Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Analysis for Integrating Two Related Studies of Different Data Types and Different Study Designs Using Hierarchical Modeling Approaches

Background: A chronic disease such as asthma is the result of a complex sequence of biological interactions involving multiple genes and pathways in response to a multitude of environmental exposures. However, methods to model jointly all factors are still evolving. Some of the current challenges include how to integrate knowledge from different data types and different disciplines, as well as how to utilize relevant external information such as gene annotation to identify novel disease genes and gene-environment inter-actions. Methods: Using a Bayesian hierarchical modeling framework, we developed two alternative methods for joint analysis of an epidemiologic study of a disease endpoint and an experimental study of intermediate phenotypes, while incorporating external information. Results: Our simulation studies demonstrated superior performance of the proposed hierarchical models compared to separate analysis with the standard single-level regression modeling approach. The combined analyses of the Southern California Children's Health Study and challenge study data suggest that these joint analytical methods detected more significant genetic main and gene-environment interaction effects than the conventional analysis. Conclusion: The proposed prior framework is very flexible and can be generalized for an integrative analysis of diverse sources of relevant biological data.
Exchange Rate Regimes and Financial Dollarization: Does Flexibility Reduce Bank Currency Mismatches?

The dollarization of bank deposits and credit is widespread in developing countries,resulting in varying degrees of currency mismatches in domestic financial intermediation, which in turn may accentuate balance sheet problems and thus financial fragility. It is widely argued that flexible exchange rate regimes encourage banks to match dollar-denominated liabilities with a corresponding amount of dollar-denominated assets, ameliorating currency mismatches. Does the behavior of dollar deposits and credit in financially dollarized economies support that presumption? A new database on deposit and credit dollarization in developing and transition countries is assembled and used to address this question. Empirical results suggest that, if anything, floating regimes seem to exacerbate, rather than ameliorate, currency mismatches in domestic financial intermediation, as those regimes seem to encourage deposit dollarization more strongly than they encourage matching via credit dollarization.
Apple Market Integration: Implications for Sustainable Agricultural Development

In a market driven economy, price signals guide and regulate production, consumption and marketing decisions over time, form and place. Identifying the causes of price differences in interregional or spatial markets has therefore become an important economic analytical tool to understand markets better. If markets are not well integrated, price signals are distorted, which leads to an inefficient allocation of resources. Further, it may constrain sustainable agricultural development and aggravate inequitable patterns of income distribution. This paper examines the degree of spatial market integration in the regionalapple markets of Pakistan using cointegration analysis and monthly wholesale price data from January, 1996 to December, 2005. Results show that apple markets are perfectly integrated and Quetta is the dominating market. The high degree of market integration observed in this case is consistent with view that apple markets in Pakistan are quite competitive and provide little justification for government intervention designed to improve competitiveness to enhance market efficiency.
Inferring Diversity and Evolution in Fish by Means of Integrative Molecular Cytogenetics

Fish constitute a paraphyletic and profusely diversified group that has historically puzzled ichthyologists. Hard efforts are necessary to better understand this group, due to its extensive diversity. New species are often identified and it leads to questions about their phylogenetic aspects. Cytogenetics is becoming an important biodiversity-detection tool also used to measure biodiversity evolutionary aspects. Molecular cytogenetics by fluorescence in situ hybridization (FISH) allowed integrating quantitative and qualitative data from DNA sequences and their physical location in chromosomes and genomes. Although there is no intention on presenting a broader review, the current study presents some evidences on the need of integrating molecular cytogenetic data to other evolutionary biology tools to more precisely infer cryptic species detection, population structuring in marine environments, intra- and interspecific karyoevolutionary aspects of freshwater groups, evolutionary dynamics of marine fish chromosomes, and the origin and differentiation of sexual and B chromosomes. The new cytogenetic field, called cytogenomics, is spreading due to its capacity to give resolute answers to countless questions that cannot be answered by traditional methodologies. Indeed, the association between chromosomal markers and DNA sequencing as well as between biological diversity analysis methodologies and phylogenetics triggers the will to search for answers about fish evolutionary, taxonomic, and structural features.
A Method of Analyzing the Strain of Arterial Wall

Analyzing the strain of arterial wall pressed by the pressure is the foundation to judge the arterial elasticity, which is an important reference to estimate Heart-blood Vessel System Function. In this study, a method is proposed to analyze the arterial wall strain using intravascular ultrasound (IVUS) images, the method is based on finite deformation power theory, with which a modal is established and arterial wall is divided by determinate number conjoint triangles and the strain of arterial wall is calculated by the foundation of these triangle elements. The merit of this method is that it predigests the research objects and makes full use of the character of the triangle deformation. At the same time, the main strain and main direction of each element testifies the modal.
A Transformation of the Navier-Stokes Equations for Efficient Fluid Animation Jinho Park

