Search Results (435)

Digital twins (DTs) have seen widespread application across industries, enabling deep integration of cyber–physical systems. However, previous research has largely focused on domain-specific DTs and lacks a universal, cross-industry modeling framework, resulting in high development costs and low reusability. To address these challenges, this study proposes a DT modeling method based on hierarchical decoupling and topological connections. First, the system is decomposed top–down into three levels—system, subsystem, and component—through hierarchical functional decoupling, reducing system complexity and supporting independent component development. Second, a method for constructing component-level DTs using standardized information sets is introduced, employing the JSON-LD language to uniformly describe and encapsulate component information. Finally, a topological connection mechanism abstracts the relationships between components into an adjacency matrix and assembles components and subsystems bottom–up using graph theory, ultimately forming the system-level DT. The effectiveness of the proposed method was validated using a typical surface water purification system as a case study, where the system was decomposed into four functional subsystems and 12 types of components. Experimental results demonstrate that the method efficiently enables automated integration of DTs from standardized components to subsystems and the complete system. Compared with conventional monolithic modeling approaches, it significantly reduces system complexity, supports efficient component development, and accelerates system integration. For example, when the number of components exceeds 300, the proposed method generates topology connections 44.69% faster than direct information set traversal. Consequently, this approach provides a novel and effective solution to the challenges of low reusability and limited generality in DT models, laying a theoretical foundation and offering technical support for establishing a universal cross-industry DT modeling framework. Full article

Soil compaction in grassland and agricultural soils reduces water infiltration, root growth and ecosystem services. Conventional deep tillage and coring can alleviate compaction but are energy intensive and strongly disturb the turf. This study proposes an earthworm-inspired subsurface robot as a low-disturbance loosening tool for compacted grassland soils. Design principles are abstracted from earthworm body segmentation, anchoring–propulsion peristaltic locomotion and corrugated body surface, and mapped onto a robotic body with anterior and posterior telescopic units, a flexible mid-body segment, a corrugated outer shell and a brace-wire steering mechanism. Kinematic simulations evaluate the peristaltic actuation mechanism and predict a forward displacement of approximately 15 mm/cycle. Using the finite element method and a Modified Cam–Clay soil model, different linkage layouts and outer-shell geometries are compared in terms of radial soil displacement and drag force in cohesive loam. The optimised corrugated outer shell combining circumferential and longitudinal waves lowers drag by up to 20.1% compared with a smooth cylinder. A 3D-printed prototype demonstrates peristaltic locomotion and steering in bench-top tests. The results indicate the potential of earthworm-inspired subsurface robots to provide low-disturbance loosening in conservation agriculture and grassland management, and highlight the need for field experiments to validate performance in real soils. Full article

Accurate forecasting of groundwater level dynamics poses a critical challenge for sustainable water management in arid regions. However, the strong spatiotemporal heterogeneity inherent in groundwater systems and their complex interactions between natural processes and human activities often limit the effectiveness of conventional prediction methods. To address this, a hybrid CNN-LSTM deep learning model is constructed. This model is designed to extract multivariate coupled features and capture temporal dependencies from multi-variable time series data, while simultaneously simulating the nonlinear and delayed responses of aquifers to groundwater abstraction. Specifically, the convolutional neural network (CNN) component extracts the multivariate coupled features of hydro-meteorological driving factors, and the long short-term memory (LSTM) network component models the temporal dependencies in groundwater level fluctuations. This integrated architecture comprehensively represents the combined effects of natural recharge–discharge processes and anthropogenic pumping on the groundwater system. Utilizing monitoring data from 2021 to 2024, the model was trained and tested using a rolling time-series validation strategy. Its performance was benchmarked against traditional models, including the autoregressive integrated moving average (ARIMA) model, recurrent neural network (RNN), and standalone LSTM. The results show that the CNN-LSTM model delivers superior performance across diverse hydrogeological conditions: at the upstream well AJC-7, which is dominated by natural recharge and discharge, the Nash–Sutcliffe efficiency (NSE) coefficient reached 0.922; at the downstream well AJC-21, which is subject to intensive pumping, the model maintained a robust NSE of 0.787, significantly outperforming the benchmark models. Further sensitivity analysis reveals an asymmetric response of the model’s predictions to uncertainties in pumping data, highlighting the role of key hydrogeological processes such as delayed drainage from the vadose zone. This study not only confirms the strong applicability of the hybrid deep learning model for groundwater level prediction in data-scarce arid regions but also provides a novel analytical pathway and mechanistic insight into the nonlinear behavior of aquifer systems under significant human influence. Full article

