Search Results (53)

Balancing convergence accuracy and population diversity remains a fundamental challenge in multi-objective optimization, particularly for complex and constrained engineering problems. To address this issue, this paper proposes a novel Multi-Objective Crested Porcupine Optimizer (MOCPO), inspired by the hierarchical defensive behaviors of crested porcupines. The proposed algorithm integrates four biologically motivated defense strategies—vision, hearing, scent diffusion, and physical attack—into a unified optimization framework, where global exploration and local exploitation are dynamically coordinated. To effectively extend the original optimizer to multi-objective scenarios, MOCPO incorporates a reference-point guided external archiving mechanism to preserve a well-distributed set of non-dominated solutions, along with an environmental selection strategy that adaptively partitions the objective space and enhances solution quality. Furthermore, a multi-level leadership mechanism based on Euclidean distance is introduced to provide region-specific guidance, enabling precise and uniform coverage of the Pareto front. The performance of MOCPO is comprehensively evaluated on 18 benchmark problems from the WFG and CF test suites. Experimental results demonstrate that MOCPO consistently outperforms several state-of-the-art multi-objective algorithms, including MOPSO and NSGA-III, in terms of IGD, GD, HV, and Spread metrics, achieving the best overall ranking in Friedman statistical tests. Notably, the proposed algorithm exhibits strong robustness on discontinuous, multimodal, and constrained Pareto fronts. In addition, MOCPO is applied to UAV path planning in four complex terrain scenarios constructed from real digital elevation data. The results show that MOCPO generates shorter, smoother, and more stable flight paths while effectively balancing route length, threat avoidance, flight altitude, and trajectory smoothness. These findings confirm the effectiveness, robustness, and practical applicability of MOCPO for solving complex real-world multi-objective optimization problems. Full article

Underwater acoustic imaging is essential in marine science and engineering, enabling high-resolution detection and characterization of underwater structures and targets. However, conventional deconvolution beamforming methods using broadband signals often suffer from model mismatch, inter-frequency interference, and limited noise robustness. To overcome these challenges, this study rigorously analyzes the point spread function of the imaging system and introduces Acoustic Frequency Comb (AFC) excitations to enhance resolution. By exploiting the autocorrelation characteristics of AFC signals and optimizing key parameters, imaging artifacts are effectively suppressed and the main-lobe width is narrowed, resulting in a 50% improvement in range resolution. Comparative analyses identify the Richardson–Lucy algorithm as the most effective in enhancing azimuthal resolution and maintaining robustness under array perturbations and low signal-to-noise ratios. Parametric studies further demonstrate that AFC excitation outperforms conventional linear frequency modulated pulses, achieving a 30% main-lobe width reduction, 10 dB sidelobe suppression, and a 14 dB noise decrease. Finally, tank experiments confirm the simulation results, showing that accurate PSF modeling enabled by AFC ensures high angular resolution. The discrete spectral structure facilitates more effective separation of signal and noise during iterative deconvolution, while excellent autocorrelation characteristics guarantee high range resolution, yielding superior overall imaging performance. Full article

This study aimed to evaluate the characteristics of short acquisition times using the Clear adaptive Low-noise Method (CaLM) and Advanced intelligent clear-IQ engine (AiCE) reconstructions in a semiconductor-based positron emission tomography (PET)/computed tomography system. PET data were acquired for 30 min in list mode and resampled into time frames ranging from 15 to 120 s. Images were reconstructed using three-dimensional ordinary Poisson ordered-subset expectation maximization (OSEM) with time of flight (TOF) and OSEM with TOF and point spread function modeling (PSF) algorithms, with OSEM iterations adjusted from 1 to 20 and CaLM applied under Mild, Standard, and Strong settings. AiCE reconstruction allows for the modification of only the acquisition time. The images were evaluated based on the coefficient of variation, recovery coefficient, % background variability (N_10mm), % contrast-to-% background variability ratio (Q_H10mm/N_10mm), and contrast-to-noise ratio. While OSEM with TOF reconstruction did not significantly reduce the acquisition time, the addition of PSF correction suggested the potential for further reduction. Given that the AiCE characteristics may vary depending on the equipment used, further investigation is required. Full article

