Series Of Mappings Research Articles

Mechanism of transition from subdiffusive transport to normal diffusion for passive tracers in a plane periodical flow induced by Gaussian noise

The known analytical solution describing a two-dimensional viscous flow with vortices under a driving force is generalized. It is shown that a periodic pattern of asymmetric vortices arises when the force amplitude exceeds a critical value. The transport of an ensemble of passive particles through the resulting structure has been studied. The envelope of each vortex contains a stagnation point, and the tracer motion along it without noise is infinitely long. It is shown that the macroscopic transport of an ensemble of tracers is extremely slow in the noise-free case. The latter leads to the mixing of the tracer ensemble. We study the peculiarities of such transport using a special flow model. Such a model has the form of a series of recurrence mappings. The recurrence mappings are constructed for the ensemble transport through a unit cell using the numerical solution of the Langevin equations in the presence of random particle displacements caused by molecular diffusion. The presence of diffusion allows particles to penetrate into the vortex, which leads to an additional slowing down of transport. The effect of noise on the variance of the tracer ensemble is investigated. It is shown that the growth of the standard deviation with time can be described by a power law. On an intermediate time scale, which grows exponentially long, as the noise strength tends to zero, a subdiffusive behavior is observed. The dependence of the subdiffusion exponent on the molecular diffusivity is obtained.

Clusterisation and Temporal Trends of Heat Flux by UAS Thermal Camera

Analysis of a series of thermal mappings obtained by UAS flights on quiescent volcanoes requires some special techniques to be performed. The main challenge is represented by the difficulty of separating hot and cold pixels in areas where their temperatures are quite similar. This task is indeed much simpler, for example, for lava flows where the temperature differences between the hot lava and the cold soil is rather big. This paper shows various software developed in order to perform this extraction and calculate the trends over time of both the average temperature and the heat flux from the soil. This prototypal implementation used thermal flights performed over a time span of a few years on an area in the Campi Flegrei caldera in southern Italy. Standard image manipulation techniques were used to segmentate and clusterise each thermal mapping in order to reduce the thermal anomalies to some sets of simpler features characterised by their fundamental parameters. The temporal trends of some physical parameters (temperature, heat flux, etc.) were extracted from these sets, and we found interesting results necessary for correlations and for ongoing research with other parameters.

Time Series of Land Cover Mappings Can Allow the Evaluation of Grassland Protection Actions Estimated by Sustainable Development Goal 15.1.2 Indicator: The Case of Murgia Alta Protected Area

Protected areas, or national parks, are established to preserve natural ecosystems; their effectiveness on the territory needs to be evaluated. We propose considering a time series of the SDG 15.1.2 indicator, “Proportion of important sites for terrestrial and freshwater biodiversity that are covered by protected areas, by ecosystem type”, to quantify the presence over time of grassland ecosystem in Murgia Alta (southern Italy), within the Natura 2000 and national park boundaries. Time series of remote sensing imagery, freely available, were considered for extracting, by Support Vector Machine classifiers, a time series of grassland cover mappings from 1990 to 2021. This latter was, then, used for computing a time series of the SDG 15.1.2 indicator. A high reduction (about 15,000 ha) of grassland presence from 1990 to 2004, the foundation years of the national park, followed by the increasing stability up to nowadays, was evaluated. Furthermore, grassland presence was evaluated in a 5-km buffer area, surrounding Natura 2000 boundary, revealing a continuous loss from 1990 up to now (about 500 ha) in the absence of protection actions. This study represents the first long-term analysis for the grassland ecosystem in Murgia Alta and the first effort to analyze a time series of the SDG 15.1.2 indicator. The findings can provide inputs to governments in monitoring the effectiveness of protection actions.

