Search Results (19,957)

This study presents the deployment of Machine Learning (ML) models on low-cost edge devices (ESP32) for real-time water quality prediction in tilapia aquaculture. A compact monitoring and control system was developed with low-cost sensors to capture key environmental parameters under field conditions in Northern Thailand. Three ML models—Multiple Linear Regression (MLR), Decision Tree Regression (DTR), and Random Forest Regression (RFR)—were evaluated. RFR achieved the highest accuracy (R² > 0.80), while MLR, with moderate performance (R² ≈ 0.65–0.72), was identified as the most practical choice for ESP32 deployment due to its computational efficiency and offline operability. The system integrates sensing, prediction, and actuation, enabling autonomous regulation of dissolved oxygen and pH without constant cloud connectivity. Field validation demonstrated the system’s ability to maintain DO within biologically safe ranges and stabilize pH within an hour, supporting fish health and reducing production risks. These findings underline the potential of Edge AIoT as a scalable solution for small-scale aquaculture in resource-limited contexts. Future work will expand seasonal data coverage, explore federated learning approaches, and include economic assessments to ensure long-term robustness and sustainability. Full article

Connected and Autonomous Vehicles are promising for advancing traffic safety and efficiency. However, the increased connectivity makes these vehicles vulnerable to a broad array of cyber threats. This paper presents a novel hybrid approach for intrusion detection in in-vehicle networks, specifically focusing on the Controller Area Network bus. Ensemble learning techniques are combined with sophisticated optimization techniques and dynamic adaptation mechanisms to develop a robust, accurate, and computationally efficient intrusion detection system. The proposed system is evaluated on real-world automotive network datasets that include various attack types (e.g., Denial of Service, fuzzy, and spoofing attacks). With these results, the proposed hybrid adaptive system achieves an unprecedented accuracy of 99.995% with a 0.00001% false positive rate, which is significantly more accurate than traditional methods. In addition, the system is very robust to novel attack patterns and is tolerant to varying computational constraints and is suitable for deployment on a real-time basis in various automotive platforms. As this research represents a significant advancement in automotive cybersecurity, a scalable and proactive defense mechanism is necessary to safely operate next-generation vehicles. Full article

In this study, we numerically investigate the equilibrium dynamics of a rotating system consisting of two masses connected by a massless rod within the framework of the circular restricted three-body problem. The larger primary is modeled as a radiating body and the smaller as an oblate spheroid. We explore the influence of the involved parameters, i.e., mass ratio ($\mu$), force ratio (k), radiation pressure factor ($q_1$), and oblateness coefficient ($A_2$), on the number, positions, and linear stability of equilibrium points. Zero velocity curves are presented in the equatorial plane for varying values of the Jacobi constant. Up to five equilibrium points are identified of which three are collinear ($L_1$, $L_2$, $L_3$) and two are non-collinear ($L_4$, $L_5$). The positions of all equilibria shift under variations in the perturbing parameters. While the collinear points are generally unstable, $L_1$ can exhibit stability for certain combinations of $\mu$, k, and $q_1$. The non-collinear points may also be stable under specific conditions with stability zones expanding with increased parameter values. The model is applied to the irregular, elongated asteroid 951 Gaspra, for which five equilibrium points are found. Despite positional dependence on oblateness and radiation, the perturbations do not significantly affect the equilibrium points’ stability and the motion near them remains linearly unstable. The Lyapunov families of periodic orbits emanating from the collinear equilibria of this particular system are also investigated. Full article

This article presents an original experimental and numerical approach to examining the pull-out behavior of fastening systems made of steel bars simultaneously embedded in both ends of concrete samples. This double-embedded configuration simulates a connection between the existing concrete structure and a new external exoskeleton, promoting seismic strengthening. Pull-out tests were performed across six specimen configurations combining different concrete strength classes in order to compare the adhesive solution against traditional monolithic cast-in rebar embedments. The adhesive-anchored bars achieved a peak pull-out force of ~28.6 kN, which is about 18% higher than with mixed anchorage (one end adhesive, one end cast-in). All specimens failed in concrete cracking and pull-out cone formation, with no steel bar yielding, indicating that failure was governed by concrete strength. Finite element simulations in ANSYS Explicit Dynamics were validated against these experiments, confirming the observed behavior and enabling the extension of our analysis to broader concrete strength ranges. Overall, the results demonstrate that double-ended adhesive anchorage significantly increases the connection’s load-bearing capacity and ductility compared to mixed configurations. Full article

