Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relative Efficiency of Two Multistage Linear Phenotypic Selection Indices to Predict the Net Genetic Merit

Multistage linear phenotypic selection indices predict the individual net genetic merit at different individual ages or stages and are cost-saving strategies for improving several traits. In a two-stage context, we compared the relative efficiency of the optimum multistage linear phenotypic selection index (OMLPSI) and the decorrelated multistage linear phenotypic selection index (DMLPSI) theory to predict the individual net genetic merit and selection response using a real and a simulated dataset. In addition, we described a method for obtaining the OMLPSI selection intensity in a two-stage context. The criteria used to compare the relative efficiency of both indices were that the total selection response of each index must be lower than or equal to the single-stage linear phenotypic selection index (LPSI) selection response, similar to the accuracy of each index to predict the net genetic merit. Using four different total proportions (p = 0.05, 0.10, 0.20, and 0.30) for the real dataset, the total DMLPSI selection response was 22.80% higher than the estimated single-stage LPSI selection response, whereas the total OMLPSI selection response was only 2.21% higher than the estimated single-stage LPSI selection response. In addition, at Stage 2, OMLPSI accuracy was 62.24% higher than the DMLPSI accuracy for predicting the net genetic merit. We found similar results for the simulated data. Thus, we recommend using OMLPSI when performing the multistage phenotypic selection. Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600, Mexico City, Mexico. Received 10 Nov. 2018. Accepted 28 Feb. 2019. *Corresponding author ( j.crossa@cgiar.org). Assigned to Associate Editor Timothy Beissinger. Abbreviations: DMLPSI, decorrelated multistage linear phenotypic selection index; LPSI, single-stage linear phenotypic selection index; OMLPSI, optimum multistage linear phenotypic selection index; QTL, quantitative trait locus. Published in Crop Sci. 59:1037–1051 (2019). doi: 10.2135/cropsci2018.11. 0678 © 2019 The Author(s). This is an open access article distributed under the CC BY license (https://creativecommons.org/licenses/by/4.0/). Published May 16, 2019
Cross-cultural ageism: ageism and attitudes toward aging among Jews and Arabs in Israel

ABSTRACT Background: While it is generally agreed that traditional societies are more favorable toward their elders, research findings have been inconsistent. Accordingly, this study presents a cultural comparison between Jews and Arabs in Israel in attitudes toward older adults and personal views regarding one's own aging. It was assumed that Arabs would rate their culture as more tolerant toward older adults, would report spending more time with them, and express lower ageism and aging anxieties. Method: We examined 154 native Israeli citizens, 86 Jewish and 68 Muslim Arabs, who completed measures of ageism, aging anxieties, and cultural views of older adults. Results: Arabs rated their culture as more tolerant toward their elders, perceived older adults as significantly more contributing to society, and reported engaging in less avoiding behaviors toward them. Arabs also exhibited less general fears of growing old and concerns over one's physical appearance in old age. But it was interesting to note that Arab women reported higher scores of aging anxieties and ageist attitudes in comparison to Arab men, whereas no such differences were found among Jews. Conclusions: Our findings point that the cultural importance of elders for the Arab cohort transcends beyond Westernization processes which affect the Arab society in Israel, and reflect the demanding role of Arab women as primary caregivers for the elders in the family. Limitations and implications of the study are discussed.
Deep learning for ocean remote sensing: an application of convolutional neural networks for super-resolution on satellite-derived SST data

In this paper, we propose to address the downscaling of ocean remote sensing data using image super-resolution models based on deep learning, and more particularly Convolutional Neural Networks (CNNs). The goal of this study, for which we focus on satellite-derived Sea Surface Temperature (SST) data, is to evaluate the efficiency and the relevance of deep learning architectures applied to oceanographic remote sensing data. By using a CNN architecture, namely SRCNN (Super Resolution CNN), on a large-scale dataset of SST fields, we show that it allows a considerable gain in terms of PSNR compared to classical downscaling techniques. These results point out the relevance of deep learning models specifically trained for ocean remote sensing data and advocate for other applications to the reconstruction of high-resolution sea surface geophysical fields from multi-sensor satellite observations.
Incidence of Ciprofloxacin-Resistant of Methicillin Resistant Staphylococcus aureus isolated from Iraqi patients

