Search Results (1,253)

This paper proposes a multi-strategy Secretary Bird Optimization Algorithm (MS-SBOA) for solving global optimization problems and 3D wireless sensor network deployment. While preserving the original two-phase search framework of SBOA, the proposed algorithm achieves a dynamic balance between global exploration and local exploitation through the synergistic integration of multiple enhancement strategies, including a hybrid initialization scheme combining Latin hypercube sampling and quasi-opposition-based learning, a success-history-based adaptive parameter learning mechanism, a finance-inspired market-state trading operator, and an elite-guided population regulation strategy. Experimental results on the IEEE CEC2020 and CEC2022 benchmark test suites demonstrate that MS-SBOA significantly outperforms nine comparative algorithms, including VPPSO, IAGWO, and QHSBOA, under both 10-dimensional and 20-dimensional settings. The proposed algorithm exhibits superior optimization accuracy, faster convergence speed, and stronger robustness. Statistical analyses using the Wilcoxon rank-sum test and the Friedman mean rank test further confirm that the observed performance improvements are statistically significant. Moreover, MS-SBOA is applied to three-dimensional wireless sensor network (3D WSN) deployment optimization problems, where the average coverage rates reach 76.22% and 82.32% for 30-node and 50-node deployment scenarios, respectively. The resulting node distributions are more uniform, and the computational efficiency is improved compared with competing algorithms. Full article

Task scheduling in cloud computing environments is a complex NP-hard problem that requires maximizing resource utilization while satisfying quality-of-service (QoS) constraints. Traditional meta-heuristic algorithms often become stuck in local optima, while single deep reinforcement learning (DRL) models exhibit instability when exploring large-scale solution spaces. To address this, this paper proposes a hybrid scheduling algorithm based on multi-objective sand cat colony optimization (MoSCO). This algorithm utilizes a D3QN network to extract task features and guide population initialization, followed by a multi-objective Sand Cat Swarm Optimization (SCSO) algorithm for refined local search. Results from 50 independent replicate experiments conducted in a simulated cloud environment, coupled with an analysis of the dynamic convergence process, demonstrate that MoSCO exhibits significant superiority and robustness. Scatter plot convergence analysis further confirms that MoSCO’s knowledge injection mechanism effectively overcomes the blind exploration phase of traditional algorithms and successfully breaks through the local optimum bottleneck in the late iteration stages of single reinforcement learning, achieving higher-quality, denser, and more stable convergence. Furthermore, 3D and 2D Pareto front analyses show that MoSCO generates highly competitive, well-distributed non-dominated solutions, offering flexible trade-off options for conflicting objectives. Compared to PureD3QN, H-SCSO, and NSGA-II, MoSCO exhibits the smallest performance fluctuations in box plots. Specifically, MoSCO elevates the average resource utilization of clusters to 92.20%, while reducing the average maximum Makespan and Tardiness to 528 and 4187, respectively. Experimental data confirm that MoSCO effectively balances global exploration with local exploitation, delivering stable, high-quality solutions for dynamic cloud task scheduling. Full article

This paper presents a scenario-based optimization framework for evaluating the life-cycle cost of right-sizing and replacement timing for distribution transformers under demand–growth uncertainty. The proposed formulation jointly considers the discrete commercial transformer ratings, the discounted investment cost, and the monetized iron and copper losses over a 15-year planning horizon. Demand uncertainty is represented by nine scenarios defined by combinations of initial apparent power demand and annual growth rate, with $D_1\in \{45,50,55\}$ kVA and $g\in \{3\%,4\%,5\%\}$. Under these assumptions, the demand envelope evolves from an initial range of 45–55 kVA to approximately 68.1–108.9 kVA in Year 15, while expected demand increases from 50 kVA to about 87 kVA. The optimization results show that the economically optimal policy is to install a 112.5 kVA transformer in Year 1 and maintain that rating throughout the horizon, without triggering any replacement events. The selected transformer maintains expected loading between approximately 0.44 p.u. and 0.77 p.u., while the upper-demand scenario remains below 1.0 p.u. over the entire horizon. These results indicate that, for the demand–growth conditions analyzed, the preferred outcome is a single initial sizing decision rather than a phased replacement strategy. Therefore, the proposed framework provides a consistent scenario-based alternative to deterministic margin-based planning for distribution transformer asset management. Full article

