Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Film on the Empathy Ratings of Nursing Students

The purpose of this quasi-experimental study was to examine the effects of viewing the feature film Wit on the empathy ratings of nursing students. The Jefferson Scale of empathy (JSE) was used to measure nursing students’ empathy levels. findings suggest a statistically significant increase in empathy scores in the experimental group from pre-test to post-test #1 (t = 2.60; p = 0.0133) and also from pre-test to post-test #2 (t = 2.10; p = 0.0424). In this study, the experience of viewing the film, as opposed to classroom teaching alone, enhanced student empathy ratings.
Two-stage replication strategy in P2P VoD systems

In P2P (Peer-to-Peer) VoD (Video-on-Demand) systems, one of the key problems is cache replication. However, with the large scale P2P VoD systems deployed, people study on the log of these systems and gradually realize that the strategy which caches videos proportionally to their popularities is not optimal, especially for cold resources. In simulation, we show that cold videos produce the majority of server workload. In our work, we propose a two-stage cache replication strategy, which increases the distribution of cold resources in the system and reduces the redundant cache of popular resources. Through simulation, we find that the cache proportion of popular videos and cold videos has been readjusted. Owing to more proportion of cache capacity used to cache cold videos, the server workload produced by cold videos is reduced sharply while the server workload produced by popular videos stays low.
Gender-Specific Associations Between Kinesiology Undergraduate Students’ Personality Traits and their Motivation in School Physical Education

ABSTRACT The HEXACO dimensions of personality traits (honesty–humility, emotionality, extraversion, agreeableness, conscientiousness, and openness to experience) have been linked to many adaptive outcomes in physical education-related (PE) settings; yet, little is known about the relationship between personality traits and motivation in students of school PE. Using survey data from 300 (48.8% men, 51.2% women) university kinesiology students, this study explored gender-specific relations between the undergraduate students’ HEXACO personality traits and several indices of their motivation recalled from their experiences in school-based PE, namely, enjoyment, self-efficacy, positive affect, perceived autonomy support, and task and ego goal orientation. A second aim was to test differences in these constructs between kinesiology and PE majors. Results revealed that the HEXACO personality dimensions collectively predicted each of the six motivational constructs in females and four in males, extraversion predicted five motivational constructs in females and four in males, and openness to experience predicted three in females and two in males. Compared to kinesiology majors (n = 202), PE majors (n = 98) were statistically significantly higher in extraversion, enjoyment, perceived autonomy support, self-efficacy, and positive affect. Motivationally vulnerable students in PE may be those who are more introverted (shy, passive, and reserved) and open to experience (intellectual, creative, unconventional, innovative, and inquisitive). Further, PE majors might be more likely than kinesiology majors to pursue a vocation as a physical educator in part because they are more extraverted and have had more motivating (i.e., enjoyable, autonomy-supportive, performance-based, and self-efficacious) experiences in school-based PE.
ADROIT: Android malware detection using meta-information

Android malware detection represents a current and complex problem, where black hats use different methods to infect users' devices. One of these methods consists in directly upload malicious applications to app stores, whose filters are not always successful at detecting malware, entrusting the final user the decision of whether installing or not an application. Although there exist different solutions for analysing and detecting Android malware, these systems are far from being sufficiently precise, requiring the use of third-party antivirus software which is not always simple to use and practical. In this paper, we propose a novel method called ADROIT for analysing and detecting malicious Android applications by employing meta-information available on the app store website and also in the Android Manifest. Its main objective is to provide a fast but also accurate tool able to assist users to avoid their devices to become infected without even requiring to install the application to perform the analysis. The method is mainly based on a text mining process that is used to extract significant information from meta-data, that later is used to build efficient and highly accurate classifiers. The results delivered by the experiments performed prove the reliability of ADROIT, showing that it is capable of classifying malicious applications with 93.67% accuracy.
Coatings of Fe3O4 Nanoparticles as Selective Solar Absorber

Cost-effective and pollution-free green chemical method has been employed for synthesizing Fe3O4 nanoparticles which can be used as a solar absorbent and characterized further for their structural, optical and morphological properties using X-ray diffraction and UV-VIS-IR spectrophotometry and transmission electron microscopy techniques, respectively. Presence of Fe 2+ and Fe 3+ in nanoparticles is confirmed from the X-ray photoelectron spectroscopy analysis. The nanometric grain-size allows deposition of thin films, and the resulting coatings onto copper substrate show a relatively low thermal emittance in a range of 0.05-0.10. The solar absorptance values are between 0.76 and 0.85, which can provide an acceptable selectivity. Attempt is also made to find influence of the thickness effect on the selectivity having 15.2 as best value for one layer coating.
Development and Analysis of Markov Chain Model for Optimally Allocating Operators at Call Centers

