ABSTRACT
[...]the time and money involved-it costs at least $30,000 to activate a site and takes an average of 100 days for an investigator site to be operational. [...]the impact on patients and participants is clear-particularly those with underlying health conditions. Artificial intelligence will be central to this-automating analyses of large data sets will augment human researchers' skills and lead to better clinical trials, from protocol and trial design to recruitment and management.
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The COVID-19 pandemic exposed the vulnerability of global supply chains of many products. One area that requires improved supply chain resilience and that is of particular importance to electronic designers is the shortage of basic dual in-line package (DIP) electronic components commonly used for prototyping. This anecdotal observation was investigated as a case study of using additive manufacturing to enforce contact between premade, off-the-shelf conductors to allow for electrical continuity between two arbitrary points by examining data relating to the stock quantity of electronic components, extracted from Digi-Key Electronics. This study applies this concept using an open hardware approach for the design, testing, and use of a simple, parametric, 3-D printable invention that allows for small outline integrated circuit (SOIC) components to be used in DIP package circuits (i.e., breadboards, protoboards, etc.). The additive manufacture breakout board (AMBB) design was developed using two different open-source modelers, OpenSCAD and FreeCAD, to provide reliable and consistent electrical contact between the component and the rest of the circuit and was demonstrated with reusable 8-SOIC to DIP breakout adapters. The three-part design was optimized for manufacturing with RepRap-class fused filament 3-D printers, making the AMBB a prime candidate for use in distributed manufacturing models. The AMBB offers increased flexibility during circuit prototyping by allowing arbitrary connections between the component and prototyping interface as well as superior organization through the ability to color-code different component types. The cost of the AMBB is CAD $0.066/unit, which is a 94% saving compared to conventional PCB-based breakout boards. Use of the AMBB device can provide electronics designers with an increased selection of components for through-hole use by more than a factor of seven. Future development of AMBB devices to allow for low-cost conversion between arbitrary package types provides a path towards more accessible and inclusive electronics design as well as faster prototyping and technical innovation.
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The popularity of the online teaching model increased during the COVID-19, and virtual reality online education is now firmly established as a future trend in educational growth. Human–computer interaction and collaboration between virtual models and physical entities, as well as virtual multi-sensory cognition, have become the focus of research in the field of online education. In this paper, we analyze the mapping form of teaching information and cue information on users' cognition through an experimental system and investigate the effects of the presentation form of online virtual teaching information, the length of the material, users' memory of the information, and the presentation form of information cues on users' cognitive performance. The experimental results show that different instructional information and cue presentation designs have significant effects on users' learning performance, with relatively longer instructional content being more effective and users being more likely to mechanically remember the learning materials. By studying the impact of multi-sensory information presentation on users' cognition, the output design of instructional information can be optimized, cognitive resources can be reasonably allocated, and learning effectiveness can be ensured, which is of great significance for virtual education research in digital twins.
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The personal protective equipment (PPE) has protected the frontline health workers from getting affected in COVID 19 spread situations to a certain level. Among the PPEs, PAPRs (Powered Air Purifying Respirators) are considered as one of the most efficient equipment for protection purposes. In pandemic spread situations, the PAPR becomes very much essential considering its protection. The PAPR is mainly imported to India. But the cost of PAPR being on the higher side (Rupees (Rs) 100000) becomes unaffordable to many frontline health workers. This paper focuses on the development of a cost-effective PAPR that is affordable to them. This paper projects a detailed step-by-step process of design and development of PAPR, and its evolution in each iteration. The study was conducted with the medical officers from AIMS Hospital and engineers from AMMACHI labs to bring out effective solutions for frontline health workers during a pandemic. © 2022 IEEE.
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The current crisis (triggered by the COVID 19 pandemic) is an opportunity to make a profound and systemic change towards a more sustainable economy that works for both people and the planet. It is about decoupling economic growth from environmental degradation, increasing resource efficiency and promoting sustainable lifestyles. The Design for Sustainability (D4S) concept describes methodologies for making sustainable (social, economic and environmental) improvements to products by applying elements of life cycle thinking. It is intended to go beyond the environmental optimization of products and reduce environmental impacts while maintaining an acceptable quality of service. This paper explores the characteristics that the databases or surveys used to link the properties of a certain product or service with the sensations of the users must have. The necessary size will be analyzed in terms of properties and levels of the product, emotions produced and number of respondents;putting it in relation to the data analysis and processing techniques that will be used in later phases. © 2022 by the authors. Licensee AEIPRO, Spain.
