Search Results (15,551)

Printing with high-performance polymers such as polyether ether ketone (PEEK) and polyetherimide (PEI) presents issues regarding shrinkage and warpage due to elevated temperatures. One method highlighted to mitigate against this is through polymer blending. This study explores the development and characterization of PEEK and PEI blends as filament for fused filament fabrication (FFF) in additive manufacturing. Filaments were produced via melt extrusion using PEEK/PEI weight ratios 100/0, 80/20, 70/30, 60/40, 50/50, 40/60, 20/80, and 0/100 (wt.%). The aim is to identify an optimum blend which enhances printability and maintains mechanical and thermal integrity. The extruded filaments were first characterized through differential scanning calorimetry (DSC) to determine miscibility with all ratios presenting a single glass transition temperature. Samples were then 3D-printed and assessed through mechanical testing, DSC, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The PEEK/PEI 80/20 (wt.%) blend was recognized as the optimum blend for maintaining crystallinity (35%) as well as good mechanical properties, averaging ultimate tensile strengths (UTSs) of 75.6 MPa and a Young’s modulus of 1338 MPa. Thermal properties also improved while warpage reduced and printability improved. Full article

Reusable enzyme carriers are valuable for proteomic workflows, yet many supports are expensive or lack robustness. This study describes the covalent immobilization of recombinant trypsin on micrometer-sized corundum particles and assesses their performance in protein digestion and antibody analysis. The corundum surface was cleaned with potassium hydroxide, silanized with 3-aminopropyltriethoxysilane and activated with glutaraldehyde. Recombinant trypsin was then attached, and the resulting imines were reduced with sodium cyanoborohydride. Aromatic amino acid analysis (AAAA) estimated an enzyme loading of approximately 1 µg/mg. Non-specific adsorption of human plasma proteins was suppressed by blocking residual aldehydes with a Tris-glycine-lysine buffer. Compared with free trypsin, immobilization shifted the temperature optimum from 50 to 60 °C and greatly improved stability in 1 M guanidinium hydrochloride. Activity remained above 80% across several reuse cycles, and storage at 4 °C preserved functionality for weeks. When applied to digesting the NISTmAb, immobilized trypsin provided peptide yields and sequence coverage comparable to soluble enzyme and outperformed it at elevated temperatures. MALDI-TOF MS analysis of Herceptin digests yielded fingerprint spectra that correctly identified the antibody and achieved >60% sequence coverage. The combination of low cost, robustness and analytical performance makes corundum-immobilized trypsin an attractive option for research and routine proteomic workflows. Full article

In 2024, four papers that presented four different solution approaches for the knapsack problem with forfeits (KPF) appeared in the OR literature. However, none of these four solution approaches compared their performance to the other three on a standard set of 120 KPF test instances. In this short paper, both empirically and statistically, these four KPF solution approaches are compared. Furthermore, by using the solutions from the best method (HESM) among the four to initialize Gurobi, bounded solutions are obtained. For the 120 KPF test instances, this simple hybrid approach resulted in solutions that, on average, were guaranteed to be within 7% of the optimums. This type of guarantee does not exist for other KPF solution methods in the literature. It is very important for operations research (OR) practitioners that need to ensure the value of their solutions to management to have some guarantee of the quality of these solutions. Full article

Alumina (Al₂O₃) reinforced copper matrix composites are widely used in the electronic industry, rail transit, and other fields due to their excellent electrical conductivity, ductility, and wear resistance. However, due to problems such as non-wetting and thermal expansion differences between alumina and Cu, weak interfacial bonding can easily reduce physical and thermal properties. A uniform silver layer was deposited on Al₂O₃ via chemical plating to enhance interface bonding with copper. Al₂O₃@Ag/Cu composites with 1–3 wt.% Al₂O₃ were prepared by rapid hot-press sintering. The effects of plating temperature and Al₂O₃ content on microstructure and properties were investigated. The results show that the optimum coating temperature is 25 °C, and a thin and uniform silver coating can be formed. This effectively improved Al₂O₃–Cu interface bonding while maintaining 77.8% of copper’s thermal conductivity (320.7 W/(m·K)). The composites showed improved wear resistance with increasing Al₂O₃ content. At 3 wt.% Al₂O₃@Ag, the wear rate was 3.36 × 10⁻⁵ mm³/(N·m), 84.4% lower than pure copper, with plow groove wear as the main mechanism. Full article

