Reviewerly/exHarmony huggingface dataset:
Personality expression in cartoon animal characters using Sasang typology

Abstract The movement style is an adequate descriptor of different personalities. While many studies investigate the relationship between apparent personality and high‐level motion qualities in humans, similar research for animal characters still needs to be done. The variety in animals' skeletal configurations and texture complicates their pose estimation process. Our affect analysis framework includes a workflow for pose extraction in animal characters and a parameterization of the high‐level animal motion descriptors inspired by Laban movement analysis. Using a data set of quadruped walk cycles, we prove the display of typologies in cartoon animal characters, reporting the point‐biserial correlation between our motion parameters and the Sasang categories that reflect different personalities.
The importance of multimodal play and storytelling in medtech for children: A Case Study of Co-designing a Mixed Realities Play Kit to Prepare 4 to 10-year-Olds for an MRI Scan

This article examines the research and development of a mixed realities play-kit to prepare children for an MRI scan to be undertaken without the need for a General Anaesthetic. The kit uses three different types of play; augmented, virtual reality and physical to help children become familiar with the look of an MRI scanner, the noises it makes, the role of the radiographer, what to expect when they go to hospital and to practise staying still. We reflect on the initial multimodal research methods that were used to bring children into the first stages of the design and development process. These included, model making, drawing, play and informal conversations. From which, data were analysed with visual and thematic means to make an original contribution to the field of medtech design for children, in that we found young children (aged six and under) prefer to receive medical information through opportunities for multimodal play and storytelling. As a direct result of this finding, we matched different play types to the various areas of preparation outlined above. In doing so, paying attention to the specific affordances of the different ways in which modes are combined depending on if physical, augmented or virtual reality play are used. Such findings are likely to be useful to other researchers and developers creating medtech products for young children. For those interested in multimodality specifically, this article also provides insight into the connection between information, modes of communication and play and the application of these to research design.
Transformation protocols of pure-coherent states under incoherent operation

Abstract It is well known that the majorization condition is the necessary and sufficient for the deterministic transformations of pure-coherent states under incoherent operation (IO). In this paper, we present the protocol 1 (product-form) which provides a method for the pure-coherent transformation under IO and overcomes the restriction of the number of Kraus operators of Protocol I (Torun and Yildiz 2018 Phys. Rev. A 97 052331). Then, we show that the corresponding uncorrelated-catalytic protocol (discarding the catalytic state) is not incoherent-preserving. We construct the protocol 2 such that the uncorrelated-catalytic transformation with four-dimensional catalyst state can be implemented probabilistically under dephasing-covariant IO. Especially, the protocol 2 provides the target state from the catalyst-assisted transformation and its equivalent states with respect to Pauli operators <?CDATA $X,Z$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>X</mml:mi> <mml:mo>,</mml:mo> <mml:mi>Z</mml:mi> </mml:math> .
“Micro World – Exploring the Microbial Kingdom”: design and testing of a microbial VR science product

We designed a microbial science popularization product based on virtual reality technology, “Micro World – Exploring the Microbial Kingdom,” and conducted usability tests. Participants used head-mounted VR glasses to experience virtual scenarios teaching microbiological knowledge. The product’s user experience was evaluated through a User Experience Questionnaire (UEQ), and the results showed that our product provided both usefulness and enjoyment. In addition, the quality of participants’ relevant knowledge acquisition was measured using the Student Education of Educational Quality (SEEQ). The SEEQ results show that “Micro World” is an effective tool for popularizing microbiology science and can actively promote students’ independent learning and improve learning quality.
Exploring characteristics and outcomes of UN military protection operations

Abstract This chapter provides descriptive statistics of the key characteristics of military operations from 1999 to 2017 where Blue Helmets used force to protect and it estimates the outcomes of operations across time and missions in Africa. The basic statistics are valuable to better understand the phenomenon at the center of this book—the application of force by Blue Helmets—and point to where we should look to learn more about successes and failures. The outcome estimations are a first attempt at analyzing the effectiveness of UN troops’ military efforts to protect civilians from violence across time and place. It finds that UN troops succeed about as often as they fail when they use force to protect, indicating that there is reason for optimism in their ability to provide physical protection to threatened populations, under the right conditions.
Vision-Based Work Zone Safety Alert System in a Connected Vehicle Environment

