Miracle-dz/UniFAR-FTUs huggingface dataset:
A deep learning framework for modeling structural features of RNA-binding protein targets

RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this paper, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https://github.com/thucombio/deepnet-rbp.
Implementing the safe minimum standard approach: two case studies from the U.S. Endangered Species Act

In situations characterized by true uncertainty and potential irreversibility, the safe minimum standard (SMS) approach is a decision rule to protect some critical natural resource-unless the social costs of doing so are somehow "intolerable. " The SMS has been discussed widely, but actual case studies remain rare. We present two case studies, focusing on endangered fishes in the Colorado and Virgin River systems, demonstrating that the legal framework of the U.S. Endangered Species Act (ESA) is consistent with the SMS. The case studies incorporate the results from applied general equilibrium modeling and provide an avenue for investigating excessive economic consequences.
The Characteristics of Millisecond Pulsar Emission. I. Spectra, Pulse Shapes, and the Beaming Fraction

The extreme physical conditions in millisecond pulsar magnetospheres, as well as an evolutionary history that differs from that of normal pulsars, raise the question whether these objects also differ in their radio emission properties. We have monitored a large sample of millisecond pulsars for a period of 3 yr using the 100 m Effelsberg radio telescope in order to compare the radio emission properties of these two pulsar populations. Our sample comprises a homogeneous data set of very high quality. With some notable exceptions, our findings suggest that the two groups of objects share many common properties. A comparison of the spectral indices between samples of normal and millisecond pulsars demonstrates that millisecond pulsar spectra are not significantly different from those of normal pulsars. This is contrary to what has previously been thought. There is evidence, however, that millisecond pulsars are slightly less luminous and less efficient radio emitters than normal pulsars. We confirm recent suggestions that a diversity exists among the luminosities of millisecond pulsars, with the isolated millisecond pulsars being less luminous than the binary millisecond pulsars, implying that the different evolutionary history has an influence on the emission properties. There are indications that old millisecond pulsars exhibit somewhat flatter spectra than the presumably younger ones. We present evidence that, contrary to common belief, the millisecond pulsar profiles are only marginally more complex than those found among the normal pulsar population. Moreover, the development of the profiles with frequency is rather slow, suggesting very compact magnetospheres. The profile development seems to anticorrelate with the companion mass and the spin period, again suggesting that the amount of mass transfer in a binary system might directly influence the emission properties. The angular radius of radio beams of millisecond pulsars does not follow the scaling predicted from a canonical pulsar model applicable for normal pulsars. Instead, they are systematically smaller, supporting the concept of a critical rotational period below which such a scaling ceases to exist. The smaller inferred luminosity and narrower emission beams will need to be considered in future calculations of the birthrate of the Galactic population.
Exploiting Data-Independence for Fast Belief-Propagation

Maximum a posteriori (MAP) inference in graphical models requires that we maximize the sum of two terms: a data-dependent term, encoding the conditional likelihood of a certain labeling given an observation, and a data-independent term, encoding some prior on labelings. Often, data-dependent factors contain fewer latent variables than data-independent factors - for instance, many grid and tree-structured models contain only first-order conditionals despite having pairwise priors. In this paper, we note that MAP-inference in such models can be made substantially faster by appropriately preprocessing their data-independent terms. Our main result is to show that message-passing in any such pairwise model has an expected-case exponent of only 1.5 on the number of states per node, leading to significant improvements over existing quadratic-time solutions.
The Twenty-Sixth Amendment as a Teachable Moment: Young Adult Voter Turnout in U.S. Elections, 1972-2006

Ratification of the 26th Amendment in 1971 was a watershed event in America's long and often tumultuous electoral reform journey. The persistently low voter turnout of newly enfranchised 18-20 year-olds since then not only is troubling from a democratic perspective but also is puzzling in light of the rapidly rising educational attainment of this age group during the same period. In this investigation, I develop an original theoretical frame by which to examine relationships between the 1972-2006 voter turnout patterns of 26th Amendment eligible voters and a large complement of educational and non-educational influences manifested during the end of high school and the years immediately following high school. Drawing upon multiple data sources, including a greatly under-utilized national survey series that is maintained under National Center for Education Statistics (NCES) auspices, I reaffirm the overall strength of educational attainment as a young adult voter turnout predictor while providing new evidence that attainment effects are attenuated by other educational and non-educational circumstances and traits. My results, which also reveal the dynamism of these influences in predicting young adult voter turnout, are suggestive of five areas in which the 26th Amendment can serve as a teachable moment to strengthen the democratic education mission through: (1) expanded post-high school enrollment opportunities; (2) energized high school citizenship training; (3) strengthened connections between the high school literacy and civics curricula; (4) improved use of technology to deliver civically relevant messages; and (5) more aggressive voter registration efforts on high school and college campuses.
The “K-Correction” for Irradiated Emission Lines in LMXBs: Evidence for a Massive Neutron Star in X1822–371 (V691 CrA)

