Miracle-dz/UniFAR-FTUs huggingface dataset:
Normalizing bead-based microRNA expression data: a measurement error model-based approach

MOTIVATION Compared with complementary DNA (cDNA) or messenger RNA (mRNA) microarray data, microRNA (miRNA) microarray data are harder to normalize due to the facts that the total number of miRNAs is small, and that the majority of miRNAs usually have low expression levels. In bead-based microarrays, the hybridization is completed in several pools. As a result, the number of miRNAs tested in each pool is even smaller, which poses extra difficulty to intrasample normalization and ultimately affects the quality of the final profiles assembled from various pools. In this article, we consider a measurement error model-based method for bead-based microarray intrasample normalization. RESULTS In this study, results from quantitative real-time PCR (qRT-PCR) assays are used as 'gold standards' for validation. The performance of the proposed measurement error model-based method is evaluated via a simulation study and real bead-based miRNA expression data. Simulation results show that the new method performs well to assemble complete profiles from subprofiles from various pools. Compared with two intrasample normalization methods recommended by the manufacturer, the proposed approach produces more robust final complete profiles and results in better agreement with the qRT-PCR results in identifying differentially expressed miRNAs, and hence improves the reproducibility between the two microarray platforms. Meaningful results are obtained by the proposed intrasample normalization method, together with quantile normalization as a subsequent complemental intersample normalization method. AVAILABILITY Datasets and R package are available at http://gauss.usouthal. edu/publ/beadsme/.
Post-prandial plasma glucose prediction in type I diabetes based on Impulse Response Models

In this paper the impact of different meals and rapid insulin were estimated as Finite Impulse Response Models from a data set of 18 patients. Based on these models short-term individualized predictors were tested for 20 and 60 minute prediction. The predictors were evaluated using Clarke Grid Analysis and had on average more than 94 % and 75 % in the A zone and less than 1 % and 3 % in the errorous C/D/E zones, which in comparison to other published results is competitive.
Faculty Experiences with Bullying in Higher Education Causes , Consequences , and Management Loraleigh Keashly Wayne State University

Although much research has been done on workplace aggression and bullying over the past two decades, academics have paid relatively little attention to bullying in their own institutions. In this article, we discuss what is currently known about bullying in academia, with a particular focus on faculty behavior, and apply empirical and conceptual findings from research on aggression and bullying in other work settings and the significant literature on conflict management in higher education. We begin by describing the nature and prevalence of aggression and bullying in higher education. Drawing on well-established findings from interpersonal aggression research, we discuss several important social, situational, and contextual antecedents to aggression (including academic culture, climate, values, and work practices) and demonstrate how these may serve as causes and consequences of bullying. Embedded in this discussion, we offer a number of specific propositions for future research. We conclude with a discussion of possible actions for prevention and management of bullying in higher educational settings. In the 1990s, researchers began to discuss, and explore, bullying among adults in work settings (Leymann, 1990). For the better part of the past two decades, a growing number of researchers (ourselves included) have been conducting research on this and related phenomena (e.g., workplace aggression and violence, mobbing, emotional abuse, etc.). Surprisingly, university-
Politics in the Courtroom: Political Ideology and Jury Decision Making

This paper uses data from the Gothenburg District Court in Sweden and a research design that exploits the random assignment of politically appointed jurors (termed namndeman) to make three contributions to the literature on jury decision-making: (i) an assessment of whether systematic biases exist in the Swedish namndeman system, (ii) causal evidence on the impact of juror political party on verdicts, and (iii) an empirical examination of the role of peer effects in jury decision-making. The results reveal a number of systematic biases: convictions for young defendants and those with distinctly Arabic sounding names increase substantially when they are randomly assigned jurors from the far-right (nationalist) Swedish Democrat party, while convictions in cases with a female victim increase markedly when they are assigned jurors from the far-left (feminist) Vanster party. The results also indicate the presence of peer effects, with jurors from both the far-left and far-right parties drawing the votes of their more centrist peers towards their positions. Peer effects take the form of both sway effects, where jurors influence the opinions of their closest peers in a way that can impact trial outcomes, and dissent aversion, where jurors switch non-pivotal votes so that the decision is unanimous.
THE GENESIS OF MORPHOLOGIES IN EXTENDED RADIO SOURCES: X-SHAPES, OFF-AXIS DISTORTIONS, AND GIANT RADIO SOURCES

