Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluency: A review of developmental and remedial practices.

The authors review theory and research relating to fluency instruction and development. They surveyed the range of definitions for fluency, primary features of fluent reading, and studies that have attempted to improve the fluency of struggling readers. They found that (a) fluency instruction is generally effective, although it is unclear whether this is because of specific instructional features or because it involves children in reading increased amounts of text; (b) assisted approaches seem to be more effective than unassisted approaches; (c) repetitive approaches do not seem to hold a clear advantage over nonrepetitive approaches; and (d) effective fluency instruction moves beyond automatic word recognition to include rhythm and expression, or what linguists refer to as the prosodic features of language. The process of becoming literate can be conceptualized as a series of qualitatively different stages through which learners progress as they become increasingly proficient with print (Chall, 1996b; Harris & Sipay, 1990). One of the primary advances in this process involves the shift from dealing with words on a word-byword basis to a rapid, accurate, and expressive rendering of text. In other words, learners develop such familiarity with print that they achieve fluency in their reading. Fluent reading may underlie or assist in effective engagement with text (LaBerge & Samuels, 1974). The purpose of this article is a review of the literature examining how children move toward fluent reading. It will incorporate both theoretical discussions and practical studies relating to fluency research. Specifically, to accomplish this purpose, we have reviewed the theoretical accounts of reading that include an important role for fluency in the reading process and studies that have attempted to facilitate its development.
Discriminator at SemEval-2018 Task 10: Minimally Supervised Discrimination

We participated to the SemEval-2018 shared task on capturing discriminative attributes (Task 10) with a simple system that ranked 8th amongst the 26 teams that took part in the evaluation. Our final score was 0.67, which is competitive with the winning score of 0.75, particularly given that our system is a zero-shot system that requires no training and minimal parameter optimisation. In addition to describing the submitted system, and discussing the implications of the relative success of such a system on this task, we also report on other, more complex models we experimented with.
Cleaved Mini-DysferlinC 72 , and L-Type Channels Underpin Calcium-Dependent Muscle Membrane Repair

Angela Lek,1,2 Frances J. Evesson,1,2 Frances A. Lemckert,1,2 Gregory M. I. Redpath,1,2 Ann-Katrin Lueders,1 Lynne Turnbull,3 Cynthia B. Whitchurch,3 Kathryn N. North,1,2 and Sandra T. Cooper1,2 1Institute for Neuroscience and Muscle Research, Children’s Hospital at Westmead, Sydney, NSW 2145, Australia, 2Discipline of Paediatrics and Child Health, Faculty of Medicine, University of Sydney, Sydney, NSW 2006, Australia, and 3Microbial Imaging Facility, ithree institute, University of Technology Sydney, Broadway, NSW 2007, Australia
Designing for Virtual Communities in the Service of Learning: Computer-Mediated Discourse Analysis

Over the past fifteen years, the Internet has triggered a boom in research on human behavior. As growing numbers of people interact on a regular basis in chat rooms, web forums, listservs, email, instant messaging environments and the like, social scientists, marketers, and educators look to their behavior in an effort to understand the nature of computer-mediated communication and how it can be optimized in specific contexts of use. This effort is facilitated by the fact that people engage in socially meaningful activities online in a way that typically leaves a textual trace, making the interactions more accessible to scrutiny and reflection than is the case in ephemeral spoken communication, and enabling researchers to employ empirical, micro-level methods to shed light on macro-level phenomena. Despite this potential, much research on online behavior is anecdotal and speculative, rather than empirically grounded. Moreover, Internet research often suffers from a premature impulse to label online phenomena in broad terms, for example, all groups of people interacting online are “communities”; the language of the Internet is a single style or “genre. ” Notions such as community and genre are familiar and evocative, yet notoriously slippery, and unhelpful (or worse) if applied indiscriminately. An important challenge facing Internet researchers is thus how to identify and describe online phenomena in culturally meaningful terms, while at the same time grounding their distinctions in empirically observable behavior.
Apparatus for Scalable Functionalization of Single-Walled Carbon Nanotubes via the Billups-Birch Reduction

