Miracle-dz/UniFAR-FTUs huggingface dataset:
Online teen dating violence, family and school climate from a gender perspective / Violencia de pareja online en la adolescencia, clima familiar y escolar desde la perspectiva de género

Abstract The aim of this study is to analyse relationships from the family and school context and online teen dating violence from a gender perspective. The participants in this study included 919 adolescents (52.4% girls), aged 15–18 years (M = 16.12; SD = 0.99), who reported having or having had a partner in the last year. Multivariate analyses (MANOVAs) were performed to analyse the relationships between the variables of interest. The results show that teens who are violent with their partners in an online environment indicate higher levels of family conflict and less school affiliation than non-violent teens. In the boys, there is a lower perception of support from the teacher, and in girls, less family cohesion. The scope of these results and their implication in the prevention of this type of violence is presented in the discussion.
Stability analysis of networked control systems

We introduce a control network protocol, try-once-discard (TOD), for networked control systems (NCS), and provide, for the first time, an analytic proof of global exponential stability for both the new protocol and the commonly used statically scheduled access methods. Controllers are designed without regarding the presence of the network in the feedback loop, so consequently many controller design techniques may be employed. The performance of the new network protocol and the statically scheduled protocols are compared in simulations.
Transmission mode selection and communication establishment in the hybrid device-to-device and cellular networks

The decision-making of the transmission mode and communication establishment are two key issues in the initial procedure for the hybrid system of the cellular and device-to-device (D2D) network. In this paper, according to cellular users and D2D terminals use the same resources or not, we firstly propose two criteria to select the transmission mode. When these two kinds of users reuse resources, the minimum interference to the cellular system is considered to suggest the criterion. However, the system throughput based criterion is derived when they use different resources. To this end, an effective mechanism to establish D2D communication and avoid interference is presented. Simulations show that our criteria are effective and can obtain a better system performance compared with the pure cellular mode and D2D mode.
User identification using raw sensor data from typing on interactive displays

Personalized soft-keyboards which adapt to a user's individual typing behavior can reduce typing errors on interactive displays. In multi-user scenarios a personalized model has to be loaded for each participant. In this paper we describe a user identification technique that is based on raw sensor data from an optical touch screen. For classification of users we use a multi-class support vector machine that is trained with grayscale images from the optical sensor. Our implementation can identify a specific user from a set of 12 users with an average accuracy of 97.51% after one keystroke. It can be used to automatically select individual typing models during free-text entry. The resulting authentication process is completely implicit. We furthermore describe how the approach can be extended to automatic loading of personal information and settings.
Developing Empathy Through Confluent Education

Background and Purpose. Although empathy is a highly valued component of health care, there is little agreement as to exactly what it is and how it might be developed in physical therapist students. Position and Rationale. This article explores the nature and process of empathy as well as the constituent personal capacities that enable empathic function. It then proposes that confluent education, an approach that deliberately integrates affective and cognitive learning, may be a valuable educational vehicle for the development of empathy in physical therapist students. Specific features of confluent education are described, as are various strategies for creating confluence in professional education. These features and techniques of confluent education are then correlated with the enabling personal capacities of the empathic process so as to clarify the proposed linkage between this specific educational modality and the development of empathy in physical therapist students. Discussion and Conclusions. Insofar as empathy is a key constituent of effective interactions between physical therapists and patients, it is important that the training of physical therapist students facilitate this capacity. Confluent education, with its emphasis on the integration of affective and cognitive learning, may provide one such approach to fulfilling this objective.
Spoken document summarization and retrieval for wireless application

For the purpose of wireless data transformation, spoken document summarization can efficiently reduce the redundant contents. This study presents a voice-activated spoken document summarization and retrieval scheme using text and speech analysis. In this method, prosody, speech recognition confidence, word significance, word trigram and semantic dependency are considered in the summarization score. A dynamic programming algorithm is used to seek the best summarization result. Experimental results indicate that the proposed approach effectively summarizes concise spoken sentences containing important words with semantic dependency.
AUTOMATIC EVOLUTION OF IDEAS THROUGH MULTILAYER EVOLUTIONARY SYSTEM TO SUPPORT CREATIVE THINKING

