Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Teacher Logs to Measure the Enacted Curriculum: A Study of Literacy Teaching in Third‐Grade Classrooms

In this article we examine methodological and conceptual issues that emerge when researchers measure the enacted curriculum in schools. After outlining key theoretical considerations that guide measurement of this construct and alternative strategies for collecting and analyzing data on it, we illustrate one approach to gathering and analyzing data on the enacted curriculum. Using log data on the reading/language arts instruction of more than 150 third‐grade teachers in 53 high‐poverty elementary schools participating in the Study of Instructional Improvement, we estimated several hierarchical linear models and found that the curricular content of literacy instruction (a) varied widely from day to day, (b) did not vary much among students in the same classroom, but (c) did vary greatly across classrooms, largely as the result of teachers’ participation in 1 of the 3 instructional improvement interventions (Accelerated Schools, America’s Choice, and Success for All) under study. The implications of these findings for future research on the enacted curriculum are discussed.
Safety assessment of rice bran oil in a chicken embryo model

Objective: Rice Bran Oil (RBO) is extracted from the outer layer of rice. Little information is available regarding its safety. The present study was conducted to assess its safety in chicken embryo model. Materials and Methods: RBO was injected on day 4 of incubation of chickens. The tissues and serum samples were collected. Oxidative stress parameters in the liver, kidney and brain and biochemical parameters of serum were measured. The deformities were also investigated. Results: The changes in the liver enzymes activity were not statistically significant. There was significant decrease and increase in lipid peroxidation and glutathione level, respectively. It is suggested that RBO is a natural antioxidant source. Low-density lipoprotein cholesterol (LDL) also decreased. No abnormal findings were observed in the chickens. Conclusion: No toxic effect was observed following RBO administration in chicken embryos. This study showed that RBO is not a safety concern.
Scatterer characterisation using polarimetric SAR tomography

This paper presents the first step to characterise scatterers using polarimetric SAR tomography (POLTOMSAR). It is a logical extension of the tomographic data processing, which consists to use the vectorial properties of electromagnetic waves. An introduction to the estimation of the polarisation state of retrieved target is proposed. It is based on a modified signal model adapted to the MUSIC algorithm. This makes it possible to determinate the physical nature of detected object, which is not possible using classical approach, unless having the ground-truth of the scene under study. The experimental results are shown using a multibaseline data set acquired in L-band by DLR’s experimental SAR (E-SAR) on a test site near Oberpfaffenhofen / Germany.
A comprehensive business domain ontology for cloud services

Despite the evident proliferation of Cloud Services (CS), many challenges hinder efficient service discovery and selection processes. A strong key enabler is use of ontology in CS domain. However, no broad cloud ontology has dominated yet. In this regard, we propose a fully-fledged comprehensive business domain ontology for CS with querying capabilities. The proposed CS ontology encompasses cloud taxonomy, delivery, deployment and price models. In addition to technical and computing aspects, it also covers business aspects of CS. Distinctively, it elaborates on non-functional aspects that are usually neglected in CS semantic modeling. It encompasses in-depth coverage of service characteristics, quality of service metrics and service level agreement terms. We present ontology development methodology, conceptual model and implementation details. Proposed CS ontology can be perceived as a knowledge base for CS discovery and selection. It was published as contribution to the research community.
Rapid quantification of rice root‐associated bacteria by flow cytometry

To understand the mechanism of plant–bacterium interaction, it is critical to enumerate epiphytic bacteria colonizing the roots of the host. We developed a new approach, based on flow cytometry, for enumerating these bacteria and used it with rice plants, 7 and 20 days after colonization with Herbaspirillum rubrisubalbicans and Azospirillum brasilense. The results were compared with those obtained with the traditional plate count method. Both methods gave similar numbers of H. rubrisubalbicans associated with rice roots (c. 109 CFU g−1). However, flow cytometry gave a number of viable cells of rice‐associated A. brasilense that was approx. 10‐fold greater than that obtained with the plate count method. These results suggest that the plate count method can underestimate epiphytic populations. Flow cytometry has the additional advantage that it is more precise and much faster than the plate count method.
GPU Acceleration of Content-Based Image Retrieval Based on SIFT Descriptors

