Miracle-dz/UniFAR-FTUs huggingface dataset:
When Mona Lisa smiled and love was in the air: On the cognitive energetics of motivated judgments

We describe two experiments on the determinants of motivated judgments. They explored the conjoint effects of three factors: (1) dominant judgmental motivation (geared toward accuracy or directional bias), (2) task demands, and (3) the availability of cognitive resources. We find that where a directional motivation is dominant and task demands are high (making biasing difficult), the presence (vs. absence) of resources promotes wishful judgments. Conversely, where accuracy motivation is dominant and wishful judgments are the default, resources reduce the likelihood of their occurrence. Finally, where a directional motivation is dominant and task demands are low (making biasing easy), or where the accuracy motivation is dominant and task demands are high, resources have relatively minor effects on bias.
Nucleotide diversity of Hemigrammus cf. marginatus (Characiformes, Characidae) in the upper Paraná river floodplain

Characidae is the largest and more diversified family from Characiformes and presents several classification problems, with several genera currently allocated as incertae sedis, such as the genus Hemigrammus. The upper Parana river floodplain is an environment with high fish diversity. There is at least one species of Hemigrammus, however there are divergences among some authors about the number and the identification of the species from this genus. Therefore the goal of this study was to characterize, using a molecular approach, individuals of Hemigrammus from the upper Parana river floodplain and to compare them with individuals from the type locality of Hemigrammus marginatus, since this is the only species distributed in this floodplain. For this, the DNA was extracted and a partial region from the mitochondrial genes ATPase 6 and ATPase 8 were amplified and sequenced. The results evidenced the existence of two species of Hemigrammus in the floodplain, although impossible to be distinguished only through morphological traits. High nucleotide diversity among individuals from the upper Parana river in relation to those from the type locality was also observed, indicating that both species of Hemigrammus present in the upper Parana river floodplain are not Hemigrammus marginatus.
The formation of rings and gaps in magnetically coupled disc-wind systems: ambipolar diffusion and reconnection

Radial substructures in circumstellar disks are now routinely observed by ALMA. There is also growing observational evidence that such disks can accrete through angular momentum removal by rotating disk winds. We show through idealized 2D (axisymmetric) simulations that rings and gaps develop naturally in magnetically coupled disk-wind systems on the scale of tens of au, where ambipolar diffusion (AD) is the dominant non-ideal MHD effect. In simulations where the magnetic field and bulk neutral matter are only moderately coupled, relatively laminar disk accretion occurs while the spatial distribution of radial electric current is steepened by AD into a thin layer near the midplane. The toroidal magnetic field sharply reverses polarity in this current layer, generating a large magnetic torque that drives fast accretion and drags the poloidal magnetic field into an elongated radial configuration. The reconnection of this radial field creates magnetic loops where the net poloidal magnetic flux is greatly reduced. The regions with reduced poloidal magnetic flux accrete more slowly creating dense rings and the neighboring regions where the magnetic flux is concentrated accrete faster and form gaps. In better magnetically coupled simulations, we find the continuous development of the so-called `avalanche accretion streams' near the disk surface that render the disk-wind system more chaotic. Nevertheless, prominent rings and gaps are still present. We suggest that they are also produced, at least in part, by reconnection, which again enables the segregation of the poloidal field and the disk material similar to the more diffusive disks. However, the reconnection is now driven by the non-linear growth of MRI channel flows. The formation of rings and gaps in rapidly accreting yet laminar disks has interesting implications for dust settling and trapping, grain growth, and planet formation.
Asymptotically Unbiased Estimator of the Informational Energy with kNN

Motivated by machine learning applications (e.g., classification, function approximation, feature extraction), in previous work, we have introduced a nonparametric estimator of Onicescu’s informational energy. Our method was based on the k-th nearest neighbor distances between the n sample points, where k is a fixed positive integer. In the present contribution, we discuss mathematical properties of this estimator. We show that our estimator is asymptotically unbiased and consistent. We provide further experimental results which illustrate the convergence of the estimator for standard distributions.
Analyze EEG Signals with Convolutional Neural Network Based on Power Spectrum Feature Selection

Brain Computer Interface refers to the establishment of direct communication and control channels between human brain and computer. The essential part of the BCI system is the feature extraction and classification. In this paper, we proposed an improveed architecture based on power spectrum and CNN. Furthermore, two methods of power spectrum feature extraction are discussed. The research result shows that this system can effectively identify the left-right brain signals and have higher classification accuracy with it reaching 82%
Capturing fast motion with consumer grade unsynchronized rolling-shutter cameras

