Miracle-dz/UniFAR-FTUs huggingface dataset:
BLACK HOLE MASSES OF INTERMEDIATE-REDSHIFT QUASARS: NEAR-INFRARED SPECTROSCOPY

We present near-infrared spectra of 10 luminous, intermediate-redshift quasars (z ≃2; Lbol ≃ 1047 erg s−1), observed with SofI at the NTT of ESO/La Silla. With these rest-frame optical spectra we probe the Hβ–[O iii] emission line region. Using the standard scaling relation involving the width of the Hβ line and the continuum luminosity, we measure black hole (BH) masses in the range of ∼2 × 109≲ Mbh ≲ 1010 M☉ for these sources. We also used Sloan Digital Sky Survey spectra to probe Mg ii λ2798 and C iv λ1549 emission lines and used these for BH mass measurements as well. The BH mass estimates using C iv λ1549 are on average smaller by about 60% than those based on Hβ. The massive BHs we observe could not have grown by simple radiatively efficient accretion at the observed accretion rate starting from seeds of up to a thousand solar masses. About 10% of the observed BH mass must have been accumulated by earlier merger events and radiatively inefficient accretion. Radiatively efficient accretion would further grow these BHs to masses of several 109M☉ in 2–3 e-folding times, i.e., in several 108 yr. This scenario is consistent with recent models of BH growth. The Hβ-based Eddington luminosity ratios are in the range of ∼0.2–0.7, with an average of 〈Lbol/Ledd〉 = 0.39 ± 0.05. The Lbol/Ledd ratio distribution follows a lognormal distribution which is consistent with prior studies of quasars with comparable luminosity. We also find that the gas metallicity of the broad-line region is super-solar with ∼3 Z/Z☉, based on N iii]λ1750/O iii]λ1663 and N v λ1240/C iv λ1549 emission line ratios. We find no correlation of the gas metallicity with the optical Fe ii emission line strength in our small sample, contrary to a recent suggestion.
Multi-object tracking method based on super-pixel and energy minimization

Video target tracking research is a hot topic in the field of computer vision. It has broad prospects in many fields such as video surveillance, virtual reality, interactive and automatic navigation. For multi-object tracking in video sequences, we propose a method based on super pixel and energy minimization. First we achieve target detection by super-pixel labeling with minimized energy function, and we capture the target's appearance with data cost model, which can be trained by support vector machine (SVM). Next we can track object based on continuous energy minimization method. The recall ratio of this method can be 99.8% at high overlap rate, e.g., 0.9, and yields improvement by 70%. Experimental results show that the method has advantages over other methods in complex environment with similar color background and targets, and improves the accuracy of multiple target tracking.
Teaching Students with Dyslexia and Dysgraphia: Lessons from Teaching and Science.

This resource for education professionals provides key information on dyslexia and dysgraphia, as well as practical recommendations for using research in the classroom.This book provides an overview of what recent research has added to our understanding of dyslexia and dysgraphia within the historical context of contributions from practice over the last century. The authors provide educators and therapists with research supported, practical instructional guidelines and methods for improving the oral language, reading, and writing of students with dyslexia and dysgraphia. The book blends science-supported conceptual frameworks with practical teaching strategies. It addresses identification of written language disabilities, interventions, specific topics such as reading and writing, and professional development.The message that the book communicates goes beyond learning from teaching and learning from research to taking a stand that both kinds of experience contribute to evidence-based practice. This has become very important to teachers as they're instructed to incorporate more and more research into their practices while trying to figure out how to proceed with methods that they know work from their experience.
Phosphofructokinase type 1 kinetics, isoform expression, and gene polymorphisms in cancer cells

