Miracle-dz/UniFAR-FTUs huggingface dataset:
Retirement timing and grandparenthood in Sweden : Evidence from population-based register data

OBJECTIVES This study addresses the importance of grandparenthood in relation to retirement timing in Sweden. It extends previous research by assessing a number of grandparental characteristics, such as being a grandparent, a grandparent’s age and gender, number of years since the transition to grandparenthood, number of grandchildren, number of grandchild sets, and age of the youngest grandchild, while simultaneously controlling for other central predictors of retirement timing. METHOD The study uses survival analysis on Swedish population register data for cohorts born between 1935 and 1945 over the 1993‒2012 period. RESULTS The results indicate that grandparents have a higher retirement risk than nongrandparents, even after controlling for age and other central predictors of retirement. The results also show that those who have been grandparents for more than two years have a higher risk of retirement; however, there is variation with respect to the age of the grandparent. In addition, grandparents with multiple grandchildren and grandchild sets exhibit an increased risk of retirement. The study does not find strong differences between grandmothers’ and grandfathers’ retirement timing. CONCLUSION The study finds that grandparents at different life stages have an elevated risk of retirement compared with non-grandparents, but there is also variation among grandparents, and the more complex the family situation, the higher the risk of retirement. CONTRIBUTION The inclusion of grandparenthood enriches the understanding of the complexity of the retirement decision and indicates that this decision is more closely linked to intergenerational family structures than the literature has previously shown. 1 Department of Sociology, University of Stockholm, Sweden. E-Mail: linda.kridahl@sociology.su. se. Kridahl: Retirement timing and grandparenthood in Sweden: Evidence from population-based register data 958 http://www.demographic-research.org
Data-Mining für die Analyse von Nachfrage und Angebot im Revenue Management am Beispiel von Fluggesellschaften

Nachfrageprognose und Angebotsteuerung werden im Revenue Management zunehmend auf die Betrachtung komplementare und substituierbare Produkte ausgeweitet. Im Revenue Management bedeutet dies die Prognose und Optimierung auf der Ebene von Reisewegen, Verkaufsstandorten, Buchungsklassen und Buchungsklassengruppen. Diese detaillierte Betrachtungsweise ermoglicht eine gezielte Optimierung der Angebotssteuerung, doch sie erhoht auch die Komplexitat des Modells. Dieses Paper prasentiert eine Moglichkeit zur Analyse und Klassifikation von Nachfrage und Angebot durch die Anwendung von Data-Mining. Eine entsprechende Klassifikation bildet eine Moglichkeit, das Problem kleiner Zahlen und den Aufwand komplexer Einflusse zu reduzieren.
Function Tagging

Function tags are a context-sensitive annotation applied to words and phrases of natural language text, marking their syntactic or semantic role within a larger utterance. As researchers improve results on various other problems in “pure” natural language processing (e.g part-of-speech tagging, parsing), those who work in the more “applied” NLP fields (e.g. question-answering, temporal analysis) are seeking more powerful sorts of linguistic annotation as input for their own systems. Hence, function tags. In the first part of the thesis, I present the problem of function tagging: why it is an interesting problem, who has worked on similar thing, and what exactly I intend to do. I briefly review the function tags of the Penn treebank, and explain the specific metrics by which I will evaluate my work. In the second part of the thesis, I introduce the many features that I will use to train a function tagging system, and then I present some systems that make use of them: one using feature trees, one using decision trees (briefly), and one using perceptron models. For each system, I give a brief historical perspective, an overview of where it has been used before and why I think it will be useful in this task. I will then try a number of feature combinations with interesting properties; and finally, present the best-performing tweaked-out version of that system. Finally, in the third part of the thesis, I bring them all together and discuss the advantages and disadvantages of each system in various situations. More interestingly, I will present an analysis of what features prove to be the most helpful for the different function tagging subtasks. Lastly, I will present a comparison to other systems performing related tasks, and speculate on some interesting future work.
Utilizing fourth-generation endocytoscopy and the ‘enlarged nuclear sign’ for in vivo diagnosis of early gastric cancer