We study the K-correction for the case of emission lines formed in the X-ray-illuminated atmosphere of a Roche lobe-filling star. We compute the K-correction as a function of the mass ratio q and the disk flaring angle α using a compact binary code in which the companion's Roche lobe is divided into 105 resolution elements. We also study the effect of the inclination angle in the results. We apply our model to the case of the neutron star low-mass X-ray binary X1822-371 (V691 CrA), where a K-emission velocity Kem = 300 ± 8 km s-1 has been measured by Casares et al. Our numerical results, combined with a previous determination of system parameters, yields 1.61 M☉ ≤ MNS ≤ 2.32 M☉ and 0.44 M☉ ≤ M2 ≤ 0.56 M☉ for the two binary components (i.e., 0.24 ≤ q ≤ 0.27), which provide compelling evidence for a massive neutron star in this system. We also discuss the implications of these masses into the evolutionary history of the binary.
Portfolio Insurance Strategies: A Comparison of Standard Methods When the Volatility of the Stock is Stochastic

We compare the performances of the two standard portfolio insurance methods: the Option Based Portfolio Insurance (OBPI) and the Constant Proportion Portfolio Insurance (CPPI), when the volatility of the stock index is stochastic. In this framework, we provide a quite general formula for the CPPI portfolio value. We use criteria such as comparison of payoffs functions at maturity and various quantiles. We emphasize in particular the role of the insured percentage of the initial investment.
Cell-type-specific transcriptomes and the Allen Atlas (II): discussion of the linear model of brain-wide densities of cell types

The voxelized Allen Atlas of the adult mouse brain (at a resolution of 200 microns) has been used in [arXiv:1303.0013] to estimate the region-specificity of 64 cell types whose transcriptional profile in the mouse brain has been measured in microarray experiments. In particular, the model yields estimates for the brain-wide density of each of these cell types. We conduct numerical experiments to estimate the errors in the estimated density profiles. First of all, we check that a simulated thalamic profile based on 200 well-chosen genes can transfer signal from cerebellar Purkinje cells to the thalamus. This inspires us to sub-sample the atlas of genes by repeatedly drawing random sets of 200 genes and refitting the model. This results in a random distribution of density profiles, that can be compared to the predictions of the model. This results in a ranking of cell types by the overlap between the original and sub-sampled density profiles. Cell types with high rank include medium spiny neurons, several samples of cortical pyramidal neurons, hippocampal pyramidal neurons, granule cells and cholinergic neurons from the brain stem. In some cases with lower rank, the average sub-sample can have better contrast properties than the original model (this is the case for amygdalar neurons and dopaminergic neurons from the ventral midbrain). Finally, we add some noise to the cell-type-specific transcriptomes by mixing them using a scalar parameter weighing a random matrix. After refitting the model, we observe than a mixing parameter of $5\%$ leads to modifications of density profiles that span the same interval as the ones resulting from sub-sampling.
3D FEM Calculation for Electric Field of Aluminum Electrolysis Cell Based on Ansys

The mathematical models of electric field of the 300 kA aluminum electrolysis cells were calculated with ANSYS. The result revealed that the potential of the each part of the aluminum electrolysis cell was higher at the center and lower at the edge, decreasing from top to bottom. Molten aluminum was similar to equipotential areas, and the voltage drop of the electrolyte is largest. The current of the each parts of the aluminum electrolysis cell flowed from the middle to the both sides, from the top to the bottom. The X horizontal currents of the melt were anti-symmetric along the long axis (X axis), the Y horizontal currents of the melt were anti-symmetric along the short axis t (Y axis). The voltage drop of the cell was measured and compared with the calculated results. The current efficiencies for the anode change patterns achieved in real cells were in excellent agreement with the model instability predictions. So the software ANSYS can well reflects actual status of the electric fields of the cells and can be used to design them.
Analysis of the Voltage Swing for Logic and Memory Applications in Si/SiGe Resonant Interband Tunnel Diodes Grown by Molecular Beam Epitaxy

