Miracle-dz/UniFAR-FTUs huggingface dataset:
Creation of a Tagged Corpus for Less-Processed Languages with CLaRK System

This paper addresses the problem of efficient resources compilation for less-processed languages. It presents a strategy for the creation of a morpho-syntactically tagged corpus with respect to such languages. Due to the fact that human languages are morphologically nonhomogenous, we mainly focus on inflecting ones. With certain modifications, the model can be applied to the other types as well. The strategy is described within a certain implementational environment - the CLaRK System. First, the general architecture of the software is described. Then, the usual steps towards the creation of the language resource are outlined. After that, the concrete imlementational properties of the processing steps within CLaRK are discussed: text archive compilation, tokenization, frequency word list creation, morphological lexicon creation, morphological analyzer, semi-automatic disambiguation.
What First Grade Teachers Reveal About Vocabulary Instruction: Aligning Instruction to the Common Core State Standards

This mixed methods study examined the vocabulary knowledge and instructional practices of four grade 1 teachers in order to better understand how prepared teachers are to implement the First Grade English Language Arts Common Core State Standards (CCSS). Data collected included an audiotaped semi-structured interview, a teacher survey, video-recorded class vocabulary instruction, researcher field notes, and artifacts of class activities. Findings indicate that teaching experience is not a factor in the level of vocabulary instruction teachers provide. For example, veteran teachers in the analysis rely on traditional spelling tests and basal based vocabulary instruction to teach vocabulary, while the less experienced teachers utilize trade books to guide their instruction. However, veteran teachers provide vocabulary instruction daily, while less experienced teachers did not. Findings suggest that all teachers would benefit from professional learning opportunities related to vocabulary instruction and researchers are encouraged to investigate vocabulary instruction and its alignment to the CCSS with larger sample sizes in other districts and across all grade levels.
Utilizing Q-Learning to allow a radar to choose its transmit frequency, adapting to its environment

Recent research show that utilization of knowledge of the environment can allow a radar system to adapt its processing to improve its performance. Furthermore, a radar system that utilize both a-priori and measured knowledge in an adaptive close loop manner could seem to be cognitive of its environment, able to adapt to changes to optimize performance. Reinforced learning could play a vital role as part of such a closed-loop cognitive radar system. The Q-Learning algorithm is hypothesized to be useful for this cognitive radar domain. This paper investigates the problem of adaptively choosing the radar transmit frequency through application of Q-Learning on measured radar data. A comparison is made against other frequency selection algorithms and its shown that Q-Learning manages to learn a good strategy to adaptively select radar transmit frequency, mostly outperforming the other methods tested in the scenario investigated here.
Comparison of physiological and yield traits between purple- and white-pericarp rice using SLs

Five physiological and eleven yield traits of two pairs of sister lines generated from a high generation with similar genetic background (SLs) for purple pericarp were investigated to explore the reasons behind low-yield production of colored rice. Of the five physiological traits examined, except grain anthocyanin content, there were generally similar trends between the P (purple-pericarp) lines and the corresponding W (white-pericarp) lines over two seasons (in the year 2009 and 2010 separately). The results demonstrated that the chlorophyll content of flag leaves, the net photosynthetic rate of flag leaves, and the grain anthocyanin content could be easily influenced by the environment. The physiological functions of the traits for the P lines were more active than those of the corresponding W lines in the year 2010. The grain anthocyanin content of the P lines was much greater in the year 2010 than in the year 2009 during the growth period. The investigation of yield traits revealed that the P lines had reduced 1000-grain weight, yield per plot and grain/brown rice thickness compared to the W lines. A difference comparison of these traits and a source-sink and transportation relationship analysis for these SLs suggested that small sink size was a key reason behind yield reduction of purple pericarp rice.
Fuzzy clustering-based approach to derive hierarchical structures from folksonomies

Collaborative tagging systems have recently emerged as a powerful way to label and organize large collections of data. The informal social classification structure in these systems, also known as folksonomy, provides a convenient way to annotate resources by allowing users to use any keyword or tag that they find relevant. Although folksonomies and the respective tags often lack a context-independent and intersubjective definition of meaning, the assumption that the evolving structure of these digital records contains implicit evidences for the underlying semantics has been proven by successful approaches of making the emergent semantics explicit. In this paper we propose an approach for extracting ontological structures from folksonomies that exploits the power of fuzzy clustering using new similarity and generality measure. The fuzzy clustering process discovers ambiguous tags and disambiguates them all at once, and the new similarity measure gives more accurate results as it calculates co-occurrences based on distinct users and not only in the number of co-occurrences of two distinct words. The generated ontology can be used to enhance various tasks in the tagging systems, such as tag disambiguation, result visualization, and ontology evolution. Our experimental results on real world data sets show that our method can effectively learn the ontology structure from the folksonomies.
Image-based metal artifact reduction in CT images

