Search Results (5,462)

With the increasing demand for urban rail transit capacity, shield tunneling has become the predominant method for constructing underground metro systems in densely populated cities. However, the spatial interaction between shield tunnels and adjacent retaining structures poses significant engineering challenges, potentially leading to excessive ground settlement, structural deformation, and even stability failure. This study systematically investigates the deformation behavior and associated risks of retaining systems during adjacent shield tunnel construction. An orthogonal multi-factor analysis was conducted to evaluate the effects of grouting pressure, grout stiffness, and overlying soil properties on maximum surface settlement. Results show that soil cohesion and grouting pressure are the most influential parameters, jointly accounting for over 72% of the variance in settlement response. Based on the numerical findings, a Bayesian network model was developed to assess construction risk, integrating expert judgment and field monitoring data to quantify the conditional probability of deformation-induced failure. The model identifies key risk sources such as geological variability, groundwater instability, shield steering correction, segmental lining quality, and site construction management. Furthermore, the effectiveness and cost-efficiency of various grouting reinforcement strategies were evaluated. The results show that top grouting increases the reinforcement efficiency to 34.7%, offering the best performance in terms of both settlement control and economic benefit. Sidewall grouting yields an efficiency of approximately 30.2%, while invert grouting shows limited effectiveness, with an efficiency of only 11.6%, making it the least favorable option in terms of both technical and economic considerations. This research provides both practical guidance and theoretical insight for risk-informed shield tunneling design and management in complex urban environments. Full article

Background: Helcococcus kunzii, a facultative anaerobe and Gram-positive coccus, has been documented as a cunning pathogen, mainly in immunocompromised individuals, as evidenced by recent clinical and microbiological reports. It has been associated with a variety of polymicrobial infections, comprising diabetic foot ulcers, prosthetic joint infections, osteomyelitis, endocarditis, and bloodstream infections. Despite its emerging clinical relevance, no licensed vaccine or targeted immunotherapy currently exists for H. kunzii, and its rising resistance to conventional antibiotics presents a growing public health concern. Objectives: In this study, we employed an integrated subtractive proteomics and immunoinformatics pipeline to design a multi-epitope subunit vaccine (MEV) candidate against H. kunzii. Initially, pan-proteome analysis identified non-redundant, essential, non-homologous, and virulent proteins suitable for therapeutic targeting. Methods/Results: From these, two highly conserved and surface-accessible proteins, cell division protein FtsZ and peptidoglycan glycosyltransferase FtsW, were selected as promising vaccine targets. Comprehensive epitope prediction identified nine cytotoxic T-lymphocyte (CTL), five helper T-lymphocyte (HTL), and two linear B-cell (LBL) epitopes, which were rationally assembled into a 397-amino-acid-long chimeric construct. The construct was designed using appropriate linkers and adjuvanted with the cholera toxin B (CTB) subunit (NCBI accession: AND74811.1) to enhance immunogenicity. Molecular docking and dynamics simulations revealed persistent and high-affinity ties amongst the MEV and essential immune receptors, indicating a durable ability to elicit an immune reaction. In silico immune dynamic simulations predicted vigorous B- and T-cell-mediated immune responses. Codon optimization and computer-aided cloning into the E. coli K12 host employing the pET-28a(+) vector suggested high translational efficiency and suitability for bacterial expression. Conclusions: Overall, this computationally designed MEV demonstrates favorable immunological and physicochemical properties, and presents a durable candidate for subsequent in vitro and in vivo validation against H. kunzii-associated infections. Full article

