Search Results (1,908)

Adductor canal block (ACB) is widely used for perioperative analgesia in knee surgery because it provides effective pain control while preserving quadriceps muscle strength. With the increasing use of ultrasound-guided regional anesthesia, interest has expanded beyond conventional morphologic imaging toward quantitative assessment of peripheral nerve function and biomechanics. Shear wave elastography (SWE) is an emerging ultrasound-based technique that enables real-time quantification of tissue stiffness and has recently gained attention in peripheral nerve evaluation. Previous SWE studies have primarily focused on chronic neuropathic conditions, including entrapment neuropathy and diabetic neuropathy, in which increased nerve stiffness is commonly observed. However, emerging observations suggest that peripheral nerve stiffness may dynamically decrease following regional anesthesia procedures such as ACB. This finding raises the possibility that nerve stiffness reflects not only chronic structural pathology but also transient physiologic and biomechanical modulation. Potential mechanisms underlying reduced stiffness after ACB include perineural hydrodissection, decreased fascial compression, sympathetic blockade-induced vasodilation, altered intraneural pressure, and changes in surrounding muscle tension. Because the saphenous nerve within the adductor canal is superficial and consistently visualized under ultrasound guidance, ACB represents an attractive model for investigating dynamic changes in peripheral nerve biomechanics. This narrative review summarizes current evidence regarding SWE assessment of peripheral nerves and discusses the potential implications of dynamic stiffness changes after regional anesthesia. We review the biomechanical principles of SWE, factors affecting nerve stiffness, current evidence in neuropathic and perioperative settings, technical limitations, and future clinical applications. Understanding the dynamic behavior of peripheral nerve stiffness may expand the role of SWE from a diagnostic tool for neuropathy to a quantitative biomarker for regional anesthesia and perioperative nerve physiology. Full article

Dog parks are widely used recreational spaces for human–dog interaction, yet there is little empirical data about how surface materials influence dogs’ behavior and welfare. This study evaluated dogs’ behavior on three surfaces commonly used in outdoor dog recreation areas. Ten dogs (N = 10) participated in ten structured play sessions in an experimental area with unrestricted access to all surfaces. The testing area consisted of a 12.2 m² playground divided into nine plots of equal size. Each plot was randomly assigned a surface material (i.e., natural grass, stabilized grass, or artificial turf) in a 3 × 3 block design. Environmental and surface temperatures were recorded in each session. Dog behavior was recorded during a pre- and post-play period and measured using a 10 s scan sampling technique. In addition, surface characteristic measures were collected throughout the study to evaluate differences in their tolerance to weather conditions and usage. Artificial turf consistently reached a higher temperature (25.2 °C; 95% CI: 24.5–25.8 °C) than natural (19.4 °C; 95% CI: 18.7–20.1 °C) and stabilized (20.0 °C; 95% CI: 19.3–20.6 °C). In this study, the artificial turf reached temperatures as high as 63.8 °C while, under the same environmental conditions, the surface temperature of both natural turfgrass treatments remained below 40 °C. During the pre-play period, dogs showed more active than passive behaviors on the stabilized surface (35.03%; 95% CI: 30.58–39.80%) compared to the natural (27.86%; 95% CI: 23.94–32.10%) and artificial turf (23.31%; 95% CI: 19.81–27.20%). During the post-play period, activity levels decreased across all surfaces, while the occurrence of passive behaviors increased and was observed more frequently on the natural turfgrass surfaces (27.30% on stabilized and 15.52% on natural) than on artificial turf (2.41%). Artificial turf was less affected by dog traffic and seasonal changes; however, its surface was harder than both natural turfgrass treatments. The addition of the stabilizing grid failed to reduce soil compaction as anticipated. Overall, dogs spent more time on both natural turfgrass surfaces than artificial turf. However, a potential confounding effect of location could have influenced dog behavior. Nonetheless, our findings show that dog owners should be cautious when using artificial turf areas when environmental temperatures are above 25 °C when the turf temperature is above the safety threshold for burn injuries. These findings highlight the importance of carefully selecting surface materials for outdoor dog spaces to ensure dogs’ safety and comfort. Full article

