Miracle-dz/UniFAR-FTUs huggingface dataset:
Defining and Applying Leadership: Perceptions of Teacher Leader Candidates.

This study examined shifts in perceptions of the meaning of leadership and necessary leadership skills held by 18 teachers in a graduate program on teacher leadership. Participants were queried twice regarding their definitions of leadership; once at the outset of their degree program and again 1 year later. In between, they took classes in leadership and mentor training, professional standards, school climate, legal and fiscal management, public relations and community resources, and parent and family involvement. Two Likert-scale surveys examined their perceptions of the importance of 11 leadership skills and of the extent to which they attained growth in each skills. Results found little variation in the relative importance participants assigned to the skills. Confidence emerged as the most important skill, followed by two skills that involved the participation of others in tasks undertaken by the teacher leader. Participants varied more widely in their assessment of personal growth in leadership skills. They perceived the greatest growth in knowledge of educational issues and understanding leadership styles. Initially, most participants defined leadership under the figurehead category. Midway through the program, half of them changed to define leadership in terms of the cheerleader/team player category. (Contains 15 references.) (SM) Reproductions supplied by EDRS are the best that can be made from the original document.
Cleaning the GenBank Arabidopsis thaliana data set.

Data driven computational biology relies on the large quantities of genomic data stored in international sequence data banks. However, the possibilities are drastically impaired if the stored data is unreliable. During a project aiming to predict splice sites in the dicot Arabidopsis thaliana, we extracted a data set from the A.thaliana entries in GenBank. A number of simple 'sanity' checks, based on the nature of the data, revealed an alarmingly high error rate. More than 15% of the most important entries extracted did contain erroneous information. In addition, a number of entries had directly conflicting assignments of exons and introns, not stemming from alternative splicing. In a few cases the errors are due to mere typographical misprints, which may be corrected by comparison to the original papers, but errors caused by wrong assignments of splice sites from experimental data are the most common. It is proposed that the level of error correction should be increased and that gene structure sanity checks should be incorporated--also at the submitter level--to avoid or reduce the problem in the future. A non-redundant and error corrected subset of the data for A.thaliana is made available through anonymous FTP.
The use of low-cost technologies for the promotion of Cultural Heritage sites: The case study of Veleia

In the Cultural Heritage field, thanks to the recent development of digital technologies, a large variety of sites and artifacts could benefit from their free access and promotion through the web. But despite these achievements, the high costs that are generally connected with their use often limit their widespread. As a consequence, during the last two decades, scientific research is developing new tools and methodologies aimed at overcoming this problem. In particular, for example, researches in the field of image-based technologies and the development of open-source algorithms and software aimed at helping the processing, management and visualization of 3d data through the web represent remarkable attempts to extend the use of digital technologies in the Cultural Heritage field. This contribution shows the main steps of a project aimed at testing low-cost technologies within the multi-scalar digitization process of sites and artifacts. Thus these technologies still cannot provide analogous results in terms of definition and accuracy that it is possible to achieve using more expensive technologies (e.g. range-based technologies), they can supply low-resolution reality-based 3d models and effective representations that can be easily accessed through the web, with evident benefits in cultural contents sharing and promotion. Within a multi-scalar approach, the building of these kinds of models represents the first step of a process that, starting from low-resolution acquisitions, can improve the detail and definition of 3d digital models of artifacts by gradually adopting different methodologies and technologies. As a consequence, this approach can provide evident benefits on the achievement of different communication purposes, ranging from simple visualizations for popular aims to accurate and faithful digital replicas that can be fruited by different and changing users. Moreover, the adoption of this approach is particularly important within education processes aimed at training expert operators able to speed and therefore to further reduce costs connected with the digitization of Cultural Heritage.
Clinical, genetic and neuropathological features of frontotemporal dementia: an update and guide.

INTRODUCTION Frontotemporal Lobar Degeneration encompasses a group of heterogeneous disorders with shared behavioural and cognitive symptoms, as well as gross pathological features. The genetic underpinnings and histopathological aspects are quite diverse and form the basis of molecular classification, which is not easy to correlate with clinical findings and syndromes. Scientific research has brought to light an array of knowledge, often not easy to keep up with, especially in the last few years with regard to genetics and histopathology. MATERIAL AND METHODS The authors have searched the published literature on this topic, chose relevant references, and extracted and systematized the data. RESULTS AND CONCLUSION this manuscript presents an updated review of clinical, genetic and histopathological findings in Frontotemporal Lobar Degeneration, with special focus on behavioural variant Frontotemporal Dementia, the most common disorder. Current management is also reviewed, and genetic testing strategies are proposed by the authors for use in clinical practice. Public awareness on this group of disorders should be raised.
Design of a Multithreaded Barnes-Hut Algorithm for Multicore Clusters

