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  1. A different fluid text: Textual and narrative theoretical observations on Historia von D. Johann Fausten (1587) [Ein anders unfester Text Text- und erzähltheoretische Beobachtungen zur Historia von D. Johann Fausten (1587)]
    Author: Herweg, Mathias
    Published: 2022
    Publisher:  Brill Academic Publishers

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    Source: BASE Selection for Comparative Literature
    Language: German
    Media type: Article (journal)
    Format: Online
    Parent title: Poetica, 52 (3-4), 292-314 ; ISSN: 0303-4178
    DDC Categories: 800
    Subjects: Literature & rhetoric
    Rights:

    info:eu-repo/semantics/openAccess
  2. Plotting memory
    what are we made to remember when we read narrative texts?
    Author: Mühlbacher, Manuel
    Published: 2022

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    Source: Online Contents Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Journal of literary theory; Berlin : de Gruyter, 2007-; Band 16, Heft 2 (2022), Seite 239-263; 23 cm

  3. Inherited revolution
    narratives in transgenerational memory transfer
    Author: Almeida, Ana de; Wimplinger, Christian
    Published: 2022

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    Source: Online Contents Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Journal of literary theory; Berlin : de Gruyter, 2007-; Band 16, Heft 2 (2022), Seite 289-308; 23 cm

  4. Shared histories in multiethnic societies: literature as a critical corrective of cultural memory studies
    Author: Albrecht, Monika
    Published: 2022

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    Source: Online Contents Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Journal of literary theory; Berlin : de Gruyter, 2007-; Band 16, Heft 2 (2022), Seite 309-330; 23 cm

  5. Introduction: Pre-romantic and post-romantic genius
    Author: Holmes, Deborah
    Published: 2022
    Publisher:  Wiley, Hoboken

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    Source: Union catalogues
    Language: English
    Media type: Article (journal)
    Format: Online
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    Parent title: Enthalten in: German Life and Letters; Hoboken : Wiley, 2022; 75 (2022), 3, Seite 327-340
    Scope: 1 Online-Ressource
  6. Ermächtigung des Publikums und Entmächtigung des Künstlers. Geniediskurse der Nachromantik mit Blick auf den frühen Mozartkult und Grillparzer
    Author: Michler, Werner
    Published: 2022
    Publisher:  Wiley, Hoboken

    eng: The article discusses aspects of the dialectics of genius cults in the nineteenth century, using examples of Mozart's reception: the unveiling of the Salzburg memorial statue in 1842, Franz Grillparzer's texts on Wolfgang Amadeus Mozart and his... more

     

    eng: The article discusses aspects of the dialectics of genius cults in the nineteenth century, using examples of Mozart's reception: the unveiling of the Salzburg memorial statue in 1842, Franz Grillparzer's texts on Wolfgang Amadeus Mozart and his son Franz Xaver, as well as the artist's novella Der arme Spielmann. The consolidation and popularisation of genius discourse in the genius cults of post-Romanticism exerted unprecedented if latent pressure on producers of art in the period: the cults around prominent figures make great art into an unattainable exception. The article investigates how Franz Xaver Mozart and Grillparzer reacted to this dilemma.

     
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    Source: Union catalogues
    Language: German
    Media type: Article (journal)
    Format: Online
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    Parent title: Enthalten in: German Life and Letters; Hoboken : Wiley, 2022; 75 (2022), 3, Seite 341-364
    Scope: 1 Online-Ressource
  7. "Schöne jugendliche Mädchenköpfe": Gender and 'genie' in Lou Andreas-Salome's Menschenkinder
    Author: Mairhofer, Marlen
    Published: 2022
    Publisher:  Wiley, Hoboken

    eng: In her essay ‘Der Mensch als Weib’ (1899) Lou Andreas-Salomé compares women to trees: both produce their ‘fruit’ unintentionally. This comparison seems to allow very little scope for active female creativity, let alone ingenuity. Closer... more

     

    eng: In her essay ‘Der Mensch als Weib’ (1899) Lou Andreas-Salomé compares women to trees: both produce their ‘fruit’ unintentionally. This comparison seems to allow very little scope for active female creativity, let alone ingenuity. Closer inspection, however, reveals a more differentiated view of questions of gender and creativity. By bringing biology together with psychology and outlining the differences between male and female desire, Salomé establishes the feminine as an entity in its own right. Although she denies the existence of female genius, women and geniuses suspiciously seem to have a lot in common in her writing: both embody a heightened self-sufficiency through their very essence. Characters who illustrate the complex relations between self-fulfilment, desire and creativity can be found throughout Salomé’s literary work; I take as my example here the early ‘Novellencyclus’ Menschenkinder (1899). Hans Holtema (‘Mädchenreigen’), Hildegard (‘Das Paradies’) and Irene von Geyern (‘Zurück ans All’) possess skills that can best be described as ingenium, an innate gift, which is often seen as a challenge by their (male) surroundings. Rather than offering dogmatic answers, Salomé’s novellas as well as her theoretical work around 1900 emphasise the richness of debates about gender and genius.

