RF Sputtered CeO2 Thin Films-Based Oxygen Sensors

In this paper, we report the scalable, high sensitivity, fast response, and low operating temperature Cerium oxide (CeO2) thin film-based oxygen sensors by optimizing CeO2 film thickness. CeO2 thin films of thickness ranging from 90 to 340 nm have been deposited at 400 degrees C using radio frequency (RF) magnetron sputtering on Al2O3 substrates. Ellipsometry, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM) have been used to characterize the CeO2 films for their thickness, structural, compositional/chemical, and surface morphology properties. Gas sensors have been fabricated using CeO2 film as a sensing material and tested in an oxygen gas environment. CeO2 film with an optimum thickness of 260 nm has shown high sensitivity (12.6) and fast response time (<= 10 s) along with fast recovery time (15 s) at a low operating temperature of 400 degrees C. To the best of our knowledge, these are the best values reported till date for undoped CeO2 thin film-based oxygen sensors. Furthermore, from the sensor's response, it was observed that there was no drifting from the baseline. This superior performance of CeO2 thin film-based oxygen sensor may be attributed to the combination of three factors, i.e., 1) high surface energy and reactivity due to the presence of (200) oriented CeO2 plane; 2) low resistance due to better crystallinity; and 3) perfect stoichiometry with required roughness

Optimal DG Placement in Power Systems Using a Modified Flower Pollination Algorithm

There is a huge requirement for power systems to reduce power losses. Adding distributed generators (DGs) is the most common approach to achieving lower power losses. However, several challenges arise, such as determining the ideal size as well as location of the utilized distributed generators. Most of the existing methods do not consider the variety of load types, the variety and size of the utilized DGs besides reducing the convergence time and enhancing the optimization results. The paper performed an optimization algorithm that integrated a golden search-based flower pollination algorithm and fitness-distance balance (FDB) to find out the optimal size as well as the location of the distributed generators. It was then compared with different optimization methods to determine the best optimization technique, and it was determined to be the best technique. In addition, different types of DGs are considered, including solar energy, wind energy, and biogas, along with optimizing the size of the utilized DGs to reduce the system cost. Testing with different types of bus systems, and different types of DGs in a radial distribution system was done to reveal that the modified flower pollination with golden section search was superior in comparison to others with regards to convergence and power loss reduction

CO₂ Emission Analysis for Different Types of Electric Vehicles When Charged from Floating Solar Photovoltaic Systems

Renewable energy and electric vehicle technology are the two pillars for achieving a sustainable future. Floating solar power plants use PV modules on water infrastructure to save the land and increase module efficiency. Furthermore, the reduction in evaporation saves water. Electric vehicles are one of the fastest-growing markets and the most successful technologies to combat the problem of energy and climate change. This research aims to construct a floating PV system on the lake of the Vellore Institute of Technology (VIT), to analyze electric vehicle performance and greenhouse gas (GHG) emissions when charged using the installed floating PV system. To address this, a 1.5 MWP floating PV system was simulated and analyzed using Helioscope software. When charged from the proposed floating PV plant, electric bikes, scooters, and cars saved CO2 emissions. When charged from a floating PV, E-bike, E-scooter, and E-car Net CO2 emissions became zero in 25.5, 12.1, and 7.7 months, respectively. After the aforementioned time periods, all three electric vehicle types were zero-emission vehicles. The required charge for all three types of vehicles (1,000,000 km) was analyzed using a floating PV system. E-bike, E-scooter, and E-car CO2 emission savings were −8,516,000 g/kWh, −328,000 g/kWh, and 525,600,000 g/kWh, respectively. All three types of electric vehicles can reduce CO2 emissions for nations that rely on renewable energy, but only electric cars save carbon emissions over fixed distances. Through this research, we finally conclude that electric cars reduce CO2 emissions the most compared to other electric vehicles

Sex difference in clot lysability and association to coronary artery calcification

