Reviewerly/exHarmony huggingface dataset:
Cybernetics and Simulacra: The Hyperreality of Augmented Reality Games

The paper explores and critically interrogates the proliferation of online games as showcased in the rise of augmented reality (AR) games such as Harry Potter: Wizards Unite and the like using the concepts of "cybernetics" and "simulacra."These are two powerful notions evident in contemporary times that when combined can be used to unmask the inner workings of AR games and to critique 21 st century's overdependency on and overdetermination of technology.The first task of the paper is to analytically decode AR game using the idea of cybernetics and John Cormack's creative ecosystem.Side by side this immanent exposition is the unmasking of such creative ecosystem that brings to light Jean Baudrillard's idea of hyperreality.The second task is to critically examine the philosophical underpinnings of AR that reiterates a transcendent critique by showing its implications and significations towards understanding the heterogeneity of human and machine interplay within the context of digital capitalism.
Understanding spatial presence formation and maintenance in virtual reality for younger and older adults

Background: Virtual reality (VR) has the potential to benefit physical, cognitive, and socioemotional well-being across a wide spectrum of domains.For the benefits of VR to be fully realized, people must experience spatial presence in the digital environment.We developed the Magnet Model of Spatial Presence as a framework to integrate the extant literature, identify gaps, and delineate the spatial presence formation and maintenance processes in virtual reality.Given that perception and attention are key components of the spatial presence process, age-related changes in these abilities might impact older adults' ability to develop and maintain spatial presence in a virtual environment.Objective: This research study aimed to address limitations in the literature by assessing various aspects of the spatial presence process for younger and older adults.The objectives were to evaluate how long it takes to form spatial presence; the extent that spatial presence is experienced and if it changes over several hours of time with experience; how well people maintain presence; and how well they recover from breaks in the spatial presence experience.Method: Participants were twenty-five younger adults and twenty-five older adults.The VR apparatus was an HTC Vive and the VR experiences included one passive experience and one active experience.Participation occurred for three days.Results: Most aspects of the spatial presence process were similar for older and younger adults.Presence formation occurred quickly, levels of presence were high and generally maintained over several hours of time.Younger adults experienced more breaks in presence than older adults, but all participants were generally able to easily recover from breaks in presence.Conclusion: These findings provide insights on presence formation, levels, maintenance, and break recovery.The results illustrate the potential of virtual reality for both younger and older adults.
Peggio il rimedio del male? Argomenti e valori nelle controversie sulla vaccinazione contro il Covid-19

An interdisciplinary approach involving linguistics, rhetoric, and argumentation theory helps reveal how people argue their opinions and decisions. Although the pandemic is a common experience, its risks are perceived in different ways. For some, the real threat is Covid-19 and the remedy is vaccination. For others, however, the real risk is the vaccine and the “remedy” is refusal to get vaccinated. Justifying their opinions on the subject, Italian Internet users refer to common values (such as life, health, responsibility, etc.). However, since Internet users diagnose risks in different ways, they make use of shared values in differing ways. In this paper, the views of those for and against vaccination are analyzed from three complementary perspectives. The first one concerns the differences in which people conceive of various values. The second one shows how, using the same topoi, pro- and anti-vaccine advocates create different hierarchies of values that are fundamental to their respective decisions. Finally, the third one explores differences in the ways values are used in various argumentation schemes used in disputes on vaccination.
Supply Chain Governance of Agricultural Products under Big Data Platform Based on Blockchain Technology