Creativity is a tool that helps in effective problem solving utilizing optimum scarce resources in any business. This paper presents a conceptual framework of a multilayer evolutionary system that supports creative thinking. The system evolves, using a genetic algorithm, new ideas from a set of basic ideas that are casually provided through an interactive editor or selected from past transaction records. The architecture proposed here encompasses three layers called system layer, database layer, and query producer and user interface layer. Besides the general architecture, the paper also describes the detailed methodology, genetic procedure to evolve ideas, reproduction operators like modified mutation, cross over and selection; and fitness functions to evolve suitable and strong ideas. The system layer further describes algorithm of stimulus-generation process. The proposed architecture is easy to develop, generic, domain independent and works with databases, which increases scope and usability of the system. Above all, the interactive user interface makes the system friendly and easy to operate.
Fearless dominance and performance in field sales: A predictive study

In a prospective study of 150 junior salespeople in the same company, we examined the relation between fearless dominance, which is a dimension of trait psychopathy, and objective performance in field sales. After controlling for demographic variables, length of job tenure, initial sales training quality, and disciplined achievement motivation, the results supported an inverted U-shaped relation, which showed that, after a certain turning point, increases in fearless dominance resulted in decreases in performance. Thus, the most successful salespeople in our sample possessed moderate levels of fearless dominance. Implications for theory, practice, and future research are provided in light of a number of notable strengths and limitations.
Regulation of N-Methyl-D-aspartate Receptors by Calpain in Cortical Neurons*

The N-methyl-d-aspartate (NMDA) receptor is a cation channel highly permeable to calcium and plays critical roles in governing normal and pathologic functions in neurons. Calcium entry through NMDA receptors (NMDARs) can lead to the activation of the Ca2+-dependent protease, calpain. Here we investigated the involvement of calpain in regulation of NMDAR channel function. After prolonged (5-min) treatment with NMDA or glutamate, the whole-cell NMDAR-mediated current was significantly reduced in both acutely dissociated and cultured cortical pyramidal neurons. The down-regulation of NMDAR current was blocked by bath application of selective calpain inhibitors. Intracellular injection of a specific calpain inhibitory peptide also eliminated the down-regulation of NMDAR current induced by prolonged NMDA treatment. In contrast, dynamin inhibitory peptide had no effect on the depression of NMDAR current, suggesting the lack of involvement of dynamin/clathrin-mediated NMDAR internalization in this process. Immunoblotting analysis showed that the NR2A and NR2B subunits of NMDARs were markedly degraded in cultured cortical neurons treated with glutamate, and the degradation of NR2 subunits was prevented by calpain inhibitors. Taken together, our results suggest that prolonged activation of NMDARs in neurons activates calpain, and activated calpain in turn down-regulates the function of NMDARs, which provides a neuroprotective mechanism against NMDAR overstimulation accompanying ischemia and stroke.
Increasing the Time Interval between PCV Chemotherapy Cycles as a Strategy to Improve Duration of Response in Low-Grade Gliomas: Results from a Model-Based Clinical Trial Simulation

