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The COVID-19 pandemic, emerging/re-emerging infections as well as other non-communicable chronic diseases, highlight the necessity of smart microfluidic point-of-care diagnostic (POC) devices and systems in developing nations as risk factors for infections, severe disease manifestations and poor clinical outcomes are highly represented in these countries. These POC devices are also becoming vital as analytical procedures executable outside of conventional laboratory settings are seen as the future of healthcare delivery. Microfluidics have grown into a revolutionary system to miniaturize chemical and biological experimentation, including disease detection and diagnosis utilizing muPads/paper-based microfluidic devices, polymer-based microfluidic devices and 3-dimensional printed microfluidic devices. Through the development of droplet digital PCR, single-cell RNA sequencing, and next-generation sequencing, microfluidics in their analogous forms have been the leading contributor to the technical advancements in medicine. Microfluidics and machine-learning-based algorithms complement each other with the possibility of scientific exploration, induced by the framework's robustness, as preliminary studies have documented significant achievements in biomedicine, such as sorting, microencapsulation, and automated detection. Despite these milestones and potential applications, the complexity of microfluidic system design, fabrication, and operation has prevented widespread adoption. As previous studies focused on microfluidic devices that can handle molecular diagnostic procedures, researchers must integrate these components with other microsystem processes like data acquisition, data processing, power supply, fluid control, and sample pretreatment to overcome the barriers to smart microfluidic commercialization.Copyright © 2023 by Begell House, Inc.
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The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) causes Covid-19, an infectious illness. A methodology was created to track the vaccination history of people with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that causes Covid-19, an infectious illness. The system operates on a Raspberry Pi processor that is designed to authenticate the vaccination records of individuals. The Vaccination Identification System consists of various components connected to the Raspberry Pi Zero 2W microprocessor, Pi camera, an LCD display, LED indicators, a buzzer, a DC servo motor, and a PCB converter. The proposed system grants access to vaccinated individuals and denies access to those who are not vaccinated.
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During the current crisis caused by the COVID-19 pandemic, Wearable IoT (WIoT) health devices have become essential resources for remote monitoring of the main physiological signs affected by this disease. As well as sensors, microprocessor, and wireless communication elements are widely studied, the power supply unit has the same importance for the WIoT technology, since the autonomy of the system between recharges is of great importance. This letter presents the design of the power supply system of a WIoT device capable of monitoring oxygen saturation and body temperature, sending the collected data to an IoT platform. The supply system is based on a three-stage block consisting of a rechargeable battery, battery charge controller, and dc voltage converter. The power supply system is designed and implemented as a prototype in order to test performance and efficiency. The results show that the designed block provides a stable supply voltage avoiding energy losses, which makes it an efficient and rapidly developing system.
ABSTRACT
The increasingly interconnected, fast-moving, unmanageable and unpredictable world brings with it an unprecedented variety of known and as yet unknown challenges and risks. Some of the global risks have a direct impact on critical infrastructures as well as those of energy supply in particular. A high level of functionality of critical infrastructures (CRITIS), which include the sectors of energy, information technology and telecommunications, transportation and traffic, health, water, food, finance and insurance, government and administration, as well as media and culture, is indispensable for a modern industrial society. In the context of the Corona crisis of 2020/2021, the worldwide inadequate preparation for pandemics became obvious, although the probability of epidemic outbreaks and their global spread has increased significantly in recent decades and was thus predictable to a certain extent. Moreover, it has been shown that in a globally interconnected world, complex crisis phenomena can mutually amplify and thus escalate within a short period of time. In particular, the deficits in preparedness for major risks that became apparent in the course of the Corona pandemic cannot be managed by nation states alone, especially since the probability of such events has risen continuously in recent decades and will continue to increase with growing globalization and urbanization and, in particular, as a result of climate change and its consequences. This publication addresses the challenges of energy resilience and climate protection, which will require immense attention in the future. © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2022. All rights reserved.
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During Covid-19 restrictions, electronic information resources have become a prominent source in the library. Most of the university academic activities heavily depend on electronic resources because they are easy to share, refer and communicate to the audience. This study investigates the awareness and usage of electronic information resources subscribed to by the university library. The well-designed online questionnaire helps to collect data from Undergraduate, Postgraduate, and Integrated engineering programs. A total of 232 filled questionnaires were received for the study. The data analysis shows that 91.38 % of the respondents know that electronic resources are available in the library, and the internet speed (56.90 %) is a significant hindrance in using resources. The detailed analysis of this study was discussed, and suggestions were also given to improve the awareness and usage of electronic information resources.
