ABSTRACT
Although citric acid (CA) has antioxidant, antibacterial, and acidulating properties, chronic ingestion of CA can cause urolithiasis, hypocalcemia, and duodenal cancer, emphasizing the need for early detection. There are very few documented electrochemical-based sensing methods for CA detection due to the challenging behavior of electrode fouling caused by reactive oxidation products. In this study, a novel, non-enzymatic, and economical electrochemical sensor based on cobalt oxide nanoparticles (CoOxNPs) is successfully reported for detection CA. The CoOxNPs were synthesized through a simple thermal decomposition method and characterized by SEM, FT-IR, EDX, and XRD techniques. The proposed sensing platform was optimized by various parameters, including pH (7.0), time (15 min), and concentration of nanoparticles (100 mM) etc. In a linear range of 0.05-2500 µM, a low detection limit (LOD) of 0.13 µM was achieved. Theoretical calculations (ΔRT), confirmed hydrogen bonding and electrostatic interactions between CoOxNPs and CA. The detection method exhibited high selectivity in real media like food and biological samples, with good recovery values when compared favorably to the HPLC method. To facilitate effective on-site investigation, such a sensing platform can be assembled into a portable device.
ABSTRACT
Quinoa is a highly nutritious and abiotic stress-tolerant crop that can be used to ensure food security for the rapidly growing world population under changing climate conditions. Various experiments, based on morphology, phenology, physiology, and yield-related attributes, are being conducted across the globe to check its adoptability under stressful environmental conditions. High weed infestation, early stand establishment, photoperiod sensitivity, loss of seed viability after harvest, and heat stress during its reproductive stage are major constraints to its cultivation. The presence of saponin on its outer surface is also a significant restriction to its local consumption. Scientists are using modern breeding programs, such as participatory approaches, to understand and define breeding goals to promote quinoa adaptation under marginalized conditions. Despite its rich nutritional value, there is still a need to create awareness among people and industries about its nutritional profile and potential for revenue generation. In the future, the breeding of the sweet and larger-grain quinoa varietals will be an option for avoiding the cleaning of saponins, but with the risk of having more pests in the field. There is also a need to focus on mechanized farming systems for the cultivation, harvesting, and processing of quinoa to facilitate and expand its cultivation and consumption across the globe, considering its high genetic diversity.
ABSTRACT
The roots of Wireless Sensor Networks (WSNs) are tracked back to US military developments, and, currently, WSNs have paved their way into a vast domain of civil applications, especially environmental, critical infrastructure, habitat monitoring, etc. In the majority of these applications, WSNs have been deployed to monitor critical and inaccessible terrains; however, due to their unique and resource-constrained nature, WSNs face many design and deployment challenges in these difficult-to-access working environments, including connectivity maintenance, topology management, reliability, etc. However, for WSNs, topology management and connectivity still remain a major concern in WSNs that hampers their operations, with a direct impact on the overall application performance of WSNs. To address this issue, in this paper, we propose a new topology management and connectivity maintenance scheme called a Tolerating Fault and Maintaining Network Connectivity using Array Antenna (ToMaCAA) for WSNs. ToMaCAA is a system designed to adapt to dynamic structures and maintain network connectivity while consuming fewer network resources. Thereafter, we incorporated a Phase Array Antenna into the existing topology management technologies, proving ToMaCAA to be a novel contribution. This new approach allows a node to connect to the farthest node in the network while conserving resources and energy. Moreover, data transmission is restricted to one route, reducing overheads and conserving energy in various other nodes' idle listening state. For the implementation of ToMaCAA, the MATLAB network simulation platform has been used to test and analyse its performance. The output results were compared with the benchmark schemes, i.e., Disjoint Path Vector (DPV), Adaptive Disjoint Path Vector (ADPV), and Pickup Non-Critical Node Based k-Connectivity (PINC). The performance of ToMaCAA was evaluated based on different performance metrics, i.e., the network lifetime, total number of transmitted messages, and node failure in WSNs. The output results revealed that the ToMaCAA outperformed the DPV, ADPV, and PINC schemes in terms of maintaining network connectivity during link failures and made the network more fault-tolerant and reliable.
Subject(s)
Computer Communication Networks , Wireless Technology , Algorithms , Computer Simulation , Reproducibility of ResultsABSTRACT
Despite its importance, no study investigates the effects of COVID-19 on the mental condition of international students in China. By using data from international students in China, this study finds the positive and affirmative connection between fear of COVID-19 and generalized anxiety disorder among foreign students. Furthermore, this study reveals a negative association between fear of COVID-19 and the psychological well-being of foreign students in China. We also find that emotional intelligence has a positive and optimistic moderating influence on the relationship between fear of COVID-19 and generalized anxiety disorder but it has not moderating effect on the relationship between fear of COVID-19 and psychological well-being. Our study contributes to the body and knowledge and offers new insights concerning the effects of COVID-19 on the mental condition of international students.
