Robust Concept Research Articles

Chiral Amplification of Phosphoramidates of Amines and Amino Acids in Water.

The origin of biomolecular homochirality continues to be one of the most fascinating aspects of prebiotic chemistry. Various amplification strategies for chiral compounds to enhance a small chiral preference have been reported, but none of these involves phosphorylation, one of nature's essential chemical reactions. Here we present a simple and robust concept of phosphorylation‐based chiral amplification of amines and amino acids in water. By exploiting the difference in solubility of a racemic phosphoramidate and its enantiopure form, we achieved enantioenrichment in solution. Starting with near racemic, phenylethylamine‐based phosphoramidates, ee's of up to 95 % are reached in a single amplification step. Particularly noteworthy is the enantioenrichment of phosphorylated amino acids and their derivatives, which might point to a potential role of phosphorus en‐route to prebiotic homochirality.

Flexible Auto-Weighted Local-Coordinate Concept Factorization: A Robust Framework for Unsupervised Clustering

Concept Factorization (CF) and its variants may produce inaccurate representation and clustering results due to the sensitivity to noise, hard constraint on the reconstruction error, and pre-obtained approximate similarities. To improve the representation ability, a novel unsupervised Robust Flexible Auto-weighted Local-coordinate Concept Factorization (RFA-LCF) framework is proposed for clustering high-dimensional data. Specifically, RFA-LCF integrates the robust flexible CF by clean data space recovery, robust sparse local-coordinate coding, and adaptive weighting into a unified model. RFA-LCF improves the representations by enhancing the robustness of CF to noise and errors, providing a flexible constraint on the reconstruction error and optimizing the locality jointly. For robust learning, RFA-LCF clearly learns a sparse projection to recover the underlying clean data space, and then the flexible CF is performed in the projected feature space. RFA-LCF also uses a L2,1-norm based flexible residue to encode the mismatch between the recovered data and its reconstruction, and uses the robust sparse local-coordinate coding to represent data using a few nearby basis concepts. For auto-weighting, RFA-LCF jointly preserves the manifold structures in the basis concept space and new coordinate space in an adaptive manner by minimizing the reconstruction errors on clean data, anchor points and coordinates. By updating the local-coordinate preserving data, basis concepts and new coordinates alternately, the representation abilities can be potentially improved. Extensive results on public databases show that RFA-LCF delivers the state-of-the-art clustering results compared with other related methods.

Differentially private data release via statistical election to partition sequentially

Differential Privacy (DP) formalizes privacy in mathematical terms and provides a robust concept for privacy protection. DIfferentially Private Data Synthesis (DIPS) techniques produce and release synthetic individual-level data in the DP framework. One key challenge to develop DIPS methods is the preservation of the statistical utility of synthetic data, especially in high-dimensional settings. We propose a new DIPS approach, STatistical Election to Partition Sequentially (STEPS) that partitions data by attributes according to their importance ranks according to either a practical or statistical importance measure. STEPS aims to achieve better original information preservation for the attributes with higher importance ranks and produce thus more useful synthetic data overall. We present an algorithm to implement the STEPS procedure and employ the privacy budget composability to ensure the overall privacy cost is controlled at the pre-specified value. We apply the STEPS procedure to both simulated data and the 2000–2012 Current Population Survey youth voter data. The results suggest STEPS can better preserve the population-level information and the original information for some analyses compared to PrivBayes, a modified Uniform histogram approach, and the flat Laplace sanitizer.

Robust scenario-based concept for stochastic energy management of an energy hub contains intelligent parking lot considering convexity principle of CHP nonlinear model with triple operational zones

In this paper, an energy management system is taken into account to control some distributed energy resources spread into an entity. The included facilities are aggregated by an energy hub (EH) and also equipped by some control and communication in a smart environment. Through this system, the stakeholder can prepare energy operational planning in the form of energy markets. In this paper, a novel convexity principle is presented to face the nonlinearity of combined heat and power (CHP) unit model considering triple operational zones. Here, the energy hub acts as a price taker in the energy markets. Here, some stochastic parameters such as day-ahead market price, wind power output, and plug-in hybrid electric vehicles (PHEVs) entry and exit time and their battery characteristics are considered; therefore a robust scenario-based optimization strategy is proposed to deal with them. The robust optimization is employed by upper and lower bounds for market price uncertain parameter by historical behaviors and also is presented through confidence bounds. Also, to deal with the wind power uncertainty, the scenario-based method is performed by scenario generation based on historical wind data. To demonstrate the effectiveness of the proposed strategy, a real case study is investigated and some prominent results are provided. As obtained, the CHP unit can work actively in the winter day so that the 3rd operational zone will be active and also with increasing the percentage of PHEV units to 100 % within the EH in the summer day, the percentage of power sold to the network will be increased to 68.1 % compared with no vehicle situation.