Opuntia stricta var. dillenii (OPD) fruits are rich in betalains and phenolic compounds, which are recognized for their potential health-promoting properties. This study focuses on the optimization of pulsed electric field (PEF)-assisted solid–liquid green extraction (SLE) from OPD whole fruit, using response surface methodology (RSM) experimental design to obtain green extracts rich in bioactive compounds. The optimal PEF pre-treatment conditions (electric field strength and energy input) were determined based on the cell disintegration index (Zp), followed by optimizing SLE conditions (temperature, time, and ethanol content). High-performance liquid chromatography (HPLC-DAD-ESI-Qtof) was used to characterize the individual bioactive compound profile of the obtained OPD green extracts. Results showed that optimal PEF pre-treatment conditions were at 10.5 kJ/kg and 5 kV/cm, followed by SLE at 35 °C for 165 min, using water as the solvent. Conventional optimal SLE conducted at 45 °C, 8% ethanol, and 128 min was applied as the control process. The combined PEF-assisted SLE process enhanced total betalain and phenolic compound yields by 61% and 135%, respectively. Antioxidant activities (DPPH by 145%, FRAP by 28%) and anti-inflammatory potential (hyaluronidase inhibition by 19%) were also significantly improved. This study underscores the potential use of a PEF pre-treatment to improve obtaining green extracts rich in bioactive compounds with high biological activities from OPD whole fruits, using water as a solvent. Full article

Warpage is among the most prevalent defects affecting injection molded parts. In this study, we aimed to develop methods to minimize warpage through mold design. Common strategies include matching the cavity geometry to the intended shape of the part, adjusting cavity dimensions to offset material shrinkage, and optimizing the cooling system and critical injection molding parameters. These optimization methods can offer significant improvements, but recently introduced methods that optimize the molded part and mold cavity shape result in higher levels of warpage reduction. In these methods, optimization of the shape of the molded part is achieved by shaping it in the opposite direction of warpage—a method known as inverse contouring. Inverse contouring of molded parts is a design technique in which mold cavities are intentionally modified to incorporate compensatory geometric deviations in regions anticipated to exhibit significant warpage. The final result after molded part ejection and warpage is a significant reduction in deviations between the warped and reference molded part geometries. In this study, a two-step approach for minimizing warpage was used: the first step was optimizing the most significant injection molding parameters, and the second was inverse contouring. In the first step, Response Surface Methodology (RSM) and Autodesk Moldflow Insight 2023 simulations were used to optimize molded part warpage based on three processing parameters: melt temperature, target mold temperature, and coolant temperature. For improved accuracy, a Computer-Aided Design (CAD) model of the warped molded part was exported into ZEISS Inspect 2023 software and aligned with the reference CAD geometry of the molded part. The maximal warpage value after the initial simulation was 1.85 mm based on Autodesk Moldflow Insight simulations and 1.67 mm based on ZEISS Inspect alignment. After RSM optimization, the maximal warpage was 0.73 mm. In the second step, inverse contouring was performed on the molded part, utilizing the initial injection molding simulation results to further reduce warpage. In this step, the CAD model of the redesigned, inverse-contoured molded part was imported into Moldflow Insight to conduct a second iteration of the injection molding simulation. The simulation results were exported into ZEISS Inspect software for a final analysis and comparison with the reference CAD model. The warpage values after inverse contouring were reduced within the range of ±0.30 mm, which represents a significant decrease in warpage of approximately 82%. Both steps are presented in a case study on an injection molded part made of polybutylene terephthalate (PBT) with 30% glass fiber (GF). Full article

Graphene, owing to its exceptionally high specific surface area, abundant surface functional groups, and outstanding biocompatibility, exhibits tremendous potential in the development of nanodrug delivery systems. This review systematically outlines the latest research advancements regarding graphene and its derivatives in drug loading, targeted delivery, and smart release. It covers delivery strategies and mechanisms for various types of drugs, including small molecules and macromolecules, with a particular emphasis on their applications in major diseases such as cancer, neurological disorders, and infection control. The article also discusses stimulus-responsive release mechanisms, such as pH-responsiveness and photothermal responsiveness, and highlights the critical role of surface functionalization of graphene and its derivatives in enhancing therapeutic efficacy while reducing systemic toxicity. Furthermore, the review evaluates key challenges to the clinical translation of graphene-based materials, including safety, toxicity, and metabolic uncertainties. It points out that future research should focus on integrating structural modulation of materials with biological behavior to construct intelligent nanoplatforms featuring biodegradability, low immunogenicity, and precise therapeutic targeting. The aim of this paper is to provide theoretical insights and technical guidance for the customized design and precision medicine applications of graphene and its derivative-based drug delivery systems. Full article

