Search Results (26,934)

Potential applications of microwave energy, a developed form of clean energy, are diverse and extensive. To expand the applications of microwave heating in the metallurgical field, it is essential to obtain the permittivity of ores throughout the heating process. This paper presents the design of a 2.45 GHz ridge waveguide apparatus based on the transmission/reflection method to measure permittivity, which constitutes a system capable of measuring the complex relative permittivity of the material under test with a wide temperature range from room temperature up to 1100 °C. The experimental results indicate that the system is capable of performing rapid measurements during the heating process. Furthermore, the system is capable of accurately measuring dielectric properties when the real part of the permittivity and the loss tangent vary widely. This measurement system is suitable for high-temperature dielectric property measurements and has potential applications in microwave-assisted metallurgy. Full article

In this study, Q370qENH high-strength weathering bridge steel was used as the base material. The corrosion experiment in a marine atmosphere was simulated by the salt spray test, and the outdoor atmospheric exposure corrosion experiment and electrochemical method test were carried out. The corrosion behavior of Q370qENH high-strength weathering bridge steel in a marine atmosphere was studied using electron probe microanalysis (EPMA), field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), and other surface testing techniques. The results show that the corrosion rate of the steel gradually decreases with the increase in the content of trace rare earth elements. Ce played a role in the modification of inclusions so that MnS was modified into rare earth composite inclusions, which slowed down the occurrence of corrosion. The enrichment of Cu alloy elements in the inner rust layer of the rare earth experimental steel improves the compactness of the rust layer, and the thickness of the inner rust layer is increased by 42%, which enhances the stability of the rust layer. With the increase in cerium, the protection coefficient α/γ* of the rust layer of experimental steel increases, indicating that the corrosion resistance of the material is improved. In addition, the electrochemical results show that the addition of rare earth elements in Q370qENH steel will lead to a positive shift in the electrochemical self-corrosion potential, a larger impedance radius of the steel rust layer, and a stronger protective effect. Due to the addition of trace cerium, the seawater corrosion resistance of the test steel is improved. Full article

Background: Knee osteoarthritis (OA) is the most prevalent form of osteoarthritis and a leading cause of chronic pain in adults. This study aimed to compare the short-term effects of extracorporeal shock wave therapy (ESWT), low-level laser therapy (LLLT), and pulsed electromagnetic field therapy (PEMF) on pain, function, and quality of life in patients with knee OA. Methods: A hundred and twenty patients with Kellgren–Lawrence grade 2–3 knee OA were randomized into four groups: ESWT (once a week for three sessions), LLLT (twice a week for eight sessions), PEMF (twice a week for eight sessions), and a control group with 30 patients in each group. All participants were instructed in a daily exercise program, including knee joint range of motion, stretching, and strengthening exercises (3 × 10 repetitions). Outcome measures, including the visual analog scale (VAS), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Short Form-36 (SF-36), and the Timed Up and Go (TUG) test, were assessed at baseline after treatment and at the third month. Results: There were no significant differences between groups at baseline regarding VAS, WOMAC, SF-36, and TUG scores (p > 0.05). Significant improvements were observed in all parameters post-treatment for all groups (p < 0.001). However, the improvements in the PEMF group were significantly lower than in the ESWT and LLLT groups, particularly for VAS, WOMAC pain, and SF-36 physical function scores (p < 0.05). No significant differences were found between ESWT and LLLT (p > 0.05). Conclusions: In the short-term, ESWT, LLLT, and PEMF effectively reduce pain, improve physical function, and enhance quality of life in patients with knee OA, though PEMF showed less pronounced improvements. Full article

Rigid reinforced concrete (RC) frames are generally adopted as stiff elements to make the building structures resistant to seismic forces. However, a method has yet to be fully sought to provide earthquake resistance through optimizing beam and column performance in a rigid frame. Due to its high corrosion resistance, the integration of CFRP offers an opportunity to reduce frequent repairs and increase durability. This paper presents the structural response of CFRP beams integrated into rigid frames when subjected to seismic events. Without any design provision for CFRP systems in extreme events, multiscale simulations and parametric analyses were performed to optimize the residual state and global performance. Macroparameters, represented by the ductility ratio and microfactors, have been analyzed using a customized version of the modified compression field theory (MCFT). The main parameters considered were reinforcement under tension and compression, strength of concrete, height-to-width ratio, section cover, and confinement level, all of which are important to understand their influence on seismic performance. The parametric analysis results highlight the increased ductility and higher load-carrying capacity of the CFRP-reinforced tested component compared to the RC component. These results shed light on the possibility of designing CFRP-reinforced concrete components that could improve ductile frames with increased energy dissipation and be suitable for applications in non-corrosive seismic-resistant buildings. This also shows reduced brittleness and enhancement in the failure mode. Numerical simulations and experimental results showed a strong correlation with a deviation of about 8.3%, underlining the reliability of the proposed approach for designing seismic-resistant CFRP-reinforced structures. Full article

