Search Results (7,919)

Multi-Robot Systems (MRS) demand optimal spatial resource configuration to ensure systemic efficiency in mission-critical applications. Conventional paradigms rely on rigid coverage-first principles, prioritizing exhaustive spatial scanning over rapid target discovery, thereby compromising systemic responsiveness. To bridge this gap, this study proposes the Attraction of Unknown area Centroid for Exploration (AUCE) architecture, a centralized framework designed to simultaneously optimize global exploration efficiency and early-stage target discovery rates. The control framework incorporates a dynamic region planning strategy that adaptively modulates the systemic search focus based on the specific field of view of autonomous agents, alongside an optimized S-shaped trajectory pattern to establish a rigorous balance between localized path simplicity and global coverage. A versatile profit function synthesizing constant and time-varying coefficient strategies explicitly regulates the systemic trade-off between accelerated early-stage target discovery and global path cost minimization. Quantitative simulations demonstrate that AUCE significantly outperforms established methods by mitigating redundant path costs and generating a distinct front-loading effect to accelerate target localization. Subsequent evaluations confirm the framework’s computational scalability in expanded swarms and its systemic adaptability when navigating static obstacles. Full article

Background and Clinical Significance: Conventional hard sockets are reported to result in skin breakdown for almost half of transtibial prosthesis users. Adjustable sockets have been developed to better accommodate residual limb shape and volume changes. They have demonstrated optimal skin health in prospective adult clinical studies. Case Presentation: We present the case of a 57-year-old male with a transtibial amputation who enrolled in a research study at the University of Pennsylvania. In the year before enrollment, he experienced frequent, near-constant skin breakdown of the distal residual limb at the anterior tibia due to limb volume fluctuations and excessive pressure from a conventional hard socket and was frequently unable to use his socket due to skin breakdown. The subject was fit with an adjustable, immediate fit transtibial prosthesis (iFIT Prosthetics^®). After a two-week home trial, he rated the adjustable prosthesis 62 out of 70 on an adapted Prosthetic Evaluation Questionnaire, compared with a score of 20 for his conventional prosthesis. Due to improved comfort, he discontinued the use of his conventional device. The subject was followed for over one year and wore the adjustable prosthesis exclusively without a recurrence of skin breakdown. Residual limb volume changes commonly lead to poor socket fit and skin irritation in conventionally fabricated hard sockets, often progressing to skin breakdown. In individuals with diabetes, wound healing can be prolonged and functionally limiting. In this case, an adjustable prosthesis successfully eliminated anterior tibial skin breakdown in a subject predisposed to this injury when using conventional hard sockets. Conclusions: Adjustable sockets can prevent skin breakdown in individuals with transtibial limb loss. Full article

Motor vehicle exhaust in urban tunnels can cause nitric oxide (NO) to accumulate, severely degrading air quality both inside the tunnel and in the surrounding environment. Photocatalytic technology is an efficient, secondary-pollution-free approach with clear potential for treating tunnel exhaust; however, parametric analyses for practical tunnel engineering applications remain limited. Using computational fluid dynamics (CFD), this study developed a numerical model to simulate photocatalytic NO degradation in a congested tunnel and examined how the surface reaction rate, coating extent, and longitudinal coated section affect NO reduction performance. The results show that NO reduction efficiency increased with the surface reaction rate; however, once the surface reaction rate constant exceeded 2.11 × 10⁻⁴ m/s, further gains diminished and the efficiency approached a plateau due to mass-transfer limitations. With respect to the coating extent, full four-wall coating (sidewalls, ceiling, and road surface) provided the best performance, followed by three-wall coating (excluding the ceiling). Moreover, because the road surface lies in a region of high pollutant concentration and low air velocity, coating on the road surface achieved a markedly stronger reduction effect than coating on the sidewalls or the ceiling. In the simulated 500 m tunnel, the downstream coated section achieved a markedly higher NO reduction efficiency in the ambient environment outside the tunnel (5.9%) than the upstream coated section (1.0%), approaching that of the full-length (500 m) coated section (6.6%). Therefore, in practical engineering applications, priority should be given to coating strategies targeting the downstream section and the road surface in order to balance NO reduction performance and economic cost. Such a strategy is beneficial not only for improving tunnel air quality, but also for promoting sustainable pavement and tunnel-surface engineering by reducing unnecessary coating area and enabling a more resource-efficient and cost-effective use of photocatalytic materials. These findings provide theoretical and methodological support for the sustainable design and application of photocatalytic coating systems in urban tunnels. Full article

