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The paper discusses the distribution and meaning of the additive particle -m@s in Ishkashimi. -m@s receives different semantic associations while staying in the same syntactic position. Thus, structurally combined with an object, it can semantically associate with the focused object or with the whole focused VP; similarly, combined with the subject it can semantically associate with the focused subject and with the whole focused sentence.
Yes, we can (?)
(2021)
The COVID-19 crisis has caused an extreme situation for higher education institutions around the world, where exclusively virtual teaching and learning has become obligatory rather than an additional supporting feature. This has created opportunities to explore the potential and limitations of virtual learning formats. This paper presents four theses on virtual classroom teaching and learning that are discussed critically. We use existing theoretical insights extended by empirical evidence from a survey of more than 850 students on acceptance, expectations, and attitudes regarding the positive and negative aspects of virtual teaching. The survey responses were gathered from students at different universities during the first completely digital semester (Spring-Summer 2020) in Germany. We discuss similarities and differences between the subjects being studied and highlight the advantages and disadvantages of virtual teaching and learning. Against the background of existing theory and the gathered data, we emphasize the importance of social interaction, the combination of different learning formats, and thus context-sensitive hybrid learning as the learning form of the future.
We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean propositions only. Our translation is modular and heavily benefits from the expressive input language of ASP. The resulting approach, along with its implementation, allows for solving interesting constraint satisfaction problems in ASP, showing a good performance.
X-ray spectroscopy is a sensitive probe of stellar winds. X-rays originate from optically thin shock-heated plasma deep inside the wind and propagate outwards throughout absorbing cool material. Recent analyses of the line ratios from He-like ions in the X-ray spectra of O-stars highlighted problems with this general paradigm: the measured line ratios of highest ions are consistent with the location of the hottest X-ray emitting plasma very close to the base of the wind, perhaps indicating the presence of a corona, while measurements from lower ions conform with the wind-embedded shock model. Generally, to correctly model the emerging Xray spectra, a detailed knowledge of the cool wind opacities based on stellar atmosphere models is prerequisite. A nearly grey stellar wind opacity for the X-rays is deduced from the analyses of high-resolution X-ray spectra. This indicates that the stellar winds are strongly clumped. Furthermore, the nearly symmetric shape of X-ray emission line profiles can be explained if the wind clumps are radially compressed. In massive binaries the orbital variations of X-ray emission allow to probe the opacity of the stellar wind; results support the picture of strong wind clumping. In high-mass X-ray binaries, the stochastic X-ray variability and the extend of the stellar-wind part photoionized by X-rays provide further strong evidence that stellar winds consist of dense clumps.
We summarize Chandra observations of the emission line profiles from 17 OB stars. The lines tend to be broad and unshifted. The forbidden/intercombination line ratios arising from Helium-like ions provide radial distance information for the X-ray emission sources, while the H-like to He-like line ratios provide X-ray temperatures, and thus also source temperature versus radius distributions. OB stars usually show power law differential emission measure distributions versus temperature. In models of bow shocks, we find a power law differential emission measure, a wide range of ion stages, and the bow shock flow around the clumps provides transverse velocities comparable to HWHM values. We find that the bow shock results for the line profile properties, consistent with the observations of X-ray line emission for a broad range of OB star properties.
Wolf-Rayet Stars
(2015)
Nearly 150 years ago, the French astronomers Charles Wolf and Georges Rayet described stars with very conspicuous spectra that are dominated by bright and broad emission lines. Meanwhile termed Wolf-Rayet Stars after their discoverers, those objects turned out to represent important stages in the life of massive stars.
As the first conference in a long time that was specifically dedicated to Wolf-Rayet stars, an international workshop was held in Potsdam, Germany, from 1.-5. June 2015. About 100 participants, comprising most of the leading experts in the field as well as as many young scientists, gathered for one week of extensive scientific exchange and discussions. Considerable progress has been reported throughout, e.g. on finding such stars, modeling and analyzing their spectra, understanding their evolutionary context, and studying their circumstellar nebulae. While some major questions regarding Wolf-Rayet stars still remain open 150 years after their discovery, it is clear today that these objects are not just interesting stars as such, but also keystones in the evolution of galaxies.
These proceedings summarize the talks and posters presented at the Potsdam Wolf-Rayet workshop. Moreover, they also include the questions, comments, and discussions emerging after each talk, thereby giving a rare overview not only about the research, but also about the current debates and unknowns in the field. The Scientific Organizing Committee (SOC) included Alceste Bonanos (Athens), Paul Crowther (Sheffield), John Eldridge (Auckland), Wolf-Rainer Hamann (Potsdam, Chair), John Hillier (Pittsburgh), Claus Leitherer (Baltimore), Philip Massey (Flagstaff), George Meynet (Geneva), Tony Moffat (Montreal), Nicole St-Louis (Montreal), and Dany Vanbeveren (Brussels).
