Applied Research最新文献

This study examines the nurse rostering problem in the maternity ward of a military hospital to improve operational efficiency while maintaining nurse well-being. In the initial phase, a preemptive 0–1 goal programming model (GP) is introduced to generate feasible nurse duty rosters. This model guarantees fair rotation within specified working-day limits, avoids overlapping assignments for all nurses across all shift types and prevents nurses from working 7 consecutive days. Additionally, three soft constraints are considered, where the model prevents irregular rest patterns, such as isolated work or off days, and ensures equitable workload distribution. Although the 0–1 GP model generates satisfactory schedules, the soft constraint of avoiding isolated working days is not fulfilled. Therefore, the model is further refined by using binary integer programming (BIP), which incorporates nurse categories (senior, community, and health assistants' nurses) as key components in the maternity ward. The soft constraints addressed in an initial model are now treated as hard constraints. Apart from that, this improved model also considers additional hard constraints, including night shift sequencing and recovery, daily-on-call duty, and adequate rest days constraints to improve nurse well-being. Actual duty rosters collected from the head nurse of a maternity ward are used to evaluate the performance of both models. Computational results show that the improved BIP model produces optimal schedules that satisfy operational requirements outlined by Lumut Armed Forces Hospital. For a 14-day scheduling cycle, the model, however, requires a minimum of 15 nurses, with each category comprising at least the average number of nurses to ensure model feasibility. Overall, the findings demonstrate that extending the initial formulation, from a 0–1 GP model to an improved BIP model results in a comprehensive model and improves solution quality for complex healthcare rostering problems.

Dye effluents are a major source of pollution of the water environment and human health. A variety of adsorbents have been used to study the removal of dyes from the aquatic environment. Adsorption is usually used as a simple and effective method among these approaches. Zein, a protein extracted from corn, can be used to easily produce nano- and micro-scale particles. This study is based on using microparticles of zein as an efficient adsorbent to remove dyes from aqueous solutions. Specifically, Orange G and Crystal Violet were chosen as model dyes for this purpose. Different techniques, such as FTIR, TEM, electrophoretic mobility and dye adsorption isotherms, were used to characterise the adsorbent. A design of experiments was used to study the influence of parameters, including pH, time, ionic strength, dye concentration, adsorbent mass, dye type and centrifugation. The optimum conditions of 4.5, 5.0 min, 0.5 mol L⁻¹ NaCl, 10 µmol L⁻¹, 1 mg were obtained for pH, contact time, ionic strength, dye concentration, microparticles of zein mass and centrifuge set to off, respectively. The results showed that on the fourth day 15.5% orange G and 56% crystal violet were removed.

Probiotics are considered live microorganisms that contribute to health benefits by modulating gut microbiota and improving gastrointestinal function. The present study aimed to isolate and characterize indigenous Enterococcus faecium (E. faecium) strains from healthy human fecal samples to assess their probiotic potential. Eleven isolates were selected based on Gram-positive, catalase-negative, nonmotile, and nonhemolytic characteristics, and were identified using MALDI-TOF MS and 16S rRNA gene sequencing. The bacterial isolates were assessed for acid and bile tolerance, antimicrobial activity, cell surface hydrophobicity, tolerance to osmotic (NaCl) and phenolic stress, exopolysaccharide (EPS) production, bile salt hydrolase and DNase activity, cholesterol-lowering capacity, and antioxidant activity. Findings demonstrated strong acid and bile tolerance, high NaCl and phenol resilience, positive BSH and EPS activity, and absence of DNase. Antimicrobial activity was moderate to high against gastrointestinal pathogens, antioxidant activity and surface hydrophobicity ranged from moderate to high, while cholesterol-lowering efficiency varied among strains. Cumulative probiotic potential scores were determined that highlighting strain-specific strengths, signifying that these E. faecium isolates possess multifunctional probiotic attributes suitable for functional foods and nutraceutical applications. Further in vivo studies are necessary to confirm their efficacy and safety for human consumption.

The kinematic behavior of automotive suspension systems, particularly the dynamic control of camber and caster angles, is paramount to achieving desired vehicle handling, stability, and safety characteristics. However, designing complex multi-body systems like the double wishbone suspension presents a high-dimensional, non-linear optimization problem where conventional algorithms are susceptible to premature convergence to suboptimal local minima. This paper introduces a novel, two-stage stacking ensemble optimization framework to overcome this limitation. The underlying kinematic model, including loop-closure and geometric feasibility constraints, is systematically derived using a symbolic mathematics approach to ensure high fidelity and eliminate formulation errors. Through a comparative analysis, the proposed ensemble method is shown to demonstrably outperform standard individual algorithms—Sequential Quadratic Programming (SQP), Interior-Point, and Active-Set—in solution accuracy. The optimized geometry achieves sub-millidegree root-mean-square error in tracking predefined target curves for both camber and caster throughout the suspension's travel. The results validate that this hybrid framework provides a more robust and reliable methodology for the high-fidelity synthesis of complex mechanical systems, offering a powerful tool for modern vehicle design.