As the field of big data continues to evolve, there is an increasing necessity to evaluate the equality of multiple high-dimensional covariance matrices. Many existing methods rely on approximations to the null distribution of the test statistic or its extreme-value distributions under stringent conditions, leading to outcomes that are either overly permissive or excessively cautious. Consequently, these methods often lack robustness when applied to real-world data, as verifying the required assumptions can be arduous. In response to these challenges, we introduce a novel test statistic utilizing the normal-reference approach. We demonstrate that the null distribution of this test statistic shares the same limiting distribution as a chi-square-type mixture under certain regularity conditions, with the latter reliably estimable from data using the three-cumulant matched chi-square-approximation. Additionally, we establish the asymptotic power of our proposed test. Through comprehensive simulation studies and real data analysis, our proposed test demonstrates superior performance in terms of size control compared to several competing methods. Full article

Auxetic structures have great potential in modern engineering, and their design represents an emerging field in industrial applications. The accurate synthesis of the elements of such structures requires multidisciplinary approaches that combine kinematics and structural mechanics. Design methodologies are often based on complex time-consuming numerical methods and with considerable computational burden for exploring a large set of alternatives. The aim of the present work is to propose a novel method for designing symmetrical auxetic structures based on the use of pseudo-rigid mechanisms that can reproduce their nonlinear elasto-kinematic behavior with a limited set of parameters. For the definition of these pseudo-rigid mechanisms, the theory of kinematic invariants is proposed. It allows for the deduction of surrogate rigid-link mechanisms with a simpler structure but remarkable accuracy. This approach is an emerging method employed in the generic synthesis and analysis of compliant mechanisms, and, in this study, it is extended for the first time to support the design of auxetic structures. This paper describes the analytical process to deduce the design equations and discusses the example of an application to a symmetrical re-entrant structure, comparing the results with those of a numerical flexible multibody model, a finite element model, and with experimental tests. All the comparisons demonstrate the considerable potential of the proposed methodology, which can also be adapted to other types of auxetic structures. Full article

This paper presents the development of a computer simulation framework, designed as a cost–effective and technically efficient alternative to experimental studies. The framework focuses on the Bio–Neural Dust System proposed in our previous works, which consists of two components: a light–emitting bio–nanosensor and an opsin–expressing genetically modified neuron. This innovative system holds significant potential for applications in neuroscience and biotechnology research. Programmed in Python, the framework provides researchers with a virtual tool to test and evaluate the Bio–Neural Dust System, enabling the prediction of outcomes for future in vivo experiments. This approach not only conserves resources, but also offers scientists a flexible and accessible means to investigate the complex interactions within the system prior to real–world applications. The framework’s adaptability and potential for diverse research applications highlight its importance in advancing the field of bio–nanotechnology. Full article

Three lightweight aluminum-based complex concentrated alloys with chemical compositions that have not been previously studied were manufactured and studied: Al₅₂Mg_9.6Zn₁₆Cu_15.5Si_6.9 w.t.% or Al₆₃Mg₁₃Zn₈Cu₈Si₈ a.t.% (alloy A), Al₄₄Mg₁₈Zn₁₉Cu₁₉ w.t.% or Al₅₅Mg₂₅Zn₁₀Cu₁₀ a.t.% (alloy B), and Al₄₇Mg_21.4Zn₁₂Cu_9.7Si_9.7 w.t.% or Al_52.7Mg_26.6Zn_5.6Cu_4.6Si_10.4 a.t.% (alloy AM), with low densities of 3.15 g/cm³, 3.18 g/cm³ and 2.73 g/cm³, respectively. During alloy design, the CALPHAD method was used to calculate a variety of phase diagrams for the various chemical compositions and to predict possible phases that may form in the alloy. The CALPHAD methodology results showed good agreement with the experimental results. The potential of the designed alloys to be used in some industrial applications was examined by manufacturing them using standard industrial techniques, something that is a rarity in this field. The alloys were produced using an induction furnace and pour mold casting process, while industrial-grade raw materials were utilized. Heat treatments with different soaking times were performed in order to evaluate the possibility of improving the mechanical properties of the alloys. Alloys A and AM were characterized by a multiphase microstructure with a dendritic FCC-Al matrix phase and various secondary phases (Q-AlCuMgSi, Al₂Cu and Mg₂Si), while alloy B consisted of a parent phase T-Mg₃₂(Al,Zn)₄₉ and the secondary phases α-Al and Mg₂Si. The microstructure of the cast alloys did not appear to be affected by the heat treatments compared to the corresponding as-cast specimens. However, alterations were observed in terms of the elemental composition of the phases in alloy A. In order to investigate and evaluate the mechanical properties of the as-cast and heat-treated alloys, hardness testing along with electrical conductivity measurements were conducted at room temperature. Among the as-cast samples, alloy AM had the highest hardness (246 HV₄), while among the heat-treated ones, alloy A showed the highest value (256 HV₄). The electrical conductivity of all the alloys increased after the heat treatment, with the highest increase occurring during the first 4 h of the heat treatment. Full article