Ultra-high-performance concrete (UHPC) is widely used due to its strength, toughness, and durability. Shrinkage issues are the primary cause of concrete cracking and one of the main factors limiting the widespread application of UHPC in structural engineering. The shrinkage properties of UHPC vary depending on curing conditions. Research indicates that after thermal curing, the pore structure of UHPC is optimized, resulting in a significant reduction in shrinkage values. Based on the superposition principle, temperature creep coefficients and humidity creep coefficients are introduced to correct the temperature and humidity in the test environment to a constant temperature (20 °C) and humidity (75% relative humidity). The B3 coefficient of variation method was used to compare five different creep prediction models. The CEB-FIP2010 model was selected as the benchmark creep model, and curing condition coefficients were incorporated into the model to establish a comprehensive creep calculation model considering curing conditions. After 550 days of steam curing, the shrinkage strain of the UHPC specimens was approximately 28.9% of that of the uncured specimens. The additional creep deformation caused by temperature and humidity in the uncured and steam-cured specimens accounted for approximately 10% and 20% of the total creep deformation over 550 days, respectively. The strain development rates for both tensile and compressive strains in steam-cured specimens were lower than those in uncured specimens. A ten-year long-term creep simulation of UHPC precast joint beams was conducted using the finite element software Midas-Fea, and the comparison results validated the reliability of the comprehensive creep model. Full article

The rapid expansion of the Internet of Vehicles (IoV) necessitates high-capacity backhaul connectivity, yet the deployment of such networks under strict hardware and power constraints poses significant computational challenges for network optimization. To address this challenge, this paper investigates a joint transmit–receive beamforming optimization problem for narrowband wireless backhaul in IoV networks under constant-modulus constraints. Unlike ideal digital architectures, we focus on cost-effective analog phase shifters, which introduce strictly non-convex constant-modulus constraints, rendering the optimization problem mathematically intractable for standard solvers. Since the resulting problem is highly non-convex, we develop two structured numerical methods: an iterative alternating optimization (AO) method and a joint optimization (JO) method, where AO employs auxiliary WMMSE-guided alternating updates together with constant-modulus projection, while JO jointly updates both beamformers over the constant-modulus feasible set. We compare their achievable sum-rate performance with that of a CDO-based benchmark and analyze their dominant computational costs through representative Big-O complexity expressions. Furthermore, we examine the effect of SVD-based and random feasible initializations on empirical convergence behavior, runtime, and final achievable performance. Simulation results demonstrate that the proposed computational methods significantly improve achievable sum-rate performance compared with the CDO benchmark. Moreover, SVD-based initialization provides a more structured starting point and generally leads to better convergence behavior and lower runtime than random feasible initialization. The empirical timing results further show that AO exhibits faster empirical convergence and requires lower runtime, whereas JO achieves better final sum-rate performance after more iterations. Full article