The importance of call centers has been increasing as a valuable source of information for understanding how customers have been responding to products and services in the market. Accordingly, the operational scale of call centers has been expanding, and it is now important to manage operators efficiently so as to contain the cost increase. For this purpose, one of the key challenges is how to estimate the population size of potential customers who may access call centers, since it dictates the number of operators to be prepared. The purpose of this paper is to develop and analyze a Markov chain model so as to achieve this goal.
Scaffolding Reading Comprehension to Deepen Understanding of Text

Students are required to process large amounts of text, and they must be prepared to understand and evaluate text to gain meaning about the world around them. Reading comprehension is an essential component of the reading process, and the empirical research surrounding the topic of comprehension suggests that there is a need to examine reading comprehension pedagogy. Whereas research supports the need to examine the ways in which students process text, there is debate about how well our teachers are scaffolding comprehension skills and strategies. The literature surrounding the topic of scaffolding reading comprehension encourages teachers to access a wide repertoire of strategies and skills to differentiate reading comprehension instruction and then assess the learning of individuals. Another topic that is widely researched is the relationship between reading processes, with specific focus on how vocabulary development, reading fluency, word decoding, and language comprehension affect the understanding of text. When children begin their educational journey, teachers often focus on word decoding, and reading fluency. In this literature review, I will review the research to determine the value of facilitating reading comprehension instruction in early years education, to examine the most effective strategies to support deep learning of text and to discuss the implications of scaffolding reading comprehension strategies. I will also examine the impact of formative assessment techniques designed to promote growth in comprehension.
Developing Care Professionals : Changing Disability Services in Sweden

In Sweden, professionalization projects in disability care services are currently being undertaken in order to differentiate and establish a professional identity for professionals within care work. The aim of this paper was to analyse the experiences of care workers’ meaning of the professionalization process concerning their occupation and their occupational identity in relation to tasks they perform in front-line contacts with persons with intellectual and developmental disabilities at respite care service homes. Semi-structured interviews were conducted with ten care workers. The meaning of the professionalization projects is an ongoing process of a connected mission, meaning that the care work is performed in close contact with care receivers and that it takes place within an informal and free framework, predicated on a logic of possessing a particular kind of “care-feeling. ”
N C ] 3 J an 2 01 7 Loss of inter-frequency brain hubs in Alzheimer ’ s disease

Alzheimer’s disease (AD) causes alterations of brain network structure and function. The latter consists of connectivity changes between oscillatory processes at different frequency channels. We proposed a multi-layer network approach to analyze multiple-frequency brain networks inferred from magnetoencephalographic recordings during resting-states in AD subjects and age-matched controls. We used the multi-participation coefficient (MPC) to quantify the tendency of brain regions to facilitate information propagation across different frequencies. Main results showed that regional connectivity of AD subjects was abnormally distributed across frequency bands as compared to controls. This loss of inter-frequency centrality was mainly localized in association areas exhibiting fewer interactions with higher sensory rhythms (> 20 Hz) and more connections to lower attentional ones (< 13 Hz). MPC values significantly correlated with memory impairment of AD subjects, as measured by the total recall score. Most predictive regions belonged to components of the default-mode network that are typically affected by atrophy, metabolism disruption and amyloid-β deposition. We evaluated the diagnostic power of the MPC and we showed that it led to increased classification accuracy (78.39%) and sensitivity (91.11%). These findings suggest that multi-layer network frameworks reveal complementary information that can be used to identify inter-frequency neural mechanisms of brain diseases.
An empirical study on investigating the role of KMS in promoting trust within GSD teams

The purpose of this paper is to examine the extent to which KMS usage helps in developing and maintaining trust within GSD project's team members- an area that is very important but has, to date, not been addressed adequately. Design/methodology/approach -- A survey instrument comprising of 7 factors and 35 elements was developed based on tested questions and literature review. Through a web-based survey, data were collected from GSD employees working in different countries that are using KMS for knowledge management. Findings -- The results of the survey revealed that KMS usage is positively related with employee's propensity to trust and cooperative behavior. There exist an indirect positive relationship between KMS and perceived trustworthiness. Further, Leadership support help in promoting the use of KMS for knowledge seeking and contribution within GSD organizations employees. However, the KMS usage is negatively related with monitoring behavior exist within GSD teams. Research limitations/implications -- The number of responses received was rather small since GSD and KMS are both new and emerging disciplines, and not many organizations are formally using KMS for this purpose. Practical implications -- The results of the study suggest that KMS if implemented and used properly helps the GSD organizations in getting the desired benefits of GSD. Further, leaders play an important role in the success of KMS by motivating the employees towards KMS usage. The findings of this study, we hope, will help and facilitate the organizations in making their GSD projects successful. Academics can use the results to build models that further enhance the KMS domain and propose the strategies for improving KMS usage in order to get maximum benefits through KMS.
Problems , Methods , and Challenges in Comprehensive Data Cleansing

