Miracle-dz/UniFAR-FTUs huggingface dataset:
How do technologies support School Direct students' learning on a PGCE with Qualified Teacher Status within a Networked Learning Model

This work is a study of the way that students select and use technologies to build and maintain a learning network while training to become primary school teachers. It builds on the body of research which has explored Networked Learning by applying it to the context of teacher education and by applying it to a course where the ICTs used are selected by students not provided by tutors. It is a case study based on intrinsic interest with an exploratory focus to understand how and why students make use of the technologies they select. It uses multiple data sources including group interviews with students, interviews with tutors, questionnaires, virtual learning environment data and transcripts of students’ social media interactions. The analysis of these has been performed along three lines of enquiry to establish who is talking to whom, what they are talking about and why they are talking about it. The findings bring together a novel approach to the application of Networked Learning and research into a new route into teaching and show that students are sophisticated and agile users of a range of technologies. They use a variety of technologies to build and support interactions with artefacts, tutors and other learners. Where there are constraints in place, such as tutors’ preference for face-to-face interactions there is evidence that students will make use of technologies to substitute other interactions in their place. It finds that students’ most extensive interactions take place with other students and that these are multifaceted combining interactions directly related to learning, around-task interactions and social elements. It builds on research done in blended learning, networked learning, teacher education and social aspects of learning. It will be of interest to those interested in the role of technologies in education or those involved in teacher education.
An Empirical-Analysis Of Audit Delay

This paper reports an empirical study of some determinants of "audit delay," i.e., the length of time from a company's fiscal year-end to the date of the auditor's report. Audit delay can affect the timeliness of accounting information releases, and it is well known that timeliness is associated with the market's reaction to the information released. Therefore, research on the determinants of audit delay may improve our understanding of market reactions to accounting releases. To elaborate, the timeliness of information release can affect the level of uncertainty associated with decisions based on the reported information. For example, it has been shown analytically that timeliness can affect a decision maker's action choices and expected payoff (Feltham [1972, chap. 7]). Moreover, recent empirical studies suggest that timeliness is associated with information used by the market to establish security prices. For example, it has been found that "late" announcements of earnings are associated with lower (often negative) abnormal returns than are "early" announcements (Chambers and Penman [1984], Givoly and Palmon [1982], and Kross and Schroeder [1984]).
LAGRANGIAN APPROACH OF THE FIRST-CLASS CONSTRAINED SYSTEMS

We show how to systematically derive the exact form of local symmetries for the Abelian Proca and CS models, which are converted into first-class constrained systems by the BFT formalism, in the Lagrangian formalism. As a result, without resorting to a Hamiltonian formulation we obtain the well-known U(1) symmetry for the gauge-invariant Proca model, while showing that for the CS model there exist novel symmetries as well as the usual symmetry transformations.
Primary Prevention of Alzheimer’s Disease (AD)

Alzheimer dementia (AD) is a complex, aging-associated disease whose effects on the brain (an organ made up by nonreplaceable cells) are devastating. Disease is not curable, but progress in pathobiology shows that intervention on aging can make primary prevention of AD feasible. According to the amyloid-cascade hypothesis, mechanisms of AD include: an age-related alteration of free radical metabolism in membranes, leading to a higher yield in the toxic A β 1-42 peptide and an overwhelming impact on the weaker repair mechanisms of the aging cells. The proposed intervention on aging with anti-AD effects includes a daily assumption of antioxidants (red wine polyphenols enriched with resveratrol), a reinforcement of membrane antioxidant defenses by the assumption of polyunsaturated fatty acids at the first meal after fasting, and an enhancement of cell repair function (at the proteasome and autophagy level by an intermittent feeding regimen and physical exercise plus the assumption of antilipolytic agents during time of fasting). The beneficial effects of diet and physical activity on the endogenous production of protective nerve growth factors are magnified by an enriched environment. Treatment has already been started on healthy individuals at a higher risk of AD in the city of Volterra .
Profiling of Phospho-AKT, Phospho-mTOR, Phospho-MAPK and EGFR in Non-small Cell Lung Cancer