The resistance of Staphylococcus aureus to ciprofloxacin has complicated the problem of treating staphylococcal associated infections in which MRSA is the causative agent since ciprofloxacin was the drug of choice to treat such infections. Our study investigated the incidence of Ciprofloxacin resistant S. aureus isolates that were also methicillin resistant among Iraqi patients. The obtained bacterial isolates were tested for Ciprofloxacin resistance using agar dilution method and the sequence of gyrA and parC . The results revealed that about 8% of the isolated MRSA strains were Ciprofloxacin resistant and the resistance was due to mutation in gyrA rather than parC .
Adsorption of Mercury(II) using Activated Produced from Bambusa vulgaris var. striata in a Fixed Bed Column

Pollution by mercury dissolved in aqueous media causes a crucial problem for health and environment. In this study, activated carbon from Bambusa vulgaris var. striata was produced by chemical activation using NaOH for mercury adsorption. The effects of mercury initial concentrations namely 50 and 100 mg/L on the breakthrough characteristics of the adsorption process were defined. The mechanism of the adsorption process through the fixed-bed column was fitted to the Thomas model. The activated carbon was characterized by scanning electron microscopy and energy-dispersive X-ray spectroscopy. The adsorption study with a continuous system and using the Thomas model showed that the highest adsorption capacity (q0) of mercury ions is 218.08 mg/g. It can be concluded that activated carbon from Bambusa vulgaris var. striata has a great potential to act as an adsorbent to remove mercury from water.
Color Image Quality Assessment Based on Image Quality Parameters Perceived by Human Vision System

A color image quality assessment (C-IQA) method was proposed based on the primary and fundamental image quality parameters perceived by human vision system. The methods for measuring these parameters were given. A comprehensive image quality assessment model, called as the best quality assessment function for the color image, was established through trials by means of these parameters. The maximum of the function corresponds to the color image with the best quality. The function could be used either in FR-IQA or in NR-IQA. Not only it does not relied to any reference image but also could be used to assess the reference image quality. The method could also be used to acquire the color image with the best quality by means of a reference image through a gray transformation our called Zadeh-X transformation if the reference image quality is not good enough.
Graphics processing unit optimizations for the dynamics of the HIRLAM weather forecast model

Programmable graphics processing units (GPUs) nowadays offer tremendous computational resources for diverse applications. In this paper, we present the implementation of the dynamics routine of the HIRLAM weather forecast model on the NVIDIA GTX 480. The original Fortran code has been converted manually to C and CUDA. Empirically, it is determined what the optimal number of grid points per thread is, and what the best thread and block structures are. A significant amount of the elapsed time consists of transferring data between CPU and GPU. To reduce the impact of these transfer costs, we overlap calculation and transfer of data using multiple CUDA streams. We developed an algorithm that enables our code generator CTADEL to generate automatically the optimal CUDA streams program. Experiments are performed to find out if the applicability of GPUs is useful for Numerical Weather Prediction, in particular for the dynamics part. Copyright © 2012 John Wiley & Sons, Ltd.
Cystatin C is a good predictor of hepatorenal syndrome and survival in patients with cirrhosis who have normal serum creatinine levels.