     
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    Source: Union catalogues
    Language: English
    Media type: Article (journal)
    Format: Online
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    Parent title: Enthalten in: German Life and Letters; Hoboken : Wiley, 2022; 75 (2022), 3, Seite 448-464
    Scope: 1 Online-Ressource
  8. Computer Vision-Based Classification of Flow Regime and Vapor Quality in Vertical Two-Phase Flow
    Author: Shai Kadish; David Schmid; Jarryd Son; Edward Boje
    Published: 2022
    Publisher:  MDPI AG

    This paper presents a method to classify flow regime and vapor quality in vertical two-phase (vapor-liquid) flow, using a video of the flow as the input; this represents the first high-performing and entirely camera image-based method for the... more

     

    This paper presents a method to classify flow regime and vapor quality in vertical two-phase (vapor-liquid) flow, using a video of the flow as the input; this represents the first high-performing and entirely camera image-based method for the classification of a vertical flow regime (which is effective across a wide range of regimes) and the first image-based tool for estimating vapor quality. The approach makes use of computer vision techniques and deep learning to train a convolutional neural network (CNN), which is used for individual frame classification and image feature extraction, and a deep long short-term memory (LSTM) network, used to capture temporal information present in a sequence of image feature sets and to make a final vapor quality or flow regime classification. This novel architecture for two-phase flow studies achieves accurate flow regime and vapor quality classifications in a practical application to two-phase CO 2 flow in vertical tubes, based on offline data and an online prototype implementation, developed as a proof of concept for the use of these models within a feedback control loop. The use of automatically selected image features, produced by a CNN architecture in three distinct tasks comprising flow-image classification, flow-regime classification, and vapor quality prediction, confirms that these features are robust and useful, and offer a viable alternative to manually extracting image features for image-based flow studies. The successful application of the LSTM network reveals the significance of temporal information for image-based studies of two-phase flow.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Sensors, Vol 22, Iss 996, p 996 (2022)
    Subjects: flow regime; vapor quality; computer vision; machine learning; Chemical technology
  9. An Electric Fence-Based Intelligent Scheduling Method for Rebalancing Dockless Bike Sharing Systems
    Author: Lulu Jia; Dezhen Yang; Yi Ren; Qiang Feng; Bo Sun; Cheng Qian; Zhifeng Li; Chenchen Zeng
    Published: 2022
    Publisher:  MDPI AG

    With a new generation of bike sharing services emerging, the development of dockless bike sharing services results in considerable socioeconomic and environmental benefits but also creates new issues, such as inappropriate parking behaviors and bike... more

     

    With a new generation of bike sharing services emerging, the development of dockless bike sharing services results in considerable socioeconomic and environmental benefits but also creates new issues, such as inappropriate parking behaviors and bike imbalances. To solve the inappropriate parking problem, electric fences have been introduced to guide users to park bikes in designated zones. Considering the role of electric fences in restricting user parking behaviors, an electric fence-based intelligent scheduling method for rebalancing dockless bike sharing systems is proposed in this paper. As a dynamic method that considers the real-time usage of bike sharing systems, an electric fence adjusts its capacity based on real-time information, which guides users to return bikes to electric fences with greater urgency. Because existing approaches require prespecified models and are unable to consider all the intricacies in the dynamic optimization problem, a model-free intelligent scheduling approach based on deep Q-learning that can adapt to the changing distributions of customer arrivals, available bikes, bike locations, and user travel times is used to solve the problem. Finally, a case study involving Beihang University is employed, which shows that the method performs well in rebalancing the bike sharing system and improving the mean utilization ( MU ) and customer satisfaction ( CS ).

