Cubic-shaped corylus colurna extract coated Cu2O nanoparticles-based smartphone biosensor for the detection of ascorbic acid in real food samples.

Ascorbic acid (AA) is a highly water-soluble organic chemical compound and plays a significant role in human metabolism. For the purpose of food quality monitoring, this study focuses on the development of a smartphone-integrated colorimetric and non-enzymatic electrochemical Corylus Colurna (CC) extract-Cu2O nanoparticles (Cu2O NPs) biosensor to detect AA in real food samples. The characterization of the CC-Cu2O NPs was determined using SEM, SEM/EDX, HRTEM, XRD, FTIR, XPS, TGA, and DSC. The CC-Cu2O NPs are cubic in shape with an approximate size of 10 nm. According to electrochemical results, the oxidation of AA at the modified electrode exhibited a LOD of 27.92 nmolL-1 in a wide concentration range of 0.55-22 mmolL-1. The fabricated digital CC-Cu2O NPs sensor successfully detected AA in food samples. This strategy provides a nanoplatform to determine the detection of AA in food samples.

Social Contact, Academic Satisfaction, COVID-19 Knowledge, and Subjective Well-being Among Students at Turkish Universities: a Nine-University Sample.

Adverse effects of COVID-19 are seen not only on the physical health of infected individuals but also on their subjective well-being. Sudden changes in social lives, lockdowns, and shifts towards online education have had a negative impact on many people, especially university students. As part of an international study, the current study focused on the well-being of students at Turkish universities in relation to social contact, academic satisfaction, and COVID-19 knowledge. A total of 7363 students from nine universities (86.6% from state universities, 71.04% female, and 73.52% at bachelor's level) participated in an online survey. Results revealed that females had lower levels of subjective well-being and academic satisfaction. According to a mediation model in the study, the relationship between social contact and well-being was mediated by academic satisfaction and COVID-19 knowledge. Our findings can guide future researchers, mental health professionals, universities, and policymakers to understand and improve subjective well-being of university students.

Highly sensitive and selective rGO based Non-Enzymatic electrochemical sensor for propamocarb fungicide pesticide detection.

In this study, reduced graphene oxide (rGO) was prepared using a green ultrasonic microwave assisted method and investigated rGO based non-enzymatic electrochemical sensor for detecting a synthetic fungicide as a propamocarb (PM) pesticide. The rGO-based sensor exhibited rapid response within 1 min, low detection limit of 0.6 µM and wide linear range of (1-5) µM with a high sensitivity of 101.1 µAµM-1 cm-2 for PM. Besides this, the sensor detected the propamocarb pesticide on the real cucumber sample with high sensitivity in the concentration range of (1-5) µM within a 1-minute cycle. The sensor is highly selective against propamocarb pesticide. The prepared non-enzymatic electrochemical sensor exhibited high sensitivity, high selectivity, reproducibility, and rapid response.