Hydrated lime is widely incorporated into cement-based mortars to improve workability and fresh-state properties; however, its influence on hydration products and mechanical performance remains insufficiently understood. This study investigates the effect of hydrated lime content on the mechanical behavior and microstructural development of cement-based mortars after 28 days of curing. Eight mortar formulations, ranging from lime-free (1:0:6) to lime-rich (1:5:6) mixtures, including intermediate and modified proportions, were evaluated through compressive strength, flexural tensile strength, and consistency tests. The microstructural evolution was investigated using complementary techniques, including X-ray fluorescence (XRF), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TG/DSC), and scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM/EDS). Increasing hydrated lime content improved mortar workability but was generally associated with reduced compressive strength under the curing conditions investigated. The combined characterization techniques indicated progressive modifications in the hydration products and phase assemblage, with increased calcium-rich phases, greater evidence of carbonation, and reduced continuity of the hydraulic matrix as the hydrated lime content increased. The observed microstructural changes were qualitatively consistent with the mechanical behavior of the mortars. The conclusions of this study are restricted to the 28-day curing period investigated, and further research is required to evaluate the long-term influence of hydrated lime on carbonation and durability-related properties. These findings contribute to a better understanding of the role of hydrated lime in cement-based mortars and provide experimental evidence for the optimization of mortar formulations. Full article

Blockchain is a fast-changing field that is highly useful in such areas as finance, supply chain management, voting systems, and healthcare. As a consequence, software developers are increasingly creating Blockchain-Based Applications (BBAs) and Smart Contracts (SCs). However, the development of BBAs has been associated with various problems, especially in the process of updating and debugging such systems with a high degree of reliability. This is due to the immutability of deployed SCs. In this paper, we conduct an in-depth analysis of 61 published BBA articles between 2017 and 2025 to identify some causes of these challenges. Our results indicate that there is inadequate adaptation of the Software Development Life Cycle (SDLC) for BBAs. In particular, few BBA projects—only 32% of the reviewed projects—address the analysis phase, and only 29% deal with the design phase, frequently ignoring formal modeling methods. Based on these observations, we propose a new, context-adaptive methodology that facilitates BBA developers passing through the requirements, analysis, design, and implementation processes. Formal modeling techniques—such as Use Case Maps (UCMs), Finite State Machines (FSMs), and extended Unified Modeling Language (UML) class and sequence diagrams—are used within the methodology to document BBA structural and behavioral features and maintain complete traceability between requirements and implementation. In order to overcome the blockchain-specific drawbacks of traditional UML, we present formal stereotype extensions of UML class diagrams, where a four-compartment structure is introduced to differentiate state variables, functions, events, and access modifiers on SCs. We also provide analogous extensions to UML sequence diagrams using differentiated arrow notations to distinguish between function calls and event emissions to support accurate modeling of decentralized transaction flows. These extensions are described with a rationale and are formally defined and justified by mapping rules. Our methodology is justified by two case studies that prove its applicability in different fields of blockchain. The initial case study thus designs and executes a system of a halal chicken meat supply chain on Ethereum, showing the complete traceability of requirements that are based on UCM-based requirements and FSM-generated algorithms to implement SCs. The second case study applies the methodology to a decentralized Electronic Health Record (EHR) management system, and it shows coverage and completeness modeling. The methodology was evaluated through two case studies using a structured questionnaire and quantitative metrics, including traceability accuracy, reduction-in-error indicators, SC defect and gas-analysis results, modeling overhead measurements, and static security analysis with Slither. It is also evaluated based on a group of seven literature-based qualitative evaluation criteria that include workflow expressiveness, reusability, technical concept coverage, intelligibility, completeness, tool support, and blockchain limitation modeling. Full article

