scholarly journals Spectral Properties of Dissipation

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Peter Ván ◽  
Róbert Kovács ◽  
Federico Vázquez

Abstract The novel concept of spectral diffusivity is introduced to analyze the dissipative properties of continua. The dissipative components of a linear system of evolution equations are separated into noninteracting parts. This separation is similar to mode analysis in wave propagation. The new modal quantities characterize dissipation and are best interpreted as effective diffusivities, or, in case of the heat conduction, as effective heat conductivities of the material.

2020 ◽  
pp. 1-24
Author(s):  
Zoltán I. Búzás

Abstract Formal racial equality is a key aspect of the current Liberal International Order (LIO). It is subject to two main challenges: resurgent racial nationalism and substantive racial inequality. Combining work in International Relations with interdisciplinary studies on race, I submit that these challenges are the latest iteration of struggles between two transnational coalitions over the LIO's central racial provisions, which I call racial diversity regimes (RDRs). The traditional coalition has historically favored RDRs based on racial inequality and racial nationalism. The transformative coalition has favored RDRs based on racial equality and nonracial nationalism. I illustrate the argument by tracing the development of the liberal order's RDR as a function of intercoalitional struggles from one based on racial nationalism and inequality in 1919 to the current regime based on nonracial nationalism and limited equality. Today, racial nationalists belong to the traditional coalition and critics of racial inequality are part of the transformative coalition. The stakes of their struggles are high because they will determine whether we will live in a more racist or a more antiracist world. This article articulates a comprehensive framework that places race at the heart of the liberal order, offers the novel concept of “embedded racism” to capture how sovereignty shields domestic racism from foreign interference, and proposes an agenda for mainstream International Relations that takes race seriously.


Author(s):  
Rieke Hansen ◽  
Martina van Lierop ◽  
Werner Rolf ◽  
Damjana Gantar ◽  
Ina Šuklje Erjavec ◽  
...  

AbstractConcepts such as green infrastructure, nature-based solutions, and ecosystem services gained popularity in recent discourses on urban planning. Despite their recognition as innovative concepts, all of them share a degree of ambiguity. Fuzziness can be a weakness but also an opportunity to shape novel concepts together with the stakeholders that are supposed to implement them in the planning practice. The paper traces concept development processes of green infrastructure through transdisciplinary knowledge exchange in three different projects, a European and a national research project and a local city-regional project as part of an EU regional cooperation project. In all projects, the green infrastructure concept evolved in different stages. Stakeholder involvement during these stages span from consultation to co-creation. The cases reveal two different approaches: concepts that are developed “for planning practice” might be based on a plethora of insight via consultation, while those “with planning practice” foster co-creation and might result in high acceptance among the involved stakeholders. Depending on the purpose of the novel concept, each approach can be beneficial and result in practice-related and operational products, such as guidance documents or planning strategies. However, the cases also show that in any new context an exchange about fuzzy concepts is not only needed but also a chance to stimulate cooperation and joint understanding about urban challenges and how to address them.


Blood ◽  
2011 ◽  
Vol 118 (23) ◽  
pp. 6107-6114 ◽  
Author(s):  
Jelle de Wit ◽  
Yuri Souwer ◽  
Astrid J. van Beelen ◽  
Rosa de Groot ◽  
Femke J. M. Muller ◽  
...  

Abstract IL-17–producing CD4+ T helper (Th17) cells are important for immunity against extracellular pathogens and in autoimmune diseases. The factors that drive Th17 development in human remain a matter of debate. Here we show that, compared with classic CD28 costimulation, alternative costimulation via the CD5 or CD6 lymphocyte receptors forms a superior pathway for human Th17-priming. In the presence of the Th17-promoting cytokines IL-1β, IL-6, IL-23, and transforming growth factor-β (TGF-β), CD5 costimulation induces more Th17 cells that produce higher amounts of IL-17, which is preceded by prolonged activation of signal transducer and activator of transcription 3 (STAT3), a key regulator in Th17 differentiation, and enhanced levels of the IL-17–associated transcription factor retinoid-related orphan receptor-γt (ROR-γt). Strikingly, these Th17-promoting signals critically depend on CD5-induced elevation of IL-23 receptor (IL-23R) expression. The present data favor the novel concept that alternative costimulation via CD5, rather than classic costimulation via CD28, primes naive T cells for stable Th17 development through promoting the expression of IL-23R.


Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Alberto Pascual-García

AbstractIn this comment, we analyse the conceptual framework proposed by Aguirre de Cárcer (Microbiome 7:142, 2019), introducing the novel concept of Phylogenetic Core Groups (PCGs). This notion aims to complement the traditional classification in operational taxonomic units (OTUs), widely used in microbial ecology, to provide a more intrinsic taxonomical classification which avoids the use of pre-determined thresholds. However, to introduce this concept, the author frames his proposal in a wider theoretical framework based on a conceptualization of selection that we argue is a tautology. This blurs the subsequent formulation of an assembly principle for microbial communities, favouring that some contradictory examples introduced to support the framework appear aligned in their conclusions. And more importantly, under this framework and its derived methodology, it is not possible to infer PCGs from data in a consistent way. We reanalyse the proposal to identify its logical and methodological flaws and, through the analysis of synthetic scenarios, we propose a number of methodological refinements to contribute towards the determination of PCGs in a consistent way. We hope our analysis will promote the exploration of PCGs as a potentially valuable tool, helping to bridge the gap between environmental conditions and community composition in microbial ecology.


