Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Rare Genomic Changes Does Not Support the Unikont–Bikont Phylogeny and Suggests Cyanobacterial Symbiosis as the Point of Primary Radiation of Eukaryotes

The deep phylogeny of eukaryotes is an important but extremely difficult problem of evolutionary biology. Five eukaryotic supergroups are relatively well established but the relationship between these supergroups remains elusive, and their divergence seems to best fit a “Big Bang” model. Attempts were made to root the tree of eukaryotes by using potential derived shared characters such as unique fusions of conserved genes. One popular model of eukaryotic evolution that emerged from this type of analysis is the unikont–bikont phylogeny: The unikont branch consists of Metazoa, Choanozoa, Fungi, and Amoebozoa, whereas bikonts include the rest of eukaryotes, namely, Plantae (green plants, Chlorophyta, and Rhodophyta), Chromalveolata, excavates, and Rhizaria. We reexamine the relationships between the eukaryotic supergroups using a genome-wide analysis of rare genomic changes (RGCs) associated with multiple, conserved amino acids (RGC_CAMs and RGC_CAs), to resolve trifurcations of major eukaryotic lineages. The results do not support the basal position of Chromalveolata with respect to Plantae and unikonts or the monophyly of the bikont group and appear to be best compatible with the monophyly of unikonts and Chromalveolata. Chromalveolata show a distinct, additional signal of affinity with Plantae, conceivably, owing to genes transferred from the secondary, red algal symbiont. Excavates are derived forms, with extremely long branches that complicate phylogenetic inference; nevertheless, the RGC analysis suggests that they are significantly more likely to cluster with the unikont–Chromalveolata assemblage than with the Plantae. Thus, the first split in eukaryotic evolution might lie between photosynthetic and nonphotosynthetic forms and so could have been triggered by the endosymbiosis between an ancestral unicellular eukaryote and a cyanobacterium that gave rise to the chloroplast.
The Microeconomics of Inequality, Poverty and Market Liberalizing Reforms

This paper illustrates how the use of microeconometric techniques can be used to uncover the micro dynamics behind macro shocks. Using Mexican micro data we find out that—controlling for everything else—between 1994 and 1998 returns to personal characteristics in the tradable sector increased particularly those of skilled labourers. By the year 2000 the positive shock upon the tradeable sector vanishes with returns to personal characteristics converging to the levels observed in the non-tradable sector. We use our model’s results to simulate a scenario where the Mexican economy experienced
Impact of Color Space on Human Skin Color Detection Using an Intelligent System

Skin detection is a primary step in many applications such as face detection and online pornography filtering. Due to the robustness of color as a feature of human skin, skin detection techniques based on skin color information have gained much attention recently. Many researches have been done on skin color detection over the last years. However, there is no consensus on what color space is the most appropriate for skin color detection. Several comparisons between different color spaces used for skin detection are made, but one important question still remains unanswered is, “what is the best color space for skin detection. In this paper, a comprehensive comparative study using the Multi Layer Perceptron neural network MLP is used to investigate the effect of color-spaces on overall performance of skin detection. To increase the accuracy of skin detection the median filter and the elimination steps are implemented for all color spaces. The experimental results showed that the YIQ color space gives the highest separability between skin and non-skin pixels among the different color spaces tested. Key-Words: skin detection, color-space, Neural Network
Single Cell Expression Data Reveal Human Genes that Escape X-Chromosome Inactivation