Computational efficiency is an important theme in fluid simulation since its heavy computational load is burden to designers. Our objective is to proposed a grid based method satisfying divergence free property without the projection method. The paper transforms the momentum conservation part of the Navier-Stokes equations to vector potential based equations. Our method do not need any global operations for mass conservation. The transformed equation is solved numerically in similar manner to fractional step method.
UNDERDETERMINED BLIND SOURCE SEPARATION USING A PROBABILISTIC SOURCE SPARSITY MODEL

Blind source separation consists of recovering n source signals from m measurements that are an unknown function of the sources. In solving the underdetermined (m < n) linear problem three stages can be identified: to represent the signals in an appropriate domain, to estimate the mixing matrix, and to invert the linear problem to estimate the sources. As a consequence of having more degrees of freedom than constraints, the inverse problem has an infinite number of solutions. To choose the “best” solution, additional constraints have to be imposed on the basis of some performance criterion or previous knowledge. In this communication we present a method that choose the “best” demixing matrix in a sample by sample basis by using some previous knowledge of the statistics of the sources. The behaviour of the estimator is compared to the global pseudo inverse approach and with other local heuristic methods by means of Montecarlo simulations.
A Robust Remote User Authentication Scheme Using Smart Card

In 2008, Yoon et al. [25] presented three kinds of security attacks (YLY attacks for short) of a user authentication and key agreement scheme using smart cards in different scenarios. The YLY attacks are: perfect forward secrecy, the guessing attack, and the Denning-Sacco attack. The main goal of this paper is to propose a robust remote user authentication scheme using smart card that could not only withstand the traditional attacks, such as, the man-in-the-middle attack, the replay attack, the forgery attacks, the stolen smart card attack, and the denial of service attack, but also overcomes YLY attacks.
Analysis of fatigue conditions in biceps brachii muscles using surface electromyography signals and strip spectral correlation

In this work, an attempt has been made to analyze the cyclostationarity of surface electromyography (sEMG) signals recorded during dynamic contraction of biceps brachii muscle. Twenty five healthy adult volunteers have participated in this study. The recorded signals are preprocessed and segmented into three zones, namely, non-fatigue zone, first muscle discomfort zone and fatigue zone. These signals are subjected to strip spectral correlation algorithm to estimate the spectral correlation density (SCD). Cyclic domain profile (CDP) is extracted from the normalized SCD magnitude. The area of CDP is calculated for all the three zones. The results show that strip spectral correlation algorithm based SCD estimation is able to demonstrate the cyclostationary property of sEMG signal in all three zones. It is also observed that the normalized SCD magnitude spectrum is distinct for all cases. The CDP area shows the significant variation in fatigue zone. Further it appears that cyclostationarity based on SCD can be used to differentiate different neuromuscular and pathological conditions.
Working Paper No. 440 Time-varying volatility, precautionary saving and monetary policy

This paper analyses the conduct of monetary policy in an environment where households’ desire to amass precautionary savings is influenced by fluctuations in the volatilities of disturbances that hit the economy. It uses a simple New Keynesian model with external habit formation that is augmented with demand and supply disturbances whose volatilities vary over time. If volatility fluctuations are ignored by policy, interest rates are set at a suboptimal level. The extent of ‘policy bias’ is relatively small but of greater importance the higher the degree of habit formation. The reason is that habit-forming preferences raise risk aversion, increasing the importance of the precautionary savings channel through which volatility fluctuations impact upon inflation and output.
Common Randomness in Information Theory and Cryptography - Part II: CR Capacity

For pt.I see ibid., vol.39, p.1121, 1993. The common randomness (CR) capacity of a two-terminal model is defined as the maximum rate of common randomness that the terminals can generate using resources specified by the given model. We determine CR capacity for several models, including those whose statistics depend on unknown parameters. The CR capacity is shown to be achievable robustly, by common randomness of nearly uniform distribution no matter what the unknown parameters are. Our CR capacity results are relevant for the problem of identification capacity, and also yield a new result on the regular (transmission) capacity of arbitrarily varying channels with feedback.
Skew Estimation and Segmentation of Text Line in Video Frames

A method is proposed to segment text from complex background for recognition task. First we estimate the skew of text line and rotate it to the horizontal one. Second, a sampling method based on color edge is proposed to get portion of the text pixels and non-text pixels. Then, k-means algorithm is used to partition the sampled pixels into k clusters. Third, we take the centroid and standard deviation of clusters to segment text image into k binary images. Finally, stroke-filtering is used to select correct one from k binary images. Experiments result shows that the proposed method performs much better than the previous methods.
The Estimation Algorithm of Laplacian Eigenvalues for the Tangent Bundle

