Miracle-dz/UniFAR-FTUs huggingface dataset:
Luma HDRv: an open source high dynamic range video codec optimized by large-scale testing

We present Luma HDRv -- an open source solution for encoding of high dynamic range (HDR) video. The software makes use of techniques for adapting the HDR video for compression with a standard video codec. In the design of the encoder we perform a large-scale test, using 33 HDR video sequences in order to compare 2 video codecs, 4 luminance encoding techniques (transfer functions) and 3 color encoding methods. This serves both as an evaluation of existing techniques for encoding of HDR luminances and colors, as well as to optimize the performance of Luma HDRv.
A Standard Cell-Based Frequency Synthesizer with Dynamic Frequency Counting

This paper presents a standard cell-based frequency synthesizer with dynamic frequency counting (DFC) for multiplying input reference frequency by N times. The dynamic frequency counting loop uses variable time period to estimate and tune the frequency of digitally-controlled oscillator (DCO) which enhances frequency detection's resolution and loop stability. Two ripple counters serve as frequency estimator. Conventional phase-frequency detector (PFD) thus is replaced with a digital arithmetic comparator to yield a divider-free circuit structure. Additionally, a 15 bits DCO with the least significant bit (LSB) resolution 1.55 ps is designed by using the gate capacitance difference of 2-input NOR gate in fine-tuning stage. A modified incremental data weighted averaging (IDWA) circuit is also designed to achieve improved linearity of DCO by dynamic element matching (DEM) skill. Based on the proposed standard cell-based frequency synthesizer, a test chip is designed and verified on 0.35-μm complementary metal oxide silicon (CMOS) process, and has a frequency range of (18--214) MHz at 3.3 V with peak-to-peak (Pk-Pk) jitter of less than 70 ps at 192 MHz/3.3 V.
Planned Behavior versus Goal-directed Automaticity - The Impact of Attitude and General Habit on Adoption and Non-adoption

"Planned behavior" is a widely-known paradigm used to predict individual behavior. Basing on a competing paradigm called “goal-directed automaticity”, research addressed the mutual support of both paradigms – thus the importance of habits for the continued usage. A versus between both paradigms – thus the inhibiting effect of habits on the adoption of a new system was thematized in 2012 by Polites and Karahanna. Within this research, both concepts are brought face to face by examining the results of an empirical survey of 378 County employees who were separated into adopter and non-adopter groups. Given this opposing behavioral outcome, the moderating effect of habit on the relationship between affect/cognition and intention was examined by means of a group-based regression approach. The results show opposing patterns for both groups which holds the implication that the directional impact of habit strength on this relationship is likewise opposing.
The Arabidopsis Paf 1 c Complex Component CDC 73 Participates in the Modification of FLOWERING LOCUS C Chromatin 1 [ C ] [ W ] [ OA ]

FLOWERING LOCUS C (FLC) is a key repressor of flowering in Arabidopsis (Arabidopsis thaliana) and is regulated, both positively and negatively, by posttranslational histone modifications. For example, vernalization (the promotion of flowering by cold temperatures) epigenetically silences FLC expression through repressive histone modifications such as histone H3 lysine-9 dimethylation (H3K9me2) and H3K27me3. In contrast, an RNA polymerase II-associated complex (Paf1c) activates FLC expression through increased H3K4 and H3K36 methylation. As a result of this regulation, FLC has become a useful model for the study of chromatin structure in Arabidopsis. Here we show that At3g22590 is the Arabidopsis homolog of the yeast (Saccharomyces cerevisiae) Paf1c component CDC73 and is enriched at FLC chromatin. In contrast to other Paf1c component mutants that exhibit pleiotropic developmental phenotypes, the effects of cdc73 mutations are primarily limited to flowering time, suggesting that CDC73 may only be required for Paf1c function at a subset of target genes. In rapid-cycling strains, cdc73 mutants showed reduced FLC mRNA levels and decreased H3K4me3 at the FLC locus. Interestingly, in late-flowering autonomous-pathway mutants, which contain higher levels of FLC, cdc73 mutations only suppressed FLC in a subset of mutants. H3K4me3 was uniformly reduced in all autonomous-pathway cdc73 double mutants tested; however, those showing reduced FLC expression also showed an increase in H3K27me3. Thus, CDC73 is required for high levels of FLC expression in a subset of autonomous-pathway-mutant backgrounds and functions both to promote activating histone modifications (H3K4me3) as well as preventing repressive ones (e.g. H3K27me3).
Prenatal Exposure to Stress and Stress Hormones Influences Child Development