In this paper, a novel surface plasmon resonance (SPR) biosensor structure built by zinc oxide (ZnO), silver (Ag), aluminum oxide (Al₂O₃), and black phosphorus (BP) is proposed. The incident light wave wavelength is 632.8 nm. The detection of waterborne bacteria was accomplished through the utilization of the hybrid structure. The transfer matrix method (TMM) is employed to analyze the suggested SPR structure. The angular sensitivity, the figure of merit (FOM), and MR of the proposed construction and other constructions are numerically investigated and compared. To optimize the sensor's performance, the influence of the thickness of each layer on the proposed construction's performance was simulated. Additionally, this study compared the effects on sensitivity, FOM and MR of two-dimensional materials graphene, WS₂, and BP. It is found that the proposed sensing structure's highest sensitivity of 187.18 and 252.18 deg RIU⁻¹ with a high figure of merits of 58.31 and 57.97 RIU⁻¹ for V. cholera and E. coli samples detection, respectively. This sensing structure might provide ideas for the construction of precision detection-suited SPR sensors.

Induction heating-based functional ultra-thin friction layer (FUFL) for removing snow and ice was found severe aggregate spalling due to repeated induction heating. This study tried to reveal how induction heating affects FUFL's resistance to particle spalling through an originally developed assessment through computer image processing. Firstly, AC-5 asphalt mixtures incorporating steel slag and steel fibers were designed. Secondly, an abrasion-spalling accelerating device and an evaluation method based on image processing of MATLAB were proposed to assess the spalling level, reflecting changes of spalling level by measuring the change rate of the black pixel percentage. Finally, a quantitative analysis of how induction heating determines particle spalling degree by ice melting time dependence was performed. Results illustrated that steel slag can enhance the splitting strength, stability, interlayer shear strength, improve the induction heating rate and ice melting effect, but also exacerbate the particle spalling. The developed evaluation method was adequate in assessing aggregate spalling. Aggregate spalling degree of FUFL was positively correlated to the number of freeze-thaw cycles. It was found that the comprehensive road performance, induction heating performance, and spalling performance of FUFL could be optimally enhanced by adding 1% steel fibers.

This study investigated the effect of different drying techniques on the yield and quality of essential oil extracted from Alpinia officinarum rhizomes and their application in functional candy formulation. Fresh galangal rhizomes were subjected to sun drying (SD), tray drying at 50°C, 60°C, and 70°C (TD50, TD60, TD70), and hot air drying (HAD). Among these, TD60 exhibited the best retention of bioactive compounds, with the highest total phenolic content (51.7 mg GAE/g) and flavonoid content (36.7 mg QE/g), along with maximum DPPH radical scavenging activity (73.69%). The essential oil yields obtained via solvent extraction ranged from 6.85 ± 0.06% (SD) to 7.45% (TD60), confirming TD60 as the optimal drying condition. GC-MS analysis identified major bioactive constituents such as 1, 8-cineole, galangin, and methyl cinnamate. The extracted essential oils were incorporated into candy formulations to evaluate their nutraceutical potential. The galangal oil–infused candy exhibited enhanced antioxidant activity (61% inhibition) compared to powder-based (54%) and control candies (13%). Proximate analysis showed moderate moisture (2.26%), with increased fat (0.65 g/100 g) and ash content (0.045 g/100 g). Antimicrobial testing revealed inhibition zones of 35 mm against Staphylococcus aureus and 25 mm against Enterococcus faecalis, indicating strong antibacterial efficacy. Sensory analysis demonstrated high consumer acceptance of the oil-infused candy, and 60-day storage studies confirmed its microbial stability with minimal TPC (7.87 log cfu/g).

Quantum computing leverages the principles of quantum mechanics to perform computations that are infeasible for classical computers. Color centers, which are point defects in a crystal lattice where vacancies in the lattice and/or an impurity atom replace a host atom, exhibit unique optical, electronic, and nuclear spin properties that make them suitable for quantum information and communication processing as well as for quantum computations with quantum memory. Among the color centers, nitrogen-vacancy centers in diamond, the most developed, silicon vacancy (V_Si) centers in silicon carbide (SiC), and boron vacancy (V_B) centers in hexagonal boron nitride (hBN) have emerged as leading candidates. Diamond and SiC material hosts are particularly promising due to the long spin and photon coherence times, optical addressability, compatibility with various quantum operations, while SiC promises higher compatibility with scalable industrial fabrication processing, and 2D materials are better suited for hybrid photonics and electronics integration. This paper provides a detailed overview of the advantages, challenges, and recent advancements in using these color centers for quantum computing. In addition, it discusses other potential color centers of interest, such as silicon (SiV) and germanium (GeV) vacancies in diamond, tin vacancies (SnV) in diamond, chromium and nickel centers in diamond, and rare-earth ions in host materials like yttrium orthosilicate and calcium fluoride. By understanding and utilizing the properties of these diverse color centers, researchers aim to develop more efficient, scalable, and versatile quantum computers, which could lead to hybrid quantum-classical systems that combine the strengths of different platforms and potentially transform fields like cryptography, material science, drug discovery, and complex system simulations (climate modeling, fusion energy).