We examine relationships between the morphology in double radio sources and the radio–optical position angle offset—the relative orientation of the radio axis with respect to the major axis of the host galaxy. The study was done for a representative sample of radio sources, the nearby (redshift z < 0.5) 3CRR sources, and separately for samples of giant radio sources and X-shaped radio sources. We find that radio morphological features have a dependence on the radio-optical position angle offset and on whether the source is a major- or minor-axis source. The evidence indicates an anisotropic gas environment, related to the ellipticity of the host galaxy, that causes the source linear size evolution, strength of backflow in the radio lobes, off-axis lobe distortions and the formation of wings, and X-shaped radio sources to depend on the radio–optical position angle offset. We identify a class of X-shaped radio sources, which are either edge-darkened or lacking hotspots, and appear to have inner doubles suggesting a restarting of activity. We suggest a common formation mechanism, requiring backflows, for these apparently FR-I X-shaped radio sources as well as the edge-brightened X-shaped sources.
Predictive Factors Influencing Health Conservation in Professional Career-retired Elders

Purpose: This study was done to identify the relationships between body composition, social support, self-esteem, and health conservation and to identify the predictive factors influencing health conservation among professional career-retired elders. Methods: Participants were 112 professional career-retired elders living in D or G cities. Data collection was done through interviews during March and April, 2015. Body composition was measured with the Inbody 230 (Biospace, Korea), social support with the Medical Outcomes Study Social Support Survey (MOS-SSS), self-esteem with Self Esteem Questionnaire, and health conservation with the Health Conservation Scale. Data analysis included one-way ANOVA, independent t-test, Pearson correlation, and stepwise multiple regression, done with the SPSS/WIN 19.0 program. Results: The results show that fitness score, social support, self-esteem and financial status are the predictive factors influencing health conservation in professional career-retired elders. This result accounts for 63.3% of the variance in health conservation. Conclusion: The results indicate that to increase health conservation among professional career-retired elders, nursing interventions are needed to increase fitness score, social support, and self-esteem.
The Bottleneck of Second Language

Explaining why some linguistic features and constructions are easy or difficult to acquire in a second language has become a prominent current concern in generative second language acquisition (SLA) research. Based on a comparison of findings on the L2 acquisition of functional morphology, syntax, semantics and pragmatics, the Bottleneck Hypothesis argues that functional morphemes and their features are the bottleneck of L2 acquisition; acquisition of universal syntax, semantics and pragmatics flows smoothly (Slabakova 2006, 2008, 2013). The article surveys experimental studies supporting this view. A pedagogical implication of this model is discussed, namely, that an enhanced focus on practicing grammar in language classrooms is beneficial to learners.
Using WordNet to Extend FrameNet Coverage

We present two methods to address the problem of sparsity in the FrameNet lexical database. The first method is based on the idea that a word that belongs to a frame is ``similar'' to the other words in that frame. We measure the similarity using a WordNet-based variant of the Lesk metric. The second method uses the sequence of synsets in WordNet hypernym trees as feature vectors that can be used to train a classifier to determine whether a word belongs to a frame or not. The extended dictionary produced by the second method was used in a system for FrameNet-based semantic analysis and gave an improvement in recall. We believe that the methods are useful for bootstrapping FrameNets for new languages.
Sparse multigrid modal estimation: Initial grid selection

Modal retrieval problem can be addressed using sparse estimation techniques coupled with a multigrid approach. Selection of the initial grid, in the multigrid algorithm, is a critical problem that needs satisfactory solutions. In this paper we propose a strategy for selecting a coarse initial grid which guarantees convergence of the algorithm even starting with a single atom in the dictionary. The idea is to define the atoms so as their correlation with the signal modes is greater than a specified threshold. We show through simulations that the proposed solution provides accurate estimations even in presence of noise. Moreover, we investigate the convergence of the multigrid algorithm towards the true parameters.
From first words to grammar in children with focal brain injury

The effects of focal brain injury were investigated in the first stages of language development, during the passage from first words to grammar. Parent report, free‐speech data, or both are reported for 53 infants and preschool children between 10 and 44 months of age. All children had suffered a single, unilateral brain injury to the left or right hemisphere, incurred before 6 months of age (usually in the pre‐ or perinatal period). This is the period in which one would expect to see maximal plasticity, but it is also the period in which the initial specializations of particular cortical regions ought to be most evident. In direct contradiction of hypotheses based on the adult aphasia literature, results from 10 to 17 months suggest that children with right‐hemisphere injuries are at greater risk for delays in word comprehension and in the gestures that normally precede and accompany language onset. Although there were no differences between left‐ and right‐hemisphere injury per se on expressive language.
Differential Responses of Pattern Recognition Receptors to Outer Membrane Vesicles of Three Periodontal Pathogens