BACKGROUND/AIMS We evaluated the usefulness of cystatin C as a prognostic marker in patients with liver cirrhosis and normal serum creatinine. METHODOLOGY We retrospectively analyzed prospectively enrolled patients with liver cirrhosis and normal serum creatinine from February 2007 to March 2008. We checked liver function and kidney variables including serum creatinine, cystatin C and glomerular filtration rate from 51Cr-EDTA on the same day for all patients. The endpoints of the study were either development of hepatorenal syndrome or mortality. RESULTS In total, 112 patients with liver cirrhosis were enrolled in the study (87 men and 25 women, age 52 ± 12 years). Twelve (11%), 59 (53%) and 41 (36%) patients were in Child-Pugh class A, B and C, respectively. Cystatin C was better correlated with glomerular filtration rate from 51Cr-EDTA than creatinine. The 1-year cumulative incidence of hepatorenal syndrome and the 1-year survival rate of patients were 20.5% and 79.5%, respectively. Cystatin C, Model for End-Stage Liver Disease and serum sodium were the independent predictive factors for hepatorenal syndrome. Cystatin C, serum sodium and prothrombin time were the independent factors for predicting survival. CONCLUSIONS In patients with liver cirrhosis and normal creatinine levels, cystatin C is a useful marker for predicting hepatorenal syndrome and survival.
Using Drug Similarities for Discovery of Possible Adverse Reactions

We propose a new computational method for discovery of possible adverse drug reactions. The method consists of two key steps. First we use openly available resources to semi-automatically compile a consolidated data set describing drugs and their features (e.g., chemical structure, related targets, indications or known adverse reaction). The data set is represented as a graph, which allows for definition of graph-based similarity metrics. The metrics can then be used for propagating known adverse reactions between similar drugs, which leads to weighted (i.e., ranked) predictions of previously unknown links between drugs and their possible side effects. We implemented the proposed method in the form of a software prototype and evaluated our approach by discarding known drug-side effect links from our data and checking whether our prototype is able to re-discover them. As this is an evaluation methodology used by several recent state of the art approaches, we could compare our results with them. Our approach scored best in all widely used metrics like precision, recall or the ratio of relevant predictions present among the top ranked results. The improvement was as much as 125.79% over the next best approach. For instance, the F1 score was 0.5606 (66.35% better than the next best method). Most importantly, in 95.32% of cases, the top five results contain at least one, but typically three correctly predicted side effect (36.05% better than the second best approach).
Stabilization and robust stabilization of nonlinear differential-algebraic systems: a Hamiltonian function method

The stabilization and robust stabilization of nonlinear differential algebraic systems (NDAS) are investigated using the Hamiltonian function method. Based on a novel dissipative Hamiltonian realization structure, we first present a criterion for the stability analysis of NDAS and construct a stabilization controller consequently. Then, for NDAS in presence of disturbances, the L2 gain is analyzed via generalized Hamilton-Jacobi inequality. An Hinfin control strategy is proposed for Hamiltonian realizable NDAS
In vivo imaging of cortical pathology in multiple sclerosis using ultra-high field MRI

Objective: We used ultra-high field MRI to visualize cortical lesion types described by neuropathology in 16 patients with multiple sclerosis (MS) compared with 8 age-matched controls; to characterize the contrast properties of cortical lesions including T2*, T2, T1, and phase images; and to investigate the relationship between cortical lesion types and clinical data. Methods: We collected, on a 7-T scanner, 2-dimensional fast low-angle shot (FLASH)-T2*-weighted spoiled gradient-echo, T2-weighted turbo spin-echo (TSE) images (0.33 × 033 × 1 mm3), and a 3-dimensional magnetization-prepared rapid gradient echo. Results: Overall, 199 cortical lesions were detected in patients on both FLASH-T2* and T2-TSE scans. Seven-tesla MRI allowed for characterization of cortical plaques into type I (leukocortical), type II (intracortical), and type III/IV (subpial extending partly or completely through the cortical width) lesions as described histopathologically. Types III and IV were the most frequent type of cortical plaques (50.2%), followed by type I (36.2%) and type II (13.6%) lesions. Each lesion type was more frequent in secondary progressive than in relapsing–remitting MS. This difference, however, was significant only for type III/IV lesions. T2*-weighted images showed the highest, while phase images showed the lowest, contrast-to-noise ratio for all cortical lesion types. In patients, the number of type III/IV lesions was associated with greater disability (p < 0.02 by Spearman test) and older age (p < 0.04 by Spearman test). Conclusions: Seven-tesla MRI detected different histologic cortical lesion types in our small multiple sclerosis (MS) sample, suggesting, if validated in a larger population, that it may prove a valuable tool to assess the contribution of cortical MS pathology to clinical disability.
An Integrative Multi-Network and Multi-Classifier Approach to Predict Genetic Interactions

