Miracle-dz/UniFAR-FTUs huggingface dataset:
CHANGES IN TEACHERS' PRACTICES WHILE ASSUMING NEW LEADERSHIP ROLES

Jo Clay OlsonUniversity of Colorado at Denver This study explores the notion that as teachers develop their leadership skills their classroom practices gradually reflect a reform orientation. Within a systemic change project, an 18-month leadership institute was designed to nurture teachers’ professional growth and to develop the skills and knowledge needed to plan and present mathematics reform recommendations to colleagues. Changes in teachers’ practices were investigated using a case-study design by analyzing the questions asked, the cognitive demand of the instructional tasks posed, and the questions asked on formal assessments. Findings from this study suggest that teachers’ practices change when they examine their own teaching practices. Despite calls for reform in school mathematics by The National Council of Teachers of Mathematics (NCTM, 1980, 1989, 2000) classroom practices in United States during the last century have shown little change (Cuban, 1993; Stigler & Hieber, 1999). To support mathematics reform, NCTM (1991) described a need for mathematics teacher leaders who would become specialists “positioned between classroom teachers and administration” (p. 375) to assist with the improvement of mathematics education. These teachers would be responsible for building the content and pedagogical knowledge of colleagues, refocusing conversations from activities to an analysis of practice, and arranging collaborative investigations about student thinking.Studies that examine teacher leadership are built upon the belief that, as teachers enhance their leadership skills and emerge as leaders, their practice also evolves (e.g.,Louckes-Horsely et al., 1998; Swanson, 2000). It is assumed that as teachers develop their leadership qualities, they gradually assimilate a reform orientation and their practice changes. The current study extends the research base on teacher leadership and change by examining this assumption. More specifically, this study asked the following question: How do teachers’ classroom practices, as evidenced by their classroom discourse, instructional tasks posed, and assessments, change while participating in a leadership institute designed to promote professional growth? THEORETICAL ORIENTATION The research question focused my attention on the psychological processes of teacher change within a mathematics classroom. Symbolic interactionism facilitates the interpretation of the interactions between people as indications of personally constructed meaning (Becker & McCall, 1990; Denzin, 1992). Communication is thought to be a symbolic process that consists of an ensemble of social practices (including language, intonation, gestures, and written symbolic representations) that portray an individual’s private construction of knowledge. Thus, an individual’s interactions can be analyzed and interpreted to indicate this constructed knowledge
Today ’ s Research on Aging

As Americans live longer, researchers have begun to investigate how people can move into old age not just healthier, but also happier. Increasingly, researchers are exploring relationships between physical and mental health and social connections among the elderly. The Behavioral and Social Research Program at the National Institute on Aging (NIA) supports research on the relationships between aging and social connections. This newsletter will review recent NIAsponsored and other research that explores these relationships, especially research on the ways social networks affect health and happiness and influence longevity.
Building and Scheduling Coarse Grain Task Graphs Ecole Normale Supérieure De Lyon Building and Scheduling Coarse Grain Task Graphs Building and Scheduling Coarse Grain Task Graphs

It has been shown recently that it is possible to eeciently schedule direct acyclic task graphs. A tool like Pyrros 14] is able to generate a parallel program, if the user speciies precedence constraints between the tasks. This approach has two major drawbacks: it is hard for the user to perform a good analysis of the source code and scheduling a DAG is costly in terms of memory and time. In 3], a new model of parallel computation, the parameterized task graph is introduced. The Parameterized Task Graph (PTG) is a compact, problem size independent representation of some frequently used direct acyclic task graphs. In 4, 10], techniques and a tool (PlusPyr), are designed to generate such a representation from an annotated sequential program. In this report, we review the PTG and associated techniques, we give a general framework and an algorithm to dynamically schedule the parameterized graph and generate the associated code. On a montr e r ecemment qu'il est possible d'ordonnancer eecacement un graphe de t^ aches acyclique. Un outil comme Pyrros 14] est capable de g en erer un programme parall ele si l'utilisateur sp eciie les contraintes de pr ec edence entre les t^ aches. Cette approche a deux d efauts majeurs : il est diicile pour l'utilisateur de faire une bonne analyse du code source et ordonnancer un graphe acyclique est co^ uteux en termes de temps et de m emoire. Dans 3], un nouveau mod ele de calcul parall ele, le graphe de t^ aches param etr e a et e introduit. Le GTP est une repr esentation compacte, ind ependante de la taille du probl eme, de quelques graphes de t^ aches acycliques orient es fr equemment utilis es. Dans 4, 10], des techniques et un outil (PlusPyr) sont construit pour g en erer une telle repr esentation a partir d'un programme s equentiel annot e. Dans ce rapport, nous revoyons le GTP et les techniques associ es, nous donnons une structure g en erale et un algorithme pour ordonnancer dynamiquement le graphe param etr e et g en erer le code associ e.
Short-SET: An energy-efficient write scheme for MLC PCM