One globalisation or many? Risk society in the age of the Anthropocene

My goal in this article is to reconsider current ideas of globalisation, and of the relations between nature and society, by looking at two theoretical programmes of the past four decades. I start by reconsidering Ulrich Beck’s theory of risk society and highlight some of its core strengths and weaknesses. I then revisit more recent debates on the Anthropocene and unpack some key dimensions. There, I contend that arguments on the Anthropocene allow us to develop a more robust concept of globalisation than those currently available: an idea of globalisation that is the inescapable condition of what humans are as a species. Finally, I offer some preliminary reflections on the new stage of globalisation that seems to have started with the Covid-19 pandemic.

Interpolation algorithm in designing of feed-forward robust precision control motion

Based on the structure and dynamic process of the ladder secondary double-sided linear induction motor (DSLIM) with asymmetry position of primary part of motor, the motor parameters may change with the secondary position, which directly cause the stability of electromagnetic thrust. It is difficult to meet the system control performances for designing of controller in the dynamic characteristics of the speed closed loop. This paper describes some solving algorithm by adopting the rotor field oriented control as the model matching strategy to achieve the smooth control of the electromagnetic thrust. The arrangement of model matching process is based on the Nevallina pick solution as linear interpolation method. Through the robust control concept and model matching control, the stability of the electromagnetic thrust during the motor step change process can be achieved. The simulation results verify the truth of the presented control strategies.

Theorising Digital Tools: Mutual Constitution of the Person and Digital in a Conceptual PlayWorld

The COVID-19 pandemic has led us to an unanticipated and challenging world. In educational settings, one of the ways to respond to this crisis has been the online delivery of content. One of the valid critiques of these online delivery models is the passive role of the participants. The challenge is we still know very little about how technology could support children’s active participation in their learning. This challenge exacerbates with children in early years and in their home setting, which is the focus of our research at Monash University’s Conceptual PlayLab. This paper reports on solving the theoretical problem of digital design that can create a relational space for children’s STEM concept formation. The paper argues that engagement with digital tools demands clear design principles that could support both robust concept formation and also development of learning motives in children. Drawing on Wartofsky’s work on artefacts and tool-use and (Fleer 2017a, 2019), conceptualisation of “digital coadjuvant”, we make a case that technology offers a transformative potential for children to imagine and explore together with their caregivers in the Conceptual PlayWorld. We have showed through a practice example on how person and digital technologies become mutually constituted in a pop-up Conceptual PlayWorld. The design principle highlighted in the paper argues for transcending the binary of digital and non-digital. The paper concludes that Conceptual PlayWorld offers a design model that uses digital tools to sustain and amplify children’s exploration in their imaginary play situation.

Integrated approach enabling robust and tolerance design in product concept development

Abstract Along with the ever-increasing customer demands, early consideration of variation in terms of robust design is important to avoid expensive iterations in the product development. However, existing methods are detached from the development process and can therefore only be applied at a late stage or only with comprehensive expert knowledge. Especially in the concept stage, where the geometry of a product is not yet defined and the optimisation potential is high, effective solution proposals for systematic consideration of variation are lacking. Therefore, this paper describes a new integrated approach facilitating robust and tolerance design in the concept stage. The novelty of the approach using ontologies and graph-based visualisation is the close linkage of product development and tolerance knowledge, which allows automation and helps to avoid time- and cost-intensive iteration loops. As a result, a robust and tolerance-compliant concept design, an initial qualitative tolerance specification and instructions for the further tolerancing process are already available at the end of the concept stage. The applicability and the benefits of the approach are illustrated by representative case studies and a user study allowing a critical comparison between the conventional, mostly subjective procedure and the presented approach.

