Miracle-dz/UniFAR-FTUs huggingface dataset:
An Emotion-driven Approach to Hospital Physicians’ Work-Related User Experience

Recent studies have found a correlation between information technology use and physician burnout, though little is known about physicians’ workplace user experience. Thus, this paper examines physicians’ work with electronic medication orders through a user experience and well-being lens. We interviewed ten physicians working clinically at a large Swedish hospital and analyzed their experiences qualitatively from an emotion-driven perspective. Participants’ stories were associated with joy, relaxation, confusion, anxiety, and frustration. On this basis, we formulated four UX goals: I feel joy as I complete my IT-supported tasks quickly and effortlessly, the steps I carry out feel meaningful as I understand their purpose, I feel confident on how to proceed to produce the outcome I want, and I experience relaxation as I feel supported in minimizing risk of patient harm. By (re)designing health IT systems and practices to foster these positive experiences, health IT designers may improve physician work well-being.
A Survey on Parallelism and Determinism

Parallelism is often required for performance. In these situations an excess of non-determinism is harmful as it means the program can have several different behaviours or even different results. Even in domains such as high-performance computing where parallelism is crucial for performance, the computed value should be deterministic. Unfortunately, non-determinism in programs also allows dynamic scheduling of tasks, reacting to the first task that succeeds, cancelling tasks that cannot lead to a result, and so on. Non-determinism is thus both a desired asset or an undesired property depending on the situation. In practice, it is often necessary to limit non-determinism and to identify precisely the sources of non-determinism to control what parts of a program are deterministic or not. This survey takes the perspective of programming languages, and studies how programming models can ensure the determinism of parallel programs. This survey studies not only deterministic languages but also programming models that prevent one particularly demanding source of non-determinism: data races. Our objective is to compare existing solutions to the following questions: How programming languages can help programmers write programs that run in a parallel manner without visible non-determinism? What programming paradigms ensure this kind of properties? We study these questions and discuss the merits and limitations of different approaches.
A Research on University Students' Behavioral Intention to use New-generation Information Technology in Intelligent Foreign Language Learning

A better understanding of how advancement in science and technology affect students’ learning behavior in academic setting can help all educators in higher education. With the advancement of science and technology, the new-generation information technology represented by "Cloud Computing, Big Data, Internet of Things, Mobile Network and Artificial Intelligence" has been profoundly changing the form of education, accelerating the transformation from Teaching 1.0 to Learning 2.0. To investigate the factors influencing university students using new generation of information technology in intelligent foreign language learning, this study proposed a research model based on Technology Acceptance Model (TAM). The sample data were collected from a survey of 237 students at a university. The analysis of structural equation modeling indicated that perceived usefulness, perceived ease of use, construction of foreign language intelligence classroom, and computer self-efficacy all have a positive impact on learners’ behavioral intention. These findings suggest that more emphasis should be laid on students’ learning characteristics, advantages of new generation of technology, as well as teachers’ intelligent literacy, so as to further promote the deep integration of the new-generation information technology and intelligent foreign language learning, improving the learning effectiveness ultimately and effectively.
Collaboration as a Driving Factor for Hit Song Classification

The Web has transformed many services and products, including the way we consume music. In a currently streaming-oriented era, predicting hit songs is a major open issue for the music industry. Indeed, there are many efforts in finding the driving factors that shape the success of songs. Yet another feature that may improve such efforts is artistic collaboration, as it allows the songs to reach a wider audience. Therefore, we propose a multi-perspective approach that includes collaboration between artists as a factor for hit song prediction. Specifically, by combining online data from Billboard and Spotify, we model the issue as a binary classification task by using different model variants. Our results show that relying only on music-related features is not enough, whereas models that also consider collaboration features produce better results.
AGE AND STRUCTURE PARAMETERS OF THE REMOTE M31 GLOBULAR CLUSTER B514 BASED ON HST, 2MASS, GALEX, AND BATC OBSERVATIONS