A prototype design of a reactor for scalable functionalization of SWCNTs by the reaction of alkyl halides with Billups-Birch reduced SWCNTs is described. The Hauge apparatus is designed to allow for the safe handling of all the reagents and products under an inert atmosphere at controlled temperatures. The extent of reaction of Li/NH3 solution with the SWCNTs is measured in-situ by solution conduction, while homogenous mixing is ensured by the use of a homogenizer, and thermocouple are placed at different heights within the reactor flask. Addition of an alkyl halide yield alkyl-functionalized SWCNTs, which may be isolated by solvent extraction leaving a solid sample that is readily purified by hydrocarbon extraction. As an example, reaction of SWCNT/Li/NH3 with 1-iododecane yields dodecane-functionalized SWCNTs (C12-SWCNTs), which have been characterized by TG/DTA, XPS, and Raman spectroscopy. Sample extraction during the reaction allows for probing of the rate of the reaction in order to determine the end point of the reaction, which for C12-SWCNTs (at −78 °C) is 30 min.
The visual fields of two ground-foraging birds, House Finches and House Sparrows, allow for simultaneous foraging and anti-predator vigilance

In birds, differences in the extent and position of the binocular visual field reflect adaptations to varying foraging strategies, and the extent of the lateral portion of the field may reflect anti-predator strategies. The goal of this study was to describe and compare the visual fields of two ground-foraging passerines, House Finch Carpodacus mexicanus and House Sparrow Passer domesticus . We found that both species have a binocular field type that is associated with the accurate control of bill position when pecking. Both species have eye movements of relatively large amplitude, which can produce substantial variations in the configuration of the binocular fields. We propose that in these ground foragers, their relatively wide binocular fields could function to increase foraging efficiency by locating multiple rather than single food items prior to pecking events. The lateral fields of both species are wide enough to facilitate the detection of predators or conspecifics while head-down foraging. This suggests that foraging and scanning are not mutually exclusive activities in these species, as previously assumed. Furthermore, we found some slight, but significant, differences between species: House Sparrow binocular fields are both wider and vertically taller, and the blind area is wider than in House Finches. These differences may be related to variations in the degree of eye movements and position of the orbits in the skull.
An optimized system to solve text-based CAPTCHA

CAPTCHA(Completely Automated Public Turing test to Tell Computers and Humans Apart) can be used to protect data from auto bots. Countless kinds of CAPTCHAs are thus designed, while we most frequently utilize text-based scheme because of most convenience and user-friendly way \cite{bursztein2011text}. Currently, various types of CAPTCHAs need corresponding segmentation to identify single character due to the numerous different segmentation ways. Our goal is to defeat the CAPTCHA, thus firstly the CAPTCHAs need to be split into character by character. There isn't a regular segmentation algorithm to obtain the divided characters in all kinds of examples, which means that we have to treat the segmentation individually. In this paper, we build a whole system to defeat the CAPTCHAs as well as achieve state-of-the-art performance. In detail, we present our self-adaptive algorithm to segment different kinds of characters optimally, and then utilize both the existing methods and our own constructed convolutional neural network as an extra classifier. Results are provided showing how our system work well towards defeating these CAPTCHAs.
Dominance or Challenge? An Explanation of Power Structures Among Coalitions in Swiss Decision-Making Processes

This paper studies the conditions under which a given power distribution among coalitions of collective actors in political decision-making processes emerge. The distribution of power among actors is one of the basic dimensions of politics and is important because of its influence on the output of the decision-making processes. The paper distinguishes between ideal-types of power structures with a dominant coalition (“dominance”) and structures with distributed power among several coalitions (“challenge”). It takes into account four conditions supposed to interact with each other, i.e. the degree of federalism of a policy project, its degree of Europeanization, its policy type (i.e. direct vs. indirect coercion), and the openness of the pre-parliamentary phase of the decision-making process. In order to assess the importance of these conditions, I compare the 11 most important decision-making processes in Switzerland between 2001 and 2006 by a Fuzzy-Set Qualitative Comparative Analysis (fsQCA). Results suggest that Europeanization or an open pre-parliamentary phase lead to a power structure of dominance, whereas only a specific combination of all four conditions is able to explain power structures of challenge. I argue that this is good news for the integration capacity of the Swiss political system.
Direct control of mode-locking states of a fiber laser

