nils-herrmann/clean_scirepeval huggingface dataset:
Restoring Rational Choice: The Challenge of Consumer Financial Regulation

This lecture considers the case for consumer financial regulation in an environment where many households lack the knowledge to manage their financial affairs effectively. The lecture argues that financial ignorance is pervasive and unsurprising given the complexity of modern financial products, and that it contributes meaningfully to the evolution of wealth inequality. The lecture uses a stylized model to discuss the welfare economics of paternalistic intervention in financial markets, and discusses several specific examples including asset allocation in retirement savings, fees for unsecured short term borrowing, and reverse mortgages.
Revealing Invisible Water: Moisture Recycling as an Ecosystem Service
Venue: PloS one

An ecosystem service is a benefit derived by humanity that can be traced back to an ecological process. Although ecosystem services related to surface water have been thoroughly described, the relationship between atmospheric water and ecosystem services has been mostly neglected, and perhaps misunderstood. Recent advances in land atmosphere modeling have revealed the importance of terrestrial ecosystems for moisture recycling. In this paper, we analyze the extent to which vegetation sustains the supply of atmospheric moisture and precipitation for downwind beneficiaries, globally. We simulate land surface evaporation with a global hydrology model and track changes to moisture recycling using an atmospheric moisture budget model, and we define vegetation regulated moisture recycling as the difference in moisture recycling between current vegetation and a hypothetical desert world. Our results show that nearly a fifth of annual average precipitation falling on land is from vegetation regulated moisture recycling, but the global variability is large, with many places receiving nearly half their precipitation from this ecosystem service. The largest potential impacts for changes to this ecosystem service are land use changes across temperate regions in North America and Russia. Likewise, in semi arid regions reliant on rainfed agricultural production, land use change that even modestly reduces evaporation and subsequent precipitation, could significantly affect human well being. We also present a regional case study in the Mato Grosso region of Brazil, where we identify the specific moisture recycling ecosystem services associated with the vegetation in Mato Grosso. We find that Mato Grosso vegetation regulates some internal precipitation, with a diffuse region of benefit downwind, primarily to the south and east, including the La Plata River basin and the megacities of Sao Paulo and Rio de Janeiro. We synthesize our global and regional results into a generalized framework for describing moisture recycling as an ecosystem service. We conclude that future work ought to disentangle whether and how this vegetation regulated moisture recycling interacts with other ecosystem services, so that trade offs can be assessed in a comprehensive and sustainable manner.
Revealing and analyzing imperceptible deviations in images and videos

The world is filled with objects that appear to follow some perfect model. A sleeping baby might look still and a house's roof .should be straight. However, both the baby and the roof can deviate subtly from their ideal models of perfect stillness and perfect straightness. These deviations can reveal important information like whether the baby is breathing normally or whether the house's roof is sagging. In this dissertation, we make the observation that these subtle deviations produce a visual signal that while invisible to the naked eye can be extracted from ordinary and ubiquitous images and videos. We propose new computational techniques to reveal these subtle deviations by producing new images and videos, in which the tiny deviations have been magnified. We focus on magnifying deviations from two ideal models: perfect stillness and perfect geometries in space. In the first case, we leverage the complex steerable pyramid, a localized version of the Fourier transform, whose notion of local phase can be used to process and manipulate small motions or changes from stillness in videos. In the second case, we find hidden geometric deformations in images by localizing edges to sub pixel precision. In both cases, we experimentally validate that the tiny deviations we magnify are indeed real, comparing them to alternative ways of measuring tiny motions and subtle geometric deformations in the world. We also give a careful analysis of how noise in videos impacts our ability to see tiny motions. Additionally, we show the utility of revealing hidden deviations in a wide variety of fields, such as biology, physics and structural analysis.
Data transformation and migration in polystores
Venue: 2016 IEEE High Performance Extreme Computing Conference (HPEC)

Ever increasing data size and new requirements in data processing has fostered the development of many new database systems. The result is that many data intensive applications are underpinned by different engines. To enable data mobility there is a need to transfer data between systems easily and efficiently. We analyze the state of the art of data migration and outline research opportunities for a rapid data transfer. Our experiments explore data migration between a diverse set of databases, including PostgreSQL, SciDB, S Store and Accumulo. Each of the systems excels at specific application requirements, such as transactional processing, numerical computation, streaming data, and large scale text processing. Providing an efficient data migration tool is essential to take advantage of superior processing from that specialized databases. Our goal is to build such a data migration framework that will take advantage of recent advancement in hardware and software.
Perceptions About the Dominance of English as a Global Language: Impact on Foreign Language Teachers' Professional Identity