This study proposes methods of computer simulation to study and optimize the cybersecurity of Small Modular Nuclear Reactors (SMRs). SMRs hold the potential to help build a clean and sustainable power grid but will struggle to gain widespread adoption without public confidence in their security. SMRs are emerging technologies and potentially carry higher cyber threats due to remote operations, large numbers of cyber-physical systems, and cyber connections with other industrial concerns. A method of agent-based computer simulations to model the effects, or payoff, of collaboration between cyber defenders, power plants, and cybersecurity vendors is proposed to strengthen SMR cybersecurity as these new power generators enter into the market. The agent-based model presented in this research is intended to illustrate the potential of using simulation to model a payoff function for collaborative efforts between stakeholders. Employing simulation to heighten cybersecurity will help to safely leverage the potential of SMRs in a modern and low-emission energy grid. Full article

Wood is a renewable, carbon-sequestering, and structurally versatile material that has supported human civilization for millennia and continues to play a central role in advancing sustainable development. Although its low density, high specific strength, and esthetic appeal make it highly attractive, its intrinsic flammability presents significant challenges for safety-critical uses. This review offers a comprehensive analysis that uniquely integrates three key domains, covering advanced processing technologies, flame-retardant functionalization strategies, and multifunctional applications. Clear connections are drawn between processing approaches such as delignification, densification, and nanocellulose extraction and their substantial influence on improving flame-retardant performance. The review systematically explores how these engineered wood substrates enable more effective fire-resistant systems, including eco-friendly impregnation methods, surface engineering techniques, and bio-based hybrid systems. It further illustrates how combining processing and functionalization strategies allows for multifunctional applications in architecture, transportation, electronics, and energy devices where safety, durability, and sustainability are essential. Future research directions are identified with a focus on creating scalable, cost-effective, and environmentally compatible wood-based materials, positioning engineered wood as a next-generation high-performance material that successfully balances structural functionality, fire safety, and multifunctionality. Full article

We propose a comprehensive literature review based on big data and V2X research to find promising tools to detect vehicles for traffic research and provide safe autonomous vehicle (AV) traffic. Presented data sources can provide real-time data for V2X systems and offline databases from VATnets for micro- and macro-modeling in traffic research. The authors want to present a set of sources that are not based on GNSS and other systems that could be interrupted by high-rise buildings and dense smart city infrastructure, as well as review of big data sources in traffic modeling that can be useful in future traffic research. Both reviews findings are summarized in tables at the end of the review sections of the paper. The authors added propositions in the form of two hypotheses on how traffic models can obtain data in the urban canyon connected environment scenario. The first hypothesis uses Roadside Units (RSUs) to retrieve data in similar ways to cellular data in traffic research and proves that this source is data rich. The second one acknowledges Bluetooth/Wi-Fi scanners’ research potential in V2X environments. Full article

Topological signal processing is emerging alongside Graph Signal Processing (GSP) in various applications, incorporating higher-order connectivity structures—such as faces—in addition to nodes and edges, for enriched connectivity modeling. Rich point clouds acquired by multi-camera systems in Visual Simultaneous Localization and Mapping (V-SLAM) are typically processed using graph-based methods. In this work, we introduce a topological signal processing (TSP) framework that integrates texture information extracted from V-SLAM; we refer to this framework as TSP-SLAM. We show how TSP-SLAM enables the extension of graph-based point cloud processing to more advanced topological signal processing techniques. We demonstrate, on real stereo data, that TSP-SLAM enables a richer point cloud representation by associating signals not only with vertices but also with edges and faces of the mesh computed from the point cloud. Numerical results show that TSP-SLAM supports the design of topological filtering algorithms by exploiting the mapping between the 3D mesh faces, edges and vertices and their 2D image projections. These findings confirm the potential of TSP-SLAM for topological signal processing of point cloud data acquired in challenging V-SLAM environments. Full article

