Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of MAOA genotype, childhood trauma, and sex on trait and state-dependent aggression

Monoamine oxidase A (MAOA) genotypic variation has been associated with variation in aggression, especially in interaction with childhood trauma or other early adverse events. Male carriers of the low‐expressing variant (MAOA‐L) with childhood trauma or other early adverse events seem to be more aggressive, whereas female carriers with the high‐expressing variant (MAOA‐H) with childhood trauma or other early adverse events may be more aggressive. We further investigated the effects of MAOA genotype and its interaction with sex and childhood trauma or other early adverse events on aggression in a young adult sample. We hypothesized that the association between genotype, childhood trauma, and aggression would be different for men and women. We also explored whether this association is different for dispositional (trait) aggression versus aggression in the context of dysphoric mood. In all, 432 Western European students (332 women, 100 men; mean age 20.2) were genotyped for the MAOA gene. They completed measures of childhood trauma, state and trait measures of aggression‐related behaviors (STAXI), and cognitive reactivity to sad mood (LEIDS‐R), including aggression reactivity. Women with the MAOA‐H had higher aggression reactivity scores than women with the MAOA‐L. This effect was not observed in men, although the nonsignificant findings in men may be a result of low power. Effects on the STAXI were not observed, nor were there gene by environment interactions on any of the aggression measures. A protective effect of the low‐expression variant in women on aggression reactivity is consistent with previous observations in adolescent girls. In females, the MAOA‐H may predispose to aggression‐related problems during sad mood.
Infinite hierarchies and prior distributions

Suppose that we had independent data from an Exp(Oo1) distribution. In a Bayesian framework, we suppose that a priori 60 r Exp(01), and that with uncertainty on the hyperparameter 01, we might also give it a prior, Exp(02 1) say. In fact at each level of the hierarchy we can hedge our bets by imposing a further level of prior uncertainty. Suppose we impose N levels of the hierarchy by fixing the hyperparameter ON and sequentially setting
A Learning Algorithm for Continually Running Fully Recurrent Neural Networks

The exact form of a gradient-following learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have (1) the advantage that they do not require a precisely defined training interval, operating while the network runs; and (2) the disadvantage that they require nonlocal communication in the network being trained and are computationally expensive. These algorithms allow networks having recurrent connections to learn complex tasks that require the retention of information over time periods having either fixed or indefinite length.
Studies on pattern regulation in hydra. II. Factors controlling hypostome formation.

In a previous paper (Webster & Wolpert, 1966 a ) it was shown that during regulation the time required for the determination of the dominant region, the hypostome, was dependent on the original position of the hypostome-forming region on the linear axis. Hypostome determination occurred more quickly from distal than from proximal regions, suggesting an axial gradient. As Spiegelman (1945) has pointed out, a gradient in time for determination is not sufficient for limited realization to occur in a regulative system (Webster & Wolpert, 1966 a ). In addition, some mechanism for suppressing potentialities is required. One of the characteristic features of a dominant region is that it inhibits the formation of a new dominant region (Huxley & de Beer, 1934), and earlier work on hydra (Rand, Bovard & Minnich, 1926) has presented some evidence for inhibition of distal regeneration by distal structures. This paper will be concerned with a detailed analysis of the factors controlling hypostome formation.
Taxes, Leverage, and the Cost of Equity Capital

We examine the associations among leverage, corporate and investor level taxes, and the firm's implied cost of equity capital. Expanding on Modigliani and Miller [1958, 1963], the cost of equity capital can be expressed as a function of leverage and corporate and investor level taxes. Based on this expression, we predict that the cost of equity is increasing in leverage, and that corporate taxes mitigate this leverage-related risk premium, while the personal tax disadvantage of debt increases this premium. We empirically test these predictions using implied cost of equity estimates and proxies for the firm's corporate tax rate and the personal tax disadvantage of debt. Our results suggest that the equity risk premium associated with leverage is decreasing in the corporate tax benefit from debt. We find some evidence that the equity risk premium from leverage is increasing in the personal tax penalty associated with debt. Copyright University of Chicago on behalf of the Institute of Professional Accounting, 2006.
Improving permeability semivariograms with transition probability models of hierarchical sedimentary architecture derived from outcrop analog studies

