Miracle-dz/UniFAR-FTUs huggingface dataset:
The counstruction of social inclusion through music education: Two Swedish ethnographic studies of the El Sistema programme

Drawing on theories from sociology and music education, as well as closely linked disciplines, the article discusses how social inclusion is constructed in the choir and orchestra school El Sistema. The objective of the programme in Sweden is to use music as a vehicle for individual and social development as well as to serve as an intercultural meeting place and thereby for social inclusion. The results, generated from two ethnographic studies, in Gothenburg and Malmö, show that there are different ways of constructing social inclusion within El Sistema. Viewed from an integrative sociological perspective on music education, the students are primarily positioned as representatives of the El Sistema community, rather than as independent agents in control of the music and their learning. However, the programme also allows for temporarily interrupting the community rationale by enhancing teachers’ agency and allowing the children to participate on their own terms—though this is mainly limited to the social events.
Effect of Cognitive Depletion on Password Choice

Background. The Limited Strength model [3] of cognitive psychology predicts that human capacity to exert cognitive effort is limited and that decision making is impeded once high depletion is reached. Aim. We investigate how password choice differs between depleted and undepleted users. Method. Two groups of 50 subjects each were asked to generate a password. One group was cognitively depleted, the other was not. Password strength was measured and compared across groups. Results. Using a stepwise linear regression we found that password strength is predicted by depletion level, personality traits and mood, with an overall adjusted R 2 = . 206. The depletion level was the strongest predictor of password strength (predictor importance .371 and p = .001). Participants with slight effortful exertion created significantly better passwords than the undepleted control group. Participants with high depletion created worse passwords than the control group. Conclusions. That strong depletion diminishes the capacity to choose strong passwords indicates that cognitive effort is necessary for the creation of strong passwords. It is surprising that slight exertion of cognitive effort prior to the password creation leads to stronger passwords. Our findings open up new avenues for usable security research through deliberately eliciting cognitive effort and replenishing after depletion and indicate the potential of investigating personality traits and current mood. © 2016 Newcastle University. Printed and published by Newcastle University, Computing Science, Claremont Tower, Claremont Road, Newcastle upon Tyne, NE1 7RU, England. Bibliographical details Effect of Cognitive Depletion on Password Choice Extended Technical Report Thomas Groß, Kovila Coopamootoo, Amina Al-Jabri NEWCASTLE UNIVERSITY Computing Science. Technical Report Series. CS-TR-1496
Editorial: The Clinical Significance of the Repetitive Ventricular Response

THE CLINICAL SIGNIFICANCE of the repetitive ventricular response (RVR) has become an issue of considerable interest and controversy. '-6 Despite the interest and efforts of several investigators, definite conclusions about its significance are not possible. In fact, the clinical and electrophysiologic aspects of the RVR have been a source of confusion, particularly for those not well acquainted with cardiac electrophysiologic studies. Of primary importance is the fact that a uniform definition of RVR has not been established. In this communication, it refers to the occurrence of one or more (but less than five) nonstimulated ventricular beats after a paced ventricular premature beat (V2) either during basic atrial (sinus or atrial paced) or ventricular rhythms. A similar definition has been used in most of the published clinical studies, although the separation of multiple RVRs from nonsustained ventricular tachycardia (VT) has not been clarified.
Biological and Molecular Variability of Alfalfa mosaic virus Affecting Alfalfa Crop in Riyadh Region

In 2011–2012, sixty nine samples were collected from alfalfa plants showing viral infection symptoms in Riyadh region. Mechanical inoculation with sap prepared from two collected samples out of twenty five possitive for Alfalfa mosaic virus (AMV) by ELISA were produced systemic mosaic on Vigna unguiculata and Nicotiana tabacum, local lesion on Chenopodium amaranticolor and C. quinoa. Vicia faba indicator plants that induce mosaic and mottle with AMV-Sagir isolate and no infection with AMV-Wadi aldawasser isolate. Approximately 700-bp was formed by RT-PCR using AMV coat protein specific primer. Samples from infected alfalfa gave positive results, while healthy plant gave negative result using dot blot hybridization assay. The nucleotide sequences of the Saudi isolates were compared with corresponding viral nucleotide sequences reported in GenBank. The obtained results showed that the AMV from Australia, Brazil, Puglia and China had the highest similarity with AMV-Sajer isolate. While, the AMV from Spain and New Zealaland had the lowest similarity with AMV-Sajer and Wadi aldawasser isolates. The data obtained in this study has been deposited in the GenBank under the accession numbers KC434083 and KC434084 for AMV-Sajer and AMV- Wadialdawasser respectively. This is the first report regarding the gnetic make up of AMV in Saudi Arabia.
The Von Willebrand Factor Propeptide (VWFpp) Traffics an Unrelated Protein to Storage