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This study employed the response surface methodology to optimize the extraction conditions for recovering vitamins D2 and K1 from green leafy vegetables using ultrasonication-assisted extraction. The vitamin content was determined using an Accucore C18 column and a UPLC-Q-ToF/MS method. An RSM-I-Optimal design was used for designing the experiment to find the best combination of solvent level (mL), sonication time (min), sonication frequency (kHz), and temperature (°C). The experimental data from a 25-sample set were fitted to a second-order polynomial equation using multiple regression analysis. The extraction models had R2 values of 0.895 and 0.896, respectively, and the probability values (p < 0.0001) indicated that the regression model was highly significant. The optimal extraction conditions were: solvent level of 65 mL, sonication time of 45 min, sonication frequency of 70 kHz, and temperature of 45 °C. Under these conditions, the predicted recovery (%) values for vitamins D2 and K1 were 90.7% and 90.4%, respectively. This study has the potential to use the reported extraction method for routine quantification of vitamins D2 and K1 in the laboratory using UPLC-Q-ToF/MS.
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The aim of this paper is to formulate and solve the aircraft maintenance scheduling design optimization problem while considering the effects of a pandemic, such as the COVID-19 pandemic. Aircraft maintenance is dependent on how much the aircraft is in service, among other factors. It is no surprise that the pandemic has significantly impacted airline operations, due to travel restrictions and people’s hesitancy to travel. Thus, it is important for airliners to consider the progression of the pandemic when designing their flight and maintenance schedules. The approach proposed in this paper addresses this issue by integrating several models. The first one is a time series forecasting model to predict future COVID-19 cases – in this paper we use a Long Short-Term Memory (LSTM) network. The second model is a simple neural network for predicting flight frequencies based on historical flight data and the results of the first model. The predicted flight frequencies are used to generate a flight schedule, which serves as input to the third model – the maintenance schedule design optimization model, which is formulated as a mixed binary-integer non-linear optimization problem. The final output from the integrated model is the optimized maintenance schedule and associated costs. To demonstrate the proposed approach, we present an illustrative example with 3 aircraft and perform a sensitivity analysis to gain further insight into the results. Copyright © 2022 by ASME.
ABSTRACT
Additive manufacturing is a rapidly evolving technological field, beyond he simple application of 3D printers, leading to an entirely new means of designing and manufacturing objects, paving the way for novel and unexplored possibilities. It is currently used in the production of mechanical components and tooling, medical and surgical implants and, also, to facilitate surgical design. The advantages stemming from this technology should be facilitated to combat the COVID-19 pandemic. With cases of respiratory failure and respiratory distress globally soaring and unavailability of standard automated ventilators in certain regions, the need to meet this demand is crucial. In this context, the research team considered it appropriate to move towards finding a solution to the problem of shortage in respirators in health systems worldwide. Having originally received plans for 3D printing from the University of Illinois, which produced disposable mechanical respirators with this technology, the possibility of optimizing and producing them at UNIWA was explored. The CAD files were analyzed in order to evaluate their printability resulting in partial redesign in order to limit dimensional variability, acceptable surface finish and make the printing process generally easier, faster, and less expensive. In addition, these modifications make the parts more suitable for casting, if high output is required. Metallic and thermoplastic composite respirators were produced and then tested in real operating conditions, i.e. with oxygen supply resembling a hospital environment. The initial results are considered positive, both in the quality of construction and in their performance. Furthermore, combination ofmanufacturing technologies is assessed, aiming at high output production. © 2022 American Institute of Physics Inc.. All rights reserved.
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This paper presents a newly developed microfluidic flow control theory for autonomous sample dispensing into an array of reaction microchambers. The theoretical predictions for the possible dispensing number and maximum flow rate were validated by comparison to experimental results. Moreover, we successfully demonstrated the rapid genetic detection of multiple infectious viruses including SARS-CoV-2 in fabricated polydimethylsiloxane (PDMS)-based microfluidic devices based on the loop-mediated isothermal amplification (LAMP) method. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.
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This article examines the long-run two-way causal relationship between government revenues and spending and their interaction with the yearly change in public debt for eighteen OECD countries by using annual data for 1976-2017 period. The empirical literature has mainly focused on the long run relationship between government expenditure and revenues or other single country time series while only a few studies have used panel causality analysis and none have investigated the link with the evolution of public debt ratios. The purpose of this paper is to present a dynamic model identifying the underlying relationships constituting the fiscal policy set-up in sample countries. We apply a robust dynamic panel causality methodology based on SUR systems and Wald tests with country specific bootstrap critical values. The study also aims to provide the basis for recommendations on the policy response to public finance challenges stemming from exogenous shocks like the global pandemic that began in 2020. By developing an enhanced analysis of the long-term causal relationship between taxation, spending and their interaction with changes in public debt, the study not only provides fresh insights into the sustainability and optimal design of fiscal adjustment efforts but also offers a country-specific schematization as a guide for policymaking.
