Search Results (29,223)

The Controller Area Network (CAN) remains the backbone of in-vehicle communication, but its lack of built-in security exposes safety-critical systems to cyberattacks. This paper presents a real-time, reconfigurable, specification-driven intrusion detection system (IDS) implemented on a custom test bench that emulates an EV powertrain. The CAN traffic captured from the four-ECU setup formed the dataset used in this study. The IDS enforces a compact, reconfigurable ruleset covering timing bounds, jitter envelopes, identifier whitelists, frame format, data length code (DLC) compliance, bus-load thresholds, application-level CRC, and alive-counter verification. The IDS achieves detection times below 2 ms with false positive rates under 1% for injection, denial of service (DoS), and fuzzy attacks, even at CAN bus loads up to 70%, while microcontroller resource usage remains within the constraints of automotive-grade devices, supporting deployment in embedded environments. The main contributions of this study are as follows: (i) a validated and reproducible EV powertrain test bench with millisecond-level timing, (ii) a deployable and easily reconfigurable ruleset with deterministic runtime, and (iii) a latency-oriented evaluation framework that is portable across automotive microcontroller platforms. The EV powertrain dataset v1.0 was released in a public GitHub repository to facilitate reproducible research and enable future benchmarking studies. Full article

Hydrogen-enriched fuel injection in staged gas-turbine combustors is commonly achieved through jet-in-crossflow (JICF) configurations, where flame stabilization is governed by a local balance between flow-induced strain/mixing and chemical reaction rates. This work investigates turbulent reacting JICF relevant to staged combustion conditions using high-fidelity simulations with adaptive mesh refinement (AMR) and differential-diffusion effects together with Lagrangian particle statistics. Chemistry model uncertainties are incorporated by using a projection method that maps uncertainty estimates from detailed mechanisms into the model used in this work. Results show that the macroscopic flame topology remains in a stable two-branch regime (lee-stabilized and lifted) and is primarily controlled by the jet momentum–flux ratio J. Visualization of the normalized scalar dissipation rate reveals that the flame front resides on the low-dissipation side of intense mixing layers, occupying an intermediate region between over-strained and under-mixed regions. While hydrogen content does not significantly change the global stabilization mode for the cases studied, uncertainty analysis reveals composition-dependent differences that are not apparent in the mean behavior alone. In particular, visualization in Eulerian (χ, T) state-space analysis and particle statistics conditioned on the stoichiometric surface demonstrate that higher-hydrogen cases observe a lower scalar dissipation rate and exhibit substantially reduced variability in OH production under kinetic-parameter perturbations, whereas lower-hydrogen blends experience higher dissipation and amplified chemical sensitivity. These findings highlight that, even in globally similar JICF regimes, the hydrogen content can modify the local response of the flame to kinetic-parameter uncertainty, motivating uncertainty-aware interpretation and design for hydrogen-fueled staging systems. Full article

Semiconductor lasers have been widely employed in chaos-based information processing due to their ability to generate enhanced chaotic bandwidths. In this study, we investigate broadband polarization chaos in optically injected QD spin-VCSELs and their ability to act as high-speed physical entropy sources for random number generation (RNG). We achieve chaotic bandwidths approaching 50 GHz per polarization mode using elliptical injection. With optimized conditions and post-processing, we demonstrate RNG at rates of up to 240 Gb/s. The quality of the generated random sequences is evaluated using multiple statistical metrics, including entropy estimation based on the NIST SP800-90B framework, uniqueness analysis using Hamming distance, and bias assessment through autocorrelation and histogram analysis. In addition, the influence of different polarization injection schemes on randomness is examined using the NIST SP800-22 statistical test suite. These results highlight the potential of QD spin-VCSELs as compact and ultrafast sources for RNG in secure communication systems. Full article

