Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning, Forgetting, and Relearning for Keystroke- and Mouse-Driven Tasks: Relearning Is Important

We investigate performance change arising through learning, forgetting, and relearning. Participants learned a spreadsheet task with either keystroke-driven (keyboard, n = 30) or mouse-based menu-driven (mouse, n = 30) commands. Their performance confirmed the power law of practice. The keyboard users learned to complete the task faster than the mouse users on the last learning session (Day 4). At a 6-day retention interval, the mouse users were observed to forget more—they took more time to complete the task than the keyboard users. Of interest, the participants in the two modality groups showed no reliable differences in their forgetting under the retention of 12 and 18 days. With additional practice, the mouse group users with the 6-day retention relearned more—they reliably reduced the time to complete the task in comparison to the paired keyboard group. These results help understand why people may choose to use a mouse-driven graphical user interface rather than a keystroke-driven interface: People choosing to use a mouse-based menu-driven interface may not need to use a knowledge-in-the-head strategy but knowledge-in-the-world, and may be doing so because this strategy provides better relearning, rather than because it is faster or easier initially or because it is better for learning or forgetting. These results provide a richer explanation of why menu-driven interfaces (knowledge-in-the-world) are more ubiquitous and suggests when they can be replaced, for example, where use is infrequent but often enough that forgetting does not substantially occur. Our results provide preliminary suggestions for choosing optimal training strategies and supporting these strategies in terms of the three stages of learning and forgetting.
A highly linear dual-band Doherty power amplifier for femto-cell base stations

A power amplifier (PA) for a femto-cell base station should be highly efficient, linear and small. The efficiency for amplification of a high peak-to-average power ratio (PAPR) signal is improved by designing an asymmetric Doherty PA (DPA). The linearity is improved by applying third-order inter-modulation (IM3) cancellation method. For dual-band operation, a tunable switched capacitor is applied. A small size is achieved by designing the DPA using GaN MMIC process. The implemented dual-band DPA delivers a DE of 45.5/41.6%, ACLR of -35.6/-34.5 dBc, and a gain of 15.7/13.2 dB with an average output power of 35.3/33.7 dBm, respectively, for a 7.2 dB PAPR 10 MHz bandwidth LTE signal at 2.3 and 2.65 GHz.
Using a learning analytics manager for monitoring of the collaborative learning activities and students' motivation into the Moodle system

The current paper presents the results related to the use of a Learning Analytics Manager for the monitoring processes of the collaborative learning activities and the students' motivation into the Learning Management System Moodle. The proposed manager was developed as a new functionality integrated to a service called Motivation Booster. This service is the result of a previous work that allowed it embedded into the Moodle system. A case study was performed with students enrolled in a Software Engineering course from the Computer Science Department during the first semester in the 2016 academic year at the Universidad Pontificia Bolivariana Seccional Montería (Colombia). The outcomes associated with collaborative learning variables and the motivational messages received by the students were analyzed from the feedback information showed through the implemented Learning Analytics Manager. The use of the proposed manager let to corroborate that the students improved the way to complete learning activities in the system.
The Corpus and the Lexicon: Standardising Deep Lexical Acquisition Evaluation

This paper is concerned with the standardisation of evaluation metrics for lexical acquisition over precision grammars, which are attuned to actual parser performance. Specifically, we investigate the impact that lexicons at varying levels of lexical item precision and recall have on the performance of pre-existing broad-coverage precision grammars in parsing, i.e., on their coverage and accuracy. The grammars used for the experiments reported here are the LinGO English Resource Grammar (ERG; Flickinger (2000)) and JaCY (Siegel and Bender, 2002), precision grammars of English and Japanese, respectively. Our results show convincingly that traditional F-score-based evaluation of lexical acquisition does not correlate with actual parsing performance. What we argue for, therefore, is a recall-heavy interpretation of F-score in designing and optimising automated lexical acquisition algorithms.
Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker

Multiple people tracking consists in detecting the subjects at each frame and matching these detections to obtain full trajectories. In semi-crowded environments, pedestrians often occlude each other, making tracking a challenging task. Most tracking methods make the assumption that each pedestrian's motion is independent, thereby ignoring the complex and important interaction between subjects. In this paper, we present an approach which includes the interaction between pedestrians in two ways: first, considering social and grouping behavior, and second, using a global optimization scheme to solve the data association problem. Results on three challenging publicly available datasets show our method outperforms state-of-the-art tracking systems.
The Occurrence and Effects of Verbal and Visual Anchoring of Tropes on the Perceived Comprehensibility and Liking of TV Commercials