B514 is a remote M31 globular cluster (GC) which is located at a projected distance of Rp ≃ 55 kpc. Deep observations with the Advanced Camera for Surveys on the Hubble Space Telescope are used to provide accurate integrated light and star counts of B514. By coupling the analysis of the distribution of the integrated light with star counts, we are able to reliably follow the profile of the cluster out to ∼40″. Based on the combined profile, we study in detail its surface brightness distribution in the F606W and F814W filters and determine its structural parameters by fitting a single-mass isotropic King model. The results showed that the surface brightness distribution departs from the best-fit King model for r > 10″. B514 is quite flat in the inner region and has a larger half-light radius than the majority of normal GCs of the same luminosity. It is interesting that, in the MV versus log Rh plane, B514 lies nearly on the threshold for ordinary GCs as defined by Mackey & van den Bergh. In addition, B514 was observed as part of the Beijing–Arizona–Taiwan–Connecticut (BATC) Multicolor Sky Survey, using 13 intermediate-band filters covering a wavelength range of 3000–8500 Å. Based on aperture photometry, we obtain its spectral energy distributions (SEDs) as defined by the 13 BATC filters. We determine the cluster's age and mass by comparing its SEDs (from 2267 to 20000 Å, comprised of photometric data from the near-ultraviolet band of the Galaxy Evolution Explorer, 5 Sloan Digital Sky Survey bands, 13 BATC intermediate-band filters, and Two Micron All Sky Survey near-infrared JHKs filters) with theoretical stellar population synthesis models, resulting in an age of 11.5 ± 3.5 Gyr. This age confirms the previous suggestion that B514 is an old GC in M31. B514 has a mass of 0.96–1.08 × 106 M☉ and is a medium-mass GC in M31.
Several Results in Black Hole Nonformation

Black Hole Nonformation was suggested in 2006 by Vachaspati, Stojkovic and Krauss as a sensible solution to the paradox of information, as deduced from calculations in the semiclassical theory of Gravitation. Our own results in the context of classical General Relativity (with the addition of several thermodynamic argumentations) led us to an equivalent statement: collapsing bodies emit their complete amount of mass and energy as radiation before the formation of any event horizon. In this paper, we submit the metric we rendered to the test of Einstein Field Equations, and we propose some modifications to extend our solutions to more general situations, as the initial moments of collapse and electrically charged collapses, as well as we effectuate some considerations about rotating collapses.
Human-Centered AI Design in Reality: A Study of Developer Companies’ Practices : A study of Developer Companies’ Practices

Human-Centered AI (HCAI) advocates the development of AI applications that are trustworthy, usable, and based on human needs. While the conceptual foundations of HCAI are extensively discussed in recent literature, the industry practices and methods appear to lag behind. To advance HCAI method development, current practices of AI developer companies need to be understood. To understand how HCAI principles manifest in the current practices of AI development, we conducted an interview study of practitioners from 12 AI developer companies in Finland, focusing on the early stages of AI application development. Our thematic analysis reveals current development practices and identifies four main challenges: (i) detachment of HCAI work from technical development, (ii) clients’ central role as the source of user requirements, (iii) uncertain nature of AI, and (iv) lack of value-based understanding of AI. The findings inform the development of HCAI methods and implementation of HCAI principles in AI application development.
Geração Automática de Benchmarks para Compilação Preditiva

O treinamento de um compilador preditivo requer uma quantidade muito vasta de benchmarks, que aproxime o universo de programas que o compilador irá encontrar durante sua utilização. Atualmente existem diversas técnicas para gerar benchmarks para calibrar compiladores preditivos. Contudo, essas técnicas, quando aplicadas a linguagens inseguras, como C, C++ ou dialetos de montagem, tendem a esbarrar em um desafio: a geração de códigos executáveis. A dificuldade em detectar comportamento indefinido, somada à dificuldade de criar entradas que executem vários caminhos de um mesmo programa, torna a geração de benchmarks executáveis um desafio. Este artigo descreve Jotai, um conjunto de aproximadamente 30 mil programas executáveis, minerados a partir de repositórios de código aberto. Jotai usa um inferidor de tipos publicamente disponível para garantir que códigos minerados automaticamente possam compilar, e usa uma linguagem de domínio específico para gerar entradas válidas para programas. Essa coleção pôde ser utilizada para prever o benefício advindo de otimizações de código; para encontrar boas configurações para as diferentes heurísticas usadas por compiladores; e para analisar correlações, por exemplo, entre o número de instruções processadas durante a execução de um programa e o tempo que esse programa leva para terminar.
The influence of mass-transfer variability on the growth of white dwarfs, and the implications for Type Ia supernova rates

