Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating children's interactions around digital texts in classrooms: how are these framed and what counts?

This article argues that, in informing our understanding of the possibilities and challenges associated with new technologies in educational contexts, we need to explore what counts to children when using digital texts in classrooms, and what children think counts for their teachers. It suggests that such insights can be gained by investigating children's interactions around these texts and, drawing on Goffman's work, considering how these are framed. This is illustrated using examples from a study of classroom digital literacy events. The article suggests that it is important to consider how frames disrupt, intersect with and over-layer each other.
Randomized Dual Coordinate Ascent with Arbitrary Sampling

We study the problem of minimizing the average of a large number of smooth convex functions penalized with a strongly convex regularizer. We propose and analyze a novel primal-dual method (Quartz) which at every iteration samples and updates a random subset of the dual variables, chosen according to an arbitrary distribution. In contrast to typical analysis, we directly bound the decrease of the primal-dual error (in expectation), without the need to first analyze the dual error. Depending on the choice of the sampling, we obtain efficient serial, parallel and distributed variants of the method. In the serial case, our bounds match the best known bounds for SDCA (both with uniform and importance sampling). With standard mini-batching, our bounds predict initial data-independent speedup as well as additional data-driven speedup which depends on spectral and sparsity properties of the data. We calculate theoretical speedup factors and find that they are excellent predictors of actual speedup in practice. Moreover, we illustrate that it is possible to design an efficient mini-batch importance sampling. The distributed variant of Quartz is the first distributed SDCA-like method with an analysis for non-separable data.
Draft Genome Sequence of Streptomyces albulus Strain CCRC 11814, an ε-Poly-l-Lysine-Producing Actinomycete

ABSTRACT Here, we report the draft genome sequence of Streptomyces albulus strain CCRC 11814, a soil-dwelling, Gram-positive bacterium. S. albulus produces ε-poly-l-lysine, which has diverse antimicrobial activity. The genome is 9.43 Mb in size, with a G+C content of 72.2%, and contains 9,177 protein-coding sequences.
Gastric Cancer (Biomarkers) Knowledgebase (GCBKB): A Curated and Fully Integrated Knowledgebase of Putative Biomarkers Related to Gastric Cancer

The Gastric Cancer (Biomarkers) Knowledgebase (GCBKB) (http://biomarkers.bii.a-star.edu.sg/background/gastricCancerBiomarkersKb.php) is a curated and fully integrated knowledgebase that provides data relating to putative biomarkers that may be used in the diagnosis and prognosis of gastric cancer. It is freely available to all users. The data contained in the knowledgebase was derived from a large literature source and the putative biomarkers therein have been annotated with data from the public domain. The knowledgebase is maintained by a curation team who update the data from a defined source. As well as mining data from the literature, the knowledgebase will also be populated with unpublished experimental data from investigators working in the gastric cancer biomarker discovery field. Users can perform searches to identify potential markers defined by experiment type, tissue type and disease state. Search results may be saved, manipulated and retrieved at a later date. As far as the authors are aware this is the first open access database dedicated to the discovery and investigation of gastric cancer biomarkers.
Luteimonas terrae sp. nov., isolated from rhizosphere soil of Radix ophiopogonis.

A Gram-staining-negative, strictly aerobic, rod-shaped and bright-yellow-pigmented bacterium, motile by means of a single polar flagellum, designated THG-MD21T, was isolated from rhizosphere soil of Radix ophiopogonis in Henan province, PR China. On the basis of 16S rRNA gene sequence similarity, strain THG-MD21T belongs to the genus Luteimonas and was most closely related to Luteimonas aestuarii B9T (98.2 % sequence similarity), Lysobacter panaciterrae Gsoil 068T (97.2 %) and Luteimonas marina FR1330T (97.0 %). The DNA G+C content was 64.4 mol%. The DNA-DNA relatedness between strain THG-MD21T and its closest phylogenetic neighbours was below 30.0 %. The only isoprenoid quinone detected in strain THG-MD21T was ubiquinone-8.The major polar lipids were found to be phosphatidylethanolamine, phosphatidylglycerol and diphosphatidylglycerol, and the predominant fatty acids were iso-C11 : 0, iso-C15 : 0, iso-C16 : 0, C16 : 0 and iso-C17 : 1ω9c. The DNA-DNA hybridization result and characteristics revealed by a polyphasic study showed that strain THG-MD21T represents a novel species, for which the name Luteimonas terrae sp. nov. is proposed. The type strain is THG-MD21T ( = KACC 18131T = JCM 30122T).
Modeling and Analyzing Timed Security Protocols Using Extended Timed CSP

