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The results of a study on the possible connection between the spread of the SARS-CoV-2 virus and the Earth's magnetic field based on the analysis of a large array digital data for 95 countries of the world are presented. The dependence of the spatial SARS-CoV-2 virus spread on the magnitude of the BIGRF Earth's main magnetic field modular induction values was established. The maximum diseases number occurs in countries that are located in regions with reduced (25. 0-30. 0 μT) and increased (48. 0-55. 0 μT) values, with a higher correlation for the first case. The spatial dependence of the SARS-CoV-2 virus spreading on geomagnetic field dynamics over the past 70 years was revealed. The maximum diseases number refers to the areas with maximum changes in it, both in decrease direction (up to - 6500 nT) and increase (up to 2500 nT), with a more significant correlation for countries located in regions with increased geomagnetic field. © 2022 EAGE. All Rights Reserved.
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The COVID-19 pandemic forced the educational institutions in the Philippines to go full online, full modular or blended during its height in 2020. This study surveyed students' perception of online classes after having experienced the modality for one school year. An online questionnaire was developed and validated to collect data relevant for this research. The Cronbach's alpha value obtained is 0.85 suggesting an acceptable internal reliability. The survey went through evaluation by experts and was found to be valid and reliable. The quantitative and qualitative data gathered show that the students perceive online or virtual classes as innovative. It increases their autonomy and self-determination. It opens access to variety of platforms, online resources, and materials. However, there is a need to improve conduct of online classes to make learning easy and enjoyable, make it more engaging and motivating. Findings in this study reveal that the general perception of students on the conduct of online classes is neither positive nor negative. However, most of the negative feedback come from unreliable internet connectivity, physiological issues, financial demands, delayed feedback and issues with authenticity of examination scores that come along with online instruction. The results of this study can be used as a basis for development of interventions that could help address the issues that come along with online learning. Further research is recommended to fill the gaps created by the virtual teaching and learning arrangements to assist educators and institution administrators in drafting policies and strategies in managing the challenges of online modality. © 2023 ACM.
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Prevention of infectious diseases as the Covid-19 is of essential importance for the well-being of humanity. This is especially so at hospitals, where many vulnerable individuals frequent. Hand disinfection is one of the methods for preventing communicable diseases. In this paper we introduce a new modular mobile service robot designed for hand disinfection in hospitals and other public spaces. It consists of two separable parts: the driving base and the disinfection stand. The base was made in a horseshoe shape which allows it to lift its payload (the stand) near its center of gravity and distribute the weight evenly on its four wheels. The stand is able to function both in conjunction with the base and also autonomously. The whole robot was designed with social interaction in mind to achieve better hand sanitization compliance, which is of essential importance in hospitals for preventing infectious diseases. We conducted a test of how well the robot is able to find and approach people in its vicinity who face different directions. Even though the robot does not achieve its goal position ideally, it always ends up facing the user, which is even more important for starting an interaction than reaching its goal position very precisely. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The physics output of modern experimental HEP collaborations hinges not only on the quality of its software but also on the ability of the collaborators to make the best possible use of it. With the COVID-19 pandemic making in-person training impossible, the training paradigm at Belle II was shifted from periodic workshops towards guided self-study. To that end, the study material was rebuilt from scratch as a series of modular and hands-on lessons tightly integrated with the software documentation using Sphinx. Each lesson contains multiple exercises that are supplemented with hints and complete solutions. Rather than duplicating information, students are systematically taught to work with the technical reference documentation to find the important sections for themselves. Unit tests ensure that all examples work with different software versions, and feedback buttons make it easy to submit comments for improvements. © Published under licence by IOP Publishing Ltd.
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The global novel coronavirus pneumonia has brought great impact on people's daily life, and has also strengthened the importance of health care and public health in various countries. This design is a whole body disinfection device designed for public space and semi public space. It uses ergonomics, modular design and other concepts to develop an epidemic prevention and control product that is easy to assemble, move and keep, intuitive to use and fast to run. Such epidemic prevention and control products are relatively rare in the market. This design aims to help China and even the world improve the public health and safety of public space and semi public space with large population flow and density in the post epidemic era, and to quickly assemble, emergency and carry out epidemic prevention and control in case of large-scale respiratory tract infectious diseases in the future, To avoid the spread of the virus in the dense population, to achieve early detection, early prevention. © 2022 IEEE.
