Miracle-dz/UniFAR-FTUs huggingface dataset:
What Supports Serendipity on Twitter? Online Survey on the Role of Technology Characteristics and Their Use

Serendipity experiences are highly desirable in work life, considering both individuals’ learning and organizational innovation capacity. This study looks into information and social serendipity in the context of Twitter. While Twitter can be viewed as a fruitful platform for serendipity to emerge, there is little understanding of what technology characteristics and use practices contribute to such experiences in work-related use. Drawing from the functional affordances theory, the paper investigates the role of presenteeism, self-disclosure, recommendation quality and pace of change, and different types of Twitter use as possible antecedents of serendipity. A cross-sectional international online survey was conducted with 473 respondents who actively use Twitter in their work. An exploratory factor analysis was performed, followed by linear regression analysis to identify relevant statistical associations. The findings indicate that presenteeism (i.e., the fundamental element of reachability) seems to have an effect on serendipity while the more designable characteristics, like the quality of recommendations, do not. Overall, the findings imply that serendipity experiences are primarily explained by individual characteristics like personality and specific ways of using Twitter. This is amongst the first studies on the role of Twitter characteristics as functional affordances in the formation of serendipity. The extensive empirical study contributes a detailed analysis of the antecedents of serendipity and opens avenues for research and design to identify new serendipity-inducing mechanisms.
Ski Fall Detection from Digital Images Using Deep Learning

In this paper, we explore how to take advantage of computer vision to assist ski resorts and monitor the safety of skiers on the tracks. In order to quickly detect any falls or injures, and provide first aid for injured people, we make use of archived ski videos, which are employed to explore the possibility of skiers fall detection. Throughout combinations of visual object detection with human pose detection by using deep learning methods. Our ultimate goal of this project is to provide a way for ski safety monitoring which has potential applications for physical training. Our contribution in this paper is to propose a fall detection method suitable for skiers based on visual object detection, we have obtained 0.94 mAP accuracy in preliminary tests.
KOZAI CYCLES, TIDAL FRICTION, AND THE DYNAMICAL EVOLUTION OF BINARY MINOR PLANETS

In recent years, many binary minor planets (BMPs) have been discovered in the solar system. Many models have been suggested for their formation, but these encounter difficulties explaining their observed characteristics. Here, we show that secular perturbations by the Sun (Kozai mechanism) fundamentally change the evolution and the initial distribution of BMPs predicted by such models and lead to unique observational signatures. The Kozai mechanism can lead to a large periodic oscillations in the eccentricity and inclination of highly inclined BMP orbits, where we predict such effects to be observable with current accuracy within a few years (e.g., for the binary asteroid Huenna). In addition, the combined effects of the Kozai mechanism and tidal friction (KCTF) drives BMPs into short-period circular orbits. We predict a specific inclination-dependent distribution of the separation and eccentricity of BMPs, due to these effects, including a zone of avoidance at the highest inclinations. Specifically, the Kozai evolution could explain the recently observed peculiar orbit of the Kuiper Belt binary 2001 QW322. Additionally, the KCTF process could lead to BMPs coalescence and serve as an important route for the formation of irregular shaped single minor planets with large axial tilts.
H II REGIONS: WITNESSES TO MASSIVE STAR FORMATION

We describe the first three-dimensional simulation of the gravitational collapse of a massive, rotating molecular cloud that includes heating by both non-ionizing and ionizing radiation. These models were performed with the FLASH code, incorporating a hybrid, long characteristic, ray-tracing technique. We find that as the first protostars gain sufficient mass to ionize the accretion flow, their H II regions are initially gravitationally trapped, but soon begin to rapidly fluctuate between trapped and extended states, in agreement with observations. Over time, the same ultracompact H II region can expand anisotropically, contract again, and take on any of the observed morphological classes. In their extended phases, expanding H II regions drive bipolar neutral outflows characteristic of high-mass star formation. The total lifetime of H II regions is given by the global accretion timescale, rather than their short internal sound-crossing time. This explains the observed number statistics. The pressure of the hot, ionized gas does not terminate accretion. Instead, the final stellar mass is set by fragmentation-induced starvation. Local gravitational instabilities in the accretion flow lead to the build-up of a small cluster of stars, all with relatively high masses due to heating from accretion radiation. These companions subsequently compete with the initial high-mass star for the same common gas reservoir and limit its mass growth. This is in contrast to the classical competitive accretion model, where the massive stars are never hindered in growth by the low-mass stars in the cluster. Our findings show that the most significant differences between the formation of low-mass and high-mass stars are all explained as the result of rapid accretion within a dense, gravitationally unstable, ionized flow.
The z = 0.54 LoBAL Quasar SDSS J085053.12+445122.5. I. Spectral Synthesis Analysis Reveals a Massive Outflow