For print advertising, it has been shown that rhetorical figures, tropes in particular, are used abundantly and that the effect on ad appreciation depends on the ad being perceived as comprehensible. To help the audience arrive at the intended interpretation, sometimes anchoring information is provided. The question is to what extent the same holds for TV commercials. A content analysis of 200 TV commercials revealed that the vast majority contained tropes and (verbal and visual) anchoring information that either hinted at the intended interpretation or spelled it out completely; this anchoring information could be presented before/during the trope or after. For each commercial, aggregated consumer response data were analyzed. Verbally and visually spelling out the intended interpretation increased the perceived comprehensibility. For the visual anchoring information, this led to higher appreciation scores; for verbal anchoring information, increased comprehensibility canceled out the negative effect on appreciation caused by providing this information. Verbal anchoring information presented after the trope improved appreciation compared to it being presented before or during. Advertisers appear to take into account that solving the riddle posed by a trope may be difficult if the processing pace is set by the medium and provide additional help.
Segmenting Motion Capture Data into Distinct Behaviors

Much of the motion capture data used in animations, commercials, and video games is carefully segmented into distinct motions either at the time of capture or by hand after the capture session. As we move toward collecting more and longer motion sequences, however, automatic segmentation techniques will become important for processing the results in a reasonable time frame.We have found that straightforward, easy to implement segmentation techniques can be very effective for segmenting motion sequences into distinct behaviors. In this paper, we present three approaches for automatic segmentation. The first two approaches are online, meaning that the algorithm traverses the motion from beginning to end, creating the segmentation as it proceeds. The first assigns a cut when the intrinsic dimensionality of a local model of the motion suddenly increases. The second places a cut when the distribution of poses is observed to change. The third approach is a batch process and segments the sequence where consecutive frames belong to different elements of a Gaussian mixture model. We assess these three methods on fourteen motion sequences and compare the performance of the automatic methods to that of transitions selected manually.
Activity-Dependent Presynaptic and Postsynaptic Structural Plasticity in the Mature Cerebellum

Two models of spine formation have been proposed. Spines can derive from emerging dendritic filopodia that have encountered presynaptic partners, or presynaptic molecules may induce the spine maturation event directly from the dendritic shaft. The first model applies better to the Purkinje cell (PC), because numerous free spines have been described in several conditions, particularly when granule cells degenerate before parallel fiber (PF) synapses are formed. A large number of new spines, many of them being free, appear in the proximal dendritic domain after blockage of electrical activity by tetrodotoxin (TTX). A complete blockage of the AMPA receptors by NBQX (2,3-dioxo-6-nitro-1,2,3,4-tetrahydrobenzoquinoxaline-7-sulfonamide), leading to a complete absence of PF- and climbing fiber (CF)-evoked EPSCs and of spontaneous glutamatergic quantal events, mimics the TTX effect. In contrast, metabotropic glutamate receptor blockage by MCPG [(S)-α-methyl-4-carboxyphenylglycine] is ineffective. In normal conditions, in the proximal dendritic domain of the PC, clusters of a few spines are present only under each CF varicosity. It has been proposed that the active CF is responsible for spine pruning in the territory surrounding the CF synapses. Here, we show that such a pruning is mediated by AMPA but not by metabotropic receptors. Finally, after AMPA receptor blockage, there is a reduced number of spines in each spine cluster underlying CF varicosity. In conclusion, PCs tend to express spines over the entire dendritic territory. CF activity reinforces the CF synaptic contacts and actively suppresses spines in the surrounding territory, which is an effect mediated by AMPA receptors.
Extended self: implications for country-of-origin

Purpose – This paper aims to examine country-of-origin (COO) effects from the theoretical angle of extended self and “otherness”. Traditional COO perspectives view COO as an important quality-related, informational cue used to form product evaluations, develop preferences and make purchase decisions. Design/methodology/approach – An experiment was conducted with the COO of a fresh milk product manipulated to examine these predictions. Data were collected from four samples, Americans living in the USA, Americans living in China, Chinese living in China and Chinese living in the USA. Findings – Results found that COO effects were stronger when consumers felt greater animosity toward the foreign country, were more ethnocentric and were less acculturated (i.e. conceptualized as a less expanded self). Additionally, negative product events were interpreted in light of self, in that reactions to an adverse act were stronger when “others” committed the act. American consumers living abroad were more heavily influ.
Talk, technologies and teenagers: understanding the school journey using a mixed-methods approach

This paper focuses on the methods used in a project which set out to capture the movements and to consider the wellbeing of 30 teenagers on their journeys to and from school. A mobile phone linked to a GPS receiver was used to automatically log travel patterns whilst the respondents added ‘blog’ images and text about how they felt on the journey. Follow up interviews further explored the data. The paper shows that by using a range of methods the young people became involved in the project in different ways providing a rich picture of contingent and complex school journeys.
Data Mining Applications: A comparative Study for Predicting Student's performance