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Providing quality learning in science during the onset of the COVID-19 pandemic became one of the quandaries of most secondary schools in the Philippines, especially in remote areas. Likewise, high school teachers at Occidental Mindoro State College (OMSC) despite the prominence of technological learning platforms, have still resorted to the use of printed modules as primary learning modality due to the emergence of digital gap among the learners. Thus, the possibility of addressing the gap through the utilization of m-learning approach in teaching science on a distance-learning set-up was explored. Using a developed mobile-learning modular app (MoLMA) by the researcher, the approach was utilized in one of the Grade-7 Science classes of the institution. Following a descriptive-comparative mixed-method research design, the perceived usefulness of m-learning approach was gathered based on the pre-and post-perception responses of the teacher-users before and after the intervention. A focus group discussion was conducted therein after to gather an in-depth response. Results revealed high positive feedback in the utilization of m-learning before and after the intervention. Though both yielded positive responses, t-test results showed a difference between the areas of instructional delivery, enhancement of learning, and flexibility and convenience. Apart from promoting ubiquitous and personalized learning experience, results of FGD showed its cost- and time-efficiency in teaching biology subjects compared to the modular. Technologically speaking, results showed that m-learning is one of the most adaptive and accessible ways of utilizing technology-enabled learning in science at the onset of pandemic. It is recommended that the effectiveness of the approach in increasing students' academic performance shall be also tested. © ICCE 2022.All rights reserved.
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In the United States, public transit vehicles have a very low average load factor (10.1-12.4%), resulting in an excessive waste of seat capacity and poor fuel economy per passenger mile served. This problem is gravely exacerbated by the COVID-19 pandemic, which at its peak had caused more than 70% reduction in transit ridership nationwide. On the other hand, the rapid uptake of e-commerce, also accelerated by the pandemic, has put tremendous pressure on last-mile delivery. A co-modality system that integrates transit services with last-mile logistics offers a promising solution to better utilization/sharing of vehicle capacity and supporting infrastructure. Here we show such a system may be implemented based on Autonomous Modular Vehicle Technology (AMVT). At the core of AMVT is the ability to operate a fleet of modular autonomous vehicles or pods that can be moved, stationed, joined, and separated in real time. Coupling modularity with autonomy is poised to enable co-modality and beyond. We describe an AMVT bimodality system that provides integrated public transit and last-mile logistics services with a fleet of pods and discuss relevant research challenges and opportunities, research approaches, and real-world adoption issues. © 2009-2012 IEEE.
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Chatbots are a powerful tool to design and implement sophisticated computer systems able to interact with human users through natural language. Chatbots are considered more friendly to users than other sources of information, and consequently, they have been largely applied to various domains. In this work, we propose a chatbot application aimed at answering questions about COVID-19 vaccines. Besides the interesting application domain and the knowledge engineering behind this development, we also introduce a modular chatbot architecture based on an easy-to-update database and natural language templates in which new information (for example, new vaccines) can be added without the need for retraining the chatbot. Furthermore, in this paper, we provide an empirical evaluation of the proposed chatbot application. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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During the COVID-19 pandemic, a rise of (agent-based) simulation models for predicting future developments and assessing intervention scenarios has been observed. At the same time, dashboarding has become a popular way to aggregate and visualise large quantities of data. The AScore Pandemic Management Cockpit brings together multiagent-based simulation (MABS) and analysis functionalities for crisis managers. It combines the presentation of data and forecasting on the effects of containment measures in a modular, reusable architecture that streamlines the process of use for these non-researcher users. In this paper, the most successful features and concepts for the simplification of simulation usage are presented: definition of scenarios, limitation of parameters, and integrated result visualisation, all bundled in a web-based service to offer a low-barrier entry to the usage of MABS in decision-making processes. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The demand for scalable, rapid and sensitive COVID-19 diagnostics is particularly pressing at present to help contain the spread of infection and prevent overwhelming the capacity of health systems. While high-income countries have managed to rapidly expand diagnostic capacities, such is not the case in resource-limited settings of low- to medium-income countries. We report the development of an integrated modular centrifugal microfluidic platform costing less than 250 USD to perform loop-mediated isothermal amplification (LAMP) of viral RNA directly from heat-inactivated nasopharyngeal swab samples. The platform was validated with a panel of 131 nasopharyngeal swab samples collected from symptomatic COVID-19 patients. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.