Mode locking is a non-equilibrium steady state. Capability to control mode-locking states can be used to improve performance as well as shed light on non-equilibrium physics using the laser as an experimental platform. We demonstrate direct control of the mode-locking state using spectral pulse shaping by incorporating a spatial light modulator at a Fourier plane inside the cavity of an Yb-doped fiber laser. We show that we can halt and restart mode locking, suppress instabilities, induce controlled reversible and irreversible transitions between mode-locking states, and perform advanced pulse shaping while using pulses as short as 40 fs.
Electric field-controlled magnetization switching in Co/Pt thin-film ferromagnets

Abstract A study of dynamic and reversible voltage-controlled magnetization switching in ferromagnetic Co/Pt thin film with perpendicular magnetic anisotropy at room temperature is presented. The change in the magnetic properties of the system is observed in a relatively thick film of 15 nm. A surface charge is induced by the formation of electrochemical double layer between the metallic thin film and non-aqueous lithium LiClO4 electrolyte to manipulate the magnetism. The change in the magnetic properties occurred by the application of an external electric field. As the negative voltage was increased, the coercivity and the switching magnetic field decreased thus activating magnetization switching. The results are envisaged to lead to faster and ultra-low-power magnetization switching as compared to spin-transfer torque (STT) switching in spintronic devices.
Sensitization of PTB7:PC71BM organic solar cells using Si-PCPDTBT

Ternary blend solar cells are a promising approach to improve the efficiency of bulk heterojunction organic solar cells. We demonstrated ternary blend solar cells composed of PTB7:Si-PCPDTBT:PC71BM as photoactive layers. In this study, we varied the concentration of the Si-PCPDTBT sensitizer. Si-PCPDTBT was shown to sensitize the spectral response of PTB7 to longer wavelengths. In turn, the ternary blend solar cells, with a sensitizer concentration of 15 wt%, generated more photocurrent than the reference PTB7:PC71BM. An increase in the device fill factor (FF) was also observed that was further investigated by impedance spectroscopy measurement. This material combination couples the high performance of PTB7 and long wavelength response of Si-PCPDTBT. A power conversion efficiency enhancement of 29% was observed for the ternary system.
A protocol for quantifying hydrogen evolution by dye-sensitized molecular photocathodes and its implementation for evaluating a new covalent architecture based on an optimized dye-catalyst dyad.

A protocol that combines gas chromatography and a high-sensitivity micro Clark-type electrode is described to quantify hydrogen production across gas and solution phases for systems operating at very low currents such as dye-sensitized H2-evolving photocathodes. Data indicate that a significant fraction of H2 remains in aqueous solution even after several hours of experiments. Using this protocol, re-evaluation of a dye-sensitized H2-evolving photocathode based on a dye-catalyst dyad showed a reproducible 66% increase of the faradaic efficiency compared with previously reported headspace GC measurements [Kaeffer et al., J. Am. Chem. Soc. , 2016, 138, 12308-12311]. This dyad was based on an organic push-pull dye where donor and acceptor are separated by one thiophene group. Insertion of a second thiophene group between the donor and acceptor led to a more efficient system with 30% improved faradaic efficiency for H2 evolution.
Neural Storyline Extraction Model for Storyline Generation from News Articles