The widespread integration of wind energy conversion systems has fundamentally reshaped modern power grid architecture. However, the limited dynamic response of wind turbine (WT) converters during grid faults—particularly their inability to provide sufficient reactive current and maintain voltage stability under severe dips—necessitates a redefinition of the conventional low-voltage ride-through (LVRT) curve. This study addresses this challenge by proposing a Mutation-Adaptive Mean Variance Mapping Optimization (A-MVMO) algorithm for the control of grid-side converters (GSCs) in wind farms (WFs). To systematically assess post-fault voltage recovery, a Time-Segmented Analysis for Voltage Recovery (T-SAVR) approach is developed with a multi-objective function. The performance of the proposed A-MVMO is benchmarked against standard MVMO and conventional particle swarm optimization (PSO) under both moderate (0.7 pu) and severe (0.15 pu) voltage dips using the IEEE 39-bus system implemented in DIgSILENT/PowerFactory. The results demonstrate that A-MVMO achieves fast, oscillation-free voltage recovery with negligible overshoot (<1%) and lower current injection than PSO and MVMO, while satisfying all engineering constraints. Moreover, the co-optimization of Park-level and turbine-level controllers ensures seamless coordination, as evidenced by the close tracking between the farm-wide reactive power reference and the aggregated turbine response. The T-SAVR method proves essential for focusing optimization on controllable recovery dynamics, yielding a superior LVRT curve. Full article

Natural gas reservoirs characterized by high heterogeneity and containing bottom-bound water often face the problem of water intrusion, making it difficult to recover the recoverable gas. This paper addresses the issue of enhanced gas recovery in water-flooded reservoirs and, through high-temperature, high-pressure long-core displacement experiments, investigates the displacement effects of different reservoir properties and injection media (dry gas, N₂, CO₂) under simulated water-flooding conditions. The experiment utilized two sets of sandstone cores—one with moderate permeability (304.8 mD) and one with high permeability (1004.6 mD). Three cores from each set were spliced together to form a 0.9 m long core, simulating the gas injection and displacement process following water infiltration. The results indicate that while water intrusion occurs more rapidly in high-permeability reservoirs, gas injection yields better recovery results than in medium-permeability reservoirs. Among the three injection media, dry gas demonstrated the best displacement efficiency, followed by N₂, with CO₂ performing the worst. CO₂ tends to react with highly mineralized formation water under high-temperature and high-pressure conditions, forming precipitates and causing energy to be absorbed by the water, which reduces displacement efficiency. It is recommended that dry gas injection be used for enhanced recovery in the moderate-permeability reservoirs of the Y gas field, while N₂ injection may be considered for the high-permeability reservoirs to balance effectiveness and cost. The research results provide experimental support for subsequent gas injection to enhance gas recovery in this gas field. Full article

The paramount value of image fusion is manifested in effectively enhancing downstream tasks. However, compatibility with subsequent tasks is compromised due to the semantic deficiency of fusion representations generated by current approaches. To mitigate this limitation, a semantic-guided multi-level collaborative fusion network is proposed, termed DSIFuse. By leveraging semantic priors and global context extracted from auxiliary segmentation branches, a multi-level interaction space is constructed to explicitly refine cross-modal features. Specifically, a cross-modal feature correction mechanism is designed to enhance semantic alignment by injecting complementary visible–infrared information at each layer, while a three-level interaction strategy gradually integrates unimodal features and semantic maps to generate semantically enriched representations. To mitigate semantic information loss during image reconstruction, a semantic compensation block is employed, incorporating interactive representations from prior layers and global semantic maps into the multi-scale decoder. Finally, the overall loss integrates semantic supervision, gradient, and intensity loss. Experiments conducted on public datasets indicate that clear fusion images are generated by DSIFuse, with improved structural consistency and reduced artifacts. Under a unified benchmark, the fused representations subsequently yield improved performance in downstream object detection tasks. Full article

