design choice
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2022 ◽  
Vol 18 (1) ◽  
Author(s):  
Michael A. Stoto ◽  
Abbey Woolverton ◽  
John Kraemer ◽  
Pepita Barlow ◽  
Michael Clarke

Abstract Background The COVID-19 pandemic has led to an avalanche of scientific studies, drawing on many different types of data. However, studies addressing the effectiveness of government actions against COVID-19, especially non-pharmaceutical interventions, often exhibit data problems that threaten the validity of their results. This review is thus intended to help epidemiologists and other researchers identify a set of data issues that, in our view, must be addressed in order for their work to be credible. We further intend to help journal editors and peer reviewers when evaluating studies, to apprise policy-makers, journalists, and other research consumers about the strengths and weaknesses of published studies, and to inform the wider debate about the scientific quality of COVID-19 research. Results To this end, we describe common challenges in the collection, reporting, and use of epidemiologic, policy, and other data, including completeness and representativeness of outcomes data; their comparability over time and among jurisdictions; the adequacy of policy variables and data on intermediate outcomes such as mobility and mask use; and a mismatch between level of intervention and outcome variables. We urge researchers to think critically about potential problems with the COVID-19 data sources over the specific time periods and particular locations they have chosen to analyze, and to choose not only appropriate study designs but also to conduct appropriate checks and sensitivity analyses to investigate the impact(s) of potential threats on study findings. Conclusions In an effort to encourage high quality research, we provide recommendations on how to address the issues we identify. Our first recommendation is for researchers to choose an appropriate design (and the data it requires). This review describes considerations and issues in order to identify the strongest analytical designs and demonstrates how interrupted time-series and comparative longitudinal studies can be particularly useful. Furthermore, we recommend that researchers conduct checks or sensitivity analyses of the results to data source and design choices, which we illustrate. Regardless of the approaches taken, researchers should be explicit about the kind of data problems or other biases that the design choice and sensitivity analyses are addressing.


2022 ◽  
pp. 320-331
Author(s):  
Robin Throne ◽  
Abeni El-Amin ◽  
Lucinda Houghton

This chapter presents a conceptual analysis of the current trends for research paradigmatic perspectives used in doctoral social justice research approaches. The chapter offers a concise resource for doctoral scholars and their research supervisors to establish and illustrate a relevant paradigmatic perspective aligned with the research method and design choice to view the dissertation research problem in doctoral social justice research. Paradigmatic perspectives from feminist, critical theoretical perspectives, and grounded theory are also included as examples of specific approaches.


2021 ◽  
Author(s):  
Jonas Kristiansen Nøland ◽  
Christian Hartmann ◽  
Runar Mellerud

Hydrogen-powered airplanes have recently attracted a revitalized push in the aviation sector to combat CO2 emissions. However, to also reduce, or even eliminate, non-CO2 emissions and contrails, the combination of hydrogen with all-electric solutions is undoubtedly the best option to move toward the ambitious goal of climate-neutral aviation. Another important design choice is to store hydrogen cryogenically in its liquid form (LH2) to reduce space occupation compared to storage as compressed gas. However, the LH2 fuels cannot be utilized directly in fuel cells. It needs to be brought from liquid to a gas at about 350 K, where large amounts of heat must be added. Thus, a synergy can be made from this otherwise wasted cryogenic refrigeration power where superconducting machines (SCMs) and cold power electronics (CPE) are low-hanging fruits that could lead to radical space and weight reductions onboard the aircraft. These opportunities can be realized without having to pay the price, nor the volume occupation and mass needed for the cooling ability usually needed to achieve these extraordinary performances. In fact, this ground-breaking synergy makes cryogenic energy conversion relevant in a whole new way for aviation. The SCMs’ more than five times higher power densities than their conventional counterparts are exceptionally significant. This article introduces the recently proposed cryo-electric drivetrain initiatives and explores the opportunities of using direct hydrogen cooling as a potential heating solution to enhance the overall performance and scalability of zero-emission propulsion systems in future regional aircraft.


