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The response of a patient in a clinical trial usually depends on both the selected treatment and some latent covariates, while its variance varies across the treatment groups. A general heteroscedastic linear additive model incorporating the treatment effect and the covariate effects is often used in such studies. In this paper, under D- and DA-optimality criteria, it is shown that the product of an optimal treatment allocation and an optimal design for covariates is also optimal among all possible designs for this linear additive model. Moreover, the optimal treatment allocation is characterized by a unique set of solutions to a system of equations. The connection between D- and DA-optimal designs is also revealed. Several examples are presented to illustrate the applications of the above results to some selected models.
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Insulin receptors have been demonstrated to be involved in embryogenesis, food intake regulation and glucose metabolism in several fish, while more researchis needed for further understanding. In this study, the complete coding sequence (CDS) of insulin receptor a (insra) gene and insulin receptor b (insrb) gene in grass carp were obtained, the CDS were 4068 bp and 4514 bp in length, encoding 1355 aa protein and 1351 aa protein. Both of insra and insrb in grass carp showed high amino acid identities with other fish. Insra and insrb genes were widely expressed in all tested tissues with an overlapping but distinct expressions. The high levels of insra mRNA were distributed in hindgut and heart tissues. The insrb gene showed the highest expression levels in liver and hindgut. We also proved that two forms of grass carp insulin receptors participate in the regulation of blood glucose and might act differently. Phylogenetic analysis confirmed that different isoforms of fish insulin receptors are derived from two distinct genes, which was inconsistent with the generation of mammalian insulin receptors. Synteny analyses of insulin receptor genes showed that genes surrounding the insulin receptor genes were conserved in fish. Arhgef18, PEX11G, humanC19orf45 genes were highly conserved among mammal species. However, no conserved synteny was observed among fish, mammals, avians and amphibians.
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mRNA positioning in the cell is important for diverse cellular functions and proper development of multicellular organisms. Single-molecule RNA FISH (smFISH) enables quantitative investigation of mRNA localization and abundance at the level of individual molecules in the context of cellular features. Details about spatial mRNA patterning at various times, in different genetic backgrounds, at different developmental stages, and under varied environmental conditions provide invaluable insights into the mechanisms and functions of spatial regulation. Here, we describe detailed methods for performing smFISH along with immunofluorescence for two large, multinucleate cell types: the fungus Ashbya gossypii and cultured mouse myotubes. We also put forward a semi-automated image processing tool that systematically detects mRNAs from smFISH data and statistically analyzes the spatial pattern of mRNAs using a customized MATLAB code. These protocols and image analysis tools can be adapted to a wide variety of transcripts and cell types for systematically and quantitatively analyzing mRNA distribution in three-dimensional space.
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In this communication, a corresponding states-based model for the calculation/estimation of the gas compressibility factor (z-factor) of natural gasses is proposed. The method applies the gene expression programming (GEP) algorithm. The parameters of the new model comprise the pseudo-reduced pressure and pseudo-reduced temperature. For assessing the performance and accuracy of the developed model, several statistical and graphical error analyses have been applied simultaneously. Additionally, comparisons have been made between this method and the most widely-used correlations and equations of state (EoS) available in the literature. Various statistical parameters are also used to evaluate the validity and the predictive capability of the newly developed method. Furthermore, the Leverage approach (Williams plot) is used to determine the realm of prediction capability of the new z-factor model and to detect any probable erroneous data points. The results obtained demonstrate that the newly proposed model is more reliable and more effective than the empirical models and EoS methods for prediction of z-factors of natural gasses.