Supramolecular Networks: Helical Networks of π‐Conjugated Rods – A Robust Design Concept for Bicontinuous Cubic Liquid Crystalline Phases with Achiral Ia3¯d and Chiral I23 Lattice (Adv. Funct. Mater. 45/2020)

In article number 2004353, Goran Ungar, Carsten Tschierske, and co-workers present a general design concept of bicontinuous cubic liquid crystals consisting of helical networks that are stable over a broad temperature range. Increasingly bulky substituents cause increasing helical twist between the three-chain 2,2′-bithiophene based molecular rods, resulting in a sequence of three distinct phases: two ranges of achiral double network (Ia 3 ¯ d) separated by a range of spontaneously chiral triple network (I23).

A single Gauss point continuum finite element formulation for gradient-extended damage at large deformations

Some years ago, a family of large deformation continuum finite elements based on reduced integration was investigated by Reese (2005), Schwarze and Reese (2011) and Frischkorn and Reese (2015). Many structural components with different kinds of elastic and inelastic material behavior were considered and these elements showed accurate results while being more efficient than similar three-dimensional formulations based on full integration. The objective of the present contribution is to extend the analysis to non-local damage and fracture. To this end, the incorporation of the gradient-extended damage plasticity model for large deformations of Brepols et al. (2020) into the framework of reduced integration-based continuum elements is presented. For the sake of brevity, the present work is restricted to solids with only one integration (Gauss) point in the center of the element. The weak form of the formulation, which is based on a two-field variational functional closely related to the enhanced-assumed strain (EAS) method is extended by the weak form of the micromorphic balance equation. The steps required in order to transform the extended formulation into a stable, robust and efficient single Gauss point concept are described in detail. Due to the analogy to fully-coupled thermomechanical problems, the derivation of a novel micromorphic hourglass stabilization is based on earlier contributions of the research group. Therein, the Taylor series expansion of all constitutively dependent quantities plays a crucial role. Representative numerical examples of quasi-brittle and ductile fracture reveal the accuracy and efficiency of the proposed approach. Besides the ability to deliver mesh-independent results, the framework is especially suitable for constrained situations in which conventional low-order finite elements suffer from well-known locking phenomena.

The Lexicographic Tolerable Robustness Concept for Uncertain Multi-Objective Optimization Problems: A Study on Water Resources Management

In this study, we introduce a robust solution concept for uncertain multi-objective optimization problems called the lexicographic tolerable robust solution. This approach is advantageous for the practical implementation of problems in which the solution should satisfy priority levels in the objective function and the worst performance vector of the solution obtained by the proposed concept is close to a reference point of the considered problem, within an acceptable tolerance threshold. Important properties of the solution sets of this introduced concept as well as an algorithm for finding such solutions are presented and discussed. We provide the implementation of the proposed lexicographic tolerable robust solution to improve understanding for practitioners by relying on the data of the water resources master plan for Serbia from Simonovic, 2009. Moreover, we are also concerned with the method of updating a desirable solution for fitting with the preferences when compromising of the multiple groups of decision makers is needed.

Time of PTV is ending, robust optimization comes next

Continuous improvements have been made in the way to prescribe, record and report dose distributions since the therapeutic use of ionizing radiations. The international commission for radiation units and measurement (ICRU) has provided a common language for physicians and physicists to plan and evaluate their treatments. The PTV concept has been used for more than two decades but is becoming obsolete as the CTV-to-PTV margin creates a static dose cloud that does not properly recapitulate all planning vs. delivery uncertainties. The robust optimization concept has recently emerged to overcome the limitations of the PTV concept. This concept is integrated in the inverse planning process and minimizes deviations to planned dose distribution through integration of uncertainties in the planning objectives. It appears critical to account for the uncertainties that are specific to protons and should be accounted for to better exploit the clinical potential of proton therapy. It may also improve treatment quality particularly in hypofractionated photon plans of mobile tumors and more widely to photon radiotherapy. However, in contrast to the PTV concept, a posteriori evaluation of plan quality, called robust evaluation, using error-based scenarios is still warranted. Robust optimization metrics are warranted. These metrics are necessary to compare PTV-based photon and robustly optimized proton plans in general and in model-based NTCP approaches. Assessment of computational demand and approximations of robust optimization algorithms along with metrics to evaluate plan quality are needed but a step further to better prescribe radiotherapy may has been achieved.