Content-based image retrieval (CBIR) is to retrieve images from a database that are similar to a query image. In CBIR, to compute the similarity between two images, feature vectors are first extracted from each image, and the similarity is computed based on the extracted features. In particular, scale-invariant local features, such as SIFT and SURF, have been gaining much public attention for their performance, and have successfully been applied in diverse applications. When using such features, one image is typically described by hundreds of feature vectors, leading to huge image databases. Moreover, when processing queries, vast amount of features need to be processed, which ends up with slow query execution. To make CBIR fast, in this paper, we try to exploit a GPU (graphics processing unit) to parallelize the query processing. Since GPUs have many processing units, we can utilize massive parallelism available on them. Our method is divided into two phases, namely, database construction and query processing. In the database construction phase, it takes as input the images and build a database on GPU by compressing the feature vectors extracted from the images using using LSH (locality sensitive hashing), thereby reducing the memory footprint and the processing cost as well. In the query processing phase, it takes as input a query image and searches similar images in parallel on the GPU. Experimental results show that the proposed method is 55 times faster than a serial CPU implementation, and 2.5 times faster than a parallel CPU implementation.
Protecting QoS in the Ciphertext Domain

The Automated Digital Network System (ADNS) provides network services and entry into the Defense Information System Network (DISN) for U.S. Navy ships, submarines and shore facilities. ADNS is the Navy's primary tactical wide area network (WAN) and intends to provide optimal use of the bandwidth assigned by the system to Unclassified, Secret, Sensitive Compartmented Information (SCI), and Joint and Coalition networks. As the primary tactical network interface between ships and shore-based RNOSC and NCTS, ADNS INC III is employed to support Mission Critical Command and Control (C2) communications and as such, ADNS INC III must provide protection against adversarial flooding attacks aimed at consuming a significant portion of our bandwidth. We are the first to show that through statistical ciphertext (CT) flow analysis using Maximum Entropy Estimation it is possible to detect malicious flooding attacks and to further police the protected core traffic to preserve Quality of Service (QoS).
Testing for selection on color and pattern in a mimetic radiation

In this paper, we analyze variation in spectral reflectance and color pattern among populations to demonstrate dramatic divergence between four distinct morphs of the mimic poison frog Ranitomeya imitator . We also analyze genetic divergence in d-loop mtDNA sequences between populations. We then use coalescent-based simulations to demonstrate that the high levels of observed phenotypic divergence are not consistent with levels of genetic divergence expected under neutral drift among populations, implying an important role for selection in driving divergence between these populations.
Using unlabeled data to handle domain-transfer problem of semantic detection

Due to highly domain-specific nature, supervised sentiment classifiers typically require a large number of new labeled training data when transferred to another domain. This is so-called domaintransfer problem. In this work, we attempt to tackle this problem by combining old-domain labeled examples with new-domain unlabeled ones. The basic idea is to use old-domain-trained classifier to label some informative unlabeled examples in new domain, and train the base classifier again. The experimental results demonstrate that proposed method dramatically boosts the accuracy of the base sentiment classifier on new domain.
Quantitative 3D analysis of the canal network in cortical bone by micro-computed tomography.