This study employed response surface methodology (RSM) to optimize admixture proportions in 3D-printed cementitious materials, with the aim of enhancing printability. Based on preliminary tests, three additives, namely, an accelerator, hydroxypropyl methylcellulose (HPMC), and polycarboxylate superplasticizer (PCE), were incorporated to evaluate their effects on flowability and dynamic yield stress. A Box–Behnken central composite design was used to establish a mathematical model, followed by the RSM-driven optimization of mix proportions. The optimized formulation (0.32% accelerator, 0.24% HPMC, and 0.23% PCE) achieved a flowability of 147.5 mm and a dynamic yield stress of 711 Pa, which closely matched the predicted values and fulfilled the printability requirements, thus establishing RSM as an effective approach for designing printable cementitious composites. This approach established an RSM-based optimization framework for mix proportion design. These findings offer a mechanistic framework for rational 3DPC mixture design, combining theoretical insights and practical implementation in additive construction. Full article

The pods from Neltuma ruscifolia (vinal), an underutilized species, are rich in bioactive functional compounds. However, the extraction procedures to obtain the highest proportion of these compounds, considering sustainability aspects, have not been optimized. This study aimed to optimize and compare three affordable extraction methods—dynamic maceration (DME), ultrasound-assisted extraction (UE), and microwave-assisted extraction (ME)—to obtain enriched extracts. The effects of temperature, ethanol-to-water ratio in the solvent, extraction time, and frequency (for ME) were evaluated using a Box–Behnken design and response surface methodology to optimize total polyphenolic content (TPC), total flavonoids (TF), and antioxidant capacity (DPPH). Energy consumption and carbon footprints were also assessed, and phenolic compounds in the optimized extracts were identified by HPLC. The ethanol-to-water ratio emerged as the most influential factor, showing synergistic effects with both time and temperature, enabling optimal yields at intermediate ethanol concentrations. Gallic acid, rutin, and theobromine were found to be the most abundant components, followed by cinnamic, caffeic, and chlorogenic acids. Although UE exhibited the lowest energy consumption (0.64 ± 0.03 Wh/mg of TPC), the simple and easily implementable DME—optimized at 40 min, 50 °C, and 42% ethanol—proved to be the most efficient method, combining high extractive performance (TPC 1432 mg GAE/100 g Dw), reduced solvent use, and intermediate energy efficiency (1.84 Wh/mg of TPC). These findings highlight the potential of vinal as a natural source of bioactive ingredients obtained through simple and cost-effective techniques adaptable to small producers while underscoring the value of experimental design in optimizing sustainable extraction technologies and elucidating the interactions between key processing factors. Full article

In this paper, a method to reduce mutual coupling between an E-plane and H-plane coupled microstrip patch antenna is presented. Two dual differentially fed square patches are designed in a 1 × 2 antenna array configuration. To minimize mutual coupling and its effects, coupled split-ring resonators (SRRs) are designed, characterized and positioned between the patches. Circular SRRs are designed and coupled to produce a band-stop response to suppress surface waves propagating within the dielectric substrate while enhancing isolation. Mutual coupling interactions and the suppression mechanism are discussed in relation to the patches and SRRs. The patch radiators are dual differentially fed to achieve polarization diversity. E- and H-planes decoupling is achieved between the two patches throughout their bandwidth while maintaining good antenna performance. A prototype of the antenna array and the SRR is fabricated and measured to validate the decoupling approach. With a separation distance of 0.49$\lambda$ between the patches, the measured S-parameters show an impedance bandwidth of |S11|≤−10 dB, covering 9.27–9.46 GHz, and −38 dB and −35 dB mutual coupling for E- and H-planes, respectively, are observed throughout the antenna operating bandwidth. Full article

