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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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Viral diseases are common and natural in human it spreads from animals and other humans. It seeks to identify the proper, reliable, and effective disease detection as quickly as possible so that patients can receive the right care. It becomes vital for medical field searches to have assistance from other disciplines like statistics and computer science because this detection is frequently a challenging process. These fields must overcome the difficulty of learning novel, non-traditional methodologies. Because so many new techniques are being developed, a thorough overview must be given while avoiding some specifics. In order to do this, we suggest a thorough analysis of machine learning which is used for the diagnosis of viral diseases caused in humans as well as plans. Predictions are made which is not obvious at the first glance does machine learning will be more helpful in making decisions. The study focuses on the machine learning algorithms for diagnosis of viral diseases for early diagnosis and treatment of viral diseases with greater accuracy. The work helps the researchers and medical professionals for learning and to give treatment for determining the applications of different machine learning techniques run to evaluate the parameters. Through examination of various parameters new machine learning model is proposed understanding the applications of machine learning in viral disease diagnosis like imaging techniques, plant virus diagnosis and the solution for the problem, Covid 19 diagnosis. © 2023 Bharati Vidyapeeth, New Delhi.
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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.
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Risk assessment models typically assume ideal mixing, in which the pathogen-laden aerosol particles emitted by a person are evenly distributed in the room. This study points out the local deviation from this idealized assumption and a correlation between the level of pathogen concentration and the distance from the emitter. For this purpose, several numerical studies (CFD) were analyzed, and a validation experiment was performed. Statistical evaluation of the spatial pathogen distribution was used to determine the potential exposure to elevated pathogen concentrations. Compared to an ideally mixed room, at a distance of 1.5 m, the mixing ventilation cases show a 25% risk of being exposed to twice the amount of pathogens and a 5% risk to more than 5 times the assumed value. For displacement ventilation there is a 75% chance of being exposed to less pathogens than in complete mixing at a distance of 1 m. The measurement values agree with the simulation results. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
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significant recommender systems (RS) development has occurred along with the Internet of Things (IoT) development in recent years. Recommender systems have been widely spread across diverse fields, including environmental preservation, e-commerce, healthcare, social and governance systems. There has been a growing focus on e-government as part of smart city initiatives in today's world of connected devices and infrastructure, especially after the COVID-19 pandemic. With the use of information and communication technologies (ICTs), the government can enhance the delivery of public services, increase transparency, accountability, and credibility, as well as engage citizens in the decision-making process. To facilitate 'smart' governance, one of a smart city initiative's objectives is integrating e-government into the city's governance framework. The lack of personalized services for particular stakeholders is one of the most significant limitations of e-governance. There are a number of open challenges coupled with interesting opportunities, making this a very promising and exciting area for research to shape recommendation systems for urban environments. Considering the overwhelming amount of information, services, and tasks available through smart government applications, it is a greater chance of providing personalized recommendations for different stakeholders and tasks within multi-faceted and multi-dimension. There is still a lot of research to be done on recommendation systems in the context of smart cities or smart government. This paper survey the existing studies on recommendation systems for smart governance. The study aims to address smart city challenges to considered when designing and implementing recommendations for e-governance and the target stakeholder's interests. © 2022 IEEE.
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Community greenhouses are important for the production of local food and reduction of food supply insecurities within cities. As we've seen with Covid-19, pandemics highlight the criticality of local food access to underprivileged urban districts. Since almost 60 % of the energy used in greenhouses is spent in heating and cooling, ground heat exchangers (GHEs) can play a significant role in supplying temperature regulation, but geothermal heat pump systems tend to be expensive for community organizations. An efficient way to reduce GHEs installation costs is to dig trenches to install the system horizontally and cover a part of heating and cooling loads only. In order to ensure cost effectiveness and optimize operations, this type of system was studied for urban greenhouses where ground space can be limited. Sizing calculations were performed for GHEs of a 7.62 m x 15.24 m greenhouse located on the Island of Montreal where the annual, monthly, and hourly energy consumption were estimated from previous building simulations. Three scenarios were used to specify sizing of the system in terms of excavation dimensions and percentage of the greenhouse peak loads covered;(1) number and length of trenches required for a horizontal GHE (HGHE) covering 100% of cooling and heating loads;(2) number and length of trenches required for an HGHE to cover 100% of peak heating loads and 60% of peak cooling loads and;(3) the percentage of heating and cooling peak loads that can be covered by an HGHE located under the greenhouse with similar dimensions (around 116 m2). Estimated excavation dimensions for cases 1 and 2 are 51.8 m x 8 m (414.4 m2) and 40.8 m x 8 m (326.4 m2). Estimated percentage of peak loads covered for case 3 is 40% of heating peak loads and 30% of cooling peak loads. © 2022 Geothermal Resources Council. All rights reserved.