Reservoir Characterization and Productivity Forecast Based on Knowledge Interaction Neural Network

The reservoir characterization aims to provide the analysis and quantification of the injection-production relationship, which is the fundamental work for production management. The connectivity between injectors and producers is dominated by geological properties, especially permeability. However, the permeability parameters are very heterogenous in oil reservoirs, and expensive to collect by well logging. The commercial simulators enable to get accurate simulation but require sufficient geological properties and consume excessive computation resources. In contrast, the data-driven models (physical models and machine learning models) are developed on the observed dynamic data, such as the rate and pressure data of the injectors and producers, constructing the connectivity relationship and forecasting the productivity by a series of nonlinear mappings or the control of specific physical principles. While, due to the “black box” feature of machine learning approaches, and the constraints and assumptions of physical models, the data-driven methods often face the challenges of poor interpretability and generalizability and the limited application scopes. To solve these issues, integrating the physical principle of the waterflooding process (material balance equation) with an artificial neural network (ANN), a knowledge interaction neural network (KINN) is proposed. KINN consists of three transparent modules with explicit physical significance, and different modules are joined together via the material balance equation and work cooperatively to approximate the waterflooding process. In addition, a gate function is proposed to distinguish the dominant flowing channels from weak connecting ones by their sparsity, and thus the inter-well connectivity can be indicated directly by the model parameters. Combining the strong nonlinear mapping ability with the guidance of physical knowledge, the interpretability of KINN is fully enhanced, and the prediction accuracy on the well productivity is improved. The effectiveness of KINN is proved by comparing its performance with the canonical ANN, on the inter-well connectivity analysis and productivity forecast tasks of three synthetic reservoir experiments. Meanwhile, the robustness of KINN is revealed by the sensitivity analysis on measurement noises and wells shut-in cases.

From steady-state TASEP model with open boundaries to 1D Ising model at negative fugacity

We expose a series of exact mappings between particular cases of four statistical physics models: (i) equilibrium 1D lattice gas with nearest-neighbor repulsion, (ii) (1 + 1)D combinatorial heap of pieces, (iii) directed random walks on a half-plane, and (iv) 1D totally asymmetric simple exclusion process (TASEP). In particular, we show that generating function of a 1D steady-state TASEP with open boundaries can be interpreted as a quotient of partition functions of 1D hard-core lattice gases with one adsorbing lattice site and negative fugacity. This result is based on the combination of a representation of a steady-state TASEP configurations in terms of (1 + 1)D heaps of pieces (HP) and a theorem of X Viennot which projects the partition function of (1 + 1)D HP onto that of a single layer of pieces, which in this case is a 1D hard-core lattice gas.

Project Review: Kelly Kirshtner: In the Shoulder Season (Love Letter #2)

Book Review| September 01 2020 Project Review: Kelly Kirshtner: In the Shoulder Season (Love Letter #2) Kelly Kirshtner: In the Shoulder Season (Love Letter #2), Facebook and Instagram: March 25–April 23, 2020. Nathaniel Stern Nathaniel Stern Nathaniel Stern is an artist, writer, and teacher between the departments of Art+Design and Mechanical Engineering, and the Lubar Entrepreneurship Center at the University of Wisconsin-Milwaukee. He is the author of Interactive Art and Embodiment: The Implicit Body as Performance (2013) and Ecological Aesthetics: Artful Tactics for Humans, Nature, and Politics (2018). Search for other works by this author on: This Site PubMed Google Scholar Afterimage (2020) 47 (3): 91–98. https://doi.org/10.1525/aft.2020.473007 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Nathaniel Stern; Project Review: Kelly Kirshtner: In the Shoulder Season (Love Letter #2). Afterimage 1 September 2020; 47 (3): 91–98. doi: https://doi.org/10.1525/aft.2020.473007 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAfterimage Search It's a note. A love letter. Or, more precisely, Love Letters, where each “letter” is awkwardly inscribed in the landscape, piece by slow and semi-continuous piece. Most of us are familiar with the general concept—if not practice—of GPS (Global Positioning System) art. Using live software to track a walk, run, or bicycle ride, the vestigial traces of our embodied performance turned dis-embodied data make lines and curves to construct a pencil-like drawing on internet-based maps. The familiar red traveled paths on Google and Apple graphics or satellite images are planned in advance to become dogs or bicycles—or, as my first few image search results revealed: dinosaurs, Darth Vader, and stick figures. But Kelly Kirshtner's ongoing series of mappings, and this particular piece—In the Shoulder Season (Love Letter #2) (2020)—took more than the standard twists and turns expected of one such drawing out. “Shoulder season” is an explicit... You do not currently have access to this content.