The present work serves to improve the stable cooperation relationship among subjects of supply chain such as enterprises, farmers, intermediary organizations, and retailers and enhance the governance and optimization of agricultural product supply chain, thus strengthening the competitiveness of China’s agricultural industry. The supply chain governance of agricultural products is taken as the research object. Initially, the stabilities of two supply chain organization modes, “company and farmer” and “company, intermediary organization and farmer,” are analyzed by static game analysis. Then, based on the above analysis and the characteristics of blockchain institutional technology, a detailed analyzation is made on the mechanism of supply chain of agricultural products governance based on blockchain technology. Finally, the functional framework of agricultural supply chain governance is designed based on the basic framework of blockchain technology, and analyzation is made on the trust mechanism and contract mechanism of agricultural supply chain governance based on blockchain technology. The research results show that problems such as information and cognitive constraints in agricultural supply chain governance cannot be completely solved only through the evolution of blockchain organizational structure and the supply of governance mechanism, and speculative behavior will still appear. Optimizing the governance of supply chain of agricultural products based on blockchain technology can realize the transformation of its governance scenario. Meanwhile, the blockchain technologies such as deintermediation, demistrust, and intelligent contract play an important role in the process of agricultural supply chain governance, which can make it change in many aspects such as organization mode, application operation, and governance mechanism. The rapid development of new generation information technologies such as blockchain, the Internet of Things, and computer technology makes it possible to comprehensively digitize economic activities such as production and transaction in the supply chain of agricultural products. The present work combines the technical logic of blockchain digital governance with the institutional logic of agricultural product supply chain governance and tries to solve the instability problems caused by imperfect organization, lack of trust, and incomplete contract in agricultural product supply chain governance with the characteristics of blockchain such as deintermediation, demistrust, and intelligent contract.
TemPredict: A Big Data Analytical Platform for Scalable Exploration and Monitoring of Personalized Multimodal Data for COVID-19

A key takeaway from the COVID-19 crisis is the need for scalable methods and systems for ingestion of big data related to the disease, such as models of the virus, health surveys, and social data, and the ability to integrate and analyze the ingested data rapidly. One specific example is the use of the Internet of Things and wearables (i.e., the Oura ring) to collect large-scale individualized data (e.g., temperature and heart rate) continuously and to create personalized baselines for detection of disease symptoms. Individualized data, when collected, has great potential to be linked with other datasets making it possible to combine individual and societal scale models for further understanding the disease. However, the volume and variability of such data require novel big data approaches to be developed as infrastructure for scalable use. This paper presents the data pipeline and big data infrastructure for the TemPredict project, which, to the best of our knowledge, is the largest public effort to gather continuous physiological data for time-series analysis. This effort unifies data ingestion with the development of a novel end-to-end cyberinfrastructure to enable the curation, cleaning, alignment, sketching, and passing of the data, in a secure manner, by the researchers making use of the ingested data for their COVID-19 detection algorithm development efforts. We present the challenges, the closed-loop data pipelines, and the secure infrastructure to support the development of time-sensitive algorithms for alerting individuals based on physiological predictors illness, enabling early intervention.
DePo: Dynamically Offload Expensive Event Processing to the Edge of Cyber-Physical Systems

Event processing is one of the cornerstones to manage massive data streams in Cyber-Physical Systems (CPS). Due to CPS applications' increasing complexity, detecting highly complicated events ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">aka</i> . “expensive” events) leads to significant performance degradation, particularly harmful to mission-critical systems. To tackle this challenge, we define a new task - dynamic event processing offloading to CPS-edges. This paper proves the problem NP-hard and proposes a solution - <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DePo</monospace> . <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DePo</monospace> splits the expensive events into sub-models and offloads them to CPS edges. We design a long and short-term event memory mechanism in <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DePo</monospace> that enables the edges and server to process expensive events collaboratively within their capabilities. Besides, we propose a concept called Edge Utility to measure the optimality of offloading schemes. A heuristic algorithm is presented in this study to guide how to dispatch events to edges, thereby helping <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DePo</monospace> generate a sub-optimal solution in polynomial computational complexity. Our extensive experiments show that the performance gap between <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DePo</monospace> and the optimal benchmark is less than 5%. <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DePo</monospace> effectively reduces more than 40% redundant states and provides over 100% higher throughput than state-of-the-art approaches. Experimental results verified the high stability and scalability of <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DePo</monospace> , especially when dealing with a large number of expensive events.
On the Role of Corpus Ordering in Language Modeling

