Generic Uncertainty Research Articles

Neural Representation of Valenced and Generic Probability and Uncertainty.

Representing the probability and uncertainty of outcomes facilitates adaptive behavior by allowing organisms to prepare in advance and devote attention to relevant events. Probability and uncertainty are often studied only for valenced (appetitive or aversive) outcomes, raising the question of whether the identified neural machinery also processes the probability and uncertainty of motivationally neutral outcomes. Here, we aimed to dissociate valenced from valence-independent (i.e., generic) probability (p; maximum at p = 1) and uncertainty (maximum at p = 0.5) signals using human neuroimaging. In a Pavlovian task (n = 41; 19 females), different cues predicted appetitive, aversive, or neutral liquids with different probabilities (p = 0, p = 0.5, p = 1). Cue-elicited motor responses accelerated, and pupil sizes increased primarily for cues that predicted valenced liquids with higher probability. For neutral liquids, uncertainty rather than probability tended to accelerate cue-induced responding and decrease pupil size. At the neural level, generic uncertainty signals were limited to the occipital cortex, while generic probability also activated the anterior ventromedial prefrontal cortex. These generic probability and uncertainty signals contrasted with cue-induced responses that only encoded the probability and uncertainty of valenced liquids in medial prefrontal, insular, and occipital cortices. Our findings show a behavioral and neural dissociation of generic and valenced signals. Thus, some parts of the brain keep track of motivational charge while others do not, highlighting the need and usefulness of characterizing the exact nature of learned representations.

A new genus of scutigerid centipede from southern South America with the description of two new species and an updated molecular phylogeny of the myriapod order Scutigeromorpha (Myriapoda: Chilopoda).

Scutigeromorph centipedes are conspicuous, yet often ignored myriapods for which little work has been conducted in southern South America. After examining recent and museum collections from Chile and Argentina, two new species of generic uncertainty were identified. A new genus of scutigerid centipede, Edgethreua , is therefore described with two new species, E. chilensis from Central Chile (type species of the genus) and E. goloboffi from Argentinian Patagonia. The new genus is characterised by the presence of scattered setiform bristles with short paired spines and the absence of simple spinulae and spines on all stomatotergites, the presence of a single spine-bristle in the prefemur of the second maxilla, a patch of cuticular ridges and pores surrounding the sensilla of the proximal labral portion of the epipharynx, the morphology of the sensilla of the distal patch of the hypopharynx and the morphology of the female gonopods. A phylogenetic analysis of the new species using two nuclear ribosomal RNA genes (18S and 28S rRNA), two mitochondrial ribosomal RNA genes (12S and 16S rRNA) and the mitochondrial protein-encoding gene cytochrome c oxidase subunit I show that the new genus does not cluster with any other described genus of scutigeromorph represented in molecular phylogenies. The data indicate that the new genus is probably sister group to a clade including the genera Lassophora , Ballonema and the subfamily Thereuoneminae, although one analysis suggests a position as sister group to Scutigerinae. ZooBank: urn:lsid:zoobank.org:pub:A4D453F3-9031-4E21-84C7-87F16C07AD51.

Ambiguity-Aware Multi-Object Pose Optimization for Visually-Assisted Robot Manipulation

6D object pose estimation aims to infer the relative pose between the object and the camera using a single image or multiple images. Most works have focused on predicting the object pose without associated uncertainty under occlusion and structural ambiguity (symmetricity). However, these works demand prior information about shape attributes, and this condition is hardly satisfied in reality; even asymmetric objects may be symmetric under the viewpoint change. In addition, acquiring and fusing diverse sensor data is challenging when extending them to robotics applications. Tackling these limitations, we present an ambiguity-aware 6D object pose estimation network, PrimA6D++, as a generic uncertainty prediction method. The major challenges in pose estimation, such as occlusion and symmetry, can be handled in a generic manner based on the measured ambiguity of the prediction. Specifically, we devise a network to reconstruct the three rotation axis primitive images of a target object and predict the underlying uncertainty along each primitive axis. Leveraging the estimated uncertainty, we then optimize multi-object poses using visual measurements and camera poses by treating it as an object SLAM problem. The proposed method shows a significant performance improvement in T-LESS and YCB-Video datasets. We further demonstrate real-time scene recognition capability for visually-assisted robot manipulation.