Kinetic analysis of PFK‐1 from rodent AS‐30D, and human HeLa and MCF‐7 carcinomas revealed sigmoidal [fructose 6‐phosphate, Fru6P]‐rate curves with different Vm values when varying the allosteric activator fructose 2,6 bisphosphate (Fru2,6BP), AMP, Pi, NH 4+ , or K+. The rate equation that accurately predicted this behavior was the exclusive ligand binding concerted transition model together with non‐essential hyperbolic activation. PFK‐1 from rat liver and heart also exhibited the mixed cooperative‐hyperbolic kinetic behavior regarding activators. Lowering pH induced decreased affinity for Fru6P, Fru2,6BP, citrate, and ATP (as inhibitor); as well as decreased Vm and increased content of inactive (T) enzyme forms. High K+ prompted increased (Fru6P) or decreased (activators) affinities; increased Vm; and increased content of active (R) enzyme forms. mRNA expression analysis and nucleotide sequencing showed that the three PFK‐1 isoforms L, M, and C are transcribed in the three carcinomas. However, proteomic analysis indicated the predominant expression of L in liver, of M in heart and MCF‐7 cells, of L > M in AS‐30D cells, and of C in HeLa cells. PFK‐1M showed the highest affinities for F6P and citrate and the lowest for ATP (substrate) and F2,6BP; PFK‐1L showed the lowest affinity for F6P and the highest for F2,6BP; and PFK‐1C exhibited the highest affinity for ATP (substrate) and the lowest for citrate. Thus, the present work documents the kinetic signature of each PFK‐1 isoform, and facilitates the understanding of why this enzyme exerts significant or negligible glycolysis flux‐control in normal or cancer cells, respectively, and how it regulates the onset of the Pasteur effect. J. Cell. Biochem. 113: 1692–1703, 2012. © 2011 Wiley Periodicals, Inc.
Incident Management Optimization through the Reuse of Experiences and Natural Language Processing

Information Technology (IT) Governance need for tools and processes that assist the qualification, retention and reuse of solutions to leverage the management of incidents. In this sense, this work proposes a process for resolving incidents, whose differential is the use of CBR (Case Based Reasoning) and NLP (Natural Language Processing) techniques, aiming the reuse of experience in handling similar incidents. Specially, NLP techniques, such as morphosyntactic analysis and semantic textual similarity, are used in the retrieval phase of the CBR system. We applied the proposed process in a real scenario after the deployment of an ERP system in a mixed capital company, in order to validate if the use of CBR and NLP components in an Incident Management Process optimizes the handling of incidents.
Minimum Process Coordinated Checkpointing Scheme for Ad Hoc Networks

The wireless mobile ad hoc network (MANET) architecture is one consisting of a set of mobile hosts capable of communicating with each other without the assistance of base stations. This has made possible creating a mobile distributed computing environment and has also brought several new challenges in distributed protocol design. In this paper, we study a very fundamental problem, the fault tolerance problem, in a MANET environment and propose a minimum process coordinated checkpointing scheme. Since potential problems of this new environment are insufficient power and limited storage capacity, the proposed scheme tries to reduce the amount of information saved for recovery. The MANET structure used in our algorithm is hierarchical based. The scheme is based for Cluster Based Routing Protocol (CBRP) which belongs to a class of Hierarchical Reactive routing protocols. The protocol proposed by us is nonblocking coordinated checkpointing algorithm suitable for ad hoc environments. It produces a consistent set of checkpoints; the algorithm makes sure that only minimum number of nodes in the cluster are required to take checkpoints; it uses very few control messages. Performance analysis shows that our algorithm outperforms the existing related works and is a novel idea in the field. Firstly, we describe an organization of the cluster. Then we propose a minimum process coordinated checkpointing scheme for cluster based ad hoc routing protocols.
To help or not to help an outgroup member: The role of the target's individual attributes in resolving potential helpers' motivational conflict