Bamboo has evolved a highly optimized structural system in its culms, which this study transfers into lightweight fiber composite trusses fabricated by coreless filament winding. Focusing on the structural segmentation involving diaphragms of the biological role model, this design principle was integrated into the additive manufacturing process using a multi-stage winding, a tiling approach, and a water-soluble winding fixture. Through a FE-assisted analytical abstraction procedure, the transition to a carbon fiber material system was considered by determining a geometrical configuration optimized for structural mass, bending deflection, and radial buckling. Samples were fabricated from CFRP and experimentally tested in four-point bending. In mass-specific terms, integrating diaphragms into wound fiber composite samples improved failure load by 36%, ultimate load by 62%, and energy absorption by a factor of 7, at a reduction of only 14% in stiffness. Benchmarking against steel and PVC demonstrated superior mass-specific performance, although mōsō bamboo still outperformed all technical solutions, except in energy absorption. Full article

In coastal regions, the interaction between freshwater and seawater creates a dynamic system in which the spatial distribution of salinity critically constrains the use of freshwater for human consumption. Although saline intrusion is a globally widespread phenomenon, its inland extent varies significantly with hydrological conditions, posing a persistent threat to groundwater quality and sustainability. This study aimed to characterize salinity distribution using an integrated karst-watershed approach, thereby enabling the identification of both lateral and vertical salinity gradients. The study area is in the northwestern Yucatan Peninsula. Available hydrogeological data were analyzed to determine aquifer type, soil texture, evidence of saline intrusion, seawater fraction, vadose zone thickness, and field measurements. These included sampling from 42 groundwater sites (open sinkholes and dug wells), which indicated a fringe zone approximately 5 km in size influenced by seawater interaction, in mangrove areas and in three key zones of salinity patterns: west of Mérida (Celestun and Chunchumil), and northern Yucatan (Sierra Papacal, Motul, San Felipe). Vertical Electrical Sounding (VES) and conductivity profiling in two piezometers indicated an apparent seawater influence. The interface was detected at a depth of 28 m in Celestun and 18 m in Chunchumil. These depths may serve as hydrogeological thresholds for freshwater abstraction. Results indicate that saltwater can extend several kilometers inland, a factor to consider when evaluating freshwater availability. This issue is particularly critical within the first 20 km from the coastline, where increasing tourism exerts substantial pressure on groundwater reserves. A coastal-to-inland salinity was identified, and an empirical equation was proposed to estimate the seawater fraction (fsea%) as a function of distance from the shoreline in the Cenote Ring trajectory. Vertically, a four-layer model was identified in this study through VES in the western watershed: an unsaturated zone approximately 2.6 m thick, a confined layer in the coastal Celestun profile about 9 m thick, a freshwater lens floating above a brackish layer between 8 and 25 m, and a saline interface at 37 m depth. The novelty of this study, in analyzing all karstic water surfaces together as a system, including the vadose zone and the aquifer, and considering the interactions with the surface, is highlighted by the strength of this approach. This analysis provides a better understanding and more precise insight into the integrated system than analyzing each component separately. These findings have significant implications for water resource management in karst regions such as Yucatan, underscoring the urgent need for sustainable groundwater management practices to address seawater intrusion. Full article