The presence of metal in the scanning field of a CT scanner can create so-called metal artifacts in the reconstructed images. These streak artifacts obscure information about anatomical structures, making it difficult for radiologists to correctly interpret the images or for computer programs to analyze them. Several methods have been proposed in the literature based on the reconstruction of the missing/corrupted projection data using the raw data directly from the tomographs. This paper proposes an image-based strategy consisting of the image registration and the morphological reconstruction. Preliminary results on the CT images from different CT scanners and patients are presented and discussed.
Predicting Patient State-of-Health using Sliding Window and Recurrent Classifiers

Bedside monitors in Intensive Care Units (ICUs) frequently sound incorrectly, slowing response times and desensitising nurses to alarms (Chambrin, 2001), causing true alarms to be missed (Hug et al., 2011). We compare sliding window predictors with recurrent predictors to classify patient state-of-health from ICU multivariate time series; we report slightly improved performance for the RNN for three out of four targets.
Intervention with Male Toddlers who have Witnessed Parental Violence

Research evidence indicates that witnessing parental violence has serious negative effects on children and may predispose male children, in particular, to become violent in future relationships. This study utilizes attach' ment theory as a framework for understanding and intervening with male toddlers and their mothers in the aftermath of domestic violence. A detailed case study is used to illustrate this intervention approach.
Are there effects of a match between learning style and teaching style in an EFL classroom?

ABSTRACT Purpose. This study aimed to explore whether a match between learning style and teaching style in English as a foreign language (EFL) class affects two student variables: proficiency and motivation to learn English. Design/methodology/approach. Participants consisted of nine EFL teachers and 331 Japanese undergraduate students who were required to take EFL courses. To examine learning style and teaching style, we applied the Kolb Learning Style Inventory and the Kolb Educator Role Profile, respectively. Findings. We created groups for student-teacher match and student-teacher mismatch (i.e., student’s learning style vs. teacher’s teaching style). The match group including four matched learning style–teaching style pairs was significantly related to proficiency and motivation, while the mismatch group including all other pairs was also significantly related to them. When further analysing the four constituent pairs within the match group, results varied in effect, depending on not only the pair of learning and teaching style but also the variables. Originality/value. This study was the first to examine how specific matched learning style–teaching style pairs affect proficiency and motivation. The results add to the literature on the mixed effects of matched versus mismatched styles, highlighting the complexity of the relationship and the possible reasons for some of the effects.
Real World Routing Using Virtual World Information

In this paper, we propose to leverage socialgraphs from Online Social Networks (OSN) to improve theforwarding efficiency of mobile networks, more particularlyDelay Tolerant Networks (DTN). We extract communitystructures from three popular OSNs, Flickr, LiveJournal,and YouTube, and quantify the clustering features of eachnetwork at different levels of hierarchical resolution. Wethen show how community information can be used forforwarding using hints small enough to store on a mobiledevice. We also provide a first comparison study of thetopological community structures for different types ofOSNs with millions of users.
Silencing of the hTERT gene through RNA interference induces apoptosis via Bax/Bcl-2 in human glioma cells

Glioma cells are characterized by their invasiveness and resistance to conventional therapeutics. The downregulation of human telomerase reverse transcriptase (hTERT) can lead to decreased cell proliferation and/or the induction of apoptotic cell death in cancer cells but has rarely been reported in glioma cells. Here, we assessed the effect of the silencing of the hTERT gene on cell apoptosis and its possible molecular mechanism in T98G glioma cells. We found that the silencing of the hTERT gene in T98G cells significantly decreased cell proliferation and telomerase activity, increased the number of cells in G1 phase and decreased the number of cells in S phase, and induced apoptosis via decreasing the protein level of Bcl-2 and c-Myc and increasing the protein levels of Bax and p53.
Asymmetrical structure of ionization and kinematics in the Seyfert galaxy NGC 5033

We present integral field spectroscopy of NGC 5033, a low luminosity Seyfert galaxy. The observations were made with INTEGRAL, a fiber based system operating at the WHT. The intensity map of the H emission line represents a spiral or ring-like pattern of HII regions. On the contrary, the [OIII] intensity map morphology is markedly anisotropic. The strong morphological differences imply that the [ OIII] emitters represent highly ionized gas illuminated by the central source. The [ OIII] map morphology is compatible with a biconical structure of ionization induced by strong extinction in the galaxy disc that also obscures half of the spheroidal stellar bulge. We identify the spectrum corresponding to the Seyfert 1 nucleus from the presence of H broad emission lines. This spectrum is located in a region where strong extinction is expected but exhibits the bluest spectral energy distribution. The Seyfert 1 nucleus seems to be off center with respect to the stellar rotation center. This result has been also found in other Seyfert galaxies and interpreted in terms of a past merger. The off centering could indicate the presence of nonsymmetric departures in the gravitational potential which could be fueling the active nucleus. The kinematics of the [ OIII] emitters show important deviations at a kpc scale with respect to the stellar velocity field and show features related to the asymmetrical morphology of the high ionization region.
Adaptive Models for Gene Networks