Helical Networks of π‐Conjugated Rods – A Robust Design Concept for Bicontinuous Cubic Liquid Crystalline Phases with Achiral Ia3¯d and Chiral I23 Lattice

AbstractBicontinuous cubic liquid crystalline phases of π‐conjugated molecules, representing self‐assembled 3D‐ordered interpenetrating networks with cubic symmetry, are receiving increasing attention due to their capacity for charge transport in all three dimensions and their inherent spontaneous helicity. Herein, a robust general design concept for creating bicontinuous cubic phases is reported. It is based on a nonsymmetric‐substituted π‐conjugated 5,5′‐diphenyl‐2,2′‐bithiophene platform with one end containing three out‐fanning flexible chains and with a range of substituents at the other end (the apex). The cubic phases are stable over broad temperature ranges, often down to ambient temperature, and tolerate a wide range of apex substitution patterns, allowing structural diversity and tailoring of the cubic phase type and application‐relevant properties. With an increasing number and size of apex substituents, a sequence of three different modes of cubic self‐assembly is observed, following an increasing helical twist. Thus, two ranges of the achiral double network Iad phase range can be distinguished, a long pitch and a short pitch, with the chiral triple network I23 cubic phase in the intermediate pitch range. The findings provide a new prospect for the directed design of cubic phase‐forming functional materials based on spontaneously formed helical network liquid crystals with tunable application specific properties.

Energy and resources cooperation for greenhouse gases emissions reduction of industrial sector

Energy and resources cooperation has a great potential of reducing greenhouse gases (GHG) emissions of companies, especially in industrial and business parks where facilities are located in geographical proximity. Such cooperation could cut emissions without significant impact on profit, and in some cases, may even reduce costs by decreasing waste generation and improving energy efficiency. This paper combines similar themes of industrial symbiosis, sharing economy and circular economy to formulate a single robust concept of energy and resources cooperation. A framework and methodology for mass implementation of energy and resources cooperation is proposed by integrating disparate fields of industrial ecology, business studies and industrial investments. Furthermore, an approach of enhancing such cooperation is proposed which involves an establishment of a specialized Cooperation Development and Management Company. Finally, research agenda is set out to capitalise the developments of industry 4.0 and peer to peer sharing for energy and resources cooperation.

Joint Label Prediction Based Semi-Supervised Adaptive Concept Factorization for Robust Data Representation

Constrained Concept Factorization (CCF) yields the enhanced representation ability over CF by incorporating label information as additional constraints, but it cannot classify and group unlabeled data appropriately. Minimizing the difference between the original data and its reconstruction directly can enable CCF to model a small noisy perturbation, but is not robust to gross sparse errors. Besides, CCF cannot preserve the manifold structures in new representation space explicitly, especially in an adaptive manner. In this paper, we propose a joint label prediction based Robust Semi-Supervised Adaptive Concept Factorization (RS2ACF) framework. To obtain robust representation, RS2ACF relaxes the factorization to make it simultaneously stable to small entrywise noise and robust to sparse errors. To enrich prior knowledge to enhance the discrimination, RS2ACF clearly uses class information of labeled data and more importantly propagates it to unlabeled data by jointly learning an explicit label indicator for unlabeled data. By the label indicator, RS2ACF can ensure the unlabeled data of the same predicted label to be mapped into the same class in feature space. Besides, RS2ACF incorporates the joint neighborhood reconstruction error over the new representations and predicted labels of both labeled and unlabeled data, so the manifold structures can be preserved explicitly and adaptively in the representation space and label space at the same time. Owing to the adaptive manner, the tricky process of determining the neighborhood size or kernel width can be avoided. Extensive results on public databases verify that our RS2ACF can deliver state-of-the-art data representation, compared with other related methods.

A user preference modelling method for the assessment of visual complexity in building façade

PurposeThis study aims to provide a method to assess the perceptual impact of the visual complexity of building façades.Design/methodology/approachThe research identifies the number of design elements and the variation in their position and colour as variables of visual complexity. It introduces the concepts of vertices and corners as atomic indicators on which the measurement of these variables is built. It measures visual complexity and its variables in images of building façades and analyses their relationships with participants' reactions. It reports on the effect of visual complexity on preferences, the adequacy of different methods in measuring visual complexity and the perceptual impact of each of its variables.FindingsThe research demonstrates that visual complexity can be assessed through the measure of its variables and their statistical mapping to users' preferences.Originality/valueThe manuscript provides the foundation for a planning/assessment tool for the visual control of the built environment using computer systems based on the preferences of residents through the examination of the relationship between the users and their environment. It creates a paradigm, which introduces a robust concept in the visual analysis of urban design.