Using raw milk in cheesemaking poses several risks and often requires higher salt levels. Gel brine is a promising brining method to reduce salt and to prevent excessive softening, yet it was not employed to raw milk cheese before. In this study, the impact of ripening in gel brine—prepared by adding selected thickeners (gelatin and carrageenan) to a 12% salt brine—on the composition, proteolysis, texture, and microbiological properties of raw milk cheese was examined over 120 days. The aim was to assess the potential of gel brine to shorten the ripening time of raw milk cheese at a relatively low salt concentration while maintaining acceptable quality parameters. Response surface methodology was used to determine the optimum ripening time and thickener concentrations required to achieve target microbial counts, proteolysis, and moisture levels. The addition of stabilizers did not significantly influence the overall composition of the cheese, except for salt in dry matter. Stabilizers also limited the increase in trichloroacetic acid-soluble nitrogen (TCA-SN) during storage and led to a marked reduction in Escherichia coli counts. Texture profile analysis results were significantly affected (p < 0.05). The optimum conditions were estimated as 0.9% carrageenan, 0.8% gelatin, and 35 days of ripening. Full article

The extensive application of carbon fibers (CFs) and their composites in aerospace and electronics has established the optimization of their electrical conductivity as a critical research priority. Conventional electrodeposition techniques are limited by CF inherent chemical inertness and low surface energy, which increase the energy barrier for copper deposition, leading to defective coatings and weakened interfacial bonding. This study demonstrated that sodium hypophosphite (NaH₂PO₂) enhances CF copper deposition efficiency through concentration gradient experiments (0–30 g/L), revealing its modulation of deposition kinetics, crystallographic evolution, and interfacial adhesion strength. Electrochemical analysis showed that NaH₂PO₂ accelerates initial copper nucleation by reducing activation energy without forming complexes. Increasing its concentration expanded monofilament diameter from 8.55 to 9.26 μm post-deposition, with copper loading rising 28.89%. XRD analysis identified 20 g/L as the optimum for crystallinity, producing maximal grain size (8.27 nm) and predominant (111) orientation. This structure achieved a conductivity of 1.63 × 10³ S·cm⁻¹ (55.24% enhancement) and improved breaking force from 13.54 to 14.57 cN. Adhesion tests showed that the 20 g/L group maintained stability comparable to the control. These results suggest that 20 g/L is the preferred concentration balancing conductivity enhancement with mechanical stability. This approach offers a novel strategy for fabricating highly conductive CF composites. Full article

Accurate parameter estimation of photovoltaic (PV) models is fundamentally a challenging nonlinear optimization problem, characterized by strong nonlinearity, high dimensionality, and multiple local optima. These characteristics significantly hinder the convergence accuracy, stability, and efficiency of conventional metaheuristic algorithms when applied to PV parameter identification. Although the enterprise development (ED) optimization algorithm has shown promising performance in various optimization tasks, it still suffers from slow convergence, limited solution precision, and poor robustness in complex PV parameter estimation scenarios. To overcome these limitations, this paper proposes a multi-strategy enhanced enterprise development (MEED) optimization algorithm for high-precision PV model parameter estimation. In MEED, a hybrid initialization strategy combining chaotic mapping and adversarial learning is designed to enhance population diversity and improve the quality of initial solutions. Furthermore, a historical trend-guided position update mechanism is introduced to exploit accumulated search information and accelerate convergence toward the global optimum. In addition, a mirror-reflection boundary control strategy is employed to maintain population diversity and effectively prevent premature convergence. The proposed MEED algorithm is first evaluated on the IEEE CEC2017 benchmark suite, where it is compared with 11 state-of-the-art metaheuristic algorithms under 30-, 50-, and 100-dimensional settings. Quantitative experimental results demonstrate that MEED achieves superior solution accuracy, faster convergence speed, and stronger robustness, yielding lower mean fitness values and smaller standard deviations on the majority of test functions. Statistical analyses based on Wilcoxon rank-sum and Friedman tests further confirm the significant performance advantages of MEED. Moreover, MEED is applied to the parameter estimation of single-diode and double-diode PV models using real measurement data. The results show that MEED consistently attains lower root mean square error (RMSE) and integrated absolute error (IAE) than existing methods while exhibiting more stable convergence behavior. These findings demonstrate that MEED provides an efficient and reliable optimization framework for PV model parameter estimation and other complex engineering optimization problems. Full article

