ± 307 (gut), 1550 ± 253 (gonads), 1520 ± 140 (body wall), and 1250 ± 97 (respiratory trees). All complexes contain many of the same as well as different proteins with MWs of 10–20 kDa and >20 kDa. The number and type of proteins in the 10–20 kDa range vary among organs: body wall (20), gonads (19), coelomic fluid (16), gut (13), and respiratory trees (14). In addition, each complex contains specific proteins and peptides that are not present in complexes from other organs, and the number of such unique proteins also differs: body wall (13), gonads (7), respiratory trees (5), gut (4), and coelomic fluid (0). In the entire set of complexes isolated from the whole organism, 469 oligopeptides were identified, whereas only 370 peptides were detected in complexes from the five analyzed individual organs. The number of various peptides with MWs below 10 kDa in individual organ complexes decreases in the following order: body wall (134) > gut (115) > coelomic fluid (95) > respiratory trees (88) > gonads (70). These complexes contain both shared and distinct oligopeptides. Such highly stable complexes from different organs of sea cucumber Eupentacta fraudatrix have been isolated and characterized for the first time. In contrast to individual proteins and peptides, multiprotein complexes have expanded functional possibilities, as they can interact with various molecules and cells with which the individual proteins, enzymes, and peptides comprising the complexes can interact. Thus, they can perform the functions of all components located on their surfaces. One may suppose that many of the specific proteins, peptides, and enzymes within each complex are necessary for carrying out the specific biological functions of each individual organ. Full article

The ballistic impact behavior of soft body armor is governed by complex interactions between material architecture and projectile characteristics. This review provides a critical overview of the evolution of textile and composite-based armor materials developed for ballistic protection. Emphasis is placed on experimental and analytical methodologies used to elucidate impact energy dissipation, deformation mechanisms, and failure modes. Key material-related parameters influencing ballistic performance including areal density, weave architecture, yarn crimp, twist, and thread density are systematically discussed, along with assembly variables such as ply orientation, layer number, and hybrid configurations. In parallel, the influence of projectile mass, velocity, and geometry on impact resistance is examined. The review also summarizes internationally adopted ballistic and stab-resistance standards employed for soft armor evaluation. Various assessment techniques, including yarn–yarn friction analysis, puncture resistance testing, ballistic limit velocity determination, and back-face signature measurement, are critically reviewed. Strategies aimed at enhancing impact performance, such as rubber or latex impregnation, fiber surface modification, and the incorporation of shear thickening fluids, are comprehensively discussed. Attention is given to shear thickening fluids due to their significant role in improving energy absorption and flexibility. The fundamental mechanisms governing shear thickening behavior and the parameters affecting their performance are analyzed. Overall, this review highlights emerging material design strategies and performance optimization approaches for next-generation soft body armor systems. Full article

Purpose: Maintaining fluid homeostasis is crucial, and replenishing electrolytes—particularly sodium (Na⁺)—is critical for effective rehydration after thermal hypohydration. Despite the growing consumption of carbonated water (CW), its impact on post-hypohydration body fluid balance, either alone or combined with electrolytes, remains inadequately investigated. Therefore, this study was designed to examine the separate and interactive effects of carbonation and electrolyte provision in rehydration fluids—utilizing a 2 × 2 factorial design (carbonation × electrolytes)—on ingestive behavior and systemic fluid balance following mild thermal stress-induced hypohydration. Methods: Subjects (eight women and seven men, age range: 19–25 years) were dehydrated by performing three bouts of stepping exercise for 20 min, separated by 10 min of rest, at 25 °C. Following the dehydration protocol, subjects ingested pure water (W), CW (gas volume, 3.43 ± 0.20 (mean ± standard deviation)), electrolyte-added water (EW), or electrolyte-added CW (ECW) (gas volume, 3.04 ± 0.29 (mean ± standard deviation)) ad libitum. EW and ECW contained 19 mEq/L Na⁺. We assessed ingestive behavior and body fluid balance during the 180 min rehydration period. Results: The dehydration protocol induced hypohydration by ~10 g/kg body weight (~1% of body weight). Cumulative fluid intake was greater in the W trial than in the CW, EW, and ECW trials. Cumulative urine output was greater in the W and CW trials than in the EW trial. The fluid retention ratio was greater in the EW and ECW trials than in the CW trial. Consequently, the final fluid recovery was lower in the CW trial compared to the W, EW, and ECW trials; however, the combination of carbonation and electrolytes (ECW) did not significantly surpass the non-carbonated trials (W and EW) due to the reduced intake volume caused by carbonation. Conclusions: The data suggest that ad libitum ingestion of carbonated water is less effective than plain water for recovering from mild hypohydration (~1% body weight loss), as it reduces spontaneous fluid intake. However, electrolyte supplementation mitigates this reduced recovery by attenuating diuresis and consequently improving fluid retention ratio. Full article