As analogs for aquifers, outcrops of sedimentary deposits allow sedimentary units to be mapped, permeability to be measured with high resolution, and sedimentary architecture to be related to the univariate and spatial bivariate statistics of permeability. Sedimentary deposits typically can be organized into hierarchies of unit types and associated permeability modes. The types of units and the number of hierarchical levels defined on an outcrop might vary depending upon the focus of the study. Regardless of how the outcrop sediments are subdivided, a composite bivariate statistic like the permeability semivariogram is a linear summation of the autosemivariograms and cross semivariograms for the unit types defined, weighted by the proportions and transition probabilities associated with the unit types. The composite sample semivariogram will not be representative unless data locations adequately define these transition probabilities. Data reflecting the stratal architecture can often be much more numerous than permeability measurements. These lithologic data can be used to better define transition probabilities and thus improve the estimates of the composite permeability semivariogram. In doing so, bias created from the incomplete exposure of units can be reduced by a Bayesian approach for estimating unit proportions and mean lengths. We illustrate this methodology with field data from an outcrop in the Española Basin, New Mexico.
Moduli Stabilisation versus Chirality for MSSM like Type IIB Orientifolds

We investigate the general question of implementing a chiral MSSM like D-brane sector in Type IIB orientifold models with complete moduli stabilisation via F-terms induced by fluxes and space-time instantons, respectively gaugino condensates. The prototype examples are the KKLT and the so-called large volume compactifications. We show that the ansatz of first stabilising all moduli via F-terms and then introducing the Standard Model module is misleading, as a chiral sector notoriously influences the structure of non-perturbative effects and induces a D-term potential. Focusing for concreteness on the large volume scenario, we work out the geometry of the swiss-cheese type Calabi-Yau manifold P_[1,3,3,3,5][15]_(3,75) and analyse whether controllable and phenomenologically acceptable Kaehler moduli stabilisation can occur by the combination of F- and D-terms.
Nasal-Associated Lymphoid Tissue Is a Mucosal Inductive Site for Virus-Specific Humoral and Cellular Immune Responses1

Peyer’s patches are known as mucosal inductive sites for humoral and cellular immune responses in the gastrointestinal tract. In contrast, functionally equivalent structures in the respiratory tract remain elusive. It has been suggested that nasal-associated lymphoid tissue (NALT) might serve as a mucosal inductive site in the upper respiratory tract. However, typical signs of mucosal inductive sites like development of germinal center reactions after Ag stimulation and isotype switching of naive B cells to IgA production have not been directly demonstrated. Moreover, it is not known whether CTL can be generated in NALT. To address these issues, NALT was structurally and functionally analyzed using a model of intranasal infection of C3H mice with reovirus. FACS and histological analyses revealed development of germinal centers in NALT in parallel with generation and expansion of IgA+ and IgG2a+ B cells after intranasal reovirus infection. Reovirus-specific IgA was produced in both the upper respiratory and the gastrointestinal tract, whereas production of reovirus-specific IgG2a was restricted to NALT, submandibular, and mesenteric lymph nodes. Moreover, virus-specific CTL were detected in NALT. Limiting dilution analysis showed a 5- to 6-fold higher precursor CTL frequency in NALT compared with a cervical lymph node. Together these data provide direct evidence that NALT is a mucosal inductive site for humoral and cellular immune responses in the upper respiratory tract.
The Effect of Collisional Enhancement of Balmer Lines on the Determination of the Primordial Helium Abundance

This paper describes a new determination of the primordial helium abundance (YP), based on the abundance analysis of five metal-poor extragalactic H II regions. For three regions of the sample (SBS 0335-052, I Zw 18, and H29) we present tailored photoionization models based on improved calculations with respect to previous models. In particular, we use the photoionization models to study quantitatively the effect of collisional excitation of Balmer lines on the determination of the helium abundance (Y) in the individual regions. This effect is twofold: first, the intensities of the Balmer lines are enhanced with respect to the pure recombination value, mimicking a higher hydrogen abundance; second, the observed reddening is larger than the true extinction, as a result of the differential effect of collisions on different Balmer lines. In addition to these effects, our analysis takes into account the following features of H II regions: (1) the temperature structure, (2) the density structure, (3) the presence of neutral helium, (4) the collisional excitation of the He I lines, (5) the underlying absorption of the He I lines, and (6) the optical thickness of the He I lines. The object that shows the highest increase in Y after the inclusion of collisional effects in the analysis is SBS 0335-052, whose helium abundance has been revised by ΔY = +0.0107. The revised Y-values for the five objects in our sample yield an increase of +0.0035 in YP, giving YP = 0.2391 ± 0.0020.
Modular Multitask Reinforcement Learning with Policy Sketches