Activation of numerous pathways has been documented in non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) has emerged as a common therapeutic target. The mitogen-activated protein kinase (MAPK) and AKT signaling pathways are downstream of EGFR and deregulated via genetic and epigenetic mechanisms in many human cancers. We evaluated selected markers in the EGFR pathway with reference to outcome. Tissues from 220 cases of NSCLC patients presented in a tissue microarray were assayed with immunohistochemistry for phosphorylated AKT, phosphorylated MAPK, phosphorylated mTOR, and EGFR and then quantified by automated image analysis. Individually, the biomarkers did not predict. Combined as ratios, p-mTOR/p-AKT, and p-MAPK/EGFR function as prognostic markers of survival (p=0.008 and p=0.029, respectively), however, no significance was found after adjustment (p=0.221, p=0.103). The sum of these ratios demonstrates a stronger correlation with survival (p<0.001) and remained statistically significant after adjustment (p=0.026). The algebraic combination of biomarkers offer the capacity to understand factors that predict outcome better than current approaches of evaluating biomarkers individually or in pairs. Our results show the sum of p-mTOR/p-AKT and p-MAPK/EGFR is a potential predictive marker of survival in NSCLC patients.
Nanofunctionalized zirconia and barium sulfate particles as bone cement additives

Zirconia (ZrO2) and barium sulfate (BaSO4) particles were introduced into a methyl methacrylate monomer (MMA) solution with polymethyl methacrylate (PMMA) beads during polymerization to develop the following novel bone cements: bone cements with unfunctionalized ZrO2 micron particles, bone cements with unfunctionalized ZrO2 nanoparticles, bone cements with ZrO2 nanoparticles functionalized with 3-(trimethoxysilyl)propyl methacrylate (TMS), bone cements with unfunctionalized BaSO4 micron particles, bone cements with unfunctionalized BaSO4 nanoparticles, and bone cements with BaSO4 nanoparticles functionalized with TMS. Results demonstrated that in vitro osteoblast (bone-forming cell) densities were greater on bone cements containing BaSO4 ceramic particles after four hours compared to control unmodified bone cements. Osteoblast densities were also greater on bone cements containing all of the ceramic particles after 24 hours compared to unmodified bone cements, particularly those bone cements containing nanofunctionalized ceramic particles. Bone cements containing ceramic particles demonstrated significantly altered mechanical properties; specifically, under tensile loading, plain bone cements and bone cements containing unfunctionalized ceramic particles exhibited brittle failure modes whereas bone cements containing nanofunctionalized ceramic particles exhibited plastic failure modes. Finally, all bone cements containing ceramic particles possessed greater radio-opacity than unmodified bone cements. In summary, the results of this study demonstrated a positive impact on the properties of traditional bone cements for orthopedic applications with the addition of unfunctionalized and TMS functionalized ceramic nanoparticles.
Cooperation and Resource Sharing in Data Networks : A Delay Perspective

From multi-description/multi-path routing for multi-media applications to content distribution in P2P networks to community networking, many forms of resource sharing have been proposed to improve the network performance. From the perspective of any one user, when ignoring the interaction among users, all such schemes reduce to various forms of providing parallelism and, hence, increased throughput. In this paper, we argue that focusing on parallelism is by no means sufficient as it ignores the existence of many users with potentially similar strategies. In this paper, we illustrate the issue of resource sharing in the above context via a multi-queue multi-server problem. Although, our proposed model is not realistic in that it ignores the overhead inefficiencies, it does capture the trade-off between parallelism and reassembly/synchronization delay to a larger extent. We use this model to provide analytical results in a special case of homogeneous users and servers. Furthermore, we prove the robustness of a certain locally optimal strategy to noncooperation in a Nash equilibrium/strategy context.
Multifeedback-Layer Neural Network