Sex chromosomes pose an inherent genetic imbalance between genders. In mammals, one of the female’s X-chromosomes undergoes inactivation (Xi). Indirect measurements estimate that about 20% of Xi genes completely or partially escape inactivation. The identity of these escapee genes and their propensity to escape inactivation remain unsolved. A direct method for identifying escapees was applied by quantifying differential allelic expression from single cells. RNA-Seq fragments were assigned to informative SNPs which were labeled by the appropriate parental haplotype. This method was applied for measuring allelic specific expression from Chromosome-X (ChrX) and an autosomal chromosome as a control. We applied the protocol for measuring biallelic expression from ChrX to 104 primary fibroblasts. Out of 215 genes that were considered, only 13 genes (6%) were associated with biallelic expression. The sensitivity of escapees' identification was increased by combining SNP mapping for parental diploid genomes together with RNA-Seq from clonal single cells (25 lymphoblasts). Using complementary protocols, referred to as strict and relaxed, we confidently identified 25 and 31escapee genes, respectively. When pooled versions of 30 and 100 cells were used, <50% of these genes were revealed. We assessed the generality of our protocols in view of an escapee catalog compiled from indirect methods. The overlap between the escapee catalog and the genes’ list from this study is statistically significant (P-value of E-07). We conclude that single cells’ expression data are instrumental for studying X-inactivation with an improved sensitivity. Finally, our results support the emerging notion of the non-deterministic nature of genes that escape X-chromosome inactivation.
Estrogens as a cause of human cancer: the Richard and Hinda Rosenthal Foundation award lecture.

The concept that hormones can cause, i.e., increase the incidence of, neoplasia was first developed by Bittner et al. (1), based on experimental studies of estrogens and mammary can cer in mice. We have refined that concept into a hypothesis for a major role of estrogen and other hormones in the etiology of several human cancers (2). A key element of this hypothesis is that neoplasia is the consequence of excessive hormonal stim ulation of a particular target organ, the normal growth and function of which are under hormonal control. The response of this end organ (e.g., endometrium, breast) to the proliferative effects of the hormone is a progression from normal growth to hyperplasia to neoplasia. In this model, hormones increase the incidence of neoplasia in the absence of outside initiators such as chemicals or ionizing radiation. We have hypothesized three specific circumstances in which estrogen plays a role in this model of hormone-induced neopla sia. In the first two circumstances, which relate to the breast and the endometrium, estrogens themselves act as the stimu latory hormones, increasing the frequency of mitotic activity in the target organ. As rare consequences of this estrogen-induced proliferation, malignant phenotypes develop due to errors in the mechanics of cell division (e.g., DNA copying errors, chro mosomal translocations, etc.) (Fig. 1). We believe that breast cancer risk is determined primarily by the total cumulative exposure of breast tissue to bioavailable estrogens and the associated cumulative mitotic activity. Al though a related mechanism applies to endometrial cancer, the critical exposure in the endometrium is not estrogen per se but that fraction of estrogen which is unopposed by the modifying influences of progesterone. The primary prevention of these two estrogen-induced neoplasms probably will come not from control of exposure to classical exogenous initiators but from modification of factors which directly affect the secretion, tissue binding, and availability of estrogen itself over a woman's entire
Nonsmooth Matrix Valued Functions Defined by Singular Values

A class of matrix valued functions defined by singular values of nonsymmetric matrices is shown to have many properties analogous to matrix valued functions defined by eigenvalues of symmetric matrices. In particular, the (smoothed) matrix valued Fischer-Burmeister function is proved to be strongly semismooth everywhere. This result is also used to show the strong semismoothness of the (smoothed) vector valued Fischer-Burmeister function associated with the second order cone. The strong semismoothness of singular values of a nonsymmetric matrix is discussed and used to analyze the quadratic convergence of Newton’s method for solving the inverse singular value problem.
A VISCOSITY SOLUTION METHOD FOR SHAPE-FROM-SHADING WITHOUT IMAGE BOUNDARY DATA

In this paper we propose a solution of the Lambertian shape-from-shading (SFS) problem by designing a new mathematical framework based on the notion of viscosity solution. The power of our approach is twofolds: (1) it defines a notion of weak solutions (in the viscosity sense) which does not necessarily require boundary data. Moreover, it allows to characterize the viscosity solutions by their “minimums”; and (2) it unifies the works of [Rouy and Tourin, SIAM J. Numer. Anal. 29 (1992) 867–884], [Lions et al . , Numer. Math. 64 (1993) 323–353], [Falcone and Sagona, Lect. Notes Math. 1310 (1997) 596–603], [Prados et al. , Proc. 7th Eur. Conf. Computer Vision 2351 (2002) 790–804; Prados and Faugeras, IEEE Comput. Soc. Press 2 (2003) 826–831], based on the notion of viscosity solutions and the work of [Dupuis and Oliensis, Ann. Appl. Probab. 4 (1994) 287–346] dealing with classical solutions.
A Dynamic General Equilibrium Approach to Asset Pricing Experiments