Knowledge Discovery and Data Mining (KDD) is a multidisciplinary area focusing upon methodologies for extracting useful knowledge from data and there are several useful KDD tools to extracting the knowledge. This knowledge can be used to increase the quality of education. But educational institution does not use any knowledge discovery process approach on these data. Data mining can be used for decision making in educational system. A decision tree classifier is one of the most widely used supervised learning methods used for data exploration based on divide&conquer technique. This paper discusses use of decision trees in educational data mining. Decision tree algorithms are applied on students' past performance data to generate the model and this model can be used to predict the students' performance. It helps earlier in identifying the dropouts and students who need special attention and allow the teacher to provide appropriate advising/counseling.
The Effect of Vaginal Lubrication on Unsatisfactory Results of Cervical Smears

Objective Speculum lubrication with water-based gels before cervical smear sampling has been investigated and commented on thoroughly during the last decade. The present meta-analysis was based on randomized and quasi-randomized control trials and evaluated its impact on unsatisfactory cytologic results. We also assessed its efficacy in producing lower pain scores during speculum insertion. Materials and Methods We searched MEDLINE (1966– 2013), Scopus (2004–2013), Clinicaltrials.org (1997–2013), Popline (1973–2013), Cochrane Central Register of Controlled Trials (CENTRAL) (1999–2013), and Google Scholar (2004–2013) engines for published randomized control trials, as well as the reference lists from all the included studies. Results Five randomized trials and 2 quasi-randomized trials were included in the present review involving 8,717 women. Unsatisfactory results based on conventional cytology did not statistically differ among procedures performed with lubricated speculums and those without (odds ratio = 0.94, 95% CI = 0.64–1.37). Consequently, pain scores also did not differ significantly among the 2 groups (odds ratio = −0.37, 95% CI = −1.10 to 0.36). Only 2 studies evaluated unsatisfactory results on liquid-based cytology, precluding firm results. Conclusions It seems that speculum lubrication does not interfere with the rates of unsatisfactory results when examination is based on conventional cytology. Conversely, however, the limited number of studies evaluating speculum lubrication on liquid-based cytology precludes firm conclusions.
Use of prescription and nonprescription hypnotics in a Canadian elderly population.

BACKGROUND Hypnotics are commonly used by older adults, yet little is known about the patterns of their use and effectiveness in this population. METHODS Three thousand eight hundred sixty anonymous, self-report surveys were distributed to community pharmacies (n=356) across Canada to obtain information on the patterns of use of hypnotics from elderly volunteers. RESULTS The mean age of respondents was 72+/-7 years (range 60 to 95 years) and 66% were women. In the past year, 53% of respondents used hypnotics. Prescription products accounted for 83% of the past year's use (66% benzodiazepines, 11% zopiclone, 4% antidepressants, 2% opioids), and 17% of the products used were over-the-counter (5% herbal, 5% antihistamines, 3% analgesics). Use was regular (50% daily) and chronic (mean duration six years: range two weeks to 30 years). Hypnotics significantly (P<0.001) improved subjective sleep latency (mean 32 min compared with 93 min), number of nocturnal awakenings (mean two compared with four) and total hours of sleep (mean 7 h compared with 4 h). Effectiveness was highly rated: at the most recent use of the product, mean 7.6 (SD+/-2.2) of 10; initially, 7.9 (SD+/-2.3) with a significance of P=0.02. Most respondents (59%) reported side effects, mainly dry mouth (30%), memory problems (22%) and daytime sleepiness (22%), although 60% rated the side effects as mild. The mean number of other medications used was five (range zero to 17). Of the 54 subjects who used nonprescription sleep products, only half (52%) indicated that their physician was aware of this use. CONCLUSIONS Prescription drugs were primarily used for sleep and were perceived to be effective even with long term use, despite mild side effects.
JC Virus Induces Nonapoptotic Cell Death of Human Central Nervous System Progenitor Cell-Derived Astrocytes

ABSTRACT JC virus (JCV), a human neurotropic polyomavirus, demonstrates a selective glial cell tropism that causes cell death through lytic infection. Whether these cells die via apoptosis or necrosis following infection with JCV remains unclear. To investigate the mechanism of virus-induced cell death, we used a human central nervous system progenitor-derived astrocyte cell culture model developed in our laboratory. Using in situ DNA hybridization, immunocytochemistry, electron microscopy, and an RNase protection assay, we observed that astrocytes support a progressive JCV infection, which eventually leads to nonapoptotic cell death. Infected astrocyte cell cultures showed no difference from noninfected cells in mRNA expression of the caspase family genes or in any ultrastructural features associated with apoptosis. Infected cells demonstrated striking necrotic features such as cytoplasmic vacuolization, watery cytoplasm, and dissolution of organelles. Furthermore, staining for caspase-3 and terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling were not detected in infected astrocyte cultures. Our findings suggest that JCV-induced cell death of these progenitor cell-derived astrocytes does not utilize an apoptosis pathway but exhibits a pattern of cell destruction consistent with necrotic cell death.
Distributed Detection via Gaussian Running Consensus: Large Deviations Asymptotic Analysis

