Miracle-dz/UniFAR-FTUs huggingface dataset:
Regular Article -theoretical Physics

A new method to distinguish hadronically decaying boosted Z bosons from W bosons using the ATLAS detector Abstract The distribution of particles inside hadronic jets produced in the decay of boosted W and Z bosons can be used to discriminate such jets from the continuum background. Given that a jet has been identified as likely resulting from the hadronic decay of a boosted W or Z boson, this paper presents a technique for further differentiating Z bosons from W bosons. The variables used are jet mass, jet charge, and a b-tagging discriminant. A likelihood tagger is constructed from these variables and tested in the simulation of W → W Z for bosons in the transverse momentum range 200 GeV < p T < 400 GeV in √ s = 8 TeV pp collisions with the ATLAS detector at the LHC. For Z-boson tagging efficiencies of Z = 90, 50, and 10 %, one can achieve W +-boson tagging rejection factors (1// W +) of 1.7, 8.3 and 1000, respectively. It is not possible to measure these efficiencies in the data due to the lack of a pure sample of high p T , hadronically decaying Z bosons. However, the modelling of the tagger inputs for boosted W bosons is studied in data using a t ¯ t-enriched sample of events in 20.3 fb −1 of data at √ s = 8 TeV. The inputs are well modelled within uncertainties, which builds confidence in the expected tagger performance.
Using a multiobjective approach to retrieve information on surface properties used in a SVAT model

The reliability of model predictions used in meteorology, agronomy or hydrology is partly linked to an adequate representation of the water and energy balances which are described in so-called SVAT (Soil Vegetation Atmosphere Transfer) models. These models require the specification of many surface properties which can generally be obtained from laboratory or field experiments, using time consuming techniques, or can be derived from textural information. The required accuracy of the surface properties depends on the model complexity and their misspecification can affect model performance. At various time and spatial resolutions, remote sensing provides information related to surface parameters in SVAT models or state variables simulated by SVAT models. In this context, the Simple Soil-Plant-Atmosphere Transfer-Remote Sensing (SiSPAT-RS) model was developed for remote sensing data assimilation objectives. This new version of the physically based SiSPAT model simulates the main surface processes (energy fluxes, soil water content profiles, temperatures) and remote sensing data in the visible, infrared and thermal infrared spectral domains. As a preliminary step before data assimilation in the model, the objectives of this study were (1) to apply a multiobjective approach for retrieving quantitative information about the surface properties from different surface measurements and (2) to determine the potential of the SiSPAT-RS model to be applied with ‘little’ a priori information about input parameters. To reach these goals, the ability of the Multiobjective Generalized Sensitivity Analysis (MOGSA) algorithm to determine and quantify the most influential input parameters of the SiSPAT-RS model on several simulated output variables, was investigated. The results revealed the main influential input parameters according to different contrasted environmental conditions, and contributed to the reduction of their a priori uncertainty range. A procedure for specifying surface properties from MOGSA results was tested on the thermal and hydraulic soil parameters, and evaluated through the SiSPAT-RS model performance. Although slightly lower than a reference simulation, the performance were satisfactory and suggested that complex SVAT models can be driven with little a priori information Journal of Hydrology 287 (2004) 214–236 www.elsevier. com/locate/jhydrol 0022-1694/$ see front matter q 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol. 2003.10. 003 * Corresponding author. Address: INRA Avignon-Unité CSE, Domaine Saint Paul, Site Agroparc 84914 Avignon Cedex 9, France. Tel. : þ33-432-722427; fax: þ33-432-722362. E-mail address: jdemarty@avignon.inra. fr (J. Demarty). on soil properties, as in a future context of remote sensing data assimilation. Measurement acquired on a winter wheat field of the ReSeDA (Remote Sensing Data Assimilation) experiment were used in this study. q 2004 Elsevier B.V. All rights reserved.
Improving Personalization Solutions through Optimal Segmentation of Customer Bases