In Chile and worldwide, walnut (Juglans regia L.) production faces significant losses due to crown and root rot caused by the phytopathogen Phytophthora cinnamomi. Currently, control methods have proven insufficient or unfavorable for the environment, increasing the need for sustainable alternatives. This research evaluates nanoemulsions based on extracts of medicinal plants endemic to Chile to control P. cinnamomi in walnut crops. The methodology included an in vitro test to determine the effective inhibitory concentrations of three nanoemulsions (N80, N90, and N100) on the mycelial growth of the phytopathogen, a test on walnut plants under controlled conditions, and two field tests using concentrations between 300 and 500 ppm. The in vitro results showed that the nanoemulsions could inhibit 90% of mycelial growth at 80 to 100 ppm concentrations. In the field, the N90 nanoemulsion at 500 ppm significantly reduced disease symptoms preventively and post-inoculation, compared with the control. This research is the first to study the use of nanoemulsions from native Chilean plants to control P. cinnamomi, showing potential to reduce the use of synthetic fungicides, contributing to safer and more ecological phytosanitary management. Full article

Egg-based yoghurt (EBY) is a novel yoghurt fermented by lactic acid bacteria with high nutritional and health values, serving as a potential alternative to milk-based yoghurt. However, the hardness, adhesiveness, and water-holding capacity of egg-based yoghurt need to be further improved. In this study, the improvement in EBY quality by gellan gum and its underlying mechanism were investigated. The results showed that gellan gum significantly improved the quality of EBY (p < 0.05). Among the five concentration gradients tested, the EBY supplemented with 0.045% gellan gum exhibited the best quality with the highest sensory score of 83.57. With the increasing amount of gellan gum, hydrogen bonding interactions in the yoghurt significantly increased, while ionic bonding remained unchanged, but hydrophobic interactions and disulphide bonding gradually decreased. Low-field NMR assay results demonstrated that gellan gum significantly raised the amount of strongly bonded water while decreasing the amount of immobile water in the yoghurt. Confocal laser scanning microscopy revealed that EBY with 0.045% gellan gum had a better texture, whereas too much or too little gellan gum led to a coarser structure. In summary, gellan gum altered the water phase state and enhanced the water holding capacity through increased hydrogen bonding interactions, which consequently improved the yoghurt’s texture and sensory qualities. This study provides a reference for the development and application of EBY. Full article

Facial recognition technology has significantly advanced in recent years, with promising applications in fields ranging from security to consumer electronics. Its importance extends beyond convenience, offering enhanced security measures for sensitive areas and seamless user experiences in everyday devices. This study focuses on the development and validation of a facial recognition system utilizing a Haar cascade classifier and the AdaBoost machine learning algorithm. The system leverages characteristic facial features—distinct, measurable attributes used to identify and differentiate faces within images. A biometric facial recognition system was implemented on a Raspberry Pi microcomputer, capable of detecting and identifying faces using a self-contained reference image database. Verification involved selecting the similarity threshold, a critical factor influencing the balance between accuracy, security, and user experience in biometric systems. Testing under various environmental conditions, facial expressions, and user demographics confirmed the system’s accuracy and efficiency, achieving an average recognition time of 10.5 s under different lighting conditions, such as daylight, artificial light, and low-light scenarios. It is shown that the system’s accuracy and scalability can be enhanced through testing with larger databases, hardware upgrades like higher-resolution cameras, and advanced deep learning algorithms to address challenges such as extreme facial angles. Threshold optimization tests with six male participants revealed a value that effectively balances accuracy and efficiency. While the system performed effectively under controlled conditions, challenges such as biometric similarities and vulnerabilities to spoofing with printed photos underscore the need for additional security measures, such as thermal imaging. Potential applications include access control, surveillance, and statistical data collection, highlighting the system’s versatility and relevance. Full article

