Miracle-dz/UniFAR-FTUs huggingface dataset:
STRUCTURAL IVE FOR DYNAMIC TREATMENT EFFECTS: SPANKING EFFECT ON BEHAVIOR

Finding the effects of multiple sequential treatments on a response variable measured at the end of a trial is difficult, if some treatments are affected by interim responses; e.g., assessing the effects of spanking on behavior when parents adjust their spanking level depending on interim behaviors. A headway, ‘ Ge stimation’, has been made in 1980’s generalizing the usual static treatment effect analysis under ‘selection on observables’. But G estimation is hard to implement. In this paper, firstly, we propose a much simpler alternative to G estimation– a single or multiple IVE’s for a linear structural model–and show that our proposal and G estimation identify the same effect under some assumptions. Secondly, we explore the relation between our proposal and Granger causality to show that our approach is more general, although the two become equivalent for testing non-causality under a stationarity assumption. Thirdly, our approach and G estimation are applied to find the effects of spanking on behavior. We find that mild spanking at early years reduces a child’s behavior problems later, which seems to differ from most findings in the psychology literature.
R&D Spillovers, Concentration and Market Performance

In a two-stage R&D game of process innovation, we investigate the effect of exogenously changing R&D spillovers and market concentration on the equilibrium level of effective cost reduction, total output, profits and social welfare. Interpreting spillover as a measure of patent protection, we find that weaker patent protection results in less R&D. We also show that firms prefer weaker patent protection, but social welfare is maximized for higher levels of patent protection. In terms of market concentration we show that firm profits decrease with increasing numbers of firms. Social welfare is typically maximized under oligopoly with the optimal number of firms depending on the level of spillover and efficiency of R&D investment.
Unfortunately, Your Task Allocation is in Need of Improvement

This study investigates whether the informative content of negative robot feedback influences perceived adequacy of feedback and willingness to improve decisions made during an allocation task. For this purpose, 153 subjects received feedback from a robotic co-worker after an allocation task, which provided either process-level information, task-level information, self-regulation information, or person-specific feedback. As the results of this study indicate, negative robot feedback that is related to the task and contains information about the current progress and potentials for improvement is perceived as more appropriate and leads to a higher willingness to improve than feedback which is neither informative nor specific regarding the handled task.
Measuring Users' Attitudinal and Behavioral Responses to Persuasive Communication Techniques in Human Robot Interaction

Many social robots have been developed to support the needs of users, such as tour guides [1] or sales robots [2], [3]. In these systems, the main purpose of the human robot interaction is to support the user's need. However, what if in addition to these capabilities, the robot had a goal of persuading the user to do something of which the user had no knowledge. What would the user's perceptions on the interaction be? We developed a social robot with the ability to employ six types of persuasion conversation logic, namely, scarcity, emotion, social identity, commitment, concreteness, and no persuasion [4] and measured the users' attitudinal and behavioral responses when interacting with our robot. In this pilot study we describe our initial results with success rates varying across all six persuasion techniques. Particular persuasion techniques demonstrated as high as a 75% success rate at directing users towards a secret task.
How to Make Robots' Optimal Anthropomorphism Level: Manipulating Social Cues and Spatial Context for an Improved User Experience

With the growing interest in robot related research and industry, there is a demand to shape user experience more sophisticatedly in human-robot interaction. The purpose of this study is to define the elements for manipulating robot's verbal anthropomorphism and investigate the influence on user experience associated with spatial context. Based on the identified elements, we divided the robot's anthropomorphism into three levels (high, medium, low) and associated them with two spatial contexts (open, closed). The results revealed that a higher level of verbal anthropomorphism mostly induced positive user experiences; however, people sometimes tended to prefer a medium level, especially in terms of usefulness. Further, privacy concerns were significantly higher in open space. Consequently, we propose that designers and researchers deviate from the two levels of anthropomorphism (e.g., high or low, existing or not) generally used in prior studies to a new perspective that also considers the spatial context.
A Haptic Multimodal Interface with Abstract Controls for Semi-Autonomous Manipulation

Even as autonomous capabilities improve, many robot manipulation tasks require human(s)-in-the-loop to resolve high-level problems in uncertain environments or ambiguous situations. Prior work in highly autonomous applications tends to use interfaces with few human interface modalities, poten-tially missing out on the benefits that multimodal interfaces have demonstrated in lower-level operation. In this work, we demonstrate a system with a multimodal interface for a controlling a robot at a high level of autonomy. This example highlights how multiple modalities could enable redundant and robust interactions, increased situational awareness, and compact representations of complex commands, such as how to grasp an object.
Quantum radiation from an evaporating nonsingular black hole

