Miracle-dz/UniFAR-FTUs huggingface dataset:
Desire for vengeance and revenge: An emotion‐based approach to revenge

When someone has suffered at the hands of someone else, he or she might develop a tendency to take revenge, that is: “An attempt, at some cost or risk to oneself, to impose suffering upon those who have made us suffer. ” (Elster, 1990, p. 155). Traditionally, most research on vengeance has focused on the act of revenge and not so much on the emotional state of desire for vengeance. In this dissertation, I described a set of studies that further enhances our understanding of desire for vengeance and its relation with actual revenge. I focused on three questions. First, what is desire for vengeance? Second, when and under which circumstances does desire for vengeance lead to revenge? And third, why are people motivated to take revenge? The results presented in this dissertation provided important insights in desire for vengeance and revenge. First, the experiential content of desire for vengeance was revealed. Second, it was shown that revenge is more likely when salient others of the victim approve revenge, or when the victim experiences strong feelings of anger as part of his or her desire for vengeance. And third, it was shown that in severe situations individuals experience more satisfaction from personally getting back at the offender than from observing vengeance by a third party. Whereas in moderate severe situations individuals experience equal amounts of satisfaction after personal revenge and vengeance by a third party. Altogether, this dissertation increases our understanding of desire for vengeance and its relation with actual revenge.
Unifying Space and Service for Makers, Entrepreneurs, and Digital Scholars

This article explores the evolution and role of makerspaces in academic libraries, with a particular focus on how libraries are using innovation spaces in support of entrepreneurship and digital humanities on campus. At the University of Arizona Libraries in Tucson, a unique new coworking and makerspace called the iSpace has developed. While many libraries have long supported digital humanities and digital scholarship, the emergence of makerspaces has led to new approaches to learning and knowledge creation within the library and campus ecosystem. Cross-disciplinary collaborations and the cultivation of a community of learners are two among many benefits to this approach and service. As academic libraries aim to meet multiple demands on space, budgets, and changing learning environments, many of them will consider establishing their own makerspaces. Looking at makerspaces through this lens of wide support for both entrepreneurs and digital scholars will provide unique perspectives for wider conversations.
The QualiSPo approach to OSS product quality evaluation

The quality of Open Source Software (OSS) is generally much debated. Some state that it is generally higher than closed-source counterparts, while others are more skeptical. In the QualiSPo project the authors addressed the problem of evaluating OSS products in a manner that is both as complete as possible and objective. To this end, a toolset and an evaluation framework are needed. The paper describes such toolset and framework, and accounts for the first evaluations that are being obtained.
A scalable cloud computing deployment framework for efficient MapReduce operations using Apache YARN

Cloud computing has become the buzz word since many years. The importance of data storage and processing in cloud has increased since the past two years. The digital data growth has contributed significantly for cloud storage. Hadoop is being used for data intensive computations and the latest Hadoop version YARN is more efficient than its predecessors. In this paper we are proposing a framework which will help in deploying cloud over YARN architecture. The paper also deals with the bulk creation of virtual machines in cloud.
Designing personalised , multilingual speech and language based applications

In this paper, we outline the challenges facing interaction designers of next generation personalised, multilingual speech and language based interfaces. The ever-increasing amount of digital content requires the application of language technologies such as machine translation, text categorisation and automatic speech recognition and synthesis in order to make the content accessible to a wide range of users across the globe. Also much of the content produced in the modern era is multimodal in nature, incorporating not only text, but diagrams, pictures, audio and video. Hence technologies such as speech recognition also come in to play. Yet due to the imperfect nature of these technologies, the experience of the user interacting with different modalities needs to be carefully considered. A variety of cultural and contextual factors can also influence the success of the application. We examine the challenges in terms of requirements, design and evaluation and outline a research agenda.
Improving Crowdsourced Live Streaming with Aggregated Edge Networks

Recent years have witnessed a dramatic increase of user-generated video services. In such user-generated video services, crowdsourced live streaming (e.g., Periscope, Twitch) has significantly challenged today's edge network infrastructure: today's edge networks (e.g., 4G, Wi-Fi) have limited uplink capacity support, making high-bitrate live streaming over such links fundamentally impossible. In this paper, we propose to let broadcasters (i.e., users who generate the video) upload crowdsourced video streams using aggregated network resources from multiple edge networks. There are several challenges in the proposal: First, how to design a framework that aggregates bandwidth from multiple edge networks? Second, how to make this framework transparent to today's crowdsourced live streaming services? Third, how to maximize the streaming quality for the whole system? We design a multi-objective and deployable bandwidth aggregation system BASS to address these challenges: (1) We propose an aggregation framework transparent to today's crowdsourced live streaming services, using an edge proxy box and aggregation cloud paradigm; (2) We dynamically allocate geo-distributed cloud aggregation servers to enable MPTCP (i.e., multi-path TCP), according to location and network characteristics of both broadcasters and the original streaming servers; (3) We maximize the overall performance gain for the whole system, by matching streams with the best aggregation paths.
USE OF WEATHER RADAR WITH LUMPED PARAMETER HYDROLOGIC MODELS