Storyline generation aims to extract events described on news articles under a certain news topic and reveal how those events evolve over time. Most approaches to storyline generation first train supervised models to extract events from news articles published in different time periods and then link relevant extracted events into coherent stories. They are domain dependent and cannot deal with unseen event types. To tackle this problem, approaches based on probabilistic graphic models jointly model the generations of events and storylines without the use of annotated data. However, the parameter inference procedure is too complex and models often require long time to converge. In this paper, we propose a novel neural network based approach to extract structured representations and evolution patterns of storylines without using annotated data. In this model, title and main body of a news article are assumed to share the similar storyline distribution. Moreover, similar documents described in neighboring time periods are assumed to share similar storyline distributions. Based on these assumptions, structured representations and evolution patterns of storylines can be extracted. The proposed model has been evaluated on three news corpora and the experimental results show that it outperforms state-of-the-art approaches for storyline generation on both accuracy and efficiency.
Zwift: A Programming Framework for High Performance Text Analytics on Compressed Data

Today's rapidly growing document volumes pose pressing challenges to modern document analytics frameworks, in both space usage and processing time. Recently, a promising method, called text analytics directly on compressed data (TADOC), was proposed for improving both the time and space efficiency of text analytics. The main idea of the technique is to enable direct document analytics on compressed data. This paper focuses on the programming challenges for developing efficient TADOC programs. It presents Zwift, the first programming framework for TADOC, which consists of a Domain Specific Language, a compiler and runtime, and a utility library. Experiments show that Zwift significantly improves programming productivity, while effectively unleashing the power of TADOC, producing code that reduces storage usage by 90.8% and execution time by 41.0% on six text analytics problems.
Fast Automatic Vehicle Annotation for Urban Traffic Surveillance

Automatic vehicle detection and annotation for streaming video data with complex scenes is an interesting but challenging task for intelligent transportation systems. In this paper, we present a fast algorithm: detection and annotation for vehicles (DAVE), which effectively combines vehicle detection and attributes annotation into a unified framework. DAVE consists of two convolutional neural networks: a shallow fully convolutional fast vehicle proposal network (FVPN) for extracting all vehicles’ positions, and a deep attributes learning network (ALN), which aims to verify each detection candidate and infer each vehicle’s pose, color, and type information simultaneously. These two nets are jointly optimized so that abundant latent knowledge learned from the deep empirical ALN can be exploited to guide training the much simpler FVPN. Once the system is trained, DAVE can achieve efficient vehicle detection and attributes annotation for real-world traffic surveillance data, while the FVPN can be independently adopted as a real-time high-performance vehicle detector as well. We evaluate the DAVE on a new self-collected urban traffic surveillance data set and the public PASCAL VOC2007 car and LISA 2010 data sets, with consistent improvements over existing algorithms.
Depth and nonlinearity induce implicit exploration for RL

The question of how to explore, i.e., take actions with uncertain outcomes to learn about possible future rewards, is a key question in reinforcement learning (RL). Here, we show a surprising result: We show that Q-learning with nonlinear Q-function and no explicit exploration (i.e., a purely greedy policy) can learn several standard benchmark tasks, including mountain car, equally well as, or better than, the most commonly-used $\epsilon$-greedy exploration. We carefully examine this result and show that both the depth of the Q-network and the type of nonlinearity are important to induce such deterministic exploration.
Primate frontal eye fields. II. Physiological and anatomical correlates of electrically evoked eye movements.