Language models pretrained on vast corpora of unstructured text using self-supervised learning framework are used in numerous natural language understanding and generation tasks.Many studies show that language acquisition in humans follows a rather structured simple-to-complex pattern and guided by this intuition, curriculum learning, which enables training of computational models in a meaningful order, such as processing easy samples before hard ones, has been shown to potentially reduce training time.The question remains whether curriculum learning can benefit pretraining of language models.In this work, we perform comprehensive experiments involving multiple curricula strategies varying the criteria for complexity and the training schedules.Empirical results of training transformer language models on English corpus and evaluating it intrinsically as well as after fine-tuning across eight tasks from the GLUE benchmark, show consistent improvement gains over conventional vanilla training.Interestingly, in our experiments, when evaluated on one epoch, the best model following a document-level hard-to-easy curriculum, outperforms the vanilla model by 1.7 points (average GLUE score) and it takes the vanilla model twice as many training steps to reach comparable performance.
G-RRT*: Goal-oriented sampling-based RRT* path planning Algorithm for mobile robot navigation with improved convergence rate

Randomized sampling-based path planning algorithms are widely used for mobile robot navigation in complex configuration space. The optimal Rapidly Exploring Random Tree (RRT*) is one of the popular sampling-based path planning algorithms that guarantees collision-free optimal path planning solutions. Even though the RRT* path planning algorithm is asymptotically optimal, its convergence is very slow. To address this problem, this paper proposes a Goal-oriented RRT* algorithm called G-RRT*. The key idea of G-RRT* is to reduce the sampling space by generating more samples near the goal configuration. The proposed algorithm is validated in a maze environment using existing algorithms. The proposed G-RRT* path planning algorithm outperforms RRT* and Informed RRT* in three performance measures convergence time, the initial cost solution, and the number of nodes visited.
Material meets the city

research-article Share on Material meets the city: a materials experience perspective on urban interaction design Authors: Linda Hirsch LMU Munich LMU MunichView Profile , Eleni Economidou University of Salzburg University of SalzburgView Profile , Irina Paraschivoiu University of Salzburg University of SalzburgView Profile , Tanja Döring University of Bremen University of BremenView Profile Authors Info & Claims InteractionsVolume 29Issue 1January - February 2022 pp 58–63https://doi.org/10.1145/3501358Online:06 January 2022Publication History 0citation329DownloadsMetricsTotal Citations0Total Downloads329Last 12 Months329Last 6 weeks44 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Extended Reality in the World Wide Web: Investigating and Testing the Use Cases of WebVR Manuals

Web Virtual Reality (WebVR) extends the World Wide Web (WWW) in its possibilities by enabling it to present 3D objects.Past research suggests that this could enhance accessibility and calls for further research on user acceptance of this technology.This study conducts an online experiment with a manual for folding an origami figure and compares data from a classic approach versus one where a WebVR manual is presented.Time, quality, knowledge transfer, and motivation are measured, and mediation is tested for usability, cognition, imagination, and comprehensibility.Participants show higher levels of motivation, mediated by comprehensibility and less cognitive effort.The reduced cognitive strain enhances knowledge transfer.Furthermore, the time used is lower in the WebVR setting than in the traditional one.This effect is moderated by usability.Regarding quality, no significant effects are reported.
Informal Student Groups in the Context of the COVID‑19 Pandemic

Informal student groups in Far Eastern Federal University exhibited significant activity and received essential support from the university administrators during the COVID‑19 pandemic. Since the pandemic burst out, the number of informal student groups known to administrators has only increased, counterintuitively. Our findings show that the value of informal student groups for participants in the educational process is comparable to that of formal education programs, although participation in such groups is not part of any formal requirements or explicit societal demands. A series of interviews was conducted with members of informal student groups (a volunteer community, a group of medical volunteers, associations of engineering and information technology students), faculty members, and administrators. Analysis of interview transcripts shows that informal student groups can be considered valuable in the university corporation as a way of entering a profession, as a response to the implicit societal demand for “maturity” and agency development in students, and as a means of “appropriating” the learning environment and becoming a member of the university corporation. At the same time, a number of respondents perceive self-organization within student groups as generally and intrinsically valuable. Our findings show that informal student groups have an unspoken value in themselves, supported by an equally unspoken societal demand for “collectivist education”, which is yet to be discussed.
Artificial Intelligence: Technologies, Applications, and Policy Perspectives. Insights from Portugal