We use laboratory experiments to test a consumption-based general equilibrium model of asset pricing, which posits that agents buy and sell assets for the purpose of intertemporally smoothing consumption. Such asset pricing models are widely used by macroeconomists and finance researchers but have not yet been subjected to experimental testing. In the experiments we induced several features which, according to the theory, determine asset prices, such as risk and time preferences and the process for income and dividend payments. Our analysis indicates that intertemporal consumption-smoothing strongly inhibits the formation and magnitude of asset price bubbles, a stark departure from most recent asset pricing experiments. In fact, when subjects are motivated to smooth consumption, assets trade at a discount relative to their expected value and markets are thick; when this condition is eliminated in an otherwise identical economy, assets trade at a premium in thin markets. For useful comments we thank Elena Asparouhova, Peter Bossaerts, Craig Brown, John Geanakoplos, Stephen Spear and seminar participants at Claremont Graduate University Department of Politics and Economics, the University of Utah Department of Finance, the 2009 CARESS-Cowles Conference on General Equilibrium and its Applications, the 2009 Society for the Advancement of Economic Theory Conference, and the 2009 Economic Science Association North American Regional Meeting. Contact: sean.crockett@baruch.cuny. edu Contact: jduffy@pitt.edu
The matter power spectrum from the Lyα forest: an optical depth estimate

We measure the matter power spectrum from 31 Lyα spectra spanning the redshift range of 1.6‐3.6. The optical depth, τ , for Lyα absorption of the intergalactic medium is obtained from the flux using the inversion method of Nusser & Haehnelt. The optical depth is converted to density by using a simple power-law relation, τ ∝ (1 + δ) α . The non-linear 1D power spectrum of the gas density is then inferred with a method that makes simultaneous use of the one- and two-point statistics of the flux and compared against theoretical models with a likelihood analysis. A cold dark matter model with standard cosmological parameters fits the data well. The power-spectrum amplitude is measured to be (assuming a flat Universe), σ 8 = (0.92 ± 0.09) × (� m/0.3) −0.3 , with α varying in the range of 1.56‐1.8 with redshift. Enforcing the same cosmological parameters in all four redshift bins, the likelihood analysis suggests some evolution in the temperature‐density relation and the thermal smoothing length of the gas. The inferred evolution is consistent with that expected if reionization of He II occurred at z ∼ 3.2. A joint analysis with the Wilkinson Microwave Anisotropy Probe results together with a prior on the Hubble constant as suggested by the Hubble Space Telescope key project data,
Ranking predicted protein structures with support vector regression

Protein structure prediction is an important problem of both intellectual and practical interest. Most protein structure prediction approaches generate multiple candidate models first, and then use a scoring function to select the best model among these candidates. In this work, we develop a scoring function using support vector regression (SVR). Both consensus‐based features and features from individual structures are extracted from a training data set containing native protein structures and predicted structural models submitted to CASP5 and CASP6. The SVR learns a scoring function that is a linear combination of these features. We test this scoring function on two data sets. First, when used to rank server models submitted to CASP7, the SVR score selects predictions that are comparable to the best performing server in CASP7, Zhang‐Server, and significantly better than all the other servers. Even if the SVR score is not allowed to select Zhang‐Server models, the SVR score still selects predictions that are significantly better than all the other servers. In addition, the SVR is able to select significantly better models and yield significantly better Pearson correlation coefficients than the two best Quality Assessment groups in CASP7, QA556 (LEE), and QA634 (Pcons). Second, this work aims to improve the ability of the Robetta server to select best models, and hence we evaluate the performance of the SVR score on ranking the Robetta server template‐based models for the CASP7 targets. The SVR selects significantly better models than the Robetta K*Sync consensus alignment score. Proteins 2008. © 2007 Wiley‐Liss, Inc.
Software quality and agile methods

