Financial Globalisation and Total Factor Productivity Growth in Pakistan

The study aimed at examining the impact of financial globalisation and natural resource rents on Total Factor Productivity growth in Pakistan. The total factor productivity growth is computed by the growth accounting model assuming the Cobb-Douglas production Function, while the KOF index of globalisation is used to quantify financial globalisation. The series encompassed the time period from 1985 to 2019, and in order to get empirical results, an Autoregressive Lag Distributed Model is used. The empirical outcomes proved that financial globalisation positively impacts productivity. Hence, the propositions put forth by endogenous growth and new trade theories that globalisation has a central role in achieving productive growth are confirmed by the empirical findings of this study. On the other hand, the results indicated that rent-seeking behaviour concerning natural resources has a negative influence on total factor productivity growth in the long run demonstrating a natural resource curse exists for Pakistan’s economy. Based on its findings, the study recommended that promoting outward-oriented policies with a primary focus on financial integration is crucial for augmenting the overall productivity of domestic factors of production. Likewise, it is imperative to discourage rent-seeking behaviour from natural resources to increase the factor’s productivity

A Comparison of Perspectives of Special and Regular Education Teachers on Inclusive Education

Many teachers feel unprepared to meet the educational needs of students with disabilities in the general education classroom setting. Presently, limited information exists about the separate viewpoints general and special education teachers hold about providing inclusive education. The purpose of this causal-comparative study is to compare the perspectives of inclusive education held by general and special education teachers located in the state of North Carolina. The perspective about inclusive education will be measured using the Multidimensional Attitudes toward Inclusive Education Scales (MATIES). The framework guiding this study is the Ajzen theory of planned behavior which explains that one’s beliefs, attitude toward behavior, subjective norms, and perceived control, together shape an individual’s behavioral intentions and behaviors. Therefore, to understand teacher behavior in relation to teaching in an inclusive classroom, this study looked to understand their attitude about inclusive education, their belief of social norms, and the control they have over their own behavior through the use of the MATIES. The instruments were administered through the use of SurveyMonkey online survey platform. A MANOVA was used to analyze the data

Climate Change: The Ultimate Cereal Killer: The Impact of Temperature and Precipitation on Agricultural Yields

The global food supply depends on agricultural production, but as the negative effects of climate change are exacerbated by human activity, how will agriculture need to change to accommodate both climate change and the increasing population? In order to understand what adaptations will be necessary, we perform analysis on the relationship between climate change (temperature and precipitation) and crop yields (barley, rice, and soybean). We take a multinational approach, using ten countries for each model, to see the global impact of climate change on production. Testing many models, we settle on country-specific time trends, eliminating many confounding variables by focusing on climate’s effect on variations from the trend. For all three crops, the analysis shows that temperature has a significant effect on output while precipitation has a negligible effect. The models account for upwards of 96% of the variation from the trend for each crop on a year-by-year basis. In a similar way to how irrigation has altered agriculture\u27s reliance on natural water supplies, we now need to focus on developing technology to counteract the effects of increasing temperatures on crop growth

Pierre Daviault, « L'éminent puriste » ? Conception de la langue française et de l'anglicisme au Canada d'un traducteur-chroniqueur

Ce mémoire s’intéresse à la vision de la langue et de l’anglicisme de Pierre Daviault. Ce traducteur-chroniqueur a été étiquetté de puriste par ses contemporains en raison de certains discours alarmants sur l’état de la langue française au Canada entre les années 1930 et 1960. Dans ce mémoire, nous nous intéressons à cette étiquette de puriste en analysant sa vision de la langue française parlée au Canada et comment celle-ci est influencée par les phénomènes de variation. Nous étudions aussi sa position en tant que chroniqueur par rapport aux anglicismes, ainsi que le rôle qu’il attribue aux traducteurs dans le processus d’anglicisation de la langue. Enfin, nous nous intéressons aux solutions qu’il propose pour combattre l’anglicisation de la langue dont une a été un élément clé dans le développement de la profession de traducteur au Canada. Pour ce faire, nous analysons un corpus de 24 articles publiés dans différentes revues scientifiques et littéraires et de deux chroniques de langue : « Parlons mieux : épurons notre langue » (1930-1931) et « Propos sur notre français » (1952-1960)

A hybrid method for traumatic brain injury lesion segmentation

Traumatic brain injuries are significant effects of disability and loss of life. Physicians employ computed tomography (CT) images to observe the trauma and measure its severity for diagnosis and treatment. Due to the overlap of hemorrhage and normal brain tissues, segmentation methods sometimes lead to false results. The study is more challenging to unitize the AI field to collect brain hemorrhage by involving patient datasets employing CT scans images. We propose a novel technique free-form object model for brain injury CT image segmentation based on superpixel image processing that uses CT to analyzing brain injuries, quite challenging to create a high outstanding simple linear iterative clustering (SLIC) method. The maintains a strategic distance of the segmentation image to reduced intensity boundaries. The segmentation image contains marked red hemorrhage to modify the free-form object model. The contour labelled by the red mark is the output from our free-form object model. We proposed a hybrid image segmentation approach based on the combined edge detection and dilation technique features. The approach diminishes computational costs, and the show accomplished 96.68% accuracy. The segmenting brain hemorrhage images are achieved in the clustered region to construct a free-form object model. The study also presents further directions on future research in this domain