Cortical bone is perforated by an interconnected network of porous canals that facilitate the distribution of neurovascular structures throughout the cortex. This network is an integral component of cortical microstructure and, therefore, undergoes continual change throughout life as the cortex is remodeled. To date, the investigation of cortical microstructure, including the canal network, has largely been limited to the two-dimensional (2D) realm due to methodological hurdles. Thanks to continuing improvements in scan resolution, micro-computed tomography (muCT) is the first nondestructive imaging technology capable of resolving cortical canals. Like its application to trabecular bone, muCT provides an efficient means of quantifying aspects of 3D architecture of the canal network. Our aim here is to introduce the use of muCT for this application by providing examples, discussing some of the parameters that can be acquired, and relating these to research applications. Although several parameters developed for the analysis of trabecular microstructure are suitable for the analysis of cortical porosity, the algorithm used to estimate connectivity is not. We adapt existing algorithms based on skeletonization for this task. We believe that 3D analysis of the dimensions and architecture of the canal network will provide novel information relevant to many aspects of bone biology. For example, parameters related to the size, spacing, and volume of the canals may be particularly useful for investigation of the mechanical properties of bone. Alternatively, parameters describing the 3D architecture of the canal network, such as connectivity between the canals, may provide a means of evaluating cumulative remodeling related change.
AntNet-RSLR: A proposed Ant routing protocol for MANETs

A mobile ad hoc networks (MANETs) is a dynamic mobile wireless network that can be formed without the need for any pre-existing wired or wireless infrastructure. One of the main challenges in an ad hoc network is the design of robust routing algorithms that adapt to the frequent and randomly changing network topology. This paper proposes a novel routing scheme for MANETs, which adapts the AntNet protocol with the blocking-expanding Ring Search and Local Retransmission technique (AntNet-RSLR). According to this protocol, a group of mobile agents build paths between pair of nodes, exploring the network concurrently and exchanging obtained information to update the routing tables that decreases both of the routing message overhead and the average end to end delay less than the well known AntNet, AODV and DSR routing protocols. This led to increase the throughput more than AntNet, AODV and DSR routing protocols. AntNet-RSLR has been implemented using NS-2 simulator.
A matter of degrees: The role of education in the professionalisation journey of social work in New Zealand

Social work in Aotearoa New Zealand (ANZ) is a contested profession on a journey of professionalisation in an era where contradictory forces impact on its position and strength. Social work education reflects these tensions, being influenced by economic and political forces. The delineation of a benchmark qualification for entry is a core feature of professional status and so the inception of professional registration has impacted on social work education in ANZ as it has elsewhere. The aim of this paper is to explore dimensions of the history of social work education in ANZ, the impact of the Social Workers Registration Act (2003) (SWRA) and to examine some current constraints and consider the challenges professional education faces in the next 50 years. It is argued that social work education has been, is and will remain a site of struggle.
Privacy via Subsumption

We describe an object calculus allowing object extension and structural subtyping. Each object has a "dictionary" to mediate the connection between names and components. This extra indirection yields the first object calculus combining both object extension and full width subtyping in a type-safe manner. If class inheritance is modeled with object extension, private fields and methods can be achieved directly by scoping restrictions: private fields or methods are those hidden by subsumption. We prove that the type system is sound, discuss a variant allowing covariant self types, and give some examples of the expressiveness of the calculus.
Mathematical model and topological method for reliability calculation of distribution networks

A mathematical model for distribution network reliability calculation is given in this paper. A topological method is used determining such reliability indices as probability of element failure, frequency of element failures, duration of element failure. The method is universal for determination of reliability indices and applicable to calculations of any other (e.g. autonomic) electric power networks.
How to use the LSA website

