Miracle-dz/UniFAR-FTUs huggingface dataset:
Haplotype-Based Genotyping in Polyploids

Accurate identification of polymorphisms from sequence data is crucial to unlocking the potential of high throughput sequencing for genomics. Single nucleotide polymorphisms (SNPs) are difficult to accurately identify in polyploid crops due to the duplicative nature of polyploid genomes leading to low confidence in the true alignment of short reads. Implementing a haplotype-based method in contrasting subgenome-specific sequences leads to higher accuracy of SNP identification in polyploids. To test this method, a large-scale 48K SNP array (Axiom Arachis2) was developed for Arachis hypogaea (peanut), an allotetraploid, in which 1,674 haplotype-based SNPs were included. Results of the array show that 74% of the haplotype-based SNP markers could be validated, which is considerably higher than previous methods used for peanut. The haplotype method has been implemented in a standalone program, HAPLOSWEEP, which takes as input bam files and a vcf file and identifies haplotype-based markers. Haplotype discovery can be made within single reads or span paired reads, and can leverage long read technology by targeting any length of haplotype. Haplotype-based genotyping is applicable in all allopolyploid genomes and provides confidence in marker identification and in silico-based genotyping for polyploid genomics.
ADVANCED NUMERICAL SIMULATION DEDICATED TO THE PREDICTION OF HEAT TRANSFER IN A HIGHLY LOADED TURBINE GUIDE VANE

This paper proposes to investigate the capacity of numerical simulation to estimate wall heat fluxes in a highly loaded turbine guide vane (with both structured and unstructured flow solvers). Different numerical approaches are assessed, from steady-state methods based on the Reynolds Averaged Navier-Stokes (RANS) equations to more sophisticated methods such as the Large Eddy Simulation (LES) technique. As expected steady flow simulations fail to predict the wall heat transfer, mainly because unsteady flows and laminar-to turbulent transition are not taken into account. The results underline the role of the vortex shedding, mainly through the emission of acoustic waves that interact with the suction side boundary layer. Only the LES (partially) succeeds to estimate wall heat fluxes since this method considerably improves the level of physical description (including boundary layer transition). However, the LES still requires validation and developments for such complex flows. This study also points out the dependency of results to the freestream turbulence intensity, which is a difficult parameter to manage with LES. Structured and unstructured flow solvers predict a different behaviour of the boundary layer (natural or by-passed transition), depending on the external turbulence intensity.Copyright © 2010 by ASME
Simultaneous Localization and Mapping with Dynamic Rigid Objects

Accurate estimation of the environment structure simultaneously with the robot pose is a key capability of autonomous robotic vehicles. Classical simultaneous localization and mapping (SLAM) algorithms rely on the static world assumption to formulate the estimation problem, however, the real world has a significant amount of dynamics that can be exploited for a more accurate localization and versatile representation of the environment. In this paper we propose a technique to integrate the motion of dynamic objects into the SLAM estimation problem, without the necessity of estimating the pose or the geometry of the objects. To this end, we introduce a novel representation of the pose change of rigid bodies in motion and show the benefits of integrating such information when performing SLAM in dynamic environments. Our experiments show consistent improvement in robot localization and mapping accuracy when using a simple constant motion assumption, even for objects whose motion slightly violates this assumption.
GENERALIZED LINEAR MIXED MODEL ESTIMATION USING PROC GLIMMIX: RESULTS FROM SIMULATIONS WHEN THE DATA AND MODEL MATCH, ANDWHEN THE MODEL IS MISSPECIFIED