Background/Objectives: It is challenging to develop efficient vaccines against intracellular pathogens such as viruses, and since viral infections are one of the main challenges for farmed salmon, a novel vaccine strategy is needed. mRNA vaccines are optimized and approved for humans, but for fish, the mRNA technology is new, and optimization is required to ensure efficient protein expression. We made an mRNA tailored to salmon and studied the effect of modified nucleosides and the length of the poly(A) tail on protein expression from in vitro-transcribed mRNA in CHSE-214 cells, using enhanced green fluorescent protein (EGFP) as a reporter. Methods: Different lengths of the poly(A) tail were tested, and various modified nucleotides were incorporated in the mRNA during in vitro transcription, including pseudouridine (Ψ), N1-methylpseudouridine (m1Ψ), N6-methyladenosine (m6A), 5-methyluridine (m5U), and 5-methylcytidine (m5C). Protein expression was observed in fluorescence microscopy and quantified using flow cytometry. Results: mRNA containing Ψ resulted in the strongest EGFP expression 1–3 days post-transfection (dpt), while EGFP expression from m5C mRNA was high throughout the experiment (<10 dpt). m5U-containing mRNA had low EGFP expression until 6 dpt, but reached the level of m5C mRNA at 10 dpt. The m5U mRNA, however, expressed EGFP at much higher intensity than all the other mRNAs at all time points. Poly(A) tails with lengths of 40, 100, and >100 were tested, and the one with >100 adenines showed the highest expression. The effects of phosphatase treatment and purification of the mRNA were also investigated. Furthermore, EGFP expression was observed in yolk-sac salmon larvae following micro-injection. Conclusions: Our study provides an important basis for the development of efficient mRNA-based vaccines in the future. Full article

All-optical logic gates have emerged as a critical technology for enabling broadband, low-loss, and high-speed communication systems, addressing the inherent bandwidth limitations of electronic counterparts. Here, we propose a Y-shaped structure leveraging unidirectional modes in the terahertz regime, which enables the realization of multifunctional all-optical logic gates within the lower- and upper-frequency bandwidth regions, including, but not limited to, AND, OR, NOT, and XNOR gates. Numerical simulations and theoretical analyses confirm that the proposed logic gates exhibit robust one-way propagation characteristics, with electromagnetic signals demonstrating complete immunity to backscattering even in the presence of structural defects. Furthermore, nonlocal effects are found to have a negligible impact on the operational bandwidths of our design. Building upon this Y-shaped configuration, we further develop an all-optical digital logic system (AODLS) capable of supporting bifrequency multi-input and multi-output logic operations. When lower- and upper-frequency signals are injected into separate input ports, their corresponding output signals remain fully independent, eliminating cross-talk and enabling true parallel computation. This dual-band parallel processing capability represents a significant advance over conventional single-band all-optical logic systems, opening new avenues for high-throughput all-optical computing and integrated photonic circuits. Full article

This work presents an experimental aerodynamic study of a Mars rover model, aimed at characterizing its flow behavior under Martian environmental conditions. Due to the extremely low Reynolds numbers associated with Mars’ thin atmosphere, the experiments were conducted using a scaled model of the rover manufactured via additive techniques. The study first focuses on understanding how the geometry of the rover influences the overall flow field, identifying key aerodynamic features such as separation zones, vortical structures, and flow reattachment regions driven by the complexity of the vehicle. A comprehensive investigation of the flow around the model was performed using both a hydrodynamic towing tank with dye injection for qualitative visualization, and particle image velocimetry (PIV) for quantitative flow field analysis in wind tunnel tests. After the general flow characterization, a more detailed local analysis was conducted using laser Doppler anemometry (LDA). This phase of the study targeted precise velocity measurements at specific locations corresponding to the MEDA (Mars Environmental Dynamics Analyzer) wind sensors onboard the rover. Quantitative results indicate that the central body induces a local flow acceleration of 20% to 40% relative to the free stream while severe turbulence was recorded in specific angular sectors, with velocity fluctuations reaching up to 120% for Sensor 1 and 90% for Sensor 2. Full article

