Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring speech-language pathologists’ perspectives of aphasia self-management: a qualitative study

Access to aphasia rehabilitation diminishes over time due to limited resources within the health care system. This results in many people with chronic aphasia being unable to access ongoing rehabilitation services (Rose, Ferguson, Power, Togher, & Worrall, 2014). A self-management model for aphasia rehabilitation may offer an innovative and sustainable solution to this issue of limited access. Self-management models of care have been shown to increase self-efficacy and improve quality of life for individuals poststroke (Lennon, McKenna, & Jones, 2013). However, there is a paucity of information about what self-management in aphasia consists of and how this model of care is implemented (Wray, Clarke, & Forster, 2017). In order to determine how a selfmanagement model could be implemented with a communication disorder such as aphasia, key stakeholders such as individuals with aphasia, communication partners, and speech-language pathologists (SLPs) should be consulted. These results are part of a larger study within a broader body of research which seeks to explore the views of SLPs regarding self-management of aphasia.
Path sampling, a robust alternative to gossiping for opportunistic network routing

Opportunistic Networks have been designed for transmitting data in difficult environments, characterized by high mobility, sporadic connectivity, and constrained resources. To sustain these networks, the literature describes methods such as Epidemic and Spray&Wait, which do not learn from the network behaviour, and Gossiping-based algorithms that collect historical network data to improve efficiency. In this paper, we show that Gossiping-based solutions suffer from pathological behaviour in some simple network scenarios. Under certain conditions almost all the data transmitted by some nodes may get lost in the network, not reaching its destination. To address this problem we have proposed an algorithm that responds in a more robust manner while staying relatively simple. In this work, we show that our algorithm achieves delivery rates comparable to gossiping-based algorithms, while being more robust and providing better fairness. To illustrate this result, we test native implementations of our solution, Path Sampling, and related algorithms on a network simulator.
Finding Influential Bloggers

Blogging is a popular way of expressing opinions and discussing topics. Bloggers demonstrate different levels of commitment and most interesting are influential bloggers. Around such bloggers, the groups are forming, which concentrate users sharing similar interests. Finding such bloggers is an important task and has many applications e.g. marketing, business, politics. Influential ones affect others which is related to the process of diffusion. However, there is no objective way to telling which blogger is more influential. Therefore, researchers take into consideration different criteria to assess bloggers (e.g. SNA centrality measures). In this paper we propose new, efficient method for influential bloggers discovery which is based on relation of commenting in blogger's thread and is defined on bloggers level. Next, we compare results with other, comparative method proposed by Agarwal et al. called iFinder which is based on links between posts.
An Approach to Planning with Incomplete Information (extended Abstract)

Classical planners presuppose complete and correct information about the world. This paper provides the syntax and semantics for uwl, a representation for goals and actions that facilitates planning with incomplete information about the world's state. While the expressive power of uwl is limited compared to previous work on logics of knowledge and belief, uwl has the advantage of being easily incorporated into planning algorithms. We describe a provably correct planning algorithm based on uwl. To demonstrate uwl's expressive power we encode a subset of the UNIX 1 domain (planning to achieve UNIX goals, using UNIX shell commands as primitive actions), which is di cult to capture using existing planning languages. Topic area: reasoning methods, planning. Authors' names are listed alphabetically within two status-oriented equivalence classes. Our research was funded in part by National Science Foundation Grants IRI-8957302 and IRI{ 9008670, O ce of Naval Research Grant 90-J-1904, a NASA Graduate Student Researcher's Fellowship, an O ce of Naval Research Graduate Fellowship, and a grant from the Xerox corporation. Helpful comments were provided by Keiji Kanazawa, Craig Knoblock, and Leora Morgenstern. 1 UNIX is a trademark of AT&T Bell Labs.
Revisando los modelos pedagógicos en educación física. Ideas clave para incorporarlos al aula

Tomando como referencia un trabajo anterior sobre modelos pedagógicos enEducación Física, el objetivo fundamental del presente artículo es incidir sobrelos aspectos clave que los docentes necesitan tener en cuenta para incorporar estosplanteamientos metodológicos de manera satisfactoria a sus clases. Para ello sedetallan aquellos elementos que ayudan en la transición de la teoría a la práctica decada uno de los principales modelos pedagógicos.
Notecards in a nutshell

NoteCards is an extensible environment designed to help people formulate, structure, compare, and manage ideas. NoteCards provides the user with a “semantic network” of electronic notecards interconnected by typed links. The system provides tools to organize, manage, and display the structure of the network, as well as a set of methods and protocols for creating programs to manipulate the information in the network. NoteCards is currently being used by more than 50 people engaged in idea processing tasks ranging from writing research papers through designing parts for photocopiers. In this paper we briefly describe NoteCards and the conceptualization of idea processing tasks that underlies its design. We then describe the NoteCards user community and several prototypical NoteCards applications. Finally, we discuss what we have learned about the system's strengths and weaknesses from our observations of the NoteCards user community.
The Incentives to Work : Working Children and Household Decision-Making