2021 ◽  
Author(s):  
Jonas Kristiansen Nøland ◽  
Christian Hartmann ◽  
Runar Mellerud

Hydrogen-powered airplanes have recently attracted a revitalized push in the aviation sector to combat CO2 emissions. However, to also reduce, or even eliminate, non-CO2 emissions and contrails, the combination of hydrogen with all-electric solutions is undoubtedly the best option to move toward the ambitious goal of climate-neutral aviation. Another important design choice is to store hydrogen cryogenically in its liquid form (LH2) to reduce space occupation compared to storage as compressed gas. However, the LH2 fuels cannot be utilized directly in fuel cells. It needs to be brought from liquid to a gas at about 350 K, where large amounts of heat must be added. Thus, a synergy can be made from this otherwise wasted cryogenic refrigeration power where superconducting machines (SCMs) and cold power electronics (CPE) are low-hanging fruits that could lead to radical space and weight reductions onboard the aircraft. These opportunities can be realized without having to pay the price, nor the volume occupation and mass needed for the cooling ability usually needed to achieve these extraordinary performances. In fact, this ground-breaking synergy makes cryogenic energy conversion relevant in a whole new way for aviation. The SCMs’ more than five times higher power densities than their conventional counterparts are exceptionally significant. This article introduces the recently proposed cryo-electric drivetrain initiatives and explores the opportunities of using direct hydrogen cooling as a potential heating solution to enhance the overall performance and scalability of zero-emission propulsion systems in future regional aircraft.


Designs ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 76
Author(s):  
Laetitia Zoungrana ◽  
Sayon dit Sadio Sidibé ◽  
Benoît Herman ◽  
Yézouma Coulibaly ◽  
Hervé Jeanmart

This paper introduces the design of a biomass gasification reactor with specific constraints for its manufacturing and operation in the West African conditions. The foreseen applications are the valorisation into heat and electricity of agricultural biomass residues. Rice husk is chosen as the reference fuel for the design. Local manufacturing is a key feature and the main focus of the design, as it allows us to reduce the capital costs and facilitate the maintenance. The design methodology is based on the conceptual approach proposed by Cross. This approach leads in several steps to a rational design choice based on the evaluation of different solutions. In this study, nine reactor types have been compared leading to a prototype that best suits the defined objectives such as a local manufacturing, a secure installation and a sufficient gas quality. From this conception approach, the Semi-Batch, Fixed-bed reactor with air Aspiration appears the most suitable. Its specific characteristics for the foreseen application are a power of 44 kW based on the syngas lower heating value, an average fuel consumption of 20.38 kg/h and an average air flow of 28.8 kg/h for optimal gasification. The gasifier resulting from the design methodology has been built. It is presented in the paper.


Author(s):  
Shun Zhong ◽  
Jingyuan Tan ◽  
Zhicheng Cui ◽  
Tanghong Xu ◽  
Liqing Li

Purpose. Impacts appear in a wide range of mechanical systems. To study the dynamical behavior introduced by impact in practical way, a single-degree-of-freedom impact oscillator rig is designed. Originality. A simple piece-wise linear system with symmetrical flexible constraints is designed and manufactured to carry out a wide range of experimental dynamic analysis and ultimately to validate piece-wise models. The new design choice is based on the following criteria: accuracy in representing the mathematical model, manufacturing simplicity, flexibility in terms of parameter changes and cost effectiveness as well avoidance of the delay introduced by the structure. Meanwhile, the new design provides the possibility of the applications of the complex control algorithms. Design/methodology/approach. The design process is described in detail. The initial experimental results of the rig as well as numerical simulation results are given. In this rig, the mass driven force is generated by electromagnet, which can be adjusted and control easily. Also, most of the physical parameters can be varied in a certain range to enhance flexibility of the system allowing to observe subtle phenomena. Findings. Compared with the simulation results, the designed rig is proved to be validated. Then, the initial experimental results demonstrate potentials of this rig to study fundamental impact phenomena, which have been observed in various engineering systems. They also indicate that this rig can be a good platform for investigating nonlinear control methods.


2021 ◽  
Author(s):  
Sander van der Linden ◽  
Matthew H. Goldberg ◽  
Rakoen Maertens ◽  
John R Kerr ◽  
Edward Maibach ◽  
...  

Chinn and Hart (2021) argue that their experiment on the effects of communicating the scientific consensus on climate change revealed “mixed” and “inconsistent findings”. We note that Chinn and Hart (2021) provide clear and consistent evidence that the scientific consensus message has positive indirect effects on climate beliefs, attitudes, and support for public action, and that these effects are more pronounced among conservatives (as predicted). Importantly, however, the authors’ claim that these positive findings might simply be the result of an experimental design choice: the use of a pre-test of the dependent variables. Here we argue that no convincing evidence is provided for the conclusion that pre-tests should not be used. In fact, contrary to the authors’ recommendation, we make the case that the inclusion of a pre-test in randomized controlled designs increases power and precision. Furthermore, we point to its central importance for the ability to capture and evaluate the Gateway Belief Model’s (GBM) key predictions about changes in public attitudes.


