Miracle-dz/UniFAR-FTUs huggingface dataset:
Association Between Elevated Liver Enzymes and C-Reactive Protein: Possible Hepatic Contribution to Systemic Inflammation in the Metabolic Syndrome

Objective— The objective of this study was to test whether the frequent association between liver enzyme elevations and various components of the metabolic syndrome is associated with higher C-reactive protein (CRP) levels. Methods and Results— Alanine aminotransferase (ALT), alkaline phosphatase (Alk-P), and high-sensitivity CRP were measured in 1740 subjects. Adjusted geometric mean CRP was calculated for subjects with normal and elevated ALT and for subjects with normal and elevated Alk-P, adjusting for age, sex, smoking, physical activity, body mass index, fasting glucose, triglycerides, the presence of hypertension and low HDL cholesterol, and use of aspirin or hormone replacement therapy. Adjusted CRP levels were higher in subjects with elevated ALT (2.21 versus 1.94 mg/L, P=0.028) or elevated Alk-P (2.58 versus 1.66 mg/L, P<0.0001). Logistic regression showed that compared with subjects with normal liver function tests, the adjusted odds for high-risk CRP (>3 mg/L) were significantly higher in subjects with elevated ALT (OR, 1.5; 95% CI, 1.2 to 1.9, P=0.002) or elevated Alk-P (OR, 2.1; 95% CI, 1.7 to 2.6, P<0.0001). Conclusions— Elevations of liver enzymes are associated with higher CRP concentrations. Hepatic inflammation secondary to liver steatosis is a potential contributor to the low-grade inflammation associated with the metabolic syndrome.
A Two-Phase Structure for Keratin Fibers

A two-phase structure is proposed for keratin fibers consisting of a water-absorbing matrix M, in which non-water-absorbing cylinders of phase C are embedded. The cylinders of phase C are parallel to the fiber direction. The main assumption made is that only the mechanical moduli of phase M are affected by moisture uptake as long as the fiber is not stretched. On this basis, using the longitudinal and radial swelling data available, quantitative relationships between the dry and wet Young's Moduli and rigidity moduli were obtained which agreed with experimental results. Further, other physical observations were shown to be compatible with this model.
A Study of Financial Contagion in Interbank System

Financial contagion was often observed during the recent financial crisis, which indicates a critical need for a new and fundamental understanding of its dynamics. Drawing analogies with the extinction analysis -- a technique widely used in the study of ecosystems - we focus on modeling and analyzing the financial contagion in a system where a large number of financial institutions are randomly connected by direct balance sheet linkages owing to their lending or borrowing relationships. We propose a simple contagion algorithm to study the effect of several determinants, such as the topology of a financial network, exposure ratio, leverage ratio, and liquidation ratio. We find that the financial contagion weakens with the growth of a network's connectivity to some extent. Therefore, a financial system with higher connectivity is more stable or robust. We also find that the exposure ratio increases the risk of financial contagion, but both the leverage ratio and liquidation ratio have negative relationships with financial contagion.
Inexact primal-dual path-following algorithms for a special class of convex quadratic SDP and related problems

We propose a primal-dual path-following Mehrotra-type predictor-corrector method for solving convex quadratic semidenite programming (QSDP) problems. For the special case when the quadratic term has the form 1 X (UXU), we compute the search direction at each iteration from the Schur complement equation. We are able to solve the Schur complement equation ecien tly via the preconditioned symmetric quasiminimal residual iterative solver with two appropriately constructed preconditioners. Numerical experiments on a variety of QSDPs with matrices of dimensions up to 2000 are performed and the computational results show that our methods are ecien t and robust. Our methods can also be extended to linear SDP problems with upper bound constraints on primal matrix variables.
Unification of Software Reliability Models Using Markovian Arrival Processes

This paper proposes an unified modeling framework of Markov-type software reliability models (SRMs) using Markovian arrival processes (MAPs). The MAP is defined as a point process whose inter-arrival time follows a phase-type distribution incorporating the correlation between successive two arrivals. This paper presents MAP representation of Markov-type SRMs, called MAP-based SRMs. This framework enables us to use generalized formulas for several reliability measures such as the expected number of failures and the software reliability which can be applied to all the Markov-type SRMs. In addition, we discuss the parameter estimation for the MAP-based SRMs from grouped failure data and find maximum likelihood estimates of all the Markov-type SRMs. The resulting MAP-based SRM is a novel approach to unifying the model-based software reliability evaluation using failure data.
Design of depth of anesthesia controllers in the presence of model uncertainty