Milanovicella? canadillana sp. nov., an Upper Cretaceous supposedly calcitic Dasycladale (green algae) from the middle Santonian–lower Campanian of northeastern Spain

A new dasycladalean green alga is described as Milanovicella? canadillana from the Upper Cretaceous (middle Santonian–lower Campanian) of northeastern Spain. It occurs in foram-algal wackestones of the La Cañadilla Formation ascribed to a shallow marine (hyposaline?) to coastal environment. The associated microfauna is dominated by miliolids. The generic uncertainty of the taxon displaying multiple, often double verticils (= excluding Clypeina) refers to its unknown starting point with respect to the main axis and the overall thallus morphology. The calcified skeleton of M.? canadillana appears to consist of yellowish fibrous calcite as noted within some genera (e.g., Salpingoporella, Clypeina) and a handful of species discontinuously reported from the Mesozoic and Paleogene dasycladale record. The new taxon expands the diversity of calcareous algae during the Santonian – Campanian interval, that has previously been regarded as comparatively low.

Generic Uncertainty Parameter Analysis and Optimization of Series–Series Wireless Power Transfer System for Robust Controller Design

In a typical wireless power transfer (WPT) system, the load, the mutual inductance, and the required tuning frequency can vary in a particular range. Variation of each parameter can substantially impact the dynamic characteristics of the system. Thus, they can be considered as sources of uncertainty in the system. To address this, robust control methods such as μ-synthesis are developed to deal with possible system uncertainties. This article first undertakes the generic dynamic analysis of the series–series WPT compensation network for two modes of operation, i.e., constant output voltage (COV) mode and constant output current (COC) mode, in the presence of three aforementioned uncertainty sources. Subsequently, the frequency detuning as a function of the compensation capacitor variation is explored and broadened as a technique to obtain the optimized compensation capacitor value that can lead to a plant with minimized dynamic deviations from its nominal system in the operating range between COC and COV modes. As such, this approach offers a design procedure for a least conservative robust controller, which can significantly improve the system performance. The optimized structure and the corresponding designed μ-synthesis controller are comprehensively elaborated. The theoretical achievements and experimental results show superior dynamic performance of the optimized structure and the corresponding designed controller in the presence of three uncertainty sources compared to the COC and COV modes of operation.

Эмблематика и исцеление от меланхолии в «Анатомии меланхолии» Р. Бёртона

The article analyzes emblematic discourse in Robert Burton’s The Anatomy of Melancholy, offering an extended view of the emblematics that organizes both the structure and the narrative of the book and is anticipated by the emblematic frontispiece. The article examines the book’s intricate structure in its connection with the generic uncertainty of the text. The singular vs universal dualism forms the book’s underpinning structure that implies emblematic and dialectic intentions of The Anatomy of Melancholy. The article further analyzes the emblematic frontispiece, revealing consistently explicated emblematic structures that emphasize the antithesis of “duplicity” vs “singularity” implicit in the book’s multi-level structure. Analysis further demonstrates the book’s continuity with cento- and florilegia traditions, also epitomized in the emblematic method. The essay argues that Burton was using discursive emblems and the emblematic discourse to establish his status as an artifex, which helps him avoid melancholy himself and encourage his reader to struggle with it. The article postulates that the emblematic frontispiece embodies the dialectic of “duplicity” and “singularity” and solves it by enabling the emblematic mechanism of reading of the book through the emblematic lenses, uniting the Word and the Image: it is what Burton eventually offers both himself and his reader to cure melancholy.

Pseudoactinoporella Conrad 1970 (Family Bornetellaceae) revisited: A Lower Cretaceous corticated and capitulum-shaped, stalked Tethyan Dasycladale

Based on material from the area of Rafsanjan, Central Iran (P.? iranica Bucur et al.), and southeastern France (type-species P. fragilis Conrad), the genus Pseudoactinoporella Conrad is revisedwith respect to thallusmorphology and suprageneric classification. Reported as possessing a cylindrical or presumably club-shaped thallus, Pseudoactinoporella was assigned to the tribe Salpingoporellinae. In fact, P.? iranica represents a species displaying a capitulum-shaped, stalked thallus whose original description refered to the stalk only. The stalk of P.? iranica shows a spinose aspect due to individualized laterals and is well calcified. The “head” (capitulum) only preserves a thin wall displaying a pattern of cup-like depressions each with a central pore communicating with the fully cemented interior and interpreted as a cortex. P. fragilis is typically presented by trumpet-shaped fragments belonging to the stalk and the transition to the unpreserved (eroded? uncalcified?) “head”. For both species, a goniosporate reproduction type (= ampullae disposed laterally along the ramifications) is assumed herein. Due to these characteristics, it appears reasonable to leave apart the generic uncertainty of P. iranica as expressed in the original description. Consequently, Pseudoactinoporella is removed from the Salpingoporellinae and assigned to the family Bornetellaceae and the tribe Bornetelleae.