On the Web, where the search costs are low and the competition is just a mouse click away, it is crucial to segment the customers intelligently in order to offer more targeted and personalized products and services to them. Traditionally, customer segmentation is achieved using statistics-based methods that compute a set of statistics from the customer data and group customers into segments by applying distance-based clustering algorithms in the space of these statistics. In this paper, we present a direct grouping-based approach to computing customer segments that groups customers not based on computed statistics, but in terms of optimally combining transactional data of several customers to build a data mining model of customer behavior for each group. Then, building customer segments becomes a combinatorial optimization problem of finding the best partitioning of the customer base into disjoint groups. This paper shows that finding an optimal customer partition is NP-hard, proposes several suboptimal direct grouping segmentation methods, and empirically compares them among themselves, traditional statistics-based hierarchical and affinity propagation-based segmentation, and one-to-one methods across multiple experimental conditions. It is shown that the best direct grouping method significantly dominates the statistics-based and one-to-one approaches across most of the experimental conditions, while still being computationally tractable. It is also shown that the distribution of the sizes of customer segments generated by the best direct grouping method follows a power law distribution and that microsegmentation provides the best approach to personalization.
Generic Algorithm with Varying Block Sizes to Improve the Capacity of a Wireless Communications Networks

Problem statement: Channel capacity can be an essential parameter for wireless communication to improve the link quality. Until now, the channel capacity has been evaluated by utilizing Shannon capacity theory, but it presented many limitations and restrictions. The objectives of this study were to: (i) Expose, quantify, present and to give a clear and concise exposition of the mathematical principles of the proposed generic algorithm and (ii) Calculate and simulate the SNR, the BER and the channel capacity for wireless underwater transceiver and compare with the literature references. Approach: Contrary to the existing theory (Shannon capacity theory that required and needed of the exact channel state distribution and particularly the precisely estimation of cut-off threshold profile, so, the bad estimation allowed suspending transmission even for good channel conditions), the proposed generic algorithm was used to determine the channel capacity performance with varying block size input packet information (N was varied from 50-200) as a function of the optimum transmit power (from 3.5-7.0 w). This approach did not require the exact channel state distribution; but the channel was well modeled and the cut-off threshold profile had to be numerically solved. The iteration results of this algorithm were utilized to calculate and simulate the SNR, the BER and the channel capacity for wireless underwater transceiver performance. Results: The consultation performance of channel capacity wireless underwater communication, obtained with present approach, were significantly better in any transmission conditions (no suspending transmission) because the proposed algorithm was well suited to obtain results about channel capacity. In the other hand, the amount of transmitted data per resource depended on the channel conditions was performed. Blocking is no longer critical if data traffic without or with sensitivity has to be served. Data rate results were allowed of the users to be satisfied because of the wanted to achieve a certain guarantees. This was attributed to higher SNR, a lower BER and an optimal channel capacity value with the minimal transmission power. Conclusion: These results indicated that using this generic algorithm can enhance and optimize the link quality and the performance of wireless underwater communication.
Inflammatory monocytes recruited after skeletal muscle injury switch into antiinflammatory macrophages to support myogenesis