Co-pyrolysis of polyolefins (LDPE, PP, PS) mixed with silicone rubber (SR) was investigated using a laboratory-scale pyrolysis apparatus to evaluate product composition, synergistic interactions, and siloxane recovery potential. Synergistic effects were assessed by comparing experimental mass balances and product distributions with calculated values derived from individual polymer pyrolysis. Co-pyrolysis resulted in a reduction in liquid yield and an increase in gaseous products and solid residue compared to calculated values, with liquid yields decreasing by up to ≈15 wt% at high SR content. This shift was accompanied by an enrichment in lighter hydrocarbons in both phases, reaching up to a ≈18% relative increase at high SR content, and by a redistribution towards smaller cyclic siloxanes. Chromatographic analysis confirmed that no new compounds were formed, but the proportion of low molecular weight species increased with silicone content. These effects are attributed to the distinct thermal behavior of the polymers, as silicone rubber does not melt but becomes brittle, allowing molten polyolefins to infiltrate surface cracks and prolong residence time, thereby promoting secondary cracking. Furthermore, recovery of hexamethylcyclotrisiloxane (D₃), the primary silicone pyrolysis product, was demonstrated from the liquid co-pyrolysis products via solvent-assisted filtration using ethanol, achieving purities above 99.5% and recovery rates up to ≈75% compared to other possible methods. These findings provide insights into co-pyrolysis behavior and offer a basis for developing strategies for the recovery of siloxane and advanced recycling of mixed polymer waste. Full article

Background/Objectives: Endometrial cancer frequently develops resistance to apoptosis-based therapies, highlighting the need for alternative strategies that control tumor growth independently of cell death induction. Three-dimensional (3D) tumor models more accurately recapitulate tumor architecture, cellular interactions, and treatment resistance compared to conventional two-dimensional (2D) cultures. This study aimed to investigate whether imatinib-based combination treatments can enforce sustained cytostatic responses in a 3D endometrial cancer model. Methods: Ishikawa spheroids were treated with imatinib alone or in combination with lithium chloride or medroxyprogesterone acetate. Proliferation was assessed by bromodeoxyuridine incorporation, cell cycle distribution by flow cytometry, and apoptosis by Annexin V/propidium iodide staining over 96 h. Results: Imatinib monotherapy produced modest antiproliferative effects, whereas combination treatments resulted in sustained suppression of DNA synthesis, increased G₀/G₁ accumulation, and reduced S-phase entry. Despite strong growth inhibition, apoptotic fractions remained low across all groups. Conclusions: Imatinib-based combinations suppress 3D endometrial cancer growth predominantly through sustained cell cycle arrest rather than apoptosis induction. Targeting apoptosis-resistant proliferation through cytostatic mechanisms may represent a complementary therapeutic strategy for hormone-responsive endometrial cancer and warrants further translational evaluation. Full article

The progressive phase-out of coal-fired power plants in Portugal has significantly reduced the availability of fly ash (FA) as a supplementary cementitious material (SCM), reinforcing the need for sustainable alternatives. Waste glass powder (WGP), characterized by its high amorphous silica content, has emerged as a promising candidate; however, most studies focus on ultrafine particles or isolated performance indicators, lacking an integrated technical, environmental, and economic assessment. This study evaluates cement pastes incorporating 25% WGP (by volume) with different particle size distributions, including fineness levels comparable to cement and FA. Mechanical performance, grinding energy demand, carbon footprint, and cost were systematically analyzed. The results indicate that WGP is technically viable as an SCM, with a median particle size (D₅₀) of approximately 48 µm providing the most balanced performance. Although finer particles enhance pozzolanic reactivity, the associated increase in grinding energy and economic cost offsets these gains. The findings demonstrate that optimizing particle size, rather than maximizing fineness, enables a technically robust and industrially realistic use of WGP. This approach supports circular economic strategies and contributes to the decarbonization of the construction sector by identifying an efficient replacement pathway for FA under resource-scarcity conditions. Full article