Unprecedented levels of air pollution in our cities due to rapid urbanization have caused major health concerns, severely affecting the population, especially children and the elderly. A steady loss of ecological balance, without remedial measures like phytoremediation, coupled with alarming vehicular and industrial pollution, have pushed the Air Quality Index (AQI) and particulate matter (PM) to dangerous levels, especially in the metropolitan cities of India. Monitoring and accurate prediction of inhalable Particulate Matter 2.5 (PM2.5) and Particulate Matter 10 (PM10) levels, which cause escalations in and increase the risks of asthma, respiratory inflammation, bronchitis, high blood pressure, compromised lung function, and lung cancer, have become more critical than ever. To that end, the authors of this work have proposed a federated learning (FL) framework for monitoring and predicting PM2.5 and PM10 across multiple locations, with a resultant impact analysis with respect to key health parameters. The proposed FL approach encompasses four stages: client selection for processing and model updates, aggregation for global model updates, a pollution prediction model with necessary explanations, and finally, the health impact analysis corresponding to the PM levels. This framework employs a VGG-19 deep learning model, and leverages Causal Inference for interpretability, enabling accurate impact analysis across a host of health conditions. This research has employed datasets specific to India, Nepal, and China for the purposes of model prediction, explanation, and impact analysis. The approach was found to achieve an overall accuracy of 92.33%, with the causal inference-based impact analysis producing an accuracy of 84% for training and 72% for testing with respect to PM2.5, and an accuracy of 79% for training and 74% for testing with respect to PM10. Compared to previous studies undertaken in this field, this proposed approach has demonstrated better accuracy, and is the first of its kind to analyze health impacts corresponding to PM2.5 and PM10 levels. Full article

This paper details the design and fabrication of a triode–anode magnetron injection gun (MIG) for a 170 GHz gyrotron for use in magnetic confinement thermonuclear fusion. To solve the mismatch problem of electric and magnetic fields in the electron emission area caused by geometric deformation under the thermal field, the temperature of the MIG was tested to accurately describe the thermal field distribution, and geometric dimension variables under the operating temperature were simulated. By analyzing the electric and magnetic fields under the thermal field, the design scheme of the MIG was optimized to achieve the goals of reducing the spread of electron beam velocity in the interaction region and improving the interaction efficiency. Full article

Velocity gradient is an important parameter for interpreting tomographic velocity field and identifying geological boundaries. It is usually translated from the results of seismic travel-time tomography. Recent researches show seismic polarization direction appears to be a promising data source for obtaining velocity gradient field directly. However, what remains unclear is the sensitivity of polarization direction to velocity gradient, which causes difficulty for correctly inverting polarization direction data. To clarify this problem, the sensitivity of velocity gradient parameters on polarization direction is discussed in this paper. It was found that the sensitivity of polarization direction is related to the spatial position of the model parameter. The further the parameter position is from the sensor, the lower the sensitivity is. Such nonuniform distribution of sensitivity may cause distortion of inversion results with incomplete projection data. Based on this analysis, adjustment factors are introducing to the polarization direction inversion algorithm for correctly inverting polarization direction data. Numerical tests are conducted to verify our theoretical analysis and inversion algorithm. Test results show that our theoretical analysis is accurate in both homogeneous velocity field and near velocity interfaces. The inversion method with the adjustment factor can more accurately recover the velocity gradient, offering a promising approach for geological boundary imaging. Full article

Laminaria hyperborea, a key species in marine forest ecosystems, is experiencing pressure at its southern distribution limit in northern Portugal due to climate change and human-induced stressors. The ongoing degradation of marine forests highlights the need for effective restoration strategies to protect biodiversity and maintain the essential services provided by these habitats. Cultivation of juvenile kelps in laboratory settings is a common approach shared across multiple strategies aimed at supporting reforestation efforts; however, the specific cultivation process for L. hyperborea remains largely underexplored. In this study, we tested two seeding densities to optimize the production of L. hyperborea recruits for reforestation initiatives. We assessed the effects of seeding density on juvenile development by measuring both area coverage and length. Our findings revealed that higher seeding density initially promoted greater area coverage (e.g., 8.69 ± 0.38 cm² vs. 3.35 ± 0.27 cm²) but reduced the length of individual recruits over time (e.g., 0.26 ± 0.0026 cm vs. 0.39 ± 0.003 cm at T3). This suggests that increased competition for resources at high densities limits individual growth. In contrast, lower densities produced larger, more robust individuals (e.g., 0.50 ± 0.004 cm vs. 0.262 ± 0.003 cm at T4), which may enhance post-transplantation survival in challenging environmental conditions. This suggests that utilizing lower seeding densities may improve individual growth while decreasing overall resource use and maintenance needs, promoting a more sustainable cultivation process and minimizing impacts on donor populations. However, further research is essential to refine the cultivation protocols and fully understand the variables influencing juvenile kelp development. Improving all phases of the restoration process, from laboratory cultivation to field deployment, will be critical for reducing costs, streamlining logistics, and ensuring the scalability of future kelp restoration efforts. Full article