Macrophages (MPs) are important for skeletal muscle regeneration in vivo and may exert beneficial effects on myogenic cell growth through mitogenic and antiapoptotic activities in vitro. However, MPs are highly versatile and may exert various, and even opposite, functions depending on their activation state. We studied monocyte (MO)/MP phenotypes and functions during skeletal muscle repair. Selective labeling of circulating MOs by latex beads in CX3CR1GFP/+ mice showed that injured muscle recruited only CX3CR1lo/Ly-6C+ MOs from blood that exhibited a nondividing, F4/80lo, proinflammatory profile. Then, within muscle, these cells switched their phenotype to become proliferating antiinflammatory CX3CR1hi/Ly-6C− cells that further differentiated into F4/80hi MPs. In vitro, phagocytosis of muscle cell debris induced a switch of proinflammatory MPs toward an antiinflammatory phenotype releasing transforming growth factor β1. In co-cultures, inflammatory MPs stimulated myogenic cell proliferation, whereas antiinflammatory MPs exhibited differentiating activity, assessed by both myogenin expression and fusion into myotubes. Finally, depletion of circulating MOs in CD11b–diphtheria toxin receptor mice at the time of injury totally prevented muscle regeneration, whereas depletion of intramuscular F4/80hi MPs at later stages reduced the diameter of regenerating fibers. In conclusion, injured skeletal muscle recruits MOs exhibiting inflammatory profiles that operate phagocytosis and rapidly convert to antiinflammatory MPs that stimulate myogenesis and fiber growth.
Developmental regulation of transcription factor AP-2 during Xenopus laevis embryogenesis

We have isolated a cDNA clone encoding the Xenopus homologue of the transcription factor AP-2 (XAP-2). The predicted amino acid sequence derived from the Xenopus cDNA shows very strong conservation with the amino acid sequence of human AP-2, suggesting that this protein is evolutionarily conserved, at least among vertebrates. This is further substantiated by the demonstration that an in vitro translation product of XAP-2 cDNA bound specifically to an AP-2 binding site from the human MT-IIA gene. Northern blot analysis of Xenopus embryo RNA revealed the existence of three major XAP-2 mRNA species that were only detectable after the midblastula transition (when embryonic transcription is activated), with peak accumulation of the transcripts occurring during gastrulation. Therefore, in contrast to other Xenopus transcription factors, XAP-2 is not maternally derived but arises exclusively from zygotic transcription. Unlike the situation in cultured human teratocarcinoma (NT2) cells, retinoic acid treatment did not induce XAP-2 mRNA in Xenopus embryos, even though the treatment had a pronounced morphogenetic effect on the embryos. Our results suggest that XAP-2 may play a distinctive role during Xenopus embryogenesis.
Predictors of Sexual Satisfaction for Partnered Lesbian, Gay, and Bisexual Adults

Past research on sexual satisfaction (SS) has primarily developed along three lines of research: interpersonal exchange as related to SS, impact of body image on sexuality and SS, and dysfunction and sexual anxiety as detractors from SS. Furthermore, past research has tended to focus on heterosexual couples, thereby excluding potentially important predictors of SS that are unique to LGB men and women. In this study, we sought to integrate the three disparate lines of research related to SS and attend to LGB-specific factors that may influence SS. We employed multiple linear regression to analyze data from 369 partnered LGB men and women. This method allowed for the examination of how each predictor influenced SS while accounting for the relationships between SS and the other variables. Results indicated that four variables (sexual anxiety, relationship commitment, body image, and identity pride) contributed significantly to SS. Neither internalized homonegativity nor gender contributed significantly to SS; however, analyses indicated that for partnered LGB adults, relationship commitment was an important predictor of SS for women, but not for men. Overall, our findings indicate that partnered LGB adults’ perception of their SS is influenced by factors that are unique to their LGB identity (i.e., identity pride), as well as by those shared by heterosexually identified adults (i.e., body image, relationship commitment, and sexual anxiety). These findings have implications for psychotherapy and SS research with LGB clients.
N-acetyl cysteine inhibits H2O2-mediated reduction in the mineralization of MC3T3-E1 cells by down-regulating Nrf2/HO-1 pathway

