Miracle-dz/UniFAR-FTUs huggingface dataset:
Evening College Students' Views on Their Own Behavior in English Writing Classes: A Preliminary Study

This paper reports on a preliminary investigation into evening college students’ views on their own behavior in English writing classes. A total of 68 English-majored students enrolled in the evening session of the Applied Foreign Languages department at a university of science and technology in northern Taiwan participated in this study. Questionnaire surveys were conducted with a primary focus on various inappropriate behaviors stated in the classroom conduct code. Initial findings showed that the majority of the participants were highly engaged in classroom activities. However, some were also involved in other activities. Chatting with classmates might be a more serious problem against the rules from students’ perspective. 
Star cluster formation and disruption time-scales — I. An empirical determination of the disruption time of star clusters in four galaxies

We have derived the disruption times of star clusters from cluster samples of four galaxies, M51, M33, the Small Magellanic Cloud (SMC) and the solar neighbourhood. If the disruption time of clusters in a galaxy depends only on their initial mass as t d i s (yr) = t d i s 4 (M c l /10 4 M O .) γ , and if the cluster formation rate is constant, then the mass and age distributions of the observed clusters will each be given by double power-law relations. For clusters of low mass or young age the power law depends on the fading of the clusters below the detection limit due to the evolution of the stars. For clusters of high mass and old age the power law depends on the disruption time of the clusters. The samples of clusters in M51 and M33, observed with HST-WFPC2, indeed show the predicted double power-law relations in both their mass and age distributions. The values of t d i s 4 and y can be derived from these relations. For the cluster samples of the SMC and the solar neighbourhood, taken from the literature, only the age distribution is known. This also shows the characteristic double power-law behaviour, which allows the determination of t d i s 4 and y in these galaxies. The values of y are the same in the four galaxies within the uncertainty, and the mean value is y = 0.62 ′ 0.06. However, the disruption time t d i s 4 of a cluster of 10 4 M O . is very different in the different galaxies. The clusters in the SMC have the longest disruption time, t d i s 4 ≃ 8 x 10 9 yr, and the clusters at 1-3 kpc from the nucleus of M51 have the shortest disruption time of t d i s 4 ≃ 4 x 10 7 yr. The disruption time of clusters 1-5 kpc from the nucleus of M33 is t d i s 4 ≃ 1.3 x 10 8 yr and for clusters within 1 kpc from the Sun we find t d i s 4 ≃ 1.0 × 10 9 yr.
Hyperbranched-polymer nanocomposite gratings with ultrahigh refractive index modulation amplitudes for volume holographic optical elements

We report on an experimental investigation of recording a plane-wave volume holographic transmission grating in a photopolymerizable nanoparticle-polymer composite film dispersed with hyperbranched-polymer (HBP) organic nanoparticles in an acrylate monomer blend codoped with an electron donor and acceptor photoinitiator/inhibitor system. The HBP organic nanoparticle possesses the ultrahigh refractive index of 1.82 at 532 nm owing to the inclusion of triazine and aromatic ring units, which provides a large difference in the refractive index between HBP and the formed polymer. It is found that the recorded NPC grating with 23 vol.% HBP dispersion possesses the saturated refractive index modulation amplitude as large as 4.5 x 10-2 at 532 nm and at recording intensities of a few mW/cm2. Obtained results suggest the use of our newly developed HBP-dispersed NPC as volume optical holographic elements for wearable display for augmented and mixed reality.
Toward a Causal Interpretation from Observational Data: A New Bayesian Networks Method for Structural Models with Latent Variables

Because a fundamental attribute of a good theory is causality, the information systems (IS) literature has strived to infer causality from empirical data, typically seeking causal interpretations from longitudinal, experimental, and panel data that include time precedence. However, such data are not always obtainable and observational (cross-sectional, nonexperimental) data are often the only data available. To infer causality from observational data that are common in empirical IS research, this study develops a new data analysis method that integrates the Bayesian networks (BN) and structural equation modeling (SEM) literatures. Similar to SEM techniques (e.g., LISREL and PLS), the proposed Bayesian networks for latent variables (BN-LV) method tests both the measurement model and the structural model. The method operates in two stages: First, it inductively identifies the most likely LVs from measurement items without prespecifying a measurement model. Second, it compares all the possible structural models among the identified LVs in an exploratory (automated) fashion and it discovers the most likely causal structure. By exploring the causal structural model that is not restricted to linear relationships, BN-LV contributes to the empirical IS literature by overcoming three SEM limitations (Lee, B., A. Barua, A. B. Whinston. 1997. Discovery and representation of causal relationships in MIS research: A methodological framework. MIS Quart. 21(1) 109–136) — lack of causality inference, restrictive model structure, and lack of nonlinearities. Moreover, BN-LV extends the BN literature by (1) overcoming the problem of latent variable identification using observed (raw) measurement items as the only inputs, and (2) enabling the use of ordinal and discrete (Likert-type) data, which are commonly used in empirical IS studies. The BN-LV method is first illustrated and tested with actual empirical data to demonstrate how it can help reconcile competing hypotheses in terms of the direction of causality in a structural model. Second, we conduct a comprehensive simulation study to demonstrate the effectiveness of BN-LV compared to existing techniques in the SEM and BN literatures. The advantages of BN-LV in terms of measurement model construction and structural model discovery are discussed.
Incidencia del sexo, número de hermanos y orden de nacimiento en las metas académicas de estudiantes universitarios