Current upper-limb rehabilitation robots primarily focus on training tasks involving free movements or static interactions with rigid objects. These paradigms lack simulation of complex object manipulation tasks encountered in daily life, thereby limiting the training of patients’ high-level sensorimotor integration capabilities. To address this gap, this study proposes an innovative robotic rehabilitation training system designed for functional occupational therapy. Specifically, the task of transporting a water cup was abstracted into a cup–ball system integrated with a robotic arm. The ball was modeled as a point mass, and kinematic and dynamic analyses of the system were conducted. A visual tracking method was employed to monitor the ball’s motion and calculate its slosh angle. Owing to the impaired fine motor control in stroke patients, a sloshing suppression control strategy integrating exponential filtering, feedforward force compensation, and impedance control was proposed to prevent the ball from spilling. Experiments validated the effectiveness of the proposed method. The results indicated that with full compensation, the oscillation rate of the ball was significantly reduced, and the smoothness of the hand force was markedly improved. This study presents an effective method for addressing dynamic uncertainty in rehabilitation robot training, thus significantly improving the functional relevance of the training. Full article

This paper presents an innovative derivation of intensity–duration–frequency (IDF) curves, which play a crucial role in the design of hydraulic infrastructures. IDF curves are herein derived from excess rainfall, that is, the net rainfall obtained by removing abstractions related to hydrological losses from total gross rainfall. When long fine fine-resolution time series of rainfall depth are available at a site, excess rainfall can be obtained by applying a simplified hydrological model of a catchment, including solely the gross-excess rainfall conversion. The application of annual maxima (AM) analysis on excess rainfall intensity data enables the construction of excess rainfall-based intensity–duration–frequency (ERIDF) curves. For assigned rainfall event criticality (return period) and duration, these curves directly provide the associated excess rainfall intensity value. This results in a better preservation of the return period in the rainfall–runoff transformation when used inside the rational formula for estimating peak water discharge, in comparison with the conventional approach adopted by practitioners, based on derivation of IDF curves and on the application of runoff coefficient for gross-excess rainfall conversion inside the rational formula. Full article

Groundwater resources in Jordan are under severe stress due to rapidly increasing water demand and over-abstraction that far exceeds natural replenishment. In addition, water quality is threatened by pollution from the misuse of fertilizers and pesticides, leakage from septic tanks, and illegal waste disposal. This study focuses on the Aqeb, Corridor, and Special Economic Zone wellfields, where hydrological and hydrochemical investigations were carried out. A total of 36 groundwater samples were collected and analyzed for hydrochemical composition, stable isotopes of oxygen (δ¹⁸O) and hydrogen (δ²H), and trace elements. In addition, two exploration 2D seismic profiles crossing the study area were interpreted, providing critical insights into the activity of the subsurface Fuluk Fault zone and its relationship with the wellfields. The hydrochemical results reveal elevated total dissolved solids and nitrate concentrations, accompanied by more depleted δ¹⁸O and δ²H values in wells located in the central part of the study area. Three distinct hydrochemical groups were identified within the same aquifer, indicating heterogeneity in groundwater chemistry that reflects variations in recharge conditions, flow paths, and geochemical processes. The first group (high Na/Cl with low salinity) likely represents recently recharged waters with limited rock–water interaction. The second group (intermediate Na/Cl and moderate salinity) may be influenced by evaporation, irrigation return flow, or cation exchange. The third group (low Na/Cl with high salinity) suggests the dissolution of sulfate minerals or mixing with deeper mineralized groundwater, possibly facilitated by structural features such as the Fuluk Fault. Seismic interpretation indicates several active near-surface fault systems that are likely to serve as preferential pathways for salinity and nitrate enrichment, linked to intensive agricultural activities and wastewater leakage from nearby septic tanks. The findings emphasize the combined influence of geochemical processes, excessive groundwater abstraction, and structural features in controlling water quality in the region. Full article