Work zones, being a critical component of roadway transportation systems, can benefit greatly from computer vision-enabled roadway infrastructures, specifically in connected vehicle (CV) environments. Connected infrastructures, such as roadside units (RSU) and on-board units (OBU), can greatly improve the environmental awareness and safety of CVs driving through a work zone. The contribution of this paper lies in developing a vision-based approach to generate work zone safety messages in real time, utilizing video streams from roadside monocular traffic cameras that can be used by CV work zone safety apps on mobile devices to reliably navigate through a work zone. A monocular traffic camera calibration method is proposed to establish the accurate mapping between the image plane and Global Position System (GPS) space. Real test scenarios show that our algorithm can precisely and effectively locate work zone boundaries from a monocular traffic camera in real time. We demonstrate the capabilities and features of our system through real-world experiments where the driver cannot see the work zone. End-to-end latency analysis reveals that the vision-based work zone safety warning system satisfies the active safety latency requirements. This vision-based work zone safety alert system ensures the safety of both the worker and the driver in a CV environment.
Understanding university teachers’ digital competencies: a systematic mapping study

Being digitally competent is an imperative requirement for the 21st century university teacher, a fact recognized by both the literature and policymakers. Although this topic has been addressed in different reviews and critical studies recently, none of them have systematically and explicitly addressed the factors that explain, or are explained by, the digital competencies of university teachers. Examples of these factors include, among others, demographic, professional and psychological aspects of university teachers, as well as very specific digital competencies. The present study seeks to close this gap through a systematic mapping of the literature published until 2021 in journals indexed by Scopus and Web of Science (WOS). Based on the selection of 53 primary studies, we characterized the literature and summarized the main results reported so far. The analysis allowed us to conclude the following: 1) there is a growing number of contributions aimed at understanding the acquisition of digital competencies, especially from external factors; 2) European, and more specifically Spanish, university teachers from multiple disciplines are the most studied population; 3) most studies adopted quantitative approaches to explain but not prove causality; 4) there is a great heterogeneity of relationships and results that explain the digital competencies of university professors. The implications of these results are discussed with a view to identifying the gaps that provide scope for future research.
Simulating many-body physics with quantum nonlinear optics

The rapidly growing field of quantum information can benefit greatly from quantum nonlinear optics, which has the potential to generate highly correlated optical states with a sufficiently large interaction strength per photon. Such states play a crucial role in various quantum applications. While the traditional approach to generating correlated optical states involves controlled interactions between individual single photons through nonlinear mediums, a more efficient approach is to use the evolution of multiphotons in the highly nonlinear optical medium. To facilitate this approach, we propose a scheme that traces the time evolution of the photons encoded in Fock space to generate complex correlated states. Our approach mimics the dynamics of many-body systems with adjustable interaction strength, allowing us to simulate state transfer on a spin chain by tuning the interaction. We also investigate the feasibility of our scheme based on current technologies and explore the potential of quantum nonlinear optics in quantum simulation.
Quantum gradient evaluation through quantum non-demolition measurements

We discuss a Quantum Non-Demolition Measurement (QNDM) protocol to estimate the derivatives of a cost function with a quantum computer. %This is a key step for the implementation of variational quantum circuits. The cost function, which is supposed to be classically hard to evaluate, is associated with the average value of a quantum operator. Then a quantum computer is used to efficiently extract information about the function and its derivative by evolving the system with a so-called variational quantum circuit. To this aim, we propose to use a quantum detector that allows us to directly estimate the derivatives of an observable, i.e., the derivative of the cost function. With respect to the standard direct measurement approach, this leads to a reduction of the number of circuit iterations needed to run the variational quantum circuits. The advantage increases if we want to estimate the higher-order derivatives. We also show that the presented approach can lead to a further advantage in terms of the number of total logical gates needed to run the variational quantum circuits. These results make the QNDM a valuable alternative to implementing the variational quantum circuits.
Introduction to the special issue on test automation: Trends, benefits, and costs