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Applied Sciences, Vol 12, Iss 5031, p 5031 (2022)
    Subjects: bike sharing system; dockless bikes; electric fence; deep Q-learning; intelligent scheduling; Technology; T; Engineering (General). Civil engineering (General); Biology (General); Physics; Chemistry
  10. MULTI-MODAL SEMANTIC MESH SEGMENTATION IN URBAN SCENES
    Author: D. Laupheimer; N. Haala
    Published: 2022
    Publisher:  Copernicus Publications

    The semantic segmentation of the huge amount of acquired 3D data has become an important task in recent years. Meshes have evolved into a standard representation next to Point Clouds (PCs) – not least because of their great visualization... more

     

    The semantic segmentation of the huge amount of acquired 3D data has become an important task in recent years. Meshes have evolved into a standard representation next to Point Clouds (PCs) – not least because of their great visualization possibilities. Compared to PCs, meshes have commonly smaller memory footprints while jointly providing geometrical and high-resolution textural information. For this reason, we opt for semantic mesh segmentation, which is a widely overlooked topic in photogrammetry and remote sensing yet. In this work, we perform an extensive ablation study on multi-modal handcrafted features adapting the Point Cloud Mesh Association (PCMA) (Laupheimer et al., 2020) which establishes explicit connections between faces and points. The multi-modal connections are used in a two-fold manner: (i) to extend per-face descriptors with features engineered on the PC and (ii) to annotate meshes semi-automatically by propagating the manually assigned labels from the PCs. In this way, we derive annotated meshes from the ISPRS benchmark data sets Vaihingen 3D (V3D) and Hessigheim 3D (H3D). To demonstrate the effectiveness of the multi-modal approach, we use well-established and fast Random Forest (RF) models deploying various feature vector compositions and analyze their performances for semantic mesh segmentation. The feature vector compositions consider features derived from the mesh, the PC or both. The results indicate that the combination of radiometric and geometric features outperforms feature sets of a single feature type only. Besides, we observe that relative height is the most crucial feature. The main finding is that the multi-modal feature vector integrates the complementary strengths of the underlying modalities. Whereas the mesh provides outstanding textural information, the dense PCs are superior in geometry. The multi-modal feature descriptor achieves the best performance on both data sets. It significantly outperforms feature sets that incorporate only features derived from the mesh by +7.37 ...

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-2-2022, Pp 267-274 (2022)
    Subjects: Technology; T; Engineering (General). Civil engineering (General); Applied optics. Photonics
  11. One-Shot Learning with Pseudo-Labeling for Cattle Video Segmentation in Smart Livestock Farming
    Author: Yongliang Qiao; Tengfei Xue; He Kong; Cameron Clark; Sabrina Lomax; Khalid Rafique; Salah Sukkarieh
    Published: 2022
    Publisher:  MDPI AG

    Computer vision-based technologies play a key role in precision livestock farming, and video-based analysis approaches have been advocated as useful tools for automatic animal monitoring, behavior analysis, and efficient welfare measurement... more

     

    Computer vision-based technologies play a key role in precision livestock farming, and video-based analysis approaches have been advocated as useful tools for automatic animal monitoring, behavior analysis, and efficient welfare measurement management. Accurately and efficiently segmenting animals’ contours from their backgrounds is a prerequisite for vision-based technologies. Deep learning-based segmentation methods have shown good performance through training models on a large amount of pixel-labeled images. However, it is challenging and time-consuming to label animal images due to their irregular contours and changing postures. In order to reduce the reliance on the number of labeled images, one-shot learning with a pseudo-labeling approach is proposed using only one labeled image frame to segment animals in videos. The proposed approach is mainly comprised of an Xception-based Fully Convolutional Neural Network (Xception-FCN) module and a pseudo-labeling (PL) module. Xception-FCN utilizes depth-wise separable convolutions to learn different-level visual features and localize dense prediction based on the one single labeled frame. Then, PL leverages the segmentation results of the Xception-FCN model to fine-tune the model, leading to performance boosts in cattle video segmentation. Systematic experiments were conducted on a challenging feedlot cattle video dataset acquired by the authors, and the proposed approach achieved a mean intersection-over-union score of 88.7% and a contour accuracy of 80.8%, outperforming state-of-the-art methods (OSVOS and OSMN). Our proposed one-shot learning approach could serve as an enabling component for livestock farming-related segmentation and detection applications.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Animals, Vol 12, Iss 558, p 558 (2022)
    Subjects: one-shot learning; video segmentation; pseudo-labeling; precision livestock farming; deep learning; Veterinary medicine; Zoology
  12. Attraction vs. Alignment as Drivers of Collective Motion
    Author: Daniel Strömbom; Grace Tulevech
    Published: 2022
    Publisher:  Frontiers Media S.A.