Background. We previously developed a mathematical model capturing tumor size dynamics of adult low-grade gliomas (LGGs) before and after treatment either with PCV (Procarbazine, CCNU, and Vincristine) chemotherapy alone or with radiotherapy (RT) alone. Objective. The aim of the present study was to present how the model could be used as a simulation tool to suggest more effective therapeutic strategies in LGGs. Simulations were performed to identify schedule modifications that might improve PCV chemotherapy efficacy. Methods. Virtual populations of LGG patients were generated on the basis of previously evaluated parameter distributions. Monte Carlo simulations were performed to compare treatment efficacy across in silico clinical trials. Results. Simulations predicted that RT plus PCV would be more effective in terms of duration of response than RT alone. Additional simulations suggested that, in patients treated with PCV chemotherapy, increasing the interval between treatment cycles up to 6 months from the standard 6 weeks can increase treatment efficacy. The predicted median duration of response was 4.3 years in LGGs treated with PCV cycles given every 6 months versus 3.1 years in patients treated with the classical regimen. Conclusion. The present study suggests that, in LGGs, mathematical modeling could facilitate clinical research by helping to identify, in silico, potentially more effective therapeutic strategies.
Assessing the validity of NART-estimated premorbid IQs in the individual case.

The National Adult Reading Test (NART: Nelson, 1982) has become the standard means of estimating premorbid intelligence. The danger in using the NART for this purpose is that it yields an invalid estimate if a client's performance on the test has suffered impairment. In the present study a sample of 659 healthy subjects was used to build a regression equation for the prediction of NART scores from demographic variables (i.e. years of education, social class, age and sex). The multiple correlation between these demographic variables and the NART was . 70 (p less than .0001). Comparing a client's obtained and predicted NART score will permit the clinician to assess objectively whether NART performance is impaired, and thus whether or not the NART will provide a valid estimate of premorbid intelligence.
Effects of Approximate Filtering on the Appearance of Bidirectional Texture Functions

The BTF data structure was a breakthrough for appearance modeling in computer graphics. More research is needed though to make BTFs practical in rendering applications. We present the first systematic study of the effects of Approximate filtering on the appearance of BTFs, by exploring the spatial, angular and temporal domains over a varied set of stimuli. We perform our initial experiments on simple geometry and lighting, and verify our observations on more complex settings. We consider multi-dimensional filtering versus conventional mipmapping, and find that multi-dimensional filtering produces superior results. We examine the tradeoff between under- and oversampling, and find that different filtering strategies can be applied in each domain, while maintaining visual equivalence with respect to a ground truth. For example, we find that preserving contrast is more important in static than dynamic images, indicating greater levels of spatial filtering are possible for animations. We find that filtering can be performed more aggressively in the angular domain than in the spatial. Additionally, we find that high-level visual descriptors of the BTF are linked to the perceptual performance of pre-filtered approximations. In turn, some of these high-level descriptors correlate with low level statistics of the BTF. We show six different practical applications of applying our findings to improving filtering, rendering and compression strategies.
COSMOLOGICAL SOLUTION FROM D-BRANE MOTION IN NS5-BRANES BACKGROUND

We study dynamics of a D3-brane propagating in the vicinity of k coincident NS5 branes. We show that when gs is small, there exists a regime in which dynamics of the D-brane is governed by Dirac–Born–Infeld action while higher order derivative in the expansion cannot be neglected. This leads to a restriction on how fast scalar field may roll. We analyze the motion of a rolling scalar field in this regime, and extend the analysis to cosmological systems obtained by coupling this type of field theory to four-dimensional gravity. It also leads to some FRW cosmologies, some of which are related to those obtained with tachyon matter.
Pilot Testing a Digital Career Literacy Training for Vocational Rehabilitation Professionals

Digital career literacy encompasses the skills needed to find and maintain employment in the modern job market. Unfortunately, many state vocational rehabilitation (VR) professionals report feeling unprepared to help their consumers with digital career literacy tasks. To address this gap, we developed and tested five training webinars with VR professionals in Montana, Alabama, and Washington. We randomly assigned VR offices to intervention or control group. VR professionals in the intervention group received access to the training webinars. We collected survey data at baseline and 4 months after the intervention’s conclusion (n = 136). A repeated measures ANOVA showed significant group by factor effects in counselor preparedness to use online tools during the VR process (intervention group: M1 = 24.41, SD1 = 7.62; M2 = 28.76, SD2 = 7.27; control group: M1 = 25.94, SD1 = 8.64; M2 = 27.21, SD2 = 9.14); F(1, 124) = 5.957, p = . 016. A McNemar nonparametric test indicated that more VR professionals in the intervention group reported using LinkedIn at the 4-month follow-up, as compared with the control group (p = .039). There were no significant changes in use of other online tools. This may relate to administrative policies that do not provide clear guidelines for using online tools in the counseling process.
Morphological Analysis Can Improve a CCG Parser for English

