Miracle-dz/UniFAR-FTUs huggingface dataset:
The Rent Impact of Disclosing Energy Performance Certificates: Energy Efficiency and Information Effects

Energy performance certificates (EPC) can help solve information asymmetries between landlords and tenants about dwellings’ energy performance. EPCs may enable rent premiums for energy efficient dwellings, incentivizing energy efficiency investment in rental property. However, low EPC disclosure rates may undermine their potential to promote investment. Using a cross-sectional dataset of residential rental advertisements from Brussels, we estimate rent premiums from EPCs under de facto voluntary EPC disclosure. We use the Heckman correction and an instrumental variable approach to tackle potential selection bias and endogeneity. First, we find that highly energy-efficient compared to inefficient dwellings earn a rent premium, provided that EPCs are disclosed (energy efficiency effect). This premium may incentivize investment in energy efficiency of rental property. Second, dwellings with average energy performance are penalized from disclosing an EPC (information effect). This may provide a strategic motivation to hide EPCs that indicate mediocre energy performance.
First economic assessment of ecosystem services from Natura 2000 network in Lombardy (Northern Italy)

Natura 2000 network is a cornerstone for biodiversity conservation and the implementation of the European Union Biodiversity Strategy to 2020. Despite this, the great potential of the ecosystem service (ES) concept to add value to current conservation approaches remains insufficiently explored and there is a lack of quantitative and monetary data for the potential socio-economic benefits associated to the network. Information gaps on the economic value of ES provided by Natura 2000 are relevant in the case of Italy and, in particular, Lombardy, the Italian region hosting the highest number of Natura 2000 sites (242). The study considers the main potential ES delivered by the Natura 2000 network in Lombardy and performs a choice experiment exercise on two pilot areas (Adamello and Ticino Regional Parks) involving about 3,000 resident panellists at regional scale. Value function benefit transfer based on individual characteristics of respondents, land use and socio-economic characteristics of all regional municipalities has been performed as well. With few exceptions, results show an increase in willingness-to-pay (WTP) values that is consistent with the increase in the levels for attributes covered by the surveys. Besides providing some preliminary economic values, the research contributes to the development of a methodology for assessing and monitoring ES over time, with the aim to inform future policies and decision-making processes.
Reporting Participation in Epidemiologic Studies: A Survey of Practice

Self-selection bias may threaten the internal validity of epidemiologic studies. Studies with a low level of participation are particularly vulnerable to this bias, and commentators note apparent declines in participation in recent years. The authors therefore conducted a retrospective review to survey the practice of reporting participation in epidemiologic studies, to assess changes in participation over time, and to evaluate the impact of increased biologic specimen collection on participation. The authors abstracted selected study characteristics from 355 peer-reviewed, original, analytic-epidemiology research articles published from January 1 to April 30, 2003, in 10 high-impact general epidemiology, public health, and medical journals. At least some information regarding participation was provided in 59% of cross-sectional studies, 44% of case-control studies, and 32% of cohort studies. Participation appears to have declined during 1970–2003 for all study designs. Participation declined most steeply for controls in population-based, case-control studies (� 1.86% per year, 95% confidence interval: � 3.03, � 0.69), with steeper declines after 1990. Proportionately more studies collected biologic specimens over time, particularly for cohort and case-control study designs (ptrend ¼ 0.06 and 0.03, respectively), yet participation was reported separately for the biologic specimen study component in only 27% of studies. The authors conclude that epidemiologists need to address declining participation and to report participation consistently, including for biologic specimen collection. blood specimen collection; case-control studies; cohort studies; cross-sectional studies; epidemiologic methods; patient participation
A Person-Centered Approach to Understanding Teachers' Classroom Practices and Perceived School Goal Structures

ABSTRACT We examined 179 teachers' perceptions of their own classroom practices and their school's motivational climate to illuminate the ways these perceptions work in concert. Using teachers' responses to two scales of the Patterns of Adaptive Learning Survey, a cluster analysis revealed three profiles of teachers described as cluster 1: Aligned: Performance Moderate, Mastery High: We agree with everything! ; cluster 2: Aligned: Performance Low, Mastery High: Yea to Mastery! Nay to Performance! ; and cluster 3: Unaligned: Classroom Mastery with School Performance: We're Mastery Structured in a Performance School. Cluster analyses revealed significant differences suggesting these teacher groups had distinct profiles. This study adds to the literature on goal theory aimed at understanding and advancing teachers' motivationally supportive practices and can be used in teacher education and development to help teachers identify, reflect on, and understand their classroom goal structures and how they relate to structures operating at the school level.
MMT HYPERVELOCITY STAR SURVEY. III. THE COMPLETE SURVEY