    Moving animal groups exhibit a range of fascinating behaviors. The standard explanation for how these groups form and function is that the individual animals interact via attraction, repulsion, and alignment, where alignment is proposed to drive the... more

     

    Moving animal groups exhibit a range of fascinating behaviors. The standard explanation for how these groups form and function is that the individual animals interact via attraction, repulsion, and alignment, where alignment is proposed to drive the collective motion. However, it has been shown both experimentally and theoretically that alignment interactions are not required to induce group level alignment. In particular, via the use of self-propelled particle models it has been established that several other mechanisms induce group level alignment (aka polarization) in combination with attraction alone. However, no systematic comparison of these mechanisms among themselves, or with explicit alignment, has been presented and it remains unclear how, or even if, they can be distinguished at the collective level. Here, we introduce two previously unreported mechanisms, burst-and-glide and burst-and-stop, and show via simulation that they also induce polarization in combination with attraction alone. Then, we compare the polarization inducing characteristics of six mechanisms; asymmetric interactions, asynchrony, anticipation, burst-and-glide, burst-and stop, and explicit alignment. We show that the mechanisms induce polarization in different parts of the attraction parameter space, that the route to polarization from uniformly random initial conditions, as well as repolarization following strong perturbations, is markedly different among the mechanisms. In particular, we find that alignment based and non-alignment based mechanisms can be distinguished via their polarization and repolarization processes. These findings further challenge the current alignment based theory of collective motion and may contribute to a more versatile theory of collective motion across scales.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Frontiers in Applied Mathematics and Statistics, Vol 7 (2022)
    Subjects: flocking; self-propelled particles; polarization; animal behavior; schooling; swarming; Applied mathematics. Quantitative methods; Probabilities. Mathematical statistics
  13. Informative and Reliable Tract Segmentation for Preoperative Planning
    Author: Oeslle Lucena; Pedro Borges; Jorge Cardoso; Keyoumars Ashkan; Rachel Sparks; Sebastien Ourselin
    Published: 2022
    Publisher:  Frontiers Media S.A.

    Identifying white matter (WM) tracts to locate eloquent areas for preoperative surgical planning is a challenging task. Manual WM tract annotations are often used but they are time-consuming, suffer from inter- and intra-rater variability, and noise... more

     

    Identifying white matter (WM) tracts to locate eloquent areas for preoperative surgical planning is a challenging task. Manual WM tract annotations are often used but they are time-consuming, suffer from inter- and intra-rater variability, and noise intrinsic to diffusion MRI may make manual interpretation difficult. As a result, in clinical practice direct electrical stimulation is necessary to precisely locate WM tracts during surgery. A measure of WM tract segmentation unreliability could be important to guide surgical planning and operations. In this study, we use deep learning to perform reliable tract segmentation in combination with uncertainty quantification to measure segmentation unreliability. We use a 3D U-Net to segment white matter tracts. We then estimate model and data uncertainty using test time dropout and test time augmentation, respectively. We use a volume-based calibration approach to compute representative predicted probabilities from the estimated uncertainties. In our findings, we obtain a Dice of ≈0.82 which is comparable to the state-of-the-art for multi-label segmentation and Hausdorff distance <10mm. We demonstrate a high positive correlation between volume variance and segmentation errors, which indicates a good measure of reliability for tract segmentation ad uncertainty estimation. Finally, we show that calibrated predicted volumes are more likely to encompass the ground truth segmentation volume than uncalibrated predicted volumes. This study is a step toward more informed and reliable WM tract segmentation for clinical decision-making.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Frontiers in Radiology, Vol 2 (2022)
    Subjects: diffusion MRI; tract segmentation; deep learning; uncertainty quantification; calibration; tractography; Medical physics. Medical radiology. Nuclear medicine
  14. A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data
    Author: Diana M. Pérez-Valencia; María Xosé Rodríguez-Álvarez; Martin P. Boer; Lukas Kronenberg; Andreas Hund; Llorenç Cabrera-Bosquet; Emilie J. Millet; Fred A. van Eeuwijk
    Published: 2022
    Publisher:  Nature Portfolio

    Abstract High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which... more

     

    Abstract High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data. In a first stage, we correct for design features and spatial trends per time point. In a second stage, we focus on the longitudinal modelling of the spatially corrected data, thereby taking advantage of shared longitudinal features between genotypes and plants within genotypes. We propose a flexible hierarchical three-level P-spline growth curve model, with plants/plots nested in genotypes, and genotypes nested in populations. For selection of genotypes in a plant breeding context, we show how to extract new phenotypes, like growth rates, from the estimated genotypic growth curves and their first-order derivatives. We illustrate our approach on HTP data from the PhenoArch greenhouse platform at INRAE Montpellier and the outdoor Field Phenotyping platform at ETH Zürich.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Scientific Reports, Vol 12, Iss 1, Pp 1-16 (2022)
    Subjects: Medicine; R; Science; Q
  15. A Comparative Study of Gradient Descent Method and a Novel Non-Gradient Method for Structural Shape Optimization
    Author: Ishan Jha; Krishna K. Pathak; Mrigank Jha; Ashutosh Ranjan
    Published: 2022
    Publisher:  Ram Arti Publishers