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The United Downs geothermal power project has been developed by Geothermal Engineering Ltd (GEL) and is the first geothermal electricity project in the UK. The site was selected in 2010 for its geology (strongly faulted, radiogenic granite), surface infrastructure, grid connection and potential community acceptance. The deep drilling programme started in 2018, with the production well drilled to 5,275 m MD and deviating from 3,390 m to a final inclination of 33.5º, representing the deepest onshore well in the UK. The injection well was then drilled to 2,393m MD, deviating from 1,020 m to a final inclination of 40º. The drilling of a deep production well and shallow injection well into a natural fault zone is a concept developed by GEL, based on some of the results from the research at the Hot Dry Rocks project in Rosemanowes, Cornwall. The production well has successfully encountered significant permeability horizons within the target fault zone, temperatures of 180ºC and world-class lithium concentrations. It is expected to provide between 2 and 3 MWe to the National Grid and carbon neutral heat to a proposed 6 km heat main and the project has been associated with many universities and pan European research projects. Despite the delays caused by the Covid-19 pandemic, the United Downs project has seen a number of exciting milestones since EGC 2019, including completion of drilling, extensive well testing/stimulation and signing of the first Power Purchase Agreement (PPA) for deep geothermal electricity in the UK with Ecotricity. The team also secured grant funding for a demonstration plant that will trial Direct Lithium Extraction (DLE) from the deep geothermal fluid. This paper presents an overview of the initial results of drilling and testing, briefly highlighting the success of hydraulic stimulation and management of induced seismicity during development. It also provides a forward look to the final stages of the United Downs development and the future of geothermal power projects across Cornwall. © 2022 Geothermal Resources Council. All rights reserved.
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A global pandemic affected the type and place of work in several ways. For coworking places it caused disruptions according to direct (e.g. measures) and indirect (e.g. urban outmigration) reasons. The present chapter focuses on how coworking places in Hungary choose different adaptation strategies to deal with the unprecedented challenge that COVID-19 accounted for. It gives insight into the Hungarian pandemic situation between 2020 and 2022, identifying restrictions and no state financial aid whatsoever which determined the playing field for coworking places. The chapter contains different sections related to the outbreak and the Hungarian coworking landscape as well as coping strategies these alternative workspaces relied on to survive the first two years of the pandemic: location change, size reduction, change of function, and relying on informal networks are the identified ones. © 2023, The Author(s).
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PurposeThe purpose of this paper is to explain how aspects of institutional theory can be used to explain how tertiary educational providers must necessarily adopt the same features while competing in the market for students. Using new institutional sociology (NIS), the authors seek to explain this phenomena and how such diverse private providers have borrowed from the polytechnics and universities to share the same institutional features.Design/methodology/approachThis paper employs NIS to explain how tertiary educational providers must necessarily adopt the same features while competing in the market for students. In the last few decades, the Auckland tertiary market for overseas students has enjoyed strong growth before Covid-19.FindingsDecoupling provides a link between NIS and legitimacy theory in that it explains how symbolic strategies are aimed at some kind of legitimization rather than directed at technical efficiencies. It is argued that the public tertiary providers are more prone to decoupling than PTEPs because they are less attentive to costs due to their more monopolistic position in the market.Originality/valueOriginally, the market was dominated by the local universities and polytechnics with few private providers. Currently, private providers cater for a large share of the certificate and diploma market and have a growing stake in the degree market. As these changes came about so, more diverse private providers entered the market. This paper explains how these diverse entrants came to share the same organizational features.
