Miracle-dz/UniFAR-FTUs huggingface dataset:
Using deep bidirectional recurrent neural networks for prosodic-target prediction in a unit-selection text-to-speech system

Deeply-stacked Bidirectional Recurrent Neural Networks (BiRNNs) are able to capture complex, short-and long-term, context dependencies between predictors and targets due to the non-linear dependency they introduce on the entire observation when predicting a target, thanks to the use of recurrent hidden layers that accumulate information from all preceding and future observations. This aspect of the model makes them desirable for tasks such as the prediction of prosodic contours for text-to-speech systems, where the surface prosody can be a result of the interaction between local and non-local features. Although previous work has demonstrated that they attain state-of-the-art performance for this task within a parametric synthesis framework, their use within unit-selection synthesis systems remains unexplored. In this work we deploy this class of models within a unit selection system, investigate their effect on the outcome of the unit search, and perceptually evaluate it against the baseline (decision-tree-based) approach.
Robust Geographic Routing with Virtual Destination Based Void Handling for MANETs

Traditional MANET routing protocols are quite susceptible to nodes' mobility, especially for large-scale networks in which the end-to-end path length is usually large. In order to improve the routing performance in the face of fast changing network topology, we propose a novel Robust Geographic Routing (RGR) protocol which takes advantage of the broadcast nature of wireless medium by employing opportunistic routing like forwarding strategy. At the same time, a Virtual Destination based Void Handling (VDVH) scheme is also proposed to work together with RGR. Simulation results show that RGR achieves excellent performance even under high node mobility and the new void handling scheme also works well and further enhances the performance of RGR.
Noise-Robust MUSIC-Based Sound Source Localization Using Steering Vector Transformation for Small Humanoids

We focus on the problem of localizing soft/weak voices recorded by small humanoid robots, such as NAO. Sound source localization (SSL) for such robots requires fast processing and noise robustness owing to the restricted resources and the internal noise close to the microphones. Multiple signal classification using generalized eigenvalue decomposition (GEVDMUSIC) is a promising method for SSL. It achieves noise robustness by whitening robot internal noise using prior noise information. However, whitening increases the computational cost and creates a directiondependent bias in the localization score, which degrades the localization accuracy. We have thus developed a new implementation of GEVD-MUSIC based on steering vector transformation (TSV-MUSIC). The application of a transformation equivalent to whitening to steering vectors in advance reduces the realtime computational cost of TSV-MUSIC. Moreover, normalization of the transformed vectors cancels the direction-dependent bias and improves the localization accuracy. Experiments using simulated data showed that TSV-MUSIC had the highest accuracy of the methods tested. An experiment using real recoded data showed that TSV-MUSIC outperformed GEVDMUSIC and other MUSIC methods in terms of localization by about 4 points under low signal-to-noiseratio conditions.
YAP repression of the WNT3 gene controls hESC differentiation along the cardiac mesoderm lineage

Here, Estaras et al. researched how the Hippo effector YAP represses hESC differentiation and demonstrate that YAP binds to the WNT3 gene enhancer and prevents the gene from being induced by Activin in proliferating hESCs. Their findings indicate that YAP maintains hESC pluripotency by preventing WNT3 expression in response to Activin, thereby blocking a direct route to embryonic cardiac mesoderm formation.
Type I IFN Modulates Innate and Specific Antiviral Immunity1

IFNs protect from virus infection by inducing an antiviral state and by modulating the immune response. Using mice deficient in multiple aspects of IFN signaling, we found that type I and type II IFN play distinct although complementing roles in the resolution of influenza viral disease. Both types of IFN influenced the profile of cytokines produced by T lymphocytes, with a significant bias toward Th2 differentiation occurring in the absence of responsiveness to either IFN. However, although a Th1 bias produced through inhibition of Th2 differentiation by IFN-γ was not required to resolve infection, loss of type I IFN responsiveness led to exacerbated disease pathology characterized by granulocytic pulmonary inflammatory infiltrates. Responsiveness to type I IFN did not influence the generation of virus-specific cytotoxic lymphocytes or the rate of viral clearance, but induction of IL-10 and IL-15 in infected lungs through a type I IFN-dependent pathway correlated with a protective response to virus. Combined loss of both IFN pathways led to a severely polarized proinflammatory immune response and exacerbated disease. These results reveal an unexpected role for type I IFN in coordinating the host response to viral infection and controlling inflammation in the absence of a direct effect on virus replication.
Glycosaminoglycan synthesis in the separate layers of the chick sclera during myopic eye growth: Comparison with mammals