Software often needs to exist in different variants, which account for varying customer requirements, environments, or non-functional aspects, such as energy consumption. Unfortunately, the number of variants can grow exponentially with the number of features. As such, developing and evolving variant-rich systems is challenging, since they do not only evolve “in time” as single systems, but also “in space” with new variants. Fortunately, many different methods and tools for variant-rich systems have been proposed over the last decades, especially in the field of software product line engineering. However, their level of evaluation varies significantly, threatening their relevance for practitioners and that of future research. Many tools have only been evaluated on ad hoc datasets, minimal examples, or unrealistic and limited evolution scenarios, missing large parts of the actual evolution lifecycle of variant-rich systems.Our long-term goal is to provide benchmarks to increase the maturity of evaluation of methods and tools for evolving variant-rich systems. However, providing manually curated and sufficiently detailed benchmarks that cover the whole evolution lifecycle of variant-rich systems is challenging. We present the framework vpbench, which simulates the evolution of a variant-rich system and thereby generates an evolution enriched with metadata explaining the evolution. The generated benchmarks, i.e., the evolution histories and metadata, can serve as ground truth to check the results of tools applied on it. We formalize the claims we make about the generator and the generated benchmarks as requirements. The design of vpbench comprises modular generators and evolution operators that automatically evolve real codebases. We implement simple and advanced evolution operators—e.g., relying on code transplantation to incorporate features from real projects. We demonstrate how vpbench addresses its claimed requirements, also considering multiple degrees of realism, extensibility and language-independence of the generated benchmarks.
Label shift conditioned hybrid querying for deep active learning

Active learning aims to interactively select the most informative data for accelerating the learning procedure. In this paper, we propose a novel and principled deep active learning approach under label shift—the labeled dataset has a different class distribution with respect to the unlabeled data pool. By formulating the querying procedure as a distribution matching problem, we derive the generalization guarantee under label shift. Moreover, the theoretical results inspire a unified practical framework for deep batch active learning: in the training stage, we jointly correct the label shift and align the semantic conditional distributions; as for the querying stage, label-shift-conditioned hybrid querying (LSCHQ) strategy is proposed to balance uncertainty and diversity under label shift. Empirical results show that our proposed method is highly effective and outperforms other baseline algorithms over a variety of benchmarks and a real-world dataset.
Entity alignment for temporal knowledge graphs via adaptive graph networks

The temporal entity alignment task aims to discover entities with the same meaning but belonging to different temporal knowledge graphs (KGs). Most existing entity alignment studies mainly focus on static entity alignment, while temporal entity alignment has not received enough attention. However, entity alignment containing temporal information is more in line with real-world application scenarios, and applying static entity alignment models directly to temporal KGs usually does not achieve satisfactory performance because many events (entities) in the knowledge graph will change with time. Therefore, we propose an adaptive graph network (AGN) for entity alignment between temporal KGs. Specifically, we use a time-aware graph attention network model as an encoder to aggregate the features and temporal relationships of neighboring nodes. To adapt to various temporal knowledge graphs, we design a training scheme with adaptive relative error loss minimization, which aims to provide relative positions of entities in vector space for model optimization. Furthermore, we propose an adaptive fine-tuning distance algorithm based on supervised information, which aims to adaptively fine-tune the locations of entities in the vector space for the entity alignment similarity measure. Our proposed AGN model can be naturally extended to entity alignment datasets across multiple temporal knowledge graphs. We evaluate our proposed model via temporal knowledge graphs on public datasets and our newly proposed noisy dataset. We also demonstrate the advantages of the AGN model through extensive experiments, which achieves state-of-the-art performance on the temporal knowledge graph dataset.
Collaborative bi-aggregation for directed graph embedding

Directed graph is able to model asymmetric relationships between nodes and research on directed graph embedding is of great significance in downstream graph analysis and inference. Learning source and target embeddings of nodes separately to preserve edge asymmetry has become the dominant approach, but also poses challenge for learning representations of low or even zero in/out degree nodes that are ubiquitous in sparse graphs. In this paper, a collaborative bi-directional aggregation method (COBA) for directed graph embedding is proposed. Firstly, the source and target embeddings of the central node are learned by aggregating from the counterparts of the source and target neighbors, respectively; Secondly, the source/target embeddings of the zero in/out degree central nodes are enhanced by aggregating the counterparts of opposite-directional neighbors (i.e. target/source neighbors); Finally, source and target embeddings of the same node are correlated to achieve collaborative aggregation. Both the feasibility and rationality of the model are theoretically analyzed. Extensive experiments on real-world datasets demonstrate that COBA comprehensively outperforms state-of-the-art methods on multiple tasks and meanwhile validates the effectiveness of proposed aggregation strategies.
Human performance consequences of normative and contrastive explanations: An experiment in machine learning for reliability maintenance