2021 ◽  
Author(s):  
◽  
Van Tran Bao Le

<p>A database is said to be C-Armstrong for a finite set Σ of data dependencies in a class C if the database satisfies all data dependencies in Σ and violates all data dependencies in C that are not implied by Σ. Therefore, Armstrong databases are concise, user-friendly representations of abstract data dependencies that can be used to judge, justify, convey, and test the understanding of database design choices. Indeed, an Armstrong database satisfies exactly those data dependencies that are considered meaningful by the current design choice Σ. Structural and computational properties of Armstrong databases have been deeply investigated in Codd’s Turing Award winning relational model of data. Armstrong databases have been incorporated in approaches towards relational database design. They have also been found useful for the elicitation of requirements, the semantic sampling of existing databases, and the specification of schema mappings. This research establishes a toolbox of Armstrong databases for SQL data. This is challenging as SQL data can contain null marker occurrences in columns declared NULL, and may contain duplicate rows. Thus, the existing theory of Armstrong databases only applies to idealized instances of SQL data, that is, instances without null marker occurrences and without duplicate rows. For the thesis, two popular interpretations of null markers are considered: the no information interpretation used in SQL, and the exists but unknown interpretation by Codd. Furthermore, the study is limited to the popular class C of functional dependencies. However, the presence of duplicate rows means that the class of uniqueness constraints is no longer subsumed by the class of functional dependencies, in contrast to the relational model of data. As a first contribution a provably-correct algorithm is developed that computes Armstrong databases for an arbitrarily given finite set of uniqueness constraints and functional dependencies. This contribution is based on axiomatic, algorithmic and logical characterizations of the associated implication problem that are also established in this thesis. While the problem to decide whether a given database is Armstrong for a given set of such constraints is precisely exponential, our algorithm computes an Armstrong database with a number of rows that is at most quadratic in the number of rows of a minimum-sized Armstrong database. As a second contribution the algorithms are implemented in the form of a design tool. Users of the tool can therefore inspect Armstrong databases to analyze their current design choice Σ. Intuitively, Armstrong databases are useful for the acquisition of semantically meaningful constraints, if the users can recognize the actual meaningfulness of constraints that they incorrectly perceived as meaningless before the inspection of an Armstrong database. As a final contribution, measures are introduced that formalize the term “useful” and it is shown by some detailed experiments that Armstrong tables, as computed by the tool, are indeed useful. In summary, this research establishes a toolbox of Armstrong databases that can be applied by database designers to concisely visualize constraints on SQL data. Such support can lead to database designs that guarantee efficient data management in practice.</p>


2021 ◽  
Author(s):  
Andrey Fradkin ◽  
Elena Grewal ◽  
David Holtz

Reputation systems are used by nearly every digital marketplace, but designs vary and the effects of these designs are not well understood. We use a large-scale experiment on Airbnb to study the causal effects of one particular design choice—the timing with which feedback by one user about another is revealed on the platform. Feedback was hidden until both parties submitted a review in the treatment group and was revealed immediately after submission in the control group. The treatment stimulated more reviewing in total. This is due to users’ curiosity about what their counterparty wrote and/or the desire to have feedback visible to other users. We also show that the treatment reduced retaliation and reciprocation in feedback and led to lower ratings as a result. The effects of the policy on feedback did not translate into reduced adverse selection on the platform.


2021 ◽  
Vol 8 ◽  
Author(s):  
Radu Mariescu-Istodor ◽  
Pasi Fränti

The scalability of traveling salesperson problem (TSP) algorithms for handling large-scale problem instances has been an open problem for a long time. We arranged a so-called Santa Claus challenge and invited people to submit their algorithms to solve a TSP problem instance that is larger than 1 M nodes given only 1 h of computing time. In this article, we analyze the results and show which design choices are decisive in providing the best solution to the problem with the given constraints. There were three valid submissions, all based on local search, including k-opt up to k = 5. The most important design choice turned out to be the localization of the operator using a neighborhood graph. The divide-and-merge strategy suffers a 2% loss of quality. However, via parallelization, the result can be obtained within less than 2 min, which can make a key difference in real-life applications.


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