    Motivated by the works on non-gradient techniques in the domain of shape optimization of the structure, the present work intends to suggest a novel non-gradient procedure for shape optimization of structures and compare it to an existing... more

     

    Motivated by the works on non-gradient techniques in the domain of shape optimization of the structure, the present work intends to suggest a novel non-gradient procedure for shape optimization of structures and compare it to an existing gradient-based method. The presented technique optimizes the shape of structural parts using a fuzzy controlled integrated zero-order methodology incorporating the notion of design elements and automated mesh construction with mesh refinement at each iteration. The movement of nodes and convergence monitoring is taken care of using the triangular fuzzy membership function. The changes in shape occur according to the selected target maximum shear stress (σt) with a view of reaching as near to the target as possible at all the points. The present methodology is packaged in a piece of software termed GSO (Gradientless shape optimization) coded in FORTRAN language. To explain the efficacy of the current approach, a few basic structural shapes have been optimized under various constraints, and the results of the same are compared to those obtained using Optistruct (a part of software suite HyperWorks from Altair engineering), which works on gradient descent method. The proposed approach works well and produces more industry fabricable results than what is produced by the gradient descent method in Optistruct.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: International Journal of Mathematical, Engineering and Management Sciences, Vol 7, Iss 2, Pp 258-271 (2022)
    Subjects: shape optimization; fuzzy set; fuzzy membership function; finite element; non-gradient; design element; optistruct; Technology; T; Mathematics
  16. An efficient 3D column-only P300 speller paradigm utilizing few numbers of electrodes and flashings for practical BCI implementation.
    Author: Onur Erdem Korkmaz; Onder Aydemir; Emin Argun Oral; Ibrahim Yucel Ozbek
    Published: 2022
    Publisher:  Public Library of Science (PLoS)

    The event related P300 potentials, positive waveforms in electroencephalography (EEG) signals, are often utilized in brain computer interfaces (BCI). Many studies have been carried out to improve the performance of P300 speller systems either by... more

     

    The event related P300 potentials, positive waveforms in electroencephalography (EEG) signals, are often utilized in brain computer interfaces (BCI). Many studies have been carried out to improve the performance of P300 speller systems either by developing signal processing algorithms and classifiers with different architectures or by designing new paradigms. In this study, a new paradigm is proposed for this purpose. The proposed paradigm combines two remarkable properties of being a 3D animation and utilizing column-only flashings as opposed to classical paradigms which are based on row-column flashings in 2D manner. The new paradigm is utilized in a traditional two-layer artificial neural networks model with a single output neuron, and numerous experiments are conducted to evaluate and compare the performance of the proposed paradigm with that of the classical approach. The experimental results, including statistical significance tests, are presented for single and multiple EEG electrode usage combinations in 1, 3 and 15 flashing repetitions to detect P300 waves as well as to recognize target characters. Using the proposed paradigm, the best average classification accuracy rates on the test data are improved from 89.97% to 93.90% (an improvement of 4.36%) for 1 flashing, from 97.11% to 98.10% (an improvement of 1.01%) for 3 flashings and from 99.70% to 99.81% (an improvement of 0.11%) for 15 flashings when all electrodes, included in the study, are utilized. On the other hand, the accuracy rates are improved by 9.69% for 1 flashing, 4.72% for 3 flashings and 1.73% for 15 flashings when the proposed paradigm is utilized with a single EEG electrode (P8). It is observed that the proposed speller paradigm is especially useful in BCI systems designed for few EEG electrodes usage, and hence, it is more suitable for practical implementations. Moreover, all participants, given a subjective test, declared that the proposed paradigm is more user-friendly than classical ones.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: PLoS ONE, Vol 17, Iss 4, p e0265904 (2022)
    Subjects: Medicine; R; Science; Q
  17. An interval-stochastic compromise programming for urban water resource allocation
    Author: Mehrnoosh Khademi; Somayeh Sharifi; Mehdi Salimi; Bruno Antonio Pansera; Massimiliano Ferrara
    Published: 2022
    Publisher:  Accademia Peloritana dei Pericolanti

    As water demand is exponentially increasing and supplies are scarce, integrated urban water management is an important task in all cities and regions. It is a multi-objective problem, because of the many objectives and criteria that should be... more

     

    As water demand is exponentially increasing and supplies are scarce, integrated urban water management is an important task in all cities and regions. It is a multi-objective problem, because of the many objectives and criteria that should be analyzed. The key goal of this research was to create an integrated decision-making-based multistage scenario-based interval-stochastic programming (IDMSISP) model for urban water management. IDMSISP is a multistage optimization method with two objective functions that can reflect dynamics, uncertainty, and risk analysis in water resource management. This model was developed for the case of study, based on compromise programming. Two prominent objectives involving the value of the benefit of the network and social satisfaction level are examined. The capacity and environment constraints are considered under uncertainty. The uncertainty in these constraints was solved by applying the chance constraint method.

