Miracle-dz/UniFAR-FTUs huggingface dataset:
From War to Peace, from Chaos to School: A Study Among Asylum-Seeking Families in Switzerland

The "migrant crisis" has received a large media coverage addressing the ways to limit refugees' settlement in European countries. Although an increasing number of asylum seekers are or will be admitted in the different states, little attention is devoted to the receiving conditions in the countries of settlement. Yet, a great amount of the incomers involve families with children, so that the schooling issue should be regarded as a major challenge for the receiving countries. Indeed, according to the largely ratified Convention on the Rights of the Child (1989), the right to education has to be implemented irrespective of the family legal status. In this paper, we will show that systematically evaluating these pupils' resources and needs in their mother tongue should be regarded as a key for their adequate orientation into the new school system. We will report situations ranging from illiteracy to unexpected skills acquired through informal schooling or makeshift means. Moreover, on the basis of a series of interviews with the families of newly arrived pupils, we will highlight the schooling impairments these children have experienced in their home country or during their fleeing journey. We will contend that identifying these pupils' needs and resources is a decisive tool against their undiscriminated relegation into special structures, as a result either of stereotyping or of teachers' feeling of helplessness -which are often intertwined. 1
Gender Gaps in Pay and Inter-Firm Mobility

The gender gap in inter-firm mobility is an important contributor to the gender pay gap but is as yet unexplained. In a structural model of workplace choice, I show that the gender mobility gap can be understood as a consequence of women's typical roles as secondary earners in most households which induces households to put more weight on the non-pay dimensions of women's workplaces. I provide direct empirical evidence for this explanation by documenting that the sensitivity of quits to wages is weaker the less an individual contributes to household earnings. Furthermore, gender differences are small once differences in earner roles are accounted for. My quantitative model evaluations show that ignoring the influence of earner roles on inter-firm mobility leads to substantial biases in wage-gap decompositions and predicted policy effects.
A polynomial lower bound on adaptive complexity of submodular maximization

In large-data applications, it is desirable to design algorithms with a high degree of parallelization. In the context of submodular optimization, adaptive complexity has become a widely-used measure of an algorithm’s “sequentiality”. Algorithms in the adaptive model proceed in rounds, and can issue polynomially many queries to a function f in each round. The queries in each round must be independent, produced by a computation that depends only on query results obtained in previous rounds. In this work, we examine two fundamental variants of submodular maximization in the adaptive complexity model: cardinality-constrained monotone maximization, and unconstrained non-mono-tone maximization. Our main result is that an r-round algorithm for cardinality-constrained monotone maximization cannot achieve an approximation factor better than 1 − 1/e − Ω(min{ 1/r, log2 n/r 3 }), for any r < n c (where c>0 is some constant). This is the first result showing that the number of rounds must blow up polynomially large as we approach the optimal factor of 1−1/e. For the unconstrained non-monotone maximization problem, we show a positive result: For every instance, and every δ>0, either we obtain a (1/2−δ)-approximation in 1 round, or a (1/2+Ω(δ2))-approximation in O(1/δ2) rounds. In particular (and in contrast to the cardinality-constrained case), there cannot be an instance where (i) it is impossible to achieve an approximation factor better than 1/2 regardless of the number of rounds, and (ii) it takes r rounds to achieve a factor of 1/2−O(1/r).
Robust consistency of choice switching in decisions from experience

Decision making is a multifaceted process but studies of individual differences in decision behavior typically use only the proportions of choices from different options as behavioral indices. I examine whether the probability of choice switching in decisions from experience, reflecting one’s exploration strategy, is consistent across sessions and tasks. In Study 1, I re-analyzed an experiment in which participants performed six decision tasks in two sessions that were 45 days apart. Choice switching rates were highly consistent across sessions and tasks, and their consistency exceeded that of rates of risky choices. In Study 2 I conducted a similar analysis for the Technion Prediction Tournament, and also found higher consistency across tasks in switching rates than in choice rates. Additionally, in both studies, there were moderate to high correlations between switching rates at the beginning and towards the end of the task. The results thus highlight an often overlooked but highly consistent and independent aspect of human behavior.
Corner detection of deformable fabric using Deep Learning