A method is investigated to directly engineer the voltage swing in SiGe resonant interband tunnel diodes (RITDs). Voltage swing, defined here as the voltage difference between the peak voltage and the projected peak voltage, is independent of series resistance, and thus directly impacts the noise margin in hybrid tunnel diode memory and logic applications. The three components of the total RITD current are analyzed to describe the voltage swing. The dependence of voltage swing on delta-doping concentrations and post-growth annealing temperatures in SiGe RITDs grown by low-temperature molecular beam epitaxy (LT-MBE) is investigated and the experimental results are compared with a theoretical analysis. Techniques to increase the voltage swing are discussed
Functionality-Based Web Image Categorization

The World Wide Web provides an increasingly powerful and popular publication mechanism. Web documents often contain a large number of images serving various different purposes. Identifying the functional categories of these images has important applications including information extraction, web mining, web page summarization and mobile access. In this paper we outline a novel algorithm for automatic identification of two of the most important image categories, namely story and preview images.
Periostin Deficiency Increases Bone Damage and Impairs Injury Response to Fatigue Loading in Adult Mice

Bone damage removal and callus formation in response to fatigue loading are essential to prevent fractures. Periostin (Postn) is a matricellular protein that mediates adaptive response of cortical bone to loading. Whether and how periostin influences damage and the injury response to fatigue remains unknown. We investigated the skeletal response of Postn -/- and Postn +/+ mice after fatigue stimulus by axial compression of their tibia. In Postn +/+ mice, cracks number and surface (CsNb, CsS) increased 1h after fatigue, with a decrease in strength compared to non-fatigued tibia. At 15 days, CsNb had started to decline, while CtTV and CtBV increased in fatigued vs non-fatigued tibia, reflecting a woven bone response that was present in 75% of the fatigued bones. Cortical porosity and remodelling also prominently increased in the fatigued tibia of Postn +/+ mice. At 30 days, paralleling a continuous removal of cortical damage, strength of the fatigued tibia was similar to the non-fatigue tibia. In Postn -/- mice, cracks were detectable even in the absence of fatigue, while the amount of collagen crosslinks and tissue hardness was decreased compared to Postn +/+. Fatigue significantly increased CsNb and CsS in Postn -/-, but was not associated with changes in CtTV and CtBV, as only 16% of the fatigued bones formed some woven bone. Cortical porosity and remodelling did not increase either after fatigue in Postn -/- , and the level of damage remained high even after 30 days. As a result, strength remained compromised in Postn -/- mice. Contrary to Postn +/+ , which osteocytic lacunae showed a change in the degree of anisotropy (DA) after fatigue, Postn-/- showed no DA change. Hence periostin appears to influence bone materials properties, damage accumulation and repair, including local modeling/remodeling processes in response to fatigue. These observations suggest that the level of periostin expression could influence the propensity to fatigue fractures.
Financial distress and bankruptcy in highly levered transactions : the comparative roles of debt composition and governance changes

In the HLT literature there is conflicting evidence on the relative impact of debt composition, governance changes and the role of the LBO specialist on the likelihood of financial distress and bankruptcy. In this paper we examine the influence of these factors in a sample of HLTs. Our sample includes not only leveraged buyouts but also leveraged recapitalizations. Observing these transactions over time, we observe that debt composition is a more critical influence than proposed changes in control for the likelihood of an HLT encountering financial distress or going bankrupt. Our evidence is consistent with the Chemmanur and Fulghieri (1994) model of the choice between bank debt and public debt. As a result, our evidence questions the marginal contribution of private equity firms and suggests that further research on their role is needed.
Energy Derivatives' Market Dynamics

This chapter examines the EU Emissions Trading Scheme options and futures markets dynamics during the period 2005–2011. Observations on returns, volatilities and volumes on derivative instruments are studied. In addition, spot/future correlations, term structures and option implied volatility smiles and surfaces are examined. The aim is to ascertain whether the behavior of the EU ETS derivatives markets can be compared to that of commodity markets, specifically the developed West Texas Intermediate (WTI) crude oil derivatives market. The results indicate that the EU Emissions Trading Scheme derivatives markets have matured markedly since the start of Phase 2 of the Scheme, with rising volumes and declining return volatilities. Spot/future correlations, term structures and option volatility smiles and surfaces exhibit comparable behavior over time, albeit with certain discrepancies, with that found in the developed WTI crude oil derivatives market. These results are valuable both for traders of EU allowances and for those policy makers seeking to improve the design of the EU Emissions Trading Scheme.
Retinotopic organization of human visual cortex mapped with positron- emission tomography