A simulation study was conducted to determine how well SAS PROC GLIMMIX (SAS Institute, Cary, NC), statistical software to fit generalized linear mixed models (GLMMs), performed for a simple GLMM, using its default settings, as a naive user would do. Data were generated from a wide variety of distributions with the same sets of linear predictors, and under several conditions. Then, the data sets were analyzed by using the correct model (the generating model and estimating model were the same) and, subsequently, by misspecifying the estimating model, all using default settings. The data generation model was a randomized complete block design where the model parameters and sample sizes were adjusted to yield 80% power for the F-test on treatment means given a 30 block experiment with blockby-treatment interaction and with additional treatment replications within each block. Convergence rates were low for the exponential and Poisson distributions, even when the generating and estimating models matched. The normal and lognormal distributions converged 100% of the time; convergence rates for other distributions varied. As expected, reducing the number of blocks from 30 to five and increasing replications within blocks to keep total N the same reduced power to 40% or less. Except for the exponential distribution, estimates of treatment means and variance parameters were accurate with only slight biases. Misspecifying the estimating model by omitting the block-by-treatment random effect made F-tests too liberal. Since omitting that term from the model, effectively ignoring a process involved in giving rise to the data, produces symptoms of over-dispersion, several potential remedies were investigated. For all distributions, the historically recommended variance stabilizing transformation was applied, and then the transformed data were fit using a linear mixed model. For one-parameter members of the exponential family an over-dispersion parameter was included in the estimating model. The negative binomial distribution was also examined as the estimating model distribution. None of these remedial steps corrected the over-dispersion problem created by misspecifying the linear predictor, although using a variance stabilizing transformation did improve convergence rates on most distributions investigated.
Nuclear factor erythroid‐derived 2–related factor 2 activates glutathione S‐transferase expression in the midgut of Spodoptera litura (Lepidoptera: Noctuidae) in response to phytochemicals and insecticides

Detoxication enzymes play an important role in insect resistance to xenobiotics such as insecticides and phytochemicals. We studied the pathway for activating the expression of glutathione S‐transferases (GSTs) in response to selected xenobiotics. An assay of the promoter activity of GST epsilon 1 (Slgste1) of Spodoptera litura led to the discovery of a cis‐regulating element. An antioxidant response element was activated in response to indole‐3‐carbinol (I3C) and chlorpyrifos (CPF) and was able to bind with the xenobiotic sensor protein nuclear factor erythroid‐derived 2–related factor 2 (SlNrf2). SlNrf2 and Slgste1 were responsive to reactive oxygen species induced by I3C and CPF in a S. litura cell line, as well as in S. litura midguts. SlNrf2 RNA interference (RNAi) reduced the message RNA levels of Slgste1 and the peroxidase activity of GSTs in response to I3C, xanthotoxin, CPF and deltamethrin. SlNrf2 RNAi and inhibitor treatment of GST activity decreased the viability of I3C‐treated cells. These results indicate that SlNrf2 activates the expression of GSTs in response to oxidative stresses caused by exposure to xenobiotics.
BlinkML : Approximate Machine Learning with Probabilistic Guarantees

With the increase of dataset volumes, training machine learning (ML) models has become a major computational cost in most organizations. Given the iterative nature of model and parameter tuning, many analysts use a small sample of their entire data during their initial stage of analysis to make quick decisions on which direction to take (e.g., whether and what types of features to add, what type of model to pursue), and use the entire dataset only in later stages (i.e., when they have converged to speci c model). This sampling, however, is performed in an ad-hoc fashion. Most practitioners are not able to precisely capture the e ect of sampling on the quality of their model, and eventually on their decision making process during the tuning phase. Moreover, without systematic support for sampling operators, many optimizations and reuse opportunities are lost. In this paper, we introduce BlinkML, a system for fast training of ML models with quality guarantees. BlinkML allows users to make error-computation tradeo s: instead of training a model on their full data (i.e., full model), they can train on a smaller sample and thus obtain an approximate model. With BlinkML, however, they can explicitly control the quality of their approximate model by either (i) specifying an upper bound on how much the approximate model is allowed to deviate from the full model, or (ii) inquiring about the minimum sample size using which the trained model would meet a given accuracy requirement. Moreover, the error guarantees can be expressed in terms of the model’s parameters or its nal (classi cation or regression) predictions. BlinkML currently supports any ML model that relies on maximum likelihood estimation—an important class of ML algorithms, which includes Generalized Linear Models (e.g., linear regression, logistic regression, max entropy classi er, Poisson regression) as well as PPCA (Probabilistic Principal Component Analysis). Our experiments show that BlinkML can speed up the training of large-scale ML tasks by 1.54×–322× while incurring only 1% accuracy loss compared to the full model trained on the entire data. PVLDB Reference Format: Yongjoo Park, Jingyi Qing, Xiaoyang Shen, Barzan Mozafari. BlinkML: Approximate Machine Learning with Probabilistic Guarantees. PVLDB, 12(xxx): xxxx-yyyy, 2019. DOI: https://doi.org/TBD Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Articles from this volume were invited to present their results at The 45th International Conference on Very Large Data Bases, August 2019, Los Angeles, California. Proceedings of the VLDB Endowment, Vol. 12, No. xxx Copyright 2018 VLDB Endowment 2150-8097/18/10. $ 10.00. DOI: https://doi.org/TBD
Normal Heartbeat Sound and the Behavior of Newborn Infants‐‐A Replication Study