Layered sodium transition-metal oxides are promising cathode materials for sodium-ion batteries due to their high theoretical capacity; however, their practical application is often limited by sluggish Na⁺ diffusion kinetics and structural instability during cycling. P2/O3 phase coexistence has been proposed as an effective strategy to balance capacity and stability, yet it is typically achieved through precise Na-content tuning or complex synthesis conditions, which restrict compositional flexibility. Herein, we demonstrate a phase-engineering approach that induces stable P2/O3 phase coexistence without adjusting the overall Na stoichiometry by controlling the dopant incorporation pathway. Using Na_0.8(Ni_0.25Fe_0.33Mn_0.33Cu_0.07)O₂ (NaNFMC) as a model system, Mg doping via a wet chemical route enables homogeneous dopant distribution, which triggers local stacking rearrangement and the formation of prismatic Na⁺ diffusion channels characteristic of the P2 phase. In contrast, dry-doped samples with identical Mg content retain a predominantly O3-type structure, highlighting the decisive role of dopant incorporation in governing phase evolution. As a result of the phase-engineered P2/O3 coexisting framework, the Mg wet-doped cathode exhibits enhanced initial reversibility, superior rate capability, and improved long-term cycling stability compared to pristine and dry-doped counterparts. Voltage-resolved dQ/dV and cyclic voltammetry analyses reveal stabilized redox behavior with reduced polarization, while electrochemical impedance spectroscopy confirms suppressed impedance growth and improved Na⁺ transport kinetics after cycling. This study establishes that phase engineering through controlled dopant incorporation provides an effective alternative to conventional Na-content tuning strategies for layered sodium cathodes. The findings offer a scalable and versatile design principle for optimizing the electrochemical performance and structural durability of next-generation sodium-ion battery cathode materials. Full article

Although polylactic acid (PLA) and acrylonitrile–butadiene–styrene (ABS) are among the most widely used polymers in material extrusion, their limited toughness and energy-absorption capacity often restrict the structural performance of 3D-printed functional components. To address the limited comparative understanding of how thermoplastic polyurethane (TPU) modifies the deformation behavior and phase characteristics of these two polymer systems, this study presents a multi-analytical evaluation of TPU-reinforced PLA and ABS blends. To this end, both polymers were blended with TPU at 10–50 wt% and processed into filaments via single-screw extrusion. The resulting filaments were used to fabricate ASTM D638 Type I tensile specimens via material extrusion under matrix-specific, but internally consistent, printing parameters. For each composition, five specimens were tested to obtain representative values of tensile strength, elongation at break, and toughness. In addition to conventional tensile testing, the evolution of strain during deformation was monitored using digital image correlation (DIC), enabling full-field characterization of local deformation behavior. To ensure experimental reliability, specimen masses were carefully controlled, and the datasets were analyzed using MATLAB. Thermal properties were investigated by differential scanning calorimetry (DSC) to determine the influence of TPU on glass transition, melting behavior, and phase mobility, and to relate these thermal characteristics to the mechanical response of the blends. The incorporation of TPU significantly increased ductility and energy absorption in both polymer matrices, although the magnitude of improvement differed. ABS/TPU blends exhibited the highest toughness enhancement, reaching 221.4% at 30 wt% TPU, while PLA/TPU systems showed nearly a twofold increase at 20 wt% TPU. DIC analysis further revealed a transition from localized brittle deformation in neat polymers to more distributed plastic deformation with increasing TPU content. DSC results indicated reduced crystallinity in PLA-rich blends and enhanced segmental mobility in ABS-based systems, consistent with the observed mechanical behavior. Overall, the combined mechanical, optical, and thermal analyses demonstrate that the optimal TPU content is matrix-dependent, providing practical guidelines for tailoring PLA- and ABS-based filaments to achieve a controlled balance between stiffness, ductility, and energy absorption in material extrusion applications. Full article

This study aimed to investigate the effects of resveratrol (RES) and carboplatin (CPT), alone and in combination, on cell viability, apoptosis, cell cycle progression, mitochondrial function, and oxidative stress in Y79 retinoblastoma (RB) cells. Particular emphasis was placed on evaluating the synergistic potential of the combination and elucidating the interconnected molecular mechanisms underlying its anticancer effects. Y79 cells were treated with RES, CPT, and their combinations. Cell viability and synergy were assessed using the MTT assay and combination index (CI) analysis. Apoptosis (annexin V/PI), cell cycle distribution (propidium iodide (PI) staining), intracellular ROS production (DCFH-DA), and mitochondrial membrane potential (JC-1) were evaluated by flow cytometry. ROS dependency was further examined using N-acetylcysteine (NAC) pretreatment. Expression levels of apoptosis- and cell cycle-related genes (BAX, BCL-2, CASP3, CASP9, CCNB1, and CDK1) were analyzed by RT-qPCR. Cytoskeletal alterations were assessed by immunocytochemistry. In addition, the antitumor effects of the combination were validated in a three-dimensional (3D) tumor spheroid model. RES and CPT reduced cell viability in a dose- and time-dependent manner and demonstrated synergistic effects (CI < 1) at selected concentrations. Combination treatment significantly increased apoptosis, induced G2/M phase arrest, enhanced ROS accumulation, and promoted mitochondrial depolarization compared with single-agent treatments. NAC pretreatment attenuated ROS generation and partially restored cell viability, supporting a contributory role of oxidative stress in combination-induced cytotoxicity. At the transcriptional level, the RES + CPT combination significantly increased the BAX/BCL-2 ratio and upregulated CASP3 and CASP9 expression, while downregulating CCNB1 and CDK1, consistent with mitochondrial apoptotic activation and G2/M arrest. Immunocytochemical analysis revealed pronounced cytoskeletal disruption and apoptotic morphology in the combination group. Importantly, in the 3D spheroid model, co-treatment markedly reduced spheroid size and viability and enhanced cell death compared with monotherapies. The combination of RES and CPT exerts a synergistic anticancer effect in Y79 RB cells through coordinated mechanisms involving ROS accumulation, mitochondrial dysfunction, caspase activation, and G2/M phase arrest. The attenuation of cytotoxicity by NAC and the validation of efficacy in a 3D tumor spheroid model strengthen the mechanistic relevance of these findings. These results support further preclinical investigation of this combination strategy in in vivo models and normal retinal cell systems. Full article