We describe our completed spectroscopic survey for unbound hypervelocity stars (HVSs) ejected from the Milky Way. Three new discoveries bring the total number of unbound late B-type stars to 21. We place new constraints on the nature of the stars and on their distances using moderate resolution MMT spectroscopy. Half of the stars are fast rotators; they are certain 2.5–4 M☉ main sequence stars at 50–120 kpc distances. Correcting for stellar lifetime, our survey implies that unbound 2.5–4 M☉ stars are ejected from the Milky Way at a rate of 1.5 × 10−6 yr−1. These unbound HVSs are likely ejected continuously over the past 200 Myr and do not share a common flight time. The anisotropic spatial distribution of HVSs on the sky remains puzzling. Southern hemisphere surveys like SkyMapper will soon allow us to map the all-sky distribution of HVSs. Future proper motion measurements with Hubble Space Telescope and Gaia will provide strong constraints on origin. Existing observations are all consistent with HVS ejections from encounters with the massive black hole in the Galactic center.
A Spectral Feature Based Convolutional Neural Network for Classification of Sea Surface Oil Spill

Spectral characteristics play an important role in the classification of oil film, but the presence of too many bands can lead to information redundancy and reduced classification accuracy. In this study, a classification model that combines spectral indices-based band selection (SIs) and one-dimensional convolutional neural networks was proposed to realize automatic oil films classification using hyperspectral remote sensing images. Additionally, for comparison, the minimum Redundancy Maximum Relevance (mRMR) was tested for reducing the number of bands. The support vector machine (SVM), random forest (RF), and Hu’s convolutional neural networks (CNN) were trained and tested. The results show that the accuracy of classifications through the one dimensional convolutional neural network (1D CNN) models surpassed the accuracy of other machine learning algorithms such as SVM and RF. The model of SIs+1D CNN could produce a relatively higher accuracy oil film distribution map within less time than other models.
Fiscal costs of monetary policy: indirect effects of an interest rate shock on Brazilian public net debt

The paper estimates the fiscal cost of an increase in the Brazilian policy interest rate - the SELIC - by considering not only the direct effect on the yield of public bonds that are indexed to the SELIC, but also indirect effects on: (i) the yield of public bonds that are indexed to the exchange rate and inflation, and (ii) the stock of public net debt through adjustments in the value of international reserves measured in domestic currency. Projections are based on the estimation of the relationship between interest rates, exchange rates and inflation by means of a vector auto-regression. We conclude that the inclusion of such indirect effects has an ambiguous effect on the response of the implicit interest rate on public net debt to shocks in the SELIC, when adjustments in the value of international reserves are not considered. However, the inclusion of the latter amplifies the fiscal cost of a more restrictive monetary policy. These results call for a better coordination between monetary, fiscal and exchange rate policies in Brazil.
Imaging the elusive H-poor gas in planetary nebulae with large abundance discrepancy factors

Abstract The discrepancy between abundances computed using optical recombination lines (ORLs) and collisionally excited lines (CELs) is a major, unresolved problem with significant implications for the determination of chemical abundances throughout the Universe. In planetary nebulae (PNe), the most common explanation for the discrepancy is that two different gas phases coexist: a hot component with standard metallicity, and a much colder plasma enhanced in heavy elements. This dual nature is not predicted by mass loss theories, and direct observational support for it is still weak. In this work, we present our recent findings that demonstrate that the largest abundance discrepancies are associated with close binary central stars. OSIRIS-GTC tunable filter imaging of the faint O ii ORLs and MUSE-VLT deep 2D spectrophotometry confirm that O ii ORL emission is more centrally concentrated than that of [Oiii] CELs and, therefore, that the abundance discrepancy may be closely linked to binary evolution.
Quintessential halos around galaxies

The nature of the dark matter that binds galaxies remains an open question. The favored candidate has so far been the neutralino. This massive species with evanescent interactions is now in difficulty. It would actually collapse in dense clumps and would therefore play havoc with the matter it is supposed to shepherd. We focus here on a massive and noninteracting complex scalar field as an alternate option to the astronomical missing mass. We investigate the classical solutions that describe the Bose condensate of such a field in gravitational interaction with matter. This simplistic model accounts quite well for the dark matter inside low-luminosity spirals whereas the agreement lessens for the brightest objects where baryons dominate. A scalar mass $m\ensuremath{\sim}0.4$ to $1.6\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}23}$ eV is derived when both high and low-luminosity spirals are fitted at the same time. Comparison with astronomical observations is made quantitative through a chi-squared analysis. We conclude that scalar fields offer a promising direction worth being explored.
The role of beta-adrenolytic drugs in treating anxiety disorders