Cleansing data from impurities is an integral part of data processing and maintenance. This has lead to the development of a broad range of methods intending to enhance the accuracy and thereby the usability of existing data. This paper presents a survey of data cleansing problems, approaches, and methods. We classify the various types of anomalies occurring in data that have to be eliminated, and we define a set of quality criteria that comprehensively cleansed data has to accomplish. Based on this classification we evaluate and compare existing approaches for data cleansing with respect to the types of anomalies handled and eliminated by them. We also describe in general the different steps in data clean-sing and specify the methods used within the cleansing process and give an out-look to research directions that complement the existing systems.
Learning motor primitives for robotics

The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the application of machine learning techniques in this context. Employing an improved form of the dynamic systems motor primitives originally introduced by Ijspeert et al. [2], we show how both discrete and rhythmic tasks can be learned using a concerted approach of both imitation and reinforcement learning. For doing so, we present both learning algorithms and representations targeted for the practical application in robotics. Furthermore, we show that it is possible to include a start-up phase in rhythmic primitives. We show that two new motor skills, i.e., Ball-in-a-Cup and Ball-Paddling, can be learned on a real Barrett WAM robot arm at a pace similar to human learning while achieving a significantly more reliable final performance.
Pose estimation of a tilted pellet using single view from robot mounted camera

This paper proposes a novel approach for finding the orientation of the tilted pellet using a single view of the pellet. This is important for the automation of pick and place problem. A texture less isolated cylindrical object is used for the pick and place operation. In this approach the isolated pellets are segmented from the background, following which, its contour is estimated. Then based on the assumption that length and diameter of the pellet remains constant, the mathematical formulation of the pose estimation of the pellet is given, and using which the orientation of the tilted pellet is computed using just single view. This is then experimentally verified for the different orientations of the pellet and the results are within the acceptable levels of accuracy A brief overview of the error estimation has been included. This error in orientation of the pellet is due to the variance in the actual height of the pellet. Error Jacobian for the above inaccuracy was calculated, and was found to be within required limits.
A comparison of displaced phase centre antenna and along-track interferometry techniques for RADARSAT-2 ground moving target indication

Canada's RADARSAT-2 commercial synthetic aperture radar (SAR) satellite will have an experimental mode that will permit ground moving target indication (GMTI) measurements to be made. In this mode of operation, the radar antenna is partitioned into two subapertures that sequentially observe the scene of interest from the same point in space. Two of the GMTI processing approaches currently being explored are examined in this paper. One utilizes the displaced phase centre antenna (DPCA) clutter-cancellation technique to provide subclutter visibility for dim, slowly moving objects. The other is based on the along-track interferometry (ATI) technique, in which magnitude and phase information of the targets' interferograms are exploited to extract them from the background clutter. In this paper the performance of each processor is examined for three RADARSAT-2 slant-range resolutions: 12.5, 3.0, and 1.5 m. The study focuses on the influence of SAR resolution cell size on the GMTI processor performance. Results indicate that, as SAR slant-range resolution increases, the SAR ATI improves in performance, whereas the SAR DPCA does not.
Subband patches: A new technique for wavelet-based still image and video coding

In this paper, the third type of wavelet decomposition is proposed that allows us to combine the plain hierarchical structure of Mallat pyramid and the adaptivity of wavelet packets. The proposed approach assumes local adaptive subband decomposition, i.e. after pyramid wavelet decomposition, each subband is segmented to find blocks that are profitable for the secondary transform in the terms of rate-distortion cost. It was suggested to encode groups of wavelet coefficients that have strong 1-D correlation (e.g., contours) using methods based on spatial-orientation trees, as rate-distortion performance of the explicit shape coding methods is low enough. The overall objective performance of the implemented encoder is estimated by rate-distortion curve. Experiments reveal 0.1-0.2 dB improvement for the same bit-rate over the coder based on space-frequency quantization.
Frequency-Domain Analysis of Intrinsic Neuronal Properties using High-Resistant Electrodes