Agile methods may produce software faster but we also need to know how they meet our quality requirements. In this paper we compare the waterfall model with agile processes to show how agile methods achieve software quality under time pressure and in an unstable requirements environment, i.e. we analyze agile software quality assurance. We present a detailed waterfall model showing its software quality support processes. We then show the quality practices that agile methods have integrated into their processes. This allows us to answer the question "can agile methods ensure quality even though they develop software faster and can handle unstable requirements? ".
Online Learning: From Information Dissemination to Fostering Collaboration

In this article the trajectory of an online course in which graduate students collaboratively investigated and shared their personal experiences with respect to adult development is described. For this study, naturalistic inquiry was used to gain a holistic view of this semester-long course and to identify the specific emergent issues that characterized course dynamics. Using open, axial, and, to a lesser degree, selective coding, the following three issues were selected for further discussion: (a) flexibility of course to accommodate participants ; (b) co-construction of meaning through the sharing of personal experiences; and (c) the expression of vulnerability and personal growth. This course provided evidence that on-line courses can support deep learning about content, open sharing about personal experiences, and the development of a sense of camaraderie among participants. Students readily shared their feelings, critically examined course issues, extended their support in helping peers, and embraced many of the challenges of taking an online course. Implications are that benefits of online courses extend beyond the time and 106 Barab, Thomas, and Merrill place independence they provide for participants, but also include the reflective and social environment they can foster. Additionally, in terms of developing environments to support interactivity, especially with respect to human-human interaction , it may be that less is more. Over the last decade we have witnessed an explosion of the use of the Internet for supporting distributed education World Wide Web (WWW or Web), creates exciting opportunities to make information available to large numbers of users residing at distributed locations and who work at different times. As such, there are numerous courses and even entire degrees being offered online—referring to those courses taking place by way of a computer network One frequently cited reason for the development of these online courses is the increased availability of educational opportunities to users who, if required to be at a particular location (e.g., university classroom) at a particular time, would not be able to take the course. Less frequently given as a rationale for these courses is that the learning climate that develops online is more supportive in terms of promoting reflection, intimacy, and community than are those climates that emerge in the traditional classroom learning environments (Sheingold, 1991; Spitzer, 1998). In fact, it has been argued that courses taken online are impersonal, superficial, misdirected, and potentially dehumanizing and depressing, with online courses actually disrupting the student-instructor interaction that creates a …
MicroRNA-31 Predicts the Presence of Lymph Node Metastases and Survival in Patients with Lung Adenocarcinoma

Purpose: We conducted genome-wide miRNA-sequencing (miRNA-seq) in primary cancer tissue from patients of lung adenocarcinoma to identify markers for the presence of lymph node metastasis. Experimental Design: Markers for lymph node metastasis identified by sequencing were validated in a separate cohort using quantitative PCR. After additional validation in the The Cancer Genome Atlas (TCGA) dataset, functional characterization studies were conducted in vitro. Results: MiR-31 was upregulated in lung adenocarcinoma tissues from patients with lymph node metastases compared with those without lymph node metastases. We confirmed miR-31 to be upregulated in lymph node-positive patients in a separate patient cohort (P = 0.009, t test), and to be expressed at higher levels in adenocarcinoma tissue than in matched normal adjacent lung tissues (P < 0.0001, paired t test). MiR-31 was then validated as a marker for lymph node metastasis in an external validation cohort of 233 lung adenocarcinoma cases of the TCGA (P = 0.031, t test). In vitro functional assays showed that miR-31 increases cell migration, invasion, and proliferation in an ERK1/2 signaling-dependent manner. Notably, miR-31 was a significant predictor of survival in a multivariate cox regression model even when controlling for cancer staging. Exploratory in silico analysis showed that low expression of miR-31 is associated with excellent survival for T2N0 patients. Conclusions: We applied miRNA-seq to study microRNomes in lung adenocarcinoma tissue samples for the first time and potentially identified a miRNA predicting the presence of lymph node metastasis and survival outcomes in patients of lung adenocarcinoma. Clin Cancer Res; 19(19); 5423–33. ©2013 AACR.
A Suffix Tree Approach to Text Categorisation Applied to Spam Filtering