     
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    Source: BASE Selection for Comparative Literature
    Language: English; Italian
    Media type: Article (journal)
    Format: Online
    Parent title: Atti della Accademia Peloritana dei Pericolanti : Classe di Scienze Fisiche, Matematiche e Naturali, Vol 100, Iss 1, p A4 (2022)
    Subjects: Science (General)
  18. Eucommia ulmoides Oliver-Tribulus terrestris L. Drug Pair Regulates Ferroptosis by Mediating the Neurovascular-Related Ligand-Receptor Interaction Pathway- A Potential Drug Pair for Treatment Hypertension and Prevention Ischemic Stroke
    Author: Qian Zhang; Jie Yang; Chuanhua Yang; Xuesong Yang; Yongzhi Chen
    Published: 2022
    Publisher:  Frontiers Media S.A.

    BackgroundIn this study, we used the network pharmacology approach to explore the potential disease targets of the Eucommia ulmoides Oliver (EUO)-Tribulus terrestris L. (TT) drug pair in the treatment of hypertension-associated neurovascular lesions... more

     

    BackgroundIn this study, we used the network pharmacology approach to explore the potential disease targets of the Eucommia ulmoides Oliver (EUO)-Tribulus terrestris L. (TT) drug pair in the treatment of hypertension-associated neurovascular lesions and IS via the ferroptosis pathway.MethodsWe used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform to search for the key active compounds and targets of the drug pair. Based on the GeneCards database, the relevant targets for the drug pair were obtained. Then, we performed the molecular docking of the screened core active ingredients and proteins using the DAVID database and the R AutoDock Vina software. Based on the GSE22255 dataset, these screened target proteins were used to build random forest (RF) and support vector machine (SVM) models. Finally, a new IS nomogram prediction model was constructed and evaluated.ResultsThere were 36 active compounds in the EUO-TT drug pair. CHRM1, NR3C1, ADRB2, and OPRD1 proteins of the neuroactive ligand-receptor interaction pathway interacted with the proteins related to the ferroptosis pathway. Molecular docking experiments identified 12 active ingredients of the drug pair that may tightly bind to those target proteins. We constructed a visual IS nomogram prediction model using four genes (CHRM1, NR3C1, ADRB2, and OPRD1). The calibration curve, DCA, and clinical impact curves all indicated that the nomogram model is clinically applicable and diagnostically capable. CHRM1, NR3C1, ADRB2, and OPRD1, the target genes of the four effective components of the EUO-TT drug pair, were considered as risk markers for IS.ConclusionsThe active ingredients of EUO-TT drug pair may act on proteins associated with the neuroactive ligand-receptor interaction pathway to regulate ferroptosis in vascular neurons cells, ultimately affecting the onset and progression of hypertension.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
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    Format: Online
    Parent title: Frontiers in Neurology, Vol 13 (2022)
    Subjects: stroke; hypertension; Eucommia ulmoides Oliver; Tribulus terrestris L; ferroptosis; network pharmacology Taubert D; Neurology. Diseases of the nervous system
  19. Deep Learning-Based 3D Shape Feature Extraction on Flash Animation Style
    Author: Mengru Zhu; Jong Han Lee
    Published: 2022
    Publisher:  Hindawi-Wiley

    Flash animation, as a kind of digital learning resource, is an important media for delivering information content, and more importantly, it is an important online learning resource with text, graphics, images, audio, video, interaction, dynamic... more

     

    Flash animation, as a kind of digital learning resource, is an important media for delivering information content, and more importantly, it is an important online learning resource with text, graphics, images, audio, video, interaction, dynamic effects, etc. Flash animation, with its powerful multimedia interaction and presentation capabilities, is widely used in distance education, high-quality course websites, Q&A platforms, etc. With the continuous development of deep learning, the 3D shape feature extraction method combined with deep learning has become a hot research topic. In this paper, we combine deep learning with traditional 3D shape feature extraction methods, so that we can not only break the bottleneck of nondeep learning methods but also improve the accuracy of 3D shape data classification and retrieval tasks, especially in the case of non-rigid 3D shapes. The scheme in this paper not only does not require a large number of training samples but also its feature extraction for flash animation is accurate. Experiments show that the success rate of accurate feature extraction of this paper’s scheme is higher than that of the state-of-the-art methods.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Wireless Communications and Mobile Computing, Vol 2022 (2022)
    Subjects: Technology; T; Telecommunication
  20. Identification of End-User Economical Relationship Graph Using Lightweight Blockchain-Based BERT Model
    Author: Mukta Jagdish; Devangkumar Umakant Shah; Varsha Agarwal; Ganesh Babu Loganathan; Abdullah Alqahtani; Saima Ahmed Rahin
    Published: 2022
    Publisher:  Hindawi Limited