Three-dimensional (3D) surface-enhanced Raman scattering (SERS) substrates have demonstrated remarkable abilities of ultrasensitive and reproducible molecular detection. The combination of both electromagnetic and chemical enhancement processes, light trapping, and multiple scattering effects of 3D structures are what enhance their performance. The principles of underlying enhancements are summarized systematically, and the main types of 3D substrates—vertically aligned nanowires, dendritic and fractal nanostructures, porous frameworks and aerogels, core–shell and hollow nanospheres, and hierarchical hybrid structures—are categorized in this review. Advances in fabrication techniques, such as template-assisted growth, electrochemical and galvanic deposition, dealloying and freeze-drying, self-assembly, and hybrid integration, are critically evaluated in terms of structural tunability and scalability. Novel developments in the field of biosensing are also highlighted, including non-enzymatic glucose sensing, tumor biomarker sensing, and drug delivery. The remaining limitations, such as low reproducibility, mechanical stability, and substrate standardization, are also noted, and future directions, such as stimuli-responsive designs, multifunctional hybrid platforms, and data-driven optimization strategies of SERS technologies, are also included. Full article

A miniaturised bionic electronic nose system was developed to solve the problems of expensive equipment and long response time for soil pesticide residue detection. The structure of the bionic electronic nasal cavity is designed based on the spatial structure and olfactory principle of the sturgeon nasal cavity. Through experimental study, the structure of the nasal cavity of the sturgeon was extracted and analyzed. The 3D model of the bionic electronic nasal cavity was constructed and verified by Computational Fluid Dynamics (CFD) simulation. The results show that the gas flow distribution in the bionic chamber is more uniform than that in the ordinary chamber. The airflow velocity near the sensor in the bionic chamber is lower than in the ordinary chamber. The eddy current intensity near the bionic chamber sensor is 2.29 times that of the ordinary chamber, further increasing the contact intensity between odor molecules and the sensor surface and shortening the response time. The 10-fold cross-validation method of K-Nearest Neighbor (K-NN), Random Forest (RF) and Support Vector Machine (SVM) was used to compare the recognition performance of the bionic electronic nasal cavity with that of the ordinary electronic nasal cavity. The results showed that, when the bionic electronic nose detection system identified the concentration of pesticide residues in soil, the recognition rate of the above three recognition algorithms reached 97.3%, significantly higher than that of the comparison chamber. The bionic chamber electronic nose system can improve the detection performance of electronic noses and has a good application prospect in soil pesticide residue detection. Full article

Traditional fluted roller seed metering devices exhibit unstable seeding rates during forage seed mixed sowing. To address this issue, a new seed metering device was designed based on the agronomic requirements of forage seed mixing and the structural characteristics of fluted roller mechanisms. The discrete element method (DEM) was employed to numerically simulate the movement of particles within the seed metering device. Single-factor experiments identified optimal parameter ranges for the seed metering device: a metering shaft speed of 10–20 r/min, a seed inlet width of 8–24 mm, and a seed outlet height of 10–20 mm. A response surface methodology (RSM) experiment was then designed using Design-Expert 13 software. The results yielded optimal operating parameters: a metering shaft speed of 18.9 r/min, a seed inlet width of 9.3 mm, and a seed outlet height of 14.4 mm. The field experiment validated the seeding performance with the optimal parameter combination. The coefficient of variation (CV) for the first-class seed (CV₁) was 4.16%, and for the second-class seed (CV₂) it was 2.98%, both of which met the requirements for mixed sowing of forage. Full article

To improve chip removal efficiency and drilling performance in oxygen-free copper, a multi-objective optimization of gun drilling process parameters was conducted using a response surface methodology and a genetic algorithm. The Box–Behnken Design (BBD) response surface analysis method was employed to evaluate the effects of feed rate, cutting speed, and cutting fluid pressure on the chip evacuation coefficient and chip volume ratio. Experimental results indicate that among the three factors, the feed rate has the most significant influence, followed by the cutting speed and the cutting fluid pressure. Additionally, the interaction between the cutting speed and the cutting fluid pressure notably impacts both chip evacuation and chip volume ratio. Using response surface modeling, a three-dimensional predictive model was developed. Based on this fitted model, optimal gun drilling parameters were identified through genetic algorithm optimization, minimizing the chip evacuation coefficient and chip volume ratio to achieve an optimized machining configuration. The optimal drilling parameters were identified as a feed rate of 0.019 mm/r, a spindle speed of 47.1 m/min, and a cutting fluid pressure of 2.4 MPa. Under these conditions, a chip evacuation coefficient of 3.2951 and a chip volume ratio of 3.3345 were achieved. The resulting chips predominantly exhibited a C-shaped morphology, accompanied by smooth and efficient evacuation. Full article