Luminous Blue Variables show strong changes in their stellar wind on time scales of typically years to decades when they expand and contract radially at approximately constant luminosity. Micro-variability on shorter time scales and amplitudes can be observed superimposed to the larger scale radial changes. I will show long-term time series of high resolution spectra which we have collected in the past 20 years for many of the well known LBVs together with a few time series of weekly sampling (HR Car, R40, R71, R110, R127, S Dor) covering a time windows of up to a few months. Wind variability is seen on short and intermediate time scales with the line profiles changing from P Cygni to inverse P Cygni and double peeked profiles sometimes for the same star and spectral line. On longer time scales the ionisation levels for all chemical elements change drastically due to the strong change of the temperature on the stellar surface. While on the long term the characteristic radial changes may have impact on the over all mass loss rates, the variabilities and asymmetries on short and intermediate time scales may cause false estimates of the mass loss rates when confronting models with the observed line profiles
The most massive stars are those with the shortest but most active life. One group of massive stars, the Luminous Blue Variables (LBVs), of which only a few objects are known, are in particular of interest concerning the stability of stars. They have a high mass loss rate and are close to being instable. This is even more likely as rotation becomes an important factor in stellar evolution of these stars. Through massive stellar winds and sometimes giant eruptions, LBV nebulae are formed. Various aspects in the evolution in the LBV phase lead, beside the large scale morphological and kinematical differences, to a diversity of small structures like clumps, rims, and outflows in these nebulae.
We discuss the results of time-resolved spectroscopy of three presumably single Population I Wolf-Rayet stars in the Small Magellanic Cloud, where the ambient metallicity is $\sim 1/5 Z_\odot$. We were able to detect and follow numerous small-scale wind-embedded inhomogeneities in all observed stars. The general properties of the moving features, such as their velocity dispersions, emissivities and average accelerations, closely match the corresponding characteristics of small-scale inhomogeneities in the winds of Galactic Wolf-Rayet stars.
The influence of the wind to the total continuum of OB supergiants is discussed. For wind velocity distributions with β > 1.0, the wind can have strong influence to the total continuum emission, even at optical wavelengths. Comparing the continuum emission of clumped and unclumped winds, especially for stars with high β values, delivers flux differences of up to 30% with maximum in the near-IR. Continuum observations at these wavelengths are therefore an ideal tool to discriminate between clumped and unclumped winds of OB supergiants.
One of the informal properties often used to describe a new virtual world is its degree of openness. Yet what is an “open” virtual world? Does the phrase mean generally the same thing to different people? What distinguishes an open world from a less open world? Why does openness matter anyway? The answers to these questions cast light on an important, but shadowy, and uneasy, topic for virtual worlds: the relationship between those who construct the virtual, and those who use these constructions.
The “output-orientation” is omnipresent in teacher education. In order to evaluate teachers' and students' performances, a wide range of different quantitative questionnaires exist worldwide. One important goal of teaching evaluation is to increase the quality of teaching and learning. The author argues, that standard evaluations which are typically made at the end of the semester are problematic due to two reasons. The first one is that some of the questions are too general and don`t offer concrete ideas as to what kind of actions can be taken to make the courses better. The second problem is that the evaluation is mostly made when the course is already over. Because of this criticism, Apelojg invented the Felix-App which offers the possibility to give feedback in real-time by asking for the emotions and needs that occur during different learning situations. The idea is very simple: positive emotions and satisfied needs are helpful for the learning process. Negative emotions and unsatisfied needs have negative effects on the learning process. First descriptive results show, that “managing emotions” during classes can have positive effects on both motivation and emotions.
Disinformation campaigns spread rapidly through social media and can cause serious harm, especially in crisis situations, ranging from confusion about how to act to a loss of trust in government institutions. Therefore, the prevention of digital disinformation campaigns represents an important research topic. However, previous research in the field of information systems focused on the technical possibilities to detect and combat disinformation, while ethical and legal perspectives have been neglected so far. In this article, we synthesize previous information systems literature on disinformation prevention measures and discuss these measures from an ethical and legal perspective. We conclude by proposing questions for future research on the prevention of disinformation campaigns from an IS, ethical, and legal perspective. In doing so, we contribute to a balanced discussion on the prevention of digital disinformation campaigns that equally considers technical, ethical, and legal issues, and encourage increased interdisciplinary collaboration in future research.
