Search Results (2,028)

Wireless Sensor Networks (WSNs) consist of numerous battery-powered sensor nodes that operate with limited energy, computation, and communication capabilities. Designing routing strategies that are both energy-efficient and attack-resilient is essential for extending network lifetime and ensuring secure data delivery. This paper proposes Adaptive Federated Reinforcement Learning-Hunger Games Search (AFRL-HGS), a Hybrid Routing framework that integrates multiple advanced techniques. At the node level, tabular Q-learning enables each sensor node to act as a reinforcement learning agent, making next-hop decisions based on discretized state features such as residual energy, distance to sink, congestion, path quality, and security. At the network level, Federated Reinforcement Learning (FRL) allows the sink node to aggregate local Q-tables using adaptive, energy- and performance-weighted contributions, with Polyak-based blending to preserve stability. The binary Hunger Games Search (HGS) metaheuristic initializes Cluster Head (CH) selection and routing, providing a well-structured topology that accelerates convergence. Security is enforced as a constraint through a lightweight trust and anomaly detection module, which fuses reliability estimates with residual-based anomaly detection using Exponentially Weighted Moving Average (EWMA) on Round-Trip Time (RTT) and loss metrics. The framework further incorporates energy-accounted control plane operations with dual-format HELLO and hierarchical ADVERTISE/Service-ADVERTISE (SrvADVERTISE) messages to maintain the routing tables. Evaluation is performed in a hybrid testbed using the Graphical Network Simulator-3 (GNS3) for large-scale simulation and Kali Linux for live adversarial traffic injection, ensuring both reproducibility and realism. The proposed AFRL-HGS framework offers a scalable, secure, and energy-efficient routing solution for next-generation WSN deployments. Full article

In Hungary, on-site mixed stabilization of cohesive soil is considered only as soil improvement not a proper pavement layer, therefore its bearing capacity is not taken into account when designing pavement. It was our hypothesis that on low-volume roads built on cohesive soil, lime or lime–cement stabilization can be an alternative to granular base layers. A case study was conducted to obtain initial results and to verify the research methodology. The efficacy of lime stabilization was evaluated across eight experimental road sections, with a view of assessing its structural and economic performance in comparison with crushed stone base layers reinforced with geo-synthetics. The results of the testing demonstrated elastic moduli of 120–180 MPa for the lime-stabilized layers, which closely matched the 200–280 MPa range observed for the crushed stone bases. The results demonstrated that lime stabilization offers a comparable load-bearing capacity while being the most cost-effective solution. Furthermore, this approach enhances sustainability by enabling the utilization of local soils, reducing reliance on imported materials, minimizing transport-related costs, and lowering carbon emissions. Lime stabilization provides a durable, environmentally friendly alternative for road construction, effectively addressing the challenges of material scarcity and rising construction costs while supporting infrastructure resilience. The findings highlight its potential to replace traditional base layers without compromising structural performance or economic viability. Full article

Effective production control requires aligning strategic planning with real-time execution under dynamic and stochastic conditions. This study proposes a scalable dual-agent Deep Reinforcement Learning (DRL) framework for the joint optimisation of Work-In-Process (WIP) control and job sequencing in flow-shop environments. A strategic DQN agent regulates global WIP to meet throughput targets, while a tactical DQN agent adaptively selects dispatching rules at the machine level on an event-driven basis. Parameter sharing in the tactical agent ensures inherent scalability, overcoming the combinatorial complexity of multi-machine scheduling. The agents coordinate indirectly via a shared simulation environment, learning to balance global stability with local responsiveness. The framework is validated through a discrete-event simulation integrating agent-based modelling, demonstrating consistent performance across multiple production scales (5–15 machines) and process time variabilities. Results show that the approach matches or surpasses analytical benchmarks and outperforms static rule-based strategies, highlighting its robustness, adaptability, and potential as a foundation for future Hierarchical Reinforcement Learning applications in manufacturing. Full article