Subsea tunnels constructed by the drill-and-blast method are increasingly required in modern infrastructure and are often exposed to high groundwater pressure and fractured rock conditions. In such environments, external water pressure acting on initial support strongly affects tunnel stability, durability, and construction safety. Because the initial support is temporary, discontinuous, and prone to cracking, evaluation of its water pressure response remains challenging. Current design practice relies on simplified assumptions and empirical approaches, inadequate for fractured rock masses under high water pressure. This review synthesizes research on external water pressure in tunnels, with emphasis on drill-and-blast subsea tunnels. Empirical reduction coefficient methods, theoretical analytical solutions, numerical techniques, and physical model testing are critically examined in terms of their theoretical basis, applicability, and limitations. Special attention is given to seepage behavior in fractured rock masses, including single-fracture seepage laws, equivalent continuum models, and discrete fracture network approaches, and their ability to represent fracture-controlled flow and water pressure redistribution. The review shows that conventional seepage or seepage–stress coupled methods are insufficient to capture stress redistribution, fracture evolution, and damage-induced permeability changes governing water pressure behavior. By contrast, advanced coupled stress–seepage–damage and stress–seepage–fracturing models provide more physically consistent frameworks for analyzing external water pressure acting on initial support. In addition, hydro-mechanical discrete lattice models are reviewed as a promising meso-scale framework for capturing crack initiation, crack coalescence, and crack-controlled seepage paths that may govern localized external water pressure redistribution behind initial support. However, their application to subsea tunnels remains limited, and current design codes still lack unified calculation methods. Major challenges remain, including the lack of consistent definitions of external water pressure, inadequate consideration of the interaction between tunnel support and surrounding rock, and insufficient validation through laboratory experiments and field observations. Future research should develop mechanism-based methods supported by monitoring and validation to improve subsea tunnel safety. Full article

Expansive soils represent a critical challenge in geotechnical engineering due to their significant volumetric changes in response to moisture variations, which cause recurrent structural damage to foundations, pavements and infrastructure. The intensification of wet–dry cycles associated with climate change increases the likelihood of failures, reinforcing the need for more efficient and sustainable stabilization methods. Conventional techniques based on lime or salts present environmental and performance limitations when used independently. This study evaluates a combined approach using sodium chloride (NaCl) and lime sludge (LS), an abundant industrial by-product, to improve the behavior of expansive soils while simultaneously valorizing a difficult-to-manage waste material. Mixtures containing 3%, 6% and 9% NaCl and 5%, 10% and 15% LS were prepared. Atterberg limits, free swell, swelling pressure and infiltration tests were carried out to analyze the response of the treated soil. The results show significant reductions in plasticity and swelling potential: the liquid limit decreased by up to 35%, the plasticity index by up to 36% and the free swell by up to 65% for the optimal combination (9% NaCl + 15% LS). In addition, infiltration increased from 25 to 40 mm, indicating improved hydraulic behavior of the treated soil. The direct reuse of lime sludge prevented its disposal in landfills and reduced the environmental impact associated with its management. Overall, the findings demonstrate that the combination of NaCl and LS is an effective and economical alternative under short-term laboratory conditions, with potential for sustainable application subject to long-term validation for mitigating the swelling of expansive soils. Pilot-scale validation under extreme climatic conditions is recommended to advance toward its integration into resilient infrastructure projects. This approach offers a more efficient, cost-effective, and sustainable technical solution, distinguished by its dual action (chemical and recycling) and its contribution to waste valorization. Future research will focus on validating the method at the pilot scale and assessing its performance under extreme climatic conditions, consolidating its applicability in resilient infrastructure projects. Full article

In this paper, the accelerated aging process of a layer of polymer composites based on the silicone rubber modified by plant-based fillers and iron carbonyl was investigated. The color change, Shore’s hardness, thermal resistance, and surface quality of the composites after weathering were tested. The degradation behavior of the silicone rubber and its composites was characterized by TGA and FTIR techniques, as well as optical microscopy. It was found that the aging process increased the hardness of the silicone rubber composites by approx. 10% compared to pure silicone, and by a further 10% by weight in the case of composites containing plant-based fillers, such as turmeric and goldenrod. The promising results indicate that a SR/CLP/Fe/AM composite modified with carbonyl iron and a surfactant acts as an effective stabilizer for the silicone rubber matrix. An increase in the maximum temperature of 40 °C was also recorded compared to the unmodified silicone rubber. The results showed that the surface color of the aged samples changed in terms of lightness and total color. It was found that silicone rubber composites containing plant-based fillers exhibit properties characteristic of age-resistant materials; in particular, the SR/CLP/Fe composites modified with carbonyl iron are more resistant to water and light during accelerated aging than unmodified silicone rubber, which ensures a longer service life. Full article