Abstract Background and study aims Fourth-generation endocytoscopy is an ultra-high magnification endoscopic technique designed to provide excellent quality in vivo histologic assessment of gastrointestinal lesions. This study aims to evaluate the diagnostic accuracy of endocytoscopy in early gastric cancer diagnosis. Patients and methods A single-center, retrospective analysis of prospectively collected data from all gastric endocytoscopic examinations was conducted. Two expert endoscopists, blinded to white-light and narrow-band imaging findings as well as histopathologic diagnosis, independently reviewed and diagnosed all endocytoscopic images. A newly recognized “enlarged nuclear sign” was detected, and its implication in early gastric cancer diagnosis was evaluated. The diagnostic performance of fourth-generation endocytoscopy was assessed while using the gold standard histopathology as a reference. Results Forty-three patients (mean age±SD, 72.6 ± 12.1 years; 31 males) were enrolled. Based on histopathology, 23 had well-differentiated adenocarcinomas, four adenomas, and 16 non-neoplastic lesions. The sensitivity, specificity, and accuracy of fourth-generation endocytoscopy for gastric cancer diagnosis were 87.0 % (95 % CI: 67.9 – 95.5), 80.0 % (95 % CI: 58.4 – 91.9), and 83.7 % (95 % CI: 70.0 – 91.9) by endoscopist A; and 91.3 % (95 % CI: 73.2 – 97.6), 75.0 % (95 % CI: 53.1 – 88.8), and 83.7 % (95 % CI: 70.0 – 91.9) by endoscopist B. The inter-observer agreement, Kappa statistic = 0.71 (95 % CI: 0.50 – 0.93), was good. The sensitivity, specificity, and accuracy of the enlarged nuclear sign for early gastric cancer diagnosis were 87.0 % (95 % CI: 67.9 – 95.5), 95.0 % (95 % CI: 76.4 – 99.1), and 90.7 % (95 % CI: 78.4 – 96.3) by endoscopist A; and 82.6 % (95 % CI: 62.9 – 93.0), 85.0 % (95 % CI: 64.0 – 94.8), and 83.7 % (95 % CI: 70.0 – 91.9) by endoscopist B. The inter-observer agreement, Kappa statistic = 0.68 (95 % CI: 0.51 – 0.89) was good. Conclusion: Fourth-generation endocytoscopy appears to aid in the diagnosis of early gastric cancer, particularly well-differentiated adenocarcinomas, due to its good diagnostic accuracy and identification of the “enlarged nuclear sign,” and deserves further evaluation in future studies.
Dysfunction telomeres in embryonic fibroblasts and cultured in vitro pluripotent stem cells of Rattus norvegicus (Rodentia, Muridae)

Abstract We studied the level of spontaneous telomere dysfunction in Rattus norvegicus (Berkenhout, 1769) (Rodentia, Muridae) embryonic fibroblasts (rEFs) and in cultured in vitro rat pluripotent stem cells (rPSCs), embryonic stem cells (rESCs) and induced pluripotent stem cells (riPSCs), on early passages and after prolonged cultivation. Among studied cell lines, rESCs showed the lowest level of telomere dysfunction, while the riPSCs demonstrated an elevated level on early passages of cultivation. In cultivation, the frequency of dysfunctional telomeres has increased in all studied cell lines; this is particularly true for dysfunctional telomeres occurring in G1 stage in riPSCs. The obtained data are mainly discussed in the connection with the specific structure of the telomere regions and their influence on the differential DNA damage response in them.
Design and analysis of multi-band circle shape MIMO antenna using defected ground structure to reduce mutual coupling

In the present paper, a multi-band circle shape MIMO radiator with and without dumbbell-shaped parasitic element for all wireless applications is proposed. The proposed antenna comprises MIMO circular shape radiating patch with U-shaped inverted slot and pair of rectangular slits. By adjusting U-shaped inverted slot, a pair of rectangular slits and neutralisation line we obtain distinct resonance frequencies centred at 3.5, 5.3, 7.0 and 8.8 GHz. The VSWR results are centred on ≤ 2 at these resonant frequencies. The far field values obtained at a wide operational bandwidth, the simulated results represent that the multi-band antenna can cover sufficient bandwidth for entire frequency bands. The multi-band antenna also shows a radiation pattern of an omni directional with an acceptable average peak gains at the resonant frequencies are 5.238 dBi, 7.044 dBi, 6.763 dBi and 7.852 dBi of LTE/WLAN bands, WiMAX band, and ITU and satellite band system applications.
A Computer Anxiety Model for Elderly Users Interacting with the Web

Even nowadays, the use of computers can be difficult for some people. The reason for that can be complex and multifactorial, such as lack of experience in using computers, lack of knowledge, problems related to usability and accessibility, fear, intimidation, or anxiety. Some people can experience multiple levels of anxiety and, for high ones, they manifest what is known as Computer Anxiety. People with Computer Anxiety (PwCA) face problems when using computers or technology at home, in the workplace, or for study purposes, which might result in multiple forms of barriers. This work reports a study that involved a pilot (4 elderly participants) and an experiment (39 elderly participants), contributing with a model that supports the identification of different levels of Computer Anxiety through the analysis of detailed interaction logs. Results show it is possible to automatically identify levels of Computer Anxiety in older adults while interacting with the web with 83.87% of accuracy. From the presented results, it is expected that specialists consider exploring the use of detailed interaction data and the presented model to identify Computer Anxiety levels, at scale, offering personalization, user interface simplification, removal of barriers, among other features to support this population.
Analysing socio-technical congruence in the package dependency network of Cargo