Robotic manipulation of deformable objects such as a towel is one of the most challenging tasks in the field of service robotics. Their unpredictable shape and pose makes it difficult to identify the most relevant parts than can be used for grasping. In this report we design a deep neural network that finds all the visible corners of a wrinkled towel. We also create a dataset to train the network. The results obtained show that it is possible to detect the corners of a cloth, but with some constraints due to the small number of images inside the dataset. Institut de Robòtica i Informàtica Industrial (IRI) Consejo Superior de Investigaciones Cient́ıficas (CSIC) Universitat Politècnica de Catalunya (UPC) Llorens i Artigas 4-6, 08028, Barcelona, Spain Tel (fax): +34 93 401 5750 (5751) http://www.iri.upc.edu Corresponding author: Albert Mitjans Coma tel: +34 93 401 0775 amitjans@iri.upc.edu http://www.iri.upc.edu/staff/amitjans
THERMODYNAMICS STUDY OF SIMPLIFIED SBF SOLUTIONS

This work is an attempt to study under thermodynamics approach some similar body fluids (SBF) with a simplified number of reagents in order to allow the homogeneous precipitation of hydroxyapatite. The Debye-Hückel’s model of activity coefficient was used as well as chemical equilibrium and mass balance equations to model the multielectrolyte system at 298K. Initially were considered ten reagents that are usually employed as raw material to produce SBF. Subsequently some reagents were selectively eliminated, that is their concentrations are equaled to zero. Then, equilibrium calculations were performed with a computational program based on multi-variable NewtonRaphson method, where the concentration and activity of each chemical specimen present in solution is considered. Besides, some modified chemical formulations were simulated in respect to free Gibbs energy change, Ca/P ratio and supersaturation.
Factors associated with telemedicine use in a tertiary care pediatrics center-A cross-sectional study

Introduction: While quality health-care is considered a fundamental human right for all citizens; the challenge remains in making it accessible to all. Information systems have been identified as possible solution that can be used to alleviate disparity between rural and urban healthcare services and bridge the digital divide. Literature has suggested that one of the barriers for successful implementation of health information system is the user acceptance by health care personnel. Objectives: To assess the factors associated with telemedicine use in a tertiary care pediatric center. Method: This is a cross-sectional study, using mixed methods to obtain data from a sample of research participants from tertiary care pediatrics center during July to October 2017. Results: In general the health-care personnel were aware of the benefit of tele-medicine to improve effectiveness and efficiency of the health care system. The barriers to the effective implementation of tele-medicine include lack of knowledge and lack of awareness regarding use and usage of the tele-medicine system. Conclusion: Health care personnel do acknowledge that tele-medicine can help to increase the effectiveness of the healthcare system. In general the acceptance of tele-medicine among healthcare personnel is positive. However in order to integrate it into standard work practices, specific training and capacity building for tele services is essential among health care personnel.
Differentiable Mapping Networks: Learning Task-Oriented Latent Maps with Spatial Structure

To efficiently operate in previously unseen environments, robots must be able to build a map – an internal representation of the environment – even from a small number of observations. But how should that map be represented and which information should be stored in it, to enable downstream tasks, for example localization? Classic approaches use a fixed map representation with strong spatial structure, such as voxels or point clouds, which makes them applicable to wide range of robotic tasks. Data-driven approaches, on the other hand, are able to learn rich and robust representations by optimizing them directly for a downstream task. Eslami et al. [4], for example, learn to construct representations of simulated environments from a few images that allow them to generate images from novel viewpoints. The challenge for learning in complex environments is choosing suitable inductive bias that enable generalization while having only limited amount of data for training. A desirable approach would combine the best of both worlds: retain the spatial structure of the classic approaches, but also leverage the power of deep neural networks to learn a flexible and effective map representation for the downstream task.
ELASTOHYDRODYNAMICS OF SLOT COATING PROCESS WITH DEFORMABLE ROLL

Slot coating is largely used in the manufacturing process of many products. In general, the minimum thickness that can be coated is proportional to the gap between the coating die and the substrate (usually backed-up by a rigid roll) and inversely proportional to the liquid viscosity. Therefore, in order to obtain thin films with liquid of high viscosity, a very small gap would be necessary. In practice, the clearance between the die and the web has to be large enough to avoid the risk of clashing two hard surfaces. A common solution is the use a backup rolls covered with an elastomeric layer. The liquid in the coating bead develops high enough pressure to deform the resilient cover, which changes the geometry of the flow, characterizing an elastohydrodynamic action. The understanding of the flow is vital to the optimization of this widely used coating method The theoretical model presented in this work takes into account the viscous flow, the roll deformation and the free surface effects in order to predict the flow behavior. It consisted of solving the Navier-Stokes equation to describe the free surface flow coupled with an array of springs to model the elastic cover deformation. The equation system was solved by the Galerkin / Finite element method. The resulting set of non-linear algebraic equations was solved by Newton’s method. The results indicate how different operating parameters, liquid and roll cover properties affect the flow.
Mobile apps for homeless people: Co-creation of Information Solutions for Digital Inclusion