In this paper we study quantum radiation from an evaporating spherically symmetric non-singular black hole. We used a modified Hayward metric for a description of a non-singular black hole. We assume that the mass parameter of this metric depends on the advanced time, and choose this dependence so that it properly reproduces both black hole formation and its subsequent evaporation. We consider a quantum massless scalar field propagating in this geometry and use 2D approximation for the calculation of the quantum average of the stress-energy tensor. For the calculation of this quantity it is sufficient to find a map between the Killing times $u_+$ and $u_-$ at the future and past null infinities, established by the propagation of the radial null rays. In this formalism the quantum energy flux at the future null infinity can be expressed in terms of the function $u_+(u_-)$ and its derivatives. We developed a special formalism, which allows one to reduce the problem of the calculation of the quantum energy flux and other observables to a solution of a simple set of ordinary differential equations. We used this approach to study quantum effects in two cases: i) with the trivial, $\alpha=1$ and ii) the non-trivial, $\alpha\ne1$, redshift function. In both cases there exists an outburst of the quantum energy radiation from the inner domain of the black hole, close to the inner part of its apparent horizon. For $\alpha=1$ this outburst is exponentially large. It is a direct consequence of the so-called mass inflation effect. We showed, that this severe problem can be solved by a proper choice of the redshift function. However, even in this case the emitted energy can be much larger than the initial mass of the evaporating black hole. This means that for a construction of a self-consistent model of a non-singular evaporating black hole the back-reaction effects are highly important.
15-year Follow-up of Abused Children Admitted in a Child Welfare Center , Western France

Objective: The aim of our study was to describe the pathways and the long-term outcome of abused children placed in a Child Welfare Center and to identify factors influencing their outcome. Method: One hundred and twenty-eight children admitted in a Child Welfare Center of Maine-et-Loire, Western France, were included in a catamnestic survey conducted from September 2011 to June 2013. The study focused on the different children pathways in and out the Center. Various medical data were recorded: mental health, socio-administrative and educational data. Results: The admission of the children was due to psychological violence in 65 cases (50.8 %), physical violence in 32 cases (25%), severe negligence in 14 cases (11%) and sexual abuse in 2 cases (1.6%). Forty-six percent of the children had at admission a delayed growth rate which was caught up in half of the cases at the end of the study. Children's Global Assessment Scale (CGAS) designed to measure disturbance severity in children, showed non-significant improvement between admission and end of follow up. Their ways a delay between detection and admission of children. Most of them suffered from physical disabilities and mental disorders. Conclusion: Our survey provides the first description of child abuse in the French department of Maine-et-Loire. Child abuse is a serious public health problem often underestimated in France. It can be improved through better detection of children at risk, access to broader educational measures and recourse to trusted adults. MeSh Headings/
Towards lean and green thinking in construction projects at Gaza Strip

Abstract Background and problem Integrating lean and green principles while implementing construction project has become an important aspect of modern construction. Lean construction and green building are used to maximize the economic benefits, address quality, reduce waste and minimize the negative environmental impacts in construction. Aims The objectives of this paper were to measure the degree of knowledge of lean and green approaches in construction industry in Gaza Strip and to identify the most important benefits from application of lean and green in construction. Methodology Literature review and questionnaire survey were used in this study. A total of 155 copies of the questionnaire were distributed randomly to owners, consultants and contractors in the Gaza Strip, and 119 copies of the questionnaire were received. Results The results revealed that the awareness level of lean and green construction by owners, consultants and contractors in the construction industry in Gaza Strip is moderate. There are very important benefits of applying lean and green construction such as “reduce non-useful work that does not add value to work”, “reduce the environmental impact of the construction process” and “saving the money needed to complete the project”. Conclusions It was concluded that integrating both concepts on projects showed that lean leads to green but not necessarily vice versa. The fields of lean and green thinking, however, have been developed largely independent of each other. There is a big gap in the knowledge and application of the lean construction and the green application.
Dendroclimatic reconstruction of maximum summer temperatures from upper treeline sites in Interior British Columbia, Canada