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In this paper a new digital background correction and calibration technique for redundant multi-bit pipeline stages is presented. In this method output voltage of each stage in converter is defined as sum of the ideal product and error signal, which error voltage include of linear non-ideal section or first order error and nonlinearity undesired signal or third order error. Linear error is formed by capacitor mismatch, op-amp offset, comparator offset and finite op-amp gain effects. Nonlinear error is deformed the output voltage depend on the nonlinear results of open loop residue amplifier. Correction begins with separately calculation and cancelation of the nonlinear and linear errors respectively. For calibration of each stage at first step, the nonlinear effects in digital output of backend ADC is eliminated and then by digital modeling of first order analog error the influence of this unfavorable signal is diminished from digital equivalent of input voltage. Therefore for cancelation of non-ideal impairment in each stage a digital filter consist of linear and nonlinear channel in digital domain is designed. The first order and third order coefficients of designed digital function are unknown and should by a pertinent method be estimated simultaneously. Adaptive filter are best choose for this method. Simulation results show that INL/DNL parameters of 14-bit radix-4 pipelined converter are improved from 17LSB/3LSB to 0.45LSB/0.41LSB after calibration. The SNDR/SFDR parameters are increased from 30dB/36dB to 83dB/90dB.
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From the perspective of recipients, the increasing influence of China and emerging donors in the aid landscape represents an opportunity to attract additional resources to finance development and improve their control over their development agenda. This paper investigates how African countries and other LMICs deal with this complex and changing aid landscape and explores how government fiscal behaviors and private agent anticipations regarding aid flows are affected.
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The distribution of firm-sizes in the U.S. – or at least its upper tail – appears to be well-described by a Pareto distribution with infinite variance. This fact forms the basis of the granular hypothesis proposed by Gabaix in his paper “The Granular Origins of Aggregate Fluctuations” (Econometrica, (2011)). The granular hypothesis provides a mechanism whereby independent firm-level shocks are capable of generating macroeconomic fluctuations. This paper considers the granular hypothesis in a new framework. It develops a DSGE model by superimposing a stochastic overlapping generations framework on a network. Idiosyncratic output shocks to individual firms are transmitted across the economy through income–expenditure channels. Specifically, firms represent vertices of the network, and a firm x is linked to another firm y if x employs one or more workers who purchase commodities produced by y. The paper’s findings agree closely with results first discovered by Gabaix: if firm-sizes in an economy are described by a Pareto distribution, then independent firm-level shocks can generate macroeconomic fluctuations in accordance with the granular hypothesis. Furthermore, the model is capable of generating aggregate volatility of the same order of magnitude as occurs in reality. Thus the paper describes a new general equilibrium framework where macroeconomic fluctuations can arise as the consequence of independent firm-level shocks.
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When using alpha-design for plant variety testing under space restrictions, ex post design modifications must be implemented to prevent variety self-proximity on plots and, consequently, to prevent damage-induced loss of experimental information. This is done ad hoc for each experiment; the unsystematic modification is, however, commonly not only unable to resolve all existing proximities, but may introduce secondary undesired proximities. In this paper, a procedure is developed for the universal construction of modified alpha-design that covers all existing proximity constraints while keeping the efficiency level of the original design. Using extensive real data simulation, we validate the procedure and confirm high damage robustness of the modified designs. The procedure has been implemented as a Matlab function and is available as on-line supplement to the paper. The function enables to design the damage-robust experiments automatically using only standard computer equipment.
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WRKY transcription factors play critical roles in plant growth and development, as well as the response to biotic and abiotic stresses. Despite the fact that WRKY gene family has been characterized in a number of plant species, very little is known in the common bean, Phaseolus vulgaris. The recently released genome sequences provide us a good opportunity for genome-wide analysis of WRKY genes in this legume crop. In this study, a total of 90 WRKY genes (PvWRKYs) were identified and classified into three groups, of which the second group was further separated into five subgroups based on the structure of the conserved domains. All the WRKY genes were located on chromosomes 1 to 11 with a non-uniformed distribution. The phylogenetic analysis revealed that the majority of the PvWRKY genes were clustered with those from soybean, indicating that most of the WRKY genes may be originated from the same ancestor with Glycine max; both tandem and segmental duplications have played an important role in the evolution and diversification of the WRKY gene family in P. vulgaris. The variety and complexity of protein structure indicate that WRKY genes may be of significance in plant growth regulation and stress responses. The analysis of expression profiles revealed that the majority of WRKY genes showed tissue-specific expression, which is indicative of diverged expression during the development of common bean.
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We examine some skew distributions used extensively within the model-based clustering literature in recent years, paying special attention to claims that have been made about their relative efficacy. Theoretical arguments are provided as well as real data examples.
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