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Advanced metering infrastructure (AMI) is becoming increasingly popular as an efficient means of energy demand management. By collecting energy data through AMI, it is possible to provide users with information that can induce them to change their behavior. To ensure that AMI continues to expand and to encourage the use of energy data, it is important to increase consumer participation and analyze their preferred service attributes. This study utilized a choice experiment to analyze consumer preferences for and acceptance of smart energy services based on AMI data. The results of a mixed logit model estimation show that consumers prefer the electricity information service for individual households and the social safety-net service among convergence services. A scenario analysis confirms that monetary compensation to offset any additional charges is important to maintain the level of consumer acceptance. These empirical findings offer insights for policymakers and companies seeking to develop policies and similar services.
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Blockchain based microgrid mechanisms can be designed efficiently to provide uninterrupted power supply and to balance load demands dynamically. In this present work, a conceptual design of a microgrid system is proposed in power system modeling. A blockchain based trading mechanism has been implemented on this system. Various optimization algorithms have been used to maximize economic profit. Finally, the Coronavirus Herd Immunity Optimizer (CHIO) algorithm is described to accommodate the impression that arises for the optimal power flow (OPF) and energy capacity. A case study has been provided to authenticate the performance of this method. The result expresses that the present scheme can largely improve the power dispatch and trading system. © 2022 IEEE.
ABSTRACT
Alternative energy alternatives to traditional energy sources like coal and fossil fuels include solar PV and wind energy conversion systems. The solar and wind energy conversion system's maximum power may be obtained by activating the converters. There are several MPPT (Maximum Power Point Tracking) regulating methods for solar and wind energy conversion systems. For solar PV energy conversion systems, this study suggests two MPPT controlling techniques: Covid-19 MPPT and FLC-based MPPT. The two MPPT methods that are suggested are put into practise using MATLAB. The first Covid-19 approach that has been developed combines aspects of hill climbing and progressive conductance methods. Calculate the direction of the perturbation for the PV modules' operation using the incremental conductance approach. The method of ascending hills is straightforward and involves fewer variables. When dI/dV equals the incremental conductance, the Maximum Power Point (MPP) is attained using the incremental conductance approach. In the hill climbing approach, the MPP is determined by comparing the power in the present and the past. Both incremental conductance and change of power are taken into account in the proposed Covid-19 MPPT regulating approach to obtain the MPP. With this hybrid approach, solar PV generates the most electricity possible under all conditions of temperature and irradiance. As a result, the planned Covid-19 technique moves forward as intended and swiftly reaches the MPP.Copyright © 2022, Anka Publishers. All rights reserved.
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Human activities have been limited by coronavirus disease 2019 (COVID-19), and the normal conditions of our lifestyles have changed, particularly in terms of electricity usage. The aim of this study was to investigate the impact of COVID-19 on the power sector in the Lao PDR in 2020, as well as the challenge of using solar energy to supply power to the network using an optimal approach. The returns on investment of network extension and the purchase of solar energy were also evaluated. Furthermore, load conditions caused by the country's lockdown policy were analyzed. We analyzed the optimal sizing and location of solar energy using a particle swarm optimization method based on the main objective functions, with the system's power loss decreasing and its reliability improved. The results demonstrated that the suddenly reduced load from industry and commercial business did not have a large impact on its operations;however, revenue was reduced. The optimal method for connecting solar energy to a network can reduce power loss and improve system reliability. In addition, we discovered that the location and capacity of solar generation can reduce the investment costs of extensions for new lines, with the surplus power being exported.