Many researchers and students interested in applying Latent Semantic Analysis (LSA) become daunted by the complexities of building spaces and applying those spaces to new problems. In an effort to provide a simpler interface, the University of Colorado built the LSA website (http://lsa.colorado.edu) 1. The website contains several precomputed semantic spaces and tools to manipulate those spaces in a number of ways. In this chapter, we will overview the site and describe some of the issues that you will need to be aware of in order to use the site correctly. Like any model, poor results can be obtained from LSA if parameters are not set appropriately. We will highlight some of the most common errors and give advice on how to use the site to generate the best results. In the discussions in this chapter, we will assume that you have a basic understanding of the mechanics of LSA and are familiar with terms such as cosine, psuedodoc etc. If this is not the case, you should read chapter two on the mathematical foundations of LSA before proceeding. Figure 1 shows the home page of the LSA website. On the left hand side is a main menu, which provides fast links to the main areas of the website. On the right hand side are the applications, a series of demonstrations of LSA in action in some applied settings and a list of links to auxiliary functions such as the site guestbook and a list of LSA publications. In this chapter, we will focus on the applications. First, however, we need to consider two issues that will be relevant regardless of which application you employ, namely how to choose a semantic space and how many factors to select.
Retinal vessel inpainting using recursive least square dictionary learning algorithm

Retinal blood vessels are considered as being interference on the retinal images for the task of detecting significant features of the most frequent eye diseases. If these blood vessel structures could be suppressed, it might lead to a more accurate segmentation of retinal lesions as well as a better extraction of textural features to be used for pathology detection. This work proposes, as a novelty, the use of sparse representations and dictionary learning techniques for retinal vessel inpainting. The dictionary learning algorithms used in this paper were the Recursive Least Square Dictionary Learning (RLS-DL), and Online Dictionary Learning (ODL). We tested the performance of the algorithm for grayscale and RGB images from the DRIVE public database, employing different neighbourhoods and sparseness factors. An average recovery error smaller than 0.022 was achieved. The results suggest that the use of sparse representations and dictionaries learned by RLS-DLA performs very well for inpainting of retinal blood vessels.
A Large-Area Image Sensing and Detection System Based on Embedded Thin-Film Classifiers

This paper presents a large-area image sensing and detection system that integrates, on glass, sensors and thin-film transistor (TFT) circuits for classifying images from sensor data. Large-area electronics (LAE) enables the formation of millions of sensors spanning physically large areas; however, to perform processing functions, thousands of sensor signals must be interfaced to CMOS ICs, posing a critical limitation to system scalability. This work presents an approach whereby image detection of shapes is performed using simple circuits in the LAE domain based on amorphous silicon (a-Si) TFTs. This reduces the interfaces to the CMOS domain. The limited computational capability of TFT circuits as well as high variability and high density of process defects affecting TFTs and sensors is overcome using a machine-learning algorithm known as error-adaptive classifier boosting (EACB) to form embedded weak classifiers. Through EACB, we show that high-dimensional sensor data from a-Si photoconductors can be reduced to a small number of weak-classifier decisions, which can then be combined in CMOS to achieve strong-classifier performance. For demonstration, a system classifying five shapes achieves performance of >85%/>95% [true-positive (tp)/true-negative (tn) rates] [near the level of an ideal software-implemented support vector machine (SVM) classifier], while the total number of signals from 36 sensors in the LAE domain is reduced by $3.5\text{-}9\times$.
Eurographics/ Acm Siggraph Symposium on Computer Animation (2006) Simulation of Bubbles

We present a novel framework based on a continuous fluid simulator for general simulation of realistic bubbles, with which we can handle as many significant dynamic bubble effects as possible. To capture nature of the very thin liquid film of bubbles, we have developed a regional level set method allowing multi-manifold interface tracking. The regional level set method is based on the definitions of regional distance and its five operators, which makes it very easy to implement. We can reconstruct an implicit surface of liquid film with arbitrary thickness from the representation of regional level set functions. To overcome the numerical instability caused by surface tension, we exploit a new semi-implicit surface tension model which is unconditionally stable and makes the simulation of surface tension dominated phenomena much more efficient. An approximated film thickness evolution model is proposed to control the bubble's lifecycle. All these new techniques combine into a general framework that can produce various realistic dynamic effects of bubbles.
Linear vertex-kernels for several dense ranking r-CSPs