This study examines the contribution of ERASMUS+ Key Action 2 (KA2) projects, funded between 2014 and 2020, to the dissemination and promotion of the United Nations Sustainable Development Goals (SDGs). A predominantly quantitative content analysis was conducted based on metadata extracted from the official European Commission database, focusing on the presence of SDG-related keywords within the titles, topics, and abstracts of the projects. In total, 24,838 KA2 projects were examined. The findings reveal a growing alignment between funded projects and certain SDGs, particularly SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), SDG 13 (Climate Action), SDG 7 (Affordable and Clean Energy), and SDG 9 (Industry, Innovation, and Infrastructure). In contrast, goals such as SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), and SDG 14 (Life Below Water) are scarcely represented. Overall, the results demonstrate an increasing commitment to sustainability themes over time and also highlight notable gaps in the promotion of several SDGs. This analysis offers valuable insights into the strategic alignment of ERASMUS+ funding with the 2030 Agenda and identifies opportunities for strengthening its future contributions to sustainable development. Full article

As the teachings continued to expand within Daoism, Thunder Rituals (Leifa 雷法) inevitably faced the crucial question of how to integrate the newly emphasized thunder element within the traditional Five-Phase system upon its emergence. To address this, Wang Wenqing (王文卿), the founding master of Shenxiao(神霄 Daoism school) Daoism who held a pivotal position in the realm of Thunder Rituals, creatively proposed the theory of “Five Zi Returning to Geng” (五子歸庚). On the one hand, drawing upon the Najia (納音 Stem–Branch Correspondence) theory from the Zhou Yi Can Tong Qi, this theory posits that thunder corresponds to the number five, occupies the central position, and belongs to the earth element, thereby reinforcing the core thesis of Leifa’s internal alchemy that thunder is generated through the interaction of water and fire. On the other hand, by ingeniously adapting the Nayin method of the Sixty JiaZi (六十甲子), it offers a creative interpretation of the abstract relationship between thunder and the Five Phases, asserting that all phases ultimately converge toward the central Geng/thunder. Together, these two aspects demonstrate that thunder in fact occupies a central position alongside earth within the Five-Phase system. This theory not only provides a sophisticated resolution to the question of thunder’s relationship with the Five Phases but also furnishes solid theoretical support for the elevated status of Thunder Rituals. Full article

This study explores nonthermal plasma reactions of methane and water in a two-phase system to produce methanol, examining reaction pathways, kinetics, and product distribution over time. The results show that methanol is the dominant liquid phase product among other oxygenates, including ethanol and acetic acid, with hydrogen as the largest fraction among gas-phase products comprising carbon monoxide, carbon dioxide, ethylene, and acetylene. Conductivity and pH trends of reactant water and their influence on reaction products were also analyzed. Methanol was found to be formed principally from the reactive coupling of methyl and hydroxyl radicals, as well as from methoxy and hydrogen radical combinations. Hydrogen was produced from three pathways: stepwise dehydrogenation of methane through electron-mediated hydrogen abstraction, sequential hydrogenation of ethane to acetylene, and water splitting. The methanol-yielding reactions proceeded at different rates in the liquid and gas phases, with gas-phase reactions occurring approximately nine times faster than the liquid-phase reactions. This work provides valuable insights into reaction pathways for direct methane conversion to oxygenates and value-added gas products under mild conditions using water as an environmentally friendly oxidant. Full article

The fluorescence of aqueous solutions of the aromatic amino acids tryptophan, tyrosine, and phenylalanine, an albumin solution, and a mixture of water-soluble animal and plant proteins is investigated after treatment with hydroxyl and hydroperoxyl radicals and continuous UV-C radiation at λ = 253.7 nm. The use of independent sources of active species allows for the study of activation and the development of free radical processes in model objects. The analysis is based on Stern–Volmer coefficients for the quenching of the fluorescence of the initial substrates and the ignition of the fluorescence of newly formed products. In the reaction with hydroxyl radicals, the hydrogen atom could be abstracted from any position in the target molecule. Under continuous UV-C radiation, the protein molecule as a whole was excited. Full article