Genetic interactions occur when a combination of mutations results in a surprising phenotype. These interactions capture functional redundancy, and thus are important for predicting function, dissecting protein complexes into functional pathways, and exploring the mechanistic underpinnings of common human diseases. Synthetic sickness and lethality are the most studied types of genetic interactions in yeast. However, even in yeast, only a small proportion of gene pairs have been tested for genetic interactions due to the large number of possible combinations of gene pairs. To expand the set of known synthetic lethal (SL) interactions, we have devised an integrative, multi-network approach for predicting these interactions that significantly improves upon the existing approaches. First, we defined a large number of features for characterizing the relationships between pairs of genes from various data sources. In particular, these features are independent of the known SL interactions, in contrast to some previous approaches. Using these features, we developed a non-parametric multi-classifier system for predicting SL interactions that enabled the simultaneous use of multiple classification procedures. Several comprehensive experiments demonstrated that the SL-independent features in conjunction with the advanced classification scheme led to an improved performance when compared to the current state of the art method. Using this approach, we derived the first yeast transcription factor genetic interaction network, part of which was well supported by literature. We also used this approach to predict SL interactions between all non-essential gene pairs in yeast (http://sage.fhcrc.org/downloads/downloads/predicted_yeast_genetic_interactions.zip). This integrative approach is expected to be more effective and robust in uncovering new genetic interactions from the tens of millions of unknown gene pairs in yeast and from the hundreds of millions of gene pairs in higher organisms like mouse and human, in which very few genetic interactions have been identified to date.
A Seismic Design Lateral Force Distribution Based on Inelastic State of Structures

It is well recognized that structures designed by current codes undergo large inelastic deformations during major earthquakes. However, lateral force distributions given in the seismic design codes are typically based on results of elastic-response studies. In this paper, lateral force distributions used in the current seismic codes are reviewed and the results obtained from nonlinear dynamic analyses of a number of example structures are presented and discussed. It is concluded that code lateral force distributions do not represent the maximum force distributions that may be induced during nonlinear response, which may lead to inaccurate predictions of deformation and force demands, causing structures to behave in a rather unpredictable and undesirable manner. A new lateral force distribution based on study of inelastic behavior is developed by using relative distribution of maximum story shears of the example structures subjected to a wide variety of earthquake ground motions. The results show that the suggested lateral force distribution, especially for the types of framed structures investigated in this study, is more rational and gives a much better prediction of inelastic seismic demands at global as well as at element levels.
Viscosity of MgSiO3 Liquid at Earth’s Mantle Conditions: Implications for an Early Magma Ocean

Mixing the Magma Ocean Molten silicate makes up the majority of the magma we see spewing out of volcanoes, yet the mantle from which these melts originate is largely solid. The high pressures and temperatures at which these melts exist make interrogating their physical properties difficult. Karki and Stixrude (p. 740) used high-powered computational methods to calculate the viscosity profiles of one of the more abundant silicate melt compositions. The addition of water to the melt lowers the viscosity to the point that large mineral grains can sink. Because Earth may have been nearly all liquid in its earliest stages of formation, a deep magma ocean with this viscosity could have controlled the temperature of Earth's early surface. The behavior of the liquid mantle during Earth’s earliest stages was controlled by the viscosity of silicate melts. Understanding the chemical and thermal evolution of Earth requires knowledge of transport properties of silicate melts at high pressure and high temperature. Here, first-principles molecular dynamics simulations show that the viscosity of MgSiO3 liquid varies by two orders of magnitude over the mantle pressure regime. Addition of water systematically lowers the viscosity, consistent with enhanced structural depolymerization. The combined effects of pressure and temperature along model geotherms lead to a 10-fold increase in viscosity with depth from the surface to the base of the mantle. Based on these calculations, efficient heat flux from a deep magma ocean may have exceeded the incoming solar flux early in Earth’s history.
Antecedents to Purchase Intention – A Perceptual Study About 'YouTube' Videos