espanolLa motivacion academica constituye una parte central en los procesos de aprendizaje y comportamiento de logro. En la literatura se ha evidenciado la existencia de diferentes motivos para implicarse en actividades de aprendizaje, que configuran las metas academicas. Existen ademas variables personales y contextuales que pueden influenciar la construccion de distintas metas academicas. Sin embargo, son escasos los trabajos sobre la incidencia de variables personales y de la estructura familiar en las metas academicas de universitarios. El objetivo de esta investigacion fue analizar la relacion entre sexo, numero de hermanos, orden de nacimiento y metas academicas de los alumnos. Participaron 567 universitarios mexicanos, entre 18 y 25 anos de edad, de familias con un solo hijo y con varios hijos, que respondieron al Cuestionario para la Evaluacion de Metas Academicas (CEMA; Nunez, Gonzalez-Pienda, Gonzalez-Pumariega, Garcia, y Roces, 1997). Los resultados muestran que los varones con menos hermanos tienden a buscar metas de logro, que se relacionan a su vez con mayor rendimiento academico. Las mujeres primogenitas se orientan a metas de aprendizaje y presentar mayor rendimiento academico, que aquellas nacidas despues. Podemos concluir que para esta muestra existe un patron especifico por sexo entre el tamano de la familia, el orden de nacimiento, las metas academicas y el rendimiento academico. EnglishAcademic motivation is a central part of learning processes and achievement behavior. In the literature the existence of different reasons to be involved in learning activities that shape academic goals has been evidenced. There are also personal and contextual variables that can influence the development of different academic goals. However, there are few studies on the incidence of personal variables and family structure in the academic goals of university students. The objective of this research was to analyze the relationship between sex, number of siblings, birth order and students’ academic goals. Participants were 567 Mexican university students, aged 18 to 25, from families with only one child and with several children, who answered the Questionnaire for the Evaluation of Academic Goals (CEMA, Nunez, Gonzalez-Pienda, Gonzalez-Pumariega, Garcia, and Roces, 1997). Results show that males with fewer siblings tend to look for achievement goals, which in turn are related to higher academic achievement. First-born women are oriented to learning goals and present higher academic performance, than those born later. We can conclude that for this sample there is a specific pattern by sex between family size, birth order, academic goals and academic performance.
Critical Incidents in the Scale-Up of State Multitiered Systems of Supports

State and national educational leaders encourage the use of an integrated multitiered system of supports (MTSS) to improve services to students with academic and social behavior problems. Implementing and sustaining MTSS is facilitated by support from leaders in state education agencies (SEAs). The purpose of this study was to identify the specific events, resources, and supports that help or hinder the work of scaling up an integrated MTSS approach from the perspective of MTSS leaders in SEAs. Researchers interviewed leaders in 27 U.S. states using the critical incident technique, a qualitative methodology to identify critical incidents associated with changes in practice. Eight helping incident, seven hindering incident, and nine “wish list” categories were identified. Helping categories included multidisciplinary leadership, access to professional development, consistent language and/or practices, consultation with external partners, and a focus on student outcomes in evaluation and planning. Seven hindering categories included competing philosophies, high personnel turnover, varying levels of readiness, and inadequate data systems. Participants also identified two unique categories associated with the items they wished had happened or could happen in the future including access to personnel with high-level MTSS training and access to more effective interventions.
Portfolio Management with Heavy-Tailed Distributions in Islamic Finance

In Islamic Finance (IF hereafter), the safety-first rule of investing (hifdh almal) is held to be of utmost importance. According to the honesty principle (amanah), the Islamic portfolio manager (mudharib) is committed to do his best to fulfill this investing rule. This involves the use of the most appropriate management tools. The use of the normal assumption in the financial modeling is growing criticized. This also applies to Islamic Finance which assets' show empirical evidence such as asymmetry, heavy-tail and volatility clustering. For these reasons, we suggest the use of the stable and tempered stable distributions and the Student's t related copulas for portfolio modeling. The optimal portfolios are then selected and their performances are measured employing the STARR and Rachev ratios. We demonstrate, in this paper, that the simulated data based on stable and tempered stable distributions and related Student's t copula methods significantly improve the performance of IF portfolios, which even outperform non-Islamic ones, especially in stressed financial periods.
Neuroinflammation Leads to Region-Dependent Alterations in Astrocyte Gap Junction Communication and Hemichannel Activity