When people are faced with the decision of whether or not to help an outgroup member, they often experience conflicting motivational tendencies due to the concurrent presence of factors prompting help and factors prompting non-help. We argue that one way of how people deal with this conflict is by taking a closer look at the target's individual attributes, especially at those indicating the target's benevolence. Findings of Experiment 1 (N = 96), in which we manipulated intercultural dissimilarity between participants and a (fictitious) recipient of help and normative pressure to help as two factors affecting motivational conflict, support this basic assumption. Specifically, response latencies analyses confirmed that participants assigned a culturally highly dissimilar target spent more time on inspecting target-related information when normative pressure, and thus motivational conflict, was high than when it was low. Experiment 2 (N = 141) extended these findings by demonstrating that providing potential helpers with explicit information about an outgroup member's benevolence increased helping intentions through reducing their negative interaction expectancies (and thus motivational conflict). As expected, this mediational relationship could only be observed for participants assigned a culturally highly dissimilar target. Experiment 3 (N = 46) replicated these mediation findings in a within-subjects design. Copyright © 2014 John Wiley & Sons, Ltd.
Trust in Channel Relationships: Calculative, Affective, Belief and Performance

There is an ongoing concern among managers and scholars: how can firms develop trust? Our paper aims to review the emerging perspective of trust and propose 6 mechanisms to build trust in channel relationships. We develop a model containing the following mechanisms: calculative, affective, believe, embeddedness, continuity and capability. We conducted a survey to check whether the mechanisms influence firm performance. The data source comprise of a sample (n=132) in the Brazilian Distribution Market of agrochemical products. Results show the impact of the first three mechanisms on firm performance. The findings highlight that, even though environment leads to suspicion and doubts, managers seek trusty relationships and try to develop it using a combination of few mechanisms to overcome difficulties and perform well.
Street crossing pedestrian detection based on edge curves motion

This paper presents a real-time method for detecting pedestrians using vertical motion form two consecutives frames. We used association approach to match edge curves between consecutive images. Significant motions can be found using horizontal-vertical projection histogram. Then the pedestrian detection process is achieved in two steps. The first one searches the region of interest by using the intersection of vertical and horizontal projection of significant motion. The second step applies the Adaboost classifier on the region of interest provided by the first step. The proposed approach has been tested on different city traffic image sequences acquired by a camera mounted in a moving car. The results demonstrate the effectiveness of the proposed method.
Glycine site N-methyl-D-aspartate receptor antagonist 7-CTKA produces rapid antidepressant-like effects in male rats.

BACKGROUND Glutamate N-methyl-D-aspartate (NMDA) receptor antagonists exert fast-acting antidepressant effects, providing a promising way to develop a new classification of antidepressant that targets the glutamatergic system. In the present study, we examined the potential antidepressant action of 7-chlorokynurenic acid (7-CTKA), a glycine recognition site NMDA receptor antagonist, in a series of behavioural models of depression and determined the molecular mechanisms that underlie the behavioural actions of 7-CTKA. METHODS We administered the forced swim test, novelty-suppressed feeding test, learned helplessness paradigm and chronic mild stress (CMS) paradigm in male rats to evaluate the possible rapid antidepressant-like actions of 7-CTKA. In addition, we assessed phospho-glycogen synthase kinase-3β (p-GSK3β) level, mammalian target of rapamycin (mTOR) function, and postsynaptic protein expression in the medial prefrontal cortex (mPFC) and hippocampus. RESULTS Acute 7-CTKA administration produced rapid antidepressant-like actions in several behavioural tests. It increased p-GSK3β, enhanced mTOR function and increased postsynaptic protein levels in the mPFC. Activation of GSK3β by LY294002 completely blocked the antidepressant-like effects of 7-CTKA. Moreover, 7-CTKA did not produce rewarding properties or abuse potential. LIMITATIONS It is possible that 7-CTKA modulates glutamatergic transmission, thereby causing enduring alterations of GSK3β and mTOR signalling, although we did not provide direct evidence to support this possibility. Thus, the therapeutic involvement of synaptic adaptions engaged by 7-CTKA requires further study. CONCLUSION Our findings demonstrate that acute 7-CTKA administration produced rapid antidepressant-like effects, indicating that the behavioural response to 7-CTKA is mediated by GSK3β and mTOR signalling function in the mPFC.
Action Recognition using Key-Frame Features of Depth Sequence and ELM