In the United States a century ago, working children turned over almost all of their earnings to their parents. What incentives, then, did they have to work? Standard answers to this question allude to altruism or the “sticks” wielded by parents and employers. This paper argues that there were also “carrots”: working gave children greater influence in household decision-making. Using data from the Bureau of Labor Statistics Cost of Living Survey 1917-1919, this paper shows that earnings from children altered intrahousehold resources allocations. Holding total expenditures per capita constant, increases in the share of household income brought in by children ages 12 to 16 increased expenditures on those children’s clothing and decreased expenditures on the father’s clothing. For working children ages 17 to 21, personal clothing expenditures were increasing in the ratio of their wages to their fathers’ wages. This paper was previously titled, “The Impact of Children’s Income on Intrahousehold Resource Allocations. ” Claudia Goldin and Martha Olney generously provided supplementary data on the occupations reported in the BLS Cost of Living Survey. Joseph Altonji, Joseph Ferrie, Timothy Guinnane, Bruce Meyer, Joel Mokyr, and Christopher Udry provided helpful comments and suggestions. The author also benefited from the comments on earlier versions of the paper provided by seminar participants at Northwestern, Washington University, and NBER/DAE Summer Institute. All errors and omissions are the responsibility of the author.
User Similarity Measure Method Based on the Comparison Model of Psychology

According to exploiting the users' preference for each attribute, we can get the similarity of users' interest. In this way, the similarity can be combined with the collaborative filtering algorithm which can get the users' interests from users' assessment. A new user similarity measure based on comparison model of psychology is proposed, which applies psychology theory to improve collaborative filtering, and the experimental results prove that the proposed model improves performance of collaborative filtering algorithm.
An Empirical Investigation into the Moderating Relationship of Computer Self-Efficacy on Performance in a Computer-Supported Task

Computers and related technologies have become pervasive in the current organizational environment. Most, if not all, organizational activities are dependent on computer-based information systems, and thus effective use of these technologies is a critical factor in reaping productivity gains, improving return on IT investments, and overall organizational performance. While the impacts of computer self-efficacy on computer task-performance are well established (e.g. Johnson and Marakas, 2000; Yi and Davis, 2003) it has not yet been incorporated into the nomological net attempting to explain performance in tasks requiring the use of computer technologies. Given that successful completion of a particular organizational task depends on both technical (e.g. computer-related) and functional (e.g. task-related) abilities (Looney, Valacich, Todd and Morris, 2006), it is important to look beyond performance in computer-only tasks and accordingly position computer self-efficacy as a determinant of performance in a richer task environment. In addition, given that organizational tasks can largely vary on the level of required computer support, it becomes relevant to understand how the effects of computer self-efficacy on task performance fluctuate as the role of the computer becomes more or less prominent.
A Consideration of Emotional Topology: Representing Psychological Transitions on a Two-Dimensional Map

Qualitative verbal and text data such as narrations and descriptions can include additional information about a subject’s spiritual response or deep psyche than questionnaires as quantitative data. Therefore, in the previous studies, various analysis methods have been developed to clarify and visualize the subject’s mental state based on these data. The present study focuses on the sequential transitions of the visualization results from our previous study. The purpose of this study was to reveal and visualize the transition patterns of the subjects’ mental states by analyzing their utterances. The mental changes were expressed with trajectories in two-dimensional space in which the relationship between various emotions was represented with self-organizing maps (SOM) as analyzed in the previous study. The present study demonstrated the modal patterns of mental changes among the subject groups by clustering the subjects. These patterns were visualized on the two-dimensional space composed of psychological evaluation axes, thus the visualization results were interpreted in terms of psychology. It was concluded that the group’s tendencies in terms of mental changes can be comprehended by noting on the transition of the mental states.
Improving Access to Malaria Rapid Diagnostic Test in Niger State, Nigeria: An Assessment of Implementation up to 2013

Nigeria's 2009–2013 malaria strategic plan adopted WHO diagnosis and treatment guidelines, which include the use of rapid diagnostic tests (RDTs) prior to prescribing treatment with artemisinin combination therapies (ACTs). The current study explores accessibility barriers to the use of RDTs in Niger State and makes recommendations for improving the uptake of RDTs. The study employs literature review, review of data from the Niger State Health Management Information System for January–October 2013, and application of Peters' conceptual framework for assessing access to health services. Data showed that 27 percent of public health facilities (HFs) implemented RDTs, with the aid of donor funds. In these facilities, 77 percent of fever cases presented during the study period were tested with RDTs; 53 percent of fever cases were confirmed cases of malaria, while 60 percent of fever cases were treated. Stockouts of RDTs were a major constraint, and severe fever tended to trigger presumptive treatment. We conclude that although implementation of RDTs led to a reduction in the use of ACTs at HFs, more substantial reduction could be achieved if the state government directed more resources towards the acquisition of RDTs as well as raising the level of awareness of potential users.
Off to a Good Start: The Early Development of the Neural Substrates Underlying Visual Working Memory