We studied single neurons in the frontal eye fields of awake macaque monkeys and compared their activity with the saccadic eye movements elicited by microstimulation at the sites of these neurons. Saccades could be elicited from electrical stimulation in the cortical gray matter of the frontal eye fields with currents as small as 10 microA. Low thresholds for eliciting saccades were found at the sites of cells with presaccadic activity. Presaccadic neurons classified as visuomovement or movement were most associated with low (less than 50 microA) thresholds. High thresholds (greater than 100 microA) or no elicited saccades were associated with other classes of frontal eye field neurons, including neurons responding only after saccades and presaccadic neurons, classified as purely visual. Throughout the frontal eye fields, the optimal saccade for eliciting presaccadic neural activity at a given recording site predicted both the direction and amplitude of the saccades that were evoked by microstimulation at that site. In contrast, the movement fields of postsaccadic cells were usually different from the saccades evoked by stimulation at the sites of such cells. We defined the low-threshold frontal eye fields as cortex yielding saccades with stimulation currents less than or equal to 50 microA. It lies along the posterior portion of the arcuate sulcus and is largely contained in the anterior bank of that sulcus. It is smaller than Brodmann's area 8 but corresponds with the union of Walker's cytoarchitectonic areas 8A and 45. Saccade amplitude was topographically organized across the frontal eye fields. Amplitudes of elicited saccades ranged from less than 1 degree to greater than 30 degrees. Smaller saccades were evoked from the ventrolateral portion, and larger saccades were evoked from the dorsomedial portion. Within the arcuate sulcus, evoked saccades were usually larger near the lip and smaller near the fundus. Saccade direction had no global organization across the frontal eye fields; however, saccade direction changed in systematic progressions with small advances of the microelectrode, and all contralateral saccadic directions were often represented in a single electrode penetration down the bank of the arcuate sulcus. Furthermore, the direction of change in these progressions periodically reversed, allowing particular saccade directions to be multiply represented in nearby regions of cortex. (ABSTRACT TRUNCATED AT 400 WORDS)
Genetic and environmental factors associated with the virulence of fish pathogen Flavobacterium columnare

Penttinen, Reetta Genetic and Environmental Factors Associated with the Virulence of Fish Pathogen Flavobacterium columnare Jyväskylä: University of Jyväskylä, 2016, 58 p. (Jyväskylä Studies in Biological and Environmental Science ISSN 1456-9701; 316) ISBN 978-951-39-6646-1 (nid.) ISBN 978-951-39-6647-8 (PDF) Yhteenveto: Kalapatogeeni Flavobacterium columnaren virulenssiin vaikuttavat geneettiset ja ympäristölliset tekijät Diss. Flavobacterium columnare is an environmentally transmitted pathogen that annually causes fatal infections and economic harm in aquaculture on a global scale. However, its virulence mechanisms are largely unknown. In this thesis, I explored new virulence determinants of F. columnare by comparative studies on virulent and non-virulent colony types. First, the cell and colony surface structures were examined with high resolution scanning electron microscopy (HR-SEM). Second, a RT-qPCR protocol was developed to explore the gene expression of putative virulence factors and the effect of nutrient availability on virulence factor expression. Finally, the gene expression of gliding motility machinery and type IX secretion system (T9SS) components was studied in various nutrient conditions, as these systems putatively contribute to F. columnare virulence. HR-SEM revealed active production of outer membrane vesicles, which are used for virulence factor transport in several other bacterial species. The analysis of extracellularly secreted proteins revealed a ~13 kDa protein, which is specific for the virulent colony type. The gene expression studies showed significantly higher expression of tissue-degrading chondroitinase in the virulent colony type, confirming its role as a virulence factor. Furthermore, high nutrient availability increased the virulence factor expression and caused more rapid fish mortality. The environmental nutrients also regulated colony spreading in the motile colony types and part of the genes involved in gliding motility and T9SS. These findings demonstrate that nutrients are important regulators of F. columnare physiology with respect to virulence factor expression, motility and secretion – all of which are important virulence attributes. However, the molecular mechanisms and the regulatory pathways underlying these changes require further studies to fully understand the infection process of this pathogen.
Automatic Measurement of Lead Time of Repetitive Assembly Work in a Factory Using a Wearable Sensor

: In this paper, we attempt to estimate lead time (duration) of each period of an operation process by a factory worker using a wrist-worn accelerometer. In a factory line production system, a worker repetitively performs prede-ﬁned operation processes, and the lead time greatly a ﬀ ects productivity of the line production system. Our proposed method automatically ﬁnds a frequent sensor data segment as a “motif” that occurs once in each operation period using only prior knowledge about predeﬁned standard lead time of the operation process, and uses the occurrence intervals of the motif to estimate the lead time.