Summary Introduction: Beta blockers are mainly used in treating cardiovascular diseases. However, it has been observed that these drugs have also an anxiolytic potential. Over the years, a number of clinical trials have been conducted aimed at determining the effectiveness of beta blockers in treating anxiety disorders. The aim of the article: The main objective of the article is to present the significance and position of adrenolytic drugs in the pharmacotherapy of anxiety disorders on the basis of available literature. Moreover, the authors also decided to take into account the data from current research results, considering the problem of side effects of using adrenolytic drugs - especially the controversial reports on their effect on the development of affective disorders. Method: An analysis was conducted of articles from Medline/PubMed database, selected on the basis of the following key words: anxiety disorders, beta blockers, adrenolytic drugs, as well as on the basis of their dates of publication: 1960-2017. In order to conduct a reliable and complete review of literature, the authors decided to include works from quite an extended period of time. The articles included in the review were published in Polish and English. Results: The review of articles concerning the treatment of anxiety disorders clearly suggests that propranolol is effective in reducing the frequency of panic attacks and the tendency for avoidance behavior in patients with agoraphobia. Other studies report on potential benefits in terms of early interventional prevention and treating posttraumatic stress disorder with propranolol. However, there is lack of randomized clinical trials concerning the therapeutic effect of other adrenolytic drugs in treating anxiety disorders. Early research works reported that (mainly lipophilic) beta blockers may have a depressogenic effect; however, the latest studies have not confirmed it. The contemporary research on the therapeutic potential of beta blockers in treating anxiety disorders is insufficient. What seems to be most promising, however, are reports concerning the desirable effects of using adrenolytic drugs in treating posttraumatic stress disorder, which implicates the necessity of conducting further research verifying the validity of their application.
RESERVATION-COMPULSORY COMMUTING RAILWAYS: INNOVATION THAT WILL BE MADE POSSIBLE BY UCRT/IPASS

Making commuting railways “reservation-compulsory” is a quick method to realise “congestion-free” commute on those railways. This is a simple idea which have generally been rejected as unrealistic. However, the author believes that the advances in technologies recent years have seen is giving the idea a fresh chance to be realised. First, combining the moving block signalling systems and the ideas proposed by the authors to realise ultra-high-frequency train operation, a drastic improvement in capacity on already densely trafficked railway routes will become possible, giving railway operators the ability to provide a wide variety of services that, if properly selected by passengers, will better suit their individual needs. The ultra-high-frequency operation realised in the above way will result in train timetables that are really difficult to use. In addition, a slight imbalance in passenger loading across railway lines, trains or even coaches in a trainset may result in considerable destabilisation of operation. Here comes the need for implementing “compulsory reservation” policy or something close to that, giving the operator the ability to control passenger behaviour to a certain extent. The reservation policy will also give the operator the ability to provide sophisticated and individualised passenger guidance, as proposed by the author in his IPASS proposal. The complicated train timetables will become easy to use through the help of the high-performance individual passenger guidance function of IPASS. Fare collection will also be easy, giving operators the possibility to apply flexible fare structure while maximising passenger benefits. In the paper, the author describes in full detail the concept and possibility of reservation-compulsory commuting railways and reveal that this can be realised by the application of the group of ideas the author has proposed in recent years as part of his “UCRT/IPASS”
Is Growth Good or Bad For the Environment in Indonesia

This paper attempts to contribute to the literature on the growth-environment nexus by asking: What is the effect of growth on Indonesia’s CO2 emissions, controlling for energy consumption and urbanization? To that end, an autogressive distributed lag approach to cointegration is applied to annual data for the period 1971–2013. Results show that income growth tends to increase CO2 emissions monotonically in Indonesia. It is also found that there is strong evidence that energy consumption increases CO2 emissions and little evidence that urbanization causes significant environmental degradation.
Efficient Neural Network Pruning and Quantization by Hard Clustering

Besides computationally demanding, large modern neural networks are often considered difficult to interpret. We address these problems from the perspective of model compression, i.e., reducing the entropy in the model parameters, by learning sparse quantized models that contain a small number of non-zero distinct parameters, without compromising stateof-the-art performance. The key idea is to modify the original optimization problem by adding K independent Gaussian priors (corresponding to the k-means objective) over the network parameters to achieve parameter quantization, as well as an `1 penalty to achieve pruning. Besides being easy to implement, our method differs from many existing quantizationbased methods by using hard clustering assignments of network parameters, which adds minimal change or overhead to standard network training. We also demonstrate experimentally that tying neural network parameters provides less gain in generalization performance than changing network architecture and connectivity patterns entirely.
Privacy-Preserving Electricity Billing System Using Functional Encryption