The transmission efficiency of underwater acoustic is doubly constrained by absorption attenuation and geometric spreading losses, with the relative interaction between these loss mechanisms exhibiting complex dynamic variations across the frequency spectrum. Achieving dynamic equilibrium between these frequency-dependent loss mechanisms is key to enhancing acoustic energy transmission performance. To address this, this paper proposes a multi-variable coupled acoustic energy transmission model that systematically integrates the cumulative effects of the propagation distance, the geometric configuration of acoustic source arrays, and the interactive influences of critical environmental factors such as the salinity, temperature, and depth to comprehensively analyze the synergistic mechanisms of absorption loss and geometric spreading loss in practical underwater environments. Based on dynamic response analysis in the frequency dimension, the model identifies and determines the optimal working frequency ranges (i.e., dynamic equilibrium points) for maximizing the efficiency of energy transmission under various propagation conditions and environmental configurations. Both theoretical derivations and numerical simulations consistently reveal a frequency band within the low-to-mid frequency range (approximately 20–100 kHz) which is associated with significantly enhanced transmission efficiency under specific parameter settings. These research findings provide a scientific basis and engineering guidance for frequency selection and the structural optimization of underwater acoustic energy systems, offering substantial theoretical value and application prospects that can strongly support the development of acoustic technologies in ocean engineering, resource exploration, and national defense security. Full article

Hydraulic fracturing of gas and oil reservoirs is the primary stimulation method for enhancing production in the field of petroleum engineering. The hydraulic fracturing technology plays a crucial role in increasing shale gas production from shale reservoirs. Understanding the effects of reservoir and fracturing conditions on fracture propagation is of great significance for optimizing the hydraulic fracturing process and has not been adequately explored in the current literature. In the context of shale reservoirs in Yibin, Sichuan Province, China, the study selects outcrops to prepare samples for uniaxial compression and Brazilian splitting tests. These tests measure the compressive and tensile strengths of shale in parallel bedding and vertical bedding directions, obtaining the shale’s anisotropic elastic modulus and Poisson’s ratio. These parameters are crucial for simulating reservoir hydraulic fracturing. This paper presents a numerical model utilizing a finite element (FE) analysis to simulate the process of multi-cluster hydraulic fracturing in a shale reservoir with natural fractures in three dimensions. A numerical simulation of the intersection of multiple clusters of 3D hydraulic fractures and natural fractures was performed, and the complex 3D fracture morphologies after the interaction between any two fractures were revealed. The influences of natural fractures, reservoir ground stress, fracturing conditions, and fracture interference concerning the spreading of hydraulic fractures were analyzed. The results highlight several key points: (1) Shale samples exhibit distinct layering with significant anisotropy. The elastic compressive modulus and Poisson’s ratio of parallel bedding shale samples are similar to those of vertical bedding shale samples, while the compressive strength of parallel bedding shale samples is significantly greater than that of vertical bedding shale samples. The elastic compressive modulus of shale is 6 to 10 times its tensile modulus. (2) The anisotropy of shale’s tensile properties is pronounced. The ultimate load capacity of vertical bedding shale samples is 2 to 4 times that of parallel bedding shale samples. The tensile strength of vertical bedding shale samples is 2 to 5 times that of parallel bedding shale samples. (3) The hydraulic fractures induced by the injection well closest to the natural fractures expanded the fastest, and the natural fractures opened when they intersected the hydraulic fractures. When the difference in the horizontal ground stress was significant, natural fractures were more inclined to open after the intersection between the hydraulic and natural fractures. (4) The higher the injection rate and viscosity of the fracturing fluid, the faster the fracture propagation. The research findings could improve the fracturing process through a better understanding of the fracture propagation process and provide practical guidance for hydraulic fracturing design in shale gas reservoirs. Full article