&NA; A group of infants exposed to a simulated heartbeat sound at 45 decibels during the first 4 days of life did not respond differently in terms of weight gain, activity, or formula intake from a group of control infants not so exposed. A significant positive correlation between weight gain and food intake was noted. Some of the pertinent differences between this replication and the previous study by Salk are considered in an effort to clarify some of the questions of design and the differences in findings.
Learning-Based Memory Allocation Optimization for Delay-Sensitive Big Data Processing

Optimal resource provisioning is essential for scalable big data analytics. However, it has been difficult to accurately forecast the resource requirements before the actual deployment of these applications as their resource requirements are heavily application and data dependent. This paper identifies the existence of effective memory resource requirements for most of the big data analytic applications running inside JVMs in distributed Spark environments. Provisioning memory less than the effective memory requirement may result in rapid deterioration of the application execution in terms of its total execution time. A machine learning-based prediction model is proposed in this paper to forecast the effective memory requirement of an application given its service level agreement. This model captures the memory consumption behavior of big data applications and the dynamics of memory utilization in a distributed cluster environment. With an accurate prediction of the effective memory requirement, it is shown that up to 60 percent savings of the memory resource is feasible if an execution time penalty of 10 percent is acceptable. The accuracy of the model is evaluated on a physical Spark cluster with 128 cores and 1TB of total memory. The experiment results show that the proposed solution can predict the minimum required memory size for given acceptable delays with high accuracy, even if the behavior of target applications is unknown during the training of the model.
Dicer‐1 is a key enzyme in the regulation of oogenesis in panoistic ovaries

In insects, the action of microRNAs (miRNAs) on oogenesis has been explored only in dipterans, which possess meroistic ovaries, a highly modified ovarian type. Here we study miRNA function in the most primitive, panoistic type of ovaries using the phylogenetically basal insect Blattella germanica (Dictyoptera, Blattellidae) as model.
Kiprah Politik Dan Sejarah Organisasi Muhammadiyah di Indonesia

The History of politics development in Indonesia, the really can't forget the role of muslim people groups in national politics stage, one of them named Muhammadiyah organization. This big organization found since 1912 by KH. Ahmad Dahlan with struggles main basic, bringing muslim people back to really confidence, which is that pure leaning to Qur’ an and hadits and not to another one. Politic action form’s manifested on three movement patterns: revivalism, secularism and modernism. In revivalism pattern, Muhammadiyah struggle’s have given its contribution to BPUPKI about year 1945 as alternative solution divides state basics. secularism is not amends, meanwhile modernism declares that Islamic teaching can be fused by politics or state problem can be carried on concurrently so forms symbiotic relationship among religion with state or politics.
Art Education and the Creativity Level of the Students