There are controversial findings regarding the roles of nuclear factor (erythroid-derived 2)-like 2 (Nrf2)/heme oxygenase-1 (HO-1) pathway on bone metabolism under oxidative stress. We investigated how Nrf2/HO-1 pathway affects osteoblast differentiation of MC3T3-E1 cells in response to hydrogen peroxide (H2O2), N-acetyl cysteine (NAC), or both. Exposing the cells to H2O2 decreased the alkaline phosphatase activity, calcium accumulation, and expression of osteoblast markers, such as osteocalcin and runt-related transcription factor-2. In contrast, H2O2 treatment increased the expression of Nrf2 and HO-1 in the cells. Treatment with hemin, a chemical HO-1 inducer, mimicked the inhibitory effect of H2O2 on osteoblast differentiation by increasing the HO-1 expression and decreasing the osteogenic marker genes. Pretreatment with NAC restored all changes induced by H2O2 to near normal levels in the cells. Collectively, our findings suggest that H2O2-mediated activation of Nrf2/HO-1 pathway negatively regulates the osteoblast differentiation, which is inhibited by NAC. [BMB Reports 2015; 48(11): 636-641]
Non-Markovian spiking statistics of a neuron with delayed feedback in presence of refractoriness.

Spiking statistics of a self-inhibitory neuron is considered. The neuron receives excitatory input from a Poisson stream and inhibitory impulses through a feedback line with a delay. After triggering, the neuron is in the refractory state for a positive period of time. Recently, [35,6], it was proven for a neuron with delayed feedback and without the refractory state, that the output stream of interspike intervals (ISI) cannot be represented as a Markov process. The refractory state presence, in a sense limits the memory range in the spiking process, which might restore Markov property to the ISI stream. Here we check such a possibility. For this purpose, we calculate the conditional probability density P (tn+1 l tn,.,t1,t0), and prove exactly that it does not reduce to P (tn+1 l tn,.,t1) for any n ⋝0. That means, that activity of the system with refractory state as well cannot be represented as a Markov process of any order. We conclude that it is namely the delayed feedback presence which results in non-Markovian statistics of neuronal firing. As delayed feedback lines are common for any realistic neural network, the non-Markovian statistics of the network activity should be taken into account in processing of experimental data.
Introducing Science Stories in Palestinian Elementary Classrooms: Facilitating Teacher Learning

ABSTRACT This qualitative interpretive study aimed to explore the use of content-based story writing as an educative curriculum to promote science teachers’ professional learning. It also aimed to help teachers interact and reflect on their students’ science stories to generate and explore content and pedagogical content knowledge. This study was carried out in the fourth and fifth-grade classrooms of 6 science teachers in Jerusalem, Palestine, during the 2013–2014 school year. Classroom observations; video recordings; teachers’ focus group conversations; students’ stories; teachers’ reflections; and field notes from the teachers, the students, and the supervisor were collected and analyzed. Thematic analysis was used to develop themes that emerged from the data. The findings showed that teachers explained many educative features, including how their views and beliefs toward teaching science changed as a result of the use of educative curriculum materials (professional learning). Teachers understood more about their new roles as science teachers as students were engaged in the learning process through producing stories that acted in later stages as a fruitful resource of knowledge for teachers and students. Teachers experienced the development of content knowledge (personal growth and self-awareness) and pedagogical knowledge (the power of using stories to enhance classroom interaction and discussion, motivation and feedback as a strategy for enhancing writing and rewriting stories). Finally, the use of stories cultivated students’ imagination and identified areas in which students needed to develop further understanding. These findings imply that educative curriculum materials that support teachers in using content-based story writing have potential for supporting Palestinian teachers who work in a complex area with very limited resources.
Modelling river discharge for large drainage basins: from lumped to distributed approach

The paper presents an upscaled application of the HBV model to the German part of the Elbe drainage basin, and intercomparison of lumped and distributed versions of the model. The objectives of the work were (a) to check the model performance for large-scale basins, and (b) to compare the lumped and distributed versions of the model. Three versions of the HBV model, one lumped and two distributed, were applied first to a number of sub-basins of the Elbe with different hydrological regimes (area > 1000 km2), and then to the whole German part of the basin (area 80 657 km2). The model performed well in all cases. The distributed model versions are more data intensive but enabled better results to be achieved. The perspectives for using the model for large-scale water quality assessment, for climate change impact studies and for coupled land-atmosphere modelling are discussed.
Mostly-Optimistic Concurrency Control for Highly Contended Dynamic Workloads on a Thousand Cores