The von Willebrand factor (VWF) propeptide (VWFpp) is critical for the targeting of VWF multimers to storage granules. VWFpp alone efficiently navigates the storage pathway in AtT-20 and endothelial cells and chaperones mature VWF multimers to storage granules when the two proteins are expressed in cis or in trans. To further define the role of VWFpp in granular sorting, we examined its ability to sort an unrelated protein, C3&agr; into the regulated secretory pathway. Chimeric constructs of VWFpp and the &agr;-chain of C3 were developed. The C3&agr; protein expressed alone did not sort to granules in AtT-20 cells. The trans expression of C3&agr; and VWFpp resulted in granular storage of VWFpp but no corresponding storage of C3&agr;. When C3&agr; is expressed as a single chain molecule with VWFpp that was rendered uncleavable by furin, C3&agr; is re-routed to storage and is colocalized with VWFpp. The uncleavable protein was expressed in bovine aortic endothelial cells where it sorted to Weibel-Palade bodies, colocalized with bovine VWF, and was released when agonist stimulated. We now demonstrate that VWFpp re-routes a constitutively secreted protein to the regulated storage pathway. Furthermore, our studies suggest that the VWFpp storage signal is contained within amino acids 201 to 741.
Higgs physics as a window beyond the MSSM

We interpret the current experimental limit on the lightest Higgs boson mass to suggest that, if nature is supersymmetric, there are additional interactions beyond those of the minimal supersymmetric standard model (MSSM) coming from new degrees of freedom around the TeV scale. Within an effective field theory analysis, the leading order corrections to the MSSM are described in terms of only two operators. This provides a highly constrained description of beyond MSSM physics. The scalar Higgs spectrum as well as the chargino and neutralino spectra and couplings are modified in a distinctive way. These operators can be generated by a variety of microscopic mechanisms.
Oral antisense that targets protein kinase A cooperates with taxol and inhibits tumor growth, angiogenesis, and growth factor production.

Protein kinase A type I (PKAI) transduces mitogenic signals from different growth factors and oncogenes and is overexpressed in the majority of human cancers. We and other investigators previously have reported that different PKAI inhibitors, including antisense oligonucleotides, have antitumor activity. In this study, we used a novel hybrid DNA/RNA mixed-backbone oligonucleotide (MBO) targeting the PKAI subunit RIalpha. We demonstrated that after oral administration, the MBO antisense RIalpha inhibited the growth of human colon cancer xenografts in nude mice and showed a cooperative antitumor effect with Taxol, which outlasted treatment withdrawal and significantly prolonged survival of mice compared with untreated controls or to single-agent-treated mice. Immunohistochemical analysis of tumor specimens showed inhibition of target protein RIalpha and of growth factor expression along with a marked inhibition of angiogenesis and an increase in p27 expression. In conclusion, a novel MBO that targets PKAI, administered p.o. , is effective and cooperates with the anticancer drug Taxol on both tumor growth and expression of factors involved in the control of cell proliferation, cell cycle, and angiogenesis. Because the MBO described has completed a phase I trial involving i.v. injection in cancer patients, these results provide the biological rationale of its activity after oral administration and may be translated into a therapeutic strategy in a clinical setting.
Data-dependent kernels in svm classification of speech patterns

Support Vector Machines (SVMs) have recently proved to be powerful pattern classi(cid:12)cation tools with a strong con-nection to statistical learning theory. One of the hurdles to using SVMs in speech recognition, and a crucial aspect of SVM design in general, is the choice of the kernel function for non-separable data, and the setting of its parameters. This is often based on experience or a potentially costly search. This paper gives some experimental justi(cid:12)cation for the Fisher kernels proposed in [4]; kernels are obtained and their extra regularisation and use of labelled and unlabelled data discussed. Fisher kernels are derived from generative probability models of the data, and are a (cid:12)rst-step to implementing kernels for variable length sequences.
Guided Policy Search as Approximate Mirror Descent

Guided policy search algorithms can be used to optimize complex nonlinear policies, such as deep neural networks, without directly computing policy gradients in the high-dimensional parameter space. Instead, these methods use supervised learning to train the policy to mimic a "teacher" algorithm, such as a trajectory optimizer or a trajectory-centric reinforcement learning method. Guided policy search methods provide asymptotic local convergence guarantees by construction, but it is not clear how much the policy improves within a small, finite number of iterations. We show that guided policy search algorithms can be interpreted as an approximate variant of mirror descent, where the projection onto the constraint manifold is not exact. We derive a new guided policy search algorithm that is simpler and provides appealing improvement and convergence guarantees in simplified convex and linear settings, and show that in the more general nonlinear setting, the error in the projection step can be bounded. We provide empirical results on several simulated robotic navigation and manipulation tasks that show that our method is stable and achieves similar or better performance when compared to prior guided policy search methods, with a simpler formulation and fewer hyperparameters.
Learning Mixed Multinomial Logit Model from Ordinal Data