Purpose. Studies in animal models of refractive development have shown that the development of and recovery from induced myopia is associated with visually-guided changes in scleral glycosaminoglycan synthesis. The present study sought to determine whether differential patterns of scleral glycosaminoglycan synthesis are present in the fibrous scleral layer of the chick during myopia development or recovery, as has previously been reported in the mammalian sclera. Methods. Myopia was induced in young chicks by monocular deprivation of pattern vision over 5 days. Other animals underwent monocular deprivation, then had the occluder removed and were allowed 2 days of recovery. A group of age-matched normal animals served as a control. Newly synthesised glycosaminoglycans in the scleral layers were labelled in vivo, using a [ 35 S]-labelled precursor delivered intraperitoneally on the final experimental day. Incorporation of this sulphate into glycosaminoglycans of the fibrous and cartilaginous scleral layers was assessed in proteinase K digests by selective precipitation with alcian blue. Results. Glycosaminoglycan synthesis in the fibrous scleral layers of myopic and recovering eyes was not significantly different to contralateral control eyes (+14 ± 7%, p = 0.09 and -2 ± 4%, p =0.64 respectively). In contrast, glycosaminoglycan synthesis was significantly elevated, relative to controls, in the cartilaginous scleral layer of eyes developing myopia (+63 ± 18%, p < 0.02), whereas in recovering eyes there was found to be a significant decrease in synthesis in the cartilaginous layer (-40 ± 6%, p < 0.001). Conclusions. The results of the current study demonstrate that the fibrous scleral layer of the chick does not display the characteristic differential patterns of glycosaminoglycan synthesis that are found in the mammalian sclera during myopia development and recovery. However, as has previously been reported, the cartilaginous layer of the chick sclera does display differential glycosaminoglycan expression, although the direction of regulation is opposite to that found in the fibrous sclera of mammals.
Integrating Hamiltonian systems defined on the Lie groups SO(4) and SO(1,3)

In this paper we study constrained optimal control problems on semi-simple Lie groups. These constrained optimal control problems include Riemannian, sub-Riemannian, elastic and mechanical problems. We begin by lifting these problems, through the Maximum Principle, to their associated Hamiltonian formalism. As the base manifold is a Lie group G the cotangent bundle is realized as the direct product G×g* where g* is the dual of the Lie algebra g of G. The solutions to these Hamiltonian vector fields l ∈ g*, are called extremal curves and the projections g(t) ∈ G are the corresponding optimal solutions. The main contribution of this paper is a method for deriving explicit expressions relating the extremal curves l ∈ g* to the optimal solutions g(t) ∈ G for the special cases of the Lie groups SO(4) and SO(1,3). This method uses the double cover property of these Lie groups to decouple them into lower dimensional systems. These lower dimensional systems are then solved in terms of the extremals using a coordinate representation and the systems dynamic constraints. This illustrates that the optimal solutions g(t) ∈ G are explicitly dependent on the extremal curves.
Evaluation of the Efficacy of Ginger, Arabic Gum, and Boswellia in Acute and Chronic Renal Failure