Future servers will be equipped with thousands of CPU cores and deep memory hierarchies. Traditional concurrency control (CC) schemes---both optimistic and pessimistic---slow down orders of magnitude in such environments for highly contended workloads. Optimistic CC (OCC) scales the best for workloads with few conflicts, but suffers from clobbered reads for high conflict workloads. Although pessimistic locking can protect reads, it floods cache-coherence backbones in deep memory hierarchies and can also cause numerous deadlock aborts. This paper proposes a new CC scheme, mostly-optimistic concurrency control (MOCC), to address these problems. MOCC achieves orders of magnitude higher performance for dynamic workloads on modern servers. The key objective of MOCC is to avoid clobbered reads for high conflict workloads, without any centralized mechanisms or heavyweight interthread communication. To satisfy such needs, we devise a native, cancellable reader-writer spinlock and a serializable protocol that can acquire, release and re-acquire locks in any order without expensive interthread communication. For low conflict workloads, MOCC maintains OCC's high performance without taking read locks. Our experiments with high conflict YCSB workloads on a 288-core server reveal that MOCC performs 8× and 23× faster than OCC and pessimistic locking, respectively. It achieves 17 million TPS for TPC-C and more than 110 million TPS for YCSB without conflicts, 170× faster than pessimistic methods.
A Fine is a Price

The deterrence hypothesis predicts that the introduction of a penalty that leaves everything else unchanged will reduce the occurrence of the behavior subject to the fine. We present the result of a field study in a group of day‐care centers that contradicts this prediction. Parents used to arrive late to collect their children, forcing a teacher to stay after closing time. We introduced a monetary fine for late‐coming parents. As a result, the number of late‐coming parents increased significantly. After the fine was removed no reduction occurred. We argue that penalties are usually introduced into an incomplete contract, social or private. They may change the information that agents have, and therefore the effect on behavior may be opposite of that expected. If this is true, the deterrence hypothesis loses its predictive strength, since the clause “everything else is left unchanged” might be hard to satisfy.
Fox in the trap: thwarting masqueraders via automated decoy document deployment

Organizations face a persistent challenge detecting malicious insiders as well as outside attackers who compromise legitimate credentials and then masquerade as insiders. No matter how good an organization's perimeter defenses are, eventually they will be compromised or betrayed from the inside. Monitored decoy documents (honey files with enticing names and content) are a promising approach to aid in the detection of malicious masqueraders and insiders. In this paper, we present a new technique for decoy document distribution that can be used to improve the scalability of insider detection. We develop a placement application that automates the deployment of decoy documents and we report on two user studies to evaluate its effectiveness. The first study indicates that our automated decoy distribution tool is capable of strategically placing decoy files in a way that offers comparable security to optimal manual deployment. In the second user study, we measure the frequency that normal users access decoy documents on their own systems and show that decoy files do not significantly interfere with normal user tasks.
On space and time correlations of isotropic and rotating turbulence

Two different approaches are used for evaluating two-time correlations of Fourier velocity modes in isotropic and in rotating homogeneous incompressible turbulence. A synthetic model is proposed and compared with the results of direct numerical simulations. This kinematic model presents the advantage to incorporate different sources of unsteadiness from arbitrary time scales to linear dynamics of rotating flows. The two main time scales characterizing the various processes involved in the dynamics of isotropic turbulence can be included: the sweeping effect, in which small scales of the flow are advected by the large scale motion, and the straining hypothesis—also called Kolmogorov or eddy turnover time scale. In the rotating case, the dispersion relation of inertial waves can also be included. Using Lighthill’s theory, the effect of these different time scales on the sound emitted by such a model is also examined and compared with direct numerical simulations.