Regional rapid forecasting of vertical ocean temperature profiles is increasingly important for marine aquaculture, as these profiles directly affect habitat management and the physiological responses of farmed species. However, observational temperature profile data with sufficient temporal resolution are often unavailable, limiting their use in regional rapid forecasting. In addition, traditional numerical ocean models suffer from intensive computational demands and limited operational flexibility, making them unsuitable for regional rapid forecasting applications. To address this gap, we propose PICA-Net (Physics-Inspired CNN–Attention–BiLSTM Network), a hybrid deep learning model that coordinates large-scale satellite observations with local-scale, continuous in situ data to enhance predictive fidelity. The model also incorporates weak physical constraints during training that enforce temporal–spatial diffusion consistency, mixed-layer homogeneity, and surface heat flux consistency, enhancing physical consistency and interpretability. The model uses hourly historical inputs to predict temperature profiles at 6 h intervals over a period of 24 h, incorporating features such as sea surface temperature, sea surface height anomalies, wind fields, salinity, ocean currents, and net heat flux. Experimental results demonstrate that PICA-Net outperforms baseline models in terms of accuracy and generalization. Additionally, its lightweight design enables real-time deployment on edge devices, offering a viable solution for localized, on-site forecasting in smart aquaculture. Full article

To stimulate the progress of clean fracturing fluid systems, an innovative erucyl ultra-long-chain gemini surfactant (EUCGS) was devised and manufactured during the course of this study. The target product was successfully prepared via a two-step reaction involving erucyl primary amine, 3-bromopropionyl chloride, and 1,3-bis(dimethylamino)propanediol, with an overall yield of 78.6%. FT-IR and ¹H NMR characterization confirmed the presence of C₂₂ ultra-long chains, cis double bonds, amide bonds, and quaternary ammonium headgroups in the product structure. Performance tests showed that EUCGS exhibited an extremely low critical micelle concentration (CMC = 0.018 mmol/L) and excellent ability to reduce surface tension (γCMC = 30.0 mN/m). Rheological property studies indicated that EUCGS solutions gradually exhibited significant non-Newtonian fluid characteristics with increasing concentration, and wormlike micelles with a network structure could self-assemble at a concentration of 1.0 mmol/L. Dynamic rheological tests revealed that the solutions showed typical Maxwell fluid behavior and significant shear-thinning properties, which originated from the orientation and disruption of the wormlike micelle network structure under shear stress. In the presence of 225 mmol/L NaCl, the apparent viscosity of a 20 mmol/L EUCGS solution increased from 86 mPa·s to 256 mPa·s. A temperature resistance evaluation showed that EUCGS solutions had a good temperature resistance at high shear rates and 100 °C. The performance evaluation of fracturing fluids indicates that the proppant settling rate (0.25 cm/min) of the EUCGS-FFS system at 90 °C is significantly superior to that of the conventional system. It features the low dosage and high efficiency of the breaker, with the final core damage rate being only 0.9%. The results demonstrate that the EUCGS achieves a synergistic optimization of high-efficiency interfacial activity, controllable rheological properties, and excellent thermal–salt stability through precise molecular structure design, providing a new material choice for the development of intelligent responsive clean fracturing fluids. Full article

Winding hot-spot temperature (HST) is a key factor affecting the insulation life of transformers. This paper proposes an optimization method based on the Kriging response surface model, which minimizes HST by adjusting the key structural parameters of the number of winding zones, vertical oil channel width, and horizontal oil channel height. First, a two-dimensional axisymmetric temperature–fluid field coupling model is established, and the finite volume method is used to solve the HST under the actual structure, which is 92.59 °C. A total of 50 sample datasets are designed using Latin hypercube sampling, and the whale optimization algorithm (WOA) is used to determine the optimal kernel parameters of Kriging with the goal of minimizing the root mean square error (RMSE) under 5-fold cross-validation. Combined with the genetic algorithm (GA) global optimization of structural parameters, the Kriging model predicts that the optimized HST is 89.77 °C, which is verified by simulation to be 89.79 °C, achieving a temperature drop of 2.80 °C, proving the effectiveness of the structural optimization method. Full article