The Relief Degree of Land Surface (RDLS) is an important index to evaluate regional environment. It has a significant effect on the local climate, geologic hazards, the path and speed of fire spreading, the migrations of wild animals, and the runoff path and speed of precipitation. The forest-steppe ecotone in northern China is one of ecological fragile zones. In-depth study of the RDLS of the forest-steppe ecotone in northern China will help to implement ecological projects scientifically and promote the construction of the national ecological security barrier. The Shuttle Radar Topography Mission (SRTM-GL1 30 m) data were used to determine the optimal analysis window for RDLS based on the mean change-point method, and the elevation difference was extracted based on the window analysis method. The RDLS model was used to extract RDLS of the forest-steppe ecotone and analyzed with the help of a spatial auto-correlation model. The correlation between mean elevation, relative elevation difference, and RDLS was also analyzed. The results show that the optimal analysis window size for RDLS was 29 × 29, corresponding to an area of 0.76 km². The RDLS under the optimal analysis window extracted from SRTM-GL1 (30 m) ranged from 0.084 to 3.516. The RDLS had significant spatial clustering, with high RDLS mainly distributed in the mountainous areas and low RDLS mainly distributed in mountain-to-plain transition zone; the RDLS between different administrative units and different watersheds had obvious variability. Overall, the RDLS was characterized as decreasing, increasing, and then decreasing from the south to north, while it was high in the west and low in the east. And the RDLS was linearly positively correlated with mean elevation and relative elevation difference. In the future, the implementation of major ecological projects in the forest-steppe ecotone in northern China, such as soil and water conservation, afforestation tree species selection, ecological corridor design, ecological management, geological disaster prevention, and forest fire prevention, should fully consider the local topographic conditions. These research results can provide topographic references for the implementation of ecological planning and engineering in this area and similar areas. It contributes to sustainable development and maximization of ecological benefits and promotes the establishment of a national ecological security barrier. Full article

The use of microwave energy to recycle high-quality coarse aggregates from waste concrete or assist hard rock breakage in underground building engineering is promising. Controlling or promoting the damage of coarse aggregates, i.e., hard rocks, under microwave irradiation is a crucial issue faced by these techniques. Understanding the damage mechanisms of hard rocks exposed to microwaves is thus urgent. Fracture toughness is a significant mechanical parameter of rocks that reflects their ability to resist crack propagation and damage evolution. In this study, the fracture toughness degradation of microwave-heated granite was investigated by combining experimental investigations and numerical simulations. A three-point-bending (TPB) experiment was conducted on granite specimens after microwave irradiation. A coupled electromagnetic–thermal–mechanical model considering the actual mineral texture of the granite specimen was established. The evolution of the temperature gradient and stress field near the initial notch tip were investigated. The results suggest that the microwave-induced maximum temperature gradient and stress in granite are at the plagioclase–quartz (Pl–Qtz) interfaces or inside the Pl near the boundary. The region of cracking initiation was defined as the damage zone, which could be obtained by comparing the microwave-induced thermal stress with the critical value. The fracture toughness degradation, which corresponds to the evolution of the damage zones, can be divided into two stages. A relatively rapid decrease in fracture toughness in the first stage is primarily caused by the spread of the scattered damage zones along the Pl–Qtz interfaces; subsequently, a gentler fracture toughness degradation results mainly from the extension of the previous damage zones. Full article

The resolution of an optical microscope is determined by the overall point spread function of the system. When examining structures significantly smaller than the wavelength of light, the contribution of the background or surrounding environment can profoundly affect the point spread function. This research delves into the impact of reflective planar substrate structures on the system’s resolution. We establish a comprehensive forward imaging model for a reflection-type confocal laser scanning optical microscope, incorporating vector field manipulation to image densely packed nanoparticle clusters. Both theoretical and experimental findings indicate that the substrate causes an interference effect between the background field and the scattered field from the nanoparticles, markedly enhancing the overall spatial resolution. The integration of vector field manipulation with an interferometric scattering approach results in superior spatial resolution for imaging isolated particles and densely distributed nanoscale particle clusters even with deep subwavelength gaps as small as 20 nm between them. However, the method still struggles to resolve nanoparticles positioned directly next to each other without any gap, necessitating further work to enhance the resolving ability. This may involve techniques like deconvolution or machine learning-based post-processing methods. Full article