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The theoretical model of the relationship among dose-response function parameters, quantum emission rate, and basic reproductive number for SARS-CoV-2 was constructed. Then, using this model, infection fields and pathways for SARS-CoV-2 and its variant were estimated. The parameters of the time activity, the number of contacts by the microenvironments and groups, and the COVID-19 risk from multiple pathways in near and far fields were used. Consequently, in lower transmissibility, droplet spray transmission in the near field was dominant, whereas in higher transmissibility, transmission from inhalation of smaller aerosols in the far field was dominant. Moreover, it was suggested that transmission from droplet spray, indirect contacts, and inhalation of smaller aerosols in the near field and inhalation of smaller aerosols in the far field was dominant for the wild-type strain, while transmission from inhalation of smaller aerosols in the far field were dominant for the Delta variant. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
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The oil industry is experiencing a critical situation as the Covid-19 pandemic outbreak. There are several challenges that facing the industry specially the investors as the global decline in demand for Energy merchandises, the future exploration and development drilling in new assets that require massive investments is still uncertain based on the current market price and conditions. The much-reported fall in oil prices and the acute pressure on IOCs to survive in this environment led the companies to stop many ongoing projects and shrink work profile that affected the oil production all over the world. The situation in Egypt is quite challenging for the investors as Egypt is a big consumer, along with the political stability that kept the economy running directed the big IOCs to embrace innovative approaches to lower the operating costs that has the direct impact on the cost per barrel to support maintaining the country growth and secure current energy demand. Dragon Oil company as newly introduced to Egypt's market after acquiring the market shares of one of the major joint ventures in Egypt (Gulf of Suez Petroleum Company- GUPCO) in October 2019 has faced the same dilemma of exerted pressure on the expenditures (Capex and Opex) in order to cope with the global market circumstances. However that didn't deter the company to embrace an innovative way of thinking and handling for the situation. Dragon Oil/GUPCO multi-disciplinary teams achieved successfully a production incremental increase of 10,000 barrels per day through the past six month by adapting a strategic management innovative plans, alternative lower cost technical solutions, production optimization and introducing new proved technologies to the 50 years old assets. This paper will highlight the complete workflow adopted by GUPCO/Dragon Oil teams covering the whole process aspects;appraise, select, define and execution phases to achieve the company goals. The work done was including restoring production from Shut-in offshore platforms or wells via fixing the surface network using neoteric solutions, widely applying rigless interventions using several new techniques in the current producers to maximize their production and optimizing the production cycle across the four production chokes In Summary, Dragon Oil/GUPCO teams managed to increase GUPCO's production despite of the restricted budget and the negative impact of COVID-19 pandemic on the oil price and reach an outstanding performance in operation excellence and safety aspects that results in arresting the natural decline and increase the growth production by about 15% from the 2019 Average production. Copyright © 2023, Society of Petroleum Engineers.