Companies in the world are constantly seeking for new ways to reach consumers. Recently, there are numerous social media platforms through which people are connected. Companies are using social media to influence customer Purchase Intention. YouTube is one of the new social media platforms used by the companies for advertisement of their products. The increasing focus on social media shaped state of the art advertising and shifted the way companies interact with their target groups. The main objective of this research is to identify the factors that affect purchase intention of customer who watch product related YouTube videos. This study is one of the rare studies that combine YouTube videos and their effects on purchase intention. Number of Views, Likes, Comments and Replies (NVLCR), Perceived Credibility (PC), Perceived Usefulness (PU), Perceived Video Characteristics (PVC), Attitude towards Purchase (ATP) are various factors studied in association with purchase intention. In this study, a Video was shown to the respondents and Online Questionnaire based on video was filled by respondents. Multiple Regression Test was applied to the relationships between variables.
A retrospective analysis of the effects of adopting individual transferable quotas in the Tasmanian red rock lobster, Jasus edwardsii, fishery

Individual transferable quotas (ITQ) were implemented in the Tasmanian red rock lobster fishery in 1998 and ten years later we assessed the impacts on the fishery. Particular attention was devoted to investigating the performances of the fishery with regard to three features identified as major impacts in the literature: rationalization of the fishing fleet, change in fishing strategy in order to maximise the fisher's profit and concentration of fishing rights and activity. On average, the fishery reacted as expected and reached its objective in terms of reconstruction of the biomass, but the overall assessment in terms of resulting profitability is not very conclusive. There is no evidence of decrease of the profitability over the period of the study but the fishery is more reactive to external factors on its export market in China than to changes in its own structure.
Immunotherapy of respiratory syncytial virus infection in cotton rats (Sigmodon fulviventer) using IgG in a small-particle aerosol.

To determine whether aerosolized IgG can be used effectively in the treatment of respiratory syncytial virus (RSV) infections, cotton rats were infected intranasally with RSV and treated 3 days later with human IgG containing anti-RSV antibodies delivered in a small-particle aerosol. Pulmonary histology and virus titers were determined 24 h after IgG treatment. A single 15-min exposure to aerosolized IgG did not exacerbate pulmonary pathology and effected a 50-fold reduction in pulmonary virus titer (2.95 vs. 4.67 log10 geometric mean pfu/g for untreated controls, P < .001), which was comparable to that effected by intranasally instilled IgG (50 mg/kg) (3.24 vs. 4.67 log10 geometric mean pfu/g for controls, P < .001). A 15-min exposure to aerosolized ribavirin (20 mg/mL) was not effective in reducing pulmonary virus. This study suggests that aerosolized IgG could be useful in the treatment of RSV lower respiratory tract infections and that it compares favorably with ribavirin.
Char2Wav: End-to-End Speech Synthesis

We present Char2Wav, an end-to-end model for speech synthesis. Char2Wav has two components: a reader and a neural vocoder . The reader is an encoder-decoder model with attention. The encoder is a bidirectional recurrent neural network that accepts text or phonemes as inputs, while the decoder is a recurrent neural network (RNN) with attention that produces vocoder acoustic features. Neural vocoder refers to a conditional extension of SampleRNN which generates raw waveform samples from intermediate representations. Unlike traditional models for speech synthesis, Char2Wav learns to produce audio directly from text