This paper presents the development of a high-resolution composite index to monitor and quantify climate-related risks across Italy. The country’s complex climatic variability, extensive coastline, and low insurance penetration highlight the urgent need for robust, locally calibrated tools to bridge the climate protection gap. Building on the methodological framework of existing actuarial climate indices, previously adapted for France and the Iberian Peninsula, the index integrates six standardised indicators capturing warm and cool temperature extremes, heavy precipitation intensity, dry spell duration, high wind frequency, and sea level change. It leverages hourly ERA5-Land reanalysis data and monthly sea level observations from tide gauges. Results show a clear upward trend in climate anomalies, with regional and seasonal differentiation. Among all components, sea level is most strongly correlated with the composite index, underscoring Italy’s vulnerability to marine-related risks. Comparative analysis with European indices confirms both the robustness and specificity of the Italian exposure profile, reinforcing the need for tailored risk metrics. The index can support innovative risk transfer mechanisms, including climate-related insurance, regulatory stress testing, and resilience planning. Combining scientific rigour with operational relevance, it offers a consistent, transparent, and policy-relevant tool for managing climate risk in Italy and contributing to harmonised European frameworks. Full article

Brucellosis remains an underreported zoonotic disease in Ecuador. Its control program in cattle integrates diagnostic testing, vaccination, and eradication incentives, although participation is largely voluntary. Since 2025, vaccination has become compulsory nationwide. Human surveillance remains largely passive, and strain-level data are very limited. This study applied an integrated approach, combining serology (Rose Bengal and SAT-EDTA), microbiological culture, and molecular diagnostics, to assess the presence and diversity of Brucella spp. in cattle and pigs from six slaughterhouses in the northern Andean highlands. A total of 2054 cattle and 1050 pigs from Carchi, Imbabura, and Pichincha were sampled. Among cattle, 133 (6.5%; 95% CI: 5.5–7.6) were seropositive, and viable B. abortus strains were isolated from 17 (12.8%). Genus identification was confirmed by IS711-PCR, while species- and biovar-level differentiation was achieved with AMOS-PCR; additional assays targeting the ery gene and RB51 marker were used to distinguish field from vaccine strains. Biotyping and molecular analysis revealed a predominance of B. abortus biovar 4 (13/17 isolates) over biovar 1, all confirmed as field strains. In pigs, 10 animals (0.95%) tested seropositive, but no isolates were recovered, highlighting limitations of serology in swine. Most livestock, including the positives, originated locally, reinforcing the representativeness of our findings. The successful isolation and molecular characterization of B. abortus demonstrates the value of combining diagnostic strategies beyond serology. These results underscore the utility of active surveillance when supported by traceability systems; this approach may also contribute to guide interventions to reduce infection risk in livestock and humans. Full article

The demand for higher data rates and energy efficiency in wireless communication systems drives power amplifiers (PAs) into nonlinear operation, causing signal distortions that hinder performance. Digital Pre-Distortion (DPD) addresses these distortions, but existing systems face challenges with complexity, adaptability, and resource limitations. This paper introduces DRL-DPD, a Deep Reinforcement Learning-based solution for DPD that aims to reduce computational burden, improve adaptation to dynamic environments, and minimize resource consumption. To ensure safety and regulatory compliance, we integrate an ad-hoc Safe Reinforcement Learning algorithm, CRE-DDPG (Cautious-Recoverable-Exploration Deep Deterministic Policy Gradient), which prevents ACLR measurements from falling below safety thresholds. Simulations and hardware experiments demonstrate the potential of DRL-DPD with CRE-DDPG to surpass current DPD limitations in both local and remote configurations, paving the way for more efficient communication systems, especially in the context of 5G and beyond. Full article