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Analysis of data sets that may be changing often or in real-time, consists of at least three important synchronized components: i) figuring out what to infer (objectives), ii) analysis or computation of those objectives, and iii) understanding of the results which may require drill-down and/or visualization. There is considerable research on the first two of the above components whereas understanding actionable inferences through visualization has not been addressed properly. Visualization is an important step towards both understanding (especially by non-experts) and inferring the actions that need to be taken. As an example, for Covid-19, knowing regions (say, at the county or state level) that have seen a spike or are prone to a spike in the near future may warrant additional actions with respect to gatherings, business opening hours, etc. This paper focuses on a modular and extensible architecture for visualization of base as well as analyzed data. This paper proposes a modular architecture of a dashboard for user interaction, visualization management, and support for complex analysis of base data. The contributions of this paper are: i) extensibility of the architecture providing flexibility to add additional analysis, visualizations, and user interactions without changing the workflow, ii) decoupling of the functional modules to ease and speed up development by different groups, and iii) supporting concurrent users and addressing efficiency issues for display response time. This paper uses Multilayer Networks (or MLNs) for analysis. To showcase the above, we present the architecture of a visualization dashboard, termed CoWiz++ (for Covid Wizard), and elaborate on how web-based user interaction and display components are interfaced seamlessly with the back-end modules. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Acute Respiratory Distress Syndrome (ARDS), also known as noncardiogenic pulmonary edema, is a severe condition that affects around one in ten-thousand people every year with life-threatening consequences. Its pathophysiology is characterized by bronchoalveolar injury and alveolar collapse (i.e., atelectasis), whereby its patient diagnosis is based on the so-called 'Berlin Definition'. One common practice in Intensive Care Units (ICUs) is to use lung recruitment manoeuvres (RMs) in ARDS to open up unstable, collapsed alveoli using a temporary increase in transpulmonary pressure. Many RMs have been proposed, but there is also confusion regarding the optimal way to achieve and maintain alveolar recruitment in ARDS. Therefore, the best solution to prevent lung damages by ARDS is to identify the onset of ARDS which is still a matter of research. Determining ARDS disease onset, progression, diagnosis, and treatment required algorithmic support which in turn raises the demand for cutting-edge computing power. This paper thus describes several different data science approaches to better understand ARDS, such as using time series analysis and image recognition with deep learning methods and mechanistic modelling using a lung simulator. In addition, we outline how High-Performance Computing (HPC) helps in both cases. That also includes porting the mechanistic models from serial MatLab approaches and its modular supercomputer designs. Finally, without losing sight of discussing the datasets, their features, and their relevance, we also include broader selected lessons learned in the context of ARDS out of our Smart Medical Information Technology for Healthcare (SMITH) research project. The SMITH consortium brings together technologists and medical doctors of nine hospitals, whereby the ARDS research is performed by our Algorithmic Surveillance of ICU (ASIC) patients team. The paper thus also describes how it is essential that HPC experts team up with medical doctors that usually lack the technical and data science experience and contribute to the fact that a wealth of data exists, but ARDS analysis is still slowly progressing. We complement the ARDS findings with selected insights from our Covid-19 research under the umbrella of the European Open Science Cloud (EOSC) fast track grant, a very similar application field. © 2022 Croatian Society MIPRO.
