ABSTRACT
NASA's Double Asteroid Redirection Test (DART) successfully intercepted the asteroid Didymos on September 26th of 2022, potentially changing its orbital period with a deflection by kinetic impact. The spacecraft launched aboard a SpaceX Falcon 9 rocket on November 24th, 2021. DART's Integration and Test (I&T) campaign was scheduled to commence in April of 2020 at the Johns Hopkins University Applied Physics Laboratory (JHU/APL) in Laurel, Maryland. In March of that year, one month prior to beginning I&T, the rapid spread of the Coronavirus (COVID-19) forced JHU/APL to rethink how to assemble, test and deliver a spacecraft on schedule during a very challenging period of time. This paper will discuss the details of the successful I&T strategy used by the DART team during the COVID-19 lockdown and subsequent return to post-lockdown life. The team learned how to effectively meet virtually, how to integrate hardware, and how to operate the spacecraft with the least amount of people required. Communication was key in keeping the various DART team members, who were located across the country, connected and safe. The team had also moved documentation online for the first time, which turned out to be very instrumental in keeping everyone on track. A variety of tools to collaborate and document test procedures and results proved valuable for record keeping. Creative solutions were implemented during the test campaign for scheduling both remote and in person monitoring. This paper will conclude with DART lessons learned and recommendations for future I&T programs. © 2023 IEEE.
ABSTRACT
The necessity to teach experimental physics in the pandemic period motivated the development of practices in which students may take measurements with instruments constructed by themselves. In this article, we present an experimental practice to approach Newton's law of cooling with a thermoscope (the earliest device for detecting changes in temperature, forerunner of the thermometer) constructed with household materials. Although the use of a non-calibrated thermoscope, the instrument presented several advantages, visual appeal, ease of handling, ease of data acquisition and good reproducibility. The students can take data, plot graphs, and verify if the Newton's law of cooling holds on the tested circumstances.
ABSTRACT
A variety of patient care and intelligent health systems can benefit from the implementation of artificial intelligence as a tool to aid caregivers. Machine learning and deep learning are two types of AI that are increasingly being used in the medical industry. Artificial intelligence methods require a large amount of clinical data from a range of imaging modalities for correct disease diagnosis. In addition, AI has greatly enhanced the quality of hospital stays, allowing patients to be released sooner and complete their recoveries at home. This article aims to provide the information on the field of AI subset i.e., machine learning-based disease detection with information that will aid them in making better decision making. This helps the researchers to classify the medical conditions in patients with a prominent dataset.
ABSTRACT
This Special Issue is associated with the European Conference on Integrated Optics (ECIO), held on May 4–6, 2022, in Milan, Italy. This conference was the 23rd in a series that started in London in 1981. After the virtual edition of 2020 and the cancellation of the 2021 edition due to the COVID-19 pandemic emergency, the 2022 ECIO conference was hosted fully in presence by Politecnico di Milano and was attended by about 250 participants. The scientific sessions of the conference were opened by two plenary speakers, Prof. Volker Sorger of George Washington University, USA, and Prof. Paul Prucnal of Princeton University, USA, who presented recent developments on integrated photonics for machine learning, high-performance computing, and neural networks.
ABSTRACT
This preliminary study aimed to identify attributes for observed and latent variables. A documentary review was employed to investigate the attributes for latent variables, namely technological integration, disruptive leadership, and organizational transformation while the observed variable was human resource management during the disruption era. The findings revealed that there are six attributes for human resource management during the disruption era, four attributes for technological integration, five attributes for disruptive leadership, and four attributes for organizational transformation. All these variables and their attributes are going to investigate using structural equation modeling in order to explore relations between observed and latent variables.