The usage of data to improve or create business models has become vital for companies in the 21st century. However, to extract value from data it is important to understand the business model. Taxonomies for data-driven business models (DDBM) aim to provide guidance for the development and ideation of new business models relying on data. In IS research, however, different taxonomies have emerged in recent years, partly redundant, partly contradictory. Thus, there is a need to synthesize the common ground of these taxonomies within IS research. Based on 26 IS-related taxonomies and 30 cases, we derive and define 14 generic building blocks of DDBM to develop a consolidated taxonomy that represents the current state-of-the-art. Thus, we integrate existing research on DDBM and provide avenues for further exploration of data-induced potentials for business models as well as for the development and analysis of general or industry-specific DDBM.
In this talk, I would like to share my experiences gained from participating in four CSP solver competitions and the second ASP solver competition. In particular, I’ll talk about how various programming techniques can make huge differences in solving some of the benchmark problems used in the competitions. These techniques include global constraints, table constraints, and problem-specific propagators and labeling strategies for selecting variables and values. I’ll present these techniques with experimental results from B-Prolog and other CLP(FD) systems.
Web Tracking
(2018)
Web tracking seems to become ubiquitous in online business and leads to increased privacy concerns of users. This paper provides an overview over the current state of the art of web-tracking research, aiming to reveal the relevance and methodologies of this research area and creates a foundation for future work. In particular, this study addresses the following research questions: What methods are followed? What results have been achieved so far? What are potential future research areas? For these goals, a structured literature review based upon an established methodological framework is conducted. The identified articles are investigated with respect to the applied research methodologies and the aspects of web tracking they emphasize.
Visual Social Networking Sites (SNSs) enable users to present themselves favorably to gain likes and the attention of others. Especially, Instagram is known for its focus on beauty, fitness, fashion, and dietary topics. Although a large body of research reports negative weight-related outcomes of SNS usage (e.g., body dissatisfaction, body image concerns), studies examining how SNS usage relates to these outcomes are scarce. Based on the visual normalization theory, we argue that SNS content facilitates normalization of so-called thin- and fit-ideals, thereby leading to biased perceptions of the average body weight in society. Therefore, this study tests whether Instagram use is associated with perceiving that the average person weighs less. Responses of 181 survey participants confirm that Instagram use is negatively related to average weight perception of both women and men. These findings contribute to the growing body of research on how SNS use relates to negative weight-related outcomes.
The management of knowledge in organizations considers both established long-term
processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
Component based software development (CBSD) and aspectoriented software development (AOSD) are two complementary approaches. However, existing proposals for integrating aspects into component models are direct transposition of object-oriented AOSD techniques to components. In this article, we propose a new approach based on views. Our proposal introduces crosscutting components quite naturally and can be integrated into different component models.
The H.E.S.S. collaboration recently reported the discovery of VHE γ-ray emission coincident with the young stellar cluster Westerlund 2. This system is known to host a population of hot, massive stars, and, most particularly, the WR binary WR 20a. Particle acceleration to TeV energies in Westerlund 2 can be accomplished in several alternative scenarios, therefore we only discuss energetic constraints based on the total available kinetic energy in the system, the actual mass loss rates of respective cluster members, and implied gamma-ray production from processes such as inverse Compton scattering or neutral pion decay. From the inferred gammaray luminosity of the order of 1035erg/s, implications for the efficiency of converting available kinetic energy into non-thermal radiation associated with stellar winds in the Westerlund 2 cluster are discussed under consideration of either the presence or absence of wind clumping.
Verbal or visual? : How information is distributed across speech and gesture in spatial dialog
(2006)
In spatial dialog like in direction giving humans make frequent use of speechaccompanying gestures. Some gestures convey largely the same information as speech while others complement speech. This paper reports a study on how speakers distribute meaning across speech and gesture, and depending on what factors. Utterance meaning and the wider dialog context were tested by statistically analyzing a corpus of direction-giving dialogs. Problems of speech production (as indicated by discourse markers and disfluencies), the communicative goals, and the information status were found to be influential, while feedback signals by the addressee do not have any influence.
Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
Gamma-rays can be produced by the interaction of a relativistic jet and the matter of the stellar wind in the subclass of massive X-ray binaries known as “microquasars”. The relativistic jet is ejected from the surroundings of the compact object and interacts with cold protons from the stellar wind, producing pions that then quickly decay into gamma-rays. Since the resulting gamma-ray emissivity depends on the target density, the detection of rapid variability in microquasars with GLAST and the new generation of Cherenkov imaging arrays could be used to probe the clumped structure of the stellar wind. In particular, we show here that the relative fluctuation in gamma rays may scale with the square root of the ratio of porosity length to binary separation, $\sqrt{h/a}$, implying for example a ca. 10% variation in gamma ray emission for a quite moderate porosity, h/a ∼ 0.01.
Background:
Childhood and adolescence are critical stages of life for mental health and well-being. Schools are a key setting for mental health promotion and illness prevention. One in five children and adolescents have a mental disorder, about half of mental disorders beginning before the age of 14. Beneficial and explainable artificial intelligence can replace current paper- based and online approaches to school mental health surveys. This can enhance data acquisition, interoperability, data driven analysis, trust and compliance. This paper presents a model for using chatbots for non-obtrusive data collection and supervised machine learning models for data analysis; and discusses ethical considerations pertaining to the use of these models.
Methods:
For data acquisition, the proposed model uses chatbots which interact with students. The conversation log acts as the source of raw data for the machine learning. Pre-processing of the data is automated by filtering for keywords and phrases.
Existing survey results, obtained through current paper-based data collection methods, are evaluated by domain experts (health professionals). These can be used to create a test dataset to validate the machine learning models. Supervised learning
can then be deployed to classify specific behaviour and mental health patterns.
Results:
We present a model that can be used to improve upon current paper-based data collection and manual data analysis methods. An open-source GitHub repository contains necessary tools and components of this model. Privacy is respected through
rigorous observance of confidentiality and data protection requirements. Critical reflection on these ethics and law aspects is included in the project.
Conclusions:
This model strengthens mental health surveillance in schools. The same tools and components could be applied to other public health data. Future extensions of this model could also incorporate unsupervised learning to find clusters and patterns
of unknown effects.
Despite the phenomenal growth of Big Data Analytics in the last few years, little research is done to explicate the relationship between Big Data Analytics Capability (BDAC) and indirect strategic value derived from such digital capabilities. We attempt to address this gap by proposing a conceptual model of the BDAC - Innovation relationship using dynamic capability theory. The work expands on BDAC business value research and extends the nominal research done on BDAC – innovation. We focus on BDAC's relationship with different innovation objects, namely product, business process, and business model innovation, impacting all value chain activities. The insights gained will stimulate academic and practitioner interest in explicating strategic value generated from BDAC and serve as a framework for future research on the subject
We present an analysis of student language input in a corpus of tutoring dialogue in the domain of symbolic differentiation. Our focus on procedural tutoring makes the dialogue comparable to collaborative problem-solving (CPS). Existing CPS models describe the process of negotiating plans and goals, which also fits procedural tutoring. However, we provide a classification of student utterances and corpus annotation which shows that approximately 28% of non-trivial student language in this corpus is not accounted for by existing models, and addresses other functions, such as evaluating past actions or correcting mistakes. Our analysis can be used as a foundation for improving models of tutoring dialogue.
Ultrasound evaluation of the patellar tendon cross-sectional area and its relation to maximum force
(2012)
Turning shy on winter's day effects of season on personality and stress response in Microtus arvalis
(2013)
This paper explores the role of the intentional stance in games, arguing that any question of artificial intelligence has as much to do with the co-option of the player’s interpretation of actions as intelligent as any actual fixed-state systems attached to agents. It demonstrates how simply using a few simple and, in system terms, cheap tricks, existing AI can be both supported and enhanced. This includes representational characteristics, importing behavioral expectations from real life, constraining these expectations using diegetic devices, and managing social interrelationships to create the illusion of a greater intelligence than is ever actually present. It is concluded that complex artificial intelligence is often of less importance to the experience of intelligent agents in play than the creation of a space where the intentional stance can be evoked and supported.
Different properties of programs, implemented in Constraint Handling Rules (CHR), have already been investigated. Proving these properties in CHR is fairly simpler than proving them in any type of imperative programming language, which triggered the proposal of a methodology to map imperative programs into equivalent CHR. The equivalence of both programs implies that if a property is satisfied for one, then it is satisfied for the other. The mapping methodology could be put to other beneficial uses. One such use is the automatic generation of global constraints, at an attempt to demonstrate the benefits of having a rule-based implementation for constraint solvers.