A major obstacle in the design of controllers to regulate the depth of anesthesia (DoA) consists in the high model uncertainty due to inter-patient variability. Surprisingly, the use of control design methods that explicitly tackle this problem is almost absent from the literature on automatic control of anesthesia. In this work, a DoA controller is designed taking into account model uncertainty to comply with robust stability and robust performance specifications for a patient population undergoing elective general surgery, with hypnosis induced by the drug propofol. Due to its Wiener nonlinear structure, the DoA model can be linearized around a given operating point. Therefore, using a database with 18 patient models, a non-parametric description of uncertainty for a linearized model is first performed. By using H∞ design methods, a continuous linear controller is then designed so as to ensure robust stability and performance within the uncertainty bounds defined. The controller that results from this procedure is approximated by a controller with a lower order that, in turn, is redesigned in discrete time for computer control application. The final result is tested in nonlinear realistic patient models, with acceptable closed-loop results.
The SR-tree: an index structure for high-dimensional nearest neighbor queries

Recently, similarity queries on feature vectors have been widely used to perform content-based retrieval of images. To apply this technique to large databases, it is required to develop multidimensional index structures supporting nearest neighbor queries efficiently. The SS-tree had been proposed for this purpose and is known to outperform other index structures such as the R*-tree and the K-D-B-tree. One of its most important features is that it employs bounding spheres rather than bounding rectangles for the shape of regions. However, we demonstrate in this paper that bounding spheres occupy much larger volume than bounding rectangles with high-dimensional data and that this reduces search efficiency. To overcome this drawback, we propose a new index structure called the SR-tree (Sphere/Rectangle-tree) which integrates bounding spheres and bounding rectangles. A region of the SR-tree is specified by the intersection of a bounding sphere and a bounding rectangle. Incorporating bounding rectangles permits neighborhoods to be partitioned into smaller regions than the SS-tree and improves the disjointness among regions. This enhances the performance on nearest neighbor queries especially for high-dimensional and non-uniform data which can be practical in actual image/video similarity indexing. We include the performance test results the verify this advantage of the SR-tree and show that the SR-tree outperforms both the SS-tree and the R*-tree.
Bayesian compressive sensing for ultra-wideband channel models

Considering the sparse structure of ultra-wideband (UWB) channels, compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS, the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered. In this paper, we study the channel estimation performance of Bayesian CS (BCS) for various UWB channel models and noise conditions. Specifically, we investigate the effects of (i) sparse structure of standardized IEEE 802.15. 4a channel models, (ii) signal-to-noise ratio (SNR) regions, and (iii) number of measurements on the BCS channel estimation performance, and compare them to the results of l1-norm minimization based estimation, which is widely used for sparse channel estimation. The study shows that BCS exhibits superior performance at higher SNR regions only for adequate number of measurements and sparser channel models (e.g., CM1 and CM2). Based on the results of this study, BCS method or the l1-norm minimization method can be preferred over the other for different system implementation conditions.
Learning Performance of a Machine Translation System: a Statistical and Computational Analysis

We present an extensive experimental study of a Statistical Machine Translation system, Moses (Koehn et al., 2007), from the point of view of its learning capabilities. Very accurate learning curves are obtained, by using high-performance computing, and extrapolations are provided of the projected performance of the system under different conditions. We provide a discussion of learning curves, and we suggest that: 1) the representation power of the system is not currently a limitation to its performance, 2) the inference of its models from finite sets of i.i. d. data is responsible for current performance limitations, 3) it is unlikely that increasing dataset sizes will result in significant improvements (at least in traditional i.i.d. setting), 4) it is unlikely that novel statistical estimation methods will result in significant improvements. The current performance wall is mostly a consequence of Zipf's law, and this should be taken into account when designing a statistical machine translation system. A few possible research directions are discussed as a result of this investigation, most notably the integration of linguistic rules into the model inference phase, and the development of active learning procedures.
Equal or non-equal temperament in a capella SATB singing

Musical instruments whose pitch control is not fixed to specific notes, such as non-fretted stringed instruments and the human voice, have the freedom to vary the intonation of each note individually. A previous experiment to test whether an soprano, alto, tenor bass (SATB) a capella quartet made use of an equal or a non-equal tempered tuning system, indicated that the latter was the preference, and that singers tended to a form of just intonation for their tuning. That experiment made use of specially written SATB exercises consisting of a number of modulations between the starting and finishing chords, which themselves were either identical or exactly an octave apart. The intonation difference between the chords in the exercises was measured relative to just intonation and equal tempered tuning. Fundamental frequency data were gathered from each member of the quartet by means of four electrolaryngographs. This paper reports on the results of a second experiment with a different quartet which aims to establish the extent to which the effect might be replicated. The implications for conductors of a capella choirs are discussed.
Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments

The method of instrumental variables was first used in the 1920s to estimate supply and demand elasticities, and later used to correct for measurement error in single-equation models. Recently, instrumental variables have been widely used to reduce bias from omitted variables in estimates of causal relationships such as the effect of schooling on earnings. Intuitively, instrumental variables methods use only a portion of the variability in key variables to estimate the relationships of interest; if the instruments are valid, that portion is unrelated to the omitted variables. We discuss the mechanics of instrumental variables, and the qualities that make for a good instrument, devoting particular attention to instruments that are derived from 'natural experiments. ' A key feature of the natural experiments approach is the transparency and refutability of identifying assumptions. We also discuss the use of instrumental variables in randomized experiments.
Multiple Description Image Coding Based on Lagrangian Rate Allocation

In this paper, a novel multiple description coding technique is proposed, based on optimal Lagrangian rate allocation. The method assumes the coded data consists of independently coded blocks. Initially, all the blocks are coded at two different rates. Then blocks are split into two subsets with similar rate distortion characteristics; two balanced descriptions are generated by combining code blocks belonging to the two subsets encoded at opposite rates. A theoretical analysis of the approach is carried out, and the optimal rate distortion conditions are worked out. The method is successfully applied to the JPEG 2000 standard and simulation results show a noticeable performance improvement with respect to state-of-the art algorithms. The proposed technique enables easy tuning of the required coding redundancy. Moreover, the generated streams are fully compatible with Part 1 of the standard
The Role of the Funny Current in Pacemaker Activity

Pacemaking is a basic physiological process, and the cellular mechanisms involved in this function have always attracted the keen attention of investigators. The “funny” (If) current, originally described in sinoatrial node myocytes as an inward current activated on hyperpolarization to the diastolic range of voltages, has properties suitable for generating repetitive activity and for modulating spontaneous rate. The degree of activation of the funny current determines, at the end of an action potential, the steepness of phase 4 depolarization; hence, the frequency of action potential firing. Because If is controlled by intracellular cAMP and is thus activated and inhibited by &bgr;-adrenergic and muscarinic M2 receptor stimulation, respectively, it represents a basic physiological mechanism mediating autonomic regulation of heart rate. Given the complexity of the cellular processes involved in rhythmic activity, an exact quantification of the extent to which If and other mechanisms contribute to pacemaking is still a debated issue; nonetheless, a wealth of information collected since the current was first described more than 30 years ago clearly agrees to identify If as a major player in both generation of spontaneous activity and rate control. If- dependent pacemaking has recently advanced from a basic, physiologically relevant concept, as originally described, to a practical concept that has several potentially useful clinical applications and can be valuable in therapeutically relevant conditions. Typically, given their exclusive role in pacemaking, f-channels are ideal targets of drugs aiming to pharmacological control of cardiac rate. Molecules able to bind specifically to and block f-channels can thus be used as pharmacological tools for heart rate reduction with little or no adverse cardiovascular side effects. Indeed a selective f-channel inhibitor, ivabradine, is today commercially available as a tool in the treatment of stable chronic angina. Also, several loss-of-function mutations of HCN4 (hyperpolarization-activated, cyclic-nucleotide gated 4), the major constitutive subunit of f-channels in pacemaker cells, are known today to cause rhythm disturbances, such as for example inherited sinus bradycardia. Finally, gene- or cell-based methods for in situ delivery of f-channels to silent or defective cardiac muscle represent novel approaches for the development of biological pacemakers eventually able to replace electronic devices.
Optimization and Interpretation of Serial QuantiFERON Testing to Measure Acquisition of Mycobacterium tuberculosis Infection

Rationale: Conversion from a negative to positive QuantiFERON‐TB test is indicative of Mycobacterium tuberculosis (Mtb) infection, which predisposes individuals to tuberculosis disease. Interpretation of serial tests is confounded by immunological and technical variability. Objectives: To improve the consistency of serial QuantiFERON‐TB testing algorithms and provide a data‐driven definition of conversion. Methods: Sources of QuantiFERON‐TB variability were assessed, and optimal procedures were identified. Distributions of IFN‐&ggr; response levels were analyzed in healthy adolescents, Mtb‐unexposed control subjects, and patients with pulmonary tuberculosis. Measurements and Main Results: Individuals with no known Mtb exposure had IFN‐&ggr; values less than 0.2 IU/ml. Among individuals with IFN‐&ggr; values less than 0.2 IU/ml, 0.2‐0.34 IU/ml, 0.35‐0.7 IU/ml, and greater than 0.7 IU/ml, tuberculin skin test positivity results were 15%, 53%, 66%, and 91% (P < 0.005), respectively. Together, these findings suggest that values less than 0.2 IU/ml were true negatives. In short‐term serial testing, “uncertain” conversions, with at least one value within the uncertainty zone (0.2‐0.7 IU/ml), were partly explained by technical assay variability. Individuals who had a change in QuantiFERON‐TB IFN‐&ggr; values from less than 0.2 to greater than 0.7 IU/ml had 10‐fold higher tuberculosis incidence rates than those who maintained values less than 0.2 IU/ml over 2 years (P = 0.0003). By contrast, “uncertain” converters were not at higher risk than nonconverters (P = 0.229). Eighty‐seven percent of patients with active tuberculosis had IFN‐&ggr; values greater than 0.7 IU/ml, suggesting that these values are consistent with established Mtb infection. Conclusions: Implementation of optimized procedures and a more rigorous QuantiFERON‐TB conversion definition (an increase from IFN‐&ggr; <0.2 to >0.7 IU/ml) would allow more definitive detection of recent Mtb infection and potentially improve identification of those more likely to develop disease.
Unmanned Ground Vehicle ( UGV ) Interoperability Payload Testing