In Recent years, manifold learning has become an important research direction in the field of machine learning and pattern recognition. As an effective way of representation embedded in low-dimensional space of high-dimensional data, the manifold learning algorithm, which is based on the spectral theory, has been widely used. This paper presents an estimation algorithm of Laplacian Eigenvalues and expands the LE algorithm's advantage of maintaining the local geometry to remaining globally through the global coordinates of the tangent bundle. The estimation algorithm of Laplacian Eigenvalues for the tangent bundle is effectively applied to nonlinear manifold dimensionality reduction and maintains the geometry of manifolds. Experimental results show that the algorithm proposed is very effective.
Research on the Application of XML in Web Services

Next generation of knowledge management systems will utilize different methods and techniques from the following communities to achieve the vision of ubiquitous knowledge: Semantic Web and Web Services, Agent Technologies, Mobility. A knowledge asset (Web resource or service) to become an intellectual capital must be shared; it increases in value while being used. XML is the ideal format for the exchange of statistical metadata between applications, because it is simple to transmit over standard protocols, and because it is well supported by manipulation APIs at the application level. This paper outlines the state of XML Web services today. It demonstrates the need for a set of additional capabilities as companies deploy XML Web services to support increasingly sophisticated business processes. Finally, it addresses how to begin to address the need for additional capabilities with a XML Web Services Architecture and its supporting specifications.
Active portfolio management: The power of the Treynor-Black model

The performance of active portfolio methods critically depends on the forecasting ability of the security analyst. The Treynor-Black model provides an efficient way of implementing active investment strategy. Despite its potential benefits, the Treynor-Black model appears to have had little impact on the financial community, mainly because it has been believed that the precision threshold of alpha forecasts used as inputs to the model is too high. We seek to lower the threshold of forecast precision needed to beat a passive-portfolio strategy by improving the econometric methods used in constructing portfolios from security analyst forecasts. We apply shrinkage estimation to beta coefficients and to discount functions for forecasts of stock abnormal returns. OLS estimates, Least Absolute Deviations (LAD) estimates and shrinkage LAD estimates are compared by contribution to portfolio performance. Despite correlations between forecasts and realizations of abnormal returns as low as 0.04, the shrinkage LAD methodology yields superior performance in outof-sample experiments.
Antiosteoporotic effects of Polycan in combination with calcium lactate-gluconate in ovariectomized rats

The aim of the present study was to investigate the optimum composition of Polycan (β-glucan complex) and calcium lactate-gluconate (CaLG) that exhibited the most beneficial effects in ovariectomy (OVX)-induced osteoporotic rats. Polycan and CaLG single formulas (100 mg/kg each), and three doses (50, 100 and 200 mg/kg) of three mixed formulas [polycan:CaLG (PCLG)=1:99, 5:95 and 10:90] were orally administered once a day for 84 days. The effects of the test materials were compared with those of a risedronate sodium-treated group. OVX resulted in an increase in body weight, decreased bone formation, elevated serum osteocalcin levels and urine deoxypyridinoline/creatinine ratio, as well as decreased serum bone-specific alkaline phosphatase levels, femur indices, bone mineral content, bone mineral density and failure load. However, these OVX-induced osteoporotic changes markedly decreased following the administration of the test materials. Continuous oral treatment of Polycan or CaLG single formulas and the PCLG mixed formulas preserved bone mass and strength. The PCLG 10:90 mixed formula exhibited the most favorable synergistic antiosteoporotic effects in the OVX-induced osteoporotic rats as compared with equal doses of the Polycan or CaLG single formulas.
Adaptive Tracking for Periodically Time-Varying and Nonlinearly Parameterized Systems Using Multilayer Neural Networks

This brief addresses the problem of designing adaptive neural network tracking control for a class of strict-feedback systems with unknown time-varying disturbances of known periods which nonlinearly appear in unknown functions. Multilayer neural network (MNN) and Fourier series expansion (FSE) are combined into a novel approximator to model each uncertainty in systems. Dynamic surface control (DSC) approach and integral-type Lyapunov function (ILF) technique are combined to design the control algorithm. The ultimate uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. Two simulation examples are provided to illustrate the feasibility of control scheme proposed in this brief.
Growing Together and Growing Apart-Supplementary Materials