Author(s):  
Amir A. Kharazi ◽  
Pezhman Akbari ◽  
Norbert Mu¨ller

A number of technical challenges have often hindered the economical application of refrigeration cycles using water (R718) as refrigerant. The novel concept of condensing wave rotor provides a solution for performance improvement of R718 refrigeration cycles. The wave rotor implementation can increase efficiency and reduce the size and cost of R718 units. The condensing wave rotor employs pressurized water to pressurize, desuperheat, and condense the refrigerant vapor — all in one dynamic process. In this study, the underlying phenomena of flash evaporation, shock wave compression, desuperheating, and condensation inside the wave rotor channels are described in a wave and phase-change diagram. A computer program based on a thermodynamic model is generated to evaluate the performance of R718 baseline and wave-rotor-enhanced cycles. The detailed thermodynamic approach for the baseline and the modified cycles is described. The effect of some key parameters on the performance enhancement is demonstrated as an aid for optimization. A generated performance map summarizes the findings.


2021 ◽  
Author(s):  
Hamzeh Asgharnezhad ◽  
Afshar Shamsi ◽  
Roohallah Alizadehsani ◽  
Abbas Khosravi ◽  
Saeid Nahavandi ◽  
...  

Abstract Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their predictive confidence. Quantifying uncertainties associated with DNN predictions is a prerequisite for their trusted deployment in medical settings. Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced. Through comprehensive experiments, it is shown that networks pertained on CXR images outperform networks pretrained on natural image datasets such as ImageNet. Qualitatively and quantitatively evaluations also reveal that the predictive uncertainty estimates are statistically higher for erroneous predictions than correct predictions. Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates. We also observe that ensemble methods more reliably capture uncertainties during the inference. DNN-based solutions for COVID-19 detection have been mainly proposed without any principled mechanism for risk mitigation. Previous studies have mainly focused on on generating single-valued predictions using pretrained DNNs. In this paper, we comprehensively apply and comparatively evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced for the first time. Using these new uncertainty performance metrics, we quantitatively demonstrate where and when we could trust DNN predictions for COVID-19 detection from chest X-rays. It is important to note the proposed novel uncertainty evaluation metrics are generic and could be applied for evaluation of probabilistic forecasts in all classification problems.


Author(s):  
Perry Daneshgari ◽  
Heather Moore ◽  
Hisham Said

The same principles that have made other skilled-trade-based industries more efficient are being deployed in construction through Industrialization, which requires understanding skilled trade work and segregating/externalizing the work from the jobsite. The construction industry still relies heavily on skilled trades and their tacit knowledge, while most of the information available at the points of installation is not passed on. A significant increase of work externalization requires a measuring and tracking method that can: 1) tap into this tacit knowledge as the basis for work planning and control; and 2) understand, quantify, and minimize the manipulation effort done onsite for the prefabricated assemblies. As such, this paper presents a planning and control framework for industrialized construction operations that integrates information entropy and the novel concept of work manipulations to monitor and measure the expected performance outcomes, in a more sophisticated approach beyond measuring äóìhoursäó� and äóìquantitiesäó� of the work. The development of the proposed framework is based on the analysis of a set of case studies that illustrate the impact of information predictability manipulation strategies on construction prefabrication decisions.


Proceedings ◽  
2020 ◽  
Vol 64 (1) ◽  
pp. 22
Author(s):  
David Fassbender ◽  
Tatina Minav

For the longest time, valve-controlled, centralized hydraulic systems have been the state-of-the-art technology to actuate heavy-duty mobile machine (HDMM) implements. Due to the typically low energy efficiency of those systems, a high number of promising, more-efficient actuator concepts has been proposed by academia as well as industry over the last decades as potential replacements for valve control—e.g., independent metering, displacement control, different types of electro-hydraulic actuators (EHAs), electro-mechanic actuators, or hydraulic transformers. This paper takes a closer look on specific HDMM applications for these actuator concepts to figure out where which novel concept can be a better alternative to conventional actuator concepts, and where novel concepts might fail to improve. For this purpose, a novel evaluation algorithm for actuator–HDMM matches is developed based on problem aspects that can indicate an unsuitable actuator–HDMM match. To demonstrate the functionality of the match evaluation algorithm, four actuator concepts and four HDMM types are analyzed and rated in order to form 16 potential actuator–HDMM matches that can be evaluated by the novel algorithm. The four actuator concepts comprise a conventional valve-controlled concept and three different types of EHAs. The HDMM types are excavator, wheel loader, backhoe, and telehandler. Finally, the evaluation of the 16 matches results in 16 mismatch values, of which the lowest indicates the “perfect match”. Low mismatch values could be found in general for EHAs in combination with most HDMMs but also for a valve-controlled actuator concept in combination with a backhoe. Furthermore, an analysis of the concept limitations with suggestions for improvement is included.


2019 ◽  
Vol 5 ◽  
Author(s):  
Konstantinos Kotis

ARTIST is a research approach introducing novel methods for real-time multi-entity interaction between human and non-human entities, to create reusable and optimized Mixed Reality (MR) experiences with low-effort, towards a Shared MR Experiences Ecosystem (SMRE2). As a result, ARTIST delivers high quality MR experiences, facilitating the interaction between a variety of entities which interact in a virtual and symbiotic way within a mega, virtual and fully-experiential world. Specifically, ARTIST aims to develop novel methods for low-effort (code-free) implementation and deployment of open and reusable MR content, applications and tools, introducing the novel concept of an Experience as a Trajectory (EaaT). In addition, ARTIST will provide tools for the tracking, monitoring and analysis of user behaviour and their interaction with the environment and with other users, towards optimizing MR experiences by recommending their reconfiguration, dynamically (at run-time) or statically (at development time). Finally, it will provide tools for synthesizing experiences into new mega and still reconfigurable EaaTs, enhancing them at the same time using semantically integrated related data/information available in disparate and heterogeneous resources.


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