Phase change memory (PCM) has many advantages over the traditional DRAM technology, hence it becomes a promising candidate for main memory. Multi-level cell (MLC) PCM has the benefits of higher capacity and lower cost-per-bit due to store multiple bits in a single cell. However, MLC PCM employs an iterative write scheme, which is precise, reliable but slow, incurring adverse impact on the system performance. In this work, we analyzed the characteristics of the SET pulse in PCM, and modeled the relationship of the resistance and the SET pulse in MLC. Based on the analysis, we proposed a short SET pulse as an iterative pulse for MLC, so as to accelerate the MLC PCM write operation without the reliability degradation. Experimental results show that the Short-SET write scheme could effectively alleviate the long write problem of MLC PCM and improve the system performanceby 90%. Meanwhile, the write power is reduced by 23%.
Validation of mixed-structured data using pattern mining and information extraction

For large-scale data mining utilizing data from ubiquitous and mixed-structured data sources, the appropriate extraction and integration into a comprehensive data-warehouse is of prime importance. Then, appropriate methods for validation and potential refinement are essential. This paper presents an approach applying data mining and information extraction methods for data validation: We apply subgroup discovery and (rule-based) information extraction for data integration and validation. The methods are integrated into an incremental process for continuous validation options. The results of a medical application demonstrate that subgroup discovery and the applied information extraction methods are well suited for mining, extracting and validating clinically relevant knowledge.
Downlink MMSE Transceiver Optimization for Multiuser MIMO Systems: MMSE Balancing

We study the problem of mean square error (MSE) transceiver design for point-to-multipoint transmission in multiuser multiple-input-multiple-output (MIMO) systems. We focus on four optimization problems: minimizing the maximum weighted layer-wise or user-wise MSE under a total power constraint; minimizing the total transmit power subject to a set of layer-wise or user-wise MSE requirements. The non-convexity of these problems makes the derivation of globally optimal algorithms very difficult for transceiver design. New optimal power allocation strategies are derived for the problems considered here. Based on the power allocation, we study how this can be used for iterative transceiver optimization. We propose iterative algorithms and prove the monotonic convergence of the algorithms. The major advantages of the proposed algorithms are their low complexity and fast convergence behavior during the first few iterations. The proposed algorithms are suitable not only for downlink transmission, but also for uplink transmission with a total power constraint.
BayGenomics: a resource of insertional mutations in mouse embryonic stem cells

The BayGenomics gene-trap resource (http://baygenomics.ucsf.edu) provides researchers with access to thousands of mouse embryonic stem (ES) cell lines harboring characterized insertional mutations in both known and novel genes. Each cell line contains an insertional mutation in a specific gene. The identity of the gene that has been interrupted can be determined from a DNA sequence tag. Approximately 75% of our cell lines contain insertional mutations in known mouse genes or genes that share strong sequence similarities with genes that have been identified in other organisms. These cell lines readily transmit the mutation to the germline of mice and many mutant lines of mice have already been generated from this resource. BayGenomics provides facile access to our entire database, including sequence tags for each mutant ES cell line, through the World Wide Web. Investigators can browse our resource, search for specific entries, download any portion of our database and BLAST sequences of interest against our entire set of cell line sequence tags. They can then obtain the mutant ES cell line for the purpose of generating knockout mice.
A virtual human architecture that integrates kinematic, physical and behavioral aspects to control H-Anim characters

Virtual humans are being increasingly used in different domains. Virtual human modeling requires to consider aspects belonging to different levels of abstractions. For example, at lower levels, one has to consider aspects concerning the geometric definition of the virtual human model and appearance while, at higher levels, one should be able to define how the virtual human behaves into an environment. H-Anim, the standard for representing humanoids in X3D/VRML worlds, is mainly concerned with low-level modeling aspects. As a result, the developer has to face the problem of defining the virtual human behavior and translating it into lower levels (e.g. geometrical and kinematic aspects). In this paper, we propose VHA (Virtual Human Architecture), a software architecture that allows one to easily manage an interactive H-Anim virtual human into X3D/VRML worlds. The proposed solution allows the developer to focus mainly on high-level aspects of the modeling process, such as the definition of the virtual human behavior.
Polynomial Time Joint Structural Inference for Sentence Compression