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Today, Off-site Manufacturing (OSM) is considered to have the potential to be the main driver for improving productivity in the construction industry. In addition to reducing the dependence of operations on adverse weather conditions, OSM offers a solution to the shortage of skilled labour. This approach to construction is being reinvented through the use of new technologies, such as Building Information Modeling (BIM), Virtual Reality (VR) and Mobile Communication Technologies (MCT). For these reasons, it is beneficial for the construction industry to evaluate its practices and consider an effective adoption of OSM. In this context, the main objective of our research project is to study the effect of the OSM approach on the project realization mode. Moreover, to evaluate the effects of early stakeholder involvement and the impact of using collaborative platforms for sharing information and digital models on the successful adoption of OSM. Also, we would like to identify the challenges and find the main barriers faced by mechanical, electrical and plumbing (MEP) contractors. The project is based on a case study that consists of building a 36-room hospital annex using the modular construction approach in the context of a COVID19 health emergency. The research reveals that the adoption of OSM with the use of BIM in a well managed mode would offer the construction industry a new collaborative paradigm that encourages the sharing of information and profits while ensuring an optimal outcome of the delivered product. © 2023, Canadian Society for Civil Engineering.
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Purpose: This study aims to focus on the sustainability of prefabricated medical emergency buildings (PMEBs) renovation after the epidemic, to address the problem that large numbers of PMEBs may be abandoned for losing their original architectural functions. This study develops an evaluation system to identify and measure sustainable factors for PMEBs’ renovation schemes. Qualitative and quantitative analysis of PMEBs’ renovation scheme was conducted based on cloud model evaluation method and selected the renovation scheme in line with sustainable development. The study promotes evaluation methods and decision-making basis for the renovation design of global PMEBs and realizes the use-value of building functions again. Design/methodology/approach: By referring to the existing literature, design standards and expert visiting a set of evaluation index systems which combines the renovation of the PMEBs and the sustainability concept has been established, which calculates the balanced optimal comprehensive weight of each indicator utilizing combination weighting method, and quantifies the qualitative language of different PMEBs’ renovation schemes by experts through characteristics of the cloud model. This paper takes Huoshenshan hospital a representative PMEB during the epidemic period as an example, to verify the feasibility of the cloud model evaluation method. Findings: The research results of this paper are that in the PMEBs’ renovation scheme structural reformative (T11) and corresponding nature with the original building (T13) have the most important influence;the continuity of architectural cultural value (T22) and regional development coherence (T23) are the key factors affecting the social dimension;the profitability of renovated buildings (T34) is the key factor affecting the economic dimension;the environmental impact (T41), resource utilization (T42) and ecological technology (T43) are the key factors in the environmental dimension. Originality/value: This study contributes to the existing body of knowledge by supplementing a set of scientific evaluation methods to make up for the sustainability measurement of PMEBs’ renovation scheme. The main objective was to make renovated PMEBs meet the needs of urban sustainable development, retain the original cultural value of the buildings, meanwhile enhance their social and economic value and realize the renovation with the least impact on the environment. © 2022, Emerald Publishing Limited.
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With the new normal of our daily lives caused by the novel COVID 19, it has become a requirement to sanitize our hands and go through manual temperature screening via a handheld infrared thermometer. Moreover, our contact info must be provided either using a smartphone app or logbook. This process is time consuming and causes long queues. Therefore, to expedite this process, a device named Modular and Open System (MOST) was designed and developed. The MOST chassis is built using an aluminum bar. This chassis is attached with a spring-operated mechanism used to dispense a liquid sanitizer from a bottle manually using the foot. The chassis is also installed with a controller, camera, MLX90614 temperature sensor, touchscreen, barcode scanner, and tower light. These components are used to perform contactless temperature measurement, capture a person’s information, display the temperature, and alert the user about their health condition. The information can be of any data such as name, phone number, identification number and others as long it is in a barcode format. Meanwhile, to improve the accuracy for temperature measurement, a distance compensation algorithm based on a quadratic least square method is applied in the MOST system. It is tested, MOST is able to expedite this process and the accuracy of temperature measurement to a user is 99%. A person only needs to stand in front of it, flash the barcode either using a card or smartphone and thus the health status can be displayed. Moreover, the data including date, time, measured temperature, and person’s information are recorded. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The use of ventilators has always been common in medical scenarios but very expensive to procure or develop. One of the main reasons for these is the components that are being used are expensive and require precise instrumentation, research and development. This paper attempts to mitigate that problem by proposing a novel way to rapidly develop a portable ventilator that uses common 3D printing technology and off-the-shelf components. This turbine and valve-based ventilator feature most of the modes that are commonly used by healthcare professionals. A unique servo-based pressure release mechanism has been designed that makes the system around 36 times more efficient than solenoid-based systems. Reliability and efficiency have been increased further through the use of a novel positive end-expiratory pressure (PEEP) valve that does not contain any electromechanical component. Effective algorithms such as feed-forward and proportional-integral-derivative (PID) controllers were used alongside the unique ĝ€Sensor data filtration methodology'. The system also provides an interactive graphical user interface (GUI) via an android application that can be installed on any readily found tabs while the firmware manages the breathing detection algorithm using a flow meter. This modular and portable ventilator also features a swappable battery and holds the ability to run on solar power. This energy-efficient and low noise system can run for 5 to 6 hours at a stretch without needing to be connected with the main's supply. This ventilator's design and development files have been certified by open-source hardware association (OSHWA): https://certification.oshwa.org/bd000001.html © 2021 ACM.