Two independent reconstructions of maximum May–August temperatures are developed from a new network of Engelmann spruce tree-ring chronologies at treeline sites across Interior British Columbia (IBC). The IBC reconstruction (ad 1600–1997) uses the longest three ring-width (RW) and two maximum latewood density (MXD) chronologies from the region. The shorter (regional) reconstruction (REG, 1845–1997) is based on an independent, more broadly based network of chronologies (12 RW and 5 MXD) and verifies the regional signal in the parsimoniously sampled IBC reconstruction. Both models explain 53% of the regional temperature variance (1912–1995) and correlate strongly (r = 0.92) over their common period. The IBC reconstruction indicates two prolonged cooler intervals, c. 1620–1710 and 1775–1880, separated by warmer conditions that approached late twentieth-century normals between c. 1710 and 1730. The mean anomaly over the 1600–1900 period is estimated at 0.38°C below the 1961–1990 mean with the seventeenth century (1601–1700) being marginally colder than the nineteenth century (–0.53: –0.49°C). Both reconstructions model the rise in temperatures from the 1880s to 1940s and indicate that maximum summer temperatures since 1930 have been warmer than at any period since 1600. The IBC record from 1600–1900 is very similar to the mean summer-temperature record reconstructed in the adjacent Canadian Rockies, providing mutual verification for the regional nature of the signal in both reconstructions. This is the first maximum summer-temperature reconstruction from North America. Significant changes are also noted in the relationships between summer mean, maximum and minimum temperatures in this region in the last few decades with a greater absolute rate of increase in mean and minimum temperatures. These changing relationships suggest it is prudent to model tree-ring response to a variety of temperature parameters rather than using mean-temperature values.
Music and Movement Based Dancing for a Non-Anthropomorphic Robot

The purpose of this research is to use human motion and musical features to generate dances for non-anthropomorphic robots. Many non-humanoid dancing robots are hard-coded by their choreographer/programmer. While some robots do generate dances based on music, most of the robots are anthropomorphic and don't use human motion to enhance their dance. This research looks to introduce novel ways of generating dances for a 7 degree of freedom (DoF) robotic arm based on a variety of musical features. It also develops new methods to capture human dance motion for non-humanoid robots. Lastly, it combines human-motion influenced robotic dance with the music based generative dance using to enhance the robot's artistic expression.
“My Robot Friend”: Application of Intergroup Contact Theory in Human-Robot Interaction

We present pilot data for one of the first comprehensive investigations of Intergroup Contact Theory [1], [2] in the context of human-robot interaction. Applying an actual intergroup contact procedure known to affect intergroup attitudes among humans (e.g., [3]), we examined whether human-robot interaction as a positive intergroup contact would change participants' evaluation of robots. Our data from 28 student participants ($N=15$ in the interaction condition and $N=13$ in the no-interaction condition) suggest that after the participant and robot self-disclosed to each other (Fast Friendship Task), participants (1) felt more positive emotions towards robots, (2) perceived robots as warmer, and (3) identified robots as more similar to humans. These preliminary findings invite further research on the application of Intergroup Contact Theory in examining social human-robot interaction and its possible contributions to understanding human psychology.
A Carryover Effect in HRI: Beyond Direct Social Effects in Human-Robot Interaction

We evaluate whether an interaction with robots can influence a subsequent Human-Human Interaction without the robots' presence. Social psychology studies indicate that some social experiences have a carryover effect, leading to implicit influences on later interactions. We tested whether a social experience formed in a Human-Robot Interaction can have a carryover effect that impacts a subsequent Human-Human Interaction. We focused on ostracism, a phenomenon known to involve carryover effects that lead to prosocial behavior. Using the Robotic Ostracism Paradigm, we compared two HRI experiences: Exclusion and Inclusion, testing their impact on a Human-Human Interaction that did not involve robots. Robotic ostracism had a carryover effect that led to prosocial behavior in the Human-Human Interaction, whereby participants preferred intimate interpersonal space and displayed increased compliance. We conclude that HRI experiences may involve carryover effects that extend beyond the interaction with robots, impacting separate and different subsequent strictly human Interactions.
We present a three-dimensional high-resolution hydrodynamic model for unsteady incompressible flow over an evolving bed topography

[1] We present a three-dimensional high-resolution hydrodynamic model for unsteady incompressible flow over an evolving bed topography. This is achieved by using a multilevel Cartesian grid technique that allows the grid to be refined in high-gradient regions and in the vicinity of the river bed. The grid can be locally refined and adapted to the bed geometry, managing the Cartesian grid cells and faces using a hierarchical tree data approach. A ghost-cell immersed-boundary technique is applied to cells intersecting the bed topography. The governing equations have been discretized using a finite-volume method on a staggered grid, conserving second-order accuracy in time and space. The solution advances in time using the fractional step approach. Large-eddy simulation is used as turbulence closure. We validate the model against several experiments and other results from literature. Model results for Stokes flow around a cylinder in the vicinity of a moving wall agree well with Wannier’s analytical solution. At higher Reynolds numbers, computed trailing bubble length, separation angle, and drag coefficient compare favorably with experimental and previous computational results. Results for the flow over twoand three-dimensional dunes agree well with published data, including a fair reproduction of recirculation zones, horse-shoe structures, and boiling effects. This shows that the model is suitable for being used as a hydrodynamic submodel in the high-resolution modeling of sediment transport and formation and evolution of subaqueous ripples and dunes.
Jaco: An Offline Running Privacy-aware Voice Assistant