CONSIDERATION OF CONTRACTUAL RISKS ASSOCIATED WITH COASTAL AND MARITIME ENGINEERING WORKS

Coastal and maritime construction projects are fraught with risks associated with working in or around the sea. Common standard contracts such as those within the FIDIC Red Book do not adequately address the peculiarities associated with this unique environment. This paper will document the major areas of generic contractual risk and uncertainty with regard to coastal and maritime projects through review of literature, case law and other published disputes, as well as personal experience. Through identification and comparison of both the risks associated with these projects and the vulnerability within the standard FIDIC language, recommendations will be made for particular conditions to improve contract wording.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/1BkXEoaZZow

Silicon Isotopes in an EMIC's Ocean: Sensitivity to Runoff, Iron Supply, and Climate

AbstractThe isotopic composition of Si in biogenic silica (BSi), such as opal buried in the oceans' sediments, has changed over time. Paleorecords suggest that the isotopic composition, described in terms of δ30Si, was generally much lower during glacial times than today. There is consensus that this variability is attributable to differing environmental conditions at the respective time of BSi production and sedimentation. The detailed links between environmental conditions and the isotopic composition of BSi in the sediments remain, however, poorly constrained. In this study, we explore the effects of a suite of offset boundary conditions during the Last Glacial Maximum (LGM) on the isotopic composition of BSi archived in sediments in an Earth System Model of intermediate complexity (EMIC). Our model results suggest that a change in the isotopic composition of Si supply to the glacial ocean is sufficient to explain the observed overall low(er) glacial δ30Si in BSi. All other processes explored trigger model responses of either wrong sign or magnitude or are inconsistent with a recent estimate of bottom water oxygenation in the Atlantic Sector of the Southern Ocean. Caveats, mainly associated with generic uncertainties in today's pelagic biogeochemical modules, remain.

Uncertainty study on thermal and energy performances of a deterministic parameters based optimal aerogel glazing system using machine-learning method

Uncertainty and sensitivity analyses of deterministic parameters based optimal aerogel glazing system are necessary due to multi-dimensional uncertainties in the real working condition, whereas thermal and energy performances of aerogel glazing system, in the academia, are normally characterized by deterministic parameters. In this study, a generic uncertainty quantification methodology was proposed using the two-dimensional Markov Chain Monte Carlo to quantify both aleatory and epistemic uncertainties of scenario parameters in the aerogel glazing system. A surrogate model, trained by mathematical heat and optical models using the machine-learning based data-driven method, was developed to predict the thermal and energy performances under multi-level scenario uncertainties. Results showed that, the developed surrogate model is efficient to deal with computational complexity of sophisticated light and heat transfer processes. When considering scenario uncertainties, the annual value of heat flux is reduced from 237.2 to 185.3 kWh/(m2.a) by 21.9%, and the annual value of total heat gain is reduced from 267.2 to 209.5 kWh/m2.a by 21.6%. This study proposes a generic methodology for multi-dimensional uncertainties’ quantification and a surrogate model for thousands of cases-based uncertainty analysis. Approaches for the stochastic uncertainty analysis on aerogel glazing system were presented, which can promote the optimal design in buildings.

Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters’ uncertainties

The uncertainty and sensitivity analyses for multivariables of the optimal system based on deterministic parameters are necessary, as multivariables are full of uncertainties in the real operation. However, the generic methodology for multi-dimensional uncertainties quantification is rare, and the energy performance simulation is normally at high computational cost, especially considering a huge amount of parameters’ uncertainties. In this study, the on-site renewable electricity generation of an optimal hybrid renewable system based on deterministic parameters, was investigated, under high-level parameters’ uncertainties. A generic uncertainty quantification methodology was proposed using the two-dimensional Markov Chain Monte Carlo to quantify multi-dimensional uncertainties. A machine-learning based data-driven model, using the supervised machine learning with high computational efficiency, was developed to predict the on-site renewable electricity generation, and thereafter used for the uncertainty and sensitivity analyses. Compared with the deterministic scenario parameters, the cases with the scenario uncertainties can increase the peak power and the total amount of the on-site renewable electricity generation. This study proposes a novel generic uncertainty quantification methodology, together with a machine-learning based data-driven model for conducting the uncertainty analysis of an optimal renewable system based on deterministic parameters, which are important for the promotion of renewable and sustainable buildings.