Water supply networks in both developed and developing major cities worldwide were constructed many years ago. Currently, these systems face numerous challenges, including population growth, climate change, emerging technologies, and the policies implemented by local governments. Such factors can impact the design life of water infrastructure, leading to service pressure deficiencies. Consequently, water infrastructure must be reinforced to ensure an adequate and reliable service. This research presents the development of an analytical formulation for hydraulic installations with a pumping station, enabling the calculation of requirements for a new parallel pipeline within an existing water system without altering the current pipe resistance class. To implement the proposed solution, it is essential to maintain the initial pump head by adjusting the impeller size. A construction cost assessment is also undertaken to identify the most cost-effective reinforcement strategy, acknowledging that pipe costs vary significantly with diameter and material, and are proportional to the square of the diameter. The proposed methodology is applied to a 30 km pipeline with a 10% increase in demand, showing that a new parallel pipe of the same diameter as the existing hydraulic installation must be installed to minimise construction costs. A multi-parametric analysis was conducted employing machine learning presets with 309 dataset points. Full article

Cultural ecosystem services (CES) play a key role in the sustainable development of rural areas—yet they remain poorly quantified in planning practice. This study examines the relationship between the supply and demand of CES provided by various types of Ecological Focus Areas (EFAs) in a rural landscape, using the municipality of Sosnowica (eastern Poland) as a case study. Landscapes such as forests, agricultural land, wetlands, and inland waters were evaluated using a set of biophysical and socio-economic indicators that reflect both their potential (supply) and actual use (demand) in terms of services such as recreation, landscape aesthetics, and cultural heritage. The findings reveal significant spatial disparities between CES supply and demand: forests and inland waters exhibit the highest supply potential, while agricultural land shows untapped opportunities in tourism and recreation. Wetlands, in particular, face notable service deficits—highlighting the need for targeted infrastructure and management interventions. Statistical analyses (Pearson correlation, Kruskal–Wallis test, Tukey HSD test) confirmed that the key factors shaping CES are accessibility and environmental attractiveness. The results indicate that CES mapping is a valuable tool for supporting sustainable rural planning, reinforcing local identity, counteracting depopulation, and stimulating socio-economic development. Full article

Highly Hazardous Pesticides (HHPs) pose severe risks to human health and the environment, making it essential to understand their molecular stability and degradation pathways. In this study, the Quantum Theory of Atoms in Molecules (QTAIM) was applied to four representative organophosphate pesticides, allowing the identification of electronically weak bonds as intrinsic sites of lability. These findings are consistent with reported hydrolytic, oxidative, enzymatic, and microbial degradation routes. Importantly, QTAIM descriptors proved largely insensitive to solvation, confirming their intrinsic character within the molecular electronic structure. To complement QTAIM, conceptual DFT (Density Functional Theory) reactivity indices were analyzed, revealing that solvent effects induce more noticeable variations in global and local descriptors than in topological parameters. In addition, a Topological Analysis of the Fukui Function (TAFF) was performed, which mapped nucleophilic, electrophilic, and radical susceptibilities directly onto QTAIM basins. The TAFF analysis confirmed that bonds identified as weak by QTAIM (notably P–O, P–S, and P–N linkages) also coincide with the most reactive sites, thereby reinforcing their mechanistic role in degradation pathways. This integrated framework highlights the robustness of QTAIM, the sensitivity of global and local reactivity descriptors to solvation revealed by conceptual DFT, and the complementary insights provided by TAFF, contributing to risk assessment, remediation strategies, and the rational design of safer pesticides. Full article

Ply Curving Termination (PCT) is an effective method to suppress stress concentration at composite ply drop-offs by locally curving the reinforcing fibers to reduce the stiffness. A previous study by the authors confirmed that PCT can suppress fatigue delamination failure in composite ply drop-off. However, the specimens used were external ply drop-offs without cover plies and did not reflect practical structural configurations. Following the basic study, this current study evaluated the fatigue damage suppression characteristic of PCT in practically relevant internal ply drop-offs with cover plies. Finite element analysis, fatigue testing, and detailed observation of the failure process using X-ray CT showed that PCT is effective in suppressing fatigue failure of internal ply drop-offs. In particular, delamination propagation from matrix cracks along the curving fibers, a weak point of PCT, is suppressed in the external ply drop-off. Finite element analysis indicated the importance of stress transfer from the cover ply to the ply drop-off, confirming that the fatigue damage suppression effect of PCT is enhanced in practical composite ply drop-off configurations. Full article