Binder Jetting 3D Printing (BJ3DP) offers an effective pathway for the rapid fabrication of complex high-entropy alloy (HEA) components. In this study, the macroscopic characteristics, microstructural evolution and mechanical properties of Al_0.5Cr_0.9FeNi_2.5V_0.2 HEA green parts prepared via BJ3DP were investigated under various sintering conditions. Results showed that the relative density of the sintered parts increased significantly with temperature, transitioning from a low density (<90%) at 1300–1330 °C to near-fully dense (~98%) at 1340–1350 °C. Consequently, the mechanical properties were remarkably improved. The yield strength (σ_0.2) increased from 300 MPa to 710 MPa (a 136% increase), and the ultimate tensile strength (σ_b) rose from 310 MPa to 780 MPa (a 148% increase) as sintering temperature rose from 1300 °C to 1350 °C. Microstructural analysis revealed that at lower sintering temperatures, the alloy exhibited high porosity and a non-coherent structure composed of an FCC matrix and Cr-rich BCC phase, with Al/Ni intermetallic compounds distributed around pores. Conversely, at the final sintering stage, pore closure was achieved, and a coherent structure consisting of an FCC matrix and scale-like L1₂ precipitates was formed. Optimal mechanical properties (tensile strength ≥ 700 MPa) were achieved when sintering at 1340 °C, primarily attributed to densification and precipitation strengthening. Full article

The safe and efficient operation of deep-sea towing systems is heavily governed by the highly nonlinear dynamic interaction between the flexible towing cable and complex seabed topographies. While existing studies accurately predict cable dynamics in mid-water or over flat seabeds, the transient responses—such as local stress concentrations and extreme tension fluctuations—induced by discontinuous topographies (e.g., stepped or 3D irregular seabeds) remain inadequately quantified. In this study, we develop an advanced 3D dynamic numerical model combining the lumped-mass finite element formulation with a modified non-linear penalty-based seabed-contact mechanics algorithm. This framework systematically evaluates the tension distribution, bending curvature, and spatial configuration shifts in the cable during the touchdown and detachment phases across inclined, stepped, and 3D seabeds. Quantitative validation against established benchmarks demonstrates robust accuracy. Results indicate that steeper seabed inclinations linearly reduce detachment time but exponentially amplify initial contact tension. Over-stepped terrains, “point-to-line” transient collisions trigger sudden tension spikes exceeding steady-state values by up to 45%. Furthermore, 3D irregular seabeds induce severe multi-directional spatial deformations, precipitating destructive whiplash effects at high towing speeds (e.g., V > 2.2 m/s). These findings provide critical physical insights and a quantitative reference for optimizing tugboat maneuvering strategies and designing fatigue-resistant cables in complex sub-sea environments. Full article

Within the framework of consistent couple stress theory (CCST) and employing Hamilton’s principle, we derive a Galerkin weak formulation to analyze the three-dimensional (3D) size-dependent free vibration characteristics of a simply supported, functionally graded (FG) magneto-electro-elastic (MEE) doubly curved (DC) microscale shell subjected to a uniform temperature change. Incorporating the differential reproducing kernel (DRK) interpolants into the weak formulation, we further develop an element-free Galerkin (EFG) method. The microscale shell of interest is composed of two-phase MEE materials, and its material properties are assumed to vary through its thickness according to a power-law distribution of the volume fractions of the constituents. The results show that the natural frequency solutions obtained using the EFG method are in excellent agreement with the reported 3D solutions for laminated composite and FG-MEE macroscale plates, with the material length-scale parameter and the inverse of the curvature radii set to zero. The effects of the material length-scale parameter, temperature change, inhomogeneity index, and mid-surface radius and length-to-thickness ratios on the FG-MEE microscale shell’s free vibration characteristics in a thermal environment are examined and appear to be significant. Full article