A Ranking r-Constraint Satisfaction Problem (ranking r-CSP) consists of a ground set of vertices V, an arity r >= 2, a parameter k and a constraint system c, where c is a function which maps rankings of r-sized subsets of V to {0,1}. The objective is to decide if there exists a ranking of the vertices satisfying all but at most k constraints. Famous ranking r-CSP include the Feedback Arc Set in Tournaments and Betweenness in Tournaments problems. We consider these problems from the kernelization viewpoint. We prove that so-called l_r-simply characterized ranking r-CSPs admit linear vertex-kernels whenever they admit constant-factor approximation algorithms. This implies that r-Betweenness in Tournaments and r-Transitive Feedback Arc Set In Tournaments, two natural generalizations of the previously mentioned problems, admit linear vertex-kernels. Moreover, we introduce another generalization of Feedback Arc Set in Tournaments, which does not fit the aforementioned framework. We obtain a 5-approximation and a linear vertex-kernel for this problem.
P2 Receptor Expression Profiles in Human Vascular Smooth Muscle and Endothelial Cells

P2 receptors mediate the actions of the extracellular nucleotides ATP, ADP, UTP, and UDP, regulating several physiologic responses including cardiac function, vascular tone, smooth muscle cell (SMC) proliferation, platelet aggregation, and the release of endothelial factors. P2 receptor characterization has been hampered by the lack of selective antagonists. The aim of the current study was to investigate the mRNA and protein expression of P2X and P2Y receptors in human SMC and in endothelial cells (EC). Smooth muscle cells were obtained from human mammary artery and EC from human umbilical vein. Using real-time PCR, the authors established quantitative mRNA assays. Protein expression was studied using Western blotting with recently developed antibodies. The P2X1 receptor was highly specific for human SMC, while the P2X4 was the highest expressed receptor in EC. The P2Y2 receptor was present in both SMC and EC. UTP-mediated effects in these cells are likely to be mediated by P2Y2 and not P2Y4 receptors since the latter had considerably lower expression. The P2Y6 receptor was expressed in both SMC and EC. The P2Y1 and surprisingly the P2Y11 receptors were the most abundantly expressed P2Y receptors in the endothelium. Overall, Western blotting confirmed the mRNA findings in most aspects, and most interestingly, indicated oligomerization of the P2Y1 receptor that may be important for its function. In conclusion, P2X1, P2Y2, and P2Y6 are the most expressed P2 receptors in SMC and are thus probably mediating the contractile and mitogenic actions of extracellular nucleotides. The P2X4, P2Y11, P2Y1, and P2Y2 are the most expressed P2 receptors in EC, and are most likely mediating release of nitric oxide, endothelium-dependent hyperpolarizing factor (EDHF), and t-PA induced by extracellular nucleotides. These findings will help to direct future cardiovascular drug development against the large P2 receptor family.
Malicious Node Attack Preventer (MNAP) Approach for Mobile Ad-hoc Networks (MANET's)

A Mobile Ad-hoc network is a heterogeneous network. They have very particular features such as high mobility, multi-hop routing, open system and the absence of any fix infrastructure. An ad-hoc network faces different type of security attack. In this paper, we discuss our implementation of the AODV protocol extension namely Malicious Node Attack Preventer (MNAP). AODV extension mechanism improves the AODV behavior. MNAP used the reserved field of RREQ and RREP packet format. MNAP implements security in AODV against black-hole and gray-hole attacks. Analyzes has been done based on PDR, throughput and delay of the node selected by doing simulation on Qualnet network simulator. General Terms Security
Characterization of Xylanase of Cladosporium cladosporioides H1 Isolated from Janggyeong Panjeon in Haeinsa Temple

Cladosporium cladosporioides H1 was found to be the most abundant microbe in Janggyeong Panjeon. C. cladosporioides H1 produced a 20 kDa xylanase, which was generally stable below 60°C and had specialized activity in an acidic condition. Our results may lead to the development of a strategy for preservation of organic cultural heritage environments.