As a sustainable construction material, mudbrick can be used widely in areas where common modern construction materials are not easily accessible but high clay content soil is available. The inclusion of locally available natural fibres in mudbrick could improve its mechanical and erosion resistance performance. This study examines the performance of fibre-reinforced mudbrick from spinifex and laterite soil which are abundant in Australia. The main objective of this study is to evaluate the mechanical and durability performance of spinifex fibre-reinforced mudbricks made with Australian laterite soil, focusing on the influence of fibre content, fibre length, and cement stabilisation. Spinifex fibre length (30 mm, 40 mm, 50 mm), spinifex fibre percentage (0.3%, 0.6%, 0.9%), and cement percentage (5% and 10%) are considered as the experiment variables. Results show that compressive strength generally decreases with fibre size. In this regard, specimens with 0.3% spinifex fibre, 40 mm fibre length, and 10% cement, with an average compressive strength value of 4.1 MPa, were found to have the highest strength among all design mixes. The elastic Young’s modulus was highest for the specimens with 0.3% spinifex fibre, 30 mm fibre length, and 10% cement with a 36.1 MPa. A low amount of longer fibres was found to be more effective in reducing water absorption in samples with higher cement content. Water absorption and compressive strength results suggest that, on average, 0.3–0.5% spinifex content of size 30 mm improves both low and high cement content mudbricks properties. Full article

This study proposes an Improved Whale Migration Algorithm (IWMA) to overcome the shortcomings of the original Whale Migration Algorithm, which suffers from premature convergence and insufficient local exploitation in high-dimensional multimodal optimization. IWMA introduces three enhancements: circle chaotic initialization to improve population diversity, a three-layer cooperative search framework to achieve a stronger balance between exploration and exploitation, and a dynamic adaptive mechanism with t-distribution re-exploration to reinforce both global escaping and local refinement. On the CEC2017 benchmark suite, IWMA demonstrates clear superiority over seven representative algorithms, delivering the best results on 27 out of 29 functions by best, 25 by mean, and 23 by standard deviation in 30 dimensions, and on 25, 18, and 18 functions, respectively, in 50 dimensions. Compared with other migration-based optimizers, its average rank improves by more than 30 percent, while runtime analysis shows only a small additional overhead of 7 to 12 percent. These outcomes, supported by convergence curves, boxplots, radar charts, and Wilcoxon tests, confirm the effectiveness of the proposed improvements. In six multi-UAV path planning scenarios, IWMA reduces the average cost by 14.5 percent compared with WMA and achieves up to 32.1 percent reduction in the most complex case. Overall, its average cost decreases by 27.4 percent across seven competitors, with a 23.6 percent improvement in the best solutions. These results demonstrate that the proposed modifications are effective, enabling IWMA to transfer its performance gains from benchmark tests to practical multi-UAV cooperative mission planning, where it consistently produces safer and smoother trajectories under complex constraints. Full article