“I wot not by what power”: Fairies, Predestination, and Genre in A Midsummer Night’s Dream

L’aveu par Demetrius qu’il ignore quel pouvoir l’a à nouveau poussé vers Helena n’est que l’affirmation la plus frappante du manque de liberté qui caractérise les personnages de A Midsummer Night’s Dream . La comédie désigne toute une matrice d’agents invisibles comme étant implicitement au service d’une doctrine calviniste de l’élection providentielle. L’incertitude générique inhérente à la « joie tragique » de la pièce peut se lire comme analogue à l’anxiété épistémologique du croyant réformé vis à vis du salut, qui peut lui-même être ramené à une question de genre : dans le theatrum mundi imaginé par Calvin, nous ne savons pas si nous jouons dans une comédie de l’élection ou dans une tragédie de la réprobation. Shakespeare utilise la mémoire culturelle liée au monde des fées — comme il avait exploité celle du purgatoire dans Hamlet — pour exposer les lignes de partage entre théologie réformée et théologie traditionnelle. La pièce interroge ainsi l’association que font les réformés entre la croyance aux fées et les superstitions papistes rejetées et suggère que les fées peuvent offrir au public protestant une thérapie contre le doute concernant les voies impénétrables de la Providence.

Numerical Methods for First Order Uncertain Stochastic Differential Equations

Uncertain stochastic calculus is a relatively new sub discipline of mathematics. This branch of mathematical sciences seeks to develop models that capture aleatory and epistemic features of generic uncertainty in dynamical systems. The growth of uncertain stochastic theory has given birth to a novel class of differential equations called uncertain stochastic differential equations (USDEs). Exact and analytic solutions to this family of differential equations are not always available. In such cases, numerical analysis provides a gateway to approximate solutions. This paper examines a Runge-Kutta method for solving USDEs. Before examining and applying the Runge-Kutta method, the paper states and proves the existence and uniqueness theorem. The Runge-Kutta method is then applied to solve an American call option pricing problem. This numerical algorithm proves to be effective and efficient because it produces almost the same results as compared to Chen's analytic formula and the classical Black-Scholes model.

Formless form, or the return of form? Prose poetry in practice and theory

Any study of prose poetry almost inevitably invokes the problem of genre. That is, generic uncertainty will always be of interest in a form that crosses a supposed boundary between prose and poetry and brings into play attempts at sharp demarcations and taxonomies with the aim of marking out territories of the poetic and the prosaic (and all stops between). In this paper, I would like to suggest that discussions of form in relation to prose poetry are symptomatic of larger struggles around form that have taken place at the level of critical practice. To do this, I suggest rather than a return of the prose poem form taken from a retro-fitting of poetic literary history, we might see the prose poem as a convergence with very short forms of prose fiction, and to look at the varying ways that these forms have been specified in their traditions. Secondly, I will look at the rise of ‘new formalism’ as a way of contextualising the critical background around which these arguments might be seen.

An Adaptive Memory Programming Framework for the Robust Capacitated Vehicle Routing Problem

We present an adaptive memory programming (AMP) metaheuristic to address the robust capacitated vehicle routing problem under demand uncertainty. Contrary to its deterministic counterpart, the robust formulation allows for uncertain customer demands, and the objective is to determine a minimum cost delivery plan that is feasible for all demand realizations within a prespecified uncertainty set. A crucial step in our heuristic is to verify the robust feasibility of a candidate route. For generic uncertainty sets, this step requires the solution of a convex optimization problem, which becomes computationally prohibitive for large instances. We present two classes of uncertainty sets for which route feasibility can be established much more efficiently. Although we discuss our implementation in the context of the AMP framework, our techniques readily extend to other metaheuristics. Computational studies on standard literature benchmarks with up to 483 customers and 38 vehicles demonstrate that the proposed approach is able to quickly provide high-quality solutions. In the process, we obtain new best solutions for a total of 123 benchmark instances.