We study, by large deviations analysis, the asymptotic performance of Gaussian running consensus distributed detection over random networks; in other words, we determine the exponential decay rate of the detection error probability. With running consensus, at each time step, each sensor averages its decision variable with the neighbors' decision variables and accounts on-the-fly for its new observation. We show that: 1) when the rate of network information flow (the speed of averaging) is above a threshold, then Gaussian running consensus is asymptotically equivalent to the optimal centralized detector, i.e., the exponential decay rate of the error probability for running consensus equals the Chernoff information; and 2) when the rate of information flow is below a threshold, running consensus achieves only a fraction of the Chernoff information rate. We quantify this achievable rate as a function of the network rate of information flow. Simulation examples demonstrate our theoretical findings on the behavior of running consensus detection over random networks.
Practical reasoning in political discourse: The UK government’s response to the economic crisis in the 2008 Pre-Budget Report

This article focuses on practical reasoning in political discourse and argues for a better integration of argumentation theory with critical discourse analysis (CDA). Political discourse and its specific genres (for example, deliberation) primarily involve forms of practical reasoning, typically oriented towards finding solutions to problems and deciding on future courses of action. Practical reasoning is a form of inference from cognitive and motivational premises: from what we believe (about the situation or about means—end relations) and what we want or desire (our goals and values), leading to a normative judgement (and often a decision) concerning action. We offer an analysis of the main argument in the UK government’s 2008 Pre-Budget Report (HM Treasury, 2008) and suggest how a critical evaluation of the argument from the perspective of a normative theory of argumentation (particularly the informal logic developed by Douglas Walton) can provide the basis for an evaluation in terms of characteristic CDA concerns. We are advancing this analysis as a contribution to CDA, aimed at increasing the rigour and systematicity of its analyses of political discourse, and as a contribution to the normative concerns of critical social science.
Analysis of Centrality in Sublinear Preferential Attachment Trees via the Crump-Mode-Jagers Branching Process

We investigate centrality and root-inference properties in a class of growing random graphs known as sublinear preferential attachment trees. We show that a continuous time branching processes called the Crump-Mode-Jagers (CMJ) branching process is well-suited to analyze such random trees, and prove that almost surely, a unique terminal tree centroid emerges, having the property that it becomes more central than any other fixed vertex in the limit of the random growth process. Our result generalizes and extends previous work establishing persistent centrality in uniform and linear preferential attachment trees. We also show that centrality may be utilized to generate a finite-sized <inline-formula><tex-math notation="LaTeX">$1-\epsilon$</tex-math><alternatives> <inline-graphic xlink:href="jog-ieq1-2622923.gif"/></alternatives></inline-formula> confidence set for the root node, for any <inline-formula><tex-math notation="LaTeX">$\epsilon > 0$</tex-math><alternatives> <inline-graphic xlink:href="jog-ieq2-2622923.gif"/></alternatives></inline-formula>, in a certain subclass of sublinear preferential attachment trees.
The Effects of Direct and Indirect Hypnotic Suggestions for Analgesia in High and Low Susceptible Subjects

Abstract The efficacy of two hypnotic induction techniques on twenty subjects whose degree of hypnotic susceptibility had been previously determined as either high or low was compared. The two induction techniques, direct and indirect, reflected a difference in permissiveness of language, use of imagery and symbolic language, the use of the subject's experience and the perceived control by the subject. Pain threshold measures, induced by electrical tooth pulp stimulation, were assessed before, during, and after induction of hypnotic analgesia. Analysis of the data showed that the indirect technique was significantly more effective than the direct technique in changing pain thresholds regardless of susceptibility. The direct technique was significantly effective with only those subjects who received high susceptibility scores. Although interpretation of results is limited due to small sample size, the findings suggest that patients with low hypnotic susceptibility, as measured by conventional tests, may st.
Neurosymbolic Integration: Cognitive Grounds and Computational Strategies

The ultimate|if implicit|goal of artiicial intelligence (AI) research is to model the full range of human cognitive capabilities. Symbolic AI and connectionism, the major AI paradigms, have each tried|and failed|to attain this goal. In the meantime, the idea has gained ground that this goal might still be within reach if we could harness the respective strengths of these two paradigms in integrated neurosymbolic models. This paper attempts to lay a cognitive basis for neurosymbolic integration and describes the diierent strategies that have been adopted to date. Uniied approaches strive to attain symbol-processing capabilities using neural network techniques alone, while hybrid approaches blend symbolic and neural models in novel architectures with the hope of gleaning the best of both paradigms.