ABSTRACT
With rapid proliferation of digitalization and compulsion by COVID-19 pandemic, learning formats have been changing from face-To-face to online. Online education enables learners to take courses from anywhere, anytime, but it can also cause some problems for learners who struggle to maintain motivation. In addition, for STEAM education, it is important to engage in hands-on activities, but the ongoing pandemic has made it difficult for students to gather in one place to perform such activities. Incorporating gamification into online education can potentially motivate students and make STEAM education more interactive. On this premise, we have developed PhyGame as a learning system to help high-school students learn Physics. The system includes common game elements such as badges and leaderboards, and interactive simulation of Physics concepts embodying game-like charm. It also includes three modes of learning that allow students to adjust the difficulty according to their own learning levels, and a function that automatically saves learning log. For evaluation, PhyGame was used by students (N=23) at a high school in central Tokyo. The students rated the system on a scale of 1 to 10, and the main results are as follows: (1) Using PhyGame made learning enjoyable (mean score: 7.74);(2) PhyGame provided a good UI/UX (mean score: 7.83);(3) The overall experience with PhyGame was satisfactory (mean: 7.00). Our evaluation results show that interactive and gamified learning systems like PhyGame have a positive impact on user engagement and motivation. © 2023 IEEE.
ABSTRACT
Humans can be said to be social creatures who always cannot be separated from communicating with other humans. This study aims to determine the influence that can attract tourists to continue to visit and feel satisfied with the facilities provided. This research method is quantitative research, the type of data needed in this research is primary data and secondary data, the source of the data used in this study is by distributing questionnaires (questionnaires), the data collection technique used in this study is through the Likert scale. The results of the study show that this Jaddih Hill tour has utilized good electronic media, so that tourists are interested in visiting again besides tourists who visit have a sense of security and calm.
ABSTRACT
The rapid response to the COVID-19 pandemic has resulted in increased municipal waste in the form of used face masks (FMs), which pose a global threat to the environment. To mitigate this, the study explores the applicability of shredded FMs as alternative reinforcing material in sands. Laboratory-grade Ottawa sand and naturally collected sea sand are adopted as the base sands for testing. The primary physical properties of the base materials and the FMs are first examined, and the soil particles are imaged via scanning electron microscopy. Thirty consolidated undrained (CU) triaxial compression tests were conducted to evaluate the effects of the weight fraction of FM, FM length, and the initial effective mean stress on the undrained shear strength parameters of the sands. The experimental results proved that FM inclusion can lead to a substantial improvement in the undrained shear strength of the sands;however, such improvement was sensitive to the initial effective mean stress, with higher undrained shear strength gains associated with lower initial effective mean stress. For a given FM content, the critical state ratio and angle of friction at the critical state increased with the FM length. Finally, the results revealed that FM-reinforced sands exhibit dilative and strain-hardening behaviors.
ABSTRACT
A common way to model an epidemic — restricted to contagion aspects only — is a modification of the Kermack-McKendrick SIR Epidemic model (SIR model) with differential equations. (Mis-)Information about epidemics may influence the behavior of the people and thus the course of epidemics as well. We have thus coupled an extended SIR model of the COVID-19 pandemic with a compartment model of the (mis-)information-based attitude of the population towards epidemic countermeasures. The resulting combined model is checked concerning basic plausibility properties like positivity and boundedness. It is calibrated using COVID-19 data from RKI and attitude data provided by the COVID-19 Snapshot Monitoring (COSMO) study. The values of parameters without corresponding observation data have been determined using an L2-fit under mild additional assumptions. The predictions of the calibrated model are essentially in accordance with observations. An uncertainty analysis of the model shows, that our results are in principle stable under measurement errors. We also assessed the scale, at which specific parameters can influence the evolution of epidemics. Another result of the paper is that in a multi-domain epidemic model, the notion of controlled reproduction number has to be redefined when being used as an indicator of the future evolution of epidemics.
ABSTRACT
This paper presents the procedure followed to conduct two various experiments as part of the ‘Mechanical Laboratory' course of the Mechanical Engineering department, at Aristotle University of Thessaloniki, during the Covid-19 period. Adapting to the personal contact restrictions imposed by the health issue outbreak, a remote experimental method is proposed. In the first experiment, the students had to generate the operational map of a cooling computer fan while on the second one the characteristic parameters of a symmetric airfoil needed to be measured. Multifunctional control panel interfaces were introduced to the students. Through these applications, the student had the opportunity to run the experiments, assess the raw data, monitor all the necessary flow parameters and acquire the important variables. The students had to post-process the results and submit two reports, one for each experiment. This teaching method provided the students with the experience of real research project and guided them to use modern tools to enhance the quality of their future work. This publication focuses on the address of the challenges, arose during the automation of the experiments. The remote experimental sessions indicated some advantages in learning procedure which was also reflected on the assignment grades. The development of the procedure has been successfully implemented and tested over a couple of years while the quarantine measure have been in place. Furthermore, the experience gained will be used to implement modern communication protocols in the experimental set-ups.