This paper introduces a robust deposition model designed for exploring the growth dynamics of deposits on surfaces under practical conditions. The study addresses the challenge of characterizing the intricate morphology of deposits, exhibiting significant visual variations. A generative approach is deployed to create diverse natural and engineered surface textures, governed by probabilistic principles. The model’s formulation addresses key questions related to deposition initiation, nucleation point behaviour, spatial scaling, deposit growth rates, spread dynamics, and surface mobility. A versatile algorithm, relying on six parameters and employing nested loops and Gaussian sampling, is developed. The algorithm’s efficacy is examined through extensive simulations, involving variations in nucleation scaling densities, aggregate scaling scenarios, spread factors, and diffusion rates. Surface statistics are computed for simulated deposits and analyzed using Fast Fourier Transform (FFT). The resulting database enables quantitative comparisons of surfaces generated with different parameters, where the database-derived parallel coordinates offer guidance for selecting optimal model parameters to achieve desired surface morphologies. The proposed approach is validated against urea-derived deposits, exhibiting statistical consistency and agreement with experimental observations. Overall, the model’s adaptable framework holds promise for understanding and predicting deposit growth on surfaces in diverse practical scenarios. Full article

Building Information Modelling (BIM) has found applications not only in the planning and designing of new buildings but also in project monitoring, record-keeping, and analyses of existing structures. In addition to its primary application, information modelling spreads to other areas, developing solutions for their specific uses. This study engaged a mixed-method literature review according to the extent of the pool of knowledge for two research steps between three concepts—from point cloud to NURBS and then from NURBS to BIM. In the first step, the keywords point cloud and NURBS were analysed using scientometric methods. In the second step, a systematic analysis of the content of works obtained with the keywords NURBS and BIM is presented, extracting problems and proposed solutions for information transfer technology. The results of a quantitative analysis identified major trends, (1) research is distributed in interdisciplinary and multidisciplinary areas and historical (heritage) modelling is the highlighted one, (2) development of technologies for object surveying, and (3) the application of data in different engineering fields, while a qualitative analysis points at problems in (1) model building, (2) interoperability, and (3) automatization. Solutions such as mixed models, multi-layered models, a mix of formats, or bridging elements (semantics, proto-model) are proposed. Full article

Spatial-structured longitudinal light beams are optical fields sculpted in three-dimensional (3D) space by diffractive optical elements. These beams have been recently suggested for use in improving several imaging capabilities, such as 3D imaging, enhancing image resolution, engineering the depth of field, and sectioning 3D scenes. All these imaging tasks are performed using coded aperture correlation holography systems. Each system designed for a specific application is characterized by a point spread function of a different spatial-structured longitudinal light beam. This article reviews the topic of applying certain structured light beams for optical imaging. Full article

In order to explore the problems of load transfer and anchorage mechanisms of tensile anchors under pull-out load for geotechnical anchoring systems, a step-wise mathematical model is established which considers the linear–nonlinear shear stress and shear displacement of the anchorage segment, using an elasto-plastic constitutive model. The displacement, axial force, and shear stress of the anchorage interface in different stages (elastic, plastic, and debonding) are analyzed and solutions are derived. And the theoretical solutions for the ultimate pull-out load of the anchor at each stage are also presented. Two in situ pull-out tests are used to verify and apply these findings in engineering. The results show that the stepwise composite model could reflect the bonding, softening and residual characteristics of the anchoring interface. In the process of the pull-out load increasing, the pulling end of the anchor initially enters the plastic stage and the debonding stage, respectively, and the failure of the anchor occurs at the pulling end, and as the axial force transfers down deeper, the damage gradually spreads deeper. The axial force distribution of the anchorage section is a monotonically decreasing curve, and the peak point of the shear stress gradually moves deeper. The calculation results of the axial force distribution curve and load–displacement curve of the anchor are in good agreement with the measured values, which verifies the rationality and reliability of the theoretical prediction method. This method can provide a theoretical reference for the load transfer analysis and design of tension anchors for geotechnical anchoring systems. Full article