We propose two polynomial time inference algorithms to compress sentences under bigram and dependency-factored objectives. The first algorithm is exact and requires O(n 6 ) running time. It extends Eisner’s cubic time parsing algorithm by using virtual dependency arcs to link deleted words. Two signatures are added to each span, indicating the number of deleted words and the rightmost kept word within the span. The second algorithm is a fast approximation of the first one. It relaxes the compression ratio constraint using Lagrangian relaxation, and thereby requires O(n 4 ) running time. Experimental results on the popular sentence compression corpus demonstrate the effectiveness and efficiency of our proposed approach.
On Differencing Object-Oriented Formal Specifications

Requirements specification is a collaborative activity that involves several developers specifying the requirements elicited through several stakeholders. Operation-base merging allows combining specifications using the information available about their state as well as their evolution or change. Thus, leading to a more precise, accurate and efficient merging. Differencing specifications is a tedious, complicated, and a crucial process needed for operation-based merging of specifications resulting from collaboration. An approach for differencing Object-Oriented formal specifications is proposed in this paper. The difference is modeled as a set of primitive operations and is produced based on the matching results of specifications’ elements. These matchings are calculated based on an approach employing elements’ syntactic and structural similarities. The proposed differencing approach is empirically validated.
Structural changes accompanying GTP hydrolysis in microtubules: information from a slowly hydrolyzable analogue guanylyl-(alpha,beta)- methylene-diphosphonate

We have used cryoelectron microscopy to try to understand the structural basis for the role of GTP hydrolysis in destabilizing the microtubule lattice. We have measured a structural difference introduced into microtubules by replacing GTP with guanylyl- (alpha,beta)-methylene-diphosphonate (GMPCPP). In a stable GMPCPP microtubule lattice, the moire patterns change and the tubulin subunits increase in size by 1.5 A. This information provides a clue to the role of hydrolysis in inducing the structural change at the end of a microtubule during the transition from a growing to a shrinking phase.
Probabilistic reconstruction in compressed sensing: algorithms, phase diagrams, and threshold achieving matrices

Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make fewer measurements than were considered necessary to record a signal, enabling faster or more precise measurement protocols in a wide range of applications. Using an interdisciplinary approach, we have recently proposed in Krzakala et al (2012 Phys. Rev. X 2 021005) a strategy that allows compressed sensing to be performed at acquisition rates approaching the theoretical optimal limits. In this paper, we give a more thorough presentation of our approach, and introduce many new results. We present the probabilistic approach to reconstruction and discuss its optimality and robustness. We detail the derivation of the message passing algorithm for reconstruction and expectation maximization learning of signal-model parameters. We further develop the asymptotic analysis of the corresponding phase diagrams with and without measurement noise, for different distributions of signals, and discuss the best possible reconstruction performances regardless of the algorithm. We also present new efficient seeding matrices, test them on synthetic data and analyze their performance asymptotically.
A new recommendation algorithm using distributed learning automata and graph partitioning

Recommendation systems aim at directing users toward the resources that best meet their needs and interests. In this paper, we propose a new recommendation algorithm based on a hybrid method of distributed learning automata and graph partitioning. The proposed method utilizes usage data and hyperlink graph of the web site. The idea of the proposed method is that an appropriate recommendation for a user can be pages similar to the pages the user has already visited. To calculate similarities between pages, it is assumed that if different users request a couple of pages together, these pages are likely to correspond to the same information need therefore can be considered similar. Experiments on synthetic and real data show that the proposed algorithm provides better recommendations than the only learning automata based recommendation method reported in the literature.
Granulocytic Sarcoma of the Uterus: A Rare Presentation of Extramedullary Relapse of AML and Importance of MRI

Granulocytic sarcoma (GS) is a solid tumor that is the extramedullary presentation of acute myelogenous leukemia, other myeloproliferative disorders, or myelodysplastic syndromes. Less commonly, it also may arise as an isolated mass. In this report, we describe a 23-year-old female patient, with a GS in the uterus and we stress the value of diffusion weighted imaging for the evaluation of uterine neoplasms. To our knowledge, our case is the first in the literature to report diffusion weighted imaging (DWI) findings of GS.
Reduction of Midline Shift Following Decompressive Hemicraniectomy for Malignant Middle Cerebral Artery Infarction