The architecture and training procedure of a novel recurrent neural network (RNN), referred to as the multifeedback-layer neural network (MFLNN), is described in this paper. The main difference of the proposed network compared to the available RNNs is that the temporal relations are provided by means of neurons arranged in three feedback layers, not by simple feedback elements, in order to enrich the representation capabilities of the recurrent networks. The feedback layers provide local and global recurrences via nonlinear processing elements. In these feedback layers, weighted sums of the delayed outputs of the hidden and of the output layers are passed through certain activation functions and applied to the feedforward neurons via adjustable weights. Both online and offline training procedures based on the backpropagation through time (BPTT) algorithm are developed. The adjoint model of the MFLNN is built to compute the derivatives with respect to the MFLNN weights which are then used in the training procedures. The Levenberg-Marquardt (LM) method with a trust region approach is used to update the MFLNN weights. The performance of the MFLNN is demonstrated by applying to several illustrative temporal problems including chaotic time series prediction and nonlinear dynamic system identification, and it performed better than several networks available in the literature
Similarities and Differences in Cognitive Deficits and Responsiveness to L-Dopa between Aged and MPTP-Treated Cynomolgus Monkeys Tested on the Same Tasks

Cognitive and motor declines are two major geriatric problems often coexisting in older adults. Also, mild cognitive impairment (MCI) is frequently observed in patients with Parkinson’s disease (PD) in addition to motor dysfunction. Amelioration of cognitive deficits, either in patients with PD or in senescence, has proven problematic in the clinic; due, in part, to a poor understanding of the mechanism underlying PD-MCI and age-associated cognitive declines. Thus, a better characterization of similarities and differences between age-associated and disease-related cognitive impairments should help better design therapeutic strategies tailored to restore cognitive functions in either the elderly or PD patients. In the present study, eighteen cynomolgus monkeys were trained and tested on a delayed matching-toposition (DMTP) and delayed matching-to-sample (DMTS) task, including 6 middle-aged, 6 aged, and 6 MPTP-treated animals. After a 3-month break, cognitive testing was resumed in all animals both before and after a 4-day treatment regimen with oral L-dopa. Here, we are reporting that 1) delay-dependent declines in percentage accuracy were seen on both tasks in normal (MPTP naive) animals while only seen on the DMTP task in MPTP-treated animals, 2) animals with MPTP-induced dopamine deficiency had a greater difficulty learning and performing on the DMTS task compared to normal animals, 3) L-dopa treatment did not improve cognitive performance on either task in any animals, but rather led to a worsening in performance on the DMTP task in normal middle-aged and MPTP-treated animals, and 4) cognitive declines correlated with age only on the DMTS but not on the DMPT task. Our results suggest that cognitive impairments seen in animals with MPTP-induced dopamine deficiency differ from those seen in aged animals.
DCU-Paris13 systems for the SANCL 2012 shared task

The DCU-Paris13 team submitted three systems to the SANCL 2012 shared task on parsing English web text. The first submission, the highest ranked constituency parsing system, uses a combination of PCFG-LA product grammar parsing and self-training. In the second submission, also a constituency parsing system, the n-best lists of various parsing models are combined using an approximate sentence-level product model. The third system, the highest ranked system in the dependency parsing track, uses voting over dependency arcs to combine the output of three constituency parsing systems which have been converted to dependency trees. All systems make use of a data-normalisation component, a parser accuracy predictor and a genre classifier.
PEMAHAMAN GURU TERHADAP KETERAMPILAN PROSES SAINS (KPS) DAN PENERAPANNYA DALAM PEMBELAJARAN IPA SMP DI SALATIGA