Riparian zones, located at the interface between terrestrial and aquatic systems, are among the most dynamic and ecologically valuable landscapes. These transitional areas play a pivotal role in maintaining environmental health by supporting biodiversity, regulating hydrological processes, filtering pollutants, and stabilizing streambanks. At the core of these functions lie the unique characteristics of riparian soils, which result from complex interactions between water dynamics, sedimentation, vegetation, and microbial activity. This paper provides a comprehensive overview of the origin, structure, and functioning of riparian soils, with particular attention being paid to their physical, chemical, and biological properties and how these properties are shaped by periodic flooding and vegetation patterns. Special emphasis is placed on Mediterranean riparian environments, where marked seasonality, alternating wet–dry cycles, and increasing climate variability enhance both the importance and fragility of riparian systems. A bibliographic study, covering 25 years (2000–2025), was carried out through Scopus and Web of Science. The results highlight that riparian areas are key for carbon sequestration, nutrient retention, and ecosystem connectivity in water-limited regions, yet they are increasingly threatened by land use change, water abstraction, pollution, and biological invasions. Climate change exacerbates these pressures, altering hydrological regimes and reducing soil resilience. Conservation requires integrated strategies that maintain hydrological connectivity, promote native vegetation, and limit anthropogenic impacts. Preserving riparian soils is therefore fundamental to sustain ecosystem services, improve water quality, and enhance landscape resilience in vulnerable Mediterranean contexts. Full article

In response to the growing complexity of modern process manufacturing systems, this paper proposes a novel simulation framework named the Process–Equipment–In-Process State (PEI) simulation method, which introduces a unified and structured approach to modeling multi-stage industrial processes. Unlike conventional simulation approaches that rely on ad hoc or loosely organized modules, the PEI method decomposes the simulation system into three core and interoperable modules: Process Structure (P), Equipment Behavior (E), and In-Process State (I). This modular abstraction facilitates the decoupling of model logic. It also enables a structure-driven simulation execution mechanism. In this structure, the process topology governs task scheduling; equipment models translate control inputs into physical conditions; and state models simulate material evolution accordingly. A complete simulation case involving water mixing, heat exchange, and slurry transformation demonstrates the method’s capability to support traceable state evolution, logical task flow, and extensible model binding. The results demonstrate that the proposed method enables module decoupling, clear simulation pathways, and traceable state changes, providing effective support for structured modeling and behavioral evolution analysis in process manufacturing. Full article

This study investigates the groundwater over-exploitation zone in Xingtai City, North China Plain, to address two critical gaps in the current understanding of groundwater chemistry: the lack of established natural background levels (NBLs) and the ambiguous mechanisms of groundwater contamination. Sixty shallow-groundwater samples were collected and analyzed using a combination of Piper diagrams, cumulative-probability statistics, contamination-index methods, and multivariate statistical techniques to determine NBLs and threshold values (TVs) for major chemical constituents and to clarify the contamination mechanisms. The results indicate that the groundwater is weakly alkaline, with the most prevalent water types being HCO₃–Na and SO₄·Cl–Na. The NBLs for Na⁺, Ca²⁺, Mg²⁺, Cl⁻, $\mathrm{S}{\mathrm{O}}_4^{2-}$ and $\mathrm{N}{\mathrm{O}}_3^{-}$ are 32.3 mg/L, 34.1 mg/L, 17.8 mg/L, 46.2 mg/L, 66.4 mg/L and 0.886 mg/L, respectively, and the corresponding TVs are 116 mg/L, 54.6 mg/L, 33.9 mg/L, 248 mg/L, 258 mg/L and 44.7 mg/L. Based on the TVs, 56.7% of the sampling sites are identified as anthropogenically contaminated. Principal component analysis reveals that groundwater over-extraction, industrial activities and water–rock interaction are the dominant drivers of groundwater contamination, whereas intensive abstraction, agricultural fertilization and domestic sewage discharge exert additional influence. The findings provide a scientific basis for pollution control and sustainable utilization of groundwater in over-exploited regions. Full article