ABSTRACT
Severe acute respiratory syndrome coronavirus is a type 2 highly contagious, and transmissible among humans;the natural human immune response to severe acute respiratory syndrome-coronavirus-2 combines cell-mediated immunity (lymphocyte) and antibody production. In the present study, we analyzed the dynamic effects of adaptive immune system cell activation in the human host. The methodology consisted of modeling using a system of ordinary differential equations;for this model, the equilibrium free of viral infection was obtained, and its local stability was determined. Analysis of the model revealed that lymphocyte activation leads to total pathogen elimination by specific recognition of viral antigens;the model dynamics are driven by the interaction between respiratory epithelial cells, viral infection, and activation of helper T, cytotoxic T, and B lymphocytes. Numerical simulations showed that the model solutions match the dynamics involved in the role of lymphocytes in preventing new infections and stopping the viral spread;these results reinforce the understanding of the cellular immune mechanisms and processes of the organism against severe acute respiratory syndrome-coronavirus-2 infection, allowing the understanding of biophysical processes that occur in living systems, dealing with the exchange of information at the cellular level.
ABSTRACT
This exploratory study evaluated the risk of contagion from airborne diseases, such as coronaviruses, in schools. For three days, the concentration of carbon dioxide in two university classrooms was monitored for 90 minutes, while the students took their math classes. We use these values to validate a first-order model for carbon dioxide concentration and calculate the air exchange rate indirectly (avoiding the need for expensive measurement equipment). The air exchange rate obtained allowed us to assess whether the usual ventilation systems (both natural and mechanical) are sufficient to guarantee a low risk of contagion of aerosols due to respiration. The results show that the risk of contagion is low if three factors are considered: the level of conversation within the classroom, the usage of a moisture extraction system, and the lecture duration. The risk is low if the lecture time is less than 50 minutes, the level of conversation is moderate, and a moisture extraction system is available. If these conditions are not met the risk is considerably higher even if mechanical ventilation is employed.
ABSTRACT
The tenth international symposium on "Large TPCs for low-energy rare event detection” was held in Paris from 15th to 17th of December 2021 at the Institute of Astroparticle physics of the University of Paris. The 2020 issue of this conference series was cancelled due to the Covid pandemic. The symposium was organized in a hybrid mode, which allowed about 40 people to attend in-person among a total of 131 registered participants. Very strict sanitary measures were taken to keep the meeting safe.As in previous events the program included neutrino physics, dark matter and axion searches, related detector R&D and theoretical aspects.To celebrate the tenth edition of the symposium the conference was held on three full days. Special speakers were invited to give a historical overview related to our field. David Nygren shared his memories of the invention and development of the Time Projection Chamber. François Vannucci revealed to us the invisible world of neutrinos. Ioannis Giomataris pointed out various innovative ideas that emerged during presentations and discussions in the last two decades. Jean Iliopoulos retraced the concept and development of the Standard Model and shared his personal vision on the future of particle physics.We wish to thank the many people who contributed to the success of the conference and especially the conveners of the sessions, who allowed for a smooth running of the meeting. We particularly acknowledge the APC management for providing the nice Buffon auditorium and infrastructure. We also thank DSM-Irfu, the University of Zaragoza, the European Research Council and ACAV Ile de France for their valuable support.The organizersList of Organizing Committee is available in this Pdf.