Motivated by generating personalized recommendations using ordinal (or preference) data, we study the question of learning a mixture of MultiNomial Logit (MNL) model, a parameterized class of distributions over permutations, from partial ordinal or preference data (e.g. pair-wise comparisons). Despite its long standing importance across disciplines including social choice, operations research and revenue management, little is known about this question. In case of single MNL models (no mixture), computationally and statistically tractable learning from pair-wise comparisons is feasible. However, even learning mixture with two MNL components is infeasible in general. Given this state of affairs, we seek conditions under which it is feasible to learn the mixture model in both computationally and statistically efficient manner. We present a sufficient condition as well as an efficient algorithm for learning mixed MNL models from partial preferences/comparisons data. In particular, a mixture of r MNL components over n objects can be learnt using samples whose size scales polynomially in n and r (concretely, r3.5n3(log n)4, with r ≪ n2/7 when the model parameters are sufficiently incoherent). The algorithm has two phases: first, learn the pair-wise marginals for each component using tensor decomposition; second, learn the model parameters for each component using RANKCENTRALITY introduced by Negahban et al. In the process of proving these results, we obtain a generalization of existing analysis for tensor decomposition to a more realistic regime where only partial information about each sample is available.
Impact of Age and Sex on Bystander Cardiopulmonary Resuscitation Knowledge

Abstract Objective: To assess the impact of age and sex on the bystander CPR Knowledge in a group of Nigerian student teachers. Materials and Methods: A quasi-experimental study design was used with the cohort made up of forty one (41) male and forty one (41) female undergraduate students of Physical and Health Education with 40 participants in the 17-20 years age group and 42 participants belonging to the 21-28 years of age bracket were randomly selected from the larger main cohort for analysis of possible impact of age and sex on their pre-training and post-training cardiopulmonary resuscitation knowledge. In addition to the descriptive statistics, one-way analysis of variance (ANOVA) was used to test the null hypotheses generated with significance level set at P < 0.05. Results: No significant age impact was found on the pre-training and post-training CPR knowledge of the student teachers (P > 0.05). However, there was a positive impact of male gender on post-training CPR knowledge of the participants (P <0.001). Conclusion: Although age could not impact significantly on the cardiopulmonary resuscitation knowledge of the participants, male gender significantly impacted on the post-training cardiopulmonary resuscitation knowledge of the cohort.
Barcelona GSE Working Paper Series Working Paper n o 784 Model Comparisons in Unstable Environments

The goal of this paper is to develop formal tests to evaluate the relative in-sample performance of two competing, misspeci ed, non-nested models in the presence of possible data instability. Compared to previous approaches to model selection, which are based on measures of global performance, we focus on the local relative performance of the models. We propose tests that are based on di¤erent measures of local performance and that correspond to di¤erent null and alternative hypotheses. The empirical application provides insights into the time variation in the performance of a representative DSGE model of the European economy relative to that of VARs. Keywords: Model Selection Tests, Misspeci cation, Structural Change, Kullback-Leibler Information Criterion Acknowledgments: We are grateful to D. Kristensen for helpful comments and M. del Negro, F. Smets, R. Wouters, W.B. Wu and Z. Zhao for sharing their codes. We also thank the editor, three anonymous referees, seminar participants at the Empirical Macro Study Group at Duke U. , Atlanta Fed, UC Berkeley, UC Davis, U. of Michigan, NYU Stern, Boston U. , U. of Montreal, UNC Chapel Hill, U. of Wisconsin, UCI, LSE, UCL, Stanfords 2006 SITE workshop, the 2006 Cleveland Fed workshop, the 2006 Triangle Econometrics workshop, the Fifth ECB Workshop, the 2006 Cass Business School Conference on Structural Breaks and Persistence, the 2007 NBER Summer Institute, the 2009 NBER-NSF Time Series Conference and the 2012 AEA Meetings for useful comments and suggestions. Support by NSF grants 0647627 and 0647770 is gratefully acknowledged. J.E. L. Codes: C22, C52, C53
Genome-Wide Modulation of Gene Transcription in Ovarian Carcinoma Cells by a New Mithramycin Analogue