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This research aims to identify and analyse the challenges faced by the energy–power supply chain (LNG Power) in Pakistan a developing economy from combined perspectives of supply chain sustainability and resilience in the context of the Triple Bottom Line framework, UN SDGs 7, 13 and energy security. The significance of this research increases many folds as energy-power supply chains have been severely disrupted by events such as COVID-19, the Russia–Ukraine war and massive devastation caused by floods in Pakistan. Pakistan meets more than 60% of its energy-power needs from natural gas (including LNG), being less harmful than coal and oil power generation. The industry is in a state of deep crisis as it faces a complex set of challenges. Exploratory research design using a mixed method case study approach was used for the identification and shortlisting of challenges. Later these were ranked using group BWM. Major challenges were lack of strategy, top management commitment, weak compliance to UN SDGs, stalled structural reforms, disasters, lack of supply chain orientation, risk management culture, financial instability, LNG non-availability, demand uncertainty, infrastructure inadequacies and lack of awareness of Industry 4.0. The research enables policy-making besides providing energy practitioners a roadmap to overcome these challenges. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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The continuing COVID-19 pandemic around the world has raised concerns about public health security and posed a serious threat to the international shipping industry. Considering the fact that current epidemic may exist for a long time, it is necessary to set up independent epidemic prevention function zones on ships to deal with possible outbreaks. Due to the characteristics of high precision and low fault tolerance of medical devices and related equipment in epidemic prevention functional zones, they require more strict power supply quality and reliability, and may cause the deterioration of the power quality of the system. To solve this problem, the paper introduced a novel power management strategy for the shipboard medical system by power generation equipment switching process optimization, partitioning and grading of different types of loads to solve the power supply and distribution problems of the introduced ship epidemic prevention zone, and ensure a stable and reliable power supply of high-power medical equipment on the ship. © 2022 IEEE.
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COVID-19, corona virus disease, has been ravaging the world since the last quarter of 2019. To address this threat, the World Health Organization (WHO) has established a list of priority medical equipment that must be used by hospitals and clinics. These equipments are in fact non-linear harmonic-producing loads that have a detrimental effect on the devices and degrade the quality of the power supply. In this paper a parallel active filter: a neuronal harmonic compensation strategy based on plug-in electric vehicles (PEVs) connected to the charging stations in the parking lot of hospitals and clinics and artificial intelligence is proposed in order to improve the quality of power supply thus protecting medical equipment in order to save lives. This strategy will be simulated in MATLAB and the results will be presented as evidence of its effectiveness. © 2022 IEEE.
ABSTRACT
The Three Phase Power Supply Phase Selector device is critical for the operation of all medical equipment, particularly medical ventilators. Because of COVID 19, the need for ventilators has increased significantly. However, hospitals in rural areas are experiencing single-phase failure and low voltage in distribution lines, which causes interruptions in ventilator operation. This paper proposes an automatic Three Phase Power Supply Phase Chooser with a Programmable Logic Controller (PLC) to keep all medical ventilators running without disruption, especially in the occurrence of single-phase failure. During a phase failure, the proposed system automatically connects the ventilator to the another available phase in a very short period. The PLC detects the restoration of the phase of the single-phase supply and automatically reconnects the ventilator to the restored phase. It also aids in maintaining an uninterrupted power supply to critical single-phase medical appliances. It also protects sensitive single-phase medical equipment from damage and burnout. This system can be used in a variety of locations where critical single-phase medical equipment must operate continuously and without disruption. The key benefit of this controller is that it is reliable, easily programmable, and flexible. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
ABSTRACT
- Covid-19 is an infectious disease that attacks the respiratory system caused by the coronavirus found in 2019. It has a deadly infection and rapid spread worldwide without exception in Indonesia. Then since the year, World Health Organization (WHO) has declared it a world pandemic. One way to prevent the spread of Covid-19, especially in the closed public area, is by spraying disinfectant to kill the virus. In this project, a low-end disinfectant sprayer has been built based on an Arduino system. The sprayer has been applied to a 10.3mx7.8m classroom with 30 units of the misting device. Performance test of the system shows that the sprayer can work accurately at the timetable to spray the classroom by consuming 58.31 W in operation and 19.80W in standby mode. The total hardware implementation cost is IDR 904,225 or less than USD 65, making affordability for implementing the system.
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The electric grid is uniquely susceptible to extreme events through both power supply and consumption pathways. Extreme events - like heatwaves and droughts - are expected to increase in frequency and severity due to climate change and are already causing consequences on power system operations and stability. Additionally, non-climate related events like the COVID-19 pandemic have had dramatic impacts on energy consumption patterns globally. We apply modern machine learning methods to model electricity consumption in Brazil, one of the largest generators of hydropower, to better understand the consumption-side effects of extreme national and regional events. After training on 20 years of historical data, we verify an R2of 0.848 and a MAPE of 2.6% for our counterfactual model and use it to assess impacts of historical events on electricity consumption. We then discuss how this approach can be applied toward measuring energy system responsiveness and resiliency on present and future scenarios. © 2022 IEEE.