We describe in this paper an implementation of the Barnes-Hut algorithm on multicore clusters. Based on a partitioned global address space (PGAS) library, the design integrates intranode multithreading and internode one-sided communication, exemplifying a PGAS + X programming style. Within a node, the computation is decomposed into tasks (subtasks) and multitasking is used to hide network latency. We study the tradeoffs between locality in private caches and locality in shared caches and bring the insights into the design. As a result, our implementation consumes less memory per core, invokes less internode communication, and enjoys better load-balancing strategies. The final code achieves up to 41 percent performance improvement over a non-multithreaded counterpart. Through detailed comparison, we also show its advantages over other well-known Barnes-Hut implementations, both in programming complexity and in performance.
From Gabor Magnitude to Gabor Phase Features: Tackling the Problem of Face Recognition under Severe Illumination Changes

Among the numerous biometric systems presented in the literature, face recognition systems have received a great deal of attention in recent years. The main driving force in the development of these systems can be found in the enormous potential face recognition technology has in various application domains ranging from access control, human-machine interaction and entertainment to homeland security and surveillance (Struc et al., 2008a). While contemporary face recognition techniques have made quite a leap in terms of performance over the last two decades, they still struggle with their performance when deployed in unconstrained and uncontrolled environments (Gross et al., 2004; Phillips et al., 2007). In such environments the external conditions present during the image acquisition stage heavily influence the appearance of a face in the acquired image and consequently affect the performance of the recognition system. It is said that face recognition techniques suffer from the so-called PIE problem, which refers to the problem of handling Pose, Illumination and Expression variations that are typically encountered in real-life operating conditions. In fact, it was emphasized by numerous researchers that the appearance of the same face can vary significantly from image to image due to changes of the PIE factors and that the variability in the images induced by the these factors can easily surpass the variability induced by the subjects’ identity (Gross et al., 2004; Short et al., 2005). To cope with image variability induced by the PIE factors, face recognition systems have to utilize feature extraction techniques capable of extracting stable and discriminative features from facial images regardless of the conditions governing the acquisition procedure. We will confine ourselves in this chapter to tackling the problem of illumination changes, as it represents the PIE factor which, in our opinion, is the hardest to control when deploying a face recognition system, e.g., in access control applications. Many feature extraction techniques, among them particularly the appearance based methods, have difficulties extracting stable features from images captured under varying illumination conditions and, hence, perform poorly when deployed in unconstrained environments. Researchers have, therefore, proposed a number of alternatives that should compensate for the illumination changes and thus ensure stable face recognition performance. 12
CloudAssoc: A pipeline for imputation based genome wide association study on cloud

Genome wide association study (GWAS) has been proved to be an efficient approach to identify susceptibility genes for complex diseases. In order to increase the power for detecting the disease causal variants, imputation has been used to predict genotype dosages of untyped variants on the basis of linkage disequilibrium evaluated by public data. However, as the volume of data grows, time-consuming of imputation based association study becomes extremely large. We developed a cloud based pipeline to implement data format conversion, imputation, quality control and association study based on Map/Reduce framework which can aid biologists to accelerate the identification and evaluation of susceptibility genes for complex diseases and make it easier to combine GWAS data from worldwide for meta analysis.
Approximate Reasoning Based on Interval-valued Intuitionistic Fuzzy Sets

This paper presents a new approximate reasoning method based on interval-valued intuitionistic fuzzy sets ( IvIFSs), where the fuzzy terms in the production rules of rule-based system are represented by IvIFSs rather than interval-valued fuzzy sets or ordinary fuzzy sets. The proposed method is more flexible than the ones presented in [7, 12]. Moreover, it can be executed much faster since it requires only simple arithmetic operations.
Wavelet-Based Compressed Sensing Using Low Frequency Coefficients

Signal models such as wavelet trees, block sparsity and statistical models are integrated into compressed sensing (CS) recovery algorithms in order to improve recovery accuracy and decrease the number of measurements. However, there are many constraints in practical applications. This paper introduces a new simple and efficient model based on the fact that low frequency coefficients are more important than others in wavelet domain. Furthermore, a degradation algorithm is designed to convert two-dimensional images to one-dimensional signals. This process makes the representations of images more sparse under a fixed wavelet basis. The proposed model and the degradation algorithm are successfully incorporated into two CS algorithms, including iteratively reweighted l1 minimization (IRL1) and iterative hard thresholding (IHT). Extensive experiments demonstrate that the proposed algorithms are significantly effective to improve recovery accuracy.
An approach towards debiasing user ratings

