Miracle-dz/UniFAR-FTUs huggingface dataset:
Procedures for generating gamma variates with non-integer parameter sets

One of the most useful distributions in stochastic modeling is the two parameter gamma distribution. This paper presents a technique for generating random gamma variates from any two parameter gamma form with either integer or non-integer parameters. Only two techniques are presently available for generating gamma variates with a non-integer shape parameter, those being a variate averaging technique proposed by Naylor, et al. and a rejection scheme proposed by Johnk. The three generation schemes are compared with respect to (1) statistical goodness of fit, (2) computer running time and (3) random number calls. The author's scheme is shown to be statistically comparable with respect to goodness of fit, and generally superior relevant to computer running times and random number calls.
TGF-β1 Gene -509C/T Polymorphism and Coronary Artery Disease: An Updated Meta-Analysis Involving 11,701 Subjects

Background: The transforming growth factor-β1 (TGF-β1) gene -509C/T polymorphism has been suggested to be associated with increased coronary artery disease (CAD) risk. However, the individual studies results are still inconsistent. Objective and methods: To investigate the relationship between TGF-β1 gene -509C/T polymorphism and CAD, a meta-analysis involving 11,701 participants from 8 individual studies was conducted. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals were evaluated by using random or fixed effect models. Results: A significant association between TGF-β1 gene -509C/T polymorphism and CAD was detected in the total population under allelic (OR: 1.130, 95% CI: 1.060–1.200, P = 0.0001), recessive (OR: 1.390, 95% CI: 1.100–1.750, P = 0.006), dominant (OR: 0.857, 95% CI: 0.785–0.935, P = 2.507 × 10−4), homozygous (OR: 1.258, 95% CI: 1.098–1.442, P = 0.001), heterozygous (OR: 1.147, 95% CI: 1.046–1.257, P = 0.003), and additive genetic models (OR: 1.131, 95% CI: 1.063–1.204, P = 5.442 × 10−5). In the subgroup analysis, there was a significant association between them in Chinese population under all of the genetic models (P < 0.05), except under the heterozygous genetic model (P > 0.05). In the Caucasian subgroup, a significant association between them was also detected under all of the genetic models (P < 0.05), except under the recessive genetic model (P > 0.05). Conclusions: TGF-β1 gene -509C/T polymorphism was significantly associated with increased CAD risk. The people with T allele of TGF-β1 gene -509C/T polymorphism might be predisposed to CAD.
Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings

Machine learning applications often involve data that can be analyzed as unit vectors on a d-dimensional hypersphere, or equivalently are directional in nature. Spectral clustering techniques generate embeddings that constitute an example of directional data and can result in different shapes on a hypersphere (depending on the original structure). Other examples of directional data include text and some sub-domains of bioinformatics. The Watson distribution for directional data presents a tractable form and has more modeling capability than the simple von Mises-Fisher distribution. In this paper, we present a generative model of mixtures of Watson distributions on a hypersphere and derive numerical approximations of the parameters in an Expectation Maximization (EM) setting. This model also allows us to present an explanation for choosing the right embedding dimension for spectral clustering. We analyze the algorithm on a generated example and demonstrate its superiority over the existing algorithms through results on real datasets.
Managing cross layer information in OMNeT + + network simulations

This paper describes a general approach to dealing with cross layer information in OMNeT++-based network simulations. Rather than prescribe a specific cross layer architecture, this work is intended to address the software engineering problem of passing information between simulation modules in a sound way. An XML-based mechanism for passing information between modules using OMNeT++’s controlInfo data structure is presented. Because XML is an intermediate format for the OMNeT++ network description language (NED), it is further suggested that allowing NED files to be annotated with information about cross layer interactions will enhance readability and reuse-ability. A further goal of this paper is to initiate discussion and collaboration in the Swedish (and international) OMNeT++ community.
Perceived Conflict and Leader Dominance: Individual and Contextual Factors Behind Preferences for Dominant Leaders

Recent research finds that political candidates and leaders with dominant, masculine physical features are more preferred under conditions of conflict than of cooperation. Importantly, however, methodological limitations of past research have hindered the identification of whether this effect reflects that voters intuitively view (1) dominant leaders as more competent in solving problems of conflict, (2) nondominant leaders as more competent in solving problems of cooperation, or (3) both. In this article, we utilize recent advances in evolutionary psychology to form precise predictions on the nature of the underlying psychology and employ an unprecedented array of data types—including highly controlled experiments, natural experiments, and behavioral measures—to investigate the validity of these predictions. Using large approximately nationally representative surveys of 2,009 Poles and Ukrainians fielded during the Crimea crisis in 2014, we find that preferences for leader dominance are exclusively driven by the intuition that dominant leaders are better able to facilitate aggressive responses during social conflict and that these preferences are regulated by contextual conditions and individual predispositions related to such responses.
Prefrontal Contributions to Rule-based and Information-integration Category Learning

