No abstract

No abstract

Intercropping legumes with cereals has been a common cropping system in short-season rainfed environments due to its increased productivity and sustainability. Intercropping barley (Hordeum vulgare L.) with Egyptian clover (Trifolium alexandrinum L.) could increase the grain yield of barley and improve resource use efficiency of the intercropping system. However, non-optimum planting geometry has been a hurdle in the adaptation of barleybased cropping systems. This study was aimed at optimizing the planting geometry, and assess the productivity and profitability of barley-Egyptian clover intercropping system. Ten different planting geometries, differing in number of rows of barley, width and number of irrigation furrows and planting method were tested. Intercropping barley with Egyptian clover improved 56-68% grain yield of barley compared with mono-cropped barley. Barley remained dominant crop in terms of aggressiveness, relative crowding coefficient and competitive ratio. The amount of water used was linearly increased with increasing size of barley strip from 3 to 8 rows. The highest water use efficiency (4.83 kg/cf 3) was recorded for 8-row barley strip system with 120 cm irrigation furrows compared to rest of the planting geometries. In conclusion, 8-rows of barley planted on beds with Egyptian clover in 120 cm irrigation furrows had the highest net income and cost benefit ratio. Therefore, it is recommended that this planting geometry can be used for better economic returns of barley-Egyptian clover intercropping system. However, barley strips with >8 rows were not included in this study, which is limitation of the current study. Therefore, future studies with >8 barley rows in strip should be conducted to infer the economic feasibility and profitability of wider barley strips.

No abstract

No abstract

Original ArticleAbstract Purpose: Contemporary literature on lung adenocarcinoma has demonstrated a genetic difference of the epidermal growth factor receptor (EGFR) pathway conferring to ethnicity, such as higher frequency of activated EGFR mutations in East Asian population. This information is missing in some developing countries, and we intend to address this gap in the literature. Methods: We examined the rate of EGFR mutations among Pakistani patients with adenocarcinoma of the lung. Fine-needle aspiration samples were gathered from 73 patients. Polymerase chain reaction was performed on extracted DNA for mutational analysis of EGFR exons 19 and 21. Results: EGFR mutations were discovered in 18 of 73 (24.6%) patients. We did not find any significant difference in EGFR mutation rate with regard to patient's age, sex, smoking history, clinical stage of lung cancer, subtypes of adenocarcinoma, and tumor differentiation. Conclusion: Our investigation shows that the EGFR mutation rate in our patient population with adenocarcinoma of the lung was higher than in African-American, Arabian, and white Caucasian patients, and was lower than the East Asian population.

The objective of this study is to investigate the effects of children advertising on children and parental influences on the children's attitude and understanding levels toward children advertisements on television. The respondents for this study were both parents and children. Among others, the study revealed the children's inability to distinguish commercials from TV programmes and to differentiate fantasy from reality. These inabilities, however, differed with children's age levels. Further, the results indicate that parents have an influence over the children's understanding levels with respect to children advertisements in television.

Background Healthcare workers are often overworked, underfunded, and face many challenges. Integration of artificial intelligence into healthcare service provision can tackle these challenges by relieving burdens on healthcare workers. Since healthcare students are our future healthcare workers, we assessed the knowledge, attitudes, and perspectives of current healthcare students at Qatar University on the implementation of artificial intelligence into healthcare services. Methods This was a cross-sectional study of QU-Health Cluster students via an online survey over a three-week period in November 2021. Chi-squared tests and gamma coefficients were used to compare differences between categorical variables. Results One hundred and ninety-three QU-Health students responded. Most participants had a positive attitude towards artificial intelligence, finding it useful and reliable. The most popular perceived advantage of artificial intelligence was its ability to speed up work processes. Around 40% expressed concern about a threat to job security from artificial intelligence, and a majority believed that artificial intelligence cannot provide sympathetic care (57.9%). Participants who felt that artificial intelligence can better make diagnoses than humans also agreed that artificial intelligence could replace their job (p  =  0.005). Male students had more knowledge (p  =  0.005) and received more training (p  =  0.005) about healthcare artificial intelligence. Participants cited a lack of expert mentorship as a barrier to obtaining knowledge about artificial intelligence, followed by lack of dedicated courses and funding. Conclusions More resources are required for students to develop a good understanding about artificial intelligence. Education needs to be supported by expert mentorship. Further work is needed on how best to integrate artificial intelligence teaching into university curricula.