Penelitian ini bertujuan untuk mengetahui pemahaman guru IPA SMP di Salatiga mengenai keterampilan proses sains dan bagaimana penerapannya dalam pembelajaran. Penelitian ini merupakan penelitian survei dengan mengunakan pendekatan kuantitatif non eksperimen. Subjek penelitian adalah seluruh guru IPA di 6 SMP di Salatiga. Teknik pengumpulan data menggunakan wawancara, kuesioner dan dokumentasi. Data yang diperoleh dianalisis secara deskriptif berdasarkan tahap pengumpulan data, reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan sebanyak 50% guru memiliki pemahaman tentang KPS dalam kategori baik dan 50% guru memiliki tingkat pemahaman yang cukup. Guru telah melakukan kegiatan-kegiatan yang mengajak siswa ke arah pengembangan KPS. Dari aspek dengan nilai persentase tertinggi hingga terendah antara lain: menginterpretasi data (85%), mengamati (71%), mengklasifikasi (57%), merumuskan masalah (57%), menyimpulkan (50%), mengkomunikasi (50%), mengindentifikasi (50%), mengukur (42%), dan melakukan ekperimen (28%). Aspek KPS telah diterapkan namun belum maksimal karena kurangnya waktu belajar mengajar, belum juga memiliki laboratorium dan juga lembar kerja siswa (LKS) dan rendahnya motivasi siswa.
Stem Cell Biomarkers in Chronic Myeloid Leukemia

Chronic myeloid leukemia (CML) is a clonal multi-step myeloproliferative disease that is initially produced and ultimately sustained by a rare subpopulation of BCR-ABL+ cells with multi-lineage stem cell properties. These BCR-ABL+ CML stem cells are phenotypically similar to normal hematopoietic stem cells which are also maintained throughout the course of the disease at varying levels in different patients. Defining the unique properties of the leukemic stem cells that produce the chronic phase of CML has therefore had to rely heavily on access to samples from rare patients in which the stem cell compartment is dominated by leukemic elements. Here we review past and ongoing approaches using such samples to identify biologically and clinically relevant biomarkers of BCR-ABL+ stem cells that explain their unusual biology and that may help to design, or at least predict, improved treatment responses in CML patients. These studies are of particular interest in light of recent evidence that chronic phase CML stem cells are not only innately resistant to imatinib mesylate and other drugs that target the BCR-ABL oncoprotein, but are also genetically unstable.
Specificity in Rehabilitation of Word Production: A Meta-Analysis and a Case Study

Speech production impairment is a frequent deficit observed in aphasic patients and rehabilitation programs have been extensively developed. Nevertheless, there is still no agreement on the type of rehabilitation that yields the most successful outcomes. Here, we ran a detailed meta-analysis of 39 studies of word production rehabilitation involving 124 patients. We used a model-driven approach for analyzing each rehabilitation task by identifying which levels of our model each task tapped into. We found that (1) all rehabilitation tasks are not equally efficient and the most efficient ones involved the activation of the two levels of the word production system: the phonological output lexicon and the phonological output, and (2) the activation of the speech perception system as it occurs in many tasks used in rehabilitation is not successful in rehabilitating word production. In this meta-analysis, the effect of the activation of the phonological output lexicon and the phonological output cannot be assessed separately. We further conducted a rehabilitation study with DPI, a patient who suffers from a damage of the phonological output lexicon. Our results confirm that rehabilitation is more efficient, in terms of time and performance, when specifically addressing the impaired level of word production.
LSF-CMA Equalization Algorithm for OFDM System using Zero-Padding Technique

We introduce an adaptive channel equalization algorithm for orthogonal frequency division multiplexing (OFDM) employing high bandwidth-efficiency quadratic amplitude modulation (QAM) signaling. Our approach uses the guard band to yield a unique equalizer estimate through a least square fitting (LSF) criterion. To refine the equalizer estimation, a combination of a LSF and constant modulus algorithm (CMA) based equalizer is proposed. In order to minimize the error of the overall structure, a stochastic gradient algorithm is implemented. It is shown that the proposed scheme is superior and more robust in low signal to noise ratio (SNR) environments. Simulation results demonstrate that using the combination scheme improves adaptive channel equalization by increasing convergence rate and decreasing the steady-state mean square error.
Palliative care education – does it influence future practice?