Inflammation attenuates gap junction (GJ) communication in cultured astrocytes. Here we used a well-characterized model of experimental brain abscess as a tool to query effects of the CNS inflammatory milieu on astrocyte GJ communication and electrophysiological properties. Whole-cell patch-clamp recordings were performed on green fluorescent protein (GFP)-positive astrocytes in acute brain slices from glial fibrillary acidic protein–GFP mice at 3 or 7 d after Staphylococcus aureus infection in the striatum. Astrocyte GJ communication was significantly attenuated in regions immediately surrounding the abscess margins and progressively increased to levels typical of uninfected brain with increasing distance from the abscess proper. Conversely, astrocytes bordering the abscess demonstrated hemichannel activity as evident by enhanced ethidium bromide (EtBr) uptake that could be blocked by several pharmacological inhibitors, including the connexin 43 (Cx43) mimetic peptide Gap26, carbenoxolone, the pannexin1 (Panx1) mimetic peptide 10Panx1, and probenecid. However, hemichannel opening was transient with astrocytic EtBr uptake observed near the abscess at day 3 but not day 7 after infection. The region-dependent pattern of hemichannel activity at day 3 directly correlated with increases in Cx43, Cx30, Panx1, and glutamate transporter expression (glial l-glutamate transporter and l-glutamate/l-aspartate transporter) along the abscess margins. Changes in astrocyte resting membrane potential and input conductance correlated with the observed changes in GJ communication and hemichannel activity. Collectively, these findings indicate that astrocyte coupling and electrical properties are most dramatically affected near the primary inflammatory site and reveal an opposing relationship between the open states of GJ channels versus hemichannels during acute infection. This relationship may extend to other CNS diseases typified with an inflammatory component.
Online Real Boosting for Object Tracking Under Severe Appearance Changes and Occlusion

Robust visual tracking is always a challenging but yet intriguing problem owing to the appearance variability of target objects. In this paper we propose a novel method to handle large changes in appearance based on online real-value boosting, which is utilized to incrementally learn a strong classifier to distinguish between objects and their background. By incorporating online real boosting into a particle filter framework, our tracking algorithm shows a strong adaptability for different target objects which undergo severe appearance changes during the tracking process.
Validation of an on-board taxi guidance system

An on-board taxi guidance system with displayed ground traffic and data link to air traffic control was validated in two main studies with 57 commercial airline pilots at DLR’s Institute of Flight Guidance simulation facilities. Following the validation guidelines by EUROCONTROL, results in terms of operational feasibility and operational improvements were gained. In a first step, eye gaze data were analysed to control the effect of increased head down times. In a second step (within the EU project EMMA2), hints for operational improvements were gathered in shape of questionnaires regarding workload and situation awareness.
A Prediction Model for Initial Trust Formation in B2C eCommerce

This study investigates initial trust formation with an unknown online company. Based on data collected from 628 respondents, the results indicate significant direct effects for trust in the Internet infrastructure, susceptibility to the social influence of media, and the presence of influential site characteristics, on user willingness to provide personal information to unknown Internet firms. This study extends the research on trust in e-commerce by providing a prediction model that is demonstrated to calculate the probability of user willingness to provide information. The utility of the model for identifying the relative importance of factors and predicting outcomes lends insight into important issues in online trust formation.
Combining temporal and spectral information for Query-by-Example Spoken Term Detection

We present a system for Query-by-Example Spoken Term Detection on zero-resource languages. The system compares speech patterns by representing the signal using two different acoustic models, a Spectral Acoustic (SA) model covering the spectral characteristics of the signal, and a Temporal Acoustic (TA) model covering the temporal evolution of the speech signal. Given a query and a utterance to be compared, first we compute their posterior probabilities according to each of the two models, compute similarity matrices for each model and combine these into a single enhanced matrix. Subsequence-Dynamic Time Warping (S-DTW) algorithm is used to find optimal subsequence alignment paths on this final matrix. Our experiments on data from the 2013 Spoken Web Search (SWS) task at Mediaeval benchmark evaluation show that this approach provides state of the art results and significantly improves both the single model strategies and the standard metric baselines.
Probabilistic modeling of sensor artifacts in critical care