Generalized Two-Level Grammar (GTWOL) provides a new method for compilation of parallel replacement rules into transducers. The current paper identifies the role of generalized lenient composition (GLC) in this method. Thanks to the GLC operation, the compilation method becomes bipartite and easily extendible to capture various application modes. In the light of three notions of obligatoriness, a modification to the compilation method is proposed. We argue that the bipartite design makes implementation of parallel obligatoriness, directionality, length and rank based application modes extremely easy, which is the main result of the paper.
Track and Treat
(2018)
E-Mail tracking mechanisms gather information on individual recipients’ reading behavior. Previous studies show that e-mail newsletters commonly include tracking elements. However, prior work does not examine the degree to which e-mail senders actually employ gathered user information. The paper closes this research gap by means of an experimental study to clarify the use of tracking-based infor- mation. To that end, twelve mail accounts are created, each of which subscribes to a pre-defined set of newsletters from companies based in Germany, the UK, and the USA. Systematically varying e-mail reading patterns across accounts, each account simulates a different type of user with individual read- ing behavior. Assuming senders to track e-mail reading habits, we expect changes in mailer behavior. The analysis confirms the prominence of tracking in that over 92% of the newsletter e-mails contain tracking images. For 13 out of 44 senders an adjustment of communication policy in response to user reading behavior is observed. Observed effects include sending newsletters at different times, adapting advertised products to match the users’ IT environment, increased or decreased mailing frequency, and mobile-specific adjustments. Regarding legal issues, not all companies that adapt the mail-sending behavior state the usage of such mechanisms in their privacy policy.
Because software development is increasingly expensive and timeconsuming, software reuse gains importance. Aspect-oriented software development modularizes crosscutting concerns which enables their systematic reuse. Literature provides a number of AOP patterns and best practices for developing reusable aspects based on compelling examples for concerns like tracing, transactions and persistence. However, such best practices are lacking for systematically reusing invasive aspects. In this paper, we present the ‘callback mismatch problem’. This problem arises in the context of abstraction mismatch, in which the aspect is required to issue a callback to the base application. As a consequence, the composition of invasive aspects is cumbersome to implement, difficult to maintain and impossible to reuse. We motivate this problem in a real-world example, show that it persists in the current state-of-the-art, and outline the need for advanced aspectual composition mechanisms to deal with this.
Artificial intelligence (AI)-based technologies can increasingly perform knowledge work tasks, such as medical diagnosis. Thereby, it is expected that humans will not be replaced by AI but work closely with AI-based technology (“augmentation”). Augmentation has ethical implications for humans (e.g., impact on autonomy, opportunities to flourish through work), thus, developers and managers of AI-based technology have a responsibility to anticipate and mitigate risks to human workers. However, doing so can be difficult as AI encompasses a wide range of technologies, some of which enable fundamentally new forms of interaction. In this research-in-progress paper, we propose the development of a taxonomy to categorize unique characteristics of AI-based technology that influence the interaction and have ethical implications for human workers. The completed taxonomy will support researchers in forming cumulative knowledge on the ethical implications of augmentation and assist practitioners in the ethical design and management of AI-based technology in knowledge work.
We present an extension to a comprehensive context model that has been successfully employed in a number of practical conversational dialogue systems. The model supports the task of multimodal fusion as well as that of reference resolution in a uniform manner. Our extension consists of integrating implicitly mentioned concepts into the context model and we show how they serve as candidates for reference resolution.
The rise of open source models for software and hardware development has catalyzed the debate regarding sustainable business models. Open Source Software has already become a dominant part in the software industry, whereas Open Source Hardware is still a little-researched phenomenon but has the potential to do the same to manufacturing in a wide range of products. This article addresses this potential by introducing a research design to analyze the prototyping phase of six different Open Source Hardware projects tackling ecological, social, and economical challenges. Using a design science research methodology, a process model is developed to concretise the prototype development steps. The prototype phase is important because it is where fundamental decisions are made that affect the openness of the final product. This paper aims to advance the discourse on open production as a concept that enables companies to apply the aspect of openness towards collaboration-oriented and sustainable business models.
This study aims to bring together scattered research findings on user satisfaction with mobile government apps into a unified framework. The researchers analyzed 70 high-quality papers from leading journals and conferences and systematically integrated different frameworks and case studies to reflect the importance of the field over time while also highlighting methodological and geographical research gaps. The study achieved a significant methodological advance by developing codebooks for empirical analysis utilizing the App Store. This approach validated the framework’s dimensions on 8,524 reviews, demonstrating the framework’s applicability to platform-based apps and identifying critical areas for future research. Combining academic insights with practical findings, this research provides comprehensive guidance for developing and evaluating user-centered mobile government apps, facilitating improved service delivery and alignment with user expectations.