Miracle-dz/UniFAR-FTUs huggingface dataset:
I Love Your Book, but I Love My Version More: Fanfiction in the English Language Arts Classroom

A t midnight on August 2, 2008, the final installment of Stephenie Meyer’s Twilight Series, Breaking Dawn, hit bookstore shelves across the globe. But, regardless of whether Bella would chose Jacob Black or Edward Cullen as her final paramour, or whether she would become a vampire or remain mortal in Meyer’s grand finale, millions of children and teens had already finished the novel. For months they had been formulating extensions of Bella’s story—alternative narratives, new twists, and their own endings. Many of them, after finishing the final book . again . pressed their computers’ power buttons, connected to the Internet, navigated to their favorite websites, and began typing their own versions of what might have happened or what they hoped would happen to bring the series to its conclusion. They returned to what has become a favorite literary destination for so many young people: fan fiction, or fanfic. Fan fiction is just what the name implies: it is fiction written by fans, often teenagers, of novels, movies, television, or other media. This fiction is based in the worlds created by the authors, but young fans extend, elaborate, or appropriate the text for their own purposes. Fanfics come in many different recognized genres, and some innovative, even multimodal forms, as well. The world of fan fiction is inhabited by a community of authors and readers, where critics argue that the point of intersection between reader and text is the only true place where the work “exists” (Keesey 128). English language arts teachers can tap into this community and intersection to engage learners on their own virtual turf. Although fan fiction can be written about a vast array of popular and classic novels, the fiction arising from the wildly popular Twilight series by Stephenie Meyer works especially well for introducing how this genre can be used in the classroom. Beware, “spoilers” for the Twilight series are necessary to best illuminate this sensation.
Txupito: An interactor component model for ambient HCI

In this paper, we describe the Txupito interactor model. Nowadays, application contents are accessible on a wide variety of devices such as laptops, tablets and smartphones but the heterogeneity of such devices does not help programmers to elaborate ambient interactive applications adapted to each device. Indeed, users do not interact in the same way on a tablet, a laptop or a smartphone. Furthermore the design of cooperative HCI (Human Computer Interface) remains a very complex task especially in an ambient and heterogeneous environment. In this paper, we propose a multimodal mobile interactor model, called Txupito, and a set of composition operators as a way to achieve interactions with hardware in a distributed and cooperative way.
Multidimensional Schemas Quality Assessment

A data warehouse is a database focused on decision making. It is built separately from the transactional (OLTP) databases of the enterprise, although it is partly fed from transactional data. Data warehouses are typically accessed by decision makers using OLAP tools, based on a specific, multidimensional representation of data. Considering the strategic importance of data warehouses, the quality of these systems is crucial. Moreover, since OLAP tool users directly access multidimensional schemas, multidimensional schemas quality is a key aspect of data warehouse quality. This paper focuses on the quality of multidimensional schemas. We present the underlying multidimensional model and the multidimensional schemas quality evaluation framework, which considers three views corresponding to three types of users: the specification view (data warehouse designer), the usage view (decision maker) and the implementation view (data warehouse developer). Concentrating on the specification view, we present and exemplify criteria and metrics pertaining to this view.
Analysis and Design of programmatic Interfaces for Integration of Diverse Web Contents

The technology that integrates various types of Web contents to build a new Web application through end-user programming is widely used nowadays. However, the Web contents do not have a uniform interface for accessing the data and computation. Most of the general Web users access information on the Web through applications until now. Hence, designing a uniform and flexible programmatic interface for integration of different Web contents is unavoidable. In this paper, we propose an approach that can be used to analyze Web applications automatically and reuse the information of Web applications through the programmatic interface we designed. Our approach can support the flexible integration of Web applications, Web services and Web feeds. In our experiments, we use a large number of Web pages from different types of Web applications and achieve the integration by the proposed programmatic interfaces. The experimental results show that our approach brings to the end-users a flexible and user-friendly programming environment.
Efficient Method for POI/ROI Discovery Using Flickr Geotagged Photos

In the era of big data, ubiquitous Flickr geotagged photos have opened a considerable opportunity for discovering valuable geographic information. Point of interest (POI) and region of interest (ROI) are significant reference data that are widely used in geospatial applications. This study aims to develop an efficient method for POI/ROI discovery from Flickr. Attractive footprints in photos with a local maximum that is beneficial for distinguishing clusters are first exploited. Pattern discovery is combined with a novel algorithm, the spatial overlap (SO) algorithm, and the naming and merging method is conducted for attractive footprint clustering. POI and ROI, which are derived from the peak value and range of clusters, indicate the most popular location and range for appreciating attractions. The discovered ROIs have a particular spatial overlap available which means the satisfied region of ROIs can be shared for appreciating attractions. The developed method is demonstrated in two study areas in Taiwan: Tainan and Taipei, which are the oldest and densest cities, respectively. Results show that the discovered POI/ROIs nearly match the official data in Tainan, whereas more commercial POI/ROIs are discovered in Taipei by the algorithm than official data. Meanwhile, our method can address the clustering issue in a dense area.
Interactional Context for Mobile Applications