With the recent advance in speech technology, smart voice assistants have been improved and are now used by many people. But often these assistants are running online as a cloud service and are not always known for a good protection of users' privacy. This paper presents the architecture of a novel voice assistant, called Jaco, with the following features: (a) It can run completely offline, even on low resource devices like a RaspberryPi. (b) Through a skill concept it can be easily extended. (c) The architectural focus is on protecting users' privacy, but without restricting capabilities for developers. (d) It supports multiple languages. (e) It is competitive with other voice assistant solutions. In this respect the assistant combines and extends the advantages of other approaches.
A Cloud-Hosted Online Learning Approach for Glycemic Index Forecasting

Recent developments in diabetes care technologies, like wearable devices for continuous glucose monitoring, have made it possible for patients to access relevant data and properly treat diabetes mellitus diseases. Thanks to machine learning, moreover, it has been possible to predict the trend of the level of glucose in the blood in real-time, thus preventing diseases. In this research, we propose to compare the two main state-of-the-art algorithms for time series forecasting, namely Autoregressive Integrated Moving Average (ARIMA) models and Recurrent Neural Network (RNN) models. In particular, we propose an auto adaptive algorithm for ARIMA models’ parameters selection based on the Augmented Dickey-Fuller test for stationarity and autocorrelation and partial autocorrelation functions for autoregressive and moving average orders and we show that somehow this would make the ARIMA model preferable to RNN-based models in an online learning scenario for time series forecasting, with a root mean square error of 1.11 mmol/l. We also propose some considerations related to a Google Cloud based infrastructure to host an online learning application, comparing the performance of the tested models also with respect to their training time and their scalability and maintenance, showing that ARIMA models clearly require a lighter infrastructure and a less complex pipeline for managing model life cycle with respect to RNN-based models.
Effects of information content and evaluative extremity on positivity and negativity biases

This article extends models that assume that the integration of mixed (positive and negative) information results in a negativity bias in the morality domain but a positivity bias in the competence domain. Using functional analysis, this study predicted a positivity bias for moderately evaluated information and a negativity bias for extremely evaluated information. Content domain (competence vs. morality) and evaluative extremity produced main effects in a 2 x 2 experiment where 108 Ss were provided with descriptions of negative and positive behaviors of fictitious targets. As expected, the negativity effect in the morality domain was strong for extremely evaluated information but weak or nonexistent for moderately evaluated information. In contrast, the positivity effect in the competence domain was stronger for moderately than for extremely evaluated information. We suggest that positive and negative evaluations serve as approach and avoidance cues in interpersonal perception. The border between good and evil is located within rather than between persons: Usually, the same person shows both positive and negative attributes. An exception may be characters in the trivial literature, but this literature is considered trivial exactly because it is populated with "black" and "white" characters. According to the well-known averaging model of information integration (N. H. Anderson, 1981), observers' impressions of a person should be neutral if this person shows the same number of positive and negative attributes, each to the same extent. Numerous studies reveal, however, that even if the relative number of positive and negative attributes is controlled and balanced, negative impressions tend to emerge (e.g., Birnbaum, 1973; Fiske, 1980; Oden & Anderson, 1971; Reeder & Coovert, 1986; Reeder & Spores, 1983; Roskey & Birnbaum, 1974; Van der Pligt & Eiser, 1980; Warr, 1974). This suggests that negative information, even if equal in extremity to positive information, is given more weight in information integration, thus yielding a negativity effect. This effect has been explained in terms of the relative novelty of negative information (Fiske, 1980), its lower ambiguity (Birnbaum, 1972; Wyer, 1973), or its greater discrepancy with the general positivity of the typical or average person (Simpson & Ostrom, 1976). According to Skowronski and Carl
Does Employing More Novice Teachers Predict Higher Suspensions for Black Students? A Hierarchical Multiple Regression Analysis

Abstract:Numerous studies highlight that novice teachers continually struggle with implementing classroom management. Unable to manage their classroom, novice teachers often resort to referring students to administration as a punitive form of classroom management (i.e., discipline). Studies show that Black students, particularly in middle school, are the largest recipients of exclusionary outcomes (i.e., out-of-school suspensions, expulsions, and referrals to law enforcement) as the result of a teacher’s office referrals. Utilizing a hierarchical multiple regression model, the present study seeks to determine if the percentage of novice teachers in middle school predicts the number of out-of-school suspensions that Black students receive.