Flower-visiting insects may be pollinators or, conversely, unrelated to the reproductive process of plants. Interactions between pollinating and non-pollinating flower visitors can negatively influence pollen transfer. Little is known about the effects of bee visits on pollination of squash (Cucurbita spp.) flowers and their interactions with the presence of other floral visitors. The study was conducted at the Facultad de Ciencias Agrarias (Universidad Nacional de Rosario) in the south of Santa Fe (Argentina) and evaluated the effect of the presence of non-pollinating floral visitors on bee foraging in the flowers of two cultivated squash species. Flower sex and squash species C. maxima and C. moschata were included as variables. A total of 937 visitors were recorded in 403 flowers. Bees of the tribes Eucerini and Apini were the most abundant pollinators with an average of 2.3 individuals per flower during 10 minutes of observation. Diptera, flower sex and squash species did not influence the number of bee visits, whereas the prolonged stay of coleoptera and formicids negatively affected the presence of bees on both squash species. The presence of coleoptera reduced bee visits by 38%, while in the presence of ants, bees did not visit the flowers. The theft of nectar and pollen by non-pollinating floral visitors could have a negative effect on the reproductive success of squash.

The healthcare sector is progressively modest and patients expect higher service quality; therefore, healthcare practitioners’ and academic researchers’ attention upsurges in exploring service quality, intensifying satisfaction and generating behavioral intention. Despite the significance of the healthcare sector and the importance of quality-related matters, there is a paucity of research and publications dealing with healthcare service quality. This conceptual review evaluates the service quality in Pakistani healthcare sector rendering patients’ perspective. The proposed model emphasizes patients’ switching intention caused by poor or inadequate service quality through intervening constructs of satisfaction and alternative attractiveness. Additionally, current review explored the alternative attractiveness as mediator which was neglected in healthcare context. The model also attempts to propose the association between alternative attractiveness and outcome variable by switching costs regarding patients’ perspectives. The conceptual framework enables hospital managers to comprehend how patients assess healthcare quality provided in the presence of alternatives. The perception of patients would assist them in allocating healthcare resources and hospital management attain performance feedback through service quality parameters. Present review developed an inclusive framework as a novel injector in healthcare sector for patients’ perceived service quality.

This study is based on the theory of planned behaviour, and its aim is to understand the impact of doctoral pursuit intention on the doctoral preparatory behaviour of female teachers in independent colleges in China, as well as to determine the moderating effect of perceived risk between doctoral pursuit intention and doctoral preparatory behaviour. The participants in the study were female teachers from independent colleges in China, who were recruited between February and March 2024 based on convenience sampling. 776 valid questionnaires were obtained, and the data were analyzed using a hierarchical regression method. According to the results, a doctoral pursuit intention has a significant and positive predictive effect on doctoral preparatory behaviour, while the perceived risk has a significant and negative moderating effect between doctoral pursuit intention and doctoral preparatory behaviour. This indicates that female teachers with high doctoral pursuit intention more actively prepare to pursue a doctoral degree when the perceived risk is low, whereas the doctoral preparatory behaviour of those with high perceived risk shows a limited increase as their doctoral pursuit intention increases. Therefore, female teachers’ pursuit of a doctoral degree should be supported on an individual basis and analysed within the broader context of the transformation of independent colleges.

This study investigated the use of digital story strategy in teaching Islamic education on achievement and how it affects the development of moral thinking. The quasi-experimental design was implemented as a methodology and the sample included of (60) students from the fourth grade from Abdul Rahman bin Awf School in Abha. The results showed that there are statistically significant differences at the significance level (α ≤ 0.05) between the average responses of students in the two groups in the test. The experimental group performed better than the control group. The findings also showed that there are statistically significant differences at the significance level (α ≤ 0.05) between the average responses of students in the two groups (experimental and control) in the moral thinking scale and favour of the experimental group.

Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.