This study was conducted to evaluate the effects of Zingiber officinale Roscoe (Ginger), Arabic gum (AG), and Boswellia on both acute and chronic renal failure (CRF) and the mechanisms underlying their effects. Acute renal failure was induced by 30 min ischemia followed by 24 h reperfusion, while CRF was induced by adenine feeding for 8 weeks. Prophylactic oral administration of ginger, AG, Boswellia, or vehicle (in control groups) was started 3 days before and along with adenine feeding in different groups or 7 days before ischemia–reperfusion. Ginger and AG showed renoprotective effects in both models of renal failure. These protective effects may be attributed at least in part to their anti-inflammatory properties as evident by attenuating serum C-reactive protein levels and antioxidant effects as evident by attenuating lipid peroxidation marker, malondialdehyde levels, and increasing renal superoxide dismutase activity. Ginger was more potent than AG in both models of renal failure. However, Boswellia showed only partial protective effect against both acute renal failure and CRF and it had no antioxidant effects. Finally, we can say that ginger and AG could be beneficial adjuvant therapy in patients with acute renal failure and CRF to prevent disease progression and delay the need for renal replacement therapy.
Does natural honey affect gastric emptying in rats

Background: Up to date no documented research tends to study influence of natural honey administration on gastric emptying in healthy male albino rats. Aims & Objective: The present study was carried out to investigate the effects of natural honey administration on gastric emptying in healthy male albino rats. Materials and Methods: A total number of 36 healthy, male, albino rats weighing 150- 200 grams were used in this study. The rats were subdivided into sex equal groups I (control group received distilled water), II (received a small dose of honey), III (received a large dose of honey), IV (received metoclopramide), V (received both small dose of honey and metoclopramide) and VI (received both large dose of honey and metoclopramide). Then, percentage of gastric emptying during one hour (experimental period) was calculated in all the groups. Results: This study revealed that honey large dose and the combination of honey large dose with metoclopramide significantly (P
Covariant estimators of time-frequency descriptors for nonstationary random processes

For a nonstationary random process, the time-time correlation function, frequency-frequency Loeve spectrum, time-frequency Wigner-Ville distribution, and frequency-time ambiguity function are each complete theoretical descriptions of second-order behavior. They are complete in the sense that they determine realizations of the random process according to the Cramer-Loeve spectral representation for a harmonizable process. In this paper we derive estimators for these descriptors by requiring them to have the same covariant dependence on time delay and complex modulation as do their theoretical counterparts.
A 1-Gb/s/pin 512-Mb DDRII SDRAM using a digital DLL and a slew-rate-controlled output buffer

We developed a 1-Gb/s/pin 512-Mb DDRII SDRAM composed of a digital delay-locked loop (DLL) and a slew-rate controlled output buffer. The digital DLL has a frequency divider for the DLL input, which performs at a operating frequency of up to 500 MHz at 1.6 V, and it provides internal clocking with 50% duty-cycle correction. The DLL has a current-mirror-type interpolator, which enables a resolution as high as 14 ps, is standby-current-free, and can operate at voltages as low as 0.8 V. The slew-rate impedance-controlled output buffer circuit reduces the output skew from 107 to 10 ps. This SDRAM was tested using a 0.13-/spl mu/m 126.5 mm/sup 2/ 512 Mb device.
Parallelization of spectrum sensing algorithms using graphic processing units

Cognitive radio (CR) is the next-generation communication system with high spectrum utilization and efficiency. It is very crucial for CR to sense the environment spectrum holes quickly and accurately. In this paper, we implement two kinds of spectrum sensing algorithms: waveform-based detection and cyclostationary feature extraction methods. Both of these algorithms are capable to separate the signal of interest from the noise or interference. In order to lower the computation time required by these complex algorithms, we parallelize these algorithms on a Graphic Processing Unit (GPU). Our methods show up to an average of 30× speedup in waveform preamble detection and an average of 39× speedup in cyclostationary feature extraction on a NVIDIA GTS 450 compared with the sequential implementation on a 2.94GHz Intel Core 2 CPU.
Distributed Multiagent Optimization : Linear Convergence Rate of ADMM