Face Hallucination via Coarse-to-Fine Recursive Kernel Regression Structure

In recent years, patch-based face hallucination algorithms have attracted considerable interest due to their effectiveness. These approaches produce a high-resolution (HR) face image according to the corresponding low-resolution (LR) input by learning a reconstruction model from the given training image set. The critical problem in these algorithms is establishing the underlying relationship between LR and HR patch pairs. Most previous methods aim to denote each input LR patch by the linear combination of the training set in the LR space while utilizing the combination weights to reconstruct the target HR patch. However, this assumes that the same combination weights should be shared between various resolution spaces, which is truly difficult to satisfy because of the one-to-many mapping relation between LR and HR patches. In this paper, we directly train a series of adaptive kernel regression mappings for predicting the lost high-frequency information from the LR patch, which avoids dealing with the above difficult problem. During the training process, we first establish a local optimization function on each LR/HR training pair according to the geometric structure of neighboring patches. The objective of local optimization can be presented in two aspects: 1) ensure the reconstruction consistency between each LR patch and the corresponding HR patch and 2) preserve the intrinsic geometry between each HR training patch and its original neighbors after the reconstruction process. The local optimizations are finally incorporated as the global optimization for calculating the optimal kernel regression function. To better approximate the target HR patch, we further propose a recursive structure to compensate for the residual reconstruction error of high-frequency details by a series of regression mappings. The proposed method is rather fast yet very effective in producing HR face images. Experimental results show that the proposed approach achieves superior performance with reasonable computational time compared with the state-of-the-art methods.

Creative Dialogues Between University of Nicosia Fine Art Students and Strovolos III Residents: A Displaced Housing Estate in Nicosia, Cyprus

This text concentrates on creative dialogues shaped by fine art students together with elderly residents from Strovolos III, displaced housing estate in Nicosia. Such neighbourhood became the classroom for the module Public Art and Socially Engaged Practices of the Fine Art program of the Uni-versity of Nicosia in the academic year 2017-2018 in collaboration with Artos Foundation. Students collaborated with the residents of Strovolos III to shape a series of creative mappings and actions.

Creative Dialogues Between University of Nicosia Fine Art Students and Strovolos III Residents: A Displaced Housing Estate in Nicosia, Cyprus

This text concentrates on creative dialogues shaped by fine art students together with elderly residents from Strovolos III, displaced housing estate in Nicosia. Such neighbourhood became the classroom for the module Public Art and Socially Engaged Practices of the Fine Art program of the Uni-versity of Nicosia in the academic year 2017-2018 in collaboration with Artos Foundation. Students collaborated with the residents of Strovolos III to shape a series of creative mappings and actions.

Postoperative navigated transcranial magnetic stimulation to predict motor recovery after surgery of tumors in motor eloquent areas

ObjectiveTo know whether motor deficits after tumor surgery are transient is reassuring for the patient and crucial for planning rehabilitation and adjuvant treatment. We analyze the value of postoperative MRI navigated transcranial magnetic stimulation (nTMS) compared to intraoperative MEP monitoring in predicting recovery of motor function. MethodsRetrospective series of nTMS mappings within 14 days after surgery for supratentorial tumors (09/2014–05/2018). All patients with motor deficits of Medical-Research-Council-Grade (MRCS) 0–4- were included. ResultsWe performed nTMS mapping on average 3.8 days after surgery and recorded nTMS MEP in 11 of 13 patients. Motor strength recovered to at least MRCS 4 within one month if postoperative nTMS elicited MEPs (positive predictive value 90.9%). If nTMS did not elicit MEPs, the patient did not recover (negative predictive value 100%). Intraoperative MEP and postoperative nTMS were equally predictive for long-term motor recovery. In cases of intraoperative MEP alteration/signal loss, but a positive postoperative nTMS mapping, 2/3 patients demonstrated a good motor recovery. ConclusionnTMS may predict long-term motor recovery of patients suffering from severe motor deficits directly after resection of tumors located in motor eloquent areas. SignificanceIn cases of intraoperative MEP alterations, postoperative nTMS may clarify the potential for motor recovery.