Current neuroscientific models describe the functional neural architecture of visual working memory (VWM) as an interaction of the frontal-parietal control network and more posterior areas in the ventral visual stream (Jonides et al., 2008; D'Esposito and Postle, 2015; Eriksson et al., 2015). These models are primarily based on adult neuroimaging studies. However, VWM undergoes significant development in infancy and early childhood, and the goal of this mini-review is to examine how recent findings from neuroscientific studies of early VWM development can be reconciled with this model. We surveyed 29 recent empirical reports that present neuroimaging findings in infants, toddlers, and preschoolers (using EEG, fNIRS, rs-fMRI) and neonatal lesion studies in non-human primates. We conclude that (1) both the frontal-parietal control network and the posterior cortical storage areas are active from early infancy; (2) this system undergoes focalization and some reorganization during early development; (3) and the MTL plays a significant role in this process as well. Motivated by both theoretical and methodological considerations, we offer some recommendations for future directions for the field.
Distorted Time Perception during Flow as Revealed by an Attention-Demanding Cognitive Task

Flow is the state of full attention to the task at hand. It is typically studied in daily life, as people engage deeply in activities such as art, sports, and leisure, and typically its affective characteristics are emphasized. This research investigates flow in the laboratory, focusing on its cognitive characteristics. Participants completed different versions of the Trail Making test, a measure of executive function, that made parametrically increasing demands on attention. As predicted, more participants were in the flow state when attentional demands were moderate than when they were low or high. This was revealed by conventional survey measures indicating a balance between the perceived challenge of the task and the perceived skill of participants. Critically, this was also evidenced by a new operational measure of time distortion, defined as the difference between people’s subjective estimates of their task completion times and the objective, experimenter-recorded times. Participants experienced downward time distortion—the feeling of time flying—when attentional demands were moderate. These findings demonstrate for the first time the causal role of attentional demands in inducing the flow state. They set the stage for future studies of flow and time distortion using attention-demanding cognitive tasks, and of the association between time perception and creative thinking.
Hyhope : A Fast Fault Simulator With Efficient Simulation Of Hypertrophic Faults

In sequential circuit fault simulation, the hypertrophic faults, which result from lengthened initialization sequence in the faulty circuits, usually produce a large number of fault events during simulation and require excessive gate evaluations. These faults degrade the performance of fault simulators attempting to simulate them exactly. In this paper, an exact simulation algorithm is developed to identify the hypertropic faults and to minimize their effects during the fault simulation. The simulator HyHOPE based on this algorithm shows that the average speedup ratio over HOPE 1.1 is 1.57 for ISCAS89 benchmark circuits. Furthermore, the result indicates the performance of HyHOPE is close to the approximate simulator in which faults are simply dropped when they become potentially detected.
Distributed Hessian-Free Optimization for Deep Neural Network

Training deep neural network is a high dimensional and a highly non-convex optimization problem. Stochastic gradient descent (SGD) algorithm and it's variations are the current state-of-the-art solvers for this task. However, due to non-covexity nature of the problem, it was observed that SGD slows down near saddle point. Recent empirical work claim that by detecting and escaping saddle point efficiently, it's more likely to improve training performance. With this objective, we revisit Hessian-free optimization method for deep networks. We also develop its distributed variant and demonstrate superior scaling potential to SGD, which allows more efficiently utilizing larger computing resources thus enabling large models and faster time to obtain desired solution. Furthermore, unlike truncated Newton method (Marten's HF) that ignores negative curvature information by using naive conjugate gradient method and Gauss-Newton Hessian approximation information - we propose a novel algorithm to explore negative curvature direction by solving the sub-problem with stabilized bi-conjugate method involving possible indefinite stochastic Hessian information. We show that these techniques accelerate the training process for both the standard MNIST dataset and also the TIMIT speech recognition problem, demonstrating robust performance with upto an order of magnitude larger batch sizes. This increased scaling potential is illustrated with near linear speed-up on upto 16 CPU nodes for a simple 4-layer network.
Design of Highly Efficient Load Modulation Transmitter for Wideband Cellular Applications