The Wigner quasiprobability, along with some of its essentialproperties, is introduced and discussed in two versions, first covering real canonical variables such as $W(q,p)$ and second a pair of complex conjugate coordinates such as $W(\alpha ,{\alpha }^{*})$. The reconstruction of the density operator $\varrho$ of states is also given. Building upon the Susskind–Glogower concept of quantum phase operators, further aspects of phase operator algebras in the quantum optics of a harmonic oscillator are discussed in relation to the realization of the $su(1,1)$ Lie algebra. Coherent phase states $|\epsilon ⟩$ are introduced in analogy to the common coherent states $|\alpha ⟩$ in two ways, as both eigenstates of certain operators and as states generated from a ground state $|0⟩$ by operators of the Lie group SU(1,1). The limiting transition to the non-normalizable Fritz London phase states $|{\mathrm{e}}^{\mathrm{i}\phi }⟩$ on the unit circle and an (over)-completeness relation for the coherent phase states are derived. The Wigner quasiprobability $W(q,p)$ for the coherent phase states is calculated and graphically represented. From the Wigner quasiprobability, a phase distribution $W\left(\phi \right)$ is calculated by integrating over the radius, and its uncertainty is defined and presented. The Hilbert–Schmidt distance is discussed as a measure of the non-classicality of states, where most of our with Viktor Dodonov work was carried out. Full article

Against the backdrop of dual-carbon goals and resource constraints, the high-value utilization of recycled fine aggregates (RFAs) remains limited, leading to inconsistent engineering performance and insufficient durability. Enzyme-induced carbonate precipitation (EICP) represents a promising low-carbon cementation method, yet its deposition uniformity and cementation efficiency are influenced by the pore structure of granular media and associated mass transfer pathways. This study employs a two-stage experimental design to investigate the synergistic effects of particle size distribution characteristics, represented primarily by d₅₀, and fiber addition on EICP-cemented RFA. Phase I (fiber-free; d₅₀ = 0.67–1.14 mm) results indicate that, across the tested gradation schemes, the CaCO₃ content generally decreased from 9.49% to 7.72% as the representative d₅₀ increased, while the dry density changed only slightly (1.637–1.617 g/cm³). However, the unconfined compressive strength (UCS) decreased from 1000 kPa to 541 kPa (45.9% reduction), indicating that strength is primarily governed by the connectivity of the cementation network rather than solely by the degree of densification. In Phase II, glass fiber (GF), polypropylene fiber (PPF), and jute fiber (JF) were incorporated into the ERFA4 gradation scheme selected for fiber modification. All three systems exhibited a unimodal optimum pattern: the peak CaCO₃ contents reached 10.71% (GF 0.5%), 10.11% (PPF 0.7%), and 11.46% (JF 0.7%), corresponding to peak UCS values of 1917, 1874, and 2450 kPa, respectively. Microscopic analysis suggested that fiber bridging coupled with CaCO₃ deposition may contribute to the formation of a “fiber-CaCO₃-particle” stress-transfer network, which is consistent with the observed enhancements in load-bearing capacity, ductility, and post-peak stability. Full article

Identifying phase transitions in complex many-body systems traditionally necessitates the definition of specific order parameters, a task often requiring prior knowledge of the statistical model and the symmetry-breaking mechanism. In this work, we propose a framework for detecting phase transitions directly from raw (experimental) data without requiring knowledge of the underlying model Hamiltonian, parameters, or pre-defined labels. Inspired by generative modeling in machine learning, our method utilizes autoregressive networks to estimate the normalized probability distribution of the system from raw configuration data. We then quantify the intrinsic sensitivity of this learned distribution to control parameters (such as temperature) to construct a robust indicator of phase transitions. This indicator is based on the expectation of the change in absolute logarithmic probability, derived entirely from the raw data. Our approach is purely data-driven: it takes raw data across varying control parameters as input and outputs the most likely estimate of the phase transition point. To validate our approach, we conduct extensive numerical experiments on the 2D Ising model on both triangular and square lattices, and on the Sherrington–Kirkpatrick (SK) model utilizing raw data generated via Markov Chain Monte Carlo and Tensor Network methods. The results demonstrate that our generative approach accurately identifies phase transitions using only raw data. Our framework provides a general tool for exploring critical phenomena in model systems, with the potential to be extended to realistic experimental data where theoretical descriptions remain incomplete. Full article