    Current methods for extracting information from user resumes do not work well with unstructured user resumes in economic announcements, and they do not work well with documents that have the same users in them. Unstructured user information is turned... more

     

    Current methods for extracting information from user resumes do not work well with unstructured user resumes in economic announcements, and they do not work well with documents that have the same users in them. Unstructured user information is turned into structured user information templates in this study. It also proposes a way to build person relationship graphs in the field of economics. First, the lightweight blockchain-based BERT model (B-BERT) is trained. The learned B-BERT pretraining model is then utilized to get the event instance vector, categorize it appropriately, and populate the hierarchical user information templates with accurate user characteristics. The aim of this research is that it has investigated the approach of creating character connection graphs in the Chinese financial system and suggests a framework for doing so in the economic sector. Furthermore, the relationship between users is found through the filled-in user information template, and a graph of user relationships is made. This is how it works: finally, the experiment is checked by filling in a manually annotated dataset. In tests, the method can be used to get text information from unstructured economic user resumes and build a relationship map of people in the financial field. The experimental results show that the proposed approach is capable of efficiently retrieving information from unstructured financial personnel resume text and generating a character relationship graph in the economic sphere.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: Computational Intelligence and Neuroscience, Vol 2022 (2022)
    Subjects: Computer applications to medicine. Medical informatics; Neurosciences. Biological psychiatry. Neuropsychiatry
  21. A Feature Fusion Airport Detection Method Based on the Whole Scene Multispectral Remote Sensing Images
    Author: Xinyu Dong; Jia Tian; Qingjiu Tian
    Published: 2022
    Publisher:  IEEE

    Being one of the most important infrastructures, airports play a vital role in both civil fields and military fields. However, detect airports directly based on the whole scene remote sensing images (RSIs) with complex background remains challenging.... more

     

    Being one of the most important infrastructures, airports play a vital role in both civil fields and military fields. However, detect airports directly based on the whole scene remote sensing images (RSIs) with complex background remains challenging. To address this issue, this article proposes a method that mainly combines spectral features and geometric features of airports with concrete runways to detect multiple airports simultaneously from a whole scene multispectral image with medium-high spatial resolution and with comparatively few bands (contains blue, green, red, and near-infrared bands). Specifically, a decision tree algorithm was developed based on the analysis of spectral features to extract main concrete areas within the whole RSI. Then, the geometric features are used to aim at extracting the point marks of candidate airports. The influence of different image spatial resolutions of the proposed method is explored and the detection effect and processing efficiency of proposed method is verified based on whole scene RSIs with complex background. The analysis of experimental results shows that Sentinel-2 images is more suitable for airport detection than Gaofen-6 and Landsat-8 images based on the proposed method. In addition, the proposed method provides high-accuracy detection of category Ⅳ airports based on Sentinel-2 images with different background complexity in experimental areas indicate the proposed method has a high robust and a good applicability. Finally, run-time test of the proposed method was conducted, and it demonstrates the proposed method has the higher processing efficiency when applying to regional airport detection.

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    Parent title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 1174-1187 (2022)
    Subjects: Airport detection; concrete runways; decision tree; multispectral remote sensing; whole scene image; Ocean engineering; Geophysics. Cosmic physics
  22. Information and behavioral responses during a pandemic
    evidence from delays in Covid-19 death reports
    Author: Gutiérrez, Emilio Fernandez; Rubli, Adrian; Tavares, Tiago
    Published: 2022

    Location:
    Fachinformationsverbund Internationale Beziehungen und Länderkunde
    Inter-library loan:
    Unlimited inter-library loan, copies and loan

    Location:
    German Institute of Development and Sustainability (IDOS), Bibliothek
    Inter-library loan:
    Unlimited inter-library loan, copies and loan
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    Source: Union catalogues
    Language: English
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Journal of development economics; Amsterdam : Elsevier, 1974; Volume 154 (January 2022), Artikel-Nummer 102774, 13 Seiten

    Subjects: Coronavirus; Informationsverbreitung; Sterblichkeit; Meinung; Mexiko; Gesundheitspolitik; COVID-19; Pandemie; Berichterstattung; Massenmedien; Bedeutung; Rolle; Sozialverhalten; Gesundheitsfürsorge; Gesundheit; Datenaufbereitung
    Scope: 13
  23. jj /
    Published: 2022