This research focuses on the reduction of the digital divide in the Netherlands. It tries to do this by using an application that promotes inclusion for the homeless. At the moment this group finds it difficult to find important information online, while in the form of a smartphone and public Wi-Fi networks they have the tools to be able to gather this information online. In collaboration with the target group and by making use of the ICT4D 3.0 framework, an attempt was made to develop an application that could provide the homeless with practical, useful information. This paper explains how this process worked and whether such an application could be a solution.
Influencing Prejudice: Different Forms of Intergroup Contact and Sexism in Video Games

Video games have become a major manifestation of digital innovations in a digitized contemporary society. However, the societal implications of the diffusion of video games into society are dealt with shabbily in existing information systems research. With this study, we want to make a first step to close this gap by looking at intergroup contact between males and females in video games and subsequent effects on prejudice (specifically sexism). Therefore, we build our study around the social identity approach and the contact hypothesis from sociology and social psychology. Accordingly, we propose four different forms of indirect intergroup contact having different effects on prejudice: 1) positive human, 2) negative human, 3) positive avatar, and 4 ) negative avatar intergroup contact. Within the paper we illustrate the theoretical background, our methodological approach, and give a short outlook.
Information Salience and Mispricing in Housing

Making the purchase price fully salient to consumers has been shown to affect demand and equilibrium prices in various markets. Using a setting where part of the home acquisition price is in the form of nonsalient debt, we show this can happen in housing—a market where a typical household makes its largest acquisition. A regulation that made the debt and the total price salient for homebuyers eliminated a large mispricing caused by consumers’ inattention to the debt before the regulation. An average homebuyer would lose about $13,300 by acquiring a dwelling with one-standard deviation ($51,000)-higher debt, but this is nearly eliminated after the regulation. To shed light on the underlying channels, we use administrative data and show that young, financially inexperienced, and first-time homebuyers used to overpay the most. The results are not driven by rational channels based on liquidity constraints and adverse selection. Our findings imply that making all-inclusive house price and mortgage features salient at the time of advertising the sale can help avoid unintentional borrowing. This paper was accepted by David Simchi-Levi, finance.
Examining Individuals' Ads Click Intention in the Wechat Moments: A Lens of Elaboration Likelihood Model

Drawing upon elaboration likelihood model (ELM), we compared the dual routes in determining users’ ads click intentions and examined the mediation mechanism of cognitive vs. affective trust on the influence processes in the Wechat Moments. A scenario-based survey was conducted in a university of China, and 183 data was collected. Structural equation modelling analysis was used to test the research model. The empirical results suggested that content personalization and social recommendation were significant antecedents of ads click intention, and their effects were mediated by cognitive trust and affective trust. Moreover, a multi-group analysis indicated that the two influence processes were moderated by prior product experience. Theoretical and practical implications are illustrated in the final section.
Financing and Fiscality in the Context of Artificial Intelligence at the Global Level

The current financing models, as well as the fiscal models, are based on the current resources available at both the financial system and the fiscal system, but in close interdependence with those existing at the global level, the technology being one of them. Moreover, we consider that increasingly in the resource hierarchy, the place of the human factor is replaced by artificial intelligence (regardless of whether we are talking about industrial robots or intelligent technologies as is the case in the banking financial field). The new ways of approaching and coordinating finances aim to increase the degree of flexibility of financial networks and harmonize the results of those financial institutions that master and use complex but complementary technologies in order to obtain a final product or services optimal and with direct connection to its beneficiary. The defining elements for any financing and control model, regardless of whether we think of Fintech or other programs such as Fiscalis , are given by the following characteristics: digitization (artificial intelligence tools are crucial for digitizing financial services and fiscal), mobilization (virtual space offers not only the possibility but especially the platform for achieving the mobility of services), disintermediation (virtual space offers the possibility of direct access without intermediaries) and automation (through the financial services existing on the online platforms, the beneficiary of the service and the service provider optimizes its time and cost in favor of making the service profitable).
Does Shorttermism Shape up Mergers? Hedge Funds’ Role in M&As

Using the information on M&A deals from January 1995 to June 2009, the paper shows that holdings of target firms by hedge funds do not destroy shareholder value or lead to higher completion probabilities as is often feared in press. Hedge fund holdings, however, do shorten the duration of negotiations in successful deals, and impact the means of payment leading to higher proportion of cash offered. At the same time, hedge funds are more likely to accept overvalued bidder stock than other investors. The impact is especially pronounced for holdings of funds with short-term investment horizon, larger portfolio size and those following Event Driven styles.
How Do Companies Collaborate in Open Source Ecosystems? An Empirical Study of OpenStack