Security protocols are hard to design, even under the assumption of perfect cryptography. This is especially true when a protocol involves different timing aspects such as timestamps, timeout, delays and a set of timing constraints. In this paper, we propose a methodology for modeling and analyzing security protocols that are aware of timing aspects. We develop a formalism for modeling security protocols by extending Timed CSP with the capability of stating complicated timing behaviors for processes and events. A reasoning mechanism for the proposed formalism is developed based on Constraint Logic Programming (CLP). Using the reasoning engine built in CLP, the authentication properties of timed security protocols are able to be verified and attacks can be discovered. We demonstrate the capability of our method by modeling and verifying real-world security protocols. New approaches of using timing information to unfold and prevent potential attacks are also presented.
The Impact of DNA Input Amount and DNA Source on the Performance of Whole-Exome Sequencing in Cancer Epidemiology

Background: Whole-exome sequencing (WES) has recently emerged as an appealing approach to systematically study coding variants. However, the requirement for a large amount of high-quality DNA poses a barrier that may limit its application in large cancer epidemiologic studies. We evaluated the performance of WES with low input amount and saliva DNA as an alternative source material. Methods: Five breast cancer patients were randomly selected from the Pathways Study. From each patient, four samples, including 3 μg, 1 μg, and 0.2 μg blood DNA and 1 μg saliva DNA, were aliquoted for library preparation using the Agilent SureSelect Kit and sequencing using Illumina HiSeq2500. Quality metrics of sequencing and variant calling, as well as concordance of variant calls from the whole exome and 21 known breast cancer genes, were assessed by input amount and DNA source. Results: There was little difference by input amount or DNA source on the quality of sequencing and variant calling. The concordance rate was about 98% for single-nucleotide variant calls and 83% to 86% for short insertion/deletion calls. For the 21 known breast cancer genes, WES based on low input amount and saliva DNA identified the same set variants in samples from a same patient. Conclusions: Low DNA input amount, as well as saliva DNA, can be used to generate WES data of satisfactory quality. Impact: Our findings support the expansion of WES applications in cancer epidemiologic studies where only low DNA amount or saliva samples are available. Cancer Epidemiol Biomarkers Prev; 24(8); 1207–13. ©2015 AACR.
Integrating Dialectical and Accrual Modes of Argumentation

This paper argues that accrual should be modelled in terms of reasoning about the application of preferences to sets of arguments, and shows how such reasoning can be formalised within metalevel argumentation frameworks. These frameworks adopt the same machinery and level of abstraction as Dung's argumentation framework. We thus provide a dialectical argumentation semantics that integrates accrual, and illustrate our approach by instantiating our framework with the arguments and attacks defined by an object level formalism that accommodates reasoning about priorities over sets of rules.
A modified ACO algorithm for multicast state scalability problem based on multicast tree similarity

Traditional IP multicast technology establishes and maintains a tree for each multicast group, and this leads to a serious state scalability problem when large numbers of multicast groups exist in a network. As a novel scheme to address this scalability problem, aggregated multicast forces multiple groups which have identical or similar trees to use one deliver tree. Given the number of multicast trees, searching for an aggregation solution to minimize the average bandwidth waste rate is an important optimization problem in aggregated multicast. In this paper, we propose a modified ant colony optimization algorithm for this optimization problem. We define the similarity of multicast trees, and combine it with similarity sequence information to define the selection heuristic information of our algorithm according to the characteristics of similarity. Simulation results indicate that our algorithm has better evolutionary ability, and the selection heuristic information can overcome the initial blindness and improve the convergence time of ACO algorithm. Compared with a greedy algorithm, our algorithm has better optimization performance.
Prevalence and Social Influences of Delayed Language Development in Preschool-Age Saudi Children

: Introduction and Aim: The development of language skills and communication is one of the most important tasks of early childhood. It is key to early learning and a building block of social skills. This study was designed to measure the prevalence of language delay and to assess the social factors impacting the prevalence of language delay among preschool-age children in the Eastern Province of Saudi Arabia. Method: A cross-sectional descriptive study was conducted from November 2016 to March 2017; a total of 1235 children aged from 3 to 5 years were involved. This study collected data through a self-administered questionnaire completed by parents, containing 2 parts: Part 1—Arabic-Ages and Stages Questionnaire, third edition (A-ASQ), to assess the prevalence of language delay; and Part 2—Sociodemographic factors, social factors, and social interaction factors. Results: The overall prevalence of language delay was 24.5 percent. Language delay was more common in 3-year-old children (p<0.001), children of male sex (p<0.001), and children with a family history of language delay (p=0.001). There were statistically significant relations between language delay and the time of less than 2-houers mothers spent with children (p=0.008), time children spent playing alone or with electronic devices (p=0.011), and time children spent watching TV (with the effect appearing at more than 2 hours per day; p=0.001). Conclusion: Language delay among preschool-age children has a high prevalence in the Eastern Province. Language development is a useful indicator of a child’s overall development, including cognitive development, and language delay can negatively affect a child’s self-esteem, school achievement, and future career. These results thus justify the need for prevention, early detection, and treatment.
Warlpiri warriors: Australian Rules football in Central Australia