Abstract Background Incidence and prevalence of cardiovascular disease (CVD) differ between sexes, and women experience CVD later than men. Changes in fibrin clot lysability are associated with CVD, and the present study addresses sex differences in fibrin clot lysability in asymptomatic middle-aged individuals and the relation to coronary artery calcification (CAC). Methods Participants free of morbidities and medication, N = 163, were randomly chosen from a national registry among citizens, 50 or 60 years of age, and were followed for 5 years. CAC was determined by the Agatston (Ag) score both at baseline and at follow-up. Based on the changes in Ag, the population was divided into two groups: ΔAg = 0 U or ΔAg > 0 U. Fibrin clot analyses were based on turbidimetric methods. Results At baseline, 116 women and 97 men were included; 84 women and 79 men completed the 5-year follow-up (77%). Independently of covariates, women with ΔAg > 0 had reduced mean (SD) fibrin lysability at follow-up, 40.2% (15.9), both in comparison to baseline, 47.8% (20.4), p = 0.001, to women with ΔAg = 0 U, 51.2% (24.5), p = 0.028, and to men with ΔAg > 0 U, 54.4% (21.0), p = 0.002. Conclusions Fibrin clot lysability changes over time with considerable sex differences. Women with progression of CAC have reduced fibrin clot lysability compared to men, indicating a sex-specific association between morphological vessel wall changes and fibrin clot lysability

CO2 Emission Analysis for Different Types of Electric Vehicles When Charged from Floating Solar Photovoltaic Systems

Renewable energy and electric vehicle technology are the two pillars for achieving a sustainable future. Floating solar power plants use PV modules on water infrastructure to save the land and increase module efficiency. Furthermore, the reduction in evaporation saves water. Electric vehicles are one of the fastest-growing markets and the most successful technologies to combat the problem of energy and climate change. This research aims to construct a floating PV system on the lake of the Vellore Institute of Technology (VIT), to analyze electric vehicle performance and greenhouse gas (GHG) emissions when charged using the installed floating PV system. To address this, a 1.5 MWP floating PV system was simulated and analyzed using Helioscope software. When charged from the proposed floating PV plant, electric bikes, scooters, and cars saved CO2 emissions. When charged from a floating PV, E-bike, E-scooter, and E-car Net CO2 emissions became zero in 25.5, 12.1, and 7.7 months, respectively. After the aforementioned time periods, all three electric vehicle types were zero-emission vehicles. The required charge for all three types of vehicles (1,000,000 km) was analyzed using a floating PV system. E-bike, E-scooter, and E-car CO2 emission savings were &minus;8,516,000 g/kWh, &minus;328,000 g/kWh, and 525,600,000 g/kWh, respectively. All three types of electric vehicles can reduce CO2 emissions for nations that rely on renewable energy, but only electric cars save carbon emissions over fixed distances. Through this research, we finally conclude that electric cars reduce CO2 emissions the most compared to other electric vehicles

NT-proBNP on Cobas h 232 in point-of-care testing: Performance in the primary health care versus in the hospital laboratory

Background. NT-proBNP may be useful for ruling out heart failure in primary health care. In this study we examined the analytical quality of NT-proBNP in primary health care on the Cobas h 232 point-of-care instrument compared with measurements performed in a hospital laboratory. Materials and methods. Blood samples requested for NT-proBNP were collected in primary health care (n = 95) and in a hospital laboratory (n = 107). NT-proBNP was measured on-site on Cobas h 232 instruments both in primary health care centres and at the hospital laboratory and all samples were also analyzed with a comparison method at the hospital. Precision, trueness, accuracy, and lot-variation were determined at different concentration levels and evaluated according to acceptance criteria. Furthermore user-friendliness was assessed by questionnaires. Results. For Cobas h 232 repeatability CV was 8.5-10.7% in the hospital setting and 5.3-10.0% in the primary health care and within the analytical quality specifications, but higher than with the comparison method (<4%). NT-proBNP results obtained in primary health care were significantly higher than by the hospital comparison method (bias ranged from 14.3-23.7%), whereas there was no significant bias when Cobas h 232 was used in the hospital setting (bias ranged from 4.9 to 7.0%). User-friendliness of Cobas h 232 was overall acceptable. Conclusion. Cobas h 232 point-of-care instrument for measurement of NT-proBNP performed satisfactorily with regard to precision, user-friendliness, and lot-variation. A decrease in NT-proBNP levels observed in samples transported to a central laboratory needs further attention and investigation