Previous research revealed that the basal ganglia play a critical role in category learning [Ell, S. (2006). Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks. Modeling visual attention and category learning in amnesiacs, striatal-damaged patients and normal aging. In Advances in Clinical-cognitive science: formal modeling and assessment of processes and symptoms (pp. 113–146). Washington DC: American Psychological Association] but less is known about the specific role of prefrontal cortical (PFC) regions in category learning. The current study examined rule-based (RB) and information-integration (II) category learning in 13 patients with damage primarily to ventral PFC regions. After 600 learning trials with feedback, patients were significantly less accurate than matched controls on both RB and II learning. Model-based analysis identified subgroups of patients whose impaired performance in each task was due to the use of sub-optimal learning strategies. Those patients impaired at either II or RB learning, performed significantly worse on the Wisconsin Card Sorting Test, a test of abstract rule formation and the ability to shift and maintain rules. Lesion analysis pointed to damage in a fairly circumscribed region of ventral medial prefrontal cortex as common to the impaired group of patients and those patients without ventral PFC damage mostly performed normally. These results provide further evidence that the ventromedial prefrontal cortex is critically important for the ability to monitor and integrate feedback in order to select and maintain optimal learning strategies.
In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines

In-sample approaches to model selection and error estimation of support vector machines (SVMs) are not as widespread as out-of-sample methods, where part of the data is removed from the training set for validation and testing purposes, mainly because their practical application is not straightforward and the latter provide, in many cases, satisfactory results. In this paper, we survey some recent and not-so-recent results of the data-dependent structural risk minimization framework and propose a proper reformulation of the SVM learning algorithm, so that the in-sample approach can be effectively applied. The experiments, performed both on simulated and real-world datasets, show that our in-sample approach can be favorably compared to out-of-sample methods, especially in cases where the latter ones provide questionable results. In particular, when the number of samples is small compared to their dimensionality, like in classification of microarray data, our proposal can outperform conventional out-of-sample approaches such as the cross validation, the leave-one-out, or the Bootstrap methods.
Role of Oxygen in Cystic Fibrosis Transmembrane Conductance Regulator Expression and

A perforating gun having no firing head and no primary explosives is attached to a tubing string and the tubing string is run into a borehole. A new well apparatus, having a firing head, is run into the tubing string until the firing head is adjacent the perforating gun. The firing head in the well apparatus detonates, firing the perforating gun. If the firing head fails to detonate, one need only remove the well apparatus from the tubing string in order to gain access to the firing head, for repair and replacement thereof. One need not remove the tubing string to gain access to the firing head.
Adaptive Object Acquisition

We propose an active vision system for object acquisition. The core of our approach is a reinforcement learning module which learns a strategy to scan an object. The agent moves a virtual camera around an object and is able to adapt dynamically to different conditions of its environment such as different objects and different purposes of the data acquisition by means of a reinforcement signal which rewards a chosen action with respect to the intendet purpose. The purpose of the acquisition we consider here is the reconstruction of non-acquired views. The learned scan path allows the generation of a sparse, view-based object representation which consists of some key views of the scan path. We present preliminary results from a project conducted with undergraduate students and show that the scan pattern obtained with the proposed method allows a better reconstruction of unfamiliar views than random scan paths. As the reward signal is based on local information at the current position of the camera this approach is an example for an organic-computing system with the emergence of a global strategy from local rules.
Restricted kappa chain expression in early ontogeny: biased utilization of V kappa exons and preferential V kappa-J kappa recombinations

To determine the extent of kappa chain diversity in the preimmune repertoire early in development, kappa cDNA libraries were analyzed from 15-d old fetal omentum, 18-d-old fetal liver, and 3-wk old bone marrow. An anchored polymerase chain reaction approach was used to avoid bias for particular V kappa families. From the sequence analysis of 27 bone marrow clones, 10 different families and 20 unique V kappa genes were identified. In contrast, the V kappa expression in the fetus is highly restricted and clearly differs from the broader distribution see in 3-wk-old bone marrow. Although several V kappa families were represented in the fetal library including V kappa 9, V kappa 10, V kappa 4,5, V kappa 8, and V kappa 1, one or two members of individual families were observed repeatedly. The fetal liver and omentum libraries were found to be largely overlapping. Given the V kappa families/exons identified in the fetal sequences, the mechanism of kappa rearrangements in the early repertoire appears to occur predominantly by inversion. Importantly, the fetal repertoire was further restricted by dominant V kappa-J kappa combinations such as V kappa 4,5-J kappa 5, V kappa 9-J kappa 4, and V kappa 10-J kappa 1. Since in some cases independent rearrangements could be established, the results indicate a bias for particular V kappa-J kappa joins. The results also suggest that clonal expansion/selection in the fetal repertoire takes place after light chain rearrangement as opposed to at the pre-B cell level in the bone marrow. The restriction observed in kappa light chain expression together with known restrictions in gene usage and junctional diversity at the heavy chain level indicate a remarkably conserved fetal repertoire.
Sensory Entrainment Mechanisms in Auditory Perception: Neural Synchronization Cortico-Striatal Activation