Motion capture plays an important role in a wide range of fields including film production, game industry, sports analysis and medicine. However, commercial optical motion capture systems are expensive due to their reliance on high speed high resolution cameras and accurate shutter synchronization. In the thesis, we present a technique based on continuous video exposure and stereo streak matching to do motion capture with a low cost, simple, portable and scalable setup of consumer grade cameras and LED markers. Neither shutter synchronization nor global shutters are required for geometric calibration and motion reconstruction. The system is presented in four stages, camera calibration and synchronization, streak segmentation and 2-D track extraction, stereo track matching and multi-view fusing. The system is qualitatively demonstrated through capturing human motion and fan spinning motion, and quantitatively evaluated by motions with known spatial trajectory and the rigidity of rigid moving objects.
Breast movement asymmetry during running: implications for breast support

This study aimed to investigate 1) the prevalence and magnitude of breast movement asymmetry, 2) the interaction between static and dynamic breast asymmetry during running and 3) the influence of sports bras on breast asymmetry. Nipple position data were collected from 167 female participants whilst treadmill running and then from a subgroup of twelve participants running in different bra conditions. Breast movement asymmetry was present in 74% of participant during running, with greater resultant static breast position asymmetry for participants that displayed asymmetry whilst running. Asymmetry was most commonly caused (65 80%) by greater movement of the left than right breast. Sports bras reduced asymmetry prevalence to as few as 17% of participants in the antero-posterior direction but only 58% in the infero-superior direction.
SNPs2ChIP: Latent Factors of ChIP-seq to infer functions of non-coding SNPs

Genetic variations of the human genome are linked to many disease phenotypes. While whole-genome sequencing and genome-wide association studies (GWAS) have uncovered a number of genotype-phenotype associations, their functional interpretation remains challenging given most single nucleotide polymorphisms (SNPs) fall into the non-coding region of the genome. Advances in chromatin immunoprecipitation sequencing (ChIP-seq) have made large-scale repositories of epigenetic data available, allowing investigation of coordinated mechanisms of epigenetic markers and transcriptional regulation and their influence on biological function. To address this, we propose SNPs2ChIP, a method to infer biological functions of non-coding variants through unsupervised statistical learning methods applied to publicly-available epigenetic datasets. We systematically characterized latent factors by applying singular value decomposition to ChIP-seq tracks of lymphoblastoid cell lines, and annotated the biological function of each latent factor using the genomic region enrichment analysis tool. Using these annotated latent factors as reference, we developed SNPs2ChIP, a pipeline that takes genomic region(s) as an input, identifies the relevant latent factors with quantitative scores, and returns them along with their inferred functions. As a case study, we focused on systemic lupus erythematosus and demonstrated our method’s ability to infer relevant biological function. We systematically applied SNPs2ChIP on publicly available datasets, including known GWAS associations from the GWAS catalogue and ChIP-seq peaks from a previously published study. Our approach to leverage latent patterns across genome-wide epigenetic datasets to infer the biological function will advance understanding of the genetics of human diseases by accelerating the interpretation of non-coding genomes.
Source of Economic Growth in Ethiopia: An Application of Vector Error Correction Model

The primary objective of this research is to examine the recent impressive economic growth of Ethiopia and to evaluate the major determinates of gross domestic product (GDP) growth. While emphasizing on the role of investment (grow fixed capital formation), human capital (employment and labor productivity growth), and trade openness (export and import) using time series data that covered from 1981 to 2014. The data analysis was performed through econometric testing with augmented Dickey-Fuller test to check the stability of time series data. Johansen co-integration test is employed to check whether GDP has empirically meaningful relationships with other variables or not? Our empirical findings reject the null hypothesis of no co-integration and accept the co-integration relationship in our model. The vector error correction model and Granger causality test identify long-run equilibrium and short-run causality in GDP growth. The result of this research shows that GDP growth has a long-run relationship with independent variables and short-run causality from export, import, and employment but grow fixed capital formation and labor productivity growth have no impact on GDP growth in short run. Aus. Aca. Busi & Eco. Rev Vol 2(4), October 2016, P 285-292
Numerical modelling of transient flows with high sediment concentrations

The main purpose of the present paper is to describe and discuss the development, validation and application of a numerical model designed to handle transient flows with high sediment transport rates. The model considers nonequilibrium transport (i.e. accounting for loading / unloading delay) and is numerically as well as physically totally coupled. The closure relations needed to evaluate the exchange fluxes between the fixed bottom and the flowing mixture (erosion and deposition rates) are also detailed in the paper. Finally, the model is validated against experimental data collected in the framework of the European project IMPACT.
Short Communication Effect of selenium-vitamin E injections of ewes on reproduction and growth of their lambs

