The scope of this study is to analyze the carbon emissions intensity of electricity generation in "Belt and Road Initiative" (BRI) countries. The total CO emissions from electricity generation in BRI nations increases from 4232.34 Mt in 2013 to 4402.38 Mt in 2015, accounting for 34.45% of global CO emissions from electricity generation. Logarithmic mean Divisia index methodology is applied to analyze the drivers of carbon emissions intensity in BRI nations. The decomposition results revealed that the regional carbon emissions intensity in BRI nations increases during 2013-2015 and the power generation efficiency is the essential factor to improve carbon emissions performance in BRI developing countries. For BRI developing countries, promoting clean and efficient thermal power is a pragmatic priority for green power development.
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http://dx.doi.org/10.1007/s11356-019-04860-5 | DOI Listing |
Zh Nevrol Psikhiatr Im S S Korsakova
December 2024
Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia.
Objective: To compare biomarkers of neurovascular unit (NVU) - S100β, NSE, BDNF and indicators of the brain electrical activity in patients who underwent coronary artery bypass grafting (CABG) depending on the use of different versions of multi-tasking cognitive training (CT).
Material And Methods: The study included 89 people, of whom 47 completed the CTI (postural and three cognitive tasks (counting backwards, verbal fluency and the open-ended task «Unusual use of an ordinary object») and 42 patients, who underwent CTII (visuomotor reaction and the same cognitive tasks) in the early postoperative CABG period. The patients of both groups underwent complex testing of psychomotor, executive functions, attention, short-term memory and EEG study in the perioperative period of CABG.
Macromol Rapid Commun
December 2024
Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles, St. Gallen, 9014, Switzerland.
Facemask materials have been under constant development to optimize filtration performance, wear comfort, and general resilience to chemical and mechanical stress. While single-use polypropylene meltblown membranes are the established go-to material for high-performing mask filters, they are neither sustainable nor particularly resistant to sterilization methods. Herein an in-depth analysis is provided of the sterilization efficiency, filtration efficiency, and breathing resistance of selected aerosol filters commonly implemented in facemasks, with a particular focus on the benefits of nanofibrous filters.
View Article and Find Full Text PDFNat Biomed Eng
December 2024
Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
Deep brain stimulation (DBS), a proven treatment for movement disorders, also holds promise for the treatment of psychiatric and cognitive conditions. However, for DBS to be clinically effective, it may require DBS technology that can alter or trigger stimulation in response to changes in biomarkers sensed from the patient's brain. A growing body of evidence suggests that such adaptive DBS is feasible, it might achieve clinical effects that are not possible with standard continuous DBS and that some of the best biomarkers are signals from the cerebral cortex.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, 03680, Ukraine.
Microgrids (MGs) have gained significant attention over the past two decades due to their advantages in service reliability, easy integration of renewable energy sources, high efficiency, and enhanced power quality. In India, low-voltage side customers face significant challenges in terms of power supply continuity and voltage regulation. This paper presents a novel approach for optimal power scheduling in a microgrid, aiming to provide uninterrupted power supply with improved voltage regulation (VR).
View Article and Find Full Text PDFSci Rep
December 2024
School of Electrical and Information, Hunan University, Changsha, 410083, China.
Accurately predicting solar power to ensure the economical operation of microgrids and smart grids is a key challenge for integrating the large scale photovoltaic (PV) generation into conventional power systems. This paper proposes an accurate short-term solar power forecasting method using a hybrid machine learning algorithm, with the system trained using the pre-trained extreme learning machine (P-ELM) algorithm. The proposed method utilizes temperature, irradiance, and solar power output at instant i as input parameters, while the output parameters are temperature, irradiance, and solar power output at instant i+1, enabling next-day solar power output forecasting.
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