Miracle-dz/UniFAR-FTUs huggingface dataset:
A NAK Suppression Scheme for Group Communications Considering the Spatial Locality of Packet Losses

Summary Today's extensive use of multicast communication demands efficiency, scalability, and reliability. Numerous schemes have been proposed to improve these critical areas and some progress has been realized. Among the most recent and effective schemes that address this issue include the tree-based NAK suppression scheme that emphasizes on reducing NAK implosion at the repair node. The procedure employed would be an optimal solution, if in fact, for every multicast session transmission, at least one receiver node is guaranteed to receive the packet. However, the largest portion of packet loss in multicasting is due to buffer overflow and as a result there is significant spatial locality of packet losses among nodes of a local group. We propose a NAK suppression scheme that considers this property. Compared to the existing schemes, the proposed scheme will significantly reduce traffic congestion, NAK implosion at repair nodes, and the overall error recovery delay. While the issue of traffic congestion reduction is obvious when receiver nodes do not have to make unfruitful attempts to acquire retransmissions from other local group members that are already starved of the same packets, the much reduced NAK implosion at repair nodes and error recovery delay are clearly illustrated in our simulation results.
Finding a Place in the Journalistic Field

This research explores how two digital native news organisations, BuzzFeed and Vice, compete for recognition and legitimacy in the journalistic field. Specifically, this paper focuses on the hiring practices and organisation of news coverage at both outlets, viewing these in Bourdieu’s terms as significant forms of capital that BuzzFeed and Vice valorise in an attempt to claim a place in the journalistic field. Findings suggest that BuzzFeed and Vice both challenge and reify existing ways of doing journalism, and thus play a double role in conserving and transforming the established cultural capital of the field. The findings of this research are based on over 20 semi-structured interviews conducted with various editors and reporters from both organisations.
Integrating Behavioral Science With Mobile (mHealth) Technology to Optimize Health Behavior Change Interventions

Recent rapid advances in technology have provided us with a golden opportunity to effect change in health-related outcomes for chronic disease by employing digital technologies to encourage and support behavior change to promote and maintain health. Behavior change theories are the bedrock to developing evidence-based mHealth interventions. Digital technologies enable researchers to empirically test behavioral theories in “real-world” contexts using behavior change techniques (Hekler, Michie, et al., 2016). According to the European Commission (2014) among the world’s population of 7 billion, there are over 5 billion mobile devices and over 90% of the users have their mobile device near them 24 hr a day. This provides a huge opportunity for behavior change and one that health psychologists have already begun to address. However, while a novel and exciting area of research, many early studies have been criticized for lacking a strong evidence base in both design and implementation. The European Commission conducted a public consultation in 2016 on the issues surrounding the use of mHealth tools (e.g., apps) and found a lack of global standards was a significant barrier. Recently, the World Health Organization (WHO) mHealth Technical Evidence Review Group developed the mHealth evidence reporting and assessment (mERA) checklist for specifying the content of mHealth interventions. Health psychologists play a key role in developing mHealth interventions, particularly in the management of chronic disease. This article discusses current challenges facing widespread integration of mobile technology into self-management of chronic disease including issues around security and regulation, as well as investigating mechanisms to overcoming these barriers.
The Impact of Religion on Family Functioning in Low-Income African American Families With Adolescents

The current study explores the association between religion and family functioning. Specifically, this study examined whether two aspects of religion, social religious support (from clergy and members of the congregation) and support from God (or spirituality), were related to frequency of household routines and parenting strategies as reported by both parents and adolescents, as well as adolescent problem behaviors. The sample consisted of 115 low-income African American mother-adolescent (age 14-18 years) dyads. Families were recruited as part of a larger study on the lives of low-income African American families with adolescents. Results indicated that higher levels of social religious support and spirituality were associated with increased levels of family routine as reported by caregivers. These results highlight the important roles relationships with God and other church members may play in supporting the lives of low-income African American parents and their children.
Study on Cultivation of College Students' Intercultural Communicative Competence in Context of Globalization

Currently English has become a lingua franca and much importance must be attached to the cultivation of Chinese college students’ intercultural communicating competence in order for them to communicate Chinese culture to the outside world, which can promote Chinese culture to go abroad and enhance the international influence of Chinese cultures. Two paths may be adopted in the college English teaching: first, to carry out intercultural teaching action research, and second learners acting as ethnography
Automatic coastline extraction in remotely sensed images using improved watershed algorithm

