Miracle-dz/UniFAR-FTUs huggingface dataset:
Values congruence: Its effect on perceptions of Montana elementary school principal leadership practices and student achievement

Title: Values Congruence: Its Effect on Perceptions of Montana Elementary School PrincipalLleadership Practices and Student Achievement Chairperson: William McCaw. Ed.D. The purpose of this quantitative study was to examine the relationship between principal and teacher values congruence and perceived principal leadership practices. Additionally, this study considered the relationship between values congruence, leadership practices, and student achievement. The perceptions teachers hold regarding their principal‟s effectiveness have proven to be an important variable that influences the quality of the school, when quality is defined in terms of student achievement levels (Cotton, 2003; Marzano et. al., 2005). This study sought a better understanding of the factors that influence a teacher‟s perceptions of their principal‟s effectiveness to provide insight into the teacher/principal relationship and its subsequent association with student achievement. The statistical analyses in this study revealed that values congruence between teachers and principals is not a variable that has a statistically significant relationship to teachers‟ perceptions of their principal‟s leadership practices. This study also revealed that teacher/principal values congruence has no statistically significant relationship to student achievement levels. This study suggests that principals would be well served to focus their efforts on factors that have been shown to improve student achievement instead of seeking to affect the congruence between their work values and their staff‟s work values. The existing research base focuses the school leader on creating practices that are conducive to building professional teacher/principal relationships rooted in the examination of student data with a constant eye upon adjusting instruction that meets the diverse needs of each individual learner (DuFour & Eacker, 1998; Schmoker, 1999, 2006). A focus upon assuring teachers‟ utilization of instructional practices that have been found to impact student achievement is also essential (Marzano et al., 2003, 2005; Danielsen, 2002). It is advisable that principals focus their efforts in these areas rather than upon seeking to effect the level of values congruence that might exist between the principal and his/her staff.
Design and FPGA Implementation of Secure Key Management

Cryptographic device ensures the secure information exchange and private authentication even in the face of various attacks. In this paper, we focus on how to prevent physical attacks and present the PUF-based security secret-key generation architecture. We develop a novel Spread PUF architecture that is more secured and has higher performance than existing PUF architectures. Our thesis also gives applications of the Spread PUF for security secret-key management, unlike prior proposals which only present their designed PUF without showing how to apply it in practical security device. All the experiments are implemented on FPGAs.
Stability analysis of passive compass gait using linearized model

The inherent self-stabilization mechanism of passive gait is one of the most fundamental question in the area of studies on limit cycle walking. It is well known that the limit cycle stability can be tested by calculating the eigenvalues of the approximated Poincaré return map, and they have been calculated numerically in previous studies. Hirata and Kokame, however, firstly succeeded to derive the Jacobian matrix of the Poincaré return map using linearization of the dynamic equation. In this paper, we reconsider their method and propose an easier approach to derive the discrete-time linear error system. Our approach enables to derive the error system without integral terms. Through the theoretical investigations, we show that a passive compass-gait is formed by the combination of unstable stance phases and marginally stable collision phases. The validity is investigated by numerical simulations.
An Integrated Image Motion Sensor for Micro Camera Module

This paper deals with the building of a vision sensor which provides standard video capture and the associated global motion between consecutive frames. We aim at proposing embedded solutions for mobile applications. The application we focus on is video stabilization. Therefore the global motion we consider here is the one typically produced by handheld devices movement. We extract this global motion from local motion measures at the periphery of the image acquisition area. Thanks to this peculiar and “taskoriented” configuration, we take advantage of CMOS focal plane processing capabilities without sacrificing the sensor fill factor. We have at first validated the technique by software. Then we have designed peripheral custom pixels dedicated to motion detection and we are implementing it in a CMOS 0. 13µm technology.
Combined mRMR-MLPSVM scheme for high accuracy and low cost handwritten digits recognition

This paper presents a novel algorithm for handwritten digit recognition which in addition to its high accuracy, enjoys low implementation complexity. The proposed algorithm sorts all features using mRMR (Minimal-Redundancy and Maximal-Relevance) method and selects the best top features by evaluating the training data. The selected features are then used as input of our classifier. The classifier that we used is an MLPSVM classifier which combines the good properties of MLP (Multi-Layer Perceptron) and SVM (Support Vector Machines). The performance of the proposed scheme is then evaluated against ORHD and MNIST datasets, which shows that despite lower complexity compared to existing methods, it can get to high accuracy of 96.1 and 98.14 on the datasets respectively.
ciForager: Incrementally discovering regions of correlated change in evolving graphs