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Data are playing an increasingly important role in the development of industry–education cooperation strategies in vocational education and training. The objective of this study was to promote the comprehensive progress of an industry–education cooperation system and improve the effect of the application of big data technology in this system. First, we designed of a big data technology application in an intelligent management platform system for industry–education cooperation. Second, we analyzed the synthetical design of the system. Finally, we optimized and designed a support vector machine (SVM) data mining (DM) algorithm model based on big data, and evaluated the model. The results revealed that the designed algorithm model provides outstanding advantages compared with similar algorithm models. In general, the highest average computation time of the designed SVM algorithm model is about 95 ms. The overall average calculation time linearly decreases around 200 iterations and tends to be stable, and the lowest overall average computation time is about 20 ms. In the DM process, the highest accuracy rate of the model is about 97%, and the lowest is about 92%. The DM accuracy rate is always stable as the number of iterations of the model continues to increase. The designed model slowly increases the occupancy rate of the system in the process of increasing computing time. At about 60 min, the system occupancy rate of the model tends to be stable, and the highest is maintained at about 23%. This study not only provides technical support for the optimization of DM algorithms with big data technology, but also contributes to the integrated development of industry–education cooperation systems.
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The management of the global energy resources has stimulated the emergence of various agreements in favor of the environment. Among the most famous are the Conference of Parties (COP) and Route 2030, which aim to limit global warming to 1.5 °C by reducing the energy consumption and global emission levels. In order to comply with the international standards for energy consumption and pollutant emissions, the Brazilian government has been promoting the expansion of biofuels in the national energy matrix. Considering this scenario, the development of a novel internal combustion engine for the exclusive use of ethanol as a fuel, equipped with state-of-the-art technologies and employing modern design concepts, consists of an innovative and promising pathway for future Brazilian mobility, from both environmental and technological outlooks. In this sense, this work presents a method to determine the main engine dimensions as part of the initial process for a new ethanol prototype engine development. The Brazilian biofuel was selected due to its physicochemical properties, which allow the engine to achieve higher loads, and also due to its large availability as a renewable energy source in the country. Furthermore, a port water injection system was fitted to the engine in order to assist the combustion process by mitigating the knock tendency. The predicted overall engine performance was obtained by carrying out a GT-PowerTM 1D-CFD simulation, whose results pointed to a maximum torque of 279 Nm from 2000 to 4000 rpm and an indicated peak power of 135 kW at 5500 rpm. With a maximum water-to-fuel ratio of 19.2%, the engine was able to perform its entire full load curve at the MBT condition, a fact that makes the WI approach along with the ethanol fuel a very attractive solution. As a result of the specific design and optimization of each geometric parameter for this unique ethanol engine, a maximum indicated fuel conversion efficiency of 45.3% was achieved. Moreover, the engine was capable of achieving over 40% of the indicated fuel conversion efficiency in almost its entire full load curve.
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One of the most competitive fields on the planet is the automotive industry. Newmarket and innovative designs regularly arise, necessitating the development of new manufacturing methods to keep up with the automotive industry. Additive manufacturing offers a significant competitive advantage in this industry, serving as a disruptive strategy by increasing production flexibility, reducing product development time, and providing optimal automotive components and bespoke vehicle products on demand. Additive manufacturing on soft assembly tools or specialised tools to make automotive components enhances automotive production. Additive Manufacturing's freeform capability allows for the design and direct fabrication of optimised automotive components aimed at improving vehicle performance, as well as tailored assembly tools to boost productivity. Another related technological advantage of additive manufacturing is the ability to create lightweight components with the help of generative design algorithms. Furthermore, the time to market for Additive Manufacturing parts has fallen dramatically, allowing mass customisation to become a reality. The strong downward trend in fuel consumption offers new automobile design, performance, and compliance with regulations. Considering the actual example switch from the conventional combustion engine to other motion systems, Additive Manufacturing is a critical enabler technology for modern automobiles. This paper provides an overview of Additive Manufacturing applications in the automobile sector, focusing on the technical and economic benefits of this manufacturing technology.
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Recent years of research and development have brought frequently used terms for new types of green solvents to the lexicon of scientists. This can lead to terminological inaccuracies. In particular, different names are being used for the same types of solvents: Deep Eutectic Solvents (DES);Natural Deep Eutectic Solvents;Low-Transition Temperature Mixtures;Low-Melting Mixtures. It would, therefore, be appropriate to eliminate certain inaccuracies and to use simplification, which means using the general term “Low-Temperature Transition Mixtures” or introducing the term “DES-like mixtures”.