There are many reasons that affect individuals’ creativity. Art education is the most relevant discipline for developing the creativity of children. Art education aims to develop the creativity of children and it helps them to analyze their problems. The main aim of the study is to determine the creativity level of the high school students who take art education lessons and those who do not. For determining the creativity level of the students an attitude scale was developed and also the Torrance Test of Creative Thinking Verbal A Form was used. The results of the study show to hat the students who take Art Education lesson were more Creative than others. There isn’t any
Shelf‐basin gradients shape ecological phytoplankton niches and community composition in the coastal Arctic Ocean (Beaufort Sea)

The contiguous Arctic shelf is the green belt of the Arctic Ocean. Phytoplankton dynamics in this environment are driven by extreme physical gradients and by rapid climate change, which influence light and nutrient availability as well as the growth and ecological characteristics of phytoplankton. A large dataset collected across the Canadian Beaufort Shelf during summer 2009 was analyzed to assess how the interplay of physical and biogeochemical conditions dictates phytoplankton niches and trophic regimes. Nonmetric multidimensional scaling and cluster analysis demonstrated marked partitioning of phytoplankton diversity. Elevated phytoplankton biomass (∼ 2.41 μg Chl a L−1) was observed in association with the surface mixed layer near the coast, close to the mouth of the Mackenzie River, and at the shelf‐break as a result of nutrient‐rich Pacific water intrusions. The coastal communities were supported by high levels of nitrogen nutrients and were taxonomically uniform, with diatoms accounting for 95% of total cell numbers. By contrast, adjacent oceanic waters were characterized by low autotrophic biomass near the surface (∼ 0.09 μg Chl a L−1) and below the mixed layer (∼ 0.23 μg Chl a L−1) due to mainly nutrient limitation. However, the oceanic community was more diverse with a mixed assemblage of diatoms and small mixotrophs/heterotrophs near the surface and a predominance of autotrophic nanoflagellates at depth. We conclude that as climate change intensifies freshening and stratification in the Western Arctic Ocean, coastal hotspots of high autotrophic productivity may play an even greater role in supporting Arctic marine ecosystems while offshore environments become increasingly oligotrophic.
What can Sydney tell us about coaching? Research with implications for practice from down under.

This paper details material from 2 presentations given at the 2015 Society of Consulting Psychology Mid-Winter Conference in San Diego, California, which presented a summary of the coaching research conducted at the Coaching Psychology Unit (CPU) at the University of Sydney. The CPU was established in 1999 with a mission to enhance the performance, productivity, and quality of life of individuals, organizations, and the broader community through excellence in education, research, and the practice of coaching psychology. Drawing on over 150 CPU publications—including 8 randomized, controlled, outcome studies; 9 between-subjects or within-subject outcome studies; and a range of cross-sectional studies—this paper considers the empirical CPU research related to 4 key questions of relevance to practitioners: (a) What is a practical theoretical framework for coaching? (b) Does coaching “work”? (c) What makes a difference in the coach– coachee relationship? (d) How can coaching psychology contribute to the broader psychological enterprise? CPU research supports the notion that a solution-focused cognitive– behavioral theoretical framework is an effective and practical approach to coaching that facilitates goal attainment and enhances well-being and is effective with a wide range of populations. Implications for research and practice are discussed.
Neighborhoods and mortality in Sweden : Is deprivation best assessed nationally or regionally?