With the continuous expansion of the lithium industry, lithium slag (LS) has been generated in large quantities, and its potential reuse in cement-based materials has become increasingly important. In this work, LS was introduced into ultra-high-performance concrete (UHPC) as a partial substitute for cement to explore its applicability in low-cement UHPC systems. The fresh properties of UHPC, including flowability and setting behavior, were measured, and its mechanical performance was evaluated through compressive and flexural strength tests. In addition, early-age autogenous shrinkage was monitored to clarify the effect of LS on dimensional stability. To further reveal the mechanisms associated with the macroscopic performance changes, isothermal conduction calorimetry, backscattered electron microscopy (BSE), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and mercury intrusion porosimetry (MIP) were adopted. These techniques were used to characterize the hydration behavior, phase composition, hydration product evolution, and pore-structure characteristics of UHPC containing different LS contents. Results demonstrate that LS incorporation effectively reduces autogenous shrinkage and accelerates setting. An optimal LS content enhances long-term strength development; however, LS incorporation compromises early-age compressive strength and flowability. Calorimetric, thermogravimetric, and BSE analyses collectively reveal that LS retards early hydration heat release and delays initial strength gain, attributable to its dilution effect, but exhibits latent pozzolanic reactivity, consuming Ca(OH)₂ and promoting secondary C–S–H formation, thereby increasing the 28-day degree of cement hydration. Pore-structure analysis further confirms that an appropriate LS content significantly reduces total porosity, average pore diameter, and the volume fraction of pores with PD > 50 nm, leading to a more refined and compact microstructure. Integrated macroscopic and microscopic evidence identifies 20 wt.% LS as the optimal replacement level: relative to the reference mixture LS0, the 28-day compressive and flexural strengths of LS20 are increased by 10.86% and 27.93%, while flowability decreases by 13.97%, initial setting time shortens by 10.54%, and autogenous shrinkage is reduced by 57.41%. The results provide a scientific basis for the resource utilization of lithium slag in UHPC and contribute to the development of cement-reduced UHPC mixtures with improved mechanical and microstructural characteristics. Full article

Advancing bio-based intelligent packaging is crucial for improving food protection and prolonging storage duration. This research fabricated zein/citric acid (Z/CA) hybrid films embedded with Fu brick tea ethanol extract (FBTE) via a casting technique. The films were comprehensively assessed for their physicochemical attributes, mechanical strength, antioxidant and antimicrobial efficacy, and biodegradability. Findings indicated that FBTE inclusion notably improved film hydrophobicity and antioxidative power, elevating DPPH and ABTS radical quenching efficiencies by 83.75% and 89.33%, respectively. However, the incorporation of high-dose FBTE (8 wt%) increased the water vapor permeability by 57.19%, which was unfavorable for moisture barrier performance, and SEM showed surface morphology and phase segregation at 8 wt% FBTE. These hybrid films demonstrated specific antibacterial behavior against Gram-positive microorganisms. Importantly, the 6 wt% FBTE film exhibited obvious inhibitory effects on lipid oxidation, decreasing peroxide value by 68%. Observations during the 28-day soil burial degradation test revealed gradual morphological changes in the film samples. These results illustrate that Z/CA/FBTE hybrid films have possess potential application value in food active packaging. Full article