With increasing importance of e-commerce, many websites have emerged where users can express their opinions about products, such as movies, books, songs, etc. Such interactions can be modeled as bipartite graphs where the weight of the directed edge from a user to a product denotes a rating that the user imparts to the product. These graphs are used for recommendation systems and discovering most reliable (trusted) products. For these applications, it is important to capture the bias of a user when she is rating a product. Users have inherent bias---many users always impart high ratings while many others always rate poorly. It is necessary to know the bias of a reviewer while reading the review of a product. It is equally important to compensate for this bias while assigning a ranking for an object. In this paper, we propose an algorithm to capture the bias of a user and then subdue it to compute the true rating a product deserves. Experiments show the efficiency and effectiveness of our system in capturing the bias of users and then computing the true ratings of a product.
Numi: A Framework for Collaborative Data Management in a Network of InfoStations

A network of infostations offering high bandwidth islands of data connectivity has often been suggested as a viable alternative to cellular WAN for providing network connectivity for mobile devices. Current data management models proposed for such networks treat these infostations mainly as passive entities that offer devices in range, access to needed information. In this paper, we propose a novel approach wherein infostations actively participate in delivering content even to devices that are not in range. Other participating mobile devices that have excess spare capacity are used as carrier nodes to transport data towards remote devices. Short range wireless technologies enabling creation of ad-hoc peer-to-peer networking capabilities between devices are used to form transient communities to exchange information. The infostations are responsible for selecting appropriate carrier devices to use so that these carriers meet the device in need at the appropriate time to participate in this collaboration. Through this, dependency on the more expensive WAN networks is minimized. We present a design of our proposed framework and its components along with a prototype implementation.
Kinetic Approaches to Understanding the Mechanisms of Fidelity of the Herpes Simplex Virus Type 1 DNA Polymerase

We discuss how the results of presteady-state and steady-state kinetic analysis of the polymerizing and excision activities of herpes simplex virus type 1 (HSV-1) DNA polymerase have led to a better understanding of the mechanisms controlling fidelity of this important model replication polymerase. Despite a poorer misincorporation frequency compared to other replicative polymerases with intrinsic 3′ to 5′ exonuclease (exo) activity, HSV-1 DNA replication fidelity is enhanced by a high kinetic barrier to extending a primer/template containing a mismatch or abasic lesion and by the dynamic ability of the polymerase to switch the primer terminus between the exo and polymerizing active sites. The HSV-1 polymerase with a catalytically inactivated exo activity possesses reduced rates of primer switching and fails to support productive replication, suggesting a novel means to target polymerase for replication inhibition.
Preparing Rural Educators To Teach Students in an Era of Standards-Based Reform and Accountability.

The No Child Left Behind Act of 2001 requires that all teachers receive state certification by the end of the 2005-06 school year. Waivers will no longer be allowed. Each state has established standards for licensing teachers. Licensure tests aligned with teacher preparation standards are required for certification. As a result of teacher shortages, many states have implemented alternative certification programs to get teachers into classrooms quickly. In spite of great unevenness in alternative certification program quality, such programs provide an important way for prospective rural teachers to become credentialed. A Minnesota study examined whether the use of teachers without full certification affected the performance of either rural or urban students. Student achievement and teacher characteristic data for all 331 Minnesota school districts with secondary students indicated that rural teachers had more experience than nonrural teachers, but were less likely to have a master's degree. Nine percent of rural teachers were teaching out of their field of licensure or under an emergency permit, compared to 5.2 percent of nonrural teachers. Teacher experience had a significant negative impact on student achievement in math and reading. Students of teachers who were relatively better paid had higher math and reading achievement. Neither teacher experience or pay had any effect on writing achievement. Differences in teacher qualifications had little impact on student achievement in math, reading, or writing. Policy implications are discussed. (Contains 25 references) (TD) Reproductions supplied by EDRS are the best that can be made from the original document. Preparing Rural Educators to Teach Students in an Era of Standards-Based Reform and Accountability
N ov 2 00 3 AJ X-ray Underluminous Active Galactic Nuclei Relative to Broad Emission Lines in Ultraluminous Infrared Galaxies