Lumped parameter hydrologic models are frequently used for operational streamflow forecasting in the United States. With the deployment of the Weather Surveillance Radar 1988 Doppler (WSR88D), many hydrologists will use radar-rainfall data as input to these models. WSR-88D precipitation products can be used in a variety of ways (Shedd and Fulton, 1993; Lindsey, 1993). In this paper, we examine two approaches. Runoff simulations based on an existing lumped parameter model, using mean areal precipitation as input, are compared to those based on a reformulated model, which attempts to better utilize the information available from weather radars by including the spatial variability of rainfall over the land segment area. The effect of precipitation sampling on model parameter calibration is also examined.
Isoform Composition of Connexin Channels Determines Selectivity among Second Messengers and Uncharged Molecules*

Intercellular connexin channels (gap junction channels) have long been thought to mediate molecular signaling between cells, but the nature of the signaling has been unclear. This study shows that connexin channels from native tissue have selective permeabilities, partially based on pore diameter, that discriminate among cytoplasmic second messenger molecules. Permeability was assessed by measurement of selective loss/retention of tracers from liposomes containing reconstituted connexin channels. The tracers employed were tritiated cyclic nucleotides and a series of oligomaltosaccharides derivatized with a small uncharged fluorescent moiety. The data define different size cut-off limits for permeability through homomeric connexin-32 channels and through heteromeric connexin-32/connexin-26 channels. Connexin-26 contributes to a narrowed pore. Both cAMP and cGMP were permeable through the homomeric connexin-32 channels. cAMP was permeable through only a fraction of the heteromeric channels. Surprisingly, cGMP was permeable through a substantially greater fraction of the heteromeric channels than was cAMP. The data suggest that isoform stoichiometry and/or arrangement within a connexin channel determines whether cyclic nucleotides can permeate, and which ones. This is the first evidence for connexin-specific selectivity among biological signaling molecules.
Radiation Dosimetry and Biodistribution in Monkey and Man of 11C-PBR28: A PET Radioligand to Image Inflammation

11C-PBR28 ([methyl-11C]N-acetyl-N-(2-methoxybenzyl)-2-phenoxy-5-pyridinamine) is a recently developed radioligand to image peripheral benzodiazepine receptors (PBRs) in brain. The aim of this study was to estimate the human radiation doses of 11C-PBR28 based on biodistribution data in monkeys and humans. In addition, we scanned 1 human subject who fortuitously behaved as if he lacked the PBR binding protein. Methods: Whole-body PBR images were acquired after intravenous bolus administration of 11C-PBR28 in 7 healthy humans (651 ± 111 MBq) and 2 rhesus monkeys (370 ± 59.9 MBq). One monkey was scanned after receptor blockade with PK 11195 (10.7 mg/kg intravenously). Results: For typical subjects (subjects 1–6), the 3 organs with highest exposure were those with the high PBR densities (kidneys, spleen, and lungs), and the effective dose was 6.6 μSv/MBq. The unusual subject (subject 7) had 60%–90% less uptake in these 3 organs, resulting in 28% lower effective dose. The activity in the baseline monkey scans was greater than that in humans for organs with high PBR densities. For this reason, the human effective dose was overestimated by 60% with monkey biodistribution data. The monkey with receptor blockade had an overall distribution qualitatively similar to that of the unusual human subject (subject 7), with decreased exposure to lungs, kidney, and spleen. Conclusion: The effective dose of 11C-PBR28 was modest and was similar to that of several other 11C-radioligands. Lack of receptor binding in the unusual human subject and in the monkey with receptor blockade decreased exposure to organs with high PBR densities and enhanced uptake in excretory and metabolic pathways.
Validation of the Small Animal Biospace Gamma Imager Model Using GATE Monte Carlo Simulations on the Grid