Because English is a low morphology language, current statistical parsers tend to ignore morphology and accept some level of redundancy. This paper investigates how costly such redundancy is for a lexicalised grammar such as CCG. We use morphological analysis to split verb inflectional suffixes into separate tokens, so that they can receive their own lexical categories. We find that this improves accuracy when the splits are based on correct POS tags, but that errors in gold standard or automatically assigned POS tags are costly for the system. This shows that the parser can benefit from morphological analysis, so long as the analysis is correct.
Mesenchymal stem cells: potential precursors for tumor stroma and targeted-delivery vehicles for anticancer agents.

BACKGROUND High concentrations of interferon beta (IFN-beta) inhibit malignant cell growth in vitro. However, the therapeutic utility of IFN-beta in vivo is limited by its excessive toxicity when administered systemically at high doses. Mesenchymal stem cells (MSC) can be used to target delivery of agents to tumor cells. We tested whether MSC can deliver IFN-beta to tumors, reducing toxicity. METHODS Human MSC were transduced with an adenoviral expression vector carrying the human IFN-beta gene (MSC-IFN-beta cells). Flow cytometry was used to measure tumor cell proliferation among in vitro co-cultures of MSC-IFN-beta cells and human MDA 231 breast carcinoma cells or A375SM melanoma cells. We used a severe combined immunodeficiency mouse xenograft model (4-10 mice per group) to examine the effects of injected MSC-IFN-beta cells and human recombinant IFN-beta on the growth of MDA 231- and A375SM-derived pulmonary metastases in vivo and on survival. All statistical tests were two-sided. RESULTS Co-culture of MSC-IFN-beta cells with A375SM cells or MDA 231 cells inhibited tumor cell growth as compared with growth of the tumor cells cultured alone (differences in mean percentage of control cell growth: -94.0% [95% confidence interval [CI] = -81.2% to -106.8%; P<.001] and -104.8% [95% CI = -82.1% to -127.5%; P<.001], respectively). Intravenous injection of MSC-IFN-beta cells into mice with established MDA 231 or A375SM pulmonary metastases led to incorporation of MSC in the tumor architecture and, compared with untreated control mice, to prolonged mouse survival (median survival for MDA 231-injected mice: 60 and 37 days for MSC-injected and control mice, respectively [difference = 23.0 days (95% CI = 14.5 to 34.0 days; P<.001]; median survival for A375SM-injected mice: 73.5 and 30.0 days for MSC-injected and control mice, respectively [difference = 43.5 days (95% CI = 37.0 to 57.5 days; P<.001]). By contrast, intravenous injection of recombinant IFN-beta did not prolong survival in the same models (median survival for MDA 231-injected mice: 41.0 and 37.0 days for IFN-beta-injected and control mice, respectively [difference = 4 days, 95% CI = -5 to 10 days; P = .308]; median survival for A375SM-injected mice: 32.0 and 30.0 days for IFN-beta-injected and control mice, respectively [difference = 2 days, 95% CI = 0 to 4.5 days; P = .059]). CONCLUSIONS Injected MSC-IFN-beta cells suppressed the growth of pulmonary metastases, presumably through the local production of IFN-beta in the tumor microenvironment. MSC may be an effective platform for the targeted delivery of therapeutic proteins to cancer sites.
Multitemporal interpretation of remote sensing data