Data mining techniques for understanding how graphs evolve over time have become increasingly important. Evolving graphs arise naturally in diverse applications such as computer network topologies, multiplayer games and medical imaging. A natural and interesting problem in evolving graph analysis is the discovery of compact subgraphs that change in a similar manner. Such subgraphs are known as regions of correlated change and they can both summarise change patterns in graphs and help identify the underlying events causing these changes. However, previous techniques for discovering regions of correlated change suffer from limited scalability, making them unsuitable for analysing the evolution of very large graphs. In this paper, we introduce a new algorithm called ciForager, that addresses this scalability challenge and offers considerable improvements. The efficiency of ciForager is based on the use of new incremental techniques for detecting change, as well as the use of Voronoi representations for efficiently determining distance. We experimentally show that ciForager can achieve speedups of up to 1000 times over previous approaches. As a result, it becomes feasible for the first time to discover regions of correlated change in extremely large graphs, such as the entire BGP routing topology of the Internet.
Towards OPC UA as portable SOA middleware between control software and external added value applications

Automation systems (ASs) based on Service-Oriented Architecture (SOA) are becoming more wide-spread. Due to their inherent property of separating the hardware-specific implementation from the logical work- or control-flow, SOA-based application programming is regarded as the next logical step in AS programming. Several successful attempts for implementing SOA-based AS have been made, but always with non-industrial, non-standard software like Devices Profile for Web Services. Based on the requirements of typical industrial SOA-based AS application, we will show that the industry standard data acquisition software OPC Unified Architecture is capable to serve as a SOA-based middleware.
Embedding and extending GIS for exploratory analysis of large-scale species distribution data

Exploratory analysis of large-scale species distribution data is essential to gain information and knowledge, stimulating hypotheses and seeking possible explanations of species distribution patterns. Geographical Information System (GIS) has played an important role in modeling and visualizing species distribution patterns for a single or a limited number of species. However, traditional GIS models do not take taxonomic components of species distribution data into consideration and are neither effective nor efficient in managing large-scale species distribution data. In this study, we propose to embed and extend GIS for large scale species distribution data analysis. We provide an integrated data model that seamlessly links geographical, taxonomic and environmental data related to species distribution data analysis. We then present LEEASP (a Linked Environment for Exploratory Analysis of large-scale Species Distribution data), a prototype that has been developed based on the integrated data model. LEEASP utilizes the state-of-the-art advanced visualization techniques and multiple view coordination techniques to visualize different data sources that are relevant to species distribution data analysis. The North America tree species distribution data and other related data are used as an example to demonstrate the feasibility of the realization of the proposed integrated data model and how LEEASP can help users explore the geographical-taxonomic-environmental relationships
Hybrid printing of photopolymers and electromechanical assemblies

Performance of electronic systems 3D-printed from raw materials falls short of conventionallyfabricated systems due to material limitations. 3D-printed transistors are low-power, have relatively poor transconductance specifications and low on-off ratios, while 3D printed conductors typically exhibit volume conductivity specifications that are an order of magnitude less favorable than their base-materials. Here we present an alternative approach that embeds electrical functionality by placing standardized prefabricated electrical components within a 3D printed structure while it is being built. The process is facilitated by restricting the components to a fixed repertoire of modular functionalities, and using a module design that is readily manipulated by automated assembly equipment and assembled on a regular lattice. This approach leverages the strengths of traditional semiconductor manufacturing technology while enabling scalable on-demand additive manufacturing of functional, integrated electromechnical systems with performance that is on par with conventional processes.
A study of quantum neural networks

The study of quantum neural networks (QNN) may give us unprecedented possibilities in creating new systems for information processing. We describe a model for quantum neuron (QN) and discuss the quantum learning rule. It is demonstrated that this single quantum neuron is able to perform the XOR function unrealizable with a single classical neuron and has the same computational power as the two-layer perceptron.
Glutaminase Dysregulation in HIV-1-Infected Human Microglia Mediates Neurotoxicity: Relevant to HIV-1-Associated Neurocognitive Disorders

Microglia represent the main cellular targets of HIV-1 in the brain. Infected and/or activated microglia play a pathogenic role in HIV-associated neurocognitive disorders (HAND) by instigating primary dysfunction and subsequent death of neurons. Although microglia are known to secrete neurotoxins when infected with HIV-1, the detailed mechanism of neurotoxicity remains unclear. Using a human microglia primary culture system and macrophage-tropic HIV-1 strains, we have now demonstrated that HIV-1 infection of microglia resulted in a significant increase in extracellular glutamate concentrations and elevated levels of neurotoxicity. RNA and protein analysis revealed upregulation of the glutamate-generating enzyme glutaminase isoform glutaminase C in HIV-1-infected microglia. The clinical relevance of these findings was further corroborated with investigation of postmortem brain tissues. The glutaminase C levels in the brain tissues of HIV dementia individuals were significantly higher than HIV serum-negative control and correlated with elevated concentrations of glutamate. When glutaminase was subsequently inhibited by siRNA or by a small molecular inhibitor, the HIV-induced glutamate production and the neuronal loss was diminished. In conclusion, these findings support glutaminase as a potential component of the HAND pathogenic process as well as a novel therapeutic target in their treatment.
AdaBoost in region-based image retrieval

