Purpose: This study aimed to explore the perception types of workplace spirituality among nurses. Method: To achieve this, Q methodology was applied, selecting 34 Q samples from a total of 102 Q statements extracted. The Q samples were distributed among 40 nurses and categorized into a normal distribution. A 9-point scale was used for measurement, and the data were analyzed using the pc-QUANL program. Results: The four types identified were ‘reflective type’, ‘nursing-oriented type’, ‘relationship-oriented type’, and ‘spirituality-oriented type’. Conclusion: The four types derived in this study classify nurses’ perceptions of workplace spirituality for establishing a nurse’s workplace spirituality that provides integrated nursing care. This categorization can serve as foundational information when planning workplace spirituality programs, considering each type’s characteristics.

Clustering technics, like k-means and its extended version, fuzzy c-means clustering (FCM) are useful tools for identifying typical behaviours based on various attitudes and responses to well-formulated questionnaires, such as among forensic populations. As more or less standard questionnaires for analyzing aggressive attitudes do exist in the literature, the application of these clustering methods seems to be rather straightforward. Especially, fuzzy clustering may lead to new recognitions, as human behaviour and communication are full of uncertainties, which often do not have a probabilistic nature. In this paper, the cluster analysis of a closed forensic (inmate) population will be presented. The goal of this study was by applying fuzzy c-means clustering to facilitate the wider possibilities of analysis of aggressive behaviour which is treated as a heterogeneous construct resulting in two main phenotypes, premeditated and impulsive aggression. Understanding motives of aggression helps reconstruct possible events, sequences of events and scenarios related to a certain crime, and ultimately, to prevent further crimes from happening.

This paper analyzes the characteristics and influence mechanisms of financial support for China’s strategic emerging industries. Using a sample of 356 listed companies across nine major industries, we conduct an in-depth analysis of the efficiency of financial support and its influencing factors. In addition, this paper analyzes the influence mechanism of financial support for strategic emerging industries based on the relevant theory of financial support for industry development. It clarifies the internal and external influencing factors. Based on the theoretical analysis, a two-stage empirical investigation was conducted: The data of 356 listed companies in strategic emerging industries from 2010 to 2022 were selected as a sample, and the data envelopment analysis (DEA) method was applied to measure efficiency. The influencing factors were then analyzed using a Tobit regression and an intermediate effects test.

Our study evaluated the effect of vanadium (V) on the behavior of Zinnia elegans “double variegated”. In this experiment, Zinnia plants grown in a greenhouse were fed with a nutrient solution and two concentrations of vanadium (0, 6, and 10 μm) applied four times during the experiment. The V at its levels of 6 µm and 10 µm increased plant length, number of inflorescences and fresh weight. We observed that during the development and appearance of flower buds, and flowering were earlier with the addition of 6 µm and 10 µm. During harvest the changes in size and shape were homogeneous with the control treatment. With the addition of 6 µm, flowers of different sizes were induced, with non-uniform petals, but with different shades of color. With 10 µm the shape of the petals, the distance between them and changes in the shades of the flowers were modified. The postharvest life for the flowers of the control treatment was shorter (15 days), the petals, anthers and floral disc at this time were observed in a poor condition. While 6 µm and 10 µm had a longer postharvest life (20 days), the flowers had a good presentation, their colors were more intense compared to the harvest stage. The application of this beneficial element contributed to the development and flowering of Zinnia in the greenhouse. It is suggested that future research be carried out on the accumulation and/or concentration of vanadium in the different stages of growth or its effect on the concentration of other nutrients.

Vehicle detection stands out as a rapidly developing technology today and is further strengthened by deep learning algorithms. This technology is critical in traffic management, automated driving systems, security, urban planning, environmental impacts, transportation, and emergency response applications. Vehicle detection, which is used in many application areas such as monitoring traffic flow, assessing density, increasing security, and vehicle detection in automatic driving systems, makes an effective contribution to a wide range of areas, from urban planning to security measures. Moreover, the integration of this technology represents an important step for the development of smart cities and sustainable urban life. Deep learning models, especially algorithms such as You Only Look Once version 5 (YOLOv5) and You Only Look Once version 8 (YOLOv8), show effective vehicle detection results with satellite image data. According to the comparisons, the precision and recall values of the YOLOv5 model are 1.63% and 2.49% higher, respectively, than the YOLOv8 model. The reason for this difference is that the YOLOv8 model makes more sensitive vehicle detection than the YOLOv5. In the comparison based on the F1 score, the F1 score of YOLOv5 was measured as 0.958, while the F1 score of YOLOv8 was measured as 0.938. Ignoring sensitivity amounts, the increase in F1 score of YOLOv8 compared to YOLOv5 was found to be 0.06%.

The article aims at developing an efficient and stable catalysts for simultaneous hydrogenation of o-chloronitrobenzene to o-chloroaniline and 1,4-butanediol dehydrogenation to γ-butyrolactone. A series of CoO-Cu-MgO catalysts, composed of 10 wt% of copper, various amount of cobalt loadings (1, 5 and 10 wt%) and remaining of MgO were developed by co-precipitation followed by thermal treatment. o-Chloroaniline and γ-butyrolactone were the main products with high yield of 85% and 90%, respectively. The advantage of the coupling process is that the hydrogenation reaction was conducted without external hydrogen, demonstrating minimize the hydrogen consumption known as hydrogen economy route. From N₂O characterization results, the high activity of 5CoO-10Cu-MgO was found that it has high amount of Cu species (Cu⁰/Cu⁺¹) which govern the stable activity and selectivity on time on stream study in presence of cobalt in Cu-MgO.