Mobility and ubiquity bring about an increasing engagement in the concept of context. Environmental context such as location or light have been studied for a while, however little research has been done on interactional context – context that evolves in the course of interaction. This paper presents results of an empirical study conducted in order to assess the interactional context. The empirical study is a major part of an ongoing research project, which is concerned with developing a context-of-use model for users’ interaction with mobile devices. The paper dicusses the findings, reports the results, and summarises the implications for future development. It argues that the interactional context plays a major role in mobile communication settings. It underpins the necessity for a socially grounded research approach as well as empirical evaluations in order to develop applications, which are unobtrusive and better support users in accomplishing their everyday tasks.
The king cobra genome reveals dynamic gene evolution and adaptation in the snake venom system

Significance Snake venoms are toxic protein cocktails used for prey capture. To investigate the evolution of these complex biological weapon systems, we sequenced the genome of a venomous snake, the king cobra, and assessed the composition of venom gland expressed genes, small RNAs, and secreted venom proteins. We show that regulatory components of the venom secretory system may have evolved from a pancreatic origin and that venom toxin genes were co-opted by distinct genomic mechanisms. After co-option, toxin genes important for prey capture have massively expanded by gene duplication and evolved under positive selection, resulting in protein neofunctionalization. This diverse and dramatic venom-related genomic response seemingly occurs in response to a coevolutionary arms race between venomous snakes and their prey. Snakes are limbless predators, and many species use venom to help overpower relatively large, agile prey. Snake venoms are complex protein mixtures encoded by several multilocus gene families that function synergistically to cause incapacitation. To examine venom evolution, we sequenced and interrogated the genome of a venomous snake, the king cobra (Ophiophagus hannah), and compared it, together with our unique transcriptome, microRNA, and proteome datasets from this species, with data from other vertebrates. In contrast to the platypus, the only other venomous vertebrate with a sequenced genome, we find that snake toxin genes evolve through several distinct co-option mechanisms and exhibit surprisingly variable levels of gene duplication and directional selection that correlate with their functional importance in prey capture. The enigmatic accessory venom gland shows a very different pattern of toxin gene expression from the main venom gland and seems to have recruited toxin-like lectin genes repeatedly for new nontoxic functions. In addition, tissue-specific microRNA analyses suggested the co-option of core genetic regulatory components of the venom secretory system from a pancreatic origin. Although the king cobra is limbless, we recovered coding sequences for all Hox genes involved in amniote limb development, with the exception of Hoxd12. Our results provide a unique view of the origin and evolution of snake venom and reveal multiple genome-level adaptive responses to natural selection in this complex biological weapon system. More generally, they provide insight into mechanisms of protein evolution under strong selection.
Efficient Region-Based Memory Management for Resource-limited Real-Time Embedded Systems.

This paper presents a simple and eﬃcient static analysis algorithm, combined with a region allocation policy for real-time embedded Java applications. The goal of this work is to provide a static analysis mechanism eﬃcient enough to be integrated in an assisted-development environment, and to implement region-based memory management primitives suited for resource-limited platforms such as smart cards.
Software's future: managing evolution

In his essay, Ed Yourdon expresses, justifies, and leaves unresolved two well-founded questions: What is the future of software? What does the future hold for the software professional? His prognosis is evasive, incomplete, and unsatisfying: the future will be good for some, not so for others. Given Yourdon's extensive experience in the real world of computer usage, as proven by the problems he has observed, it is easy to see why he feels that soft-ware's future is uncertain. But he does not point to a solution to this uncertainty, nor does he indicate what can be done to achieve the best possible outcome for software professionals. More importantly, Yourdon's analysis does not indicate what should be done to ensure the security, well being, and survival of society, which depends increasingly on software. For more than a decade now, there have been those in the software engineering community who have accepted that the need to continually change and evolve software is a fact-a fact addressed through activity that is planned, executed, and controlled by humans. Thus, the software development and maintenance processes, which I prefer to unify and call software evolution, are key to managing computerization. In my view it is key to our survival in this computer age.
Invented antonyms: Esperanto as a semantic lab