Subliminal Speed Control in Air Traffic Management: Optimization and Simulation

We address the conflict resolution problem in air traffic management. It is widely acknowledged that air traffic controllers’ (ATCs) workload is related to the density of flights. ATCs’ main task is to ensure the safety of flights throughout their trips and consists of ensuring the respect of separation standards. Recently, the concept of subliminal control has emerged as a promising conflict resolution technique that could be used to reduce the impact of conflicts on ATCs’ workload. In this research, we present deterministic conflict resolution models adapted to subliminal speed control. The proposed models are formulated as nonlinear optimization problems that seek to minimize indicators related to ATCs’ workload (total conflict duration, total number of conflicts) using only minor speed adjustments. We introduce a linear approximation of the aircraft separation equations to implement the obtained mixed integer programs on a continental size air traffic network. Specifically, we develop a simulation framework aiming at reproducing realistic navigation conditions and evaluate the robustness of our conflict resolution models using a generic uncertainty model. We show that the impact of conflicts on ATCs’ workload can be significantly reduced using only limited resources, i.e., a narrow speed modulation range, even in the presence of perturbations. Further, we demonstrate that a significant share of the potential conflicts can be resolved without inducing important delays to flights. Finally, we report that our model does not require extensive computational resources as most instances can be solved to global optimality in a few seconds.

Editorial: A complicated post-documentary era

SINCE early in the first decade of this century, the concept of documentary—never beyond contestation—has entered into a state of generic uncertainty. Reflecting on these developments, John Corner, in an influential article, dubbed the current context of production as ‘Post-documentary’ (Corner, 2002). In his view, the documentary tradition has always encompassed a range of approaches: 1. Documentary as social commentary seeking to inform audiences as citizens rather than consumers. 2. Documentary as Investigative Reporting, once the most extensive use of documentary methods on television. 3. Documentary as Radical Interrogation and Agit-Prop as found in the practices of independent cinema. 4. Documentary as popular ‘factual’ entertainment driven by ratings and box office.

A Unified Electromagnetic Inverse Problem Algorithm for the Identification of the Magnetic Material Characteristics of Electromagnetic Devices Including Uncertainty Analysis: A Review and Application

Magnetic properties of the electromagnetic devices core materials are reconstructed by solving a coupled experimental-numerical electromagnetic inverse problem. However, the measurement noise as well as uncertainties of the forward model parameters and structure may result in dramatic recovery errors in the recovered values of the material parameters. In this paper, we review the use of the electromagnetic inverse problem for the identification of the magnetic material characteristics. The inverse algorithm is combined with a generic stochastic uncertainty analysis for a priori qualitative error estimation, and a quantitative error reduction. The complete inverse methodology is applied onto the identification of the magnetizing B-H curve of the magnetic material of a commercial asynchronous machine. Both numerical and experimental results validate the inverse approach, showing a good capability for magnetic material identification in electromagnetic devices. The proposed technique is general and can be applied into a wide range of applications in electromagnetic community.

A General Framework for Uncertainty Propagation Based on Point Estimate Methods

A general framework to approach the challenge of uncertainty propagation in model based prognostics is presented in this work. It is shown how the so-called Point Estimate Methods (PEMs) are ideally suited for this purpose because of the following reasons: 1) A credible propagation and representation of Gaussian (normally distributed) uncertainty can be done with a minimum of computational effort for non-linear applications. 2) Also non-Gaussian uncertainties can be propagated by evaluating suitable transfer functions inherently. 3) Confidence intervals of simulation results can be derived which do not have to be symmetrically distributed around the mean value by applying PEM in conjunction with the Cornish-Fisher expansion. 4) Moreover, the entire probability function of simulation results can be reconstructed efficiently by the proposed framework. The joint evaluation of PEM with the Polynomial Chaos expansion methodology is likely to provide good approximation results. Thus, non-Gaussian probability density functions can be derived as well. 5) The presented framework of uncertainty propagation is derivativefree, i.e. even non-smooth (non-differentiable) propagation problems can be tackled in principle. 6) Although the PEM is sample-based the overall method is deterministic. Computational results are reproducible which might be important to safety critical applications. - Consequently, the proposed approach may play an essential part in contributing to render the prognostics and health management into a more credible process. A given study of a generic uncertainty propagation problem supports this issue illustratively.

Practical Stabilization for Uncertain Pseudo-Linear and Pseudo-Quadratic MIMO Systems

In this paper the problem of practical stabilization for a significant class of MIMO uncertain pseudo-linear and pseudo-quadratic systems, with additional bounded nonlinearities and/or bounded disturbances, is considered. By using the concept of majorant system, via Lyapunov approach, new fundamental theorems, from which derive explicit formulas to design state feedback control laws, with a possible imperfect compensation of nonlinearities and disturbances, are stated. These results guarantee a specified convergence velocity of the linearized system of the majorant system and a desired steady-state output for generic uncertainties and/or generic bounded nonlinearities and/or bounded disturbances.