We describe a framework for multitask deep reinforcement learning guided by policy sketches. Sketches annotate tasks with sequences of named subtasks, providing information about high-level structural relationships among tasks but not how to implement them—specifically not providing the detailed guidance used by much previous work on learning policy abstractions for RL (e.g. intermediate rewards, subtask completion signals, or intrinsic motivations). To learn from sketches, we present a model that associates every subtask with a modular subpolicy, and jointly maximizes reward over full task-specific policies by tying parameters across shared subpolicies. Optimization is accomplished via a decoupled actor-critic training objective that facilitates learning common behaviors from multiple dissimilar reward functions. We evaluate the effectiveness of our approach in three environments featuring both discrete and continuous control, and with sparse rewards that can be obtained only after completing a number of high-level sub-goals. Experiments show that using our approach to learn policies guided by sketches gives better performance than existing techniques for learning task-specific or shared policies, while naturally inducing a library of interpretable primitive behaviors that can be recombined to rapidly adapt to new tasks.
Collective properties of cellular identity: a computational approach

Cell type (e.g. pluripotent cell, fibroblast) is the end result of many complex processes that unfold due to evolutionary, developmental, and transformational stimuli. A cell's phenotype and the discrete, a priori states that define various cell subtypes (e.g. skin fibroblast, embryonic stem cell) are ultimately part of a continuum that may predict changes and systematic variation in cell subtypes. These features can be both observable in existing cellular states and hypothetical (e.g. unobserved). In this paper, a series of approaches will be used to approximate the continuous diversity of gene expression across a series of pluripotent, totipotent, and fibroblast cellular subtypes. We will use a series of previously-collected datasets and analyze them using three complementary approaches: the computation of distances based on the subsampling of diversity, assessing the separability of individual genes for a specific cell line both within and between cell types, and a hierarchical soft classification technique that will assign a membership value for specific genes in specific cell types given a number of different criteria. These approaches will allow us to assess the observed gene-expression diversity in these datasets, as well as assess how well a priori cell types characterize their constituent populations. In conclusion, the application of these findings to a broader biological context will be discussed.
New Statistical Applications for Differential Privacy

Differential privacy is a relatively recent development in the field of privacy-preserving data mining, which was formulated to give a mathematically rigorous definition of privacy. The concept has spawned a great deal of work regarding the development of algorithms which are privacy-preserving under this definition, and also work which seeks to understand the fundamental limitations of such algorithms. When the goal is statistical inference it is important to understand what set of analyses may be carried out in the privacy-preserving framework with reasonable accuracy, and which data summaries and results may be reported. In this work we begin by examining fundamental limitations of differentially private procedures when the goal is to release a sparse histogram, or a contingency table. We also describe error bounds when the goal is model selection for a private contingency table. Through examples we will demonstrate the implications of these lower error bounds for statistical analysis with datasets of different sizes and dimensions. Thus far, differentially private algorithms appear to be restricted to the release of finite dimensional vectors (e.g., regression coefficients, point estimates, SVM parameters). We next develop methods for releasing functional data while preserving differential privacy. Specifically, we show that when the function of interest lies inside a reproducing kernel Hilbert space, then it satisfies differential privacy to release the function plus a Gaussian process noise term. As examples we consider kernel density estimation, kernel support vector machines, and suitably smooth functions which lie in a particular Sobolev space. Finally we propose a relaxed privacy definition called random differential privacy (RDP). Differential privacy requires that adding any new observation to a database will have small effect on the output of the data-release procedure. Random differential privacy requires that adding a randomly drawn new observation to a database will have small effect on the output. We show an analog of the composition property of differentially private procedures which applies to our new definition. We show how to release an RDP histogram and we show that RDP histograms are much more accurate than histograms obtained using ordinary differential privacy. We finally show an analog of the global sensitivity framework for the release of functions under our privacy definition. We demonstrate that an extension of this idea and describe how it relates to other looser privacy definitions that have begun appearing in the literature.
Evolving Readable String Test Inputs Using a Natural Language Model to Reduce Human Oracle Cost