Using a novel theoretical framework that incorporates teacher identity, a school as community of practice, and English as a global language from a linguistic imperialism perspective, this qualitative interview study with foreign language teachers in Scotland, France, and Germany (N 13) explores connections between foreign language learning decline and the impact of this decline on teachers' identity across the three countries. Findings indicate similar trends across contexts in the dominance of English over other languages (and the identities of those who teach them) and support previous research on the importance of considering subject area, and its valuing by a range of stakeholders, as fundamental to teacher identity. Directions are proposed for future research and practice that emphasise taking an interdisciplinary approach to the notion of a subject area's decline.
The role of parental and peer attachment relationships and school connectedness in predicting adolescent mental health outcomes.
Venue: Child and adolescent mental health

Adolescent attachment relationships with parents and peers and the sense of connectedness with the schools attended have been established as salient predictors of psychological well being. Few studies, however, have assessed the relative importance of each attachment or connectedness relationship and how they interrelate to influence mental health outcomes.  A total of 203 adolescents (11 16 years) completed self report measures of parental and peer attachment (Inventory of Parental Peer Attachment Revised; Gullone Robinson, school connectedness (Psychological Sense of School Membership; Goodenow, conduct problems, emotional symptoms and prosocial behaviour (Strengths and Difficulties Questionnaire; Goodman,  Multiple regression analyses demonstrated that more insecure parental attachment (although not peer attachment or school connectedness) predicted conduct problems and emotional difficulties. Peer attachment and school connectedness were significant predictors of prosocial behaviour, whereas parental attachment was not. A mediational analysis revealed that peer attachment and school connectedness both mediate the relationship between parental attachment and prosocial behaviour. No significant moderation effects of either peer attachment or school connectedness on the relationship between parental attachment and mental health outcomes were found.  Different attachment and connectedness relationships, although related, predict adolescent mental health outcomes in distinct ways. Improving parental attachment may have particular salience in reducing negative behaviours such as conduct problems and emotional difficulties, whereas improving peer attachment and school connectedness could be important for the display of prosocial behaviour.
Consistent Algorithms for Clustering Time Series
Venue: J. Mach. Learn. Res.

The problem of clustering is considered for the case where every point is a time series. The time series are either given in one batch (offline setting) or they are allowed to grow with time and new time series can be added along the way (online setting) We propose a natural notion of consistency for this problem, and show that there are simple, computationally efficient algorithms that are asymptotically consistent under extremely weak assumptions on the distributions that generate the data. The notion of consistency is as follows. A clustering algorithm is called consistent if it places two time series into the same cluster if and only if the distribution that generates them is the same. In the considered framework the time series are allowed to be highly dependent, and the dependence can have arbitrary form. If the number of clusters is known, the only assumption we make is that the (marginal) distribution of each time series is stationary ergodic. No parametric, memory or mixing assumptions are made. When the number of clusters is unknown, stronger assumptions are provably necessary, but it is still possible to devise nonparametric algorithms that are consistent under very general conditions. The theoretical findings of this work are illustrated with experiments on both synthetic and real data.
Spatial clustering of time series via mixture of autoregressions models and Markov random fields

Time series data arise in many medical and biological imaging scenarios. In such images, a time series is obtained at each of a large number of spatially dependent data units. It is interesting to organize these data into model based clusters. A two stage procedure is proposed. In stage 1, a mixture of autoregressions (MoAR) model is used to marginally cluster the data. The MoAR model is fitted using maximum marginal likelihood (MMaL) estimation via a minorization maximization (MM) algorithm. In stage 2, a Markov random field (MRF) model induces a spatial structure onto the stage 1 clustering. The MRF model is fitted using maximum pseudolikelihood (MPL) estimation via an MM algorithm. Both the MMaL and MPL estimators are proved to be consistent. Numerical properties are established for both MM algorithms. A simulation study demonstrates the performance of the two stage procedure. An application to the segmentation of a zebrafish brain calcium image is presented.
Land cover characterization for a watershed in Kenya using MODIS data and Fourier algorithms

A time series algorithm was being presented that classifies vegetation in the Njoro Watershed, Kenya, according to the shapes of temporal normalized difference vegetation index (NDVI) profiles representing growing cycles for different vegetation. We present a two step approach that includes noise reduction using discrete Fourier filtering and a clustering algorithm that uses the Fourier components of magnitude and phase to identify phenological differences. The classification considers possible variations in shape that may be imposed by climate, soil, topography, or human impacts. The primary input to the classification is a user defined set of reference cycles to which pixels are assigned depending on a set of shape criteria. The output is a consistent classification of NDVI cycles representing vegetation classes with similar phenologies. The algorithm allows the creation of classification mosaics without typical boundary offsets and temporally comparable classification products. It identifies vegetation more accurately than single image classification methods, because it exploits the temporal variability in spectral reflectance due to phenological responses. We produced a classified land cover map at two hierarchical levels with five classes in a level I classification and seven classes in a level II classification that represents a refinement of the level I data. These map products compare favorably to previously published land cover maps that were developed using more standard supervised classification. The level I map has an overall accuracy of 94% compared to field data, while the level II map as an overall accuracy of 77%
Intermediate mass black holes from Population III remnants in the first galactic nuclei