We propose a distributed algorithm based on Alternating Direction Method of Multipliers (ADMM) to minimize the sum of locally known convex functions. This optimization problem captures many applications in distributed machine learning and statistical estimation. We provide a novel analysis that shows if the functions are strongly convex and have Lipschitz gradients, then an -optimal solution can be computed with O(κf log(1/ )) iterations, where κf is the condition number of the problem. This is the first paper in the literature that establishes this rate of convergence for distributed ADMM, matching the best known iteration complexity for centralized ADMM. Our analysis also highlights the effect of network structure on the convergence rate.
Analyzing the Effect of Corporate Environmental Performance on Corporate Financial Performance in Developed and Developing Countries

The relationship between corporate environmental performance and corporate financial performance has been extensively studied in developed countries, and has received less attention in developing countries. For this reason, the main objective of this paper is to examine the effect of corporate environmental performance on corporate financial performance during a global financial crisis, depending on the economic development level of the country where a firm is located. To this end, we obtain data for a sample of 2982 large firms from 2008 to 2015. We apply Petersen’s approach to these data, adjusting the standard errors for clustering by both firm and year. The results obtained show that the adoption of environmental practices significantly and positively affects the corporate financial performance in developed and developing countries. However, this effect is stronger for firms located in developing countries than those located in developed countries.
Phase Unwrapping for InSAR using convex feasible model

In this paper, we proposed a complete scheme for phase retrieval under the framework of convex feasible models. The scheme is composed of two steps: the phase unwrapping and denoising. At first, we proposed a novel phase unwrapping method called Ideal Unwrapper (IU). Afterwards, to solve the rest denoising problem, the theory of convex feasible is introduced. In addition, the convex sets for the Projection Onto Convex Sets (POCs) denoising, which might preserve the given arbitrary feature areas perfectly, are also constructed. Finally, numerical results are also illustrated to show the virtues of the proposed scheme. Especially, the proposed Ideal Unwrapper shows its powerful efficiency in Unwrapping two-dimensional phase images with little computational burden by comparing with the newly proposed Graph Cut method.
The LIM‐only protein Lmo2 is a bridging molecule assembling an erythroid, DNA‐binding complex which includes the TAL1, E47, GATA‐1 and Ldb1/NLI proteins

The LIM‐only protein Lmo2, activated by chromosomal translocations in T‐cell leukaemias, is normally expressed in haematopoiesis. It interacts with TAL1 and GATA‐1 proteins, but the function of the interaction is unexplained. We now show that in erythroid cells Lmo2 forms a novel DNA‐binding complex, with GATA‐1, TAL1 and E2A, and the recently identified LIM‐binding protein Ldb1/NLI. This oligomeric complex binds to a unique, bipartite DNA motif comprising an E‐box, CAGGTG, followed ∼9 bp downstream by a GATA site. In vivo assembly of the DNA‐binding complex requires interaction of all five proteins and establishes a transcriptional transactivating complex. These data demonstrate one function for the LIM‐binding protein Ldb1 and establish a function for the LIM‐only protein Lmo2 as an obligatory component of an oligomeric, DNA‐binding complex which may play a role in haematopoiesis.
Tourism and fluctuations in the Hawaiian economy.

Time series methods are used to investigate the importance of tourism to the State of Hawaii. The Hawaiian economy exhibits substantial comovement between the number of tourists and income and employment, especially at long-run frequencies. Tourism has its most immediate impact on gross state product, followed in a few months by personal income. Employment is affected after a lag of one year. The Oahu and Kauai economies are most sensitive to fluctuations in the volume of tourism. The Maui economy is correlated with agricultural shocks while the Big Island fluctuates most strongly with earnings from federal government employment.
Linear and nonlinear kelvin-helmholtz instabilities of high velocity magnetized shear layers with generalized polytrope laws

The linear stability of zero and finite width, arbitrarily compressible, and magnetized velocity shear layers with isotropic or anisotropic pressure is investigated. Such flows, modeled by the magnetohydrodynamic equations with generalized polytrope laws for the pressure parallel and perpendicular to the magnetic field, are relevant in various astrophysical, geophysical and space plasma configurations. The conditions for instability of shear layers of zero width are derived. For layers of finite width, shooting numerical schemes are employed to satisfy the Sommerfeld radiation conditions of outgoing, spatially damping modes in a frame comoving with the plasma flow. The resulting eigenvalues for the angular frequency and linear growth rate are mapped out for different regions of the wave number/Mach number space. For polytrope indices corresponding to the double adiabatic and magnetohydrodynamic equations, the results reduce to those obtained earlier using these models.
Efficient bias correction for magnetic resonance image denoising