Recently, the rapid development of inexpensive RGB-D sensor, like Microsoft Kinect, provides adequate information for human action recognition. In this paper, a recognition algorithm is presented in which feature representation is generated by concatenating spatial features from human contour of key frames and temporal features from time difference information of a sequence. Then, an improved multi-hidden layers extreme learning machine is introduced as classifier. At last, we test our scheme on the public UTD-MHAD dataset from recognition accuracy and time consumption.
Experimental and analytical studies on a high-resolution OFDM carrier frequency offset estimator

In orthogonal frequency-division multiplexing (OFDM) communications, carrier frequency offset must be estimated and compensated at the receiver to maintain orthogonality. In this paper, we examine the performance of a blind carrier frequency offset estimation algorithm for OFDM communications, Experiments were conducted on a system operating at close to 2 Mbits/s. Insights obtained from these experiments provided the motivation to explore the fundamental relationships between estimator performance and multiple system parameters such as the signal-to-noise ratio, number of data samples, frequency-selective fading, and power loading. We examine the sensitivity of the blind carrier frequency offset estimation algorithm using first-order perturbation analysis. In particular, we derive a closed-form expression for the mean square error of the carrier frequency offset estimator and present tradeoff studies for the high-resolution blind estimator performance. The analytical and simulation studies are in good agreement with experimental results.
On the use of the Hanning window for harmonic analysis in the standard framework

This paper studies the effect of the Hanning window (HW) on the processing of harmonics and interharmonics in the framework of the standard defined by the IEC. The performance of the HW is studied both in the processing of a large harmonic current fluctuation and when an interharmonic voltage component appears between two contiguous harmonic components. The results obtained are compared with the results obtained when applying the method defined in the standard and the root mean square value of each signal.
Population Genetics of Speciation in Two Closely Related Wild Tomatoes (Solanum Section Lycopersicon)

We present a multilocus sequencing study to assess patterns of polymorphism and divergence in the closely related wild tomato species, Solanum peruvianum and S. chilense (Solanum section Lycopersicon, Solanaceae). The data set comprises seven mapped nuclear loci (≈9.3 kb of analyzed sequence across loci) and four local population samples per species that cover much of the species' range (between 80 and 88 sequenced alleles across both species). We employ the analytical framework of divergence population genetics (DPG) in evaluating the utility of the “isolation” model of speciation to explain observed patterns of polymorphism and divergence. Whereas the isolation model is not rejected by goodness-of-fit criteria established via coalescent simulations, patterns of intragenic linkage disequilibrium provide evidence for postdivergence gene flow at two of the seven loci. These results suggest that speciation occurred under residual gene flow, implying that natural selection is one of the evolutionary forces driving the divergence of these tomato species. This inference is fully consistent with their recent divergence, conservatively estimated to be ≤0.55 million years. We discuss possible biases in the demographic parameter estimates due to the current restriction of DPG algorithms to panmictic species.
Muscular reinnervation and differentiation after peripheral nerve transection