White dwarfs (WDs) can increase their mass by accretion from companion stars, provided the mass-accretion rate is high enough to avoid nova eruptions. The accretion regimes that allow growth of the WDs are usually calculated assuming constant mass-transfer rates. However, it is possible that these systems are influenced by effects that cause the rate to fluctuate on various timescales. We investigate how long-term mass-transfer variability affects accreting WDs systems. We show that, if such variability is present, it expands the parameter space of binaries where the WD can effectively increase its mass. Furthermore, we find that the supernova type Ia (SNIa) rate is enhanced by a factor 2-2.5 to a rate that is comparable with the lower limit of the observed rates. The changes in the delay-time distribution allow for more SNIae in stellar populations with ages of a few Gyr. Thus, mass-transfer variability gives rise to a new formation channel of SNIa events that can significantly contribute to the SNIa rate. Mass-transfer variability is also likely to affect other binary populations through enhanced WD growth. For example, it may explain why WDs in cataclysmic variables are observed to be more massive than single WDs, on average.
Design Thinking and Non-Functional Requirements Elicitation: A Survey

Design Thinking (DT) is a human-centered approach used in innovative problem-solving. In software development projects, it can be usually applied as a toolbox, mindset or process. Moreover, DT has seen a large rise in popularity over the past decade, especially in its upfront use for eliciting requirements. Despite its many benefits and successful use cases in this scenario, some of the shortcomings related to its uses in Requirements Engineering (RE) have started to show up. One of them lies in the difficulty with eliciting other non-functional requirements (NFR) – besides usability –, possibly jeopardizing the subsequent software development life-cycle if these requirements are not properly addressed. This article presents a qualitative survey conducted via LinkedIn with 53 software developers that have had previous experiences with the use of DT as an upfront process in software projects. The focus of the research has been on identifying the existence of problems, how they became manifest, and whether the software community has tools for mitigating them. The results suggest the neglect of DT for requirements other than those of a functional or usability nature in this situation. Since this use of DT is focused on improving the users’ experience, and identifying their needs, we argue that such needs are not limited only to the functions of a software or its usability. In fact, we also advocate that other aspects that are intrinsic to NFR, such as performance and reliability are part of such needs.
Investigating Systems Engineering Approaches in the Norwegian Construction Industry: A Multi‐Case Study

There is an increasing application of Systems Engineering in the Norwegian construction industry. This paper investigates the effects of a Systems Engineering approach on project management performance, prerequisites for success, and which elements contribute to effectiveness from a technical contractor perspective. First, we find a positive perception of Systems Engineering's effect on time, cost, and quality. Second, we provide and rank a list of 12 prerequisites for success. Third, we quantify the perceived importance of five elements of the systems engineering process. Finally, we find a disconnect between what seems to be essential processes and prerequisites and what gets done in practice. To improve Systems Engineering performance, we recommend improving Systems Engineering competence and capabilities, increasing the formality of requirements analysis and documentation, and front‐loading the effort and allocation of resources in projects.
Enabling the Systems Engineering Education Ecosystem (SEEE)

System engineering education is challenged to address the need posed by rapidly changing technology epitomized by Industry 4.0 and the digital transformation. In particular, there are relatively slow and inaccurate feedback mechanisms between the needs of employers, students and universities at the level of educational program content development. To address this issue, the Systems Engineering Education Ecosystem (SEEE) was established to create and assess the feedback mechanisms by which educators, students and employers can communicate their specific educational capabilities, desires and needs, in order to provide the dynamic feedback necessary to accelerate the evolution of graduate Systems Engineering (SE) educational programs, clearly communicate the characteristics of existing programs, provide access to relevant educational materials, and create a dynamic self‐evolving educational system. This paper describes the vision, objectives, design and development process, current status and future developments, with the intention to support a global systems engineering education ecosystem.
Automatic Text Classification of PDF Documents using NLP Techniques

One of the regular activities performed by engineers during the design and development of the technical systems is to determine which sentences in a PDF specification document represent a requirement, functional architecture, design solution, variability, or other types of systems engineering (SE) data. Extracting such data from these PDF documents and transferring it into system model elements is still performed manually, requires high effort, and is error prone. Hereby, automatic extraction and classification of such SE data has a great potential, but it is still relatively scarce and a challenging task for engineers working with large PDF specification documents. One solution is to follow a suitable writing formulation which provide an immediate and easy way to classify and analyze the PDF documents. However, such formulations are not always followed strictly. As part of our work towards adopting Artificial Intelligence (AI) for Model‐Based Systems Engineering (MBSE), we have been researching the data extraction and data classification topics from PDF files in order to transfer it to system models elements. In this paper, we present the early status of a solution based on AI that uses Natural Language Processing (NLP) techniques to label the SE data existing in PDF files, extract them, and classify them into predefined classes.
Systems Engineering Integration and Test Challenges due to Security Measures in a Cloud‐Based System