Yuendumu, located in the Tanami desert of the Northern Territory, is home to the largest Warlpiri community in Australia. We examine the role of Australian Rules football in this remote Indigenous community. Football is seen to operate on many layers of Warlpiri culture, from the traditional game of ‘purlja’, the introduction of modern football in the 1950s, the growth of sports weekends, community football and the Alice Springs competition to the journey of Liam Jurrah, the first Warlpiri man to make the journey from being a desert footballer to emerging as an Australian Football League star. The importance of football in Yuendumu is revealed as a vehicle for social cohesion, group identity, pride and joy, and as an expression of manhood, enabling its young men to see themselves as modern-day Warlpiri warriors.
SBSG 0335–052W: An Extremely Low Metallicity Dwarf Galaxy

We present Multiple Mirror Telescope and Keck II telescope spectrophotometry and 3.5 m Calar Alto telescope R, I photometry of the western component of the extremely low metallicity blue compact galaxy SBSG 0335-052. The components, separated by 22 kpc, appear to be members of a unique, physically connected system. It is shown that SBSG 0335-052W consists of at least three stellar clusters and has the same redshift as SBSG 0335-052. The oxygen abundance in its two brightest knots is extremely low, 12 + log(O/H) = 7.22 ± 0.03 and 7.13 ± 0.08, respectively. These values are lower than in SBSG 0335-052 and are nearly the same as those in I Zw 18. The R-I color profiles are very blue in both galaxies because of the combined effects of ionized gas and a young stellar population emission. We argue that SBSG 0335-052W is likely to be a nearby, young dwarf galaxy.
Identification and detection of electricity customer behaviour irregularities

The present case study focusing on TNB, Malaysia's largest power utility, concentrates on load profiles as manifestations of customer behaviour. The main objective here is to base the investigation on comparing the efficacy of the Support Vector Machine (SVM) technique with the newly emerging techniques of Extreme Learning Machine (ELM) and its OS-ELM variant as means of classification and prediction in this context. Non-technical losses (NTL) represent a significant proportion of electricity losses in both developing and developed countries. The ELM-based approach presented here uses customer load-profile information to expose abnormal behaviour that is known to be highly correlated with NTL activities. This approach provides a method of data mining for this purpose and it involves extracting patterns of customer behaviour from historical kWh consumption data. The results yield classification classes that are used to reveal whether any significant behaviour that emerges are due to irregularities in consumption. In this paper, ELM and online sequential-ELM (OS-ELM) algorithms are both used to achieve an improved classification performance and to increase accuracy of results. A comparison of this approach with other classification techniques, such as the Support Vector Machine (SVM) algorithm, is also undertaken and the ELM performance and accuracy in NTL analysis is shown to be superior.
Market Clearing Price prediction using ANN in Indian Electricity Markets

The electricity industry is evolving into a distributed and competitive in which market forces drive the price of the electricity and reduce the net cost through increased competition. Forecasting system Market Clearing Volume (MCV) and Market Clearing Price (MCP) has become even more important in order to make optimal bidding and profit maximization. This research work presents Artificial Neural Network (ANN) based forecasting model to estimate future Market Clearing Prices in Indian Electricity Markets. The model is verified by comparing the results of ANN with Regression model. The performance of the ANN and Regression models are evaluated on the data available on Indian Energy Exchange (IEX) site for the period January 2013 to March 2014. This paper forecasts the daily MCPs for the months of January, February and March for the year 2014. It is found that the forecasted MCPs in the Indian Electricity Markets have the less agreement with the ANN model and appropriate agreement with the Regression model. Consequently, it confirms about the unreliability and highly sensitiveness of ANN with respect to regression model. The Mean Absolute Percentage Errors (MAPEs) are evaluated to check the robustness of the two proposed methodologies.
The replication of plastid minicircles involves rolling circle intermediates

Plastid genomes of peridinin-containing dinoflagellates are unique in that its genes are found on multiple circular DNA molecules known as ‘minicircles’ of ∼2–3 kb in size, carrying from one to three genes. The non-coding regions (NCRs) of these minicircles share a conserved core region (250–500 bp) that are AT-rich and have several inverted or direct repeats. Southern blot analysis using an NCR probe, after resolving a dinoflagellate whole DNA extract in pulsed-field gel electrophoresis (PFGE), revealed additional positive bands (APBs) of 6–8 kb in size. APBs preferentially diminished from cells treated with the DNA-replication inhibitor aphidicolin, when compared with 2–3 kb minicircles, implicating they are not large minicircles. The APBs are also exonuclease III-sensitive, implicating the presence of linear DNA. These properties and the migration pattern of the APBs in a 2D-gel electrophoresis were in agreement with a rolling circle type of replication, rather than the bubble-forming type. Atomic force microscopy of 6–8 kb DNA separated by PFGE revealed DNA intermediates with rolling circle shapes. Accumulating data thus supports the involvement of rolling circle intermediates in the replication of the minicircles.
Left-Handed Metamaterial Coplanar Waveguide Components and Circuits in GaAs MMIC Technology