The retinotopic organization of primary visual cortex was mapped in normal human volunteers. Positron-emission tomographic measurements of regional cerebral blood flow were employed to detect focal functional brain activation. Oxygen-15-labeled water, delivered by intravenous bolus, was used as the blood flow tracer to allow multiple stimulated- state (n = 5) and control-state (n = 3) measurements to be acquired for each of 7 subjects. Responses were identified by applying a maximum- detection algorithm to subtraction-format images of the stimulus- induced change in cerebral blood flow. Response locales were described using a standardized system of stereotactic coordinates. Changes in stimulus location (macular, perimacular, peripheral, upper-field, lower- field) caused systematic, highly significant changes in response locale within visual cortex. Discrete extrastriate visual responses were also observed.
Mind the Gap: Dangers of Divorcing Evaluations of Summary Content from Linguistic Quality

In this paper, we analyze the state of current human and automatic evaluation of topic-focused summarization in the Document Understanding Conference main task for 2005--2007. The analyses show that while ROUGE has very strong correlation with responsiveness for both human and automatic summaries, there is a significant gap in responsiveness between humans and systems which is not accounted for by the ROUGE metrics. In addition to teasing out gaps in the current automatic evaluation, we propose a method to maximize the strength of current automatic evaluations by using the method of canonical correlation. We apply this new evaluation method, which we call ROSE (ROUGE Optimal Summarization Evaluation), to find the optimal linear combination of ROUGE scores to maximize correlation with human responsiveness.
The dynamics of social assistance benefit receipt

This dissertation consists of three articles on social assistance benefit receipt dynamics in European countries. The first article presents an analysis of state dependence in benefit receipt in Germany based on annual survey data from the German Socio-Economic Panel. The observation period extends from 1995 to 2011, thus covering the 2005 'Hartz reforms'. I estimate a series of dynamic random-effects probit models to control for observed and unobserved heterogeneity and the endogeneity of initial conditions. The high observed state dependence has a substantial structural component, with benefit receipt one year ago being associated with an increase in the likelihood of receipt today by 13 percentage points. There is only little evidence for time-variation in state dependence. The second article presents evidence on spell durations and the frequency of repeat spells using monthly administrative data from Luxembourg, the Netherlands, Norway and Sweden. In the two Nordic countries, short-term benefit receipt is the norm, with only around 6p and 11p of spells in Norway and Sweden lasting longer than 12 months. Most recipients however have multiple spells. In Luxembourg and the Netherlands, long-term benefit receipt is frequent, with median spell durations of 14 and 9 months, respectively, and one-third and one-quarter of all spells lasting 24 months or longer. The total duration of benefit receipt across spells is much higher in the Netherlands and Luxembourg than in Norway and Sweden. The third article tests the validity of one of the central assumptions of dynamic discrete-choice models of benefit dynamics, the conditional Markov property. Using monthly administrative data from Norway, the article shows that the Markov property is violated as estimated state dependence is affected by the chosen time unit of analysis. The standard model can be improved by permitting for different entry and persistence equations and duration and occurrence dependence in benefit receipt.
Microlensing Sensitivity to Earth-Mass Planets in the Habitable Zone

Microlensing is one of the most powerful methods that can detect extrasolar planets, and a future space-based survey with a high monitoring frequency is proposed to detect a large sample of Earth-mass planets. In this paper, we examine the sensitivity of the future microlensing survey to Earth-mass planets located in the habitable zone. For this, we estimate the fraction of Earth-mass planets that will be located in the habitable zone of their parent stars by carrying out a detailed simulation of microlensing events based on standard models of the physical and dynamic distributions and the mass function of Galactic matter. From this investigation, we find that among the total detectable Earth-mass planets from the survey, those located in the habitable zone would comprise less than 3% even under a less conservative definition of the habitable zone. We find that the main reason for the low sensitivity is the projected star-planet separation at which the microlensing planet detection efficiency becomes maximum (lensing zone) is in most cases substantially larger than the median value of the habitable zone. We find that the ratio of the median radius of the habitable zone to the mean radius of the lensing zone is roughly expressed as dHZ/rE ~ 0.2(m/0.5 M☉)1/2.