This paper presents new application of a improved watershed algorithm in extraction of coastlines. The proposed algorithm uses a single queue and conditional neighborhood comparisons for processing 3_3, 5_5 neighboring pixels to reduce computational complexity while compared to the conventional watershed algorithm. The results compares with the conventional algorithm of coastlines extraction, the proposed algorithm has a clear and simple result including muddy coastlines, which needs less post-processing working.
Who stays proactive after entrepreneurship training? Need for cognition, personal initiative maintenance, and well-being

Personal initiative training is a promising way to increase entrepreneurial personal initiative, which is a key behavior for successful entrepreneurship. Although personal initiative training has been shown to promote personal initiative, little is known about how this proactive behavior can be maintained over time and what the consequences are. The training transfer literature suggests that training effects usually decline with time. It is not clear, however, which factors contribute to personal initiative maintenance and which benefits go along with it. In a randomized controlled field experiment with 912 microentrepreneurs in Lome, Togo, we investigate the influence of need for cognition—a cognitive factor driving proactive behavior—on personal initiative maintenance after training. In addition, we examine the effect of need for cognition on the well‐being consequences of personal initiative maintenance. We show that people high in need for cognition tend to maintain posttraining personal initiative longer than those low in need for cognition. However, contrary to our predictions, need for cognition has no effect on the level of well‐being that results from personal initiative maintenance. Our findings contribute to a better understanding of personal initiative and its maintenance and could be used to increase training effectiveness.
vSkyConf: cloud-assisted multi-party mobile video conferencing

As an important application in today's busy world, mobile video conferencing facilitates people's virtual face-to-face communication with friends, families and colleagues, via their mobile devices on the move. However, how to provision high-quality, multi-party video conferencing experiences over mobile devices is still an open challenge. The fundamental reason behind is the lack of computation and communication capacities on the mobile devices, to scale to large conferencing sessions. In this paper, we present vSkyConf, a cloud-assisted mobile video conferencing system to fundamentally improve the quality and scale of multi-party mobile video conferencing. By novelly employing a surrogate virtual machine in the cloud for each mobile user, we allow fully scalable communication among the conference participants via their surrogates, rather than directly. The surrogates exchange conferencing streams among each other, transcode the streams to the most appropriate bit rates, and buffer the streams for the most efficient delivery to the mobile recipients. A fully decentralized algorithm is designed to decide the best paths of streams and the most suitable surrogates for video transcoding along the paths, such that the limited bandwidth is fully utilized to deliver streams of the highest possible quality to the mobile recipients. We also carefully tailor a buffering mechanism on each surrogate to cooperate with efficient stream distribution. We have implemented vSkyConf based on Amazon EC2 and verified the excellent performance of our design, as compared to the widely adopted unicast solutions.
Transforming Graph Data for Statistical Relational Learning

Relational data representations have become an increasingly important topic due to the recent proliferation of network datasets (e.g., social, biological, information networks) and a corresponding increase in the application of Statistical Relational Learning (SRL) algorithms to these domains. In this article, we examine and categorize techniques for transforming graph-based relational data to improve SRL algorithms. In particular, appropriate transformations of the nodes, links, and/or features of the data can dramatically affect the capabilities and results of SRL algorithms. We introduce an intuitive taxonomy for data representation transformations in relational domains that incorporates link transformation and node transformation as symmetric representation tasks. More specifically, the transformation tasks for both nodes and links include (i) predicting their existence, (ii) predicting their label or type, (iii) estimating their weight or importance, and (iv) systematically constructing their relevant features. We motivate our taxonomy through detailed examples and use it to survey competing approaches for each of these tasks. We also discuss general conditions for transforming links, nodes, and features. Finally, we highlight challenges that remain to be addressed.
Extracting a Repository of Events and Event References from News Clusters

In this paper, we prose to build a repository of events and event references from clusters of news articles. We present an automated approach that is based on the hypothesis that if two sentences are a) found in the same cluster of news articles and b) contain temporal expressions that reference the same point in time, they are likely to refer to the same event. This allows us to group similar sentences together and apply open-domain Information Extraction (OpenIE) methods to extract lists of textual references for each detected event. We outline our proposed approach and present a preliminary evaluation in which we extract events and references from 20 clusters of online news. Our experiments indicate that for the largest part our hypothesis holds true, pointing to a strong potential for applying our approach to building an event repository. We illustrate cases in which our hypothesis fails and discuss ways for addressing sources or errors.
Audit Judgments Using Belief versus Probability Assessment