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In recent years, the development of e-commerce new retail formats is in full swing, and the terminal distribution has become a hot research topic under the background of new retail. The accuracy of the community navigation map is related to the low cost and high efficiency of terminal distribution and then affects the development of new e-commerce retail. However, in large communities, the existing navigation map software can only locate the main entrance of the community, and there is a lack of effective positioning for the location of buildings. Therefore, based on the existing navigation map, this paper expects to correct its application defects and carry out optimization design from the design principle, design idea, product function, product customization, and product application effect, so as to make the community navigation more accurate, faster, and more efficient, to help the low cost and efficient development of door-to-door distribution under the new retail of e-commerce.
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The importance of creating a better living environment that is conducive to public health has become increasingly prominent in the post-epidemic era. The restorative potential of urban streets has been emphasized recently, as these spaces of our everyday lives may provide people with restorative experiences. However, there is still no efficient way of delivering restorative street design, because no specific standard has been set to indicate the form such streets should take. A street has limited spaces but multiple uses;hence, the delivery of restorativeness is largely restricted by street contexts. This research proposes that this standard should be determined by the balance between street functions and restorative benefits. An expectation-current approach that involves street functions, street typologies, restorative evaluations and users’ expectations was developed in conjunction with its application to four pairs of streets. Each pair included one typical street type determined by its inherent function, and one corresponding case-study street. The restorative expectations and the streets’ current levels of restorativeness were evaluated, and their differences were used to indicate how and to what degree street-related restorative benefits should be optimized. Restorative design implications of the four case-study streets were then summarized accordingly. The expectation–current approach not only serves as a rigorous and sustainable method by stressing the balance between street functions and restorativeness, but also has the potential for application in broader assessment studies, especially when multiple environmental qualities need to be considered, with the advantage of the extensive involvement of people.
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Featured ApplicationA novel methodology for project management applicable for self-protection plans for public buildings based on the best practices of technologies, systems, and methods.Self-protection plans are the fundamental tool established to prevent and control the risks that threaten people and assets. In turn, they are essential to provide an adequate response to possible emergency situations that may occur in public or private buildings, facilities, or events. In this context, current and future challenges advocate increasing the usefulness, versatility, and adaptability of self-protection plans. For this purpose, this paper aims to develop a conceptual model for the project management of self-protection plans with a lifecycle approach. The research provides results concerning guidelines, aspects, and potential regulations, technologies, tools, methodologies, and maintenance frameworks to be followed for any building in different project phases. The methodology followed has consisted of a process in stages, with literature review and a conceptual development to obtain an adaptable model to any public building. The adaptability of the framework relies on the definition of potential methods, information systems, and technologies that can support any phase during the Self-Protection Plan life cycle. Moreover, it was applied in a specific environment, such as in public buildings under the Spanish regulation using the most common tools and applications available. Results proved that although it is possible to make a base model applicable to any publicly owned building, there is an extensive and precise subsequent work of adaptation to specific cases in which the applicable legal framework makes this task challenging. Finally, the results obtained have allowed us to reflect on future research needs.
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In recent years, precise high flow oxygen therapy as a new type of oxygen therapy machine has gradually attracted people’s attention and has been widely used in hospital emergency and clinical treatment of respiratory diseases;especially in recent years, severe coronavirus disease (COVID-19) has played an important role in the treatment of patients. This paper presents a new type of precise high flow oxygen therapy machine with electromagnetic pneumatic flow valve as the core control element. A sliding mode control strategy based on the system is proposed to realize the accurate control of oxygen concentration and output flow of oxygen therapy mixture. The physical equipment of the precision high flow system is established, and its working performance is verified through the test platform. The optimization design goal of the precision high flow equipment is achieved.
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Dumping is one of the main unit operations of mining. Notwithstanding a long history of using large rear dump trucks in mining, little knowledge exists on the cascading behavior of the run-of-mine material during and after dumping. In order to better investigate this behavior, a method for generating high fidelity models (HFMs) of dump profiles was devised and investigated. This method involved using unmanned aerial vehicles with mounted cameras to generate photogrammetric models of dumps. Twenty-eight dump profiles were created from twenty-three drone flights. Their characteristics were presented and summarized. Four types of dump profiles were observed to exist. Factors that influence the determination of these profiles include the location of the truck relative to the dump crest, the movement of the underlying dump material during the dumping process and the differences in the dump profile prior to dumping. The HFMs created in this study could possibly be used for calibrating computer simulations of dumps to better match reality.
ABSTRACT
[...]it is clear by the policies and scenarios which are already laid out, that we need to investigate in detail and improve the existing technologies in an effective manner. [13] present a frequency splitting based energy management strategy in a microgrid consisting of a diesel generator, supercapacitors, wind turbine, solar photovoltaic generator, and lithium batteries. A dedicated building has been recommended for the electrode station for the sake of limiting energy consumption, preventing electrochemical corrosion, protecting from environmental constraints, and reducing the risk of fire hazards by increasing the fire resistance by installing a firefighting system. [...]a design process for the electrode station building has been proposed in detail.