Artificial Intelligence (AI) reshapes the global scenario and redefines development and service demand. AI stands as a disruptive technology that leads to numerous, more efficient activities, industrial processes, and new business models. The literature underlines that AI can be used in all aspects of organizations and individuals' personal lives, and such nuances and potentials are still mostly unstudied, representing an interesting research gap. This chapter aims to emphasize the technologies and applications of AI to industries and services. Focusing then on the Portuguese context, this research's main objective is to concentrate on AI to recognize state of the art and the main developments and trends in the industry and services and provide insights into AI policies.
7. Weil sums of binomials: properties, applications and open problems

We present a survey on Weil sums in which an additive character of a finite field F is applied to a binomial whose individual terms (monomials) become permutations of F when regarded as functions. Then we indicate how these Weil sums are used in applications, especially how they characterize the nonlinearity of power permutations and the correlation of linear recursive sequences over finite fields. In these applications, one is interested in the spectrum of Weil sum values that are obtained as the coefficients in the binomial are varied. We review the basic properties of such spectra, and then give a survey of current topics of research: Archimedean and non-Archimedean bounds on the sums, the number of values in the spectrum and the presence or absence of zero in the spectrum. We indicate some important open problems and discuss progress that has been made on them.
Self-training with Few-shot Rationalization

While pre-trained language models have obtained state-of-the-art performance for several natural language understanding tasks, they are quite opaque in terms of their decision-making process.While some recent works focus on rationalizing neural predictions by highlighting salient concepts in text as justifications or rationales, they rely on thousands of labeled training examples for both task labels as well as annotated rationales for every instance.Such extensive large-scale annotations are infeasible to obtain for many tasks.To this end, we develop a multi-task teacher-student framework based on self-training language models with limited task-specific labels and rationales, and judicious sample selection to learn from informative pseudo-labeled examples 1 .We study several characteristics of what constitutes a good rationale and demonstrate that the neural model performance can be significantly improved by making it aware of its rationalized predictions particularly in low-resource settings.Extensive experiments in several benchmark datasets demonstrate the effectiveness of our approach.
ORGANIZATION OF FUTURE PRIMARY SCHOOL TEACHERS’ PROFESSIONAL PRACTICE WITHIN THE OPTIONAL BLOCK «FOREIGN LANGUAGE»

The article is devoted to the issue of organizing the future primary school teachers’ professional practice within the pedagogical specialty 013 «Primary education» the first (bachelor’s) level of higher education in the content of the optional block «Foreign Language». In the process of the work, the native and foreign special literature on the research problem was analyzed. The normative legal documents and reports on the issues of the primary school teacher training, in particular its practical professional component, in the leading European countries were taken into account. To achieve the goal, a set of scientific methods was used: theoretical ones – studying the state of the investigated problem, determining the essence of future primary school teachers’ professional practice; empirical methods: questionnaires, interviews; pedagogical observations. It was found that the main purpose of professional practice of future primary school teachers within the optional block «Foreign Language» is the formation of their practical methodological competence through the implementation of theoretical knowledge and skills in foreign language teaching methods at primary school, modern technologies and innovative teaching tools. When organizing this type of practice, it is necessary to take into account the following tasks for the development of future teachers’ skills: to use teaching methods, technologies and tools of foreign language teaching at primary school in accordance with the practical purpose of the lesson; to plan a foreign language lesson methodically correct; to select, analyze and effectively apply modern technologies and innovative means of teaching a foreign language in accordance with the practical purpose of the lesson; to develop lifelong learning skills; to develop the ability of future teachers to plan a foreign language lesson and to control the formation level of foreign language knowledge, skills and abilities of primary school pupils. It is proved that the result of effective organization of professional practice within the optional block «Foreign Language» is the formation of future teachers’ professional competencies: the ability to organize foreign language teaching at primary school with focus on modern methodological approaches and leading pedagogical experience; ability to communicate in a foreign language in an oral and writing forms within a certain foreign language topic; ability to use a foreign language in various situations of social, educational and professional communication.
Automatically Deciding on the Integration of Commits Based on Their Descriptions

Continuous Integration is a critical problem for software maintenance in global projects, compromising companies&#x2019; performance, which tends to accumulate a high-resolution time due to the approval process, conflict resolution, tests, and validations. The process of the validation involves the commit description interpretation and can be automated by NLP-mechanisms. This paper presents an intelligent NLP-based approach to evaluate whether the commits can be integrated into a certain software release based only on their descriptions. Our experiments showed an accuracy of 92.9%.