The gut microbiome evolves in response to host development, health state, lifestyle, nutrition, and microbial interactions. The survival of gut microbiota depends on its ability to utilize its host-indigestible complex oligosaccharides. Certain gut microbes produce glycosidases that cleave N-glycoproteins to release N-glycans that are then used as a carbon source. However, commercial glycosidases are inefficient and, thus, require improved deglycosylation strategies to study their functions and scale up their production. Therefore, the main objective of this study was to recombinantly produce and characterize the novel endo-β-N-acetylglucosaminidase 2 (EndoBI-2) from Bifidobacterium longum subsp. infantis (B. infantis) and to evaluate its enzymatic performance for controlled N-glycan release. Furthermore, the optimum reaction conditions for EndoBI-2 were investigated on model glycoprotein RNAse B using model glycoprotein. The released N-glycans were profiled by hydrophilic interaction liquid chromatography-fluorescence detection-quadrupole time-of-flight tandem mass spectrometry (HILIC-FLD-QTOF-MS/MS). We demonstrated that EndoBI-2 possesses a strong temperature tolerance and efficiently cleaves N-glycans under mild reaction conditions, exhibiting high activity at pH 5. These findings highlight EndoBI-2 as a robust and efficient biocatalyst for the production of bioactive N-glycans from diverse N-glycoproteins, with potential applications in glycobiotechnology. Full article

This study analyzed how different downward loads and rotational kinematics influence NiTi rotary instrumentation outcomes. Heat-treated NiTi instruments were used to prepare extracted human single-rooted premolars with a moderate canal curvature. Instrumentation was performed using an automated endodontic instrumentation device with controlled downward loading and torque/force sensing, under different downward load settings (1, 2, and 3 N), employing either continuous rotation (CR) or optimum torque reverse (OTR) motion, which is a torque-sensitive reciprocation. Instrumentation was completed without instrument fracture or ledge formation in all six groups. OTR-3N specimens displayed a significantly lower upward force (i.e., screw-in force) than OTR-2N specimens (p < 0.05). OTR-1N specimens required a significantly longer instrumentation time than CR-1N specimens and the other OTR specimens (p < 0.05). At 1 mm from the apex, CR-2N specimens showed a significantly larger canal-centering ratio (i.e., larger deviation) than OTR-2N specimens (p < 0.05). Overall, applying a downward load of 2–3 N in OTR mode provided shaping efficiency similar to CR, but with a reduced screw-in force and enhanced canal-centering in the apical region, supporting the use of OTR as a promising alternative to CR for curved canal preparation using heat-treated NiTi instruments. Full article