Intrinsic cellular properties of neurons in culture or slices are usually studied by the whole cell clamp method using low-resistant patch pipettes. These electrodes allow detailed analyses with standard electrophysiological methods such as current- or voltage-clamp. However, in these preparations large parts of the network and dendritic structures may be removed, thus preventing an adequate study of synaptic signal processing. Therefore, intact in vivo preparations or isolated in vitro whole brains have been used in which intracellular recordings are usually made with sharp, high-resistant electrodes to optimize the impalement of neurons. The general non-linear resistance properties of these electrodes, however, severely limit accurate quantitative studies of membrane dynamics especially needed for precise modelling. Therefore, we have developed a frequency-domain analysis of membrane properties that uses a Piece-wise Non-linear Electrode Compensation (PNEC) method. The technique was tested in second-order vestibular neurons and abducens motoneurons of isolated frog whole brain preparations using sharp potassium chloride- or potassium acetate-filled electrodes. All recordings were performed without online electrode compensation. The properties of each electrode were determined separately after the neuronal recordings and were used in the frequency-domain analysis of the combined measurement of electrode and cell. This allowed detailed analysis of membrane properties in the frequency-domain with high-resistant electrodes and provided quantitative data that can be further used to model channel kinetics. Thus, sharp electrodes can be used for the characterization of intrinsic properties and synaptic inputs of neurons in intact brains.
How dynamic is the ISPs address space? Towards internet-wide DHCP churn estimation

IP address counts are typically used as a surrogate metric for the number of hosts in a network, as in the case of ISP rankings based on botnet infected addresses. However, due to effects of dynamic IP address allocation, such counts tend to overestimate the number of hosts, sometimes by an order of magnitude. In the literature, the rate at which hosts change IP addresses is referred to as DHCP churn. Churn rates vary significantly within and among ISP networks, and such variation poses a challenge to any research that relies upon IP addresses as a metric. We present the first attempt towards estimating ISP and Internet-wide DHCP churn rates, in order to better understand the relation between IP addresses and hosts, as well as allow us to correct data relying on IP addresses as a surrogate metric. We propose an scalable active measurement methodology and then validate it using ground truth data from a medium-sized ISP. Next, we build a statistical model to estimate DHCP churn rates and validate against the ground truth data of the same ISP, estimating correctly 72.3% of DHCP churn rates. Finally, we apply our measurement methodology to four major ISPs, triangulate the results to another Internet census, and discuss the next steps to more precisely estimate DHCP churn rates.
Concept-based term weighting for Web information retrieval

In this paper we present a novel technique for determining term importance by exploiting concept-based information found in ontologies. Calculating term importance is a significant and fundamental aspect of most information retrieval approaches and it is traditionally determined through inverse document frequency (IDF). We propose concept-based term weighting (CBW), a technique that is fundamentally different to IDF in that it calculates term importance by intuitively interpreting the conceptual information in ontologies. We show that when CBW is used in an approach for Web information retrieval on benchmark data, it performs comparatively to IDF, with only a 3.5% degradation in retrieval accuracy. While this small degradation has been observed the significance of this technique is that 1) unlike IDF, CBW is independent of document collection statistics, 2) it presents a new way of interpreting ontologies for retrieval and 3) it introduces an additional source of term importance information that can be used for term weighting.
Identification of the Bile Acid Transporter Slco1a6 as a Candidate Gene That Broadly Affects Gene Expression in Mouse Pancreatic Islets

We surveyed gene expression in six tissues in an F2 intercross between mouse strains C57BL/6J (abbreviated B6) and BTBR T+ tf/J (abbreviated BTBR) made genetically obese with the Leptinob mutation. We identified a number of expression quantitative trait loci (eQTL) affecting the expression of numerous genes distal to the locus, called trans-eQTL hotspots. Some of these trans-eQTL hotspots showed effects in multiple tissues, whereas some were specific to a single tissue. An unusually large number of transcripts (∼8% of genes) mapped in trans to a hotspot on chromosome 6, specifically in pancreatic islets. By considering the first two principal components of the expression of genes mapping to this region, we were able to convert the multivariate phenotype into a simple Mendelian trait. Fine mapping the locus by traditional methods reduced the QTL interval to a 298-kb region containing only three genes, including Slco1a6, one member of a large family of organic anion transporters. Direct genomic sequencing of all Slco1a6 exons identified a nonsynonymous coding SNP that converts a highly conserved proline residue at amino acid position 564 to serine. Molecular modeling suggests that Pro564 faces an aqueous pore within this 12-transmembrane domain-spanning protein. When transiently overexpressed in HEK293 cells, BTBR organic anion transporting polypeptide (OATP)1A6-mediated cellular uptake of the bile acid taurocholic acid (TCA) was enhanced compared to B6 OATP1A6. Our results suggest that genetic variation in Slco1a6 leads to altered transport of TCA (and potentially other bile acids) by pancreatic islets, resulting in broad gene regulation.