Magnetic resonance imaging (MRI) is a popular radiology technique that is used for visualizing detailed internal structure of the body. Observed MRI images are generated by the inverse Fourier transformation from received frequency signals of a magnetic resonance scanner system. Previous research has demonstrated that random noise involved in the observed MRI images can be described adequately by the so‐called Rician noise model. Under that model, the observed image intensity at a given pixel is a nonlinear function of the true image intensity and of two independent zero‐mean random variables with the same normal distribution. Because of such a complicated noise structure in the observed MRI images, denoised images by conventional denoising methods are usually biased, and the bias could reduce image contrast and negatively affect subsequent image analysis. Therefore, it is important to address the bias issue properly. To this end, several bias‐correction procedures have been proposed in the literature. In this paper, we study the Rician noise model and the corresponding bias‐correction problem systematically and propose a new and more effective bias‐correction formula based on the regression analysis and Monte Carlo simulation. Numerical studies show that our proposed method works well in various applications. Copyright © 2012 John Wiley & Sons, Ltd.
Daily Spillover From Family to Work: A Test of the Work–Home Resources Model

The present study examines a mediated moderation model of the day-level effects of family hassles and family-work spillover (affect and cognition) on the relationship between job resources and employees’ flourishing at work. Based on the work–home resources model, the authors hypothesized that demands from one domain (family) induce repetitive thoughts or negative feelings about those problems, so that individuals are not able to function optimally and to make full use of contextual resources in the other domain (work). Multilevel analyses of 108 Chinese working parents’ 366 daily surveys revealed that the relationship between morning job resources and afternoon flourishing was significantly positive when previous day family hassles were low; the relationship became nonsignificant when previous day family hassles were high. In addition, as predicted, daily rumination also attenuated the relationship between morning job resources and afternoon flourishing, whereas daily affect did not. Finally, the moderating effect of previous day family hassles was mediated by daily rumination. The findings contribute to spillover theories by revealing the roles of affective and cognitive spillover from family to work.
Draft Genome Sequence of Prevotella copri Isolated from the Gut of a Healthy Indian Adult

ABSTRACT Prevotella copri, a Gram-negative anaerobic rod-shaped bacterium, is frequently associated with the human gastrointestinal tract and influences host physiology, immunity, and metabolic pathways. In the present study, we report the draft genome sequence of P. copri isolated from the gut of a healthy Indian adult.
Interlaboratory comparability of serum cotinine measurements at smoker and nonsmoker concentration levels: a round-robin study.

INTRODUCTION Cotinine, the primary proximate metabolite of nicotine, is commonly measured as an index of exposure to tobacco in both active users of tobacco and nonsmokers with possible exposure to secondhand smoke (SHS). A number of laboratories have implemented analyses for measuring serum cotinine in recent years, but there have been few interlaboratory comparisons of the results. Among nonsmokers exposed to SHS, the concentration of cotinine in blood can be quite low, and extensive variability in these measurements has been reported in the past. METHODS In this study, a group of seven laboratories, all experienced in serum cotinine analysis, measured eight coded serum pools with concentrations ranging from background levels of about 0.05 ng/ml to relatively high concentrations in the active smokers range. All laboratories used either gas-liquid chromatography with nitrogen-phosphorus detection or liquid chromatography with mass spectrometric detection. RESULTS All seven laboratories reliably measured the cotinine concentrations in samples that were within the range of their methods. In each case, the results for the pools were correctly ranked in order, and no significant interlaboratory bias was observed at the 5% level of significance for results from any of the pools. DISCUSSION We conclude that present methods of chromatographic analysis of serum cotinine, as used by these experienced laboratories, are capable of providing accurate and precise results in both the smoker and the nonsmoker concentration range.