This paper uses Esperanto—a constructed language with transparent morphology but rich semantic-pragmatic components—to study antonymy and polarity. We investigate the distribution of the Esperanto antonymy morpheme ‘mal-’ (as in, for instance, ‘mal-alta’: antonym-tall, short) in a 4.3 million-word corpus, Tekstaro, and use it as an empirical basis to assess different theories of negative antonyms. Our methodology consists in investigating the extent to which the antonymy morpheme ‘mal-’, which we take to denote negative polarity, bears the linguistic features predicted by traditional linguistic tests (such as incompatibility with measure and ratio phrases and low likelihood of nominalisation).
Parallelization of belief propagation method on embedded multicore processors for stereo vision

Markov random field models provide a robust formulation of low-level vision problems. Among the problems, stereo vision remains the most investigated field. The belief propagation provides accurate result in stereo vision problems, however, the algorithm remains slow for practical use. In this paper we examine and extract the parallelisms in the belief propagation method for stereo vision on multicore processors. The results show that with parallelization exploration on multi-core processors, the belief propagation algorithm can have a 13.5 times speedup compared to the single processor implementation. The experimental results also indicate that the parallelized belief propagation algorithm on multicore processors is able to provide a frame rate in 6 frames per second.
Specific Genomic Regions Are Differentially Affected by Copy Number Alterations across Distinct Cancer Types, in Aggregated Cytogenetic Data

Background Regional genomic copy number alterations (CNA) are observed in the vast majority of cancers. Besides specifically targeting well-known, canonical oncogenes, CNAs may also play more subtle roles in terms of modulating genetic potential and broad gene expression patterns of developing tumors. Any significant differences in the overall CNA patterns between different cancer types may thus point towards specific biological mechanisms acting in those cancers. In addition, differences among CNA profiles may prove valuable for cancer classifications beyond existing annotation systems. Principal Findings We have analyzed molecular-cytogenetic data from 25579 tumors samples, which were classified into 160 cancer types according to the International Classification of Disease (ICD) coding system. When correcting for differences in the overall CNA frequencies between cancer types, related cancers were often found to cluster together according to similarities in their CNA profiles. Based on a randomization approach, distance measures from the cluster dendrograms were used to identify those specific genomic regions that contributed significantly to this signal. This approach identified 43 non-neutral genomic regions whose propensity for the occurrence of copy number alterations varied with the type of cancer at hand. Only a subset of these identified loci overlapped with previously implied, highly recurrent (hot-spot) cytogenetic imbalance regions. Conclusions Thus, for many genomic regions, a simple null-hypothesis of independence between cancer type and relative copy number alteration frequency can be rejected. Since a subset of these regions display relatively low overall CNA frequencies, they may point towards second-tier genomic targets that are adaptively relevant but not necessarily essential for cancer development.
An automated initialization system for robust model-based segmentation of lungs in CT data

In this paper we study the feasibility of an automated initialization system for a robust model-based lung segmentation approach. The lung segmentation method consists of a robust active shape model (RASM) matching stage followed by an optimal surface ﬁnding step. The RASM needs to be initialized in rough proximity to the target structure for achieving good segmentation results. For this purpose we employ a feature-based alignment (FBA) method to predict three landmark points (lung apex and carina). These landmark points are subsequently used to calculate initial model parameters. The approach was evaluated on a di-verse set of 98 CT scans of normal and diseased lungs by comparison to an independent reference standard. For segmentation results based on the new initialization approach, the mean and standard deviation of the Dice coeﬃcient was 0 . 976 ± 0 . 025. In comparison, the Dice coeﬃcient of lung segmentations based on the previously utilized initialization method was 0 . 971 ± 0 . 040. The new RASM initialization approach is 3-times faster than the previously utilized method and can be expanded by including additional landmarks.
On What Manifold do Diffusion Tensors Live?

Diﬀusion tensor imaging has become an important research and clinical tool, owing to its unique ability to infer microstructural properties of living tissue. Increased use has led to a demand for statistical tools to analyze diﬀusion tensor data and perform, for example, conﬁdence estimates, ROI analysis, and group comparisons. A ﬁrst step towards developing a statistical framework is establishing the basic notion of distance between tensors. We investigate the properties of two previously proposed metrics that deﬁne a Riemannian manifold: the aﬃne-invariant and Euclidean metrics. We ﬁnd that the Euclidean metric is more appropriate for intra-voxel comparisons, and suggest that a context-dependent metric may be required for inter-voxel comparisons.
Losing focus: goal displacement at an alternative newspaper in El Salvador