We report the formation of intermediate mass black holes (IMBHs) in suites of numerical N body simulations of Population III remnant black holes (BHs) embedded in gas rich protogalaxies at redshifts z 10. We model the eects of gas drag on the BHs' orbits, and allow BHs to grow via gas accretion, including a mode of hyper Eddington accretion in which photon trapping and rapid gas inow suppress any negative radiative feedback. Most initial BH congurations lead to the formation of one (but never more than one) IMBH in the center of the protogalaxy, reaching a mass of 10 3 5 M through hyper Eddington growth. Our results suggest a viable pathway to forming the earliest massive BHs in the centers of early galaxies. We also nd that the nuclear IMBH typically captures a stellar mass BH companion, making these systems observable in gravitational waves as extreme mass ratio inspirals (EMRIs) with eLISA.
X ray twinkles and Population III stars

Pop III stars are typically massive stars of primordial composition forming at the centers of the first collapsed dark matter structures. Here we estimate the optimal X ray emission in the early universe for promoting the formation of Pop III stars. This is important in determining the number of dwarf galaxies formed before reionization and their fossils in the local universe, as well as the number of intermediate mass seed black holes. A mean X ray emission per source above the optimal level reduces the number of Pop III stars because of the increased Jeans mass of the intergalactic medium (IGM) while a lower emission suppresses the formation rate of H2 preventing or delaying star formation in dark matter minihalos above the Jeans mass. The build up of the H2 dissociating background is slower than the X ray background due to the shielding effect of resonant hydrogen Lyman lines. Hence, the nearly unavoidable X ray emission from supernova remnants of Pop III stars is sufficient to boost their number to few tens per comoving Mpc^3 by redshift z~15. We find that there is a critical X ray to UV energy ratio emitted per source that produces a universe where the number of Pop III stars is largest: 400 per comoving Mpc^3. This critical ratio is very close to the one provided by 20 40 M_sun Pop III stars exploding as hypernovae. High mass X ray binaries in dwarf galaxies are far less effective at increasing the number of Pop III stars than normal supernova remnants, we thus conclude that supernovae drove the formation of Pop III stars.
From the first stars to the first black holes

The growth of the first super massive black holes (SMBHs) at z 6 is still a major challenge for theoretical models. If it starts from black hole (BH) remnants of Population III stars (light seeds with mass 100 Msun) it requires super Eddington accretion. An alternative route is to start from heavy seeds formed by the direct collapse of gas onto a 10^5 Msun BH. Here we investigate the relative role of light and heavy seeds as BH progenitors of the first SMBHs. We use the cosmological, data constrained semi analytic model GAMETE/QSOdust to simulate several independent merger histories of z 6 quasars. Using physically motivated prescriptions to form light and heavy seeds in the progenitor galaxies, we find that the formation of a few heavy seeds (between 3 and 30 in our reference model) enables the Eddington limited growth of SMBHs at z 6. This conclusion depends sensitively on the interplay between chemical, radiative and mechanical feedback effects, which easily erase the conditions that allow the suppression of gas cooling in the low metallicity gas (Z Jcr) We find that heavy seeds can not form if dust cooling triggers gas fragmentation above a critical dust to gas mass ratio (D Dcr) In addition, the relative importance of light and heavy seeds depends on the adopted mass range for light seeds, as this dramatically affects the history of cold gas along the merger tree, by both SN and AGN driven winds.
Systemic decision making in AHP: a Bayesian approach
Venue: Ann. Oper. Res.

Systemic decision making is a new approach for dealing with complex multiactor decision making problems in which the actors' individual preferences on a fixed set of alternatives are incorporated in a holistic view in accordance with the "principle of tolerance" The new approach integrates all the preferences, even if they are encapsulated in different individual theoretical models or approaches; the only requirement is that they must be expressed as some kind of probability distribution. In this paper, assuming the analytic hierarchy process (AHP) is the multicriteria technique employed to rank alternatives, the authors present a new methodology based on a Bayesian analysis for dealing with AHP systemic decision making in a local context (a single criterion) The approach integrates the individual visions of reality into a collective one by means of a tolerance distribution, which is defined as the weighted geometric mean of the individual preferences expressed as probability distributions. A mathematical justification of this distribution, a study of its statistical properties and a Monte Carlo method for drawing samples are also provided. The paper further presents a number of decisional tools for the evaluation of the acceptance of the tolerance distribution, the construction of tolerance paths that increase representativeness and the extraction of the relevant knowledge of the subjacent multiactor decisional process from a cognitive perspective. Finally, the proposed methodology is applied to the AHP multiplicative model with lognormal errors and a case study related to a real life experience in local participatory budgets for the Zaragoza City Council (Spain)
Flaming Ignition of Solid Fuels