Finding the causative mutations for musculoskeletal system development and health status is of a higher priority for all sport horse breeders’ associations. Of the regulating proteins involved in animal ossification, 15 gene polymorphisms were chosen to be identified as connected with the nine fetlock and 14 hock bone structures measurements of 198 horses. All measurements were taken using X-rays of the limbs, which were available at the beginning and end of the horse training. The analysis of variance (GLM, SAS program) was performed taking into account identified training and horse-connected characteristics, and gene polymorphism. The larger size of the bone structure was achieved in the fetlock for the heterozygotes of COL9A2, AOAH1, BMPER, HYAL3, and ELMO1. The heterozygotes were superior to homozygotes in the hock for the following genes: COL9A2, HYAL3, ANLN, and HYAL1. The lower homozygote values were obtained for GG in CPVL in fetlock measurements, TT for HYAL3 in fetlock, TT for ANLN in fetlock, CC for FRZB in the hock, TT for MATN in the hock, and TT for COL5A2 in the hock than their opposite homozygote and heterozygote variants. COL9A2 and HYAL3 are expressed in the same way for most of the bone structures in both joints. 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

Multi-agent systems (MAS) typically model interaction topologies using directed or undirected graphs when analyzing consensus convergence rates. However, as system complexity increases, purely directed or undirected networks may be insufficient to capture interaction heterogeneity. This paper adopts hybrid networks as interaction topology to investigate strategies for improving consensus convergence rates. We propose the Hermitian Kirchhoff index, a novel metric based on resistance distance, to quantify the consensus convergence rates and establish its theoretical justification. We then examine how adding or removing edges/arcs affects the Hermitian Kirchhoff index, employing first-order eigenvalue perturbation analysis to relate these changes to algebraic connectivity and its associated eigenvectors. Numerical simulations corroborate the theoretical findings and demonstrate the effectiveness of the proposed approach. Full article

Background: The implant–abutment interface has been thoroughly examined due to its impact on the success of implant healing and longevity. Removing the abutment is advantageous, but it changes the biomechanics of the implant fixture and restoration. This in vitro three-dimensional finite element analytical (FEA) study aims to evaluate the distribution of von Mises stress (VMS) in abutment-free and three additional implant abutment connections composed of various titanium alloys. Materials and methods: A three-dimensional implant-supported single-crown prosthesis model was digitally generated on the mandibular section using a combination of microcomputed tomography imaging (microCT), a computer-assisted designing (CAD) program (SolidWorks), Analysis of Systems (ANSYS), and a 3D digital scan (Visual Computing Lab). Four digital models [A (BioHorizons), B (Straumann AG), C abutment-free (Matrix), and D (TRI)] representing three different functional biomaterials [wrought Ti-6Al-4Va ELI, Roxolid (85% Ti, 15% Zr), and Ti-6Al-4V ELI] were subjected to simulated static/cyclic static loading in axial/oblique directions after being restored with highly translucent monolithic zirconia restoration. The stresses generated on the implant fixture, abutment, crown, screw, cortical, and cancellous bones were measured. Results: The highest VMSs were generated by the abutment-free (Model C, Matrix) implant system on the implant fixture [static (32.36 Mpa), cyclic static (83.34 Mpa)], screw [static (16.85 Mpa), cyclic static (30.33 Mpa), oblique (57.46 Mpa)], and cortical bone [static (26.55), cyclic static (108.99 Mpa), oblique (47.8 Mpa)]. The lowest VMSs in the implant fixture, abutment, screw, and crown were associated with the binary alloy Roxolid [83–87% Ti and 13–17% Zr]. Conclusions: Abutment-free implant systems generate twice the stress on cortical bone than other abutment implant systems while producing the highest stresses on the fixture and screw, therefore demanding further clinical investigations. Roxolid, a binary alloy of titanium and zirconia, showed the least overall stresses in different loadings and directions. Full article

Environmental vibrations may affect the functional use of engineering structures and even lead to disastrous consequences. Vibration suppression and energy harvesting based on Nonlinear Energy Sink (NES) and the piezoelectric effect have gained significant attention in recent years. The harvested electrical energy can supply power to the structural health monitoring sensor device. In this work, the electromechanical-coupled governing equations of the primary structure coupled with the series-connected 2-degree-of-freedom NES (2-DOF NES) integrated by a piezoelectric energy harvester are derived. The absorption and dissipation performances of the system under varying transient excitation intensities are investigated. Additionally, the targeted energy transfer mechanism between the primary structure and the two NESs oscillators is investigated using the wavelet analysis. The reduced slow flow of the dynamical system is explored through the complex-variable averaging method, and the primary factors for triggering the target energy transfer phenomenon are revealed. Furthermore, a comparison is made between the vibration suppression performance of the single-degree-of-freedom NES (S-DOF NES) system and the 2-DOF NES system as a function of external excitation velocity. The results indicate that the vibration suppression performance of the first-level NES (NES1) oscillator is first stimulated. As the external excitation intensity gradually increases, the vibration suppression performance of the second-level NES (NES2) oscillator is also triggered. The 1:1:1, high-frequency, and low-frequency transient resonance captures are observed between the primary structure and NES1 and NES2 oscillators over a wide frequency range. The 2-DOF NES demonstrates superior efficiency in suppressing vibrations of the primary structure and exhibits enhanced robustness to varying external excitation intensities. This provides a new strategy for structural vibration suppression and online power supply for health monitoring devices. Full article