Monte Carlo simulations are nowadays widely used in the field of nuclear medicine. They are valuable for accurately reproducing experimental data, but at the expense of a long computing time. An efficient solution for shorter elapsed time was recently proposed: grid computing. The aim of this work is to validate a Monte Carlo simulation of the Biospace small animal γ Imager and to confirm the usefulness of grid computing for such a study. Simulated data obtained by the validated model of the gamma camera will enable to investigate new algorithms such as scatter and attenuation correction, and reconstruction methods. Good matches between measured and simulated data were achieved and a crunching factor as high as 70 was achieved on a campus grid.
ReaDDy - A Software for Particle-Based Reaction-Diffusion Dynamics in Crowded Cellular Environments

We introduce the software package ReaDDy for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution. In contrast to other particle-based reaction kinetics programs, ReaDDy supports particle interaction potentials. This permits effects such as space exclusion, molecular crowding and aggregation to be modeled. The biomolecules simulated can be represented as a sphere, or as a more complex geometry such as a domain structure or polymer chain. ReaDDy bridges the gap between small-scale but highly detailed molecular dynamics or Brownian dynamics simulations and large-scale but little-detailed reaction kinetics simulations. ReaDDy has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics.
Language learners’ representations of Spanish-speaking countries: How can they inform language pedagogy?

A number of studies have focused on language learners’ images of Spain and Spanishspeaking countries, however, none of these investigations was conducted in an Asian educational context. The current study has addressed this gap in research literature. It investigated not only representations but also salience and favourability of students’ images of the target language countries, which has not been done in earlier studies. The respondents were 31 beginner learners of Spanish. Firstly, they were asked to write images that they have about Spain; secondly, they were asked to write the names of Spanish-speaking countries that they know and provide several images for each of these countries. In addition, the students were asked to assign a favourability rating to each of the images in their lists. The findings revealed that the language learners’ images of Spain were multifarious and had a richer structure compared to the representations of Latin American countries. Despite this difference, students had predominantly positive attitudes toward Spanish-speaking countries. The article concludes by discussiong how language learners’ representations of a target language country can inform language pedagogy and offers some practical suggestions.
Origin and Loss of Nested LRRTM/α-Catenin Genes during Vertebrate Evolution

Leucine-rich repeat transmembrane neuronal proteins (LRRTMs) form in mammals a family of four postsynaptic adhesion proteins, which have been shown to bind neurexins and heparan sulphate proteoglycan (HSPG) glypican on the presynaptic side. Mutations in the genes encoding LRRTMs and neurexins are implicated in human cognitive disorders such as schizophrenia and autism. Our analysis shows that in most jawed vertebrates, lrrtm1, lrrtm2, and lrrtm3 genes are nested on opposite strands of large conserved intron of α-catenin genes ctnna2, ctnna1, and ctnna3, respectively. No lrrtm genes could be found in tunicates or lancelets, while two lrrtm genes are found in the lamprey genome, one of which is adjacent to a single ctnna homolog. Based on similar highly positive net charge of lamprey LRRTMs and the HSPG-binding LRRTM3 and LRRTM4 proteins, we speculate that the ancestral LRRTM might have bound HSPG before acquiring neurexins as binding partners. Our model suggests that lrrtm gene translocated into the large ctnna intron in early vertebrates, and that subsequent duplications resulted in three lrrtm/ctnna gene pairs present in most jawed vertebrates. However, we detected three prominent exceptions: (1) the lrrtm3/ctnna3 gene structure is absent in the ray-finned fish genomes, (2) the genomes of clawed frogs contain ctnna1 but lack the corresponding nested (lrrtm2) gene, and (3) contain lrrtm3 gene in the syntenic position but lack the corresponding host (ctnna3) gene. We identified several other protein-coding nested gene structures of which either the host or the nested gene has presumably been lost in the frog or chicken lineages. Interestingly, majority of these nested genes comprise LRR domains.
A bio-inspired model for color image segmentation

To segment an object from its background image for advanced vision processing, this article presents a novel bio-inspired framework for image segmentation in complex nature scenes, which is a hierarchical system that mimics the organization of layered early visual area in primate visual cortex. The proposed methodology consists of two typical stages: the first stage is a parallel modular structure including three segmenting operators based on color feature, form feature and texture feature, each of which solves the segmentation problem independently for the same input. They implement the similar computing as the parvocellular (P-cell), the magnocellular (M-cell) and koniocellular (K-cell) pathway in lateral geniculate nucleus (LGN) from the retina to the primary visual cortex. Then, a fusion operation, multiple feature fusion segmentation (MFFS), integrates these three feature segmentations together through the backpropagation neuron network (BPNN) in the last stage, which simulates the operation of area following the LGN in primary visual cortex. The proposed approach is applied to several segmentation experiments of many single objects in clustering conditions, the result shows that the approach is capable of competing with state-of-the-art systems.
Food hazard event extraction based on news and social media: A preliminary work