This chapter will describe how heating of a solid fuel leads to flaming ignition. The discussion will be centred on flaming ignition of solid fuels but will not address smouldering or spontaneous ignition since these subjects will be covered in Chaps. 19 and 20 respectively. Thus, the presence of a source of heat decoupled from the solid and fuel gasification will be assumed throughout the chapter.
Localisation of litchi in an unstructured environment using binocular stereo vision

The major constraints for a litchi harvesting robot were to recognise and locate litchi in an unstructured environment with varying illumination and random occlusion. A rapid and reliable method based on binocular stereo vision was developed with the aim of effectively recognising and locating litchi in the natural environment. The method involved the application of wavelet transform to a pair acquired images of litchi to normalise illumination of an object surface. A litchi recognition algorithm based on K means clustering was presented to separate litchi from leaves, branches and background. A matching algorithm to locate litchi based on a label template was discussed. Litchis with a similar label template were matched according to the preset threshold by traversing a litchi label template of a left image in a right image to find optimal matching. The experimental results showed that the proposed recognition method could be robust against the influences of varying illumination and precisely recognising litchi, the highest average recognition rate for unoccluded and partially occluded litchi was 98.8% and 97.5% respectively. From 100 pairs of tested images of unoccluded and partially occluded litchis 98% and 94% were successfully matched, respectively. Errors had no significant difference and they were less than 15 mm when the measuring distance was between 300 mm and 1600 mm under varying illumination and partially occluded conditions.
Dark Money: The Hidden History of the Billionaires Behind the Rise of the Radical Right

In the late 1980s, Richard Fink, the principal political aide of Charles Koch, laid out a blueprint for a takeover of American politics. The first phase required investments in intellectuals and think tanks to produce ideas and turn them into marketable policy initiatives. The next phase involved subsidizing " grassroots " citizen groups that would elect politicians primed to enact the policies and along with " special interest " lobbyists, keep the pressure on them and government agencies. Faced with serious threats to their energy businesses from environmentalists in and outside the government, Charles and David Koch (whose father was a founding member of the John Birch Society) committed hundreds of millions of dollars to this " vertically and horizontally integrated " plan to establish a libertarian, anti tax, anti regulation, anti union, antisocial welfare, pro corporate America. In " Dark Money: The Hidden History of the Billionaires Behind the Rise of the Radical Right, " Jane Mayer, a staff writer for The New Yorker and the author of " The Dark Side: The Inside Story of How the War on Terror Turned into a War on American Ideals, " provides an extraordinarily well documented account of the influential, interlocking organizations with innocuous names created by the Koch brothers.
Analysis of piRNA Like Small Non coding RNAs Present in Axons of Adult Sensory Neurons
Venue: Molecular Neurobiology

Small non coding RNAs (sncRNAs) have been shown to play pivotal roles in spatiotemporal specific gene regulation that is linked to many different biological functions. PIWI interacting RNAs (piRNAs) typically 25 34 nucleotide long, are originally identified and thought to be restricted in germline cells. However, recent studies suggest that piRNAs associate with neuronal PIWI proteins, contributing to neuronal development and function. Here, we identify a cohort of piRNA like sncRNAs (piLRNAs) in rat sciatic nerve axoplasm and directly contrast temporal changes of piLRNA levels in the nerve following injury, as compared with those in an uninjured nerve using deep sequencing. We find that 32 of a total of 53 annotated piLRNAs show significant changes in their levels in the regenerating nerve, suggesting that individual axonal piLRNAs may play important regulatory roles in local messenger RNA (mRNA) translation during regeneration. Bioinformatics and biochemical analyses show that these piLRNAs carry characteristic features of mammalian piRNAs, including sizes, a sequence bias for uracil at the 5' end and a 2' O methylation at the 3' end. Their axonal expression is directly visualized by fluorescence in situ hybridization in cultured dorsal root ganglion neurons as well as immunoprecipitation with MIWI. Further, depletion of MIWI protein using RNAi from cultured sensory neurons increases axon growth rates, decreases axon retraction after injury, and increases axon regrowth after injury. All these data suggest more general roles for MIWI/piLRNA pathway that could confer a unique advantage for coordinately altering the population of proteins generated in growth cones and axons of neurons by targeting mRNA cohorts.