Nickel Oxide (NiO) nanoparticles (NPs), doped with manganese (Mn) and cobalt (Co) at concentrations up to 8%, were synthesized using the composite hydroxide method (CHM). X-ray diffraction (XRD) analysis confirmed the formation of a cubic NiO structure, with no additional peaks detected, indicating successful doping. The average crystallite size was determined to range from 15 to 17.8 nm, depending on the dopant concentration. Scanning electron microscopy (SEM) images revealed mostly spherical, agglomerated particles, likely due to magnetic interactions. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the incorporation of Mn and Co into the NiO lattice, consistent with the XRD results. The dielectric properties exhibited a high dielectric constant at low frequencies, which can be attributed to ion jump orientation and space charge effects. The imaginary part of the dielectric constant decreased with increasing frequency, as it became harder for electrons to align with the alternating field at higher frequencies. Both the real and imaginary dielectric constants showed behavior consistent with Koop’s theory, increasing at low frequencies and decreasing at higher frequencies. Dielectric loss was primarily attributed to dipole flipping and charge migration. AC conductivity increased with frequency, and exhibited higher conductivity at high frequencies due to small polaron hopping. These co-doped NPs show potential for applications in solid oxide fuel cells.
Creative cities as a study discipline have garnered extensive attention and research in theory and practice as a practical approach to urban revitalization and sustainable development. This study conducted a systematic review of academic research on creative cities. Utilizing the visual analysis tools Citespace and VOSviewer, a comprehensive analysis was performed on 570 relevant articles from the Web of Science database. This study analyzed the most influential publications, authors, journals, institutions, and countries within the sample. The investigation spans various disciplinary domains, including geography, environment, culture, and others. Additionally, an exploration of the structure and characteristics of co-cited references was undertaken to enhance our understanding of the theoretical foundations of creative cities research further. Among these, the focal points of the study encompass urban development, urban policies, and the challenges faced. Finally, through co-occurrence analysis of keywords and examining the evolutionary process, the study forecasted that future trends will focus on the practical application of cities to enhance the urban image and improve urban governance from multi-dimensional perspectives such as creativity-related cultural places, public art, and so forth, exploring novel models of creative cities from case to universal. The results of this study can support scholars in grasping the development trends and exploring focal points.
Accurate temperature control during the induction heating process of carbon fiber reinforced polymer (CFRP) is crucial for the curing effect of the material. This paper first builds a finite element model of induction heating, which combines the actual fiber structure and resin matrix, and systematically analyzes the heating mechanism and temperature field distribution of CFRP during the heating process. Based on the temperature distribution and variation observed in the material heating process, a PID control method optimized by the sparrow search algorithm is proposed, which effectively reduces the temperature overshoot and improves the response speed. The experiment verifies the effectiveness of the algorithm in controlling the temperature of the CFRP plate during the induction heating process. This study provides an effective control strategy and research method to improve the accuracy of temperature control in the induction heating process of CFRP, which helps to improve the results in this field.
The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.
This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.
With the increasing call for sustainable development, cities’ demand for green innovation has also been growing. However, relatively little research summarizes the influencing factors of urban green innovation. In this study, we conducted a visual analysis of 1193 research articles on green innovation in cities from the Web of Science core database using bibliometrics and visualization analysis. By analyzing co-occurrence, co-citation, and high-frequency keywords in the literature, we explored the current research status and development trends of influencing factors of urban green innovation and summarized the research in this field. The study found that collaboration among authors and institutions in this field needs to be strengthened to a certain extent. In addition, the study identified the research hotspots and frontiers in the field of urban green innovation, including “management”, “diffusion”, “smart city”, “indicator”, “sustainable city”, “governance”, and “environmental regulation”. Among them, “management”, “governance”, “indicator”, and “internet” are the research frontiers in this field, which are expected to have profound impacts on the future development of urban green innovation. The co-citation analysis results found that China has the highest research output in this field, followed by the United States, England, Australia, and Italy. In conclusion, this study uses CiteSpace software to identify important influencing factors and development trends of urban green innovation. Urban green innovation has gradually become a norm for social and collective behavior in the process of concretization, interdisciplinary development, and technological innovation. These findings have important reference value for promoting research and practice of urban green innovation.
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