The experiment was conducted on 90 Karacabey Merino ewes divided into three groups. The first group of ewes was treated with 5 mL 0.1% sodium selenate, the second with 5 mL 0.1% sodium selenate and 250 mg vitamin E, while the third one was a control group. The effect of intra-muscular injection of selenium (Se) and Se plus vitamin E on oestrus, fertility, prolificacy, number of lambs reared the weight of lambs at birth and the live weight gain for 60 days was investigated. The injections of Se plus vitamin E significantly increased the incidence of oestrus, fertility and prolificacy in ewes, lamb body weight at day 60 and daily weight gain of ewes for 60 days postpartum compared with the control group. Keywords : keyword; keyword; keyword South African Journal of Animal Science Vol. 37 (4) 2007: pp.233-236
Very low surface recombination velocities on p- and n-type c-Si by ultrafast spatial atomic layer deposition of aluminum oxide

Using aluminum oxide (Al2 O3) films deposited by high-rate spatial atomic layer deposition (ALD), we achieve very low surface recombination velocities of 6.5 cm/s on p -type and 8.1 cm/s on n -type crystalline silicon wafers. Using spatially separated reaction zones instead of the conventional time-sequenced precursor dosing enables growth rates up to 70 nm/min, whereas conventional ALD limits the growth rate to <2 nm/min. The excellent passivation level is predominantly assigned to a high negative fixed charge density of Qf =- (4±1) × 1012 cm-2 in the Al2 O3 films. We demonstrate an excellent thermal stability of the passivation quality. © 2010 American Institute of Physics.
Accuracy of genomic values predicted using deregressed predicted breeding values as response variables

Highly accurate predicted genetic values must be obtained at an early age to promote rapid genetic progress. The objectives of this study were to compare accuracies (R 2 ) of genomic values (GVs) and to estimate genetic correlation between true genetic values and genomic values obtained using predicted breeding values (EBV) and deregressed EBV (DEBV) as response variables. A first population, effective population size 800 and 100 generations, was simulated using the QMSim program to generate linkage disequilibrium. Thereafter, 20 males and 200 females were used to generate a second 14-generation population, with 6,400 individuals per generation and its corresponding phenotype and genotype in SNP terms. Generations 7 to 14 of the second population were used in several combinations as training (PEn) and evaluation (PEv) subpopulations. GVs, their accuracies, and genetic correlations were obtained using the GenSel and ASREML programs. When PEn was the largest, the mean R 2 of GV was the highest, 0.77 ± 0.01 . The closer PEn was to PEv, the higher the R 2 , and correspondingly, the lower the predicted error variance. The trends for R 2 and PEV held true for both EBV and DEBV used as response variables. Genetic correlation estimates between true genetic values and GVs varied from 0.41 to 0.53 in the two scenarios studied. They decreased when PEn and PEv were farther apart. There were only slight advantages of using DEBVs as response variables over using EBVs.
Learning efference in CNNs for perception-based navigation control

Action-oriented perception involves complex tasks to be fulfilled in real time. In fact living beings, even the most simple, suitably integrate afferent stimuli, create an abstract, concise representation of environment stimuli and choose it for action-selection purposes. We propose a novel infrastructure, based on CNNs, where the spatial-temporal solutions are linked to the results of the perception stage. In this perspective, a primary role is devoted to the introduction of plasticity to enhance the association stimuli-CNN dynamics-action selection with application to the task of autonomous navigation control.
Learning, Macroeconomic Dynamics and the Term Structure of Interest Rates

We present a macroeconomic model in which agents learn about the central bank’s inflation target and the output-neutral real interest rate. We use this framework to explain the joint dynamics of the macroeconomy, and the term structures of interest rates and inflation expectations. Introducing learning in the macro model generates endogenous stochastic endpoints which act as level factors for the yield curve. These endpoints are sufficiently volatile to account for most of the variation in long-term yields and inflation expectations. As such, this paper complements the current macro-finance literature in explaining long-term movements in the term structure without reference to additional latent factors.
Robot Assisted Needle Placement : Developed Using Image Guided Surgery Toolkit ( IGSTK ) Release 1 . 00

Robotic systems for positioning needles or needle-shaped tools have the potential in increasing accuracy and speed of clinical procedures such as biopsy, radio frequency ablation, and target drug delivery. These systems can also minimize patient trauma. This paper describes a robot assisted needle placement system developed using the Image Guided Surgery Toolkit (IGSTK). IGSTK is an open source software toolkit that provides a robust and safe platform for researchers and clinicians to prototype image guided applications quickly and efficiently.
Mollusk Species Richness on the Rocky Shores of the State of Guerrero, Mexico, as Affected by Rains and Their Geographical Distribution