The development of smart meters that can frequently measure and report power consumption has enabledelectricity providers to offer various time-varying rates, including time-of-use and real-time pricing plans. High-resolution power consumption data, however, raise serious privacy concerns because sensitive information regarding an individual’s lifestyle can be revealed by analyzing these data. Although extensive research has been conducted to address these privacy concerns, previous approaches have reduced the quality of measured data. In this paper, we propose a new privacy-preserving electricity billing method that does not sacrifice data quality for privacy. The proposed method is based on the novel use of functional encryption. Experimental results on a prototype system using a real-world smart meter device and data prove the feasibility of the proposed method.
Title Decoded fMRI neurofeedback can induce bidirectionalconfidence changes within single participants

Neurofeedback studies using real-time functional magnetic resonance imaging (rt-fMRI) have recently incorporated the multi-voxel pattern decoding approach, allowing for fMRI to serve as a tool to manipulate fine-grained neural activity embedded in voxel patterns. Because of its tremendous potential for clinical applications, certain questions regarding decoded neurofeedback (DecNef) must be addressed. Specifically, can the same participants learn to induce neural patterns in opposite directions in different sessions? If so, how does previous learning affect subsequent induction effectiveness? These questions are critical because neurofeedback effects can last for months, but the shortto mid-term dynamics of such effects are unknown. Here we employed a within-subjects design, where participants underwent two DecNef training sessions to induce behavioural changes of opposing directionality (up or down regulation of perceptual confidence in a visual discrimination task), with the order of training counterbalanced across participants. Behavioral results indicated that the manipulation was strongly influenced by the order and the directionality of neurofeedback training. We applied nonlinear mathematical modeling to parametrize four main consequences of DecNef: main effect of change in confidence, strength of down-regulation of confidence relative to up-regulation, maintenance of learning effects, and anterograde learning interference. Modeling results revealed that DecNef successfully induced bidirectional confidence changes in different sessions within single participants. Furthermore, the effect of upcompared to down-regulation was more prominent, and confidence changes (regardless of the direction) were largely preserved even after a week-long interval. Lastly, the effect of the second session was markedly diminished as compared to the effect of the first session, indicating strong anterograde learning interference. These results are interpreted in the framework of reinforcement learning and provide important implications for its application to basic neuroscience, to occupational and sports training, and to therapy.
Labor tax and relative cost of R&D

This paper examines the impact of taxation of labor on investment in Research and Development. Given the central role of R&D as an en- gine of business expansion and economy growth, issue of estimating the barriers to R&D is a vital one, both from theoretical and practical point of view. We analyse the impact of labor taxation on decision to invest in R&D. We show that labor taxation changes relative costs of R&D investment versus fixed capital formation. It leads to allocation of investment more towards physical capital formation than R&D invest- ment. In the empirical part of the paper, using panel and cross-section of countries, we shed light on the impact of taxation of labor on R&D. Our estimates indicate that labor tax has a significant adverse impact on R&D investment, and its negative impact is larger for R&D than for physical capital.
A SECTORAL APPROACH TO THE ELECTRICITY-GROWTH NEXUS IN THE EASTERN CAPE PROVINCE OF SOUTH AFRICA

This paper takes a sectoral, panel approach to investigating the electricity-growth nexus for the Eastern Cape province of South Africa between the period of 2003 and 2017. The empirical investigation was carried out using the Pooled Mean Group (PMG) panel estimators applied to an augmented dynamic growth model whilst the caulisty tests between electricity consumption and growth where performed using the Dumitrescu-Hurlin (2012) panel non-causality tests. The findings confirm the absence of significant long-run relationship between electricity and growth whilst finding a significant and positive effect over the short-run. Moreover, our causality tests provide strong evidence of causality running from electricity consumption to economic growth hence supporting the “growth hypothesis”. In a nutshell, our results not only demonstrate the importance of performing the electricity-growth analysis at provincial level as opposed to relying on national aggregated estimates but also provides important provincial-specific policy implications and recommendations.
Out of Many , One : Unifying Web-Extracted Knowledge Bases

Extracting knowledge from large text corpora and the world wide web is an important problem in artificial intelligence. Arguably, the majority of the world’s knowledge is contained in natural language text and as such needs to be brought into structured form to be accessible for automated reasoning. There are numerous information extraction (IE) projects that address this problem, such as YAGO, Freebase, and OpenIE [10, 11]. Each of these projects has its unique strengths and weaknesses. For instance, projects unconstrained by an ontology provide more coverage, but suffer from noise and ambiguities of the extracted facts. If these projects are categorized along dimensions such as extraction types, temporal and geographical attributes, events coverage, and schema language, one realizes that the projects would be highly complementary if their knowledge was integrated.