ABSTRACT
ABOUT ICMSOA2022Organized by Yaseen Academy, 2022 The 2nd International Conference on Modeling, Simulation, Optimization and Algorithm (ICMSOA 2022), which was planned to be held during 11-13 November, 2022 at Sanya, Hainan Province, China. Due to the travel restrictions caused by covid, the participants joined the conference online via Tencent Meeting at 12 November, 2022. The Conference looks for significant contributions to related fields of Modeling, Simulation, Optimization and Algorithm. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.CALL FOR PAPERSPlease make sure your submission is in related areas of the following general topics. The topics include, but are not limited to:Simulation modeling theory and technology, Computational modeling and simulation, System modeling and simulation, Device/VLSI modeling and simulation, Control theory and applications, Military Technology Simulation, Aerospace technology simulation, Information engineering simulation, Energy Engineering Simulation, Manufacturing Simulation, Intelligent engineering simulation, Building engineering simulation, Electromagnetic field simulation, Material engineering simulation, Visual simulation, Fluid mechanics engineering simulation, Manufacturing simulation technology, Simulation architecture, Simulation software platform and Intelligent Optimization Algorithm, Dynamic Programming, Ant Colony Optimization, Genetic Algorithm, Simulated Annealing Algorithm, Tabu Search Algorithm, Ant Colony System Algorithm, Hybrid Optimization Algorithm in other related areas.The conference was begun at 10:00am, ended at 17:30am, 12 November, 2022. There were 77 participants in total, 2 keynote speakers and 17 invited oral speakers, Assoc. Prof. Jinyang Xu from Shanghai Jiaotong Univeristy in China and Dr. Victor Koledov from Innowledgement GmbH in Germany delivered their keynote speeches, each speech cost about 50 minutes, including the questions&discussion time.On behalf of the conference organizing committee, we'd like to acknowledge the unstinting support from our colleagues at Yaseen Academy, all Technical Program Members, speakers, reviewers, and all the participants for their sincere support.Conference Organizing CommitteeICMSOA 2022List of Conference General Chair, Program Chair, Conference Committee Chair Members, International Technical Committee Members, International Reviewers are available in this Pdf.
ABSTRACT
We sought to supplement medical physics textbook knowledge and clinical learning with case-based discussions. To our knowledge, this is the first report on a structured combined applied physics curriculum for radiation oncology (RO) and medical physics (MP) trainees. We reviewed our yearly applied physics course given from the years 2016-2021 inclusive. The number of applied physics trainees ranged from 7 to 14 per year (2-9 RO and 3-6 MP residents per year). Each session was taught by a pair of (RO and MP) faculty members. Twenty-nine case-based sessions were given yearly (2016 to 2019). Because of the COVID-19 pandemic restrictions, the course was shortened to 8 case-based sessions in 2020 and 2021. For the years 2016-2021, the mean and median teaching evaluation scores were 4.65 and 5, respectively (range 2-5), where 1 represents worse teaching quality and 5, the best teaching quality. For the year 2021, 2 questions relating to the video virtual format (implemented due to the covid-19 pandemic), revealed consistent high scores with the mean and median responses of 4.14 and 5, respectively (range 1-5). The results from the teaching evaluation scores indicate that the trainees highly valued the teaching sessions and teachers. Our experience indicates that a case-based applied physics course was delivered successfully with continued high teaching evaluation scores. A video virtual platform for an applied physics course could be useful, especially for small programs without a structured applied physics curriculum.
ABSTRACT
In the present day medical scenario, lung related diseases are growing in tremendous scale. There is a large leap of death rates due to lung related diseases in recent years. Since covid and other viruses are seriously causing a large variety of lung diseases including pneumonia, lung opacity, and other nostalgic diseases. Due to large amount of people visiting the hospitals everyday it becomes quite tough to evaluate reports of every patient manually. Thus, it requires automation of report analysis. With the advancement in artificial intelligence, it is now possible to analyse the scan of the patient and to produce appropriate result. This automation not only help the management but also helps the patient by reducing the costs. With the help of this project, we will introduce a platform where the user can submit their scan or lung X-ray and can get the appropriate result. In this project we are concentrating on the lung related disease called lung opacity. It is a disease where the lung of patient is filled with pus leading to inconvenience in breathing and in few severe cases it even leads to death. In order to help the hospital managements in automation and patients in early identification of diseases we are proposing a brilliant model that can tackle this problem and provide best automation solution.