The automated interpretation of aerial image data is a task with increasing significance for several applications, e.g. quality control and automatic updating of GIS data, automatic land use change detection, measurement of sealed areas for public authority uses, monitoring of land erosion etc. The use of additional sensors could improve the performance of the automated classification; however, because of additional costs or simple unavailability of data, this approach should be avoided. One possibility to stabilize an automatic image analysis is using remote sensing data of the same region of different dates that is often existing. This paper presents a method how a monotemporal knowledge representation can be expanded by a temporal component to take advantage of previous classifications of the same scene and knowledge about the time dependency of the object classes. The present approach proposes the combination of a semantic network, representing the generic description of the scene, and a state transition diagram, modeling the possible state transitions for each one of the classes of interest. The probabilities of the state transition diagram are introduced as a priori knowledge in a statistical classification procedure. Experimental results from a series of three aerial images from 1983 up to 2001 of a suburban region near Hannover are shown in order to illustrate the potential of the proposed multitemporal approach.
Item Response Theory

This is a title in our Understanding Statistics series, which is designed to provide researchers with authoritative guides to understanding, presenting and critiquing analyses and associated inferences. Each volume in the series demonstrates how the relevant topic should be reported - including detail surrounding what can be said, and how it should be said, as well as drawing boundaries around what cannot appropriately be claimed or inferred. This volume addresses an important issue for the design of survey instruments, which is rarely taught in graduate programs beyond those specifically for statisticians. Item Response Theory is used to describe the application of mathematical models to data from questionnaires and tests as a basis for measuring abilities, attitudes, or other variables. It is used for statistical analysis and development of assessments, often for high stakes tests such as the Graduate Record Examination. The author is known for her clear, accessible writing; like all books in this series, this volume includes examples of both good and bad write-ups for methods sections of journal articles.
On Pilot Grid Design for an OFDM Air Interface

In this paper, an analytical framework is established to dimension the pilot grid for OFDM in terms of overhead and power allocation. With the constraint that the receiver solely relies on pilot symbols for channel estimation, the capacity for OFDM over time-variant frequency selective channels is maximized. The authors show that the maximum capacity is achieved by placing pilots with maximum equidistant spacing given by the sampling theorem, if perfect interpolation is assumed and pilots are appropriately boosted. Allowing for realizable and possibly sub-optimum estimators where interpolation is not perfect, a semi-analytical best pilot allocation strategy is presented.
Behavior Model for Hearing-Dog Robot

Hearing dogs play a role of assisting hearing-impaired people. The touch of the dog to the people can alert the people to important life sounds, such as doorbells, alarm clocks and fire alarms. These dogs are professionally trained to touch and lead the handler to the source of the sound. Meanwhile hearing dogs are insufficient in the world. Thus a hearing-dog robot is expected as an alternative assistant. In this paper we proposed and constructed a behavior model for the hearing-dog robot. The behavior model is constructed by a discrete state transition. The robot can change the state and act properly according to the information acquired from the sensors of the robot. We conducted an experiment to evaluate the proposed behavior model. In the experiment the robot actually could act according to the behavior model, but in some cases the robot failed to notify the target user. We discussed the causes the robot failed and the improvements to solve them.
Using Dynamic Programming Strategy to Find an Optimal Solution to Exploiting Modification Direction Embedding Method

In this paper, we use dynamic programming strategy to find an optimal solution to the EMD (exploiting modification direction) embedding method proposed by Zhang et al. to carry (2n+1)-ary secret digits. An embedding/extraction function defined as a weighted sum function modulo (2n+1) is put forward in the EMD embedding method for secret digit embedding/extraction to/from an image. Among all the different permutations of these (2n+1) numbers, there exists an optimal solution corresponding to an embedding/extraction function, which can be used to minimize the distortion of stego-image. Without doubt, finding the best permutation will take a lot of computational time. Therefore, we shall use dynamic programming strategy to get an optimal solution.