To elucidate the solute sources, migration and enrichment mechanisms of water bodies in the endorheic lake region of the Qiangtang Plateau on the Tibetan Plateau and clarify the hydrogeochemical cycling patterns in alpine arid environments, this study focuses on two core scientific objectives: quantitative identification of the multi-source contributions of aquatic solutes, and revelation of the key processes governing the enrichment of strategic elements including lithium (Li) and boron (B). To achieve these goals, we conducted systematic hydrogeological field investigations and collected 28 multi-type water samples, covering springs, rivers, thermal springs, freshwater lakes, salt lake brines, atmospheric precipitation, and glacial meltwater. The physicochemical properties, major ions, and trace elements of all samples were comprehensively analyzed. On this basis, the hydrogeochemical characteristics, evolutionary processes, and solute origins of regional waters were systematically explored. Combined with PHREEQC numerical simulation, principal component analysis (PCA), and Pearson correlation analysis, the dominant controlling factors of water geochemistry were quantified, and a conceptual hydrogeochemical evolution model was established. The results reveal a clear hydrogeochemical evolutionary gradient across the study area: water bodies evolve from low-salinity HCO₃-Ca recharge end-members and transitional HCO₃·SO₄-Ca(Mg) type water to highly mineralized Cl-Na (SO₄·Cl-Na) salt lake brines, accompanied by synchronous enrichment of Li, B, arsenic (As), and other characteristic elements. Solute accumulation in regional waters is governed by the ternary coupling effects of evaporative concentration, rock weathering and leaching, and deep geothermal fluid input, while cation exchange and mineral dissolution–precipitation reactions further modulate ionic composition and ratios. Elements including As, Li, B, and chloride (Cl⁻) exhibit conservative migration behaviors in non-hydrothermal waters, whereas thermal springs possess unique geochemical signatures driven by deep fluid recharge. PCA results indicate that evaporative concentration serves as the primary controlling factor with a contribution rate of 55.39%; rock weathering provides the basic solute load (17.09%); and the coupled processes of deep fluid mixing and carbonate precipitation regulate elemental fractionation (14.21%). These findings systematically clarify the hydrogeochemical evolution laws and multi-source coupling mechanisms of inland lake waters in the Qiangtang Plateau. Furthermore, this study establishes a conceptual framework of “multi-source recharge–water–rock interaction–evaporative concentration”, advances the understanding of alpine hydrological cycling under climate change, and provides a solid scientific foundation for hydrological cycle research and green exploration of strategic mineral resources in endorheic salt lake regions. Full article

Laser powder bed fusion (LPBF) poses significant simulation challenges due to its highly nonlinear thermo-fluid-solid coupling. To address this, we propose an adaptive framework coupling the edge-based smoothed finite element method (ES-FEM) and smoothed particle hydrodynamics (SPH) via a bidirectional element-particle transformation algorithm. This integration leverages ES-FEM for modeling solid thermo-mechanical responses and SPH for resolving melt pool dynamics, enabling fully coupled simulation of temperature, fluid flow, and stress within a unified model. The framework comprises three key components: a nodal mass normalization scheme ensuring conservation during transformations, a ghost particle algorithm for solid-fluid heat transfer and interaction, and a bidirectional finite-element-to-particle conversion mechanism. This work represents the first implementation of bidirectional coupling between mesh-free Lagrangian SPH and Lagrangian FEM. The validation against benchmark cases confirms the framework’s accuracy in capturing transient thermal, hydrodynamic, and mechanical behavior. It successfully reproduces key LPBF phenomena, including melt pool morphology, Marangoni flows, and residual stress evolution, demonstrating its suitability for high-fidelity LPBF process simulation. It should be noted that the current ES-FEM-SPH framework has not taken into account the recoil pressure, evaporation, and the interaction between the powder and the molten pool. The powder is regarded as a rigid body. Future work will focus on incorporating these neglected physical factors to further improve the predictive capability of the proposed framework. Full article