In this paper, a region-based AdaBoost (RBA) algorithm that combines the similarity contributions from different regions in images to form a single value for measuring similarity between images is proposed. The region-based framework utilizes the segmentation result to capture the higher-level concept of images. AdaBoost is a method of finding a highly accurate classifier by combining weak classifiers. A modified version of AdaBoost which can get confidence-rated prediction is applied to learn the final similarity function from user's feedback. It is based on a novel selection of weak classifiers. Experimental and comparison results, which are performed using a general-purpose database containing 7000 images, are promising.
Memory-efficient content filtering hardware for high-speed intrusion detection systems

Content filtering-based Intrusion Detection Systems have been widely deployed in enterprise networks, and have become a standard measure to protect networks and network users from cyber attacks. Although several solutions have been proposed recently, finding an efficient solution is considered as a difficult problem due to the limitations in resources such as a small memory size, as well as the growing link speed. In this paper, we present a novel content filtering technique called Table-driven Bottom-up Tree (TBT), which was designed i) to fully exploit hardware parallelism to achieve real-time packet inspection, ii) to require a small memory for storing signatures, iii) to be flexible in modifying the signature database, and iv) to support complex signature representation such as regular expressions. We configured TBT considering the hardware specifications and limitations, and implemented it using a FPGA. Simulation based performance evaluations showed that the proposed technique used only 350 Kilobytes of memory for storing the latest version of SNORT rule consisting of 2770 signatures. In addition, unlike many other hardware-based solutions, modification to signature database does not require hardware re-compilation in TBT.
A multi-agent learning approach for the multi-mode resource-constrained project scheduling problem

This paper introduces a novel approach for solving the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The new approach applies simple agent learning devices, i.e. learning automata, to construct the project schedules. We present some comparative results, to show that our decentralized method can easily compete with the best performing algorithms for the MRCPSP.
Peri-Golgi vesicles contain retrograde but not anterograde proteins consistent with the cisternal progression model of intra-Golgi transport

A cisternal progression mode of intra-Golgi transport requires that Golgi resident proteins recycle by peri-Golgi vesicles, whereas the alternative model of vesicular transport predicts anterograde cargo proteins to be present in such vesicles. We have used quantitative immuno-EM on NRK cells to distinguish peri-Golgi vesicles from other vesicles in the Golgi region. We found significant levels of the Golgi resident enzyme mannosidase II and the transport machinery proteins giantin, KDEL-receptor, and rBet1 in coatomer protein I–coated cisternal rims and peri-Golgi vesicles. By contrast, when cells expressed vesicular stomatitis virus protein G this anterograde marker was largely absent from the peri-Golgi vesicles. These data suggest a role of peri-Golgi vesicles in recycling of Golgi residents, rather than an important role in anterograde transport.
Evaluation of Strategies for Enhancing Production of Low-Viscosity Liquids From Tight/Shale Reservoirs

Production of low-viscosity liquids (including condensates) from tight reservoirs (such as shales) is severely restricted by the ultra low-permeability of such formations, limiting production to a very small fraction (usually less than 5 percent) of the liquids-in-place. In this study, which is part of a wider investigation, we evaluate by means of numerical simulation several possible strategies to enhance low-viscosity liquids production from such reservoirs. These strategies include (a) physical displacement processes, (b) non-thermal processes to reduce the viscosity and the critical saturation of the liquids, (c) thermal processes, (d) enhanced reservoir stimulation, (e) novel well configurations and (f) combinations thereof. The objectives of this effort are to (1) to remove from further consideration potential production strategies that hold limited (if any) promise, and (2) to identify production strategies that appear to have potential for further study and development. We first determine the baseline production performance of such reservoirs corresponding to several reference production regimes that involve minimal or no reservoir stimulation, standard displacement fluids (H2O or CH4), standard well configurations and no thermal treatment. We then evaluate the efficiency of several production strategies: (a) traditional continuous gas flooding using parallel horizontal wells and using the currently abundant shale gas, (b) water-alternating-gas (WAG) flooding, (c) huffand-puff injection/production strategies using lean gas/rich gas in a traditional (single) horizontal well with multiple fractures, (d) flooding using appropriate gases (e.g., CO2, N2, CH4) using appropriate well configurations (mainly horizontal), with the viscosity reduction resulting from the gas dissolution into the liquids, and (e) thermal processes, in which the viscosity reduction is achieved by heating, possibly to the point of liquid vaporization and transport through the matrix to the production wells as a gas. Our study includes an analysis of the sensitivity of the liquids production to the main parameters defining each of the strategies listed above in an effort to determine the critically important parameters and factors that control the production performance and efficiency.
An Ontology Based Methodology for Automated Algorithms Recognition in Source Code