Despite the growing adoption of Ti6Al4V-ELI made by Laser Powder Bed Fusion (LPBF) in tribologically demanding applications, the influence of hybrid nanoparticle additives on its lubrication behavior under starved contact conditions remains insufficiently explored. The tribological performance of Ti6Al4V was investigated under starved boundary-to-mixed lubrication conditions using engine oil modified with Ag-doped TiO₂ nanoparticles. Double-scan LPBF-fabricated discs were tested in a ball-on-disc configuration against AISI 52100 bearing steel using a TRB³ tribometer. Nanolubricants were prepared by dispersing TiO₂ and Ag–TiO₂ nanopowders with different Ag⁺/Ti⁴⁺ ratios (0.5%, 1.5%, and 2.5%) in SAE 10W-40 engine oil at a constant nanoparticle concentration of 0.05 wt%. Comprehensive physicochemical characterization of the nanopowders and nanolubricants was performed through structural, chemical, optical, morphological, rheological, and stability analyses. Tribological experiments were conducted following a full-factorial design combining three normal loads (5–15 N), three sliding speeds (0.10–0.20 m·s⁻¹), and four lubricant formulations. The steady-state coefficient of friction ranged between 0.281 and 0.359, while the specific wear rate varied from 2.81 × 10⁻⁴ to 4.83 × 10⁻⁴ mm³·N⁻¹·m⁻¹. The contact temperature rise remained relatively moderate, within the interval of 1.9–9.4 °C. Among the investigated formulations, the lubricant containing 1.5% Ag–TiO₂ exhibited the lowest friction coefficient, whereas the formulation with the highest Ag content showed improved stability of tribological performance across the investigated operating domain. These results indicate that Ag-modified TiO₂ nanoparticles are consistent with the formation of protective tribofilms and contribute to the stabilization of friction, wear, and thermal behavior under starved lubrication conditions. ANOVA confirmed that sliding speed and the load–lubricant interaction are the dominant factors governing friction and wear, while normal load controls the thermal response. These findings support the use of Ag–TiO₂ nanolubricants as a viable strategy for stabilizing interfacial behavior in LPBF-fabricated titanium components operating under starved lubrication conditions. Full article

The microstructure, phase composition, and high-temperature oxidation behavior of Al_0.5CoCr_0.5NiPt_0.1 and AlCoCr_0.5NiPt_0.1 multi-principal element alloys (MPEAs) at 1100 °C in air were investigated. Depending on the content of aluminum, the microstructure of as-cast samples contains FCC and BCC solid solutions. Similarly, the ratio of two solid solutions varies depending on the aluminum content in the alloy. When the content of aluminum is x = 0.5, the microstructure is dominated by the FCC solid solution, while a BCC solid solution is dominated when the concentration of aluminum is increased to x = 1.0. Moreover, in both MPEAs, platinum exists as a part of solid solutions rather than a separate phase. High-temperature oxidation was carried out in a Plavka.Pro PM-1 SmartKiln muffle furnace under isothermal conditions at 1100 °C for 100 h exposure in air, and weighing was performed every 10 h. The maximum specific weight gain for the Al_0.5CoCr_0.5NiPt_0.1 alloy was 0.965 mg/cm², and 0.675 mg/cm² for the AlCoCr_0.5NiPt_0.1 alloy. Based on the high-temperature oxidation experiment results, it was established that AlCoCr_0.5NiPt_0.1 MPEA exhibits greater resistance towards high-temperature dry air corrosion with the formation of an exclusive Al₂O₃ scale on the surface with 3–5 μm thickness; the parabolic oxidation rate constant for this alloy is k_p = 20.2 × 10^–13 (g²/cm⁴s). Introduction of platinum into the composition of the Fe-free AlCoCr_0.5Ni alloy reduces the value of the parabolic oxidation rate constant by half. Full article