Background and Purpose Hemicraniectomy is a decompressive surgery used to remove a large bone flap to allow edematous brain tissue to bulge extracranially. However, early indicators of the decompressive effects of hemicraniectomy are unclear. We investigated whether reduction of midline shift following hemicraniectomy is associated with improved consciousness and survival in patients with malignant middle cerebral artery infarctions. Methods We studied 70 patients with malignant middle cerebral artery infarctions (MMI) who underwent hemicraniectomies. Midline shift was measured preoperatively and postoperatively using computed tomography (CT). Consciousness level was evaluated using the Glasgow Coma Scale on postoperative day 1. Patient survival was assessed six months after stroke onset. Results The median time interval between preoperative and postoperative CT was 8.3 hours (interquartile range, 6.1–10.2 hours). Reduction in midline shift was associated with higher postoperative Glasgow Coma Scale scores (P<0.05). Forty-three patients (61.4%) were alive at six months after the stroke. Patients with reductions in midline shifts following hemicraniectomy were more likely to be alive at six months post-stroke than those without (P<0.001). Reduction of midline shift was associated with lower mortality at six months after stroke, after adjusting for age, sex, National Institutes of Health Stroke Scale score, and preoperative midline shift (adjusted hazard ratio, 0.71; 95% confidence interval, 0.62–0.81; P<0.001). Conclusions Reduction in midline shift following hemicraniectomy was associated with improved consciousness and six-month survival in patients with MMI. Hence, it may be an early indicator of effective decompression following hemicraniectomy.
3-D Cueing: A Data Filter For Object Recognition

This paper presents a novel method for quickly ﬁltering range data points to make object recognition in large 3D data sets feasible. The general approach, called “3D cueing,” uses shape signatures from object models as the basis for a fast, probabilistic classiﬁcation sys-tem which rates scene points in terms of their likelihood of belonging to a model. This algorithm, which could be used as a front-end for any traditional 3D matching technique, is demonstrated using several models and cluttered scenes in which the model occupies between 1% and 50% of the data points.
Moving Object Trajectories Meta-Model And Spatio-Temporal Queries

In this paper, a general moving object trajectories framework is put forward to allow independent applications processing trajectories data benefit from a high level of interoperability, information sharing as well as an efficient answer for a wide range of complex trajectory queries. Our proposed meta-model is based on ontology and event approach, incorporates existing presentations of trajectory and integrates new patterns like space-time path to describe activities in geographical space-time. We introduce recursive Region of Interest concepts and deal mobile objects trajectories with diverse spatio-temporal sampling protocols and different sensors available that traditional data model alone are incapable for this purpose.
Moving target detection in multi-channel quantum video

The study proposes a method for moving object detection in multi-channel quantum video. The proposed method could detect the location of the moving target in each frame of the quantum video thereby providing a motion trail that could be used to describe the path or trajectory of the object. In validating our proposed technique, we employed a simple simulation experiment in which we detected the moving object in a short six-frame quantum video. This work presents a modest attempt to utilize quantum computing properties for moving target in quantum video research.
Causes and consequences of error in digital elevation models

All digital data contain error and many are uncertain. Digital models of elevation surfaces consist of files containing large numbers of measurements representing the height of the surface of the earth, and therefore a proportion of those measurements are very likely to be subject to some level of error and uncertainty. The collection and handling of such data and their associated uncertainties has been a subject of considerable research, which has focused largely upon the description of the effects of interpolation and resolution uncertainties, as well as modelling the occurrence of errors. However, digital models of elevation derived from new technologies employing active methods of laser and radar ranging are becoming more widespread, and past research will need to be re-evaluated in the near future to accommodate such new data products. In this paper we review the source and nature of errors in digital models of elevation, and in the derivatives of such models. We examine the correction of errors and assessment of fitness for use, and finally we identify some priorities for future research.
An analysis of entrepreneurship education (Birmingham Business School 2007-2009)

This research examines university students’ perceptions of entrepreneurship education at the Birmingham Business School. The objectives of this study were to examine the effectiveness of the undergraduate and postgraduate entrepreneurship modules at the Business School based on students’ perceptions. At present little research is available concerning the effects of the recession in 2009 on students’ perceptions about entrepreneurship education so it was decided to examine this for this research. Thirdly differences and similarities between two undergraduate year groups were examined in order to identify any themes concerning the undergraduate entrepreneurship module. Finally the relationship between student satisfaction and the likelihood of students setting up a business was examined. Three questionnaires were administered to undergraduate and postgraduate students who completed entrepreneurship modules at the Business School. Several telephone interviews were also conducted with undergraduate students to help expand on the questionnaire findings. The results show similarities between the two undergraduate years and it was recognised that the undergraduate module requires improvement. The recession impacted upon students’ perceptions of entrepreneurship education and no relationship between student satisfaction with the undergraduate module and the likelihood of setting a business was found indicating other factors may influence students’ intentions of setting up a business.