Decision aids based on artificial intelligence and machine learning can benefit human decisions and system performance, but can also provide incorrect advice, and invite operators to inappropriately rely on automation. This paper examined the extent to which example-based explanations could improve reliance on a decision aid that is based on machine learning. Participants engaged in a preventive maintenance task by providing their diagnosis of the conditions of three components of a hydraulic system. A decision aid based on machine learning provided advice but was not always reliable. Three explanation displays (baseline, normative, normative plus contrastive) were manipulated within-participants. With the normative explanation display, we found improvements in participants' decision time and subjective workload. With the addition of contrastive explanations, we found improvements in participants' hit rate and sensitivity in discriminating between correct and incorrect ML advice. Implications for the design of explainable interfaces to support human-AI interaction in data intensive environments are discussed.
Comprehensive analysis of the heterogeneous computing performance of DNNs under typical frameworks on cloud and edge computing platforms

In this paper, nearly 40 commonly used deep neural network(DNN) models are selected, and their cross-platform and cross-inference frameworks are deeply analysed. The main metrics of accuracy, the total number of model parameters, the computational complexity, the accuracy density, the inference time, the memory consumption and other related parameters are used to measure their performance. The heterogeneous computing experiment is implemented on both the Google Colab cloud computing platform and the Jetson Nano embedded edge computing platform. The obtained performance is compared with that of two previous computing platforms: a workstation equipped with an NVIDIA Titan X Pascal and an embedded system based on an NVIDIA Jetson TX1 board. In addition, on the Jetson Nano embedded edge computing platform, different inference frameworks are investigated to evaluate the inference efficiency of the DNN models. Regression models are established to characterize the variation in the computing performance of different DNN classification algorithms so that the inference results of unknown models can be estimated. ANOVA methods are proposed to quantify the differences between models. The experimental results have important guiding significance for the better selection, deployment and application of DNN models in practice. Codes are available at this https URL https://github.com/Foreverzfy/Model-Test.
<i>Brahman</i> as the Cosmic Translator and the <i>Gītā’</i>s Potentiality in American Transcendentalism

Abstract This chapter examines the function of the Gītā among the American Transcendentalists (Emerson, Thoreau, Whitman), not because the material has not been covered by other scholars, but rather because their classist, elitist, and mystical exoticism will inform all subsequent American readings of this text. The Gītā found a hospitable home in New England esotericism and spiritualism. Emerson, although initially dismissive of Indian ‘superstition’, became fascinated with the Gītā, composing his poem ‘Brahma’ in homage to it. In A Week on the Concord and Merrimac Rivers, Thoreau channelled the Gītā and in Walden’s parable of Kouroo, Thoreau aestheticized the Gītā’s divine revelation: just as the translator perfects the text through translation, the artist perfects his creation. Thoreau was also the first writer in the West to criticize the institution of caste. Whitman’s prolific references to Indian terms can be seen as superficial. Among these writers, his interest seems to be an expression of exoticism rather than any substantial inquiry. However, the Transcendentalists can be credited with showing how translation truly functions as a potentiality. Once cut from its roots and transplanted in the New World, the Gītā became a different text. It was co-opted, owned, and open to improvement.
The Nazi <i>Kṣatriya</i> Ethos

Abstract This chapter examines German Gītā scholarship surrounding the two World Wars. It examines how nineteenth- and twentieth-century German historians of religion and Indologists (Holtzmann, Garbe, Jacobi, Oldenberg, Otto) used the methodology of biblical scholarship to strip away the accretions and discover the original Gītā, believed to be tied to their joint Indo-Aryan identity. In the process, they discovered in the Gītā a kṣatriya ethos that became the focus of subsequent scholarship, culminating in the work of J.W. Hauer, the chief Nazi Indologist whose glorification of the kṣatriya would find an avid reader in Himmler who cited the Gītā to legitimize SS atrocities.
The Beats, the Monk, and Multicultural Artists

Abstract In the late twentieth century and up to the present, translation concerns are still at issue in the Western reception of the Gītā. Beginning with the Transcendental Meditation Movement and Aldous Huxley’s introduction to their translation of the Sanskrit poem, moving onto the Hare Krishna Movement and its translation of the Gītā with introductory commentary by Allen Ginsberg, Denise Levertov, and Thomas Merton, this 1960s’ reception reaches a figurative extension in the exoticism of postmodern opera (Philip Glass, John Adams), proving in the last instance how translation can be inter-semiotic, and that it is ultimately a form of performance, sometimes more Orientalist, hysterical and histrionic than others.