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The aim of this study is to present a model proposal on determining the student participation rate in synchronous courses given in Learning Management Systems (LMS). Especially in situations where equal opportunities cannot be provided or opportunities are limited, distance education provides benefits for learning anytime and anywhere (ubiquitous learning) with the support of educational technologies. When the literature is examined, thanks to distance education; It is seen that it offers a very advantageous teaching environment in terms of location, time, convenience in accessing the resources needed and cost-benefit. However, when the literature is analyzed, it is found that there is a problem in determining the participation levels and rates of students in the Learning Management Systems used in distance education. Students access the activity or course in LMS using text-based user information and passwords. Unfortunately, it is not possible to determine with the current LMS whether the participant is the real responsible person or he/she is actively/synchronously following the course. In this context, a design model has been presented using face recognition algorithms to determine attendance in distance education, to ensure more active participation and to increase success indirectly. In the proposed model, tests were made using special filters for image processing, and in cases where the number of samples was increased, more than 80% accuracy was provided. The proposed design model was developed in Visual Studio.Net platform and coded on C# programming language. SQL server is used as database management system and EmguCV library is used for the image processing stages.

This paper investigates the time-varying effects of fossil fuel consumption on CO2 emissions in India utilizing the time-varying cointegration test, allowing for multivariate long-run time-varying cointegration parameter developed by Bierens and Martins (2010) and the time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005). The long-run time-varying coefficients reveal that GDP has a positive and increasing impact on CO2 emissions over time. Moreover, results confirm the polluting effects of all fossil fuels. Besides, the TVP-VAR model findings also demonstrate that changes in income and fossil fuel consumption have a positive and significant impact on environmental degradation. Coal is found to be the most polluting fuel, followed by oil consumption. Furthermore, the time-varying responses show that increased natural gas consumption has the least influence when compared to other fossil fuels on CO2 emissions. [ABSTRACT FROM AUTHOR]

Drawing on the theory of contracts and Schumpeterian models of innovation, we demonstrate that information asymmetry and risk aversion are conducive to effect-size heterogeneity and sub-optimal allocation of R&D subsidies. Utilising an unbalanced panel of 43,650 British firms from 1998 to 2012 and an entropy balancing methodology, we find that R&D subsidies are less likely to generate additionality effects when: (a) firms are larger, older, or more R&D-intensive; and (b) investment in basic research or during crisis episodes is considered. We also report that over 85% of the subsidies are allocated to large, old and R&D-intensive firms that do not deliver additional R&D investment. Our findings reveal a policy conundrum: the case for R&D subsidies is stronger during economic downturns, when R&D investment is in basic research and when firm age, size and R&D intensity reflect success in converting R&D investment into innovative product lines; but the subsidy is less likely to increase business R&D under these conditions. [ABSTRACT FROM AUTHOR]

Hypertension prevalence is increasing in patients with hemophilia. Therefore it is an important complication of hemophilia. We aimed to present a 49-year-old male patient with hemophilia-A who presented with acute hemarthrosis and hypertensive attack. The patient was treated in our internal medicine clinic.

This paper investigates the relationship between CO2 emissions, energy consumption, economic growth, and foreign direct investment for a sample of Asia-Pacific Economic Cooperation Countries (APEC) countries from 1981:Q1 to 2021:Q1 employing panel data methodology. We identify cross-sectional dependence and hence utilize the cross-sectional augmented Dickey-Fuller panel unit root test for appropriate estimation. The cointegration test developed by Westerlund (2008) reveals a long-run equilibrium between CO2 emissions, energy consumption, economic growth, and foreign direct investment. Long-run parameter estimates based on Common Correlated Effect Mean Group indicate that an increase in FDI inflows has a negative impact on air quality, supporting the pollution haven hypothesis. The cointegration test results also show that the impact of Gross Domestic Product (GDP) on CO2 emissions varies by country in the estimation sample. In contrast to the mixed evidence on the effects of other variables, the increase in energy consumption is positively and significantly affecting CO2 emissions in all APEC countries. Emirmahmutoglu and Kose Econ Model 28:870-876, (2011)'s panel causality test results show a bidirectional relationship between FDI and CO2 emissions in Japan. Furthermore, there is a bidirectional causal relationship between GDP and energy consumption in Australia, China, Japan, and Singapore. Overall, empirical evidence suggests that APEC countries should adhere to strict regulations and invest in environmental-friendly clean technologies to attract foreign direct investment. [ABSTRACT FROM AUTHOR]