The COVID-19 pandemic has had a significant impact on human health management. A rapid diagnosis of SARS-CoV2 at the point-of-care (POC) is critical to prevent disease spread. As a POC device for remote settings, a LFIA should not require cold-chain maintenance and should be kept at normal temperatures. Antigen stability can be enhanced by addressing instability issues when dealing with fragile components, such as proteinaceous capture antigens. This study used immunologically guided protein engineering to enhance the capture nucleocapsid (NP) antigen stability of SARS-CoV2. A search of the IEDB database revealed that antibodies detecting epitopes are almost uniformly distributed over NP_1-419. In contrast, N-terminal stretches of NP_1-419 are theoretically more unstable than C-terminal stretches. We identified NP_250-365 as a NP stretch with a low instability index and B-cell epitopes. Apart from NP_1-419, two other variants (NP_121-419 and NP_250-365) were cloned, expressed, and purified. The degradation pattern of the proteins was observed on SDS-PAGE after three days of stability studies at −20 °C, 4 °C, and 37 °C. NP_1-419 was the most degraded while NP_250-365 exhibited the least degradation. Also, NP_1-419, NP_250-365, and NP_121-419 reacted with purified antibodies from COVID-19 patient serum. Our results suggest that NP_250-365 may be used as a stable capture antigen in LFIA devices to detect COVID-19. Full article

Neural injuries disrupt the normal functions of the nervous system, whose complexities limit current treatment options. Because of their enhanced therapeutic effects, neurospheres have the potential to advance the field of regenerative medicine and neural tissue engineering. Methodological steps can pose challenges for implementing neurosphere assemblies; for example, conventional static cultures hinder yield and throughput, while the presence of the necrotic core, time-consuming methodology, and high variability can slow their progression to clinical application. Here we demonstrate the optimization of primary neural cell-derived neurospheres, developed using a high-throughput, stress-free, 3D bioreactor. This process provides a necessary baseline for future studies that could develop co-cultured assemblies of stem cells combined with endothelial cells, and/or biomaterials and nanomaterials for clinical therapeutic use. Neurosphere size and neurite spreading were evaluated under various conditions using Image J software. Primary neural cells obtained from the hippocampi of three-day-old rat pups, when incubated for 24 h in a reactor coated with 2% Pluronic and seeded on Poly-D-Lysine-coated plates establish neurospheres suitable for therapeutic use within five days. Most notably, neurospheres maintained high cell viability of ≥84% and expressed the neural marker MAP2, neural marker β-Tubulin III, and glial marker GFAP at all time points when evaluated over seven days. Establishing these factors reduces the variability in developing neurospheres, while increasing the ease and output of the culture process and maintaining viable cellular constructs. Full article

Following the global spread of COVID-19, scientists and engineers have adapted technologies and developed new tools to aid in the fight against COVID-19. This review discusses various approaches to engineering biomaterials, devices, and therapeutics, especially at micro and nano levels, for the prevention, diagnosis, and treatment of infectious diseases, such as COVID-19, serving as a resource for scientists to identify specific tools that can be applicable for infectious-disease-related research, technology development, and treatment. From the design and production of equipment critical to first responders and patients using three-dimensional (3D) printing technology to point-of-care devices for rapid diagnosis, these technologies and tools have been essential to address current global needs for the prevention and detection of diseases. Moreover, advancements in organ-on-a-chip platforms provide a valuable platform to not only study infections and disease development in humans but also allow for the screening of more effective therapeutics. In addition, vaccines, the repurposing of approved drugs, biomaterials, drug delivery, and cell therapy are promising approaches for the prevention and treatment of infectious diseases. Following a comprehensive review of all these topics, we discuss unsolved problems and future directions. Full article