A hybrid time and wavenumber domain algorithm for generalized beamforming with circular synthetic aperture data

Synthetic aperture sonar systems typically scan along a linear trajectory, however autonomous underwater vehicles (AUV's) provide a useful platform for performing scans along more complicated trajectories with specific advantages. One example is the circular scan, which provides superior wavenumber coverage and resolution for images reconstructed near the circle center. A variety of approaches have been put forward for beamforming synthetic aperture data collected along a circular trajectory, but for images that span a significant fraction of the circle radius, accelerated time-domain approaches such as fast-factorized backprojection (FFBP) have been suggested. The computational requirements for generating a fully sampled image collected around a circular aperture are extremely large, however, even for FFBP. This is primarily because of the extremely small pixel size required to maintain adequate spatial sampling as larger portions of the aperture are coherently fused in the later stages of the FFBP algorithm. A method is presented for replacing the later stages of the algorithm with a series of spectral mappings, retaining the generality of the beamformer while improving computational efficiency.

Matrix-value Linear Regression for Image Denoising

Since images (or patches) can be inherently represented by matrices, in this paper, the image denosing task is addressed into learning global linear operator by using matrix-value linear regression strategy. From given training noisy images (or patches) and their corresponding clear ones, a series of linear mappings are potentially defined by those image pairs, and then integrated as a global linear operator on training set. Matrix-value linear regression can be employed to learn the global linear operator. The proposed algorithm can commendably overcome the disadvantages of the vector-based methods. Empirical experiments illustrate that the proposed algorithm is feasible and efficient, as well as easy to be implemented.

Does sound structure affect word learning? An eye-tracking study of Danish learning toddlers

Previous research has shown that Danish-learning children lag behind in early lexical acquisition compared with children learning a number of other languages. This delay has been ascribed to the opaque phonetic structure of Danish, which appears to have fewer reliable segmentation cues than other closely related languages. In support of this hypothesis, recent work has shown that the phonetic properties of Danish negatively affect online language processing in young Danish children. In this study, we used eye-tracking to investigate whether the challenges associated with processing Danish also affect how Danish-learning children between 24 and 35 months of age establish and learn novel label–object mappings. The children were presented with a series of novel mappings, either ostensively (one novel object presented alone on the screen) or ambiguously (one novel object presented together with a familiar one), through carrier phrases with different phonetic structures (more vs less opaque). Our results showed two main trends. First, Danish-learning children performed poorly on the task of mapping novel labels onto novel objects. Second, when learning did occur, accuracy was affected by the phonetic opacity of the speech stimuli. We suggest that this finding results from the interplay of a perceptually challenging speech input and a slower onset of early vocabulary experience, which in turn may delay the onset of word learning skills in Danish-learning children.

Dynamic State Aware Adaptive Source Coding for Networked Control in Cyberphysical Systems

A source coding (quantization) scheme is studied for the feedback of discrete-time and continuous-state cyber-physical systems (CPSs). It is formulated as a sequential coding optimization problem. The goal is to find a deterministic but adaptive policy, as a series of mappings from the historical information to the quantization strategy. In particular, an optimization problem is formulated, and then solved by the Bellman equation in dynamic programming (DP). To overcome the challenge of continuous state space, a practical solution is proposed by leveraging the approximate DP (ADP). The performance of the proposed strategy is examined for both scalar and vector dynamical systems in two practical applications. It shows that the designed policy can significantly outperform the simple fixed quantization strategies in CPSs and can be applied to the mobile/vehicle communication.