Highly purified outer membrane vesicles (OMVs) of the periodontal pathogens, Porphyromonas gingivalis, Treponema denticola and Tannerella forsythia were produced using tangential flow ultrafiltration, ultracentrifugation and Optiprep density gradient separation. Cryo-TEM and light scattering showed OMVs to be single lipid-bilayers with modal diameters of 75 to 158 nm. Enumeration of OMVs by nanoparticle flow-cytometry at the same stage of late exponential culture indicated that P. gingivalis was the most prolific OMV producer. P. gingivalis OMVs induced strong TLR2 and TLR4-specific responses and moderate responses in TLR7, TLR8, TLR9, NOD1 and NOD2 expressing-HEK-Blue cells. Responses to T. forsythia OMVs were less than those of P. gingivalis and T. denticola OMVs induced only weak responses. Compositional analyses of OMVs from the three pathogens demonstrated differences in protein, fatty acids, lipopolysaccharide, peptidoglycan fragments and nucleic acids. Periodontal pathogen OMVs induced differential pattern recognition receptor responses that have implications for their role in chronic periodontitis.
Evaluation of recommendations: rating-prediction and ranking

The literature on recommender systems distinguishes typically between two broad categories of measuring recommendation accuracy: rating prediction, often quantified in terms of the root mean square error (RMSE), and ranking, measured in terms of metrics like precision and recall, among others. In this paper, we examine both approaches in detail, and find that the dominating difference lies instead in the training and test data considered: rating prediction is concerned with only the observed ratings, while ranking typically accounts for all items in the collection, whether the user has rated them or not. Furthermore, we show that predicting observed ratings, while popular in the literature, only solves a (small) part of the rating prediction task for any item in the collection, which is a common real-world problem. The reasons are selection bias in the data, combined with data sparsity. We show that the latter rating-prediction task involves the prediction task 'Who rated What' as a sub-problem, which can be cast as a classification or ranking problem. This suggests that solving the ranking problem is not only valuable by itself, but also for predicting the rating value of any item.
Higher Order Statistical Decorrelation without Information Loss

A neural network learning paradigm based on information theory is proposed as a way to perform in an unsupervised fashion, redundancy reduction among the elements of the output layer without loss of information from the sensory input. The model developed performs nonlinear decorrelation up to higher orders of the cumulant tensors and results in probabilistically independent components of the output layer. This means that we don't need to assume Gaussian distribution neither at the input nor at the output. The theory presented is related to the unsupervised-learning theory of Barlow, which proposes redundancy reduction as the goal of cognition. When nonlinear units are used nonlinear principal component analysis is obtained. In this case nonlinear manifolds can be reduced to minimum dimension manifolds. If such units are used the network performs a generalized principal component analysis in the sense that non-Gaussian distributions can be linearly decorrelated and higher orders of the correlation tensors are also taken into account. The basic structure of the architecture involves a general transformation that is volume conserving and therefore the entropy, yielding a map without loss of information. Minimization of the mutual information among the output neurons eliminates the redundancy between the outputs and results in statistical decorrelation of the extracted features. This is known as factorial learning.
Improving the Fraction Word Problem Solving of Students With Mathematics Learning Disabilities

Students with mathematics learning disabilities (MLD) have a weak understanding of fraction concepts and skills, which are foundations of algebra. Such students might benefit from computer-assisted instruction that utilizes evidence-based instructional components (cognitive strategies, feedback, virtual manipulatives). As a pilot study using a multiple baseline design, with multiple probes, this study investigated the effects of Fun Fraction, a multi-component computer-assisted instructional program, on word problem solving with fractions abilities of three middle school students with MLD. Mixed findings were observed on word problem solving performance from the baseline to intervention phase after students received instruction through Fun Fraction. The percentage of non-overlapping data ranged from 56% through 100%. Limitations, suggestions for future research, and educational implications are discussed.
Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.
Spermatozoon Counts in Males and Inseminated Queens of the Imported Fire Ants, Solenopsis Invicta and Solenopsis Richteri (Hymenoptera: Formicidae)

The Coulter Counter IIA, an automatic particle counter, was a fast, accurate device for counting spermatozoa in fire ants. Queens of Solenopsis invicta, the red imported fire ant (RIFA) had an average 5,669,683 @+ 48,148 spermatozoa in the spermatheca two weeks after mating. RIFA males, ready for a nuptual flight, had an average of 8,761,637 spermatozoa. Males and females of S. richteri, the black imported fire ant, had spermatozoon counts extremely close to those of S. invicta. Spermatozoon counts from field collected physogastric S. invicta queens ranged from 551,594 to 5,634,883. A previous study reported counts (determined by a hemacytometer) of only 377,000 spermatozoa in mated RIFA females. These new figures appear to more accurately reflect the reproductive potential of the fire ant.
Hierarchical Encoding in Visual Working Memory