A set of novel left-handed LH) basic block monolithic-microwave integrated-circuit (MMIC) components (transmission line, open and short stubs) are presented with applications to the RF/microwave filter and power divider. These new open and short LH MMIC resonators have compact sizes of 0.11 and 0.22 mm2, respectively. The prototypes of an LH bandpass filter and LH power divider constructed from these basic components have been designed, fabricated, and characterized. The LH filter consisting of an LH transmission line and four LH open resonators exhibits transmission zeros at both sides of the passband from 1.02 to 1.42 GHz with 33.3% fractional bandwidth. The LH power divider including two LH branches shows equal power split from 2.8 to 3.72 GHz. The filter and power divider benefit from the miniaturized LH MMIC components and have compact sizes of 2.85 and 2.3 mm2, respectively. Loss issues of these LH structures and, more importantly, the effect of skin depth at low frequency are investigated. Full-wave simulations for conductor thicknesses of 0.2, 1.4, and 5 mum are presented for the proposed LH MMIC components and circuits. There is a good agreement between the full-wave simulations, equivalent-circuit model, and measurement results with 1.4-mum metal thickness demonstrating the effectiveness of the models.
Tenascin-C inhibits beta1 integrin-dependent cell adhesion and neurite outgrowth on fibronectin by a disialoganglioside-mediated signaling mechanism.

We have previously shown that the extracellular matrix molecule tenascin-C inhibits fibronectin-mediated cell adhesion and neurite outgrowth by an interaction with a cellular RGD-independent receptor which interferes with the adhesion and neurite outgrowth promoting activities of the fibronectin receptor(s). Here we demonstrate that the inhibitory effect of tenascin-C on beta1integrin-dependent cell adhesion and neurite outgrowth is mediated by the interaction of the protein with membrane-associated disialogangliosides, which interferes with protein kinase C-related signaling pathways. First, in substratum mixtures with fibronectin, an RGD sequence-containing fragment of the molecule or synthetic peptide, tenascin-C inhibited cell adhesion and spreading by a disialoganglioside-dependent, sialidase-sensitive mechanism leading to an inhibition of protein kinase C. Second, the interaction of intact or trypsinized, i.e., cell surface glycoprotein-free, cells with immobilized tenascin-C was strongly inhibited by gangliosides or antibodies to gangliosides and tenascin-C. Third, preincubation of immobilized tenascin-C with soluble disialogangliosides resulted in a delayed cell detachment as a function of time. Similar to tenascin-C, immobilized antibody to GD2 (3F8) or sphingosine, a protein kinase C inhibitor, strongly inhibited RGD-dependent cell spreading. Finally, the degree of tenascin-C-induced inhibition of cell adhesion was proportional to the degree of disialoganglioside levels of expression by different cells suggesting the relevance of such mechanism in modulating integrin-mediated cell-matrix interactions during pattern formation or tumor progression.
The Neuropsychology of Juvenile Delinquency: A Critical Review

Research on the performance of delinquent juveniles on neuropsychological tests suggests a role for brain dysfunction in the causation of antisocial behavior. Neuropsychological tests measure constructs representative of the various mental functions of the human brain, such as language, memory, or social judgment. Poor test scores suggest compromised brain function. Because the brain is the organ we use to perceive and respond to our environment, the relations of neuropsychological factors to delinquent behavior are expressed as interactions with social and environmental influences. Most studies of the neuropsychological status of delinquents suffer from notable methodological problems. Consistent findings of delinquency-related deficits, particularly in verbal and "executive" (self-control) functions, have nonetheless been reported by many studies, including those with the strongest designs. Neuropsychological variables predict variance in delinquent behavior independent of appropriate control variables.
Recognizing vehicle-contours with a compositional deformable model

This paper illustrates a compositional deformable model for detecting vehicle and recognizing vehicle-contours. To overcome the difficulties that vehicles in an image have various sizes, shapes, colors and poses, this model has two main characteristics: first, the model is made up of constituent parts which shared by vehicles. The locality of parts give the model the ability to recognize vehicles with different types (e.g., although vehicles have various sizes and shapes, they are usually composed by roof, windscreen, windows, etc.). Second, the spatial relationships of these parts are represented by Markov Random Field (MRF). The model is deformable to adapt to vehicles of different shapes and poses because of the appropriately changing of combinations of these parts in the MRF. Experimental results with real world images show that this method is effective in vehicle detection and vehicle-contours recognition.