Synthetic dyes frequently persist through conventional wastewater treatment, motivating the use of advanced oxidation processes capable of breaking down these stable molecules. Metal-doped carbon dots (CDs) offer a tuneable platform for catalytic dye degradation in water, although their performance varies strongly with operating conditions. The aim of this work was to determine how temperature, H₂O₂ dosage, and pH influence the catalytic behaviour of Fe-, Cu-, Zn-, and Mg-doped CDs during the degradation of methylene blue (MB) and rhodamine B (RB), optimised using a Taguchi L27 orthogonal array design. Temperature and oxidant loading were the dominant factors: higher temperatures accelerated reactions through Arrhenius-type kinetics, while increasing H₂O₂ availability improved removal until excessive levels began to suppress •OH generation. Across all condition sets, apparent rate constants spanned 7.0 × 10⁻⁴–2.65 × 10⁻² min⁻¹, with t₅₀ values of 26–217 min and t₉₀ extending from ~86 min to >700 min; final decolourisation ranged from ~17% to nearly 100%. pH played a secondary role, mainly affecting dye speciation and surface adsorption. Dopant identity shifted the optimum operating region for each catalyst: Fe- and Cu-CDs achieved complete or near-complete removal of both dyes at pH 7 and 50 °C with relatively low H₂O₂ dosage (0.5–1.0 mL); Zn-CDs reached equivalent performance at pH 7 and 25 °C but required higher oxidant loading (1.5 mL of H₂O₂), reflecting their photo-induced rather than thermally driven activation mechanism; Mg-CDs performed comparably under the same conditions as Fe- and Cu-CDs. The resulting condition–catalyst map highlights the operating regimes that maximise efficiency while minimising chemical input, providing a practical framework for selecting carbon-dot-based catalysts for water treatment applications. Full article

This study presents a highly efficient and sustainable biocatalytic platform for bisphenol A (BPA) bioremediation through the covalent immobilization of laccase onto hierarchically functionalized cotton fibers. The immobilization strategy involved selective periodate oxidation of cellulose, grafting a hexamethylenediamine (HMDA) spacer arm, and glutaraldehyde activation, ensuring stable covalent attachment. Characterization via FTIR, SEM, and BET confirmed successful surface modification and high enzyme loading, achieving an immobilization yield of 90.5%. The immobilized laccase (CT-DA-HMD-Lac) exhibited significantly enhanced performance compared to the free enzyme, with a two-fold increase in maximum reaction velocity (V_max) and a 75% improvement in catalytic efficiency of action (V_max/K_m). Furthermore, the biocatalyst demonstrated superior robustness, maintaining high activity across broader pH and temperature ranges, and retaining 75% of its initial activity after 15 consecutive reusability cycles. Storage stability was also markedly improved, with 83% activity retention after 60 days. Practical application in BPA degradation showed 85% removal efficiency within 300 min, a 2.4-fold increase in the degradation rate constant over the free enzyme. These results highlight functionalized cotton as a promising, cost-effective, and scalable support for advanced enzymatic wastewater treatment and the remediation of persistent endocrine-disrupting chemicals. Full article

In this study, a waste-to-resource route for water remediation is presented by supporting Pd and Cu nanoparticles (NPs) on hydrochar (HC) derived from spent coffee grounds (SCG). Unlike conventional noble-metal catalysts, HC was first produced via hydrothermal carbonization of SCG, followed by a completely green, tannic acid-assisted reduction step that simultaneously deposits Pd and Cu NPs without toxic reductants or organic solvents. The resulting catalysts were evaluated for catalytic reduction of 4-nitrophenol (4-NP) and for antibacterial activity against Escherichia coli (E. coli; BL21) and Staphylococcus aureus (S. aureus), including biofilm inhibition. Among formulations, the bimetallic catalyst containing approximately equal proportions of Pd and Cu (HC@Pd_0.5Cu_0.5) achieved the fastest 4-NP reduction, completing the reaction in ~3 min, with an apparent first-order rate constant of 1.35 min⁻¹ and a total turnover frequency of 483.6 h⁻¹. Notably, Cu incorporation enhanced antibacterial performance, with the Cu-rich variant (HC@Pd_0.25Cu_0.75) achieving the strongest inhibition (MICs of 1.25 mg/mL against E. coli and 2.5 mg/mL against S. aureus) and effective biofilm suppression. This dual-action catalyst, derived entirely from waste through green methods, advances circular-economy principles and green chemistry by simultaneously tackling chemical pollutants and microbial contaminants in water, thereby contributing to SDG 6 (Clean Water and Sanitation). Full article