Abstract A group of year 3 undergraduate nursing students enrolled in an Oncology and Palliative Care Course took part in a study designed to uncover if their subsequent learning had a positive impact upon their capacity to practise palliative care. All the participants reported that the course assisted them in the clinical provision of palliative care.
Cluster Analytic Detection of Disgust-Arousal

Automated detection of disgust-arousal could have applications in diagnosing and treating obsessive-compulsive disorder and Huntington’s disease. For achieving this ability, experimental data was used first to examine the thermal response of “facial muscles of disgust” to other common negative and positive expressions of emotive states. An attempt was then made to detect disgust-arousal through classification of affect-educed thermal variations measured along the facial muscles. Initial results suggest (i) muscles of disgust experience different levels of thermal variations under the influence of various emotive state and (ii) emotion-educed facial thermal patterns can be modeled as stochastically independent clusters to be separated as linear spaces and making automated detection of disgust-arousal possible.
Sandbagging and the Self: Does Narcissism Explain the Relationship Between Sandbagging and Self-Esteem?

Sandbagging – a self-presentation strategy defined by feigned performance or false claims of inability – has been associated with lower self-esteem. The purpose of this study was to investigate whether narcissism explains the relationship between sandbagging and self-esteem. College students (N = 813) completed a survey. Grandiose and vulnerable narcissism explained variance in sandbagging beyond what was explained by self-esteem. When grandiose or vulnerable narcissism was included, the relationship between self-esteem and sandbagging was no longer significant. Overall, the results were consistent with the notion that the relationship between lower self-esteem and sandbagging may be subsumed by narcissism.
Social Networks and the Political Salience of Ethnicity

Ethnic politics scholars are increasingly convinced that (a) the political salience of ethnicity and (b) the correlation between ethnolinguistic fractionalization (ELF) and poor development are driven by the dense social networks shared by co-ethnics. By this argument, social networks allow ethnic parties to leverage inbuilt networks to share information and support collective action, while ethnically fragmented communities struggle to hold politicians accountable. This paper provides the first comprehensive empirical test of the assumption underlying this argument. Using seven months of telecommunications data from 9 million mobile subscribers in Zambia — which includes records of almost 2 billion calls and SMS messages — to measure social networks across an entire country, this paper finds that electoral constituencies with high ELF also have more fragmented social networks, especially in rural areas. It also finds other potential cleavages that have not achieved political salience (namely, religious identity and employment sector) are not correlated with network fragmentation, consistent with the idea that ethnicity achieves salience because it offers an organizational advantage not offered by other cleavages. Finally, it also finds that both voter knowledge and public goods are negatively correlated with network fragmentation, consistent with the network-proxy hypothesis. ∗This project would not have been possible without the generosity of numerous parties, including Real Impact Analytics, Real Impact’s Chief Data Scientists Gautier Krings, and its CEO Sébastien Deletaille. The author is also indebted to Ramya Parthasarathy, Ernest Online Appendix available from: http://dx.doi. org/10.1561/100.00017044_app Supplementary Material available from: http://dx.doi. org/10.1561/100.00017044_supp MS submitted on 15 March 2017; final version received 30 July 2018 ISSN 1554-0626; DOI 10.1561/100.00017044 © 2019 N. Eubank
Selective harmonic elimination multilevel converter control with variant DC sources

This paper presents a new variation of selective harmonic elimination (SHE) technique for cascaded multilevel converter with variant DC voltage sources. The paper formulates the problem in a way which the levels of the DC sources are made variables within certain constraints. Therefore, the degrees of freedom for specifying the cost function are doubled when compared to existing family of techniques and for the same physical structure. Moreover, the proposed formulation provides an output with wider range of modulation indices without affecting the number of harmonics being eliminated. The theoretical findings are validated through extensive simulation studies.