The sailfish optimizer is a recent swarm-intelligence-based optimization algorithm which mimics the hunting behavior of sailfish in the ocean. It consists of two types of populations, namely, sailfish and sardine, where sailfish represent the candidate solutions and sardines freely maneuver in the search space. Existing research studies have shown that the sailfish optimizer suffers from limited global exploration capability, with local optimum stagnation and slow convergence speed. To address these limitations, an improved sailfish optimizer, namely, the Multi-Strategy Sailfish Optimizer, is proposed in this study. This improved version incorporates a modified search strategy for both sailfish and sardines, a non-linear attack power parameter, an improved hunting procedure, and a dynamic sardine population. The impact of all suggested improvements is analyzed experimentally. Several experiments with single-objective problems presented at the Congress on Evolutionary Computation in 2022 are performed to prove the effectiveness and efficiency of the proposed algorithm. This improved algorithm is compared with well-known optimization algorithms, such as the whale optimization algorithm, the sine–cosine algorithm, etc., and improved variants of those algorithms. A convergence behavior analysis is also performed using convergence graphs. Furthermore, the significance of the work is statistically validated. The analysis indicates that the Multi-Strategy Sailfish Optimizer performs significantly better than other optimization algorithms. It is also applied to solve the tension/compression spring design problem and the mobile robot path planning problem. Full article

The optimization of bioactive compound extraction from medicinal herbs is critical for developing functional food ingredients with substantiated health benefits. This study employed response surface methodology (RSM) and partial least squares (PLS) regression to maximize polyphenol recovery and antioxidant capacity from five medicinal herbs (Helichrysum stoechas, Chelidonium majus, Mentha pulegium, Artemisia absinthium, and Adiantum capillus-veneris). A custom experimental design assessed the effects of herb identity, extraction technique, and solvent-to-solid ratio on total polyphenolic content (TPC), total flavonoid content (TFC), ferric reducing antioxidant power (FRAP), and DPPH radical scavenging activity. The PLS compromise optimum was identified for M. pulegium using 60% ethanol at 55 mL/g, yielding 37.54 ± 2.10 mg GAE/g dw TPC, 21.62 ± 1.15 mg RtE/g dw TFC, 334.38 ± 12.37 µmol AAE/g dw FRAP, and 262.67 ± 9.46 µmol AAE/g dw DPPH. HPLC-DAD profiling revealed 18 polyphenolic compounds (10.22 ± 0.34 mg/g dw), dominated by kaempferol-3-O-β-rutinoside, protocatechuic acid, and luteolin-7-O-glucoside. These compounds contribute complementary mechanisms: protocatechuic acid modulates oxidative and antioxidant pathways, kaempferol-3-O-β-rutinoside exerts cardioprotective and anti-inflammatory effects via VEGF-C binding, and luteolin-7-O-glucoside suppresses NF-κB-mediated inflammatory signaling. Principal component analysis (PCA) explained 84.8% of variance, clearly separating optimized from non-optimized extracts, while PLS confirmed strong correlations between specific phenolics and antioxidant indices. Overall, this integrated chemometric approach demonstrates that data-driven optimization can deliver phenolic-rich herbal extracts with robust and balanced antioxidant potential for functional food applications. Full article

The hot deformation behavior of 6A82 aluminum alloy with a copper content of approximately 0.46 wt% was investigated by uniaxial compression tests in a temperature range of 320–530 °C and a strain rate range of 0.01–10 s⁻¹. The effects of deformation heating and friction on flow stress were analyzed and corrected. The results revealed that the reduction in flow stress due to deformation heating is more pronounced at high strain rates (≥1 s⁻¹) and low temperatures (≤390 °C) compared to other deformation conditions. The corrected data illustrated that deformation heating has a more significant influence on flow stress than friction. Hot deformation activation energy (Q) decreased from 322.63 to 236.22 kJ/mol with increasing strain. Based on the corrected flow stress, the evolution of processing maps and microstructural characterization were analyzed to evaluate workability and identify flow instabilities. It was found that strain has a slight effect on the efficiency of power dissipation, whereas the instability parameter varies considerably with increasing strain. The corresponding processing maps showed that the unstable regions undergo more complex variations than the stable regions throughout the hot deformation process. An optimum hot working domain was identified in the temperature range of 440–530 °C and strain rate of 0.01–0.37 s⁻¹. Under these deformation conditions, fine grains and uniformly distributed particles are formed through extensive dynamic recrystallization and coarsening of second phase particles, which facilitate dislocation motion and promote the formation of a sub-grain boundary. Full article