Natural processes in ecosystems shows significant variations in species richness with regular cycles that can be altered by natural or anthropogenic activities; the present research was in order to understand on some of these variations. The objectives were: 1) determine the species richness of rocky intertidal mollusks; 2) track their geographical distribution at State level; and 3) determine the changes in species richness as a result of rainfall on an annual cycle. For these purposes it was sampled in March, June, September and December 2005, the sampled area was 20 m2for each collecting site; the sampling unit was a PVC rectangle frame one by two meter per side. The mollusks found within the sampling units were collected, identified and counted. The species distribution was analyzed by sites and regions, considered species richness per season, and the distributional patterns by rainy season historical records. A total of 62 mollusks species were found, its richness associated with substrate stability and wave intensity on each site, Gastropods had the highest species richness. When analyzing the regional distribution and sites, it was found a pattern of species richness roughly constant in the proportion of species with wide distribution (generalists) versus those of restricted spatial representation (specialists). Gastropods had the highest number of species with restricted spatial representation. Seasonal rainfall differences did not quantitatively altered on the overall the species of mollusks in the rocky intertidal sampled zone however, in the analysis per Class, Gastropoda indicated changes in species richness influenced by rainfall, which were not observed in Bivalvia and Polyplacophora, suggesting that those changes might depend on adaptive processes or the lack of adaptation of gastropod species to the characteristics of the rocky intertidal habitat.
Phylogeography and population genetics of the Australian small carpenter bee, Ceratina australensis

The Australian small carpenter bee, Ceratina australensis, is the sole member of the small carpenter bees, genus Ceratina, in Australia. Ceratina australensis is found throughout eastern Australia in dead, broken stems of weedy plant species, where it makes its nests. Here we developed eight microsatellite loci and used these markers to characterize the genetic structure of three populations across three distinct ecoregions that are connected by the Murray– Darling River basin. We genotyped 57 female bees and found significant and geographically consistent variation in allelic diversity and heterozygosity between populations. Through comparisons with the results of mitochondrial DNA screening from a previous study, we infer the possibilities of male-biased dispersal and limited interpopulation migration. Based on available distribution data, the expansion of C. australensis into arid regions appears to follow the Murray–Darling River basin and associated waterways. This basin has undergone severe anthropogenic disturbance since European settlement of Australia, with large-scale changes to native vegetation communities. Although it is unknown how these changes have affected local insect communities, C. australensis does not rely on a single plant species for nesting habitat. We provide evidence for the hypothesis that expansion of C. australensis into Australia might have been aided by the introduction of non-native pithy stemmed plants.
Comparison of anthropometric measurements and body composition among the 12 years old rural and urban children

The purpose of the present study was to compare the anthropometric measurements and body composition components of the 12 years old rural and urban children from Punjab. Total 60 children (30 rural and 30 urban) were selected to participate in the study. Height of the subjects was measured with the stadiometer. Body mass was assessed by using the portable weighing machine. Widths and diameters of body parts were measured by using digital caliper. Girths and lengths were taken with the flexible steel tape. Skinfold thicknesses were measured with the help of Harpenden skinfold caliper. The results revealed that the urban children had significantly higher body mass index (BMI) ( p <0.05), % body fat ( p <0.01), total body fat ( p <0.05), biceps ( p <0.05), triceps ( p <0.01) and supra-iliac ( p <0.05) skinfold thicknesses as compared to rural children. The rural children had significantly greater upper arm length ( p <0.01) than the urban children. In conclusion, it is evident from the results that the urban children possessed higher amount of fat.
Learning to Specialize with Knowledge Distillation for Visual Question Answering

Visual Question Answering (VQA) is a notoriously challenging problem because it involves various heterogeneous tasks defined by questions within a unified framework. Learning specialized models for individual types of tasks is intuitively attracting but surprisingly difficult; it is not straightforward to outperform naive independent ensemble approach. We present a principled algorithm to learn specialized models with knowledge distillation under a multiple choice learning (MCL) framework, where training examples are assigned dynamically to a subset of models for updating network parameters. The assigned and non-assigned models are learned to predict ground-truth answers and imitate their own base models before specialization, respectively. Our approach alleviates the limitation of data deficiency in existing MCL frameworks, and allows each model to learn its own specialized expertise without forgetting general knowledge. The proposed framework is model-agnostic and applicable to any tasks other than VQA, e.g., image classification with a large number of labels but few per-class examples, which is known to be difficult under existing MCL schemes. Our experimental results indeed demonstrate that our method outperforms other baselines for VQA and image classification.