Software package distributions form large dependency networks maintained by large communities of contributors. My PhD research will consist of analysing the evolution of the socio-technical congruence of these package dependency networks, and studying its impact on the health of the ecosystem and its community. I have started a longitudinal empirical study of Cargo's dependency network and the social (commenting) and technical (development) activities in Cargo's package repositories on GitHub, and present some preliminary findings.
Applying the QuARS Tool to Detect Variability

In this demo paper we present how to use the QuARS tool to extract variability information from requirements documents. The main functionality of QuARS is to detect ambiguity in Natural Language (NL) requirement documents. Ambiguity in requirements may be due to intentional or unintentional indication of possible variability; an ambiguity detecting tool can hence be useful to analysts and clients to figure the potential of a requirements document to describe a family of different products.
Viterbi Extraction tutorial with Hidden Markov Toolkit

An algorithm used to extract HMM parameters is revisited. Most parts of the extraction process are taken from implemented Hidden Markov Toolkit (HTK) program under name HInit. The algorithm itself shows a few variations compared to another domain of implementations. The HMM model is introduced briefly based on the theory of Discrete Time Markov Chain. We schematically outline the Viterbi method implemented in HTK. Iterative definition of the method which is ready to be implemented in computer programs is reviewed. We also illustrate the method calculation precisely using manual calculation and extensive graphical illustration. The distribution of observation probability used is simply independent Gaussians r.v. s. The purpose of the content is not to justify the performance or accuracy of the method applied in a specific area. This writing merely to describe how the algorithm is performed. The whole content should enlighten the audience the insight of the Viterbi Extraction method used by HTK.
Intrinsically-Typed Mechanized Semantics for Session Types

Session types have emerged as a powerful paradigm for structuring communication-based programs. They guarantee type soundness and session fidelity for concurrent programs with sophisticated communication protocols. As type soundness proofs for languages with session types are tedious and technically involved, it is rare to see mechanized soundness proofs for these systems. We present an executable intrinsically typed small-step semantics for a realistic functional session type calculus. The calculus includes linearity, recursion, and recursive sessions with subtyping. Asynchronous communication is modeled with an encoding. The semantics is implemented in Agda as an intrinsically typed, interruptible CEK machine. This implementation proves type preservation and a particular notion of progress by construction.
Using software testing to repair models

Software testing is an important phase in the software development process, aiming at locating faults in artifacts, and achieve some confidence that the software behaves according to specification. There exists many software testing techniques applied to debugging, fault-localization, and repair of code, however, to the best of our knowledge, the application of software testing to locating faults in models and automatically repair them, is still an open issue. We present a project that investigates the use of software testing methods to automatically repair model artifacts, to support engineers in maintaining them consistent with the implementation and specification. We describe the research approach, the structure of the devised test-driven repair processes, present results in the cases of combinatorial models and feature models, and finally discuss future work of applying testing to repair models for other scenarios, such as timed automata.
Feature Modeling vs. Decision Modeling: History, Comparison and Perspectives

Modeling variability, i.e., defining the commonalities and variability of reusable artifacts, is a central task of software product line engineering. Numerous variability modeling approaches have been proposed in the last three decades. Most of these approaches are based on feature modeling (FM) or decision modeling (DM), two classes of variability approaches that go back to initial proposals made in the early 1990ies, i.e., FODA for FM and Synthesis for DM. This extended abstract summarizes the history of FM and DM as well as the results of a systematic comparison between FM and DM published earlier. We also outline perspectives, especially regarding potential synergies and key common elements that should be part of a standard variability modeling language.
Improving requirements engineering practices to support experimentation in software startups

The importance of startups to economic development is indisputable. Software startups are startups that develop an innovative software-intensive product or service. In spite of the rising of several methodologies to improve their efficiency, most of software startups still fail. There are several possible reasons to failure including under or over-engineering the product because of not-suitable engineering practices, wasted resources, and missed market opportunities. The literature argues that experimentation is essential to innovation and entrepreneurship. Even though well-known startup development methodologies employ it, studies revealed that practitioners still do not use it. Given that requirements engineering is in between software engineering and business, in this study, I aim to improve these practices to foster experimentation in software startups. To achieve that, first I investigated how requirements engineering activities are performed in software startups. Then, my goal is to propose new requirements engineering practices to foster experimentation in this context.
Generating query-specific class API summaries