The frequent non-availability of an automated oracle means that, in practice, checking software behaviour is frequently a painstakingly manual task. Despite the high cost of human oracle involvement, there has been little research investigating how to make the role easier and less time-consuming. One source of human oracle cost is the inherent unreadability of machine-generated test inputs. In particular, automatically generated string inputs tend to be arbitrary sequences of characters that are awkward to read. This makes test cases hard to comprehend and time-consuming to check. In this paper we present an approach in which a natural language model is incorporated into a search-based input data generation process with the aim of improving the human readability of generated strings. We further present a human study of test inputs generated using the technique on 17 open source Java case studies. For 10 of the case studies, the participants recorded significantly faster times when evaluating inputs produced using the language model, with medium to large effect sizes 60% of the time. In addition, the study found that accuracy of test input evaluation was also significantly improved for 3 of the case studies.
Exploiting Illumina Sequencing for the Development of 95 Novel Polymorphic EST-SSR Markers in Common Vetch (Vicia sativa subsp. sativa)

The common vetch (Vicia sativa subsp. sativa), a self-pollinating and diploid species, is one of the most important annual legumes in the world due to its short growth period, high nutritional value, and multiple usages as hay, grain, silage, and green manure. The available simple sequence repeat (SSR) markers for common vetch, however, are insufficient to meet the developing demand for genetic and molecular research on this important species. Here, we aimed to develop and characterise several polymorphic EST-SSR markers from the vetch Illumina transcriptome. A total number of 1,071 potential EST-SSR markers were identified from 1025 unigenes whose lengths were greater than 1,000 bp, and 450 primer pairs were then designed and synthesized. Finally, 95 polymorphic primer pairs were developed for the 10 common vetch accessions, which included 50 individuals. Among the 95 EST-SSR markers, the number of alleles ranged from three to 13, and the polymorphism information content values ranged from 0.09 to 0.98. The observed heterozygosity values ranged from 0.00 to 1.00, and the expected heterozygosity values ranged from 0.11 to 0.98. These 95 EST-SSR markers developed from the vetch Illumina transcriptome could greatly promote the development of genetic and molecular breeding studies pertaining to in this species.
Differential density of blood vessels in the mesencephalon of Macaque brain stem

The blood vessels (BV) of the brain stem show different patterns of development, and nutrient requeriments, metabolism and the activity of the different nuclei of the mesencephalon differ from one nucleus to another. The density of BV indirectly explains the blood flow intensity and physiological activity of the nuclei, and may explain the varying degrees of vulnerability of neurons to pathologies. To ascertain the different vascular densities of the mesencephalic nuclei, in the present work we used stereological methods to measure BV density in the Ventral Tegmental Area (VTA), the Substantia Nigra pars compacta (SNpc), the A8 Catecholaminergic Cell group (A8), the Periaqueductal Grey Matter (PAG) and the Locus Coeruleus (LC) of two intact macaques. The results pointed to a high density of BV in the LC; a low density in the SNpc, and an intermediate density in the VTA, A8 and PAG. These results confirm the high blood metabolism of the LC and suggest that the vulnerability of SNpc neurons may be related to the observed low density of BV.
Probing the intrinsic shape and alignment of dark matter haloes using SDSS galaxy groups

We study the three-dimensional and projected shapes of galaxy groups in the Sloan Digital Sky Survey Data Release 4, and examine the alignment between the orientation of the central galaxy and the spatial distribution of satellite galaxies. The projected ellipticity of a group is measured using the moments of the discrete distribution of its member galaxies. We infer the three-dimensional and projected axis ratios of their dark matter haloes by comparing the measured ellipticity distributions with those obtained from Monte Carlo simulations of projected, triaxial dark matter haloes with different axis ratios. We find that the halo shape has a strong dependence on the halo mass. While the haloes of low-mass groups are nearly spherical, those of massive groups tend to be prolate. For groups containing at least four members, the statistical distribution of their measured ellipticities does not have a strong dependence on the colours of their central galaxies. Our analysis further shows that the average three-dimensional axis ratio for haloes with 12 < log[M/(h −1 M� )] � 15 is about 1 : 0.46 : 0.46, resulting in a projected axis ratio of ∼0.77. Our results for the alignment between the orientation of the central galaxy of a group and the distribution of their satellite galaxies are in broad agreement with those obtained by Yang et al. The distribution of satellite galaxies preferentially aligns with the major axis of the central galaxy, with a clear dependence on both halo mass and galaxy colours. In particular, the alignment is stronger in more massive groups, and the strongest alignment is seen between red centrals and the distribution of red satellites. For groups with blue centrals, no significant alignment is detected. Finally, we examine how the observed alignment can be reproduced with the information about the halo axis ratios. The observed alignment signal can be reproduced if the angle between the major axis of the central galaxy and the projected major axis of the host halo has a Gaussian distribution with a mean of 0 ◦ and a dispersion of ∼23 ◦ .