Stress has significant consequences throughout the lifetime. However, when it occurs early in life, the implications may be particularly profound and long lasting. Evidence suggests that high levels of maternal stress during pregnancy are associated with alterations in the normal activity of the maternal hypothlalamic-pituitary-adrenocortical (HPA) and placental axis. Increased activity of this system is related to shortened gestation and impaired fetal growth, factors that place infants at a greater risk for a wide variety of developmental problems. In addition to the implications for birth outcome, our findings suggest that prenatal exposure to stress and stress hormones directly influences development of the fetal central nervous system (CNS). Fetuses who are exposed to disregulated production of stress hormones display impaired learning. Elevated levels of stress or stress hormones during pregnancy are also associated with more difficult infant temperament and disruption of infant HPA axis activity. These data suggest that prenatal experiences can have lasting implications for development.
Iterative quadratic relaxation method for optimization of multiple radar waveforms

MIMO radars use multiple waveforms in order to resolve more targets and achieve gains in target detection, parameter estimation and recognition, for example. In this paper, we propose a method for optimizing multiple waveforms with low peak sidelobe and peak cross-correlation levels for MIMO radar. The optimization method relaxes the original quartic problem into a quadratic one and iterates the relaxed problem to improve the solution. The numerical examples demonstrate that good waveforms are obtained with the proposed method.
Pyridoxine (Vitamin B6) and the Glutathione Peroxidase System; a Link between One-Carbon Metabolism and Antioxidation

Vitamin B6 (B6) has a central role in the metabolism of amino acids, which includes important interactions with endogenous redox reactions through its effects on the glutathione peroxidase (GPX) system. In fact, B6-dependent enzymes catalyse most reactions of the transsulfuration pathway, driving homocysteine to cysteine and further into GPX proteins. Considering that mammals metabolize sulfur- and seleno-amino acids similarly, B6 plays an important role in the fate of sulfur-homocysteine and its seleno counterpart between transsulfuration and one-carbon metabolism, especially under oxidative stress conditions. This is particularly important in reproduction because ovarian metabolism may generate an excess of reactive oxygen species (ROS) during the peri-estrus period, which may impair ovulatory functions and early embryo development. Later in gestation, placentation raises embryo oxygen tension and may induce a higher expression of ROS markers and eventually embryo losses. Interestingly, the metabolic accumulation of ROS up-regulates the flow of one-carbon units to transsulfuration and down-regulates remethylation. However, in embryos, the transsulfuration pathway is not functional, making the understanding of the interplay between these two pathways particularly crucial. In this review, the importance of the maternal metabolic status of B6 for the flow of one-carbon units towards both maternal and embryonic GPX systems is discussed. Additionally, B6 effects on GPX activity and gene expression in dams, as well as embryo development, are presented in a pig model under different oxidative stress conditions.
CULTURAL INTEGRATION IN EUROPE: THE ITALIAN CONTEXT

We explore economic and cultural integration patterns for different immigrant groups in Italy, from first to second generations and across age cohorts. We produce descriptive statistics regarding the differences of immigrants with respect to natives in terms of education, employment, female participation rates, marriage, divorce, exogamous marriage rates, and completed fertility rates. Our analysis does not show evidence of slow integration patterns for immigrants into Italy, though inter-marriage rates between immigrants and natives are very low. This is consistent with the high values we obtain for a synthetic index of integration we computed. Severe data limitations however suggest caution in the interpretation of these results. *New York University and IZA, alberto.bisin@nyu.edu **La Sapienza University of Rome, IZA and EIEF, eleonora.patacchini@uniroma1.it
Atomistic modeling of pure Li and Mg–Li system

Interatomic potentials for pure Li and the Mg–Li binary system have been developed based on the second nearest-neighbor modified embedded-atom method formalism. The potentials can describe various fundamental physical properties of pure Li (bulk, point defect, planar defect and thermal properties) and alloy behaviors (thermodynamic, structural and elastic properties) in reasonable agreement with experimental data or higher-level calculations. The applicability of the potential to atomistic investigations on the deformation behavior of Mg alloys and the effect of Li is demonstrated.
FLAG : Fast Large-Scale Graph Construction for NLP

Many natural language processing (NLP) problems involve constructing large nearest-neighbor graphs between word pairs by computing distributional similarity between word pairs from large corpora. In this paper, first we describe a system called FLAG to construct such graphs approximately from large data sets. To handle the large amount of data in memory and time efficient manner, FLAG maintains approximate counts based on sketching algorithms using commodity clusters. To find the approximate nearest neighbors quickly, FLAG exploits fast approximate nearest neighbor search algorithms. Second, we describe an extension of system FLAG that models for inferring context sensitive meaning of words. We propose an approximate Clustering by Committee (CBC) algorithm to induce hard clusters of words. These hard clusters are mapped to words in context to infer their context sensitive meaning.
Can You Feel It Will You Tell Me. Encouraging Sentiment Expression on the Web