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As people spend more time at home during the COVID-19 pandemic, residential electricity consumption is increasing. To prevent global warming, the increased electricity consumption should be covered by renewable energy, e.g. photovoltaic (PV) power generation. However, PV systems are unstable power sources due to weather conditions;it is necessary to stabilize the residential PV power supply by using batteries. Now, electric vehicles (EV) are beginning to spread, especially in emerging countries. The EV batteries are useful for stabilizing the residential PV power supply. The idea of V2X, using EVs as batteries for buildings, is well-known but still a work in progress. Instead of V2X, we started an experiment based on another idea that we use the secondhand EV lithiumion batteries to stabilize the residential PV power supply. Since 2017, the experiment has been conducted in Yamaguchi in order to evaluate the self-sufficiency of a PV system with the stationary battery, which reused secondhand EV lithium-ion batteries as its components. Analysis of the experimental data revealed that the self-sufficiency of PV system was improved by up to 1.75 times with the stationary storage battery compared to the case without the stationary storage battery. © 2021 IEEE.
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Carbon neutrality is a necessary goal as a countermeasure against climate change. Therefore, it has become more important to promote further energy saving and the use of energy storage systems in railway systems. Notwithstanding, falls in passenger traffic due to COVID-19 have had a significant impact on railway management, and reducing infrastructure maintenance costs has become an urgent issue. This paper presents recent research and development on power supply systems, especially for decarbonizing the railways and reducing resources required for maintenance of overhead contact line systems. © 2022 Ken-yusha Inc.. All rights reserved.
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The Energy Sector is highly targeted by cyber threats because of its inherent value and profitability. Recent reported security incidents verify its key playing role in the entire economic and societal concurrent reality. This paper aims to assess the cyber-security culture status of European representatives in the entire electrical power supply chain during the coronavirus pandemic and the Ukrainian war. An evaluation campaign has been carefully designed and held from 3rd March 2022 to 18th March 2022. During that period, participants from different Electrical Power and Energy Systems (EPES) organizations participated in the campaign. Gathered results were analyzed and co-examined using different techniques revealing important findings regarding the cyber-security status and resilience of individuals and organizations in the European EPES sector. © 2022 ACM.
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Purpose>The disinfection robot developed by the authors and team focuses on achieving fast and precise disinfection under a given or specific disinfection zone. This looks to solve problems with traditional robots that pay less attention to the level, efficiency and zones of disinfection. To effectively support and guarantee normal running for the whole system, a digital twin system is applied to the disinfection robot. This study aims to achieve fast, precise and thorough disinfection via the developed mobile robot.Design/methodology/approach>The designed robot is composed primarily of the following three parts: a mobile platform, a six-axis robotic arm and a ultraviolet-C (UVC) LED array. The UVC LED array is installed on the end-effector to achieve large-scale, precise manipulation. The adoption of all types of advanced sensors and the development of an intuitive and user-friendly client interface are helpful in achieving remote control, path planning, data monitoring and custom disinfection functions.Findings>Disinfection of three different locations in the laboratory was performed;the dosage distribution of the surface as radiated by the UVC robot was detected;and feasibility of development was validated.Originality/value>The developed disinfection robot achieved fast, precise and thorough disinfection for a given or specific disinfection zone.
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In the prevailing era, the most relevant issues seem to be the development of an adaptive policy of an energy sales company to ensure financial stability and sustainable development in the course of energy sales activities. This study continues the cycle of the author's general research devoted to the methodological issues of an adaptive policy development in relation to the key business processes of energy sales activities implemented by an energy sales company, the specifics of its work as a guaranteed energy (capacity) supplier, etc. The article examines the conditions and factors that determine the need to develop an adaptive system for an energy sales company to organize payment acceptance. When it comes to the business process organization for payment acceptance, energy retail companies need to take into account the conditions and factors that set the long-term trend in this area: changes in legislation, the strength of market competition and the trends of the payment acceptance market infrastructure, the ongoing coronavirus infection pandemic, and the ongoing technological change. Management decision-making should be based on the principles of economic feasibility and efficiency in conjunction with legal requirement compliance. Power supply companies need to use the conditions and factors highlighted in the study to build up competitive advantages in the field of payment acceptance organization, to maintain and develop their market position, which can only be done through an adaptation policy in this area. For the purpose of economic efficiency increase concerning organization payment acceptance business process, energy sales companies need to plan the indicators of the payment acceptance system, implement measures for their implementation (achieve target values), carry out the analysis of the achieved results and their reflection, which will ensure timely and reasonable acceptance of management decisions.