Biological systems are often treated as time-invariant by computational models that use fixed parameter values. In this study, we demonstrate that the behavior of the p53-MDM2 gene network in individual cells can be tracked using adaptive filtering algorithms and the resulting time-variant models can approximate experimental measurements more accurately than time-invariant models. Adaptive models with time-variant parameters can help reduce modeling complexity and can more realistically represent biological systems.
Detection and spatial analysis of hepatic steatosis in histopathology images using sparse linear models

Hepatic steatosis is a defining feature of nonalcoholic fatty liver disease, emerging with the increasing incidence of obesity and metabolic syndrome. The research in image-based analysis of hepatic steatosis mostly focuses on the quantification of fat in biopsy images. This work furthers the image-based analysis of hepatic steatosis by exploring the spatial characteristics of fat globules in whole slide biopsy images after performing fat detection. An algorithm based on morphological filtering and sparse linear models is presented for fat detection. Then the spatial properties of detected fat globules in relation to the hepatic anatomical structures of central veins and portal tracts are explored. The test dataset consists of 38 high resolution images from 21 patients. The experimental results provide an insight into the size distributions of fat globules and their location with respect to the anatomical structures.
BRG1 and BRM loss selectively impacts RB and P53, respectively: BRG1 and BRM have differential functions in vivo

The SWI/SNF complex is an important regulator of gene expression that functions by interacting with a diverse array of cellular proteins. The catalytic subunits of SWI/SNF, BRG1 and BRM, are frequently lost alone or concomitantly in a range of different cancer types. This loss abrogates SWI/SNF complex function as well as the functions of proteins that are required for SWI/SNF function, such as RB1 and TP53. Yet while both proteins are known to be dependent on SWI/SNF, we found that BRG1, but not BRM, is functionally linked to RB1, such that loss of BRG1 can directly or indirectly inactivate the RB1 pathway. This newly discovered dependence of RB1 on BRG1 is important because it explains why BRG1 loss can blunt the growth-inhibitory effect of tyrosine kinase inhibitors (TKIs). We also observed that selection for Trp53 mutations occurred in Brm-positive tumors but did not occur in Brm-negative tumors. Hence, these data indicate that, during cancer development, Trp53 is functionally dependent on Brm but not Brg1. Our findings show for the first time the key differences in Brm- and Brg1-specific SWI/SNF complexes and help explain why concomitant loss of Brg1 and Brm frequently occurs in cancer, as well as how their loss impacts cancer development.
An adaptive framework for personalized recommendation algorithms

Different personalized recommendation algorithms are suitable for different scenarios. In this paper, we use artificial neural networks to implement an adaptive framework. When we add different recommendation algorithms into it and train it with the data from a given scenario, it can calculate the weight of each algorithm, choose suitable algorithms and give a more accurate prediction rating.
Systems Analysis of N-Glycan Processing in Mammalian Cells

N-glycosylation plays a key role in the quality of many therapeutic glycoprotein biologics. The biosynthesis reactions of these oligosaccharides are a type of network in which a relatively small number of enzymes give rise to a large number of N-glycans as the reaction intermediates and terminal products. Multiple glycans appear on the glycoprotein molecules and give rise to a heterogeneous product. Controlling the glycan distribution is critical to the quality control of the product. Understanding N-glycan biosynthesis and the etiology of microheterogeneity would provide physiological insights, and facilitate cellular engineering to enhance glycoprotein quality. We developed a mathematical model of glycan biosynthesis in the Golgi and analyzed the various reaction variables on the resulting glycan distribution. The Golgi model was modeled as four compartments in series. The mechanism of protein transport across the Golgi is still controversial. From the viewpoint of their holding time distribution characteristics, the two main hypothesized mechanisms, vesicular transport and Golgi maturation models, resemble four continuous mixing-tanks (4CSTR) and four plug-flow reactors (4PFR) in series, respectively. The two hypotheses were modeled accordingly and compared. The intrinsic reaction kinetics were first evaluated using a batch (or single PFR) reactor. A sufficient holding time is needed to produce terminally-processed glycans. Altering enzyme concentrations has a complex effect on the final glycan distribution, as the changes often affect many reaction steps in the network. Comparison of the glycan profiles predicted by the 4CSTR and 4PFR models points to the 4PFR system as more likely to be the true mechanism. To assess whether glycan heterogeneity can be eliminated in the biosynthesis of biotherapeutics the 4PFR model was further used to assess whether a homogeneous glycan profile can be created through metabolic engineering. We demonstrate by the spatial localization of enzymes to specific compartments all terminally processed N-glycans can be synthesized as homogeneous products with a sufficient holding time in the Golgi compartments. The model developed may serve as a guide to future engineering of glycoproteins.
Bimodal Distribution of Glucose Is Not Universally Useful for Diagnosing Diabetes