In a recent trend in web communication, news outlets and blog platforms allow readers to express opinions about what they have read by choosing an associated feeling, or sentiment expression. This emerging trend, fitting between liking and full text comments, has not still found the popularity it should. The thesis of this paper is that this is also due to the way the sentiment choice is presented to the user. In order to test this hypothesis we have devised a pilot experiment; results confirm that a simpler way of choice increases sentiment expression and yields result that are more aligned with ground truth.
Recovering 3D human body configurations using shape contexts

The problem we consider in this paper is to take a single two-dimensional image containing a human figure, locate the joint positions, and use these to estimate the body configuration and pose in three-dimensional space. The basic approach is to store a number of exemplar 2D views of the human body in a variety of different configurations and viewpoints with respect to the camera. On each of these stored views, the locations of the body joints (left elbow, right knee, etc.) are manually marked and labeled for future use. The input image is then matched to each stored view, using the technique of shape context matching in conjunction with a kinematic chain-based deformation model. Assuming that there is a stored view sufficiently similar in configuration and pose, the correspondence process would succeed. The locations of the body joints are then transferred from the exemplar view to the test shape. Given the 2D joint locations, the 3D body configuration and pose are then estimated using an existing algorithm. We can apply this technique to video by treating each frame independently - tracking just becomes repeated recognition. We present results on a variety of data sets
Correlation between the green‐island phenotype and Wolbachia infections during the evolutionary diversification of Gracillariidae leaf‐mining moths

Abstract Internally feeding herbivorous insects such as leaf miners have developed the ability to manipulate the physiology of their host plants in a way to best meet their metabolic needs and compensate for variation in food nutritional composition. For instance, some leaf miners can induce green‐islands on yellow leaves in autumn, which are characterized by photosynthetically active green patches in otherwise senescing leaves. It has been shown that endosymbionts, and most likely bacteria of the genus Wolbachia, play an important role in green‐island induction in the apple leaf‐mining moth Phyllonorycter blancardella. However, it is currently not known how widespread is this moth‐Wolbachia‐plant interaction. Here, we studied the co‐occurrence between Wolbachia and the green‐island phenotype in 133 moth specimens belonging to 74 species of Lepidoptera including 60 Gracillariidae leaf miners. Using a combination of molecular phylogenies and ecological data (occurrence of green‐islands), we show that the acquisitions of the green‐island phenotype and Wolbachia infections have been associated through the evolutionary diversification of Gracillariidae. We also found intraspecific variability in both green‐island formation and Wolbachia infection, with some species being able to form green‐islands without being infected by Wolbachia. In addition, Wolbachia variants belonging to both A and B supergroups were found to be associated with green‐island phenotype suggesting several independent origins of green‐island induction. This study opens new prospects and raises new questions about the ecology and evolution of the tripartite association between Wolbachia, leaf miners, and their host plants.
A Microfluidic-Assisted Fabrication of Size-Controlled Porose CeO2 Microspheres as an Analog Production of Nuclear Fuel Beads

Porosity-controlled nuclear fuel microsphere is an essential material of fabricating minor actinide-bearing dispersion-type nuclear fuel with the infiltration processes. In this paper, monodisperse and size-controlled spherical oxide nuclear fuel particles with size range of 20μm to 800μm were fabricated by means of microfluidic technology combined with sol-gel process using cerium as a surrogate for plutonium. The porous CeO2 beads with the density range of 25% to 93% T.D. were successfully prepared by the addition of polyethylene glycol 6000 used as a porogen to the feed broth. The uniform U3O8 beads were also prepared at the same experimental conditions as CeO2 beads prepared, which shows the feasibility of the method for fabricating size-controlled monodisperse nuclear fuel beads.
A New Perspective on Gaussian Dynamic Term Structure Models

In any canonical Gaussian dynamic term structure model (GDTSM), the conditional forecasts of the pricing factors are invariant to the imposition of no-arbitrage restrictions. This invariance is maintained even in the presence of a variety of restrictions on the factor structure of bond yields. To establish these results, we develop a novel canonical GDTSM in which the pricing factors are observable portfolios of yields. For our normalization, standard maximum likelihood algorithms converge to the global optimum almost instantaneously. We present empirical estimates and out-of-sample forecasts for several GDTSMs using data on U.S. Treasury bond yields. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com. , Oxford University Press.
Affective Video Retrieval: Violence Detection in Hollywood Movies by Large-Scale Segmental Feature Extraction

Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology “out of the lab” to real-world, diverse data. In this contribution, we address the problem of finding “disturbing” scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to . 398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.
Leverage Constraints and Asset Prices: Insights from Mutual Fund Risk Taking

Prior theory suggests that time variation in the degree to which leverage constraints bind affects the pricing kernel. We propose a measure for this leverage constraint tightness by inverting the argument that constrained investors tilt their portfolios to riskier assets. We show that the average market beta of actively managed mutual funds—intermediaries facing leverage restrictions—captures their desire for leverage and thus the tightness of constraints. Consistent with theory, it strongly predicts returns of the betting-against-beta portfolio, and is a priced risk factor in the cross-section of mutual funds and stocks. Funds with low exposure to the factor outperform high-exposure funds by 5% annually, and for stocks this difference reaches 7%. Our results show that the tightness of leverage constraints has important implications for asset prices.
Defective function of GABA-containing synaptic vesicles in mice lacking the AP-3B clathrin adaptor

AP-3 is a member of the adaptor protein (AP) complex family that regulates the vesicular transport of cargo proteins in the secretory and endocytic pathways. There are two isoforms of AP-3: the ubiquitously expressed AP-3A and the neuron-specific AP-3B. Although the physiological role of AP-3A has recently been elucidated, that of AP-3B remains unsolved. To address this question, we generated mice lacking μ3B, a subunit of AP-3B. μ3B−/− mice suffered from spontaneous epileptic seizures. Morphological abnormalities were observed at synapses in these mice. Biochemical studies demonstrated the impairment of γ-aminobutyric acid (GABA) release because of, at least in part, the reduction of vesicular GABA transporter in μ3B−/− mice. This facilitated the induction of long-term potentiation in the hippocampus and the abnormal propagation of neuronal excitability via the temporoammonic pathway. Thus, AP-3B plays a critical role in the normal formation and function of a subset of synaptic vesicles. This work adds a new aspect to the pathogenesis of epilepsy.
SPDO: High-throughput road distance computations on Spark using Distance Oracles

In the past decades, shortest distance methods for road networks have been developed that focus on how to speed up the latency of a single source-target pair distance query. Large analytical applications on road networks including simulations (e.g., evacuation planning), logistics, and transportation planning require methods that provide high throughput (i.e., distance computations per second) and the ability to “scale out” by using large distributed computing clusters. A framework called SPDO is presented which implements an extremely fast distributed algorithm for computing road network distance queries on Apache Spark. The approach extends our previous work of developing the ε-distance oracle which has now been adapted to use Spark's resilient distributed dataset (RDD). Compared with state-of-the-art methods that focus on reducing latency, the proposed framework improves the throughput by at least an order of magnitude, which makes the approach suitable for applications that need to compute thousands to millions of network distances per second.
NeXO Web: the NeXO ontology database and visualization platform

The Network-extracted Ontology (NeXO) is a gene ontology inferred directly from large-scale molecular networks. While most ontologies are constructed through manual expert curation, NeXO uses a principled computational approach which integrates evidence from hundreds of thousands of individual gene and protein interactions to construct a global hierarchy of cellular components and processes. Here, we describe the development of the NeXO Web platform (http://www.nexontology.org)—an online database and graphical user interface for visualizing, browsing and performing term enrichment analysis using NeXO and the gene ontology. The platform applies state-of-the-art web technology and visualization techniques to provide an intuitive framework for investigating biological machinery captured by both data-driven and manually curated ontologies.
Pseudo-random number generation in children with high-functioning autism and Asperger’s disorder

The repetitive, stereotyped and obsessive behaviours, which are core diagnostic features of autism, are thought to be underpinned by executive dysfunction. This study examined executive impairment in individuals with autism and Asperger’s disorder using a verbal equivalent of an established pseudo-random number generating task. Different patterns of disinhibition emerged in the autism (n = 12) and Asperger’s disorder (n = 12) groups. Consistent with previous research, the autism group repeated single numbers (e.g. 2, 2, 2) more frequently than the control group. In contrast to past research suggesting intact executive abilities, this study found that the Asperger’s disorder group generated more repetitive number patterns (e.g. 45, 45) than the controls. Executive functioning in children with Asperger’s disorder may be particularly vulnerable to a lack of visual cueing and concrete rules. Qualitative differences in executive dysfunction between these groups may implicate differential disruption within the fronto-striatal circuitry.