The global water situation is deteriorating not only due to the progressing climate change but also to irrational consumer behaviors, which are driven by attitudes. Given the above, it seemed essential to identify attitudes toward the issue of access to freshwater in households, considering sustainable development guidelines. The aim of this study was, therefore, to develop a research tool for the identification of respondents’ attitudes toward this problem and then to determine its validity and reliability. The object of the study was an original questionnaire serving as a research tool for identifying the specified attitudes. The data required for this study were acquired through a critical review of the literature and a questionnaire survey method. The study was conducted in one of the Polish urban agglomerations using the Paper-and-Pencil Interviewing (PAPI) technique. An in-depth analysis of the validity and reliability of the tool, carried out using a statistical procedure, confirmed it to be a viable means to identify these attitudes in Poland. Therefore, there are reasonable grounds to assume that, following the application of the procedure presented in this manuscript, the developed tool may also be used to identify the specified attitudes when implemented in a different population. Full article

Background: Post-traumatic growth (PTG) refers to positive psychological changes resulting from the struggle with highly challenging or traumatic life events. Psychosocial interventions have demonstrated efficacy in promoting psychological well-being in the aftermath of traumatic experiences. Cognitive Behavioral Therapy (CBT) is among the most extensively studied such interventions, aligning with the PTG model’s prerequisites for growth. Objective: The aim of this systematic review was to assess the efficacy of CBT and CBT-based interventions in promoting PTG. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching PubMed, Scopus, and Google Scholar databases from inception to December 2024. Eligibility criteria included: (a) the inclusion of a CBT or CBT-based intervention, (b) measurement of PTG using the Post-Traumatic Growth Inventory (PTGI), (c) study participants having experienced traumatic life events, and (d) articles written in English. Risk of bias was assessed independently by two reviewers. Due to the heterogeneity of included studies, a qualitative narrative synthesis approach was adopted. Risk of bias was assessed using the RoB-2 tool for RCTs, ROBINS-1 for quasi-experimental studies and Newcastle–Ottawa scale for cohort studies. Certainty of evidence, assessed using the GRADE framework, is considered low. Results: A total of 19 studies were included (13 randomized controlled trials, 3 quasi-experimental, and 3 longitudinal studies). While traditional CBT produced mixed results in fostering PTG, CBT-based therapeutic protocols—particularly those explicitly designed to target PTG or incorporating structured cognitive–emotional techniques—demonstrated more consistent benefits. Limitations of the included studies include measurement of PTG as a secondary outcome, small sample sizes, and the presence of confounding variables. Conclusions: Further high-quality, multicenter randomized controlled trials with standardized protocols are needed to clarify the role of CBT in promoting growth after trauma. Full article

A novel modified generalized Riccati equation mapping neural network-based approach is the basic theme of this study by exploring the nonlinear dynamical characteristics of the the strain wave model’s soliton solutions, which govern wave propagation in micro structured solids. Strain waves are particularly intriguing, since they preserve their form and speed throughout transmission. The nonlinear dynamical behaviors of strain waves may be modeled by partial differential equations in micro structured materials. In the realm of micro structured solids, there exists a class of phenomena that are referred to as micro strain waves. These waves arise in solids possessing intricate internal architectures, including periodic lattices, precisely engineered metamaterials Understanding these waves is key to designing more complex materials and new acoustic technologies. The activation function and the weight function of the neural network are assigned to each input layer, hidden layer and output layer and the neural network itself is a multi-layer computational network. Using the structure of the neural network, every neuron in the first hidden layer is given solutions to the Riccati equation, and the new highly expressive trial functions are generated in a systematic way. In this way, a large variety of exact soliton solutions are obtained, such as bright, dark, kink, and combined solitons as well as periodic and hyperbolic wave profiles. The influence of the essential physical and mathematical parameters is explored systematically using three-dimensional, two-dimensional and contour visualizations, which illustrate how parameter variations lead to changes in the amplitude, shape and stability of the wave structures. The solutions presented reveal the dynamic properties of micro strain solitons which leads to new avenues of investigation in the study of related nonlinear phenomena in micro structured solids. In a broader context, our results highlight the great potential of analytical techniques using neural networks as a powerful and versatile toolset to study complex nonlinear wave models within the applied sciences from acoustics to photonics to smart materials engineering. Full article