We present X-ray spectra of four ultraluminous infrared galaxies (ULIRGs) with detectable broad near-infrared emission lines produced by active galactic nuclei (AGNs): Mrk 463, PKS 1345+12, IRAS 05189−2524, and IRAS 07598+6508. With the exception of IRAS 07598+6508, high quality X-ray spectra obtained with XMM or Chandra show modest (30–340 eV) equivalent widths of the 6.4 keV Fe Kα emission line and clear signatures for absorption at a level of 4–33 × 10 cm for the main power-law components from the AGNs. These spectral properties are typical of Compton-thin AGNs, and so we estimate absorptioncorrected 2–10 keV X-ray luminosities for the AGNs, Lx(2–10keV), using the Compton-thin assumption. We compare the Lx(2–10 keV) values with broad optical/near-infrared emission-line luminosities, and confirm a previous finding by Imanishi & Ueno that the Lx(2–10 keV) to broad-emission-line luminosity ratios in ULIRGs are systematically lower than those of moderately infraredluminous type-1 AGNs. A comparison of independent energy diagnostic methods Department of Astronomy, School of Science, Graduate University for Advanced Studies, Mitaka, Tokyo 181-8588
Study on Customer Churn Prediction Methods Based on Multiple Classifiers Combination

Combining multiple classifiers combination, sampling techniques, and more appropriate evaluation metrics, we first compare the selection of multiple classifiers combination based on GMDH(S-GMDH) and other classification methods on nine class imbalance data sets; we analyze the change of classification performances with and without using sampling. Then we further do customer churn prediction on ‘churn’ from the nine data sets. It is concluded that class imbalance has severely affected classification performances of various classifiers, which will surely influence churn prediction. Experiments prove that it is an effective way to improve churn prediction by combining S-GMDH and sampling techniques.
Liraglutide, a once-daily human GLP-1 analogue, added to a sulphonylurea over 26 weeks produces greater improvements in glycaemic and weight control compared with adding rosiglitazone or placebo in subjects with Type 2 diabetes (LEAD-1 SU)

Aim To compare the effects of combining liraglutide (0.6, 1.2 or 1.8 mg/day) or rosiglitazone 4 mg/day (all n ≥ 228) or placebo (n = 114) with glimepiride (2–4 mg/day) on glycaemic control, body weight and safety in Type 2 diabetes.
A New Technique of Cogging Torque Suppression in Direct-Drive Permanent-Magnet Brushless Machines

In direct-drive electric propulsion systems, where there is no reduction gear to minimize and absorb the adverse effects of cogging torque generated by the permanent-magnet (PM) machine, minimization of cogging torque generation is of particular importance. In this paper, a novel axial pole-pairing method is proposed to minimize cogging torque generation in a special three-phase outer-rotor PM brushless machine, which uses uneven stator poles to enhance back electromotive force (EMF). Analytical formulas of the machine's cogging torque are first derived. The new technique is compared with conventional cogging torque suppression methods by means of analytical models and comprehensive finite-element analysis (FEA). The FEA results show that the new method not only achieves effective cogging torque reduction, but also results in improved harmonic content of the back EMF. The validity of the FEA model is verified by experimental results from the prototype machines. Finally, the significance of optimizing both the load-independent machine design techniques and load-dependent driving techniques to achieve overall torque ripple minimization is discussed.
Annotating Negation and Speculation: the Case of the Review Domain

The paper presents the annotation of negation and speculation which is important for many NLP applications. Unlike previous research focusing on the medical domain, we investigate the review domain and attempt to annotate the SFU Review Corpus. In order to guarantee consistent annotation, we develop specific guidelines. Given the lack of research into annotation in the review domain, we explore the possibility of adapting the existing BioScope guidelines for the domain of interest. In order to reveal cases that need additional investigation, initially a small part of the corpus was annotated and this information was used for developing the guidelines. The paper describes the general principles our guidelines are based on and discusses differences with those in BioScope. It discusses the cases which were difficult to annotate. We include some insight into future work in order to improve the annotation process as well.
Castor: Scalable Secure Routing for Ad Hoc Networks

Wireless ad hoc networks are inherently vulnerable, as any node can disrupt the communication of potentially any other node in the network. Many solutions to this problem have been proposed. In this paper, we take a fresh and comprehensive approach that addresses simultaneously three aspects: security, scalability and adaptability to changing network conditions. Our communication protocol, Castor, occupies a unique point in the design space: it does not use any control messages except simple packet acknowledgments, and each node makes routing decisions locally and independently without exchanging any routing state with other nodes. Its novel design makes Castor resilient to a wide range of attacks and allows the protocol to scale to large network sizes and to remain efficient under high mobility. We compare Castor against four representative protocols from the literature. Our protocol achieves up to two times higher packet delivery rates, particularly in large and highly volatile networks, while incurring no or only limited additional overhead. At the same time, Castor is able to survive more severe attacks and recovers from them faster.