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The second phase of Johan Sverdrup came on stream in December 2022. This paper focuses on the execution of Johan Sverdrup phase 2 and describes the assessments and investments for improved oil recovery (IOR) from one of the largest oil fields in Norway. The Johan Sverdrup field development has been called Equinor's ‘digital flagship', and this paper includes the proof of concept for the digital initiatives after more than three years of operation. Despite the Covid-19 pandemic Johan Sverdrup phase 2 has been able to deliver on schedule, under budget, and with an excellent safety record. The paper includes experiences from the concept development and engineering phase to the global contracting strategy, through the construction on multiple building sites in Norway and globally, and until the end of the completion phase offshore Norway. Johan Sverdrup is the third largest oil field on the Norwegian Continental Shelf (NCS), and with recoverable reserves estimated at 2.7 billion barrels of oil equivalents, has the resources to be a North Sea Giant. Start-up of the Johan Sverdrup phase 2 extends and accelerates oil and gas production from the NCS for another five decades. This paper aims to highlight what it took to make Johan Sverdrup a true North Sea Giant, fit for the 21st century: a safe and successful execution of a mega-project, with next-generation facilities adapted to a more digital way of working, with an ambition to profitably recover more than 70% of the resources, while limiting carbon emissions from production to a minimum. In many ways the Johan Sverdrup development has set a new standard for project execution in Equinor. The impact of different variables made during the execution of the project, such as the Covid-19 pandemic, market effects, procurement strategies, value improvement initiatives, execution performance and reservoir characteristics is addressed, as well as describing assessments and investments for improved oil recovery (IOR). Data acquisition, Permanent Reservoir Monitoring (PRM), fibre-optic monitoring of wells, innovative technologies, and digitalization, as well as new ways of working are included. Equinor ´s digital strategy was established in 2017, and Johan Sverdrup was highlighted as a digital flagship at that time and a frontrunner in applying digital solutions to improve safety and efficiency from the development to the operational phase. What has been implemented so far together with experiences will be shared. © 2023, Offshore Technology Conference.
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This article considers the problem of the impact of the pandemic on medical personnel in the Russian Federation. During the pandemic, one of the most acute problems is the shortage of medical personnel. The study of the issue of shortage of medical personnel is relevant both for the whole world and for Russia. The authorities of several Russian regions at once, against the backdrop of an increase in the incidence of coronavirus, announced an acute shortage of doctors and mid-level health workers. In Russia, first of all, there was a shortage of primary health care doctors - general practitioners, general practitioners, and pediatricians. Staffing problems were discussed even before the pandemic, but during the pandemic, the workload on the medical staff increased and existing specialists began to leave. This paper presents possible solutions. Such as increasing wages and attracting students to increase staff. The purpose of the study is to analyze the reasons for the lack of personnel, identify existing problems, and formulate recommendations for their elimination. © 2023 IEEE.
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Adjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confounding present at global scales dissipates at local scales. We show that this assumption in the spectral domain is equivalent to adjusting for global-scale confounding in the spatial domain by adding a spatially smoothed version of the exposure to the mean of the response variable. Within this general framework, we propose a sequence of confounder adjustment methods that range from parametric adjustments based on the Matern coherence function to more robust semiparametric methods that use smoothing splines. These ideas are applied to areal and geostatistical data for both simulated and real datasets.
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This study used bibliometric analysis to investigate global research trends regarding the effect of COVID-19 risks in sustainable facility management fields. Between 2019 and 2021, the Scopus database published 208 studies regarding the effect of COVID-19 risks on sustainable facility control fields. VOSviewer software was used to analyse the co-occurrence of all keywords, and Biblioshiny software allowed getting the most relevant affiliation using the three-field plot. The results show the contribution by authors from 51 countries, and 73 keywords were identified and organised into six clusters, such as the effect of COVID-19 risks on human health, supply chain in construction projects and industry, disaster risk management in a changing climate, sustainable supply chain benchmarking, facility management and quality control, and, finally, sensitivity analysis & decision-making. © 2023 Khaled Jameel Aladayleh et al., published by Sciendo.
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Lung diseases rank among the world's top killers and disablers. Therefore, early identification is crucial for improving long-term survival rates and boosting the chances of recovery. Unlike the traditional method, machine learning (ML) showed great success in the medical field, mainly detecting and diagnosing different diseases. Most recently, the deep learning approach enhanced classification accuracy and eliminated the difficulty of manual feature extraction. As a literature conclusion, the model performance accuracy is inversely proportional to the number of lung diseases under consideration. In addition, no more than four classes (including normal) were considered previously. This work developed a lightweight CNN model, identified as DuaNet, with higher accuracy than the up-to-the-date models. The dataset has 930 X-ray images, categorized into five-class lung diseases: normal, tuberculosis, pneumonia COVID-19, pneumonia viral, and pneumonia bacterial. DuaNet comprises fifteen layers involving input, seven convolutional blocks, three max-pooling, three fully connected, and one output (Softmax) layer. Each convolutional block consists of a convolutional layer, Batch normalization, and ReLU activation function. The final model (DuaNet) obtained a performance accuracy of 99.87%, with 100% for other metrics. © 2022 IEEE.