We introduce SimBAL, a novel spectral-synthesis procedure that uses grids of ionic column densities generated by the photoionization code Cloudy and a Bayesian model calibration to forward-model broad absorption-line quasar (BALQ) spectra. We used SimBAL to analyze the Hubble Space Telescope Cosmic Origins Spectrograph (COS) spectrum of the low-redshift BALQ SDSS J085053.12+445122.5. SimBAL analysis yielded velocity-resolved information about the physical conditions of the absorbing gas. We found that the ionization parameter and column density increase, and the covering fraction decreases, as a function of velocity. The log column density is 22.9 (22.4) (cm−2) for solar (Z = 3 Z⊙) metallicity. The outflow lies 1–3 pc from the central engine, consistent with the estimated location of the torus. The mass outflow rate is 17–28 M⊙ yr−1, the momentum flux is consistent with LBol/c, and the ratio of the kinematic to bolometric luminosity is 0.8%–0.9%. The outflow velocity is similar to the escape velocity at the absorber’s location, and force multiplier analysis indicates that part of the outflow could originate in resonance-line driving. The location near the torus suggests that dust scattering may play a role in the acceleration, although the lack of reddening in this UV-selected object indicates a relatively dust-free line of sight. The low accretion rate (0.06LEdd) and compact outflow suggests that SDSS J0850+4451 might be a quasar past its era of feedback, although since its mass outflow is about eight times the accretion rate, the wind is likely integral to the accretion physics of the central engine.
ViMoTest: a low code approach to specify ViewModel-based tests with a projectional DSL using JetBrains MPS

Automated testing for software is a fundamental part of achieving high-quality software systems. In particular, the user interface (UI) is one suitable abstraction layer for automated tests. However, software test developers usually spend considerable effort writing automated UI tests in a maintainable way. Therefore, this work proposes a concept to design a low code approach using the ViewModel architectural pattern as an abstraction layer to develop automated UI tests. We use the Design Science Research method to design a projectional DSL as an artifact to refine our approach. As planned results, we aim to (1) develop a projectional DSL to specify ViewModel-based tests, (2) apply this novel approach in an industrial and an open-source project, and (3) perform empirical studies to get feedback for improving this approach w.r. t. creation, maintenance, and understandability of test suites. We conclude that a low code approach using a projectional DSL to specify automated tests based on ViewModels could have several benefits compared to similar approaches.
Quantifying community evolution in developer social networks

Understanding the evolution of communities in developer social networks (DSNs) around open source software (OSS) projects can provide valuable insights about the socio-technical process of OSS development. Existing studies show the evolutionary behaviors of social communities can effectively be described using patterns including split, shrink, merge, expand, emerge, and extinct. However, existing pattern-based approaches are limited in supporting quantitative analysis, and are potentially problematic for using the patterns in a mutually exclusive manner when describing community evolution. In this work, we propose that different patterns can occur simultaneously between every pair of communities during the evolution, just in different degrees. Four entropy-based indices are devised to measure the degree of community split, shrink, merge, and expand, respectively, which can provide a comprehensive and quantitative measure of community evolution in DSNs. The indices have properties desirable to quantify community evolution including monotonicity, and bounded maximum and minimum values that correspond to meaningful cases. They can also be combined to describe more patterns such as community emerge and extinct. We conduct studies with real-world OSS projects to evaluate the validity of the proposed indices. The results suggest the proposed indices can effectively capture community evolution, and are consistent with existing approaches in detecting evolution patterns in DSNs with an accuracy of 94.1%. The results also show that the indices are useful in predicting OSS team productivity with an accuracy of 0.718. In summary, the proposed approach is among the first to quantify the degree of community evolution with respect to different patterns, which is promising in supporting future research and applications about DSNs and OSS development.
Collisionless Dynamics and the Cosmic Web

Abstract I review the nature of three-dimensional collapse in the Zeldovich approximation, how it relates to the underlying nature of the three-dimensional Lagrangian manifold and naturally gives rise to a hierarchical structure formation scenario that progresses through collapse from voids to pancakes, filaments and then halos. I then discuss how variations of the Zeldovich approximation (based on the gravitational or the velocity potential) have been used to define classifications of the cosmic large-scale structure into dynamically distinct parts. Finally, I turn to recent efforts to devise new approaches relying on tessellations of the Lagrangian manifold to follow the fine-grained dynamics of the dark matter fluid into the highly non-linear regime and both extract the maximum amount of information from existing simulations as well as devise new simulation techniques for cold collisionless dynamics.
Graphical projectional editing in gentleman