Cartografías musicales de Madrid: Ciudad, música popular y nuevas tecnologías digitales

The objective of this paper is to describe and to discuss a series of musical mappings of Madrid scenes, that allow us to visualize its geografical location as well as to understand the heterogeneous nature of the places which form it. We present six digital online maps defined by the nature, the history and the identity of blues scenes in Madrid. These maps, however, do transcend their boundaries to show the mixture of different musical styles in common places of urban music. the focus of this paper is linked with anthropological, geographical and identity and memory elements and new technologies, allowing us study our subject either from a diachronical and a synchronical perspective, which enriches its musical, cultural and communicative analysis.

Genuine localization transition in a long-range hopping model.

We introduce and study a banded random matrix model describing sparse, long-range quantum hopping in one dimension. Using a series of analytic arguments, numerical simulations, and a mapping to a long-range epidemics model, we establish the phase diagram of the model. A genuine localization transition, with well defined mobility edges, appears as the hopping rate decreases slower than ℓ^{-2}, where ℓ is the distance. Correspondingly, the decay of the localized states evolves from a standard exponential shape to a stretched exponential and finally to a exp(-Cln^{κ}ℓ) behavior, with κ>1.

The Transnational, Global, and Planetary

For all of us, reading auto|biography involves a complex series of global mappings of cultural politics, life scripts, and our own lives. My news feeds over the last year have featured two types of...

Geometrically accurate, efficient, and flexible quadrature techniques for the tetrahedral finite cell method

We illustrate the importance of geometrically accurate volume quadrature for obtaining optimal accuracy with non-boundary-fitted finite element discretizations, when the problem domain is defined by sharp boundaries. We consider the tetrahedral finite cell method (TetFCM) and replace its recursive subdivision based integration approach with geometrically accurate quadrature rules that emanate from higher-order geometric parametrizations of cut tetrahedral elements. The element-wise parametrization procedure relies on the identification of the intersection topology and a series of higher-order mappings based on Lagrange polynomials. We demonstrate with several 3D examples that geometrically faithful local parametrization ensures optimal accuracy, while significantly reducing the number of quadrature points with respect to recursive subdivision. On the other hand, we highlight the strength of subdivision quadrature in the context of a patient-specific workflow for the simulation-based performance analysis of coupled bone/implant configurations. In particular, we show that accuracy, flexibility and computational efficiency of the TetFCM critically depend on flexibly applying the two different quadrature variants for fuzzy imaging data and sharp boundary representations, respectively.

Baghdad’s thirdspace: Between liminality, anti-structures and territorial mappings

Wedged in-between the dense urban grain of Baghdad, blast walls of t-shaped concrete have littered the streets and neighbourhoods since 2003, after the US led invasion. The idiosyncrasy of these walls lies in their exaggerated spatial liminality. They appear, change location and disappear overnight, and on a daily basis, leaving Iraqis to navigate through labyrinths of in-between spaces. This article critically reveals the new social and power structures that have emerged in the context of the city in response to the condition resulting from this unique urban intervention. This uncanny spatial and social condition of permanent liminality will be analysed through Victor Turner’s critical theories of liminality and anti-structure coupled with Edward Soja’s theory of Thirdspace, interpreting, through a series of territorial mappings, a complex liminal condition in a contested and disrupted city.

Towards a conceptual foundation for documenting tangible and intangible elements of a cultural object

This article analyses the concept of intangible/tangible heritage from a documentation perspective, investigating the theoretical framework developed within the various branches of the cultural heritage studies and providing a clear perspective, as well as an alignment, of the various approaches and requirements. The focus provided highlights the prospect of developing a conceptual foundation that would cover the documentation of the tangible and intangible elements of a cultural object. The theoretical assumptions are then analysed from an ontological perspective, and tested using CIDOC-CRM, developing a series of representative mappings, including information about the material, spatial and symbolic elements of a scene in a narrative cycle painted in the narthex of a byzantine church in Cyprus. The result is a formalisation of a set of requirements and a documentation paradigm which help record the tangible and intangible elements of an heritage asset.