We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular, we consider the arterial-line blood pressure sensor, which is subject to frequent data artifacts that cause false alarms in the ICU and make the raw data almost useless for automated decision making. The problem is complicated by the fact that the sensor data are acquired at fixed intervals whereas the events causing data artifacts may occur at any time and have durations that may be significantly shorter than the data collection interval. We show that careful modeling of the sensor, combined with a general technique for detecting sub-interval events and estimating their duration, enables effective detection of artifacts and accurate estimation of the underlying blood pressure values.
Fe b 20 00 Wavelet filters and infinite-dimensional unitary groups

Abstract. In this paper, we study wavelet filters and their dependence on two numbers, the scale N and the genus g. We show that the wavelet filters, in the quadrature mirror case, have a harmonic analysis which is based on representations of the C∗-algebra ON . A main tool in our analysis is the infinite-dimensional group of all maps T → U (N) (where U (N) is the group of all unitary N-by-N matrices), and we study the extension problem from low-pass filter to multiresolution filter using this group.
Learning Graph Matching: Oriented to Category Modeling from Cluttered Scenes

Although graph matching is a fundamental problem in pattern recognition, and has drawn broad interest from many fields, the problem of learning graph matching has not received much attention. In this paper, we redefine the learning of graph matching as a model learning problem. In addition to conventional training of matching parameters, our approach modifies the graph structure and attributes to generate a graphical model. In this way, the model learning is oriented toward both matching and recognition performance, and can proceed in an unsupervised fashion. Experiments demonstrate that our approach outperforms conventional methods for learning graph matching.
Bridging the Gap between Software and Hardware Techniques for I/O Virtualization

The paravirtualized I/O driver domain model, used in Xen, provides severl advantages including device driver isolation in a safe execution environment, support for guest VM transparent services including live migration, and hardware independence for guests. However, these advantages currently come at the cost of high CPU overhead which can lead to low throughput for high bandwidth links such as 10 gigabit Ethernet. Direct I/O has been proposed as the solution to this performance problem but at the cost of removing the benefits of the driver domain model. In this paper we show how to significantly narrow the performance gap by improving the performance of the driver domain model. In particular, we reduce execution costs for conventional NICs by 56% on the receive path, and we achieve close to direct I/O performance for network devices supporting multiple hardware receive queues. These results make the Xen driver domain model an attractive solution for I/O virtualization for a wider range of scenarios.
A concealment based approach to distributed video coding

This paper presents a concealment based approach to distributed video coding that uses hybrid key/WZ frames via an FMO type interleaving of macroblocks. Our motivation stems from a previous work of ours that showed promising results relative to the more common approach of splitting the sequence in key and WZ frames. In this paper, we extend our previous scheme to the case of I-B-P frame structures and transform domain DVC. We additionally introduce a number of enhancements at the decoder including use of spatio-temporal concealment for generating the side information on a MB basis, mode selection for switching between the two concealment approaches and for deciding how the correlation noise is estimated, local (MB wise) correlation noise estimation and modified B frame quantisation. The results presented indicate considerable improvement (up to 30%) compared to corresponding frame extrapolation and frame interpolation schemes.
Religious Belief vs. Religious Practice. What is More Beneficial to Elite Athletes? An Investigation of Religious/Spiritual Belief, and its Relationship to Challenge & Threat Appraisal

Religiosity/spirituality has been linked with reduced anxiety in athlete populations. This study set out to assess the impact of religious/spiritual belief, opposed to practice, to see whether it too would predict anxiety, as well as feelings of control and cognitive appraisal in elite athletes (N = 115). Self-reported self-efficacy, control, achievement goals, life satisfaction, trait anxiety and strength of belief in a higher power (SBHP) were measured and analysed with simple linear regressions and multiple regressions (with challenge and threat appraisals as the dependent variables). The models predicting both challenge and threat appraisal were found to be significant, although SBHP was not a significant predictor, nor was it significantly predicative of any of the variables, or significantly correlated with them. The contribution of religious/spiritual belief to psychological benefits is compared to religious/spiritual practice and discussed alongside implications for future research and applied practice.
Block diagonalization with algebraic interference control, extension to precoding on OFDMA chunks

Block diagonalization is a linear precoding technique which allows to suppress multi-user interference at the transmitter side. However, the interference cancellation comes at the cost of reduced number of degrees of freedom for users. We present in this contribution a new block diagonalization extension that increases the number of degrees of freedom for a subset of preferred terminals using an algebraic parameter. We show how this extension can be used in resource allocation in order to provide a better rate for high priority users without increasing the transmit power. With this scheme, the new algebraic parameter is used in addition to the transmit power in order to provide different priorities to the served users. Also, we investigate two low complexity approaches to exploit block diagonalization techniques in OFDMA scenarios by calculating one precoder for a chunk of sub-carriers. We compare these two methods in terms of sum capacity and sensitivity to the new parameter.