This paper deals with model validation of dynamic systems (with vehicle systems being of particular interest) that have multiple time-dependent output. First, we review several validation methodologies that have been reported in the literature: graphical comparison, feature-based techniques, PDF/CDF based techniques, Bayesian posterior estimation, classical hypothesis testing and Bayesian hypothesis testing. We discuss their advantages and disadvantages in terms of several attributes: applicability to different types of models, need for assumptions, computational cost, subjectivity, propensity to type-I or II errors, and others. We then proceed with the most important attribute: can the validation method provide a quantitative measure of the goodness of the model? We conclude that Bayesian-based model validation frameworks answer this question positively. A bootstrap method is presented that obviates the need to assume a statistical distribution model. The features of the Bayesian validation framework are illustrated using a thermal benchmark problem developed by Sandia National Laboratories and a battery model developed in the Automotive Research Center, a US Army Center of Excellence for modeling and simulation of ground vehicle systems.
CFD: Computational Fluid Dynamics or Confounding Factor Dissemination? The Role of Hemodynamics in Intracranial Aneurysm Rupture Risk Assessment

SUMMARY: Image-based computational fluid dynamics holds a prominent position in the evaluation of intracranial aneurysms, especially as a promising tool to stratify rupture risk. Current computational fluid dynamics findings correlating both high and low wall shear stress with intracranial aneurysm growth and rupture puzzle researchers and clinicians alike. These conflicting findings may stem from inconsistent parameter definitions, small datasets, and intrinsic complexities in intracranial aneurysm growth and rupture. In Part 1 of this 2-part review, we proposed a unifying hypothesis: both high and low wall shear stress drive intracranial aneurysm growth and rupture through mural cell–mediated and inflammatory cell–mediated destructive remodeling pathways, respectively. In the present report, Part 2, we delineate different wall shear stress parameter definitions and survey recent computational fluid dynamics studies, in light of this mechanistic heterogeneity. In the future, we expect that larger datasets, better analyses, and increased understanding of hemodynamic-biologic mechanisms will lead to more accurate predictive models for intracranial aneurysm risk assessment from computational fluid dynamics.
Genome-wide patterns of latitudinal differentiation among populations of Drosophila melanogaster from North America

Understanding the genetic underpinnings of adaptive change is a fundamental but largely unresolved problem in evolutionary biology. Drosophila melanogaster, an ancestrally tropical insect that has spread to temperate regions and become cosmopolitan, offers a powerful opportunity for identifying the molecular polymorphisms underlying clinal adaptation. Here, we use genome‐wide next‐generation sequencing of DNA pools (‘pool‐seq’) from three populations collected along the North American east coast to examine patterns of latitudinal differentiation. Comparing the genomes of these populations is particularly interesting since they exhibit clinal variation in a number of important life history traits. We find extensive latitudinal differentiation, with many of the most strongly differentiated genes involved in major functional pathways such as the insulin/TOR, ecdysone, torso, EGFR, TGFβ/BMP, JAK/STAT, immunity and circadian rhythm pathways. We observe particularly strong differentiation on chromosome 3R, especially within the cosmopolitan inversion In(3R)Payne, which contains a large number of clinally varying genes. While much of the differentiation might be driven by clinal differences in the frequency of In(3R)P, we also identify genes that are likely independent of this inversion. Our results provide genome‐wide evidence consistent with pervasive spatially variable selection acting on numerous loci and pathways along the well‐known North American cline, with many candidates implicated in life history regulation and exhibiting parallel differentiation along the previously investigated Australian cline.
Positive schizotypy is not associated with speech abnormality

Aim: This study examined whether speech abnormalities typical of formal thought disorder in schizophrenia vary with the degree of positive schizotypy in the healthy population. We hypothesized that participants with high levels of positive schizotypy would show greater abnormality in speech relative to those with low levels of positive schizotypy.