This research presents a two-dimensional transient thermo-hydraulic model designed to study how temperature and pressure change within a wellbore during CO₂ tubing fracturing. The model integrates one-dimensional axial compressible flow with radial heat transfer across the tubing, annulus, casing, cement sheath, and surrounding geological formation. Using the predicted temperature and pressure distributions, the phase behavior of the fracturing fluid along the wellbore is assessed. To enhance the accuracy of phase predictions, a visualization experiment is performed on a CO₂-based fracturing fluid containing 5 wt% of the thickener HPG. The critical transition conditions obtained experimentally are used to adjust the model accordingly. The study systematically examines the influence of key operational parameters such as injection rate, wellhead pressure, injection temperature, and the geothermal gradient of the formation. Findings reveal that injection conditions mainly govern the temperature and velocity fields, while heat transfer from the formation has a lesser impact during short-term injections. Pressure steadily decreases along the wellbore due to friction and fluid compressibility. A method based on density gradients is introduced to determine the depth at which phase transitions occur. Overall, this work offers a practical approach for predicting thermo-hydraulic behavior and phase changes during CO₂ fracturing processes. Full article

The delineation of the Area of Review (AoR) is a fundamental requirement for Class VI carbon storage permits in the United States. The regulatory definition of the pressure front relies on the potential for injected fluids or formation brine to migrate into an Underground Source of Drinking Water (USDW). However, in deep sedimentary basins such as the Texas Gulf Coast and offshore regions, targeted saline formations often lack overlying USDWs. In these scenarios, traditional methods for calculating the critical pressure threshold become mathematically undefined or yield infinite AoR boundaries. This paper proposes a practical, geomechanics-based methodology for defining the pressure front in the absence of a USDW, framed as an alternative site-specific approach under the authority of the UIC Program Director (40 CFR 146.84). By leveraging existing regulatory limits on injection pressure, the proposed framework establishes a threshold based on the minimum horizontal stress, caprock fracture pressure, and fault reactivation limits via Mohr–Coulomb failure analysis. The framework further incorporates capillary breakthrough pressure as a third containment threshold, ensuring that the most restrictive condition governs the AoR boundary. A synthetic case study of a deep Gulf Coast saline formation demonstrates that this approach produces a finite, physically meaningful AoR that scales appropriately with injection operations (evaluated at 1.0 and 2.0 Mt/yr) and captures post-injection pressure evolution during the Post-Injection Site Care (PISC) period. Sensitivity analyses on permeability and fracture gradients confirm the robustness of the method. The study also examines model limitations, injection feasibility boundaries, and extensions toward a probabilistic framework. This framework provides operators and regulators with a defensible, regulatory-consistent pathway for advancing carbon storage projects in deep sedimentary basins, complete with a standardized reviewer checklist and an example AoR delineation report template. Full article

As 5G Standalone Core networks grow, Application Programming Interface (APIs) have become a key part of how network systems talk to each other. They allow different functions to share data and complete tasks quickly. However, this also makes them targets for attacks. 5G Standalone Core networks rely on Service-Based Architecture (SBA), where network functions communicate through exposed APIs. These APIs are attractive targets for cyberattacks because they are externally accessible, handle sensitive control-plane operations, and exchange structured data using Hypertext Transfer Protocol version 2 (HTTP/2) and JavaScript Object Notation (JSON) protocols. Most older security tools work using fixed rules, which cannot always detect new or changing threats. This study aimed to fix that gap by using Artificial Intelligence to make API security smarter. Two AI models were tested: Long Short-Term Memory (LSTM), which learns from past traffic and Reinforcement Learning (RL), which learns by adapting to network behavior. Both were used to assess API traffic and assign a real-time risk score. Synthetic traffic was created using Python, including both normal API calls and different types of attacks like Distributed Denial-of-Service (DDoS), brute force, and Structured Query Language (SQL) injection. The results show that both LSTM and RL models were better than traditional rule-based systems. They found more threats, gave fewer false alerts, and responded faster. RL was especially strong at handling unknown or changing attacks. Experimental results show that the proposed LSTM and RL models achieved approximately 95% detection accuracy, significantly outperforming the static rule-based baseline model, which achieved 58% accuracy. The results demonstrate the effectiveness of adaptive AI-based security mechanisms for detecting evolving API threats. This research shows that AI can help protect 5G APIs in a smarter and more flexible way. It can support telecom networks by making threat detection faster, more accurate, and ready for future challenges. Full article