Bij letsels door verkeers- of sportongelukken raken zenuwen nogal eens zwaar beschadigd of zelfs volledig doorgesneden. Dergelijke onderbroken zenuwbanen zijn tegenwoordig goed te repareren door hechting of met een zenuwgeleider van kunststof. Toch is het herstel van de functie van het getroffen lichaamsdeel meestal teleurstellend. Jos IJkema-Paassen onderzocht hoe dat kan en laat in haar proefdieronderzoek zien wat er met een spier gebeurt wanneer de aansturende zenuw wordt doorgesneden en wat er verandert na de hernieuwde uitgroei van de zenuw. Ze ontdekte bovendien dat de veronderstelling dat kinderen beter herstellen van zenuwletsel, niet ondersteund wordt door de resultaten van haar proefschrift. Spieren bestaan uit twee soorten spiervezels: vezels die langzaam aanspannen en langzaam vermoeibaar zijn, en spiervezels die snel aanspannen en snel vermoeibaar zijn. Elke spier kent een specifieke verdeling: sommige zijn overwegend langzaam, bijvoorbeeld spieren die gebruikt worden om rechtop te blijven staan, en andere zijn overwegend snel, bijvoorbeeld spieren die gebruikt worden bij hardlopen. Spiervezels worden aangestuurd door de uitloper van een zenuwcel. De eigenschappen van de zenuwcel en de spiervezel zijn aan elkaar gekoppeld: de zenuwcel legt zijn eigenschappen op aan de spiervezel. IJkema-Paassen ontdekte dat de uitgroeiende zenuwen de spieren wel weer weten te bereiken, maar dat dit volstrekt willekeurig is. Daardoor krijgen alle spieren een min of meer eenvormige spiervezelsamenstelling; ongeacht hun (oorspronkelijke) functie. Dit is een verklaring voor het slechte functieherstel. Tegen de verwachting in, blijken zenuwdoorsnijdingen op jonge leeftijd dezelfde gevolgen te hebben als die op oudere leeftijd.
SNP Discovery Using Next Generation Transcriptomic Sequencing in Atlantic Herring (Clupea harengus)

The introduction of Next Generation Sequencing (NGS) has revolutionised population genetics, providing studies of non-model species with unprecedented genomic coverage, allowing evolutionary biologists to address questions previously far beyond the reach of available resources. Furthermore, the simple mutation model of Single Nucleotide Polymorphisms (SNPs) permits cost-effective high-throughput genotyping in thousands of individuals simultaneously. Genomic resources are scarce for the Atlantic herring (Clupea harengus), a small pelagic species that sustains high revenue fisheries. This paper details the development of 578 SNPs using a combined NGS and high-throughput genotyping approach. Eight individuals covering the species distribution in the eastern Atlantic were bar-coded and multiplexed into a single cDNA library and sequenced using the 454 GS FLX platform. SNP discovery was performed by de novo sequence clustering and contig assembly, followed by the mapping of reads against consensus contig sequences. Selection of candidate SNPs for genotyping was conducted using an in silico approach. SNP validation and genotyping were performed simultaneously using an Illumina 1,536 GoldenGate assay. Although the conversion rate of candidate SNPs in the genotyping assay cannot be predicted in advance, this approach has the potential to maximise cost and time efficiencies by avoiding expensive and time-consuming laboratory stages of SNP validation. Additionally, the in silico approach leads to lower ascertainment bias in the resulting SNP panel as marker selection is based only on the ability to design primers and the predicted presence of intron-exon boundaries. Consequently SNPs with a wider spectrum of minor allele frequencies (MAFs) will be genotyped in the final panel. The genomic resources presented here represent a valuable multi-purpose resource for developing informative marker panels for population discrimination, microarray development and for population genomic studies in the wild.
Convolutive BSS of Short Mixtures by ICA Recursively Regularized Across Frequencies

This paper proposes a new method of frequency-domain blind source separation (FD-BSS), able to separate acoustic sources in challenging conditions. In frequency-domain BSS, the time-domain signals are transformed into time-frequency series and the separation is generally performed by applying independent component analysis (ICA) at each frequency envelope. When short signals are observed and long demixing filters are required, the number of time observations for each frequency is limited and the variance of the ICA estimator increases due to the intrinsic statistical bias. Furthermore, common methods used to solve the permutation problem fail, especially with sources recorded under highly reverberant conditions. We propose a recursively regularized implementation of the ICA (RR-ICA) that overcomes the mentioned problem by exploiting two types of deterministic knowledge: 1) continuity of the demixing matrix across frequencies; 2) continuity of the time-activity of the sources. The recursive regularization propagates the statistics of the sources across frequencies reducing the effect of statistical bias and the occurrence of permutations. Experimental results on real-data show that the algorithm can successfully perform a fast separation of short signals (e.g., 0.5-1s), by estimating long demixing filters to deal with highly reverberant environments (e.g., ms).