Erosion monitoring was carried out between 2003 and 2022 using a hydrological station with a Thomson overflow, a water gauge, and a limnigraph installed at the outlet of the Kolonia Celejów gully system. The study area is located in the north-western part of the Lublin Upland in the Nałęczów Plateau mesoregion (SE Poland). The total amount and intensity of precipitation were measured using an automatic station and water runoff and suspended sediment yield (SST) were also continuously measured. High variability in water runoff was observed during this period (max. of about 76,000 m³ and mean > 26,000 m³), and as a result of numerous heavy rains, a significant increase in SST (max. of about 95 Mg to about 1200 Mg and mean of 24 Mg to about 215 Mg) was noted in the second half of the measurement period. Most of the material removed at that time came from the cutting of the gully bottom and from the redeposition of material transported from the catchment used for agricultural purposes. In order to determine the volume of material delivered to the slope–gully cascade system in November 2012, a second station was installed at the gully head, which only operated until June 2013. However, the measurements covered all snowmelts and summer runoffs, as well as the June downpours. At the same time, these measurements represent the first unique attempt to quantify the delivery of material from the slope subcatchment to the gully system. The year 2013 was also important in terms of water runoff from the loess gully catchment area (about 40,000 m³) and was a record year (SST > 1197 Mg) for the total amount of suspended material runoff (7.6% and 33.5% of the 20-year total, respectively). During the cool half of the year, 16,490 m³ of water (i.e., 42% of the annual total) flowed out of the gully catchment area, and during the warm half of the year, 23,742 m³ of water (59% of the annual total) flowed out. In contrast, 24,076.7 m³ of water flowed out of the slope subcatchment area during the year, with slightly more flowing out in the cool half of the year (12,395.9 m³ or 51.5% of the annual total). In the slope and gully subcatchment areas, the suspended sediment discharge clearly dominated in the warm half of the year (98% and 97%). The record-breaking SST amount in June was over 1100 Mg of suspended sediment, which accounted for 93% of the annual SST from the gully catchment area and over 94% in the case of the slope subcatchment area. The relationships in the slope–gully cascade system in 2013 were considered representative of the entire measurement series, which were used to determine the degree of connectivity between the slope and gully subsystems. During summer downpours, the delivery of slope material from agricultural fields accounted for approx. 15% of the material removed from the catchment area, which confirms the predominance of transverse transport in the slope catchment area and longitudinal transport in the gully. The opposite situation occurs during thaws, with as much as 90% of the material removed coming from the slope catchment area. At that time, longitudinal transport dominates on the slope and transverse transport dominates in the gully. Full article

The paper presents some design principles of an inductive displacement transducer for measuring the displacement of rock specimens under high hydrostatic pressure. It consists of a single-layer, coreless solenoid mounted directly onto the specimen and connected to an LC oscillator located outside the pressure chamber, in which it serves as the inductive component. The specimen’s deformation changes the coil’s length and inductance, thereby altering the oscillator’s resonant frequency. Paired with a reference coil, the system achieves strain resolution of ~100 nm at pressures exceeding 400 MPa. Sensor design challenges include both electrical parameters (inductance and resistance of the sensor, capacitance of the resonant circuit) and mechanical parameters (number and diameter of coil turns, their positional stability, wire diameter). The basic requirement is to achieve stable oscillations (i.e., a high Q-factor of the resonant circuit) while maintaining maximum sensor sensitivity. Miniaturization of the sensor and minimizing the tensile force at its mounting points on the specimen are also essential. Improvement of certain sensor parameters often leads to the degradation of others; therefore, the design requires a compromise depending on the specific measurement conditions. This article presents the mathematical interdependencies among key sensor parameters, facilitating optimized sensor design. Full article