BACKGROUND The association between neighborhood deprivation and mortality is well established, but knowledge about whether deprivation is best assessed regionally or nationally is scarce. OBJECTIVE The present study aims to examine whether there is a difference in results when using national and county-specific neighborhood deprivation indices and whether the level of urbanization modifies the association between neighborhood deprivation and mortality. METHODS We collected data on the entire population aged above 50 residing in the 21 Swedish counties on January 1, 1990, and followed them for mortality due to all causes and for coronary heart disease. The association between neighborhood deprivation and mortality was assessed using Cox regression, assuming proportional hazards with attained age as an underlying variable, comparing the 25% most deprived neighborhoods with the 25% most affluent ones within each region, and using both the national and the county-specific indices. The potential interactions were also assessed. RESULTS The choice of a national or a county-specific index did not affect the estimates to a large extent. The effect of neighborhood deprivation on mortality in metropolitan regions (hazard ratio: 1.21 [1.20-1.22]) was somewhat higher than that in the more rural southern (HR: 1.16 [1.15-1.17]) and northern regions (HR: 1.11 [1.09-1.12]). CONCLUSION Our data indicates that the choice of a national or a county-specific deprivation index does not influence the results to a significant extent, but may be of importance in large metropolitan regions. Furthermore, the strength of the association between neighborhood deprivation and mortality is somewhat greater in metropolitan areas than in more rural southern and northern areas. (Less)
Amplification of HTLV‐1‐related Sequences among Patients with Neurological Disorders in Highly Endemic Nagasaki: Lack of Evidence for Association of HTLV‐1 with Multiple Sclerosis

We studied DNA sequences homologous to HTLV‐1 in peripheral blood mononuclear cells (PBMC) of 30 patients with neurological disorders in Kyushu, where HTLV‐1 is highly endemic. The regions of HTLV‐1 amplified by means of polymerase chain reaction (PCR) included U3, U5, gag, pol, env and pX. Our system specifically detected HTLV‐1 sequences only from HTLV‐1‐positive cells and was sufficiently sensitive to detect one proviral copy per 103 PBMC. All PCR‐positive cases were seropositive, including 4 cases of tropical spastic paraparesis/HTLV‐1‐associated myelopathy (TSP/HAM) (4/4), and one case each of myasthenia gravis (1/7) and multiple sclerosis (1/8). The PCR‐positive rate of patients, excluding 4 TSP/HAM cases, was 8% (2/26), which is similar to the seroprevalence of the adult population in the area. The data suggest that multiple sclerosis is not associated with prototype HTLV‐1.
Serum n‐3 Fatty Acids, Fish Consumption and Cancer Mortality in Six Japanese Populations in Japan and Brazil

Japanese people consume significant amounts of long chain n‐3 polyunsaturated fatty acids (PUFAs) derived from fish, but the association of PUFAs with cancer mortality has not been fully investigated. To study geographic differences in n‐3 PUFAs intake, we compared serum fatty acid and dietary fish intake among various Japanese populations having different rates of cancer mortality. The subjects were 50 men from each of five regions in Japan and 47 Japanese men from Sao Paulo, Brazil. All were randomly selected and aged 40 to 49 years. Serum fatty acids were measured by gas chromatography and the frequency of fish intake was obtained by a food frequency questionnaire. Significant geographic differences in serum fatty acid levels (% of total fatty acids) and fish intake (days/4 weeks) were observed. The percentages of serum total PUFA were similar in the six regions, though there was an almost three‐fold difference in n‐3 PUFAs content between Brazil (3.9%) and Akita (10.9%). The frequency of total fish intake corresponded to serum n‐3 PUFAs composition. The relationship between cancer mortality and serum n‐3 PUFAs levels was not clear, though an inverse association between prostate cancer and serum n‐3 PUFAs levels appeared to exist. The results suggest that although serum n‐3 PUFAs varied significantly, the observed geographic difference did not account for the different cancer risks at the population level.
Time-Domain Impulse Response With the TD-VSIE Field-Circuit Coupling Algorithm for Nonlinear Analysis of Microwave Amplifier

In this letter, the time-domain impulse response with the time-domain volume–surface integral equation field-circuit coupling algorithm is presented. This method uses the time-domain impulse response technique to separate the calculation of the linear electromagnetic field structure from the nonlinear equivalent circuit in the microwave circuit. First, the time-domain impulse response sources of the linear microwave structure are extracted at the location of ports. Then, the nonlinear system equations are built by the time-domain impulse response sources and the equivalent circuit equations. Meanwhile, the Newton–Raphson iteration algorithm is utilized to solve the nonlinear system equations. Finally, the simulation results illustrate that the proposed method is more accurate and effective than the conventional method.