The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system.
An Extensible Memory Simulation Framework for Chip Multi-Processors

As the Chip Multi-processors (CMPs) becoming more attractive for high performance computing, key design decisions especially concerning memory hierarchy should be made more carefully. However, the existing micro-architecture simulators and software tools merely meet the needs of on-chip memory performance modeling. This paper presents a new pin-tool-based memory simulation framework for CMP, called gsim, which is intrinsically extensible with perfect support for widely used x86 ISA. The gsim is time-efficient with ignorable accuracy loss and can be easily extended for memory behavior evaluation and on- chip design space exploration. Keywords-Architecture Simulator; Cache Memory; Chip Multi- processors; Software Modeling I. INTRODUCTION
Copeptin, a Surrogate Marker for Arginine Vasopressin, Is Associated With Cardiovascular and All-Cause Mortality in Patients With Type 2 Diabetes (ZODIAC-31)

OBJECTIVE Copeptin, a surrogate marker for arginine vasopressin, has been associated with cardiovascular (CV) events and mortality in patients with type 2 diabetes complicated by end-stage renal disease or acute myocardial infarction. For stable outpatients, these associations are unknown. Our aim was to investigate whether copeptin is associated with CV and all-cause mortality in patients with type 2 diabetes treated in primary care. RESEARCH DESIGN AND METHODS Patients with type 2 diabetes participating in the observational Zwolle Outpatient Diabetes Project Integrating Available Care (ZODIAC) study were included. Cox regression analyses with age as time scale were used to assess the relationship of baseline copeptin with CV and all-cause mortality. RESULTS We included 1,195 patients (age 67 ± 12 years, 44% male). Median baseline copeptin concentration was 5.4 (interquartile range [IQR] 3.1–9.6) pmol/L. After a median follow-up of 5.9 (IQR 3.2–10.1) years, 345 patients died (29%), with 148 CV deaths (12%). Log2 copeptin was associated with CV (hazard ratio 1.17 [95% CI 0.99–1.39]; P = 0.068) and all-cause mortality (1.22 [1.09–1.36]; P = 0.001) after adjustment for age, sex, BMI, smoking, systolic blood pressure, total cholesterol to HDL ratio, duration of diabetes, HbA1c, treatment with ACE inhibitors and angiotensin receptor blockers, history of CV diseases, log serum creatinine, and log albumin to creatinine ratio; however, copeptin did not substantially improve risk prediction for CV (integrated discrimination improvement 0.14% [IQR −0.27 to 0.55%]) and all-cause mortality (0.77% [0.17–1.37%]) beyond currently used clinical markers. CONCLUSIONS We found copeptin to be associated with CV and all-cause mortality in patients with type 2 diabetes treated in primary care. Intervention studies should show whether the high CV risk in type 2 diabetes can be reduced by suppression of vasopressin, for example by reducing salt intake.
Influence Of Perceived Risk On Core Innovation: The Role Of Social Influence In Managing Uncertainty

INFLUENCE OF PERCEIVED RISK ON CORE INNOVATION: THE ROLE OF SOCIAL INFLUENCE IN MANAGING UNCERTAINTY Fangzhou Xu Advisor: Towhidul Islam University of Guelph, 2014 CoAdvisor: Theodore Noseworthy This paper attempts to investigate how the nature of innovative product attributes can affect consumer innovation adoptions. Specifically, we are interested in how and to what extent peer effects can influence this process. By operationalizing core innovation through changes of core product attributes as extreme incongruity, this research used an experiment design to predict product evaluations and time of adoptions for innovations. A total of 159 participants on-line surveys were collected concerning participants’ responses to the bike products, that differed in the changes of novel attributes. According to the results, participants evaluated innovative products with peripheral novel attributes more favourably and intended to adopt earlier than products with core novel attributes. More importantly, social network influence was reported to moderate such influence through the mediation of perceived risk. Based on the research findings, theoretical and managerial implications of this research are discussed. Limitations and future research directions are also acknowledged.
LADD Transmissions: Design, Manufacture, and New Compliance Models

We introduce new compliance models for LADD transmissions which reduce inelastic model errors by an order of magnitude. These errors are due to fiber bending, as opposed to the traditionally assumed fiber elasticity. The new LADD models are experimentally verified and applied to the modeling of concentric LADD devices. The new models are essential for the design of LADD based systems, the online estimation of LADD forces, and accurate control. Details of the design, manufacture and break-in phenomena are given, as well as the first experimental measurement of LADD efficiency, which is better than 90%.
Comparative hydrology across AmeriFlux sites: The variable roles of climate, vegetation, and groundwater

