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The coronaviruses are a deadly family of epidemic viruses that can spread from one individual to another very quickly, infecting masses. The literature on epidemics indicates that the early diagnosis of a coronavirus infection can lead to a reduction in mortality rates. To prevent coronavirus disease 2019 (COVID-19) from spreading, the regular identification and monitoring of infected patients are needed. In this regard, wireless body area networks (WBANs) can be used in conjunction with machine learning and the Internet of Things (IoT) to identify and monitor the human body for health-related information, which in turn can aid in the early diagnosis of diseases. This paper proposes a novel coronavirus-body area network (CoV-BAN) model based on IoT technology as a real-time health monitoring system for the detection of the early stages of coronavirus infection using a number of wearable biosensors to examine the health status of the patient. The proposed CoV-BAN model is tested with five machine learning-based classification methods, including random forest, logistic regression, Naive Bayes, support vector machine and multi-layer perceptron classifiers, to optimize the accuracy of the diagnosis of COVID-19. For the long-term sustainability of the sensor devices, the development of energy-efficient WBAN is critical. To address this issue, a long-range (LoRa)-based IoT program is used to receive biosensor signals from the patient and transmit them to the cloud directly for monitoring. The experimental results indicate that the proposed model using the random forest classifier outperforms models using the other classifiers, with an average accuracy of 88.6%. In addition, power consumption is reduced when LoRa technology is used as a relay node.Objectives of this study were to analyze characteristics influencing blood donation status, to identify anxieties and reasons for (non-)blood donation, and potential channels for future blood donation campaigns. A random population from Germany was interviewed using the online survey tool SoSci Survey. The access link to the questionnaire was distributed via snowball system and the Bavarian Red Cross. Statistical analysis was performed to identify factors influencing blood donation status. A total of 682 participants (27.3% blood donors) with a mean age of 33.4 and a standard deviation (SD) of 12.0 years were included into the analysis. Strongest factor associated with being blood donor was having a blood donor within family and friends (Odds ratio [OR] 5.05 [95% confidence interval [95% CI] 2.63; 9.70]; p≤0.001), whereas having anxiety related to blood donation was the strongest factor for being non-blood donor (OR 0.11 [95% CI 0.05; 0.21] p≤0.001). Other factors significantly influencing blood donor status were age, health-related quality of life, knowledge on blood donation, being an organ donor and having pre-conditions. Main anxieties avoiding blood donation were fear of physical consequences, and fear of the injection needle. Most frequently mentioned channels which should be used for blood donation campaigns were Instagram and free TV. Involving blood donors into campaigns to recruit new blood donors from their personal environment and to focus campaign content on physical benefits of blood donations might help to recruit new blood donors. In addition, running campaigns stronger on channels such as Instagram might increase their scope.This study documents the setup and roll-out of a Computerized Maintenance Management System (CMMS) in Burundi's resource constrained health care system between 1/04/2017 and 31/03/2020. First, in 2017 a biomedical assets ontology was created, tailored to the local health system and progressively mapped on international GMDN (Global Medical Devices Nomenclature) and ICMD (International Classification and Nomenclature of Medical Devices) classifications. This ontology was the cornerstone of a web-based CMMS, deployed in the Kirundo and Muramvya provinces (6 health districts, 4 hospitals and 73 health centers). During the study period, the total number of biomedical maintenance interventions increased from 4 to 350 per month, average corrective maintenance delays were reduced from 106 to 26 days and the proportion of functional medical assets grew from 88 to 91%. This study proves that a sustainable implementation of a CMMS is feasible and highly useful in low resource settings, if (i) the implementation is done in a conducive technical environment with correct workshops and maintenance equipment, (ii) the active cooperation of the administrative authorities is ensured, (iii) sufficient training efforts are made, (iv) necessary hardware and internet connectivity is available and (v) adequate local technical support can be provided.The vegetative desiccation tolerance of Selaginella brachystachya has been evaluated for its ability to revive from a desiccation (air dry) state and start normal functioning when rehydrated. In this study, S. brachystachya was identified by DNA barcoding. Experiments were conducted using the detached hydrated, desiccated and rehydrated fronds under laboratory conditions to understand the mechanism of revival upon the water availability. Scanning Electron Microscope images during desiccation showed closed stomata and inside curled leaves. Chlorophyll concentration decreased by 1.1 fold in desiccated state and recovered completely upon rehydration. However, the total carotenoid content decreased 4.5 fold while the anthocyanin concentration increased 5.98 fold and the CO2 exchange rate became negative during desiccation. β-Aminopropionitrile Lipid peroxidation and superoxide radical production were enhanced during desiccation by 68.32 and 73.4%, respectively. Relative electrolyte leakage was found to be minimal during desiccation. Activities of antioxidant enzymes, namely peroxidase (158.33%), glutathione reductase (107.70%), catalase (92.95%) and superoxide dismutase (184.70%) were found to be higher in the desiccated state. The proline concentration increased by 1.4 fold, starch concentration decreased 3.9 fold and sucrose content increased 2.8 fold during desiccation. Upon rehydration, S. brachystachya recovered its original morphology, physiological and biochemical functions. Our results demonstrate that S. brachystachya minimizes desiccation stress through a range of morphological, physiological and biochemical mechanisms. These results provide useful insights into desiccation tolerance mechanisms for potential utilization in enhancing stress tolerance in crop plants.
The online version contains supplementary material available at 10.1007/s13205-021-02667-1.
The online version contains supplementary material available at 10.1007/s13205-021-02667-1.
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