This study investigates the failure mechanisms and machining performance of 3D-printed H13 tool steel end mills driven by the creation of a Finite Element Analysis (FEA)-based digital twin. The primary objective is to assess the process capability of these tools by integrating CAD and FEA with product design simulation-based data acquisition within a digital manufacturing framework, thereby validating a physical model. This research begins by redesigning a 20 mm end mill into a 6 mm, four-flute configuration, and then FEA simulating H13 tool steel and tungsten carbide (WC) tools. This is carried out to machine Al-6082-T6 under spindle speeds of 5500 rpm and 1500 rpm, with a constant feed rate of 0.5 mm/tooth over 100,000 cycles. The process is integrated with the Siemens Insights hub via Node-RED to replicate the simulation to correlate the CPU signal spikes and enhanced processing capacity, especially in relation to CAD/CAE kernel activities. Based on the simulation insights, two H13 end mills are fabricated using Fused Filament Fabrication (FFF). The first tool, tested at 5500 rpm and a 1100 mm/min feed rate, fractured after 70 mm of cutting. The second trial, using a diamond-coated solid carbide tool at 1500 rpm and 300 mm/min, achieved successful machining with graphene-enhanced coolant. The cutting forces ranged from 300 to 500 N for 3D-printed tools, compared with 150–180 N for the carbide tool. The surface roughness varied between 0.6–1 µm and 4–6 µm for the printed tools, aligning closely with traditional tools (0.5–1 µm). Post-machining analysis using SEM and EDX confirmed tool wear and material changes. This work adopted a methodology to capture and monitor CPU signal spikes via the digital twin platform, enabling real-time comparison with failure thresholds. The results demonstrate the feasibility of using 3D-printed H13 tools for sustainable, customizable machining, offering a pathway for industries to adopt in-house tool design and manufacturing with integrated digital validation. Full article

This paper examines whether government debt financing crowds out private consumption in South Africa or whether household behaviour is consistent with Ricardian equivalence. Using quarterly data from 1960Q1 to 2025Q1, the study employs a Bayesian time-varying parameter framework that accommodates non-stationarity, structural change, and evolving fiscal transmission mechanisms, and is complemented by a Markov-switching Bayesian VAR as a robustness check. All variables are expressed relative to GDP to avoid scale effects, and inference is based on posterior distributions. The results reveal pronounced state dependence in the debt–consumption relationship. In earlier decades, increases in the debt-to-GDP ratio are associated with statistically meaningful declines in the private consumption share, consistent with crowding-out or precautionary behaviour under weaker fiscal credibility. Over time, however, this negative association weakens and converges toward neutrality, with post-2010 estimates indicating no significant effect of debt on consumption. Conditioning on fiscal stance and financial conditions shows that debt does not exert an independent influence on consumption once government expenditure, tax revenue, and interest rates are taken into account. A constant-parameter Bayesian benchmark masks these dynamics, producing an average effect close to zero. Evidence from a Markov-switching Bayesian VAR similarly finds no persistent regime-specific crowding-out effects. Overall, the findings suggest that observed debt–consumption linkages in South Africa operate primarily through broader fiscal and macroeconomic conditions rather than debt accumulation itself, highlighting the importance of fiscal credibility and policy composition. Full article

Minimizing the impacts of coupling, randomness, time variation and uncertain nonlinearity to enhance real-time performance is critical for controlling complex industrial systems. This paper proposes an optimized adaptive filtering method (LAF-MTNF) for time-varying uncertain nonlinear systems with multiple-input multiple-output (MIMO) measurement noise, which integrates the multi-dimensional Taylor network (MTN) with Lyapunov stability theory (LST). Leveraging MTN’s inherent advantages—simple structure, linear parameterization, and low computational complexity—LAF-MTNF achieves efficient real-time filtering while avoiding the exponential computation burden of neural networks. The contributions of this work are threefold: (1) A novel integration of LST and MTN is proposed for MIMO filtering, in which an energy space is constructed with a unique global minimum to eliminate local optimization traps, addressing the stability deficit of traditional MTN filters using LMS/RLS algorithms. (2) Convergence performance is systematically quantified by deriving explicit expressions for the error convergence rate (regulated by a positive constant) and convergence region (a sphere centered at the origin) while modifying adaptive gain to avoid singularity, filling the gap of incomplete performance analysis in existing Lyapunov-based filters. (3) The design is disturbance-independent, relying only on input/output measurements and requiring no prior knowledge of noise statistics, thus enhancing robustness to unknown industrial disturbances. We systematically analyze the Lyapunov stability of LAF-MTNF, and simulations on a complex MIMO system verify that it outperforms existing methods in filtering precision (mean error 0.0227 vs. 0.0674 of RBFNN) and dynamic response speed, while ensuring asymptotic stability and real-time applicability. The proposed LAF-MTNF method achieves significant advantages over traditional adaptive filtering methods in filtering accuracy, convergence speed and anti-cross-coupling capability. This method has broad application prospects in high-precision industrial servo motion control, power system state monitoring and other multi-variable nonlinear industrial scenarios with complex noise environments. Full article