Watersheds can be characterized as complex space‐time filters that transform incoming fluxes of energy, water, and nutrients into variable output signals. The behavior of these filters is driven by climate, geomorphology, and ecology and, accordingly, varies from site to site. We investigated this variation by exploring the behavior of evapotranspiration signals from 14 different AmeriFlux sites. Evapotranspiration is driven by water and energetic forcing and is mediated by ecology and internal redistribution of water and energy. As such, it integrates biological and physical controls, making it an ideal signature to target when investigating watershed filtering. We adopted a paradigmatic approach (referred to as the null model) that couples the Penman‐Monteith equation to a soil moisture model and explored the deviations between the predictions of the null model and the observed AmeriFlux data across the sites in order to identify the controls on these deviations and their commonalities and differences across the sites. The null model reproduced evapotranspiration fluxes reasonably well for arid, shallow‐rooted systems but overestimated the effects of water limitation and could not reproduce seasonal variation in evapotranspiration at other sites. Accounting for plant access to groundwater (or deep soil moisture) reserves and for the effects of soil temperature on limiting evapotranspiration resolved these discrepancies and greatly improved prediction of evapotranspiration at multiple time scales. The results indicate that site‐specific hydrology and climatic factors pose important controls on biosphere‐hydrosphere interactions and suggest that plant–water table interactions and early season phenological controls need to be incorporated into even simple models to reproduce the seasonality in evapotranspiration.
Nanotechnology as a New Therapeutic Approach to Prevent the HIV-Infection of Treg Cells

Background HIV-1 has proved to infect regulatory T cells (Treg) modifying their phenotype and impairing their suppressive capacity. As Treg cells are a crucial component in the preservation of the immune homeostasis, we researched that the antiviral capacity of carboxilan dendrimers prevents the HIV-1 infection of Treg and their effects. The phenotype and suppressive capacity of Treg treated or non-treated with carbosilane dendrimers were studied by flow cytometry. Treated and non-treated Treg from healthy donors were infected with HIV-1NL4.3. The infection of Treg cells by HIV-1, and protective effect of two dendrimers were determined by measuring antigen p24gag in the supernatant of the culture and intracellular. Results The Treg cells were treated with cationic and anionic carbosilane dendrimers. The results showed that both dendrimers did not modify the phenotype and functionality of Treg cells compared with non- treated Treg cells. Anionic dendrimers showed high biocompatibility with normal activity of the Treg cells and in antiviral assays. These dendrimers were highly active against HIV-1 preventing the infection of Treg, and were able to protect the Treg from the Foxp3 downregulation induced by the HIV-1 infection. Conclusions This is the first work showing that the in vitro use of anionic dendrimers prevent the HIV-1 replication and the infection of expanded Treg cells in culture, which raises the possibility to use Treg cells therapeutically in HIV-1-infected subjects.
Carbon-Doped Hexagonal Boron Nitride: Analysis as π-Conjugate Molecules Embedded in Two Dimensional Insulator

We analyzed the electronic structures of carbon-doped hexagonal boron nitride, focusing on the comparison with the corresponding π-conjugate hydrocarbon molecules and odd-number substitution by first principle calculation. The band gaps are about the half that of the HOMO-LUMO gaps of corresponding hydrocarbons, except for the cis-butadiene structure in which aromatic hexagonal ring formation is important. Odd number doping makes metallic materials with very different work functions, depending upon the difference in B and N numbers, and has an expected application as electrodes for flexible devices.
THE PRECESSION OF SS433's RADIO RUFF ON LONG TIMESCALES

Roughly perpendicular to SS433's famous precessing jets is an outflowing “ruff” of radio-emitting plasma, revealed by direct imaging on milliarcsecond scales. Over the last decade, images of the ruff have revealed that its orientation changes over time with respect to a fixed sky coordinate grid. For example, during two months of daily observations with the VLBA by Mioduszewski et al., a steady rotation through ∼10° is observed while the jet angle changes by ∼20°. The ruff reorientation is not coupled with the well known precession of SS433's radio jets, as the ruff orientation varies across a range of 69° while the jet angle varies across 40°, and on greatly differing and noncommensurate timescales. It has been proposed that the ruff is fed by SS433's circumbinary disk, discovered by a sequence of optical spectroscopy by Blundell et al., and so we present the results of three-dimensional numerical simulations of circumbinary orbits. These simulations show precession in the longitude of the ascending node of all inclined circumbinary orbits—an effect which would manifest itself as the observed ruff reorientation. Matching the rate of ruff precession is possible if circumbinary components are sufficiently close to the binary system, but only if the binary mass fraction is close to equality and the binary eccentricity is nonzero.