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    Source: Online Contents Comparative Literature
    Language: German
    Media type: Article (journal)
    Format: Print
    Parent title: Enthalten in: Allegoria; Palermo : Palumbo, 1989-; Band 32, Heft 84 (2022), Seite 23

  24. Sobre abismos, hospitalidades y estrategias de resistencia desde la re-presentación corporal: Cuerpo exiliado, torturado, desgarrado. Cuerpo en resistencia: A(r)mar cuerpos tullidos
    Author: Rodríguez, Vanina
    Published: 2022

    This paper is structured as a dialogue with a variety of texts. Through an interdisciplinary and intersectional approach, it will examine possible ways in which bodies are classified and framed -that is, constructed- as abnormal, deviant, and/or... more

     

    This paper is structured as a dialogue with a variety of texts. Through an interdisciplinary and intersectional approach, it will examine possible ways in which bodies are classified and framed -that is, constructed- as abnormal, deviant, and/or infirm, and their connection with categories such as exile, torture, and laceration. The intention is to rethink the meaning of the body and corporealities both as a space shaped by power and resistance. To think of these bodies, which appear to be defeated, as a space of firmness, obstinacy, rebellion, and resistance. The objective is to examine these constructions in order to generate new ways of thinking, looking, and feeling with and about the body in the reflective, creative, and meaning-making processes. As well as, on the basis of this research, to question the field of humanities and its methods of work. A genealogical methodology will be used to detect certain relevant points or events. Therefore, the aim here is not to draw a chronological line of events and reach a predefined objective, but to highlight (and reveal) moments, which are presented as an articulation of elements and which contain the capacity to provoke changes, reflections, and new researches. The authors to be discussed are: Cristina Peri Rosi: Cristina Peri Rosi, Txus García, Alejandra Pizarnik, Rita Segato, Juan Gelman and Jaques Derrida. ; El presente trabajo se articula partiendo de un diálogo con diversos textos. Mediante un enfoque interdisciplinario e interseccional se examinarán posibles formas en que los cuerpos son clasificados y definidos -es decir construidos- como anormales, desviados y/o enfermos y su vínculo con categorías como exilio, tortura y desgarramiento. La intención es repensar el sentido del cuerpo y las corporalidades no solo como un espacio normado por el poder sino también resistente. Pensar estos cuerpos, al parecer derrotados, como territorio de firmeza, obstinación, rebelión y resistencia. El objetivo es interrogar estas construcciones para generar nuevas ...

     
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    Source: BASE Selection for Comparative Literature
    Language: English; Spanish
    Media type: Article (journal)
    Format: Online
    DDC Categories: 800; 941; 993
    Subjects: literarystudies; postcolonial
    Rights:

    L::The Stacks License ; thestacks.libaac.de/rights
  25. Forum: Method as Practice
    Author: Brasch, Ilka; Starre, Alexander; Lanzendörfer, Tim; Mayer, Ruth; Sulimma, Maria; Shapiro, Stephen; Lüthe, Martin; Horn, Katrin; Dunst, Alexander; Junker, Carsten
    Published: 2022

    Given the diversity of objects and objectives of research in the field and recent debates about method, there should be a more robust conversation about the concrete practices of analysis and interpretation that are pursued in American studies in... more

     

    Given the diversity of objects and objectives of research in the field and recent debates about method, there should be a more robust conversation about the concrete practices of analysis and interpretation that are pursued in American studies in Germany and beyond. This forum brings together ten scholars who tackle the question of what exactly it is that we do when we engage in reading, analysis, and interpretation. On the one hand, the participants of this forum question core assumptions behind the methods of literary inquiry as it is often taught. The result is a renewed awareness of their own positionality as academic participants in larger fields of cultural interaction. On the other hand, each statement proposes new ways to conceptualize interpretation, affirming the role the situatedness of researchers plays in the production of scholarship. Several contributions strongly reaffirm or challenge past methods, while others place the methodological question in the context of neoliberal structures in higher education. Still others propose ways to move forward that combine existing approaches and add new means of engagement with cultural texts. In different registers, these statements help chart the affordances of critical inquiry and depart from an understanding of interpretation as objective, repeatable, and disembodied. ; amst.winter-verlag.de/article/AMST/2022/1/4

     
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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Article (journal)
    Format: Online
    DDC Categories: 800; 941; 993
    Subjects: americanstudies; digitalhumanities; culturalstudies; scienceresearch; literarystudies; popularculture
    Rights:

    L::CC BY-NC-ND 4.0 ; creativecommons.org/licenses/by-nc-nd/4.0/