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Accurate segmentation of infected areas in computed tomography (CT) images of the lungs of patients with novel coronavirus pneumonia (COVID-19) can assist doctors in diagnosing the patient's condition. This paper proposes an end-to-end new coronary pneumonia lung CT image segmentation model: SCA-Unet, which introduces the Cascading Context Module in the skip connection to expand the receptive field while retaining the context information of different layers to the greatest extent. At the same time, an Adaptive Select Module is added before each decoding layer to enhance the model's attention to segmentation targets and capture long-range dependencies. Experiments show that the model can better segment the infected area of COVID-19 patients, especially the infected area that is not easy to be segmented in the early stage, and each segmentation index is better than multiple comparison methods. © 2022 IEEE.
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Since the beginning of the COVID19 pandemic, there has been a lack of data to quantify the role played by breathing-out of pathogens in the spread of SARS-Cov-2 despite sufficient indication of its culpability. This work aims to establish the role of aerosol dispersion of SARS-Cov-2 virus and similar airborne pathogens on the spread of the disease in enclosed spaces. A steady-state fluid solver is used to simulate the air flow field, which is then used to compute the dispersion of SARS-Cov-2 and spatial probability distribution of infection inside two representative classrooms. In particular, the dependence of the turbulent diffusivity of the passive scalar on the air changes per hour and the number of inlet ducts has been given due consideration. By mimicking the presence of several humans in an enclosed space with a time-periodic inhalation-exhalation cycle, this study firmly establishes breathing as a major contributor in the spread of the pathogen, especially by superspreaders. Second, a spatial gradient of pathogen concentration is established inside the domain, which strongly refutes the well-mixed theory. Furthermore, higher ventilation rates and proximity of the infected person to the inlet and exhaust vents play an important role in determining the spread of the pathogen. In the case of classrooms, a ventilation rate equivalent to 9 air changes or more is recommended. The simulations show that the "one-meter distance rule"between the occupants can significantly reduce the risk of spreading infection by a high-emitter. © 2023 Author(s).
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R apid, sensitive and specific detection of viruses is a key issue in the medical field. Since 2020, the global outbreak of COVID-19 requires more sensitive virus detection methods. With the development of new materials, especially nanomaterials, many materials have demonstrated great physical, chemical and mechanical properties, which present potential for virus detection. Nanomaterials can be divided into zero-dimensional materials, one-dimensional materials and two-dimensional materials by structure. In this paper, the classification and the latest progress of nanomaterials are reviewed, highlighting their applications in the field of virus detection. The future prospect of nanomaterials in virus detection is also presented and discussed. © 2023 Cailiao Daobaoshe/ Materials Review. All rights reserved.
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In a modern era of unprecedented events, such as the COVID-19 pandemic, energy matters now more than ever. What was previously impossible is now a challenge that should be met with measured risk and a mitigation plan. In early 2020, a service company pursued a solution to provide a compact surface well test (SWT) package for an extended well test (EWT) on an offshore production platform in the Zafaraana field with extremely high concentrations of H2S. The solution involved proper treatment and safe delivery of well effluent within acceptable H2S limits to a floating production storage and offloading (FPSO) facility. The EWT was to be installed for a long period to allow production from the reservoir, treatment of the effluent using H2S scavenger, and delivery to the FPSO facility by means of electric transfer pumps. This was the only way to produce because the FPSO facility could not accommodate the high H2S concentrations from the reservoir. A further challenge was that it was a simultaneous operation (SIMOPs) wherein the rig was engaged in drilling and completion activities of other wells on the same offshore platform;operational conflicts were identified during the HAZOP/HAZID meeting to help mitigate potential issues. Copyright © 2023, Society of Petroleum Engineers.