Influential models of visual working memory treat each item to be stored as an independent unit and assume that there are no interactions between items. However, real-world displays have structure that provides higher-order constraints on the items to be remembered. Even in the case of a display of simple colored circles, observers can compute statistics, such as mean circle size, to obtain an overall summary of the display. We examined the influence of such an ensemble statistic on visual working memory. We report evidence that the remembered size of each individual item in a display is biased toward the mean size of the set of items in the same color and the mean size of all items in the display. This suggests that visual working memory is constructive, encoding displays at multiple levels of abstraction and integrating across these levels, rather than maintaining a veridical representation of each item independently.
The yo-yo intermittent recovery test: physiological response, reliability, and validity.

PURPOSE To examine the physiological response and reproducibility of the Yo-Yo intermittent recovery test and its application to elite soccer. METHODS Heart rate was measured, and metabolites were determined in blood and muscle biopsies obtained before, during, and after the Yo-Yo test in 17 males. Physiological measurements were also performed during a Yo-Yo retest and an exhaustive incremental treadmill test (ITT). Additionally, 37 male elite soccer players performed two to four seasonal tests, and the results were related to physical performance in matches. RESULTS The test-retest CV for the Yo-Yo test was 4.9%. Peak heart rate was similar in ITT and Yo-Yo test (189 +/- 2 vs 187 +/- 2 bpm), whereas peak blood lactate was higher (P < 0.05) in the Yo-Yo test. During the Yo-Yo test, muscle lactate increased eightfold (P < 0.05) and muscle creatine phosphate (CP) and glycogen decreased (P < 0.05) by 51% and 23%, respectively. No significant differences were observed in muscle CP, lactate, pH, or glycogen between 90 and 100% of exhaustion time. During the precompetition period, elite soccer players improved (P < 0.05) Yo-Yo test performance and maximum oxygen uptake ([OV0312]O(2max)) by 25 +/- 6 and 7 +/- 1%, respectively. High-intensity running covered by the players during games was correlated to Yo-Yo test performance (r = 0.71, P < 0.05) but not to [OV0312]O(2max) and ITT performance. CONCLUSION The test had a high reproducibility and sensitivity, allowing for detailed analysis of the physical capacity of athletes in intermittent sports. Specifically, the Yo-Yo intermittent recovery test was a valid measure of fitness performance in soccer. During the test, the aerobic loading approached maximal values, and the anaerobic energy system was highly taxed. Additionally, the study suggests that fatigue during intense intermittent short-term exercise was unrelated to muscle CP, lactate, pH, and glycogen.
Treadmill exercise inhibits hippocampal apoptosis through enhancing N-methyl-D-aspartate receptor expression in the MK-801-induced schizophrenic mice

Schizophrenia is a severe mental disorder characterized by abnormal mental functioning and disruptive behaviors. Abnormal expression of N-methyl-D-aspartate (NMDA) receptor, one of the glutamate receptor subtypes, has also been suggested to contribute to the symptoms of schizophrenia. The effect of treadmill exercise on schizophrenia-induced apoptosis in relation with NMDA receptor has not been evaluated. In the present study, we investigated the effect of treadmill exercise on neuronal apoptosis in the hippocampus using MK-801-induced schizophrenic mice. MK-801 was intraperitoneally injected once a day for 2 weeks. The mice in the exercise groups were forced to run on a treadmill exercise for 60 min, once a day for 2 weeks. In the present results, repeated injection of the NMDA receptor antagonist MK-801 reduced expression of NMDA receptor in hippocampal CA2-3 regions. MK-801 injection increased casapse-3 expression and enhanced cytochrome c release in the hippocampus. The ratio of Bax to Bcl-2 was higher in the MK-801-induced schizophrenia mice than the normal mice. In contrast, treadmill exercise enhanced NMDA receptor expression, suppressed caspae-3 activation and cytochrome c release, and inhibited the ratio of Bax to Bcl-2. Based on present finding, we concluded that NMDA receptor hypofunctioning induced neuronal apoptosis in MK-801-induced schizophrenic mice. Treadmill exercise suppressed neuronal apoptosis through enhancing NMDA receptor expression in schizophrenic mice.