The impact of nitrogen on harmful algal blooms (HABs) and functions of biota in marine ecosystems under eutrophication is a topical issue of growing importance. The article aimed at describing the diversity of planktonic bloom-forming dinoflagellates in the SW Baltic Sea coastal waters under variable eutrophication. The analysis of 44 year-long database revealed 82 dinoflagellate species and demonstrated diversity patterns of ten common bloom-forming species, including seven mixotrophs from the genera Prorocentrum, Dinophysis, and Ceratium, under variable eutrophication evaluated using total nitrogen (TN) content in water. Based on the Intermediate Disturbance Hypothesis (IDH), we presumed those coastal waters with total nitrogen concentrations that are optimal to dinoflagellates to host greater taxonomic diversity compared to areas with non-optimum TN content. The results showed that the highest dinoflagellate species richness was associated with much lower TN concentrations than the optimum values for these species. Thus, our findings disagreed with the IDH. We suggested and discussed possible reasons of this inconsistency, including algal growth rates and disturbance frequency. We also updated the classification of eutrophication levels in the Baltic Sea based on the distribution of TN content and diversity of HAB-forming dinoflagellates. The results can contribute to predictive assessment of HABs under growing eutrophication. Full article

Metropolitan service-placement optimization is computationally challenging under strict evaluation budgets and regulatory constraints. Existing approaches either neglect capacity constraints, producing infeasible solutions, or employ population-based metaheuristics requiring hundreds of evaluations—beyond typical municipal planning resources. We introduce a two-stage optimization framework combining Bayesian optimization with domain-informed heuristics to address this constrained, mixed discrete–continuous problem. Stage 1 optimizes continuous service area allocations via the Tree-structured Parzen Estimator with empirical gradient prioritization, reducing effective dimensionality from 81 services to 10–15 per iteration. Stage 2 converts allocations into discrete unit placements via efficiency-ranked bin packing, ensuring regulatory compliance. Evaluation across 35 benchmarks on Saint Petersburg, Russia (117–3060 decision variables), demonstrates that our method achieves 99.4% of the global optimum under a 50-evaluation budget, outperforming BIPOP-CMA-ES (98.4%), PURE-TPE (97.1%), and NSGA-II (96.5%). Optimized configurations improve equity (Gini coefficient of 0.318 → 0.241) while maintaining computational feasibility (2.7 h for 109-block districts). Open-source implementation supports reproducibility and facilitates adoption in metropolitan planning practice. Full article

Magnesite tailings are by-products of magnesite mining, yet their utilization rate remains extremely low. Although previous studies have explored their basic physical properties and potential use in cementitious or geotechnical materials, research on cement-stabilized magnesite tailings-particularly regarding their mechanical behavior, engineering applicability, and microstructural evolution-remains limited. Key scientific gaps include the lack of systematic evaluation of their compaction characteristics, strength development, stiffness evolution, and bearing capacity, as well as insufficient understanding of the stabilization mechanisms governing their performance. Addressing these gaps is essential for assessing their feasibility as road construction materials. In this study, magnesite tailings were selected as the primary raw material and mixed with ordinary Portland cement to prepare mixtures for evaluating their suitability as highway subgrade fillers. The compaction characteristics, unconfined compressive strength (UCS), ultrasonic pulse velocity (UPV), and California Bearing Ratio (CBR) of the mixtures were systematically examined. Furthermore, the evolution of composition and stabilization mechanisms of the mixtures was analyzed using X-ray diffraction, scanning electron microscopy, and thermogravimetric analysis. The results show that cement incorporation effectively improves the poor particle gradation of magnesite tailings, leading to a denser and more homogeneous structure. Adding 7% cement increases the maximum dry density and optimum moisture content by 3.7% and 5.1%, respectively. The unconfined compressive strength rises by 100.9–126.3% within 3–28 days, and the maximum uniaxial stress is 119.6% higher than that of the 1% cement mixture. These improvements demonstrate the potential of cement-stabilized magnesite tailings as a sustainable subgrade material and provide insight into their microstructural and mechanical behavior. Full article