Graphical modeling languages require proper management of position, size, and layout. Most modeling editors lack automated support to manage these graphical concrete syntax properties. It is a time-consuming effort that affects the understandability of the model. Projectional editors prevent end-users from modifying the concrete syntax so they can focus on the modeling task. However, while they offer multiple notations, these editors lack support for graphical languages. In this paper, we present a projectional editor for graphical languages. Our implementation extends the Gentleman editor generator with multiple layouts and interaction-oriented components to generate web editors. A demonstration of the tool is available at https://youtu.be/wd00pRAHxsU.
An analytic interface dynamo over a shear layer of finite depth

Parker's analytic Cartesian interface dynamo is generalized to the case of a shear layer of finite thickness and low resistivity (“tachocline”), bounded by a perfect conductor (“radiative zone”) on the one side, and by a highly diffusive medium (“convective zone”) supporting an α-effect on the other side. In the limit of high diffusivity contrast between the shear layer and the diffusive medium, thought to be relevant for the Sun, a pair of exact dispersion relations for the growth rate and frequency of dynamo modes is analytically derived. Graphic solution of the dispersion relations displays a somewhat unexpected, non-monotonic behavior, the mathematical origin of which is elucidated. The dependence of the results on the parameter values (dynamo number and shear layer thickness) is investigated. The implications of this result for the solar dynamo problem are discussed.
SDN-enabled Resource Provisioning Framework for Geo-Distributed Streaming Analytics

Geographically distributed (geo-distributed) datacenters for stream data processing typically comprise multiple edges and core datacenters connected through Wide-Area Network (WAN) with a master node responsible for allocating tasks to worker nodes. Since WAN links significantly impact the performance of distributed task execution, the existing task assignment approach is unsuitable for distributed stream data processing with low latency and high throughput demand. In this paper, we propose SAFA, a resource provisioning framework using the Software-Defined Networking (SDN) concept with an SDN controller responsible for monitoring the WAN, selecting an appropriate subset of worker nodes, and assigning tasks to the designated worker nodes. We implemented the data plane of the framework in P4 and the control plane components in Python. We tested the performance of the proposed system on Apache Spark, Apache Storm, and Apache Flink using the Yahoo! streaming benchmark on a set of custom topologies. The results of the experiments validate that the proposed approach is viable for distributed stream processing and confirm that it can improve at least 1.64× the processing time of incoming events of the current stream processing systems.
Modus: a Datalog dialect for building container images

Containers help share and deploy software by packaging it with all its dependencies. Tools, like Docker or Kubernetes, spawn containers from images as specified by a build system’s language, such as Dockerfile. A build system takes many parameters to build an image, including OS and application versions. These build parameters can interact: setting one can restrict another. Dockerfile lacks support for reifying and constraining these interactions, thus forcing developers to write a build script per workflow. As a result, developers have resorted to creating ad-hoc solutions such as templates or domain-specific frameworks that harm performance and complicate maintenance because they are verbose and mix languages. To address this problem, we introduce Modus, a Datalog dialect for building container images. Modus' key insight is that container definitions naturally map to proof trees of Horn clauses. In these trees, container configurations correspond to logical facts, build instructions correspond to logic rules, and the build tree is computed as the minimal proof of the Datalog query specifying the target image. Modus relies on Datalog’s expressivity to specify complex workflows with concision and facilitate automatic parallelisation. We evaluated Modus by porting build systems of six popular Docker Hub images to Modus. Modus reduced the code size by 20.1% compared to the used ad-hoc solutions, while imposing a negligible performance overhead, preserving the original image size and image efficiency. We also provide a detailed analysis of porting OpenJDK image build system to Modus.
TMI: tokenomics made easy for web3 applications

The design of tokenomics, i.e., distribution and circulation mechanisms of cryptocurrency tokens, is a top priority for almost all Web3 applications which relates to their own economic systems via native cryptocurrency tokens. Unfortunately, while the sustainability of tokenomics largely determines the long-term development of a Web3 application, the tooling support for the design of it has been far too insufficient. A common practice at the time of writing is to specify tokenomics with a combination of documents, spreadsheets, code scripts etc. In this paper, we introduce the TMI development platform for the modelling and analysis of Web3 tokenomics. TMI creates a domain-specific language and its graphical development environment for developers to succinctly model crypto-economic relations in a drag-and-drop way. Based on created models, TMI allows developers to formally analyse their tokenomics via checking fundamental economic properties, e.g., The core team of a project holds less than 20% of the project token in 36 months. A demonstration video of TMI is available at https://youtu.be/LDn-eRxPMTw.
HCI and Digital Twins – A Critical Look: A Literature Review