This experimental study of 96 experienced auditors examines whether auditors’ judgments are influenced by the ‘approach’ used by the auditors in uncertainty assessment and by the ‘framing’ of an audit assertion to be verified. Approach was manipulated by using belief functions and probability theory as the manner in which uncertainty was assessed. Differences in framing were manipulated by stating the financial statement assertions to be examined in negative versus positive form. Prior research on framing effects in auditing and in psychology reports somewhat inconsistent results. Such observed inconsistency may have resulted from the nature of framing treatment and/or the approach used to elicit auditors’ uncertainty assessments. Thus we investigate both the effects on auditors’ judgments of ‘assertion framing’ and ‘uncertainty assessment approach’ and also the possibility of significant interactions between these two factors. We find limited evidence of approach effects and pervasive evidence of framing effects. On an auditor by auditor basis, we find a wide range of differences in belief versus probability assessments given the same audit situation. However, only in one case, are the judgments captured by using belief functions statistically different from the judgments captured by using a probability approach. Furthermore, there is some evidence that the auditors exhibit a confirmation bias, that is, have a tendency to place more weight on the aspect of mixed audit evidence that confirms a given assertion than the aspect that disconfirms it. These results are important for both audit theory and practice in that they show that auditors form different likelihood assessments (either belief or probability assessments) based on the same audit evidence depending on the framing of an audit assertion. Such differences may impact both audit effectiveness and efficiency.
Identifying Space Use at Foraging Arena Scale within the Home Ranges of Large Herbivores

An intermediate spatiotemporal scale of food procurement by large herbivores is evident within annual or seasonal home ranges. It takes the form of settlement periods spanning several days or weeks during which foraging activity is confined to spatially discrete foraging arenas, separated by roaming interludes. Extended by areas occupied for other activities, these foraging arenas contribute towards generating the home range structure. We delineated and compared the foraging arenas exploited by two African large herbivores, sable antelope (a ruminant) and plains zebra (a non-ruminant), using GPS-derived movement data. We developed a novel approach to specifically delineate foraging arenas based on local change points in distance relative to adjoining clusters of locations, and compared its output with modifications of two published methods developed for home range estimation and residence time estimation respectively. We compared how these herbivore species responded to seasonal variation in food resources and how they differed in their spatial patterns of resource utilization. Sable antelope herds tended to concentrate their space use locally, while zebra herds moved more opportunistically over a wider set of foraging arenas. The amalgamated extent of the foraging arenas exploited by sable herds amounted to 12-30 km2, compared with 22-100 km2 for the zebra herds. Half-day displacement distances differed between settlement periods and roaming interludes, and zebra herds generally shifted further over 12h than sable herds. Foraging arenas of sable herds tended to be smaller than those of zebra, and were occupied for period twice as long, and hence exploited more intensively in days spent per unit area than the foraging arenas of zebra. For sable both the intensity of utilization of foraging arenas and proportion of days spent in foraging arenas relative to roaming interludes declined as food resources diminished seasonally, while zebra showed no seasonal variation in these metrics. Identifying patterns of space use at foraging arena scale helps reveal mechanisms generating the home range extent, and in turn the local population density. Thereby it helps forge links between behavioural ecology, movement ecology and population ecology.
Identifying the underlying physics of the ridge via 3-particle Δη–Δη correlations

We present the first results on 3-particle Δη–Δη correlations in minimum bias d + Au, peripheral and central Au+Au collisions at = 200 GeV measured by the STAR experiment. The analysis technique is described in detail. The ridge particles, observed at large Δη in dihadron correlations in central Au+Au collisions, appear to be uniformly distributed over the measured Δη–Δη region in 3-particle correlation. The results, together with theoretical models, should help further our understanding of the underlying physics of the ridge.
The search for ancestral nervous systems: an integrative and comparative approach

Even the most basal multicellular nervous systems are capable of producing complex behavioral acts that involve the integration and combination of simple responses, and decision-making when presented with conflicting stimuli. This requires an understanding beyond that available from genomic investigations, and calls for a integrative and comparative approach, where the power of genomic/transcriptomic techniques is coupled with morphological, physiological and developmental experimentation to identify common and species-specific nervous system properties for the development and elaboration of phylogenomic reconstructions. With careful selection of genes and gene products, we can continue to make significant progress in our search for ancestral nervous system organizations.
The Flatter, the Better: Query Compilation Based on the Flattening Transformation

We demonstrate the insides and outs of a query compiler based on the flattening transformation, a translation technique designed by the programming language community to derive efficient data-parallel implementations from iterative programs. Flattening admits the straightforward formulation of intricate query logic including deeply nested loops over (possibly ordered) data or the construction of rich data structures. To demonstrate the level of expressiveness that can be achieved, we will bring a compiler frontend that accepts queries embedded into the Haskell programming language. Compilation via flattening takes places in a series of simple steps all of which will be made tangible by the demonstration. The final output is a program of lifted primitive operations which existing query engines can efficiently implement. We provide backends based on PostgreSQL and VectorWise to make this point however, most set-oriented or data-parallel engines could benefit from a flattening-based query compiler.
Identification and analysis of fundamental issues in Terfenol-D transducer modeling