We present an approach to textual classification based on the suffix tree data structure and apply it to spam filtering. A method for scoring of documents u sing the suffix tree is developed and a number of scoring and score normalisation functions ar e tested. Our results show that the character level representation of documents and classes fa cilitated by the suffix tree significantly improves classification accuracy when compared with the cur rently popular naive Bayesian filtering method.
Non-Hermitian quantum mechanics of non-diagonalizable Hamiltonians: puzzles with self-orthogonal states

We consider quantum mechanics with non-Hermitian quasi-diagonalizable Hamiltonians, i.e. the Hamiltonians having a number of Jordan cells, in particular, biorthogonal bases. The 'self-orthogonality' phenomenon is clarified in terms of a correct spectral decomposition and it is shown that 'self-orthogonal' states never jeopardize a resolution of identity and thereby quantum averages of observables. The example of a complex potential leading to one Jordan cell in the Hamiltonian is constructed and its origin from level coalescence is elucidated. Some puzzles with zero-binorm bound states in a continuous spectrum are unravelled with the help of a correct resolution of identity.
NO ASSOCIATION BETWEEN MTHFR C677T AND SERUM URIC ACID LEVELS AMONG JAPANESE WITH ABCG2 126QQ AND SLC22A12 258WW

ABSTRACT Several genome-wide association studies (GWAS) have revealed that single nucleotide polymorphisms (SNPs) of ABCG2 and SLC22A12 were strongly associated with serum uric acid (SUA), but those of methylene tetrahydrofolate reductase (MTHFR) were not. However, there were several studies indicating the association with MTHFR C677T polymorphism. This study examined the association with the polymorphism, taking into account the genotypes of ABCG2 Q126X and SLC22A12 W258X. Subjects were 5,028 health checkup examinees of Seirei Preventive Health Care Center (3,416 males and 1,612 females) aged 35 to 69 years, who participated in the Japan Multi-Institutional Collaborative Cohort Study (J-MICC Study). Hyperuricemia was defined as SUA equal to 7 mg/dL or over. The genotype frequency was 35.9% for CC, 48.1% for CT, and 16.0% for TT, being in Hardy-Weinberg equilibrium (p=0.90). Among 4,425 participants with ABCG2 126QQ and SLC22A12 258WW who were not under medication for hyperuricemia, the mean SUA was 5.6 mg/dL, 5.6 mg/dL, and 5.7 mg/dL, respectively. When 114 participants with ABCG2 126QQ and SLC22A12 258WW under medication for hyperuricemia were included in hyperuricemia cases, the sex-age adjusted odds ratio (OR) of hyperuricemia was not significant; OR=1.00 (95% confidence interval, 0.89–1.24) for CT genotype and OR=0.98 (0.84–1.32) for TT genotype, relative to CC genotype. The present study indicated no association between SUA and MTHFR C677T genotype, after the influences of ABCG2 Q126X and SLC22A12 W258X were removed.
Numerical Solution of Non-Homogeneous Markov Processes through Uniformization

Numerical algorithms based on uniformization have been proven to be numerically stable and computationally at tractive to compute transient state distributions in ho mogeneous continuous time Markov chains Recently Van Dijk van Dijk formulated uniformization for non homogeneous Markov processes and it is of interest to investigate numerical algorithms based on uniformiza tion for non homogeneous models as well We will in troduce three di erent uniformization based algorithms for non homogeneous Markov processes We implement all three algorithms and use an example of a duplex safety model to compare the algorithms with respect to accuracy memory use and speed Based on these re sults we provide guidelines for the implementation and application of uniformization based algorithms for non homogeneous Markov processes