In this paper, the high potential of varactor-based dynamic load modulation (DLM) techniques for wideband cellular applications is demonstrated. A systematic design procedure is proposed to ensure high-efficiency wideband performance. It incorporates harmonically tuned power amplifier (PA) concepts and tunable matching techniques in an integrated design. A DLM transmitter at 2.65 GHz with a peak output power of 6 W is designed using the proposed procedure. In order to investigate the wideband performance of the implemented demonstrator, WCDMA signals with scaled bandwidths are employed. The signal peak-to-average ratio is 7 dB and the same for all the experiments. For the 38.4-MHz signal, which has a corresponding channel bandwidth of > 40 MHz, an average power added-efficiency (PAE) of 44%, normalized mean square error (NMSE) of -35 dB, and adjacent channel leakage ratio (ACLR) of -43 dBc are measured.
New Results on Optimal Area Triangulations of Convex Polygons

We consider the problems of finding two optimal triangulations of convex polygon: MaxMin area and MinMax area. These are the triangulations that maximize the area of the smallest area triangle in a triangulation, and respectively minimize the area of the largest area triangle in a triangulation, over all possible triangulations. The problem was originally solved by Klincsek by dynamic programming in cubic time [2]. Later, Keil and Vassilev devised an algorithm that runs in O(n log n) time [1]. In this paper we describe new geometric findings on the structure of MaxMin and MinMax Area triangulations of convex polygons in two dimensions and their algorithmic implications. We improve the algorithm’s running time to quadratic for large classes of convex polygons. We also present experimental results on MaxMin area triangulation.
A content based approach for recommending personnel for job positions

In this paper, we propose a content-based approach that takes into consideration an organization's needs and the skills of candidate employees in order to quantify the suitability of a candidate employee for a specific job position. The proposed algorithm utilizes Minkowski distance to perform a primary study in order to investigate how the personnel seeking and recruiting field could benefit further. Also, we conduct a three step experimental evaluation, namely, content analysis, refinement of the algorithm, and execution. The results of this experiment show that recommender systems can play an important role in the area of job seeking and recruiting.
Fully-dynamic minimum spanning forest with improved worst-case update time

We give a Las Vegas data structure which maintains a minimum spanning forest in an n-vertex edge-weighted undirected dynamic graph undergoing updates consisting of any mixture of edge insertions and deletions. Each update is supported in O(n1/2 - c) worst-case time w.h. p. where c > 0 is some constant, and this bound also holds in expectation. This is the first data structure achieving an improvement over the O(√n) deterministic worst-case update time of Eppstein et al., a bound that has been standing for 25 years. In fact, it was previously not even known how to maintain a spanning forest of an unweighted graph in worst-case time polynomially faster than Θ(√n). Our result is achieved by first giving a reduction from fully-dynamic to decremental minimum spanning forest preserving worst-case update time up to logarithmic factors. Then decremental minimum spanning forest is solved using several novel techniques, one of which involves keeping track of low-conductance cuts in a dynamic graph. An immediate corollary of our result is the first Las Vegas data structure for fully-dynamic connectivity where each update is handled in worst-case time polynomially faster than Θ(√n) w.h. p.; this data structure has O(1) worst-case query time.
Gender and Age Interact to Affect Early Outcome after Intracerebral Hemorrhage

Background Intracerebral hemorrhage (ICH) is a common and devastating form of cerebrovascular disease. In ICH, gender differences in outcomes remain relatively understudied but have been examined in other neurological emergencies. Further, a potential effect of age and gender on outcomes after ICH has not been explored. This study was designed to test the hypothesis that age and gender interact to modify neurological outcomes after ICH. Methods Adult patients admitted with spontaneous primary supratentorial ICH from July 2007 through April 2010 were assessed via retrospective analysis of an existing stroke database at Duke University. Univariate analysis of collected variables was used to compare gender and outcome. Unfavorable outcome was defined as discharge to hospice or death. Using multivariate regression, the combined effect of age and gender on outcome after ICH was analyzed. Results In this study population, women were younger (61.1+14.5 versus 65.8+17.3 years, p=0.03) and more likely to have a history of substance abuse (35% versus 8.9%, p<0.0001) compared to men. Multivariable models demonstrated that advancing age had a greater effect on predicting discharge outcome in women compared to men (p=0.02). For younger patients, female sex was protective; however, at ages greater than 60 years, female sex was a risk factor for discharge to hospice or death. Conclusion While independently associated with discharge to hospice or death after ICH, the interaction effect between gender and age demonstrated significantly stronger correlation with early outcome after ICH in a single center cohort. Prospective study is required to verify these findings.
Codebook approach for sensor-based human activity recognition

One crucial problem in sensor-based human activity recognition is how to model features that can precisely represent characteristics of a sequence of sensor values. For this, we study a codebook approach that represents the sequence as a distribution of characteristic subsequences. The extensive experiments on different recognition tasks for physical, mental and eye-based activities validate the effectiveness, generality and usability of the codebook approach, where only a few intuitive parameters need to be tuned.