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                <text>Isaac Ankrah, Michael Appiah-Kubi, Eric Ofosu Antwi, Ivy Drafor Amenyah, Mohammed Musah, Frank Gyimah Sackey, Richard Asravor, Isaiah Sikayena</text>
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                <text>This study investigates the impact of fossil fuel industry on renewable energy deployment in emerging oil-producing economies, using Ghana as the subject of analysis. Drawing on the "theory of lobby," the study extends previous analyses to examine how fossil fuel production influences the possibility of transitioning to renewable energy. The results, based on a stepwise estimation technique, within a two-regime Markov-switching Model, show a consistent negative relationship between fossil fuel production and renewable energy deployment, supporting the lobby effect theory in Ghana's energy economy. Notably, while fossil fuel production initially increases the probability of transitioning to renewable energy (from 39.65 % to 58.42 %), this trend is reversed by foreign direct investment, reducing the likelihood to approximately 42 %. These findings underscore the need to expand the lobby-effect theory to include …</text>
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                <text>The integration of new digital technologies amid a rising population in many emerging economies imposes incessant pressure on their energy systems. It has become crucial to draw result implications for future energy sustainability by exploring all relevant issues, particularly in light of how Information and Communication Technologies (ICT) influence electricity demand. Using the West African region as the subject of analysis, this study provides insights into the implied connection, taking into account the region’s disparate cultural and linguistic patterns. The study is complemented by a result-based analysis of the socioeconomic and policy implications. The outcomes, derived from the application of a dynamic panel data model to a dataset spanning 1990-2021, show that ICT adoption has significant implications on electricity consumption, with notable positive impact observed in the long run. Interestingly, this effect is largely driven by French-speaking countries in the region. Beyond this statistical revelation, this study underscores the need for a balanced approach to address the ICT-electricity demand interplay. An important conclusion emerges: Embracing digitalization while ensuring energy security and sustainability can unlock economic growth, promote social inclusion, and foster a sustainable future for West Africa.</text>
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                <text>Automatic pancreas segmentation of CT scans enables physicians to identify and monitor the abnormalities in the pancreas. This facilitates intraoperative assistance, surgical planning, prognosis, and diagnosis. Nonetheless, the size and location of the pancreas in the CT image input data present a significant challenge for automatic segmentation, and the intricacy of the background region confounds deep segmentation networks. To solve this difficulty, we propose the Encoder-Corollary Atrous Spatial Pyramid Pooling-Decoder Network (EcD-Net) for locating and segmenting the pancreas. This two-tiered method begins with a coarse segmentation stage for locating the pancreas within the overall CT image. Using the detected image from the first tier, a fine segmentation network based on U-Net is applied to segment the target organ (pancreas). A novel Saturated Multi-view Dense Module (SMD- Module) is …</text>
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                <text>Automatic pancreas segmentation of CT scans enables physicians to identify and monitor the abnormalities in the pancreas. This facilitates intraoperative assistance, surgical planning, prognosis, and diagnosis. Nonetheless, the size and location of the pancreas in the CT image input data present a significant challenge for automatic segmentation, and the intricacy of the background region confounds deep segmentation networks. To solve this difficulty, we propose the Encoder-Corollary Atrous Spatial Pyramid Pooling-Decoder Network (EcD-Net) for locating and segmenting the pancreas. This two-tiered method begins with a coarse segmentation stage for locating the pancreas within the overall CT image. Using the detected image from the first tier, a fine segmentation network based on U-Net is applied to segment the target organ (pancreas). A novel Saturated Multiview Dense Module (SMD-Module) is presented to enhance information gradient flow for the stability of the training process and easier convergence at the fine stage. A novel Corollary Atrous Spatial Pyramid Pooling Module (CASPP-Module) is proposed to simultaneously capture low-level details and high-level global context information to enhance the pancreas segmentation accuracy, extract global and local spatial data, and detect the pancreas at varied scales. On the publicly available National Institute of Health (NIH) pancreas dataset, our proposed EcD-Net surpasses previous state-of-the-art methods with a mean Dice Similarity Coefficient (DSC) of 88.84%, mean Precision (PRE), Recall (REC), and Intersection over Union (IoU) of 91.85%, 88.21%, and 89.94% respectively …</text>
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                <text>https://www.researchgate.net/profile/Benjamin-Ghansah-2/publication/385323071_EcD-Net_Encoder-Corollary_Atrous_Spatial_Pyramid_Pooling-Decoder_Network_for_Automated_Pancreas_Segmentation_of_2D_CT_Images/links/672b2cc277f274616d5eeb25/EcD-Net-Encoder-Corollary-Atrous-Spatial-Pyramid-Pooling-Decoder-Network-for-Automated-Pancreas-Segmentation-of-2D-CT-Images.pdf?__cf_chl_tk=w.nKPPDQX976.WVdYddVY05V2Jyar6C34yuuacFRMX4-1741103602-1.0.1.1-Wf2eFlbEa6zXih_DPuzs32K2hnghe4vR_vCrGwYG2OI</text>
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                <text>Capital structure decisions are the most crucial decisions taken by corporate organizations, as these decisions have massive impact on the overall cost of capital weighted average and the resultant profitability and market value of shares. Most of the researches conducted on capital structure concluded that there is an optimal capital structure that is affected by a variety of internal and external factors. These factors usually differ from country to country and industry to industry. This paper using a case study methodology, investigated the determinant of capital structure of oil companies in Ghana. The study examined how internal factors such as profitability, asset tangibility, growth, size and riskiness of a firm impacts on the capital structure of the two listed oil marketing companies in Ghana (GOIL and TOTAL) for the period between 2005 and 2014 using ordinary least square regression. The findings indicated that all the factors have significant impact on financial leverage.</text>
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                <text>Effect of Chinese foreign direct investment on economic growth in Africa</text>
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This study aims to examine the quantitative effect and direction of Chinese Foreign Direct Investment (FDI) on economic growth in Africa using a sample of 20 African countries from 2003 to 2012 with data obtained from United Nations Conference on Trade and Development and the World Bank.&#13;
Design/methodology/approach&#13;
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The study finds that a 1 per cent increase in China’s FDI stock in Africa significantly increases Africa’s gross domestic product (GDP) growth by 0.607 per cent, all things being equal. Furthermore, the study finds that a causal link exists between GDP growth in Africa and China’s …</text>
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                <text>Purpose–This study aims to examine the quantitative effect and direction of Chinese Foreign Direct Investment (FDI) on economic growth in Africa using a sample of 20 African countries from 2003 to 2012 with data obtained from United Nations Conference on Trade and Development and the World Bank.&#13;
Design/methodology/approach–The study used panel least squares regression, specifically fixed effect model to examine the quantitative effect of Chinese FDI on economic growth in Africa. The study also used Granger causality test to examine whether a causal relationship exists between economic growth and China’s FDI in Africa.&#13;
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