ABSTRACT
Objective: Coronavirus disease 2019 may be associated with a white spectrum of post recovery disease complications and health impairment. The objective of this study was to evaluate and assess the different perimeters of pulmonary Function Tests and late outcome of the disease after hospital discharge at 3 and 6 months among the patients admitted with swerve COVID Pneumonia. Method: Our analysis consisted of comparison of the FVC at 3 and 6 months after hospital discharge in order to evaluate the disease severity with time. Results: A total of 41 hospitalized patients had their Pulmonary Function Tests evaluated >70% of the patients had their FVC <80% at 3 months and >12% had their FVC <80% at 6 months. To study abnormality of spirometry in severe post COVID-19 patients who were discharge from ICU hospital and complete the follow up after one month 3, 6. CONCLUSION: In patients who developed moderate to severe pneumonia more than 70% had abnormal FVC at 3 months. These patients were to be identified and treated with optimal management and as a result only 12% of patients had long term impairment in FVC and long term sequel.
ABSTRACT
The COVID-19 pandemic had an impact on the educational system all over the world. As a result, the educational institutions have to solely rely on online method of delivering education in the form of e-lectures, e-presentations and webinars. Elearning has been defined as "an educational method that facilitates learning by the application of information technology and communication providing an opportunity for learners to have access to all the required education programmes."1 The term e-learning has been interchangeably used with the terms web-based learning, online learning or education, computer-assisted or -aided instruction, computer-based instruction, internet based learning, multimedia learning, technology-enhanced learning and virtual learning.2,3 All the institutions are striving to best deliver the content online to engage students effectively and to conduct timely assessments for them. It has led to accelerated development of online learning environment so that learning would not be hindered. Online Learning Management Systems (LMS) are web-based software for distributing, tracking, and managing courses over the Internet. These systems offer an effective solution to deliver the learning content effectively and establish a two-way communication between the faculty and students.
ABSTRACT
A significant proportion of people infected with SARS-CoV-2 report a new onset of smell or taste loss. The duration of the chemosensory impairment and predictive factors of recovery are still unclear. In this study, we aim to describe the prevalence and features of loss of smell (anosmia) and loss of taste (ageusia) in Covid-19 patients. This study was done during second wave of Covid -19 to assess the smell and taste sensations dysfunction in Covid-19 infected subjects. Subjects above age of 18 years who were infected with Covid -19 virus and recovered from Covid-19 infection were included in this study. 50.49 % subjects had loss of smell sensation. 36.76% subjects had loss of taste sensation, whereas 34.31 % subjects had loss of both smell and taste sensation. Chemosensitive dysfunction is associated with coronavirus disease and may be the only symptom that presents the disease. Smell and taste loss are highly prevalent in COVID-19.
ABSTRACT
A vehicle which is used to transport patients to hospitals is called as ambulance, this ambulance vehicle is equipped with some vital lifesaving equipment's and first aid medicines. With these medicines and equipment's, the patients are given first aid till it reaches the desired hospital. Whenever a patient is in life-threatening emergency, then the ambulance paramedics should act promptly and must update the status of the patient to their doctors. This type of treatment or service is called Emergency Medical Service (EMS). It deals with immediate treatment and timely movement of the patients. For implementing EMS in ambulance several solutions have been developed for faster means of communication between the equipment's used in ambulance and the doctors. But the solutions are not viable in emergency situations. In additions during Covid wave in 2020 there was a scarcity for hospitals beds, it was filled with many covid patients. In many hospitals there was a queue of ambulances with patients waiting outside the hospitals. In some cases, the patients even died before getting any treatment, to overcome such crucial situations we have come out with a new system combining IoT, Sensor system and Embedded Controllers. The system developed here has sensors to monitor patients' vital parameters and transmits to the hospital server, such that a doctor can know the live condition of the patient and he can give instructions to the paramedics to do emergency aids. The system is a compactable and connects to the server with a mobile hotspot. The information is updated every 10 seconds. By implementing this system in ambulances, it saves many valuable lives of the people.