Complete models of highly-magnetostrictive Terfenol-D transducers must be able to characterize the magnetostriction upon knowledge of the impressed electrical energy. Fundamental characterization laws are not available at present, because the existing modeling techniques fail to simultaneously span all operating regimes: electric, magnetic, mechanical, and thermal, across the whole performance space of these transducers. This paper attempts to capture the essential aspects of these regimes and their interactions, i.e. those that the transducer designer is likely to encounter during design, analysis and modeling of magnetostrictive devices. The issues discussed here are the magnetization and stress states, thermal effects, magnetomechanical hysteresis, AC losses, system nonlinearities, and transducer dynamics. In addition, some of the more relevant modeling techniques that address these issues are presented and analyzed.
Composite Shewhart-Poisson GWMA Control Chart with Sensitizing Rules

To enhance the detection ability of the Poisson GWMA control chart, this work uses the composite Shewhart-Poisson GWMA control chart to monitor Poisson counts to detect small shifts more quickly. The Shewhart-Poisson GWMA control chart uses numerical simulation to determine average run lengths of various process mean shifts under adjusted parameters. Consequently, adding sensitizing rules increases the ability of Poisson GWMA control chart to detect small shifts and the rate of false alarms simultaneously.
Mycoplasma pneumoniae CARDS Toxin Exacerbates Ovalbumin-Induced Asthma-Like Inflammation in BALB/c Mice

Mycoplasma pneumoniae causes a range of airway and extrapulmonary pathologies in humans. Clinically, M. pneumoniae is associated with acute exacerbations of human asthma and a worsening of experimentally induced asthma in mice. Recently, we demonstrated that Community Acquired Respiratory Distress Syndrome (CARDS) toxin, an ADP-ribosylating and vacuolating toxin synthesized by M. pneumoniae, is sufficient to induce an asthma-like disease in BALB/cJ mice. To test the potential of CARDS toxin to exacerbate preexisting asthma, we examined inflammatory responses to recombinant CARDS toxin in an ovalbumin (OVA) murine model of asthma. Differences in pulmonary inflammatory responses between treatment groups were analyzed by histology, cell differentials and changes in cytokine and chemokine concentrations. Additionally, assessments of airway hyperreactivity were evaluated through direct pulmonary function measurements. Analysis of histology revealed exaggerated cellular inflammation with a strong eosinophilic component in the CARDS toxin-treated group. Heightened T-helper type-2 inflammatory responses were evidenced by increased expression of IL-4, IL-13, CCL17 and CCL22 corresponding with increased airway hyperreactivity in the CARDS toxin-treated mice. These data demonstrate that CARDS toxin can be a causal factor in the worsening of experimental allergic asthma, highlighting the potential importance of CARDS toxin in the etiology and exacerbation of human asthma.
Publications in the doctoral thesis: challenges for doctoral candidates, supervisors, examiners and administrators

ABSTRACT Encouraging doctoral students to publish during their candidature is becoming more widely accepted and practised, both in Australia and internationally, although it is still less common in some fields. Almost all universities in Australia now offer candidates an option to include publications in their doctoral thesis. This paradigm shift has occurred over several decades as the role of doctoral education has been debated, but guidelines for students, supervisors and examiners have yet to catch up. While various benefits, challenges and criticisms have been discussed by established academics, the voices of the candidates themselves are limited. Using a narrative inquiry approach, this study helps to fill that void by reporting the personal experiences of the author, who recently completed a thesis with publications (TWP) in education. As such, this paper not only illuminates the potential challenges for doctoral candidates but it also offers possible ways in which universities, supervisors, examiners and candidates themselves can make the path to completing a doctoral TWP easier to navigate.
Cost Reduction through Combining Test Sequences with Input Data

Nowadays computer applications mainly depend on input data that bear additional constraints to be considered and evaluated carefully. Very often, this invokes test sequences that describe the path to the place where input data is to be entered, e.g., while testing graphical user interactions. Model based testing allows deriving those test sequences from a model, for example, based on event sequence graphs (ESGs) where the nodes represent events. Unfortunately, combining ESG with the great variety of input data considerably inflates them with respect to the number of their nodes. To avoid this event inflation, previous work extended ESGs by decision tables to take this variety and constraints on input data into account. This paper extends the previous work and shows how to derive input data-supplemented test sequences and, at the same time, to considerably reduce effort for test generation and test execution. A case study drawn from a large commercial web portal evaluates the approach and analyzes its characteristics.