Source code summaries are concise representations, in form of text and/or code, of complex code elements and are meant to help developers gain a quick understanding that in turns help them perform specific tasks. Generation of summaries that are task-specific is still a challenge in the automatic code summarization field. We propose an approach for generating on-demand, extrinsic hybrid summaries for API classes, relevant to a programming task, formulated as a natural language query. The summaries include the most relevant sentences extracted from the API reference documentation and the most relevant methods. External evaluators assessed the summaries generated for classes retrieved from JDK and Android libraries for several programming tasks. The majority found that the summaries are complete, concise, and readable. A comparison with summaries produce by three baseline approaches revealed that the information present only in our summaries is more relevant than the one present only in the baselines summaries. Finally, an extrinsic evaluation study showed that the summaries help the users evaluating the correctness of API retrieval results, faster and more accurately.
An Independent and Interactive Museum Experience for Blind People

Museums are gradually becoming more accessible to blind people, who have shown interest in visiting museums and in appreciating visual art. Yet, their ability to visit museums is still dependent on the assistance they get from their family and friends or from the museum personnel. Based on this observation and on prior research, we developed a solution to support an independent, interactive museum experience that uses the continuous tracking of the user's location and orientation to enable a seamless interaction between Navigation and Art Appreciation. Accurate localization and context-awareness allow for turn-by-turn guidance (Navigation Mode), as well as detailed audio content when facing an artwork within close proximity (Art Appreciation Mode). In order to evaluate our system, we installed it at The Andy Warhol Museum in Pittsburgh and conducted a user study where nine blind participants followed routes of interest while learning about the artworks. We found that all participants were able to follow the intended path, immediately grasped how to switch between Navigation and Art Appreciation modes, and valued listening to the audio content in front of each artwork. Also, they showed high satisfaction and an increased motivation to visit museums more often.
Automating Test Reuse for Highly Configurable Software

Dealing with highly configurable systems is generally very complex. Hundreds of different analysis techniques have been conceived to deal with different aspects of configurable systems. One large focal point is the testing of configurable software. This is challenging due to the large number of possible configurations and because tests themselves are rarely configurable and instead built for specific configurations. Existing tests can usually not be reused on other configurations. Therefore, tests need to be adapted for the specific configuration they are supposed to test. In this paper we report on an experiment about reusing tests in a configurable system. We used manually developed tests for specific configurations of Bugzilla and investigated which of them could be reused for other configurations. Moreover, we automatically generated new test variants (by automatically reusing from existing ones) for combinations of previous configurations. Our results showed that we can directly reuse some tests for configurations which they were not intended for. Nonetheless, our automatically generated test variants generally yielded better results. When applying original tests to new configurations we found an average success rate for the tests of 81,84%. In contrast, our generated test variants achieved an average success rate of 98,72%. This is an increase of 16,88%.
The repetition threshold for binary rich words

A word of length $n$ is rich if it contains $n$ nonempty palindromic factors. An infinite word is rich if all of its finite factors are rich. Baranwal and Shallit produced an infinite binary rich word with critical exponent $2+\sqrt{2}/2$ ($\approx 2.707$) and conjectured that this was the least possible critical exponent for infinite binary rich words (i.e., that the repetition threshold for binary rich words is $2+\sqrt{2}/2$). In this article, we give a structure theorem for infinite binary rich words that avoid $14/5$-powers (i.e., repetitions with exponent at least 2.8). As a consequence, we deduce that the repetition threshold for binary rich words is $2+\sqrt{2}/2$, as conjectured by Baranwal and Shallit. This resolves an open problem of Vesti for the binary alphabet; the problem remains open for larger alphabets.
Completing and Debugging Ontologies: State-of-the-art and Challenges in Repairing Ontologies

As semantically enabled applications require high-quality ontologies, developing and maintaining ontologies that are as correct and complete as possible is an important although difficult task in ontology engineering. A key task is ontology debugging and completion. In general, there are two steps: detecting defects and repairing defects. In this article, we discuss the state-of-the-art regarding the repairing step. We do this by formalizing the repairing step as an abductive reasoning problem and situating the state-of-the-art with respect to this framework. We show that there are still many open research problems and show opportunities for further work and advancing the field.
The Development of Web-based Graphical User Interface for Learning and Fitting Generalized Estimating Equation with Spline Smoothers

Statistical modeling (regression analyses) have been growing rapidly into various directions to accommodate various data conditions. For longitudinal or repeated measures data, one of the suitable models is GEE (Generalized Estimating Equation). In practice, to do complex modeling such as GEE, the use of statistical software is necessary and it is available on free open source software R. However, GEE modeling on R can only be access through command line interface (CLI), and most practical researchers very much rely on Graphical User Interface (GUI) based statistics software. To make access to GEE (both order 1 and 2) much easier, we developed, using Shiny toolkit, two types of web-based GUI, standard pull down menu type and e-module type (with narrative theories) that can be utilized for learning and fitting GEE. This paper discusses the features of the interfaces and illustrates the use of them.