To support the findings reported in the manuscript Growing together and growing apart: Regional and sex differences in the lifespan developmental trajectories of functional homotopy, we conducted several supplementary analyses. These include (1) regression model selection using Akaike's Information Criterion (AIC); (2) examination of VMHC test-retest reliability; (3) comparability of findings across samples and (4) examination of the impact of potential confounding factors (e.g., brain morphometry and registration) on developmental changes in VMHC. We also provide additional discussion of our findings of regional variation in development trajectories.
Genomic data as the “hitchhiker's guide” to cattle adaptation: tracking the milestones of past selection in the bovine genome

The bovine species have witnessed and played a major role in the drastic socio-economical changes that shaped our culture over the last 10,000 years. During this journey, cattle "hitchhiked" on human development and colonized the world, facing strong selective pressures such as dramatic environmental changes and disease challenge. Consequently, hundreds of specialized cattle breeds emerged and spread around the globe, making up a rich spectrum of genomic resources. Their DNA still carry the scars left from adapting to this wide range of conditions, and we are now empowered with data and analytical tools to track the milestones of past selection in their genomes. In this review paper, we provide a summary of the reconstructed demographic events that shaped cattle diversity, offer a critical synthesis of popular methodologies applied to the search for signatures of selection (SS) in genomic data, and give examples of recent SS studies in cattle. Then, we outline the potential and challenges of the application of SS analysis in cattle, and discuss the future directions in this field.
Nonparametric Pricing of Multivariate Contingent Claims

In this paper, I derive and implement a nonparametric, arbitrage-free technique for multivariate contingent claim (MVCC) pricing. Using results from the method of copulas, I show that the multivariate risk-neutral density can be written as a product of marginal risk-neutral densities and a risk-neutral dependence function. I then develop a pricing technique using nonparametrically estimated marginal risk-neutral densities (based on options data) and a nonparametric dependence function (based on historical return data). By using nonparametric estimation, I avoid the pricing biases that result from incorrect parametric assumptions such as lognormality. ; I apply this technique to estimate the joint risk-neutral density of euro-dollar and yen-dollar returns. I compare the nonparametric risk-neutral density with density based on a lognormal dependence function and nonparametric marginals. The nonparametric euro-yen risk-neutral density has greater volatility, skewness, and kurtosis than the density based on a lognormal dependence function. In a comparison of pricing accuracy for euro-yen futures options, I find that the nonparametric model is superior to the lognormal model.
Characterizing sleep in children with autism spectrum disorders: a multidimensional approach.

STUDY OBJECTIVES To relate parentally reported sleep concerns in autism spectrum disorders (ASD) to polysomnographic (PSG) findings and measures of daytime behavior and autism symptomatology. DESIGN Cross-sectional study involving validated questionnaires, sleep histories and diaries, 2 nights of PSG, and the Autism Diagnostic Observation Schedule (ADOS). SETTING Vanderbilt University General Clinical Research Center Sleep Core. PARTICIPANTS 21 children with ASD and 10 typically developing (TD) children, aged 4-10 years. Children were free of psychotropic medications, with no history of mental retardation or epileptic seizures. INTERVENTIONS N/A. MEASUREMENTS AND RESULTS Children with ASD were defined as "good sleepers" (10 children) and "poor sleepers" (11 children) on the basis of parental report; the age-comparable TD children were all reported by their parents to be good sleepers. Poor sleepers with ASD showed prolonged sleep latency and decreased sleep efficiency on night 1 of PSG and differed on insomnia-related subscales of the Children's Sleep Habits Questionnaire (CSHQ; increased sleep onset delay and decreased sleep duration). The good sleepers with ASD did not differ from the TD children in sleep architecture or on CSHQ domains. As compared with ASD good sleepers, the ASD poor sleepers also had higher scores related to affective problems on the Child Behavior Checklist and more problems with reciprocal social interaction on the ADOS. CONCLUSIONS Parentally reported sleep concerns of insomnia in children with ASD are substantiated by validated sleep questionnaires and by PSG. Furthermore, good sleepers with ASD showed fewer affective problems and better social interactions than ASD poor sleepers.
Network redesign through clusters consolidation

Nowadays many network administrators and customers are anticipating the network infrastructure to be adaptable to changes so that networks can provide better services. The existing network should be viewed as a fluid infrastructure, which has unproblematic setup to carry out redesigns. Here we have proposed a number of redesign techniques on the customers' clusters (sub-networks), since many customers maybe initially located in a cluster with less intra-cluster communications. Such customers increase the traffic on the backbone network. Thus we have proposed an optimization re-clustering problem to reduce the extra-traffic and maximize the intra-traffic within the clusters by considering customers' movement and clusters consolidation. We have utilized Simulated Annealing (SA) algorithm to search for the best solution to the re-clustering problem. Our simulation results show a better trade-off in minimizing the extra-traffic through clusters consolidation.