Background: The human gut microbiome—a diverse ecosystem of trillions of microorganisms—plays an essential role in metabolic, immune, and neurological regulation. However, modern lifestyle factors such as antibiotic overuse, cesarean delivery, reduced breastfeeding, processed and high-sodium diets, alcohol intake, smoking, and exposure to environmental toxins (e.g., glyphosate) significantly reduce microbial diversity. Loss of keystone species like Bifidobacterium infantis (B. infantis) and Lactobacillus reuteri (L. reuteri) contributes to gut dysbiosis, which has been implicated in chronic metabolic, autoimmune, cardiovascular, and neurodegenerative conditions. Materials and Methods: This Qualitative Systematic Review (QualSR) synthesized data from over 547 studies involving human participants and standardized microbiome analysis techniques, including 16S rRNA sequencing and metagenomics. Studies were reviewed for microbial composition, immune and metabolic biomarkers, and clinical outcomes related to microbiome restoration strategies. Results: Multiple cohort studies have consistently reported a 40–60% reduction in microbial diversity among Western populations compared to traditional societies, particularly affecting short-chain fatty acid (SCFA)-producing bacteria. Supplementation with B. infantis is associated with a significant reduction in systemic inflammation—including a 50% decrease in C-reactive protein (CRP) and reduced tumor necrosis factor-alpha (TNF-α) levels—alongside increases in regulatory T cells and anti-inflammatory cytokines interleukin-10 (IL-10) and transforming growth factor-beta 1 (TGF-β1). L. reuteri demonstrates immunomodulatory and neurobehavioral benefits in preclinical models, while both probiotics enhance epithelial barrier integrity in a strain- and context-specific manner. In murine colitis, B. infantis increases ZO-1 expression by ~35%, and L. reuteri improves occludin and claudin-1 localization, suggesting that keystone restoration strengthens barrier function through tight-junction modulation. Conclusions: Together, these findings support keystone species restoration with B. infantis and L. reuteri as a promising adjunctive strategy to reduce systemic inflammation, reinforce gut barrier integrity, and modulate gut–brain axis (GBA) signaling, indicating translational potential in metabolic and neuroimmune disorders. Future research should emphasize personalized microbiome profiling, long-term outcomes, and transgenerational effects of early-life microbial disruption. Full article

The corrosion of welded joints creates widespread issues for the ocean engineering, petrochemical, and nuclear power industries. Geometric discontinuity of the weld reinforcement height plays an important role in weld corrosion, but the mechanism is still unclear. The corrosion behavior of flat and convex SA106B welded joints is investigated at different flow velocities by experiments and simulation. The damage components of the material and geometric discontinuity are quantified. Electrochemical measurements, morphology observations, and flow field simulations are conducted. The results show that the corrosion of the welded joints is influenced by mass transfer and galvanic corrosion. The corrosion of the welded joints is aggravated by geometric discontinuity and increased flow velocity. The damage component introduced by the material of the welded joint decreases with increasing flow velocity, and the maximum value is 91.56% at 0.5 m/s. The damage component introduced by the geometry of the weld reinforcement height increases with increasing flow velocity, reaching up to 45.77% at 6.9 m/s. The corrosion mechanism is also discussed. Full article

The waviness defect, a common manufacturing flaw in composite structures, can significantly impact the mechanical performance. This study investigates the effects of wrinkles on the ultimate load and failure modes of two Carbon Fiber Reinforced Composite (CFRC) laminates through compressive experiments and simulation analyses. The laminates have stacking sequences of [0]_10S and [45/0/−45/90/45/0/−45/0/45/0]_S. Each laminate includes four different waviness ratios (the ratio of wrinkle amplitude to laminate thickness) of 0%, 10%, 20% and 30%. In the simulation, a novel multiaxial progressive damage model is implemented via the user material (UMAT) subroutine to predict the compressive failure behavior of wrinkled composite laminates. This multiscale analysis framework innovatively features a 7 × 7 generalized method of cells coupled with stress-based multiaxial Hashin failure criteria to accurately analyze the impact of wrinkle defects on structural performance and efficiently transfer macro-microscopic damage variables. When any microscopic subcell within the representative unit cell (RUC) satisfies a failure criterion, its stiffness matrix is reduced to a nominal value, and the corresponding failure modes are tracked through state variables. When more than 50% fiber subcells fail in the fiber direction or more than 50% matrix subcells fail in the transverse or thickness direction, it indicates that the RUC has experienced the corresponding failure modes, which are the tensile or compressive failure of fibers, matrix, or delamination in the three axial directions. This multiscale model accurately predicted the load–displacement curves and failure modes of wrinkled composites under compressive load, showing good agreement with experimental results. The analysis results indicate that wrinkle defects can reduce the ultimate load-carrying capacity and promote local buckling deformation at the wrinkled region, leading to changes in damage distribution and failure modes. Full article