This study examines whether a Salvadoran alternative newspaper maintained its critical, independent, and alternative position after the country’s first leftist president was elected and the newspaper no longer was in opposition to the government. Via a content analysis and in-depth interviews that drove the content analysis, this study improves our understanding of ‘alternativeness’ in a non-US context. Using a theoretical lens founded on alternative media scholarship and sociology’s displacement theory to examine the newspaper’s radical purpose, the study found that once the left came into power after decades of rightist and authoritarian rule, the newspaper’s alternative mission and goals were displaced, becoming less radical and more propagandistic. Pro-government coverage increased and coverage of social movements, civil society, and other traditionally ‘alternative’ topics decreased. Journalists at the newspaper acknowledged the shift in goals and lessening of radical purpose, but clung to the newspaper’s ‘alternativeness’.
New Insights on Retrieval-Induced and Ongoing Memory Consolidation: Lessons from Arc

The mainstream view on the neurobiological mechanisms underlying memory formation states that memory traces reside on the network of cells activated during initial acquisition that becomes active again upon retrieval (reactivation). These activation and reactivation processes have been called “conjunctive trace. ” This process implies that singular molecular events must occur during acquisition, strengthening the connection between the implicated cells whose synchronous activity must underlie subsequent reactivations. The strongest experimental support for the conjunctive trace model comes from the study of immediate early genes such as c-fos, zif268, and activity-regulated cytoskeletal-associated protein. The expressions of these genes are reliably induced by behaviorally relevant neuronal activity and their products often play a central role in long-term memory formation. In this review, we propose that the peculiar characteristics of Arc protein, such as its optimal expression after ongoing experience or familiar behavior, together with its versatile and central functions in synaptic plasticity could explain how familiarization and recognition memories are stored and preserved in the mammalian brain.
Updates on XML documents and schemas

In a dynamic and heterogeneous world as the Web, the need often arises to update XML data, as well as their structures, to adhere to new domain requirements. Updates may break compliance of data to schemas, and updates at schema level may in addition require to adapt associated documents to the new schema. Moreover, emerging application contexts in which updates come from different sources, such as collaborative editing, versioning, cloud computing, and disconnected execution, are more and more relevant. The main goals of this thesis are: (i) to support data and schema updates as an integrated process, investigating the mutual implications of updating either data or schema on the other, (ii) to develop a flexible framework for dynamically reasoning on XML updates, applicable in different contexts and (iii) to study provenance in the context of our XML update framework, introducing the possibility of storing and querying each individual update information to trace the data lineage.
DINASTI: Dialogues with a Negotiating Appointment Setting Interface

This paper describes the DINASTI (DIalogues with a Negotiating Appointment SeTting Interface) corpus, which is composed of 1734 dialogues with the French spoken dialogue system NASTIA (Negotiating Appointment SeTting InterfAce). NASTIA is a reinforcement learning-based system. The DINASTI corpus was collected while the system was following a uniform policy. Each entry of the corpus is a system-user exchange annotated with 120 automatically computable features.The corpus contains a total of 21587 entries, with 385 testers. Each tester performed at most five scenario-based interactions with NASTIA. The dialogues last an average of 10.82 dialogue turns, with 4.45 reinforcement learning decisions. The testers filled an evaluation questionnaire after each dialogue. The questionnaire includes three questions to measure task completion. In addition, it comprises 7 Likert-scaled items evaluating several aspects of the interaction, a numerical overall evaluation on a scale of 1 to 10, and a free text entry. Answers to this questionnaire are provided with DINASTI. This corpus is meant for research on reinforcement learning modelling for dialogue management.
Towards Tight Bounds for the Streaming Set Cover Problem

We consider the classic Set Cover problem in the data stream model. For n elements and m sets (m ≥ n) we give a O(1/δ)-pass algorithm with a strongly sub-linear ~O(mnδ) space and logarithmic approximation factor. This yields a significant improvement over the earlier algorithm of Demaine et al. [10] that uses exponentially larger number of passes. We complement this result by showing that the tradeoff between the number of passes and space exhibited by our algorithm is tight, at least when the approximation factor is equal to 1. Specifically, we show that any algorithm that computes set cover exactly using ({1 over 2δ}-1) passes must use ~Ω(mnδ) space in the regime of m=O(n). Furthermore, we consider the problem in the geometric setting where the elements are points in R2 and sets are either discs, axis-parallel rectangles, or fat triangles in the plane, and show that our algorithm (with a slight modification) uses the optimal ~O(n) space to find a logarithmic approximation in O(1/δ) passes. Finally, we show that any randomized one-pass algorithm that distinguishes between covers of size 2 and 3 must use a linear (i.e., Ω(mn)) amount of space. This is the first result showing that a randomized, approximate algorithm cannot achieve a space bound that is sublinear in the input size. This indicates that using multiple passes might be necessary in order to achieve sub-linear space bounds for this problem while guaranteeing small approximation factors.