Cloud based systems have become popular with company's Chief Information Officers and Chief Technical Officers due to their ability to support a wide range of Web based applications and services including; scalability to allow users to increase/decrease their cloud footprint real time based on demand, load balancing to optimize computing performance, and failover which allows processing/memory assets to be reassigned real time when a failure is detected or predicted on the current processing assets. In addition, organizations can lower their Information Technology (IT) costs by deferring their infrastructure maintenance/costs to the Cloud Service Provider (CSP). However, Cloud‐based security threats and mitigations are well documented in literature, and address multiple client side, network, and cloud side (service/application and data) vulnerabilities. Defined mitigations include the use of access control, encryption, key management, digital signatures, and intrusion detection/prevention systems to yield a secure cloud‐based system. Implementing these security measures adds significant system functionality to the already complex cloud‐based system that must be assessed by the system architect. The additional requirements and development must be managed by the systems engineering team, and the increased integration and test must be addressed by the systems engineering integration and test lead. This paper will highlight the scope growth realized when a system interfaces into the cloud, relative to equivalent non‐cloud based systems. The added scope will be shown to include the development, integration and test of security related hardware and software configuration items, development of significant integrated test equipment/test vectors to verify the security functionality over a wide range of conditions, multiple cooperative systems/software led activities to analyze and test software throughout its development, and the system accreditation efforts to get authorization to tie into the cloud. With this information, the systems engineering leads will have a better understanding of the challenges involved with integrating and testing a cloud‐based system and can then properly plan and budget for this activity. This paper will focus specifically on a public cloud based implementation. Hybrid and private cloud implementations will not be addressed herein.
A generic hierarchical System of Systems Engineering (SOS) Approach for Model based System Engineering (MBSE) Projects

Model based systems engineering (MBSE) has been accepted worldwide by many industries, including the automotive industry, for several years. Hundreds of projects have already been developed and deployed using MBSE approaches. MBSE is gaining importance because it provides systems advantageous life cycle processes, such as returns of investments and meeting the demands of global marketplaces, as they become increasingly complex. Consequently, the number and pace of deployment using MBSE approaches will increase in the future.
A catalog of quality criteria to guide the assessment of applications' privacy policies

Context: The information about personal data processing must be described in the companies' privacy policies. Problem: privacy policies are long documents, full of jargon, and do not always comply with the current privacy law. Besides, the privacy policies should be consistent with requirements document and application behavior, hence, it is of paramount importance that stakeholders should be able to evaluate the quality of the privacy policies. Objective: This work proposes a catalog of criteria for assessing the quality of privacy policies. Method: the snowballing technique was performed to find relevant studies that evaluate privacy policies. Results: The proposed catalog, elaborated from the empirical results of 48 studies, has 29 different criteria grouped into five categories. Contributions: The developed catalog can help: (i) requirements engineers to check the consistency of the privacy policies content with the requirements document; (ii) writers to create more precise and complete documents regarding users' rights in accordance with the requirements document, (iii) analysts and developers to make them more straightforward which information must be properly documented about the practice of data collection; (iv) end-users to understand the content of the privacy policies.
Loop amplitudes, anomalies and phenomenology

Preface 8. One-loop diagrams in the bosonic string theory 9. One-loop diagrams in superstring theory 10. The gauge anomaly in type I superstring theory 11. Functional methods in the light-cone gauge 12. Some differential geometry 13. Low-energy effective action 14. Compactification of higher dimensions 15. Some algebraic geometry 16. Models of low-energy supersymmetry Bibliography Index.
A Discrete-Continuous Algorithm for Globally Optimal Free Flight Trajectory Optimization

We present an efficient algorithm that finds a globally optimal solution to the 2D Free Flight Trajectory Optimization Problem (aka Zermelo Navigation Problem) up to arbitrary precision in finite time. The algorithm combines a discrete and a continuous optimization phase. In the discrete phase, a set of candidate paths that densely covers the trajectory space is created on a directed auxiliary graph. Then Yen’s algorithm provides a promising set of discrete candidate paths which subsequently undergo a locally convergent refinement stage. Provided that the auxiliary graph is sufficiently dense, the method finds a path that lies within the convex domain around the global minimizer. From this starting point, the second stage will converge rapidly to the optimum. The density of the auxiliary graph depends solely on the wind field, and not on the accuracy of the solution, such that the method inherits the superior asymptotic convergence properties of the optimal control stage