This paper examines how asking “why” may function as a form of censorship that regulates the actions and desires of disabled people. We describe how one author’s life was transformed by 24 h personal assistance, which let her pursue activities “unnecessary for sustaining life” and “be picky about her daily routines.” Building on phenomenological research, we argue that the lack of discretion in homemaking alienates disabled people. While Independent Living with a personal assistant enables homemaking that reflects personal preferences, pursuing “unnecessary activities” or “pickiness” can be difficult because of the pressure to explain reasons to caregivers. The author developed a habit of explaining her reasons—often initially or excessively—from a lifetime of interactions with non-disabled people who constantly demanded justification. This demand for explanation places a burden of justification on disabled people, censoring their “pickiness” or comfort by dismissing it as an “unnecessary luxury.” This “censorship of reasons” maintains the fluid flow of actions conducted by non-disabled people within an ableist society. The recognition of this creates a space for reexamining able-bodied normalcy and the excessive fluidity expected within ableist social structures. Full article

We present a unified GPU-accelerated framework for real-time Smoothed Particle Hydrodynamics (SPH) fluid simulation with two-way rigid body coupling, secondary particle effects, and volumetric rendering, implemented entirely within the Unity game engine. The framework employs a weakly compressible SPH formulation with O(n) count sort-based spatial hashing and introduces a signed distance field (SDF) coupling system that evaluates three representative geometric primitives, sphere, cylinder, and torus, of increasing topological complexity directly on the GPU. Bidirectional force exchange is achieved through lock-free atomic compare-and-swap impulse accumulation, enabling thousands of fluid particles to interact simultaneously with each rigid body without serialization. A GPU stream compaction–based secondary particle system generates and classifies foam, spray, and bubble effects in real time, while a volumetric rendering pipeline samples fluid density into a 3D texture for SDF-composited volume rendering without surface mesh extraction. A conditional kernel dispatch strategy eliminates GPU cycles for disabled subsystems, and dynamic buffer management reduces memory pressure through runtime allocation. The system sustains above 54 frames per second at four million particles on a consumer-grade GPU, with sub-linear frame time scaling and a 1.70× speedup from dynamic buffer allocation over static pre-allocation. Full article

The optimisation design of agricultural machinery is shifting from offline, experience-driven engineering towards adaptive, data-driven, and closed-loop intelligent optimisation. Conventional approaches based on computer-aided engineering (CAE), empirical testing, mathematical modelling, and static multi-objective optimisation have provided an important engineering foundation, but they remain limited under unstructured field conditions involving soil heterogeneity, crop variability, climatic disturbance, and nonlinear machinery–environment interactions. This review systematically examines the evolution of intelligent optimisation design for agricultural machinery from conventional simulation-based methods to artificial intelligence (AI)- and digital twin (DT)-enabled paradigms. First, mathematical modelling, response surface methodology, discrete element method (DEM), computational fluid dynamics (CFD), multi-body dynamics (MBD), heuristic algorithms, and early AI-assisted surrogate optimisation are reviewed to clarify their contributions and limitations. Second, frontier enabling technologies are analysed, including agriculture-specific large models, generative AI, lightweight edge intelligence, deep reinforcement learning (DRL), embodied AI, federated learning (FL), and privacy-preserving computing. Third, system-level applications integrating DT and AI are discussed, with emphasis on full-lifecycle machinery optimisation, device–edge–cloud collaborative control, multi-agent fleet coordination, predictive maintenance, and Agriculture 5.0-oriented intelligent equipment systems. Key deployment bottlenecks are further identified, including sim-to-real inconsistency, virtual–physical mismatch in DTs, edge-side trade-offs among accuracy, latency, energy consumption, and cost, insufficient validation standards, and economic adoption barriers. Finally, a 2025–2030 roadmap is proposed, highlighting large-model–DT closed loops, control biomimetics, green low-carbon optimisation, and trustworthy human–machine symbiosis for sustainable Agriculture 5.0. Full article