Emerging computing architectures exploit parallel execution units for performances improvements in programs executions. Recent advances in microprocessors and multicomputers stressed the need of methodologies able to take advantage of parallelism. Source code analysis techniques exist which are used to identify chunks of code for parallelization purposes, but they are not designed to identify complex algorithmic patterns. In this work a methodology for identification of complex patterns is described. It is based on semantic description of patterns, which allows not only for reasoning, but also for providing an easy way to produce and extend algorithmic patterns definitions. A comparison of this approach with an attribute grammar language for patterns description is also reported.
Ferulic Acid: A Hope for Alzheimer’s Disease Therapy from Plants

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by the deposition of extracellular amyloid-beta peptide (Aβ) and intracellular neurofibrillar tangles, associated with loss of neurons in the brain and consequent learning and memory deficits. Aβ is the major component of the senile plaques and is believed to play a central role in the development and progress of AD both in oligomer and fibril forms. Inhibition of the formation of Aβ fibrils as well as the destabilization of preformed Aβ in the Central Nervous System (CNS) would be an attractive therapeutic target for the treatment of AD. Moreover, a large number of studies indicate that oxidative stress and mitochondrial dysfunction may play an important role in AD and their suppression or reduction via antioxidant use could be a promising preventive or therapeutic intervention for AD patients. Many antioxidant compounds have been demonstrated to protect the brain from Aβ neurotoxicity. Ferulic acid (FA) is an antioxidant naturally present in plant cell walls with anti-inflammatory activities and it is able to act as a free radical scavenger. Here we present the role of FA as inhibitor or disaggregating agent of amyloid structures as well as its effects on biological models.
Further Analysis of the β-Order MMSE STSA Estimator for Speech Enhancement

In Bayesian approaches for speech enhancement, the clean speech is estimated by minimizing the expectation of a desired cost function. In the β-order MMSE STSA (βSA) Bayesian estimator, the cost function is the squared difference between the estimated and actual clean speech short-time spectral amplitude (STSA), both to the power β > 0. In this paper we propose an extension of the analysis of the βSA estimator for values of β < 0. We find that when β < 0, a normalization occurs in the βSA estimator which produces more noise reduction as β is reduced at the expense of additional speech distortion. Furthermore, the βSA estimator with β = -1 slightly outperforms the well known MMSE STSA and MMSE log-STSA (LSA) estimators in terms of the PESQ, for the two noises studied, while the overall MOS appreciation for β = -1 is found to be better than both MMSE STSA and LSA for white noise.
Histology and Histopathology Cell Proliferation in the Developing Rat Pineal Gland. a Bromodeoxyuridine Immunohistochemical Study

The immunohistochemical detection of bromodeoxyuridine (BrdU) was used to study the cell proliferation in the developing rat pineal gland, from the appearance of pineal primordium in the embryonic day 15 (E15) until 30 days after birth. The results showed three different proliferative phases. From E15 to E21, the pineal gland shows a phase of rapid proliferation. The second phase corresponds to the first postnatal week, in which the number of labeled cells per surface unit decreases suddenly to values between 20% to 10% of those of embryonic period. From the second postnatal week onwards, the number of BrdU-positive cells progressively decreases.
Are all Social Networks Structurally Similar? A Comparative Study using Network Statistics and Metrics

The modern age has seen an exponential growth of social network data available on the web. Analysis of these networks reveal important structural information about these networks in particular and about our societies in general. More often than not, analysis of these networks is concerned in identifying similarities among social networks and how they are different from other networks such as protein interaction networks, computer networks and food web. In this paper, our objective is to perform a critical analysis of different social networks using structural metrics in an effort to highlight their similarities and differences. We use five different social network datasets which are contextually and semantically different from each other. We then analyze these networks using a number of different network statistics and metrics. Our results show that although these social networks have been constructed from different contexts, they are structurally similar. We also review the snowball sampling method and show its vulnerability against different network metrics.