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At present, the world is undergoing a pandemic spawning from the advent of a new coronavirus outbreak known as COVID-19. As a result, hospital staff, paramedics, first responders, and the general world population have been forced to wear personal protective equipment (PPE) and take special measures to prevent catching the virus. Furthermore, because of this necessity, increasing demand on the PPE supply chain has generated many shortages, especially seen in masks designed to stop the inhalation of COVID-19 particles in the air. This inspired our group to design something that could help make PPE more accessible and affordable for the average person. The proposed is an almost entirely 3D printed design to help keep costs down and make it simplistic, such that anyone with a 3D printer has the potential to duplicate it. We hope that with the design, we can help combat the shortage and keep more people safe from COVID-19. Copyright © 2021 by ASME.
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This study introduces an inclusive and innovative online teaching pedagogy in sound design and modular synthesis using open-source software to achieve ideal student-centered learning outcomes and experience during the COVID-19 pandemic. This pedagogy proved to be effective after offering the course, conducting human subject research, and analyzing class evaluation data. The teaching strategies include comprehensive analysis in sound synthesis theory using sample patches, introduction to primary electronics, collaborative learning, hands-on lab experiments, student presentations, and alternative reading assignments in the form of educational videos. Online teaching software solutions were implemented to track student engagement. From a transformative perspective, the authors aim to cultivate student-centered learning, inclusive education, and equal opportunity in higher education in an online classroom setting. The goal is to achieve the same level of engagement as in-person classes, inspire a diverse student body, offer ample technical and mental support, as well as open the possibility of learning sound design through Eurorack modular synthesizers without investing money in expensive hardware. Students’ assignments, midterms, and final projects demonstrated their thorough understanding of the course material, strong motivation, and vibrant creativity. Human subject research was conducted during the course to improve the students’ learning experience and further shape the pedagogy. Three surveys and one-on-one interviews were given to a class of 25 students. The qualitative and quantitative data indicates the satisfaction and effectiveness of this student-centered learning pedagogy. Promoting social interaction and student well-being while teaching challenging topics during challenging times was also achieved. © 151st Audio Engineering Society Convention 2021.
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Pandemics all over the world have come to modify daily life of all citizens, the new coronavirus outbreak spread through different countries, who like Mexico had to choose to change education methodology in order to not affect learning process on students. It is due to Mexico education current situation, which not being prepared for an extreme provision such as quarantine measures, had to find options to ensure learning and establish an academic continuity plan in one of the most prestigious education institutions in the country, such as Instituto Politecnico Nacional (IPN). This paper presents the results of creation and use of a modular educational ecosystem at Instituto Politecnico Nacional (IPN) as a support to education problems in the country due to COVID-19 pandemic. The results obtained show the great participation of students and teachers in the ecosystem, basing their activities on the use of digital technologies. The statistics presented in this document show that the academic continuity plan implemented in this institution can be replicated to improve the learning models currently used in educational institutions in the country. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.