Ovarian cancer has a poor prognosis due to intrinsic or acquired resistance to some cytotoxic drugs, raising the interest in new DNA-binding agents such as mithramycin analogues as potential chemotherapeutic agents in gynecological cancer. Using a genome-wide approach, we have analyzed gene expression in A2780 human ovarian carcinoma cells treated with the novel mithramycin analogue DIG-MSK (demycarosyl-3D-β-D-digitoxosyl-mithramycin SK) that binds to C+G-rich DNA sequences. Nanomolar concentrations of DIG-MSK abrogated the expression of genes involved in a variety of cell processes including transcription regulation and tumor development, which resulted in cell death. Some of those genes have been associated with cell proliferation and poor prognosis in ovarian cancer. Sp1 transcription factor regulated most of the genes that were down-regulated by the drug, as well as the up-regulation of other genes mainly involved in response to cell stress. The effect of DIG-MSK in the control of gene expression by other transcription factors was also explored. Some of them, such as CREB, E2F and EGR1, also recognize C/G-rich regions in gene promoters, which encompass potential DIG-MSK binding sites. DIG-MSK affected several biological processes and molecular functions related to transcription and its cellular regulation in A2780 cells, including transcription factor activity. This new compound might be a promising drug for the treatment of ovarian cancer.
AC 2010-24: A VIRTUAL FACTORY APPROACH FOR DESIGN AND IMPLEMENTATION OF AGILE MANUFACTURING SYSTEMS

Worldwide competition among manufacturing enterprises has acted as a driving force for the design, development and utilization of manufacturing systems with an increased degree of agility. In these regards, Holonic Manufacturing Systems (HMS) are considered an intelligent systems paradigm to meet requirements for agile manufacturing systems. Despite all advantages of HMS, design and implementation of such control systems for real industrial cases is time consuming and requires risky, but careful consideration. While some universities may be able to expose their students to the latest manufacturing systems and technologies, others may not be that fortunate due to the lack of financial resources. Because of this, alternative ways for providing their students with equivalent education and training need to be developed. A potential solution for this issue is the adoption of advanced computer technology to facilitate the provision of flexible manufacturing-related education and training programs. To date, many studies have shown that the use of computers for teaching and training purposes is feasible and rapidly becoming an integral part of the general learning process. This paper presents a Virtual Reality (VR) system tool “VR-HMS” developed for training on design of holonic manufacturing control systems to enhance the development process. The proposed VR system is a safe approach to teaching the operations of HMS, which is well known as a large-scale and complex systems for a number of operational and structural reasons. The VR-HMS allows trainees to self-experience on these systems without the need to work in actual industry.
Visual Salience Affects Performance in a Working Memory Task

Many studies of bottom-up visual attention have focused on identifying which features of a visual stimulus render it salient—i.e., make it “pop out” from its background—and on characterizing the extent to which salience predicts eye movements under certain task conditions. However, few studies have examined the relationship between salience and other cognitive functions, such as memory. We examined the impact of visual salience in an object–place working memory task, in which participants memorized the position of 3–5 distinct objects (icons) on a two-dimensional map. We found that their ability to recall an object's spatial location was positively correlated with the object's salience, as quantified using a previously published computational model (Itti et al., 1998). Moreover, the strength of this relationship increased with increasing task difficulty. The correlation between salience and error could not be explained by a biasing of overt attention in favor of more salient icons during memorization, since eye-tracking data revealed no relationship between an icon's salience and fixation time. Our findings show that the influence of bottom-up attention extends beyond oculomotor behavior to include the encoding of information into memory.
Educators’ perceptions of school readiness within the context of a kindergarten entry assessment in Alaska

ABSTRACT This empirical study examined educators’ perceptions of kindergarten readiness, within the context of a larger study on the perceptions and use of the Alaska Developmental Profile, a mandated kindergarten entry assessment (KEA). The participants (n = 17) were primarily kindergarten teachers with varying years of experience. Data were collected through the use of surveys and semi-structured interviews and analyzed utilizing a qualitative approach. The results of the study suggest that educators’ perceptions of kindergarten readiness reflect a ‘come as you are’ philosophy and that ideally, children will come to kindergarten with some preschool experiences and some academic and social-emotional skills. The results also indicate that educators’ perceptions are not impacted by the use or results of a KEA. These findings encourage readers to consider how KEAs impact educators, what roles educators play in considering kindergarten readiness, and how schools might be ready for kindergartners instead of children being ‘ready’ for kindergarten.
Synaptic clustering during development and learning: the why, when, and how

To contribute to a functional network a neuron must make specific connections and integrate the synaptic inputs that it receives in a meaningful way. Previous modeling and experimental studies have predicted that this specificity could entail a subcellular organization whereby synapses that carry similar information are clustered together on local stretches of dendrite. Recent imaging studies have now, for the first time, demonstrated synaptic clustering during development and learning in different neuronal circuits. Interestingly, this organization is dependent on synaptic activity and most likely involves local plasticity mechanisms. Here we discuss these new insights and give an overview of the candidate plasticity mechanisms that could be involved.