OBJECTIVE—Bimodality in the distribution of glucose has been used to define the cut point for the diagnosis of diabetes. Previous studies on bimodality have primarily been in populations with a high prevalence of type 2 diabetes, including one study in a white Caucasian population. All studies included participants with known diabetes. The aim of this study was to assess whether a bimodal structure is a general phenomenon in fasting plasma glucose (FPG) and 2-h plasma glucose that is useful for deriving a common cut point for diabetes in populations of different origin, both including and excluding known diabetes. RESEARCH DESIGN AND METHODS—The Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) project is an international collaboration pooling surveys from all continents. These studies include surveys in which plasma glucose was measured during an oral glucose tolerance test; in total, 43 studies (135,383 participants) from 27 countries were included. A mixture of two normal distributions was fitted to plasma glucose levels, and a cut point for normal glycemia was estimated as their intersection. In populations with a biologically meaningful cut point, bimodality was tested for significance. RESULTS—Distributions of FPG and 2-h plasma glucose did not, in general, produce bimodal structures useful for deriving cut points for diabetes. When present, the cut points produced were inconsistent over geographical regions. CONCLUSIONS—Deriving cut points for normal glycemia from distributions of FPG and 2-h plasma glucose does not appear to be suitable for defining diagnostic cut points for diabetes.
Multimodal Analogies in Modelling and Design

Drawings, on the one hand, and teleological models, on the other, are two ways of understanding and communicating design information. Drawing on previous work, Structure-Behavior-Function (SBF) theory claims that teleological knowledge is comprised of three basic kinds of knowledge: structural knowledge, behavioral knowledge, and functional knowledge. However, the design task, in practice, revolves around drawings. For example, Computer-Aided Design (CAD) software manipulates and produces drawings, and to produce a design is to produce a set of documents that primarily consists of drawings of that design. And yet, drawings can, at best, represent only structural knowledge, and even that incompletely, as components’ roles in the design are not and cannot be determined solely by the drawing. Two questions motivate this research: (1) what role, precisely, do drawings place in the design process? and (2) how can we enhance CAD tools to make more direct use of teleological knowledge? This work explores two problems: model construction and design generation. The problem of constructing an SBF model of a mechanical device from a drawing can be solved in a robust and tractable way using analogical reasoning, by reasoning from visual and topological differences to structural, causal, and functional differences in models. Patterns of adaptation and transfer can be captured by Generic Visual Teleological Mechanisms (GVTMs), generic patterns of adaptation that capture particular abstractions. Likewise, the problem of design generation, proceeding from a functional specification to a drawing associated with a complete SBF model, can be solved in a robust and tractable manner using analogical reasoning from functional differences to structural and behavioral differences in models, and ultimately to visual differences in drawings. Patterns of adaptation, here, can be effectively solved by Generic Teleological Drawing Mechanisms (GTDMs), capturing similar patterns to GVTMs, but proceeding from function to drawing instead of the reverse. Both are essentially constructive, and together help to elucidate the nature and interplay between visual structure and topology, on the one hand, and causality and teleology, on the other hand, in modelling and design.
DESIGN AND RELIABILITY ANALYSIS OF A 4:1 MUX USING SINGLE ELECTRON TUNNELING TECHNOLOGY BASED THRESHOLD LOGIC GATE

As single electron tunneling technology based threshold logic gate uses less no of tunnel junctions so it reduces the size of Boolean logic gate compare to single electron tunneling based logic gate and single electron transistor based logic gate. The design and simulation of a 4:1 multiplexer based on buffered threshold logic gate is presented in this paper. The logic operation is verified using Monte Carlo based simulation tool SIMON. The reliability of the designed circuit is analyzed using MATLAB and SIMON. A comparison of the reliability for normal and uniform distribution of background charges has been shown in the present work. The stability of the circuit is analyzed using free energy history diagram and stability plot. Also the stability analysis for different operating temperature has been shown in this paper.