This paper presents a symmetric positive definite (SPD) coupling between the boundary element method (BEM) and the finite element method (FEM) in the framework of the numerical manifold method (NMM) for two-dimensional linear elastic static problems. The BEM subdomain is treated as a single mathematical patch whose local approximation is derived from the displacement boundary integral equation, thereby preserving the nonlocal nature of BEM. The remaining domain is covered by a finite element mesh, with each node defining a patch and the associated shape functions serving as weight functions. Weight functions are defined over the entire mathematical cover, with explicit zero values outside the support of each patch. This global definition ensures that the partition of unity holds everywhere and enables the global displacement approximation to be expressed as a superposition of contributions from all patches. Within this unified framework, the interface between the BEM and FEM subdomains emerges naturally as a transition zone of weight functions, rather than a distinct boundary. Displacement continuity is automatically satisfied through the partition of unity, and traction equilibrium is approximately enforced through the variational formulation. To fully incorporate the coupling formulation into the minimum potential energy framework, the tractions on the BEM patch are eliminated in favor of displacements using the displacement boundary integral equation (BIE). Prescribed tractions on the BEM patch are enforced via a penalty method. The resulting algebraic system is symmetric by construction and remains positive definite when either constant or isoparametric boundary elements are used. This work serves as a proof-of-concept study for the SPD coupling framework with constant elements. Numerical examples demonstrate the accuracy and convergence of the method. The results show that the coupling procedure preserves the intrinsic convergence properties of each subdomain: the BEM part converges at a rate close to unity for displacements and approximately 2.0 for stresses, while the FEM part achieves quadratic convergence for both. The study also reveals that near-singular integrals in the strain BIE can affect the convergence rate when the element size becomes sufficiently small. Full article

Achieving high selectivity in the hydrogenation of CO₂ to light olefins remains challenging because of the complex reaction network and the difficulty of regulating key intermediates. Motivated by green-hydrogen-enabled power-to-chemicals pathways, we combine density functional theory (DFT) with first-principles microkinetic simulation (FPMS) to construct a quantitatively predictive reaction-energy landscape and elucidate structure–selectivity relationships. A comprehensive reaction network is established through energy-surface fitting, and steady-state rate constants are solved to capture the microkinetic competition between elementary steps. By introducing electronic density-of-states (DOS) modulation as a design variable, we directly correlate surface structural parameters with rate-controlling steps, thereby enabling targeted regulation of C–C coupling and hydrogen transfer processes. The calculated barrier for CO₂ adsorption to COOH* is 1.35 eV, while the transition state barrier for C–C coupling is 1.50 eV, corresponding to a reaction rate of 9.7 × 10³ s⁻¹; the olefin desorption rate reaches 1.7 × 10⁷ s⁻¹. Crucially, shifting the d-band center from −2.35 eV to −1.60 eV increases the C₂–C₄ olefin selectivity from 42.6% to 68.3%, establishing an actionable electronic structure lever for catalyst optimization. These results reveal the intrinsic mechanism by which surface electronic and geometric regulation governs intermediate stabilization and rate control, providing a verifiable, mechanism-based design principle for efficient CO₂-to-olefin catalysts aligned with green hydrogen deployment. Full article