Digital twins (DTs) are one form of datafication. They are virtual reflections of physical world entities, of objects and phenomena, and are rapidly becoming an asset for innovation. There is a growing body of literature on DTs in various technology-related fields. A critical thread has emerged within this body, warning on the danger to forget that the digital part is always only a partial representation of real life, and that this partiality is always selective and biased for a specific purpose. It may thus serve some group of stakeholders better than others. We contribute with a literature review on the current understanding and use of the DT concept in the field of HCI. Our results consolidate the current understanding of DTs’ potential in HCI and note the omission of the critical perspective within the reviewed literature. The paper opens discussion of what HCI can bring to DT development and use.
Online testing of RESTful APIs: promises and challenges

Online testing of web APIs—testing APIs in production—is gaining traction in industry. Platforms such as RapidAPI and Sauce Labs provide online testing and monitoring services of web APIs 24/7, typically by re-executing manually designed test cases on the target APIs on a regular basis. In parallel, research on the automated generation of test cases for RESTful APIs has seen significant advances in recent years. However, despite their promising results in the lab, it is unclear whether research tools would scale to industrial-size settings and, more importantly, how they would perform in an online testing setup, increasingly common in practice. In this paper, we report the results of an empirical study on the use of automated test case generation methods for online testing of RESTful APIs. Specifically, we used the RESTest framework to automatically generate and execute test cases in 13 industrial APIs for 15 days non-stop, resulting in over one million test cases. To scale at this level, we had to transition from a monolithic tool approach to a multi-bot architecture with over 200 bots working cooperatively in tasks like test generation and reporting. As a result, we uncovered about 390K failures, which we conservatively triaged into 254 bugs, 65 of which have been acknowledged or fixed by developers to date. Among others, we identified confirmed faults in the APIs of Amadeus, Foursquare, Yelp, and YouTube, accessed by millions of applications worldwide. More importantly, our reports have guided developers on improving their APIs, including bug fixes and documentation updates in the APIs of Amadeus and YouTube. Our results show the potential of online testing of RESTful APIs as the next must-have feature in industry, but also some of the key challenges to overcome for its full adoption in practice.
A tool-assisted approach to engineer domain-specific languages (DSLs) using Rust

Domain-Specific Languages (DSLs) are required in a wide range of contexts, implying different execution environments. The same DSL may even have to exist in different environments. We propose in this paper an approach to engineer a DSL using the Rust language, which can be used to target several environments. Our approach focuses on selecting an implementation language, Rust, that provides multiple compilation targets for a DSL definition. However, this is a rather laborious process because Rust is only partially object-oriented, while the definition of a metamodel-based abstract syntax is essentially object-oriented. For this reason, we offer a complete DSL's development method beginning with the metamodel definition in Ecore language, then the abstract syntax conversion in Rust with a code generation tool, and finally the deployment of the language in different execution environments. We evaluated our approach by creating two DSLs with it, a Petri nets DSL and a Finite State Machine (FSM) DSL. Finally, we discuss possible improvements for our Ecore2Rust conversion tool.
HUBBLE SPACE TELESCOPE PHOTOMETRY OF GLOBULAR CLUSTERS IN M81

We perform aperture photometry and profile fitting on 419 globular cluster (GC) candidates with mV ⩽ 23 mag identified in Hubble Space Telescope/Advanced Camera for Surveys BVI imaging, and estimate the effective radii of the clusters. We identify 85 previously known spectroscopically confirmed clusters, and newly identify 136 objects as good cluster candidates within the 3σ color and size ranges defined by the spectroscopically confirmed clusters, yielding a total of 221 probable GCs. The luminosity function peak for the 221 probable GCs with estimated total dereddening applied is V ∼ (20.26 ± 0.13) mag, corresponding to a distance of ∼3.7 ± 0.3 Mpc. The blue and red GC candidates, and the metal-rich and metal-poor spectroscopically confirmed clusters, respectively, are similar in half-light radius. Red confirmed clusters are about 6% larger in median half-light radius than blue confirmed clusters, and red and blue good GC candidates are nearly identical in half-light radius. The total population of confirmed and “good” candidates shows an increase in half-light radius as a function of galactocentric distance.
Combining OCL and natural language: a call for a community effort

The growing popularity and availability of pretrained natural language models opens the door to many interesting applications combining natural language (NL) with software artefacts. A couple of examples are the generation of code excerpts from NL instructions or the verbalization of programs in NL to facilitate their comprehension. Many of these language models have been trained with open source software datasets and therefore "understand" a variety of programming languages, but not OCL. We argue that OCL needs to jump into the machine learning bandwagon or it will risk losing its appeal as a constraint specification language. For that, the key first task is to create together an OCL corpus dataset amenable for natural language processing.