Detecting and disseminating food hazard information is a critical task that directly affects the public health. In spite of its importance, however, few systems are developed to automatically gather and analyze food hazard information. In this paper, we introduce our preliminary work to build such system. Our final system aims to detect and extract food hazard event from the live data shared on the Web. We defined information template for food hazard event. Then we used the template to extract informative keywords from the website of Ministry of Food and Drug Safety, the governmental organization responsible for ensuring food safety in Korea. We explain our work process, considerations, as well as our future work to implement our system.
Arnoldi method for the model reduction of second-orer structural dynamical systems

In this paper we consider the reduction of second-order dyna mical systems with multiple inputs and multiple outputs (MIMO) arising in the numerical simulation of mechanical st ructures. In commercial software for the kind of application considered here, modal reduction is commonly used to ob tain a reduced system with good approximation abilities of the original transfer function in the lower frequency ran ge. In recent years new methods to reduce dynamical systems based on (block) versions of Krylov subspace methods em erged. This work concentrates on the reduction of second-order MIMO systems by the global Arnoldi method, an e ffici nt extension of the standard Arnoldi algorithm for MIMO systems. In particular, a new model reduction algor ithm for second order MIMO systems is proposed which automatically generates a reduced system of given ord er approximating the transfer function in the lower range of frequencies. It is based on the global Arnoldi method, det ermines the expansion points iteratively and the number of moments matched per expansion point adaptively. Numeric al examples comparing our results to modal reduction and reduction via the block version of the rational Arnoldi m ethod are presented.
A Platform-Based Software Design Methodology for Embedded Control Systems: An Agile Toolkit

A discrete control system, with stringent hardware constraints, is effectively an embedded real-time system and hence requires a rigorous methodology to develop the software involved. The development methodology proposed in this paper adapts agile principles and patterns to support the building of embedded control systems, focusing on the issues relating to a system's constraints and safety. Strong unit testing, to ensure correctness, including the satisfaction of timing constraints, is the foundation of the proposed methodology. A platform-based design approach is used to balance costs and time-to-market in relation to performance and functionality constraints. It is concluded that the proposed methodology significantly reduces design time and costs, as well as leading to better software modularity and reliability.
RSVP policy control using XACML

This work proposes a XML-based framework for distributing and enforcing RSVP access control policies, for RSVP-aware application servers. Policies are represented by extending XACML, the general purpose access control language proposed by OASIS. Because RSVP is a specific application domain, it is not directly supported by the XACML standard. Hence, this work defines the XACML extensions required for representing and transporting the RSVP access control policy information. The XACML-based framework is proposed as an alternative to the IETF PCIM-based approach. Both approaches are compared in this paper.
Structure and DNA binding activity of the mouse condensin hinge domain highlight common and diverse features of SMC proteins

Structural Maintenance of Chromosomes (SMC) proteins are vital for a wide range of processes including chromosome structure and dynamics, gene regulation and DNA repair. Eukaryotes have three SMC complexes, consisting of heterodimeric pairs of six different SMC proteins along with several specific regulatory subunits. In addition to their other functions, all three SMC complexes play distinct roles in DNA repair. Cohesin (SMC1–SMC3) is involved in DNA double-strand break repair, condensin (SMC2–SMC4) participates in single-strand break (SSB) repair, and the SMC5–SMC6 complex functions in various DNA repair pathways. SMC proteins consist of N- and C-terminal domains that fold back onto each other to create an ATPase ‘head’ domain, connected to a central ‘hinge’ domain via long coiled-coils. The hinge domain mediates dimerization of SMC proteins and binds DNA, but it is not clear to what purpose this activity serves. We studied the structure and function of the condensin hinge domain from mouse. While the SMC hinge domain structure is largely conserved from prokaryotes to eukaryotes, its function seems to have diversified throughout the course of evolution. The condensin hinge domain preferentially binds single-stranded DNA. We propose that this activity plays a role in the SSB repair function of the condensin complex.
Worldwide Influenza Surveillance through Twitter

We evaluate the performance of Twitter-based influenza surveillance in ten English-speaking countries across four continents. We find that tweets are positively correlated with existing surveillance data provided by government agencies in these countries, with r values ranging from . 37–. 81. We show that incorporating Twitter data into a strong autoregressive baseline reduces mean squared error in 80 to 100 percent of locations depending on the lag, with larger improvements when reporting delays are longer.