Open Source Software (OSS) has come to play a critical role in the software industry. Some large ecosystems enjoy the participation of large numbers of companies, each of which has its own focus and goals. Indeed, companies that otherwise compete, may become collaborators within the OSS ecosystem they participate in. Prior research has largely focused on commercial involvement in OSS projects, but there is a scarcity of research focusing on company collaborations within OSS ecosystems. Some of these ecosystems have become critical building blocks for organizations worldwide; hence, a clear understanding of how companies collaborate within large ecosystems is essential. This paper presents the results of an empirical study of the OpenStack ecosystem, in which hundreds of companies collaborate on thousands of project repositories to deliver cloud distributions. Based on a detailed analysis, we identify clusters of collaborations, and identify four strategies that companies adopt to engage with the OpenStack ecosystem. We alsofind that companies may engage in intentional or passive collaborations, or may work in an isolated fashion. Further, wefi nd that a com-pany's position in the collaboration network is positively associated with its productivity in OpenStack. Our study sheds light on howlarge OSS ecosystems work, and in particular on the patterns of collaboration within one such large ecosystem.
Student Project Proposal First Class Serialization for Distributed Haskells

3. Multi-paradigm Parallel Programming Models A CloudHaskell fork that also uses the Eden serialization support opens up a new direction for the project. CloudHaskell is an implementation of the actor model. HdpH is an implementation of the dataflow model. The two models are quite different. Even if the Eden RTS provides a unified serialization mechanism, it is an open question whether an intersection of CloudHaskell and HdpH could reveal a useful multi-paradigm parallel programming model. Section 4.3.
Hybrid Orientation of Organizational Identity and Its Relation to Particular Organizational Components

In coping with organizational changes in the current turbulent environment, focus is primarily placed on structural, "hard" factors, while socio-dynamic processes, which are related to them, are somewhat overlooked. Organizational identity represents the output of processes of staff identification with the organization. We focus on four types of organizational identity orientation: team, working groups, individual and especially hybrid. The goal of this paper is to detect whether the presumed heritage of identity of the socialist organization - in the form of hybrid orientation - persists in the period of transition, and how this orientation relates to selected characteristics of organizations today. Our study is based on the questionnaire survey among 219 organizations and shows that hybrid orientation of identity is still present either directly or can be hidden behind the form of working groups. Results of multiple ordinal regression analysis demonstrate that hybrid orientation of identity prevails in organizations with weak organizational culture that can provide an environment for the manipulative enforcement of individual interests. Our study is an attempt to understand how differences in organizational design may be associated with the arrangement of social relations and be reflected in the form of organizational identity orientations. A better understanding of these processes can improve managerial decision-making in situations when the change of external conditions raises the change of internal settings.
Towards An Artificial Intelligence Maturity Model: From Science Fiction To Business Facts

Artificial intelligence (AI) has become increasingly prevalent in organisations in different sectors. The rapid development of AI technology has rendered it essential to understand strategies for its implementation. Despite current trends, the uncertainties in the process required to establish strong AI capabilities are the major concerns for high level management. Therefore, this research-in-progress aims to understand AI practices in organisations through the development of an organisation-level AI maturity model (AIMM). However, to the best of our knowledge, no fully developed and theoretically derived AI maturity model currently exists. This research, therefore, represents an early attempt to develop an AI maturity model at the level of organisations; the results of this research will provide organisations with insights into the successful evolution and adoption of AI and can be used as a theoretical foundation for future research.
USE OF METHODS BASED ON TIME SERIES FOR IMPROVEMENT OF THE ACCURACY OF THE DEMAND FORECAST IN A PARTS DISTRIBUTION CENTER: A CASE STUDY

During some decades, the instability of the economy and the difficulties of forecast hindered the full development and application of demand forecasts methods. Currently, the Brazilian economy is presenting a low inflation and a relative stability, which leads to a more predictable demand of sales. A Parts Distribution Center (PDC) needs a good demand forecast, because its supply has a great amount of parts. The demand forecast can be carried out by two forms: qualitative or quantitative. Currently, the studied PDC uses only the qualitative method of the consensus of executives to make the demand forecast. This method is expensive in terms of cost and time, because it is based on the experience and the specialized knowledge to foresee the future. The objective of this article is to analyze different quantitative methods based on the time series to select the most adequate in comparison to the method used currently for the improvement of the accuracy of the demand forecast. These methods had been applied from a two year period interval data and after it the forecast was realized for one year in the future. This forecast was compared with real a demand of the period.