In spite of the importance of a detailed description of the filamentary current constriction of the IGBT during the turn-off operation that could lead to the device’s failure, there are to date no quantitative 3D simulation results of the filament growth and dynamic that can be compared with experimental results. In this paper we present 3D numerical simulations on the failure mode in the Unclamped Inductance Switching (UIS) test operation, extended to the full device area, which will be usefully compared with detailed experimental results on a large number of trench IGBT test samples. For the first time extended 3D dynamic electrothermal simulations of the whole die are made, to take into account both the electric and thermal effects of the filamentary conduction in avalanche mode. The onset of a filament growth condition for a current level just above the turnover voltage evaluated by the 3D simulations, and the area of the filament, obtained for the first time, are well in agreement with the quantitative data extracted by the experimental evaluations. Moreover, the thermal heating due to the filament formation is found to be quite independent from the current level, because it depends on the current density in the filament, rather than on the injected current. The delay time between the filament formation and the final failure time seen in the experimental results is verified to be due to the movement of the filament all around the chip surface in search of a cooler spot. The movement of the filament along the whole die area is verified for the first time by full area 3D electrothermal dynamic simulations, with times in agreement with the experimental delay between filament formation and final failure seen in all the failure reports. Full article

Background: With the increasing demand for non-surgical facial rejuvenation, injectable collagen biostimulators such as poly-L-lactic acid (PLLA), calcium hydroxyapatite (CaHA), polycaprolactone (PCL), poly-D,L-lactic acid (PDLLA) and powdered polydioxanone (PPDO) have become widely used by facial aesthetic practitioners. These agents stimulate neocollagenesis, providing gradual improvement in skin firmness, elasticity and facial contour with long-lasting results. While manufacturers emphasize the efficacy and favorable safety profile of these products, adverse events such as nodules, edema, inflammatory reactions and, in rare cases, granulomas have been reported. To date, no comprehensive systematic review has evaluated the proportion and nature of adverse effects associated with all major collagen biostimulators in facial aesthetic procedures. This study aims to synthesize current evidence on the proportion of adverse events linked to injectable collagen biostimulators. Methods: The systematic review will include clinical studies involving adults undergoing facial aesthetic procedures with PLLA, PDLLA, CaHA, PCL and PPDO that report adverse events during or after treatment. The search will be conducted in six main databases: CENTRAL, EMBASE, LILACS, PubMed, SCOPUS and Web of Science. No restrictions will be applied regarding language or publication date. The screening process will occur in two phases: first, two independent reviewers will assess titles and abstracts against the eligibility criteria; second, the same reviewers will conduct full-text evaluations. Data will be synthesized narratively, with a meta-analysis of proportions performed if appropriate. Additionally, sample characteristics, treatment protocols, study design and main findings will be reported. The risk of bias will be assessed independently by two reviewers using appropriate tools, based on the study design, with the support of artificial intelligence. PROSPERO registration number: CRD420251062785. Full article

Surface roughness and mechanical performance are critical determinants of the clinical behavior, hygiene, and longevity of denture base materials. This study investigated the influence of two extrusion temperatures—280 °C and 300 °C—on both the surface roughness and compressive strength of ThermoSens thermoplastic polymer specimens over a 7-day immersion period. Surface roughness was evaluated at baseline, 24 h, and 7 days using a contact profilometer, while compressive strength was measured after 7 days following ISO 604 guidelines. Samples processed at 300 °C exhibited a significantly greater reduction in surface roughness over time (28.3%) compared with those processed at 280 °C (18.3%). However, although specimens processed at 300 °C showed a greater percentage reduction, their absolute roughness values remained higher than those processed at 280 °C. Compression testing demonstrated higher strength and modulus values in the 300 °C group (91.6 ± 1.8 MPa; 1887.9 ± 42.3 MPa) compared to the 280 °C group (82.3 ± 2.1 MPa; 1755.4 ± 38.7 MPa). These findings indicate a trade-off between improved mechanical performance at higher processing temperatures and lower surface roughness at lower temperatures, highlighting the need for the careful optimization of processing conditions. Full article