Network latency remains a fundamental bottleneck in vehicle teleoperation, inducing instability and performance degradation in conventional control methods, while predictive techniques like the Smith Predictor offer a theoretical solution, their efficacy is often compromised by unmodelled dynamics and real-world disturbances. This paper presents the first experimental validation of the Successive Reference-Pose Tracking (SRPT) architecture. By streaming future reference poses rather than direct steering commands, SRPT leverages an onboard Nonlinear Model Predictive Controller to compute optimal vehicle actions while inherently accounting for dynamic constraints and network delays. Real-world human-in-the-loop experiments were conducted with four drivers on a test track featuring cornering, double lane-change, and slalom manoeuvres. Quantitative comparisons at 10 km/h across four modes—manual driving, direct teleoperation, a Smith Predictor, and SRPT—demonstrate that SRPT significantly outperforms other teleoperation methods, reducing cross-track error by up to 66% and yielding smoother, more stable control inputs. Furthermore, SRPT uniquely maintained stability during a proof-of-concept trial at 13 km/h, where it proactively moderated vehicle speed to respect actuator limits—a critical safety behavior absent in other modes. This work provides the first tangible evidence that SRPT is a robust and superior framework for delay-resilient vehicle teleoperation in real-world conditions. Full article

Photovoltaic (PV) generation and electric vehicle (EV) charging infrastructure are changing the dynamic behavior of current power systems, especially in terms of voltage stability and LVRT capabilities. In this work, 50% PV penetration on a modified Kundur two-area power system was tested to mitigate transient instability under severe fault circumstances. With PV units running at unity power factors under steady-state conditions, 50% PV penetration was defined relative to the system’s total active load demand. A steady-state power-flow study ensured generation–load balance before MATLAB/Simulink dynamic simulations. Controllable reactive power compensation was used as an EV aggregator on Bus 7. We constructed and evaluated a genetic algorithm (GA)-optimized fractional-order proportional–integral–derivative (FOPID) controller with a traditional PID controller utilizing identical optimization conditions. An inter-area tie-line critical three-phase fault was applied and removed after 100 ms to evaluate system performance. While the GA-PID controller increased transient performance, it did not restore system stability. Instead, the GA-FOPID controller provided superior dynamic support by restoring Bus 7 voltage to 0.9–1.1 pu within 250 ms after fault clearance and maintaining about 95% LVRT compliance. The suggested controller also reduced rotor angle oscillations and enhanced inter-area damping. Fractional-order control increased EV aggregators’ reactive power response during transient shocks. Thus, in renewable-energy-dominated power systems, the GA-FOPID-controlled EV support technique may improve voltage stability and LVRT compliance. Full article

Anomaly detection models trained exclusively on healthy data are widely used in wind turbine condition monitoring because failure data are scarce, heterogeneous, and often unavailable. However, these models produce anomaly indicators that are sensitive not only to fault-related degradation but also to normal operational variability, transient disturbances, and changes in loading conditions. As a result, the practical behavior of an alarm system depends not only on the anomaly detection model but also on the decision rule used to activate and maintain alarm states. This study presents a decision-oriented evaluation of persistence-based alarm confirmation in wind turbine anomaly detection. Four representative techniques are analyzed within a unified framework: Isolation Forest, One-Class Support Vector Machine, Referenced Moving Window Principal Component Analysis using Q-statistic and percentage component weight indicators, and Autoencoder-based reconstruction error. The evaluation combines controlled OpenFAST simulations of rotor unbalance under different severity and noise conditions with an industrial SCADA case study involving a documented main bearing fault. Results show that temporal persistence strongly shapes alarm outcomes across methods and datasets. Low persistence values favor early detection but promote alarms from isolated threshold exceedances, whereas moderate persistence substantially reduces false positives while preserving detection capability in severe and well-observable faults. Excessive persistence increases detection latency and missed detections, particularly for weak, intermittent, or slowly evolving fault signatures. These findings indicate that persistence-based alarm confirmation should be treated as an explicit decision-level configuration variable, rather than as a fixed post-processing or alarm-state heuristic, when designing anomaly detection systems for wind turbine condition monitoring. Full article