Revisiting groundwater chemical processes in a rapidly urbanizing basin

Monterrey procures about 40% of its water supply from groundwater resources, considering several aquifers below and nearby. This city meets semiarid climate conditions with highly variable precipitation rates. The increasing demand for groundwater during drought conditions can deteriorate water quality, raising the energy consumption and costs of lifting, moving, distributing, and treating water. Thus, the major ion content of this resource was assessed, analyzing changes across the Monterrey Basin during the last 11 years to obtain a more robust geochemical concept of the study area. Waters from three wellfields (Buenos Aires, Santiago, Mina) with low mineralization were classified as recharge waters. Waters circulating across evaporite–silicate–carbonate sediments of the Monterrey Basin with gradually increasing salinity were classified as transition zone waters (Metropolitan area) and discharge zone waters (north and northeast of the city). According to this, it can be concluded that groundwater from the different Monterrey sources exhibits high-quality mineralized water, considering the analyzed parameters. Nevertheless, further attention must be paid on nitrate and sulfate occurrence and evolution in the transition and discharge zones.

Circular literacy. A knowledge-based approach to the circular economy

ABSTRACTThis paper applies a knowledge-based approach to study the role of circular economy (CE) for sustainable development. An analysis of publications from practice-oriented CE advocates is deployed to study the types of knowledge actors foster when they pursue the transition towards a CE. With the proposed term ‘circular literacy’ (CL), an analytical framework is provided to differentiate between different types of knowledge relevant for a transition towards the CE: system, target, and transformation knowledge. The main emphasis is on identifying knowledge-related prerequisites that prevent or stimulate the transformative potential of CE thinking and practices for sustainable development. The analysis reveals how the CL in the sample is confined by a narrow economic vision of the CE, lacking a reflection of political and sociocultural aspects that are needed to be addressed in future research to gain a robust concept of a CE-driven systemic transition towards sustainability.

Robust (Bayesian) Persuasion

We propose a robust solution concept for Bayesian persuasion that accounts for the Sender's ambiguity over (i) the exogenous sources of information the Receivers may learn from, and (ii) the way the Receivers play (when multiple strategy profiles are consistent with the assumed solution concept and the available information). The Sender proceeds in two steps. First, she identifies all information structures that yield the largest payoff in the worst-case scenario, i.e., when Nature provides information and coordinates the Receivers' play to minimize the Sender's payoff. Second, she picks an information structure that, in case Nature and the Receivers play favorably to her, maximizes her expected payoff over all information structures that are worst-case optimal. We characterize properties of robust solutions, identify conditions under which robustness requires separation of certain states, and qualify in what sense robustness calls for more information disclosure than standard Bayesian persuasion. Finally, we discuss how some of the results in the Bayesian persuasion literature change once robustness is accounted for.

Fatigue life estimation for the robust design of truck radiator

The growing truck industry, results in larger fleet of trucks serving various transportation needs of the society. On the flip side, the increased sale of vehicles causes environmental pollution affecting the fragile ozone layer. Government and regulatory bodies across the globe enforced tough emission measures to curb the menace. The tougher emission norms translate into design challenges for the truck OEM’s to design lightweight and complex radiator to meet higher operating pressure and durability cycle targets within a tight packaging vehicle space. Robust radiator design is the need of the hour to address the design challenge. A robust design approach coupled with traditional nominal analysis is proposed to determine robust radiator design insensitive to variations. Fatigue Assessment also included in the approach. Nominal design analysis shows that nominal deformation and stress response has 49% reliability and 51% unreliability, which indicates that nominal design does not factor in the variations occurring due to assembly, raw material and manufacturing process. The proposed robust approach identifies robust radiator designs less sensitive to uncertainty and shows 95% reliability. Robust design has 5x higher pressure cycle life as compared against the nominal design. The robust design concept having higher reliability and less sensitive to variations are identified. The approach highlights that robust design has higher pressure cycle durability as compared against the nominal radiator design. Better fatigue life estimation is obtained by using pressure cycle test results.