Miracle-dz/UniFAR-FTUs huggingface dataset:
The relationship between writing anxiety, writing selfefficacy, and Spanish EFL students’ use of metacognitive writing strategies: a case study

The composing process of a written text is one of the most challenging tasks encountered by foreign language learners. Mastering writing depends on numerous aspects, being the use of metacognitive writing strategies a paramount factor in the process. However, writing metacognition is not isolated from other factors, and emotional constructs have a deep influence both on the use of strategies and on the final written outcome. In this article, a case study is undertaken among six upper-secondary-school Spanish EFL students in order to explore, identify, and analyze the unique relationships existing between the use of metacognitive writing strategies, writing anxiety and writing self-efficacy, observing also how these three factors influence students’ writing performance. To do so, participants were invited to take part in a think-aloud protocol while writing a text in English. Results were cross-validated with students’ completion of a questionnaire designed drawing on previous literature (O’Neil and Abedi 1996; Cheng 2004; Jones 2008; Stewart et al. 2015; Ho 2016) to measure the three factors. Participants’ responses to both research instruments showed a positive correlation between writing metacognition and writing self-efficacy. On the other hand, these two factors were reported to be negatively correlated with students’ level of writing anxiety. Findings also suggest that think-aloud protocols might have flaws when measuring emotional constructs. Thus, EFL instruction should aim at reducing both personal and environmental factors that may cause writing anxiety and decrease learners’ self-efficacy, ultimately enhancing students’ writing skills.
In vitro development of haploid mouse embryos produced by bisection of one-cell fertilized eggs

F1(CBA × C57BL'10) mouse eggs originating from spontaneous or induced ovulation and fertilized by CBA-T6T6 or PO spermatozoa were bisected with a glass needle into halves each containing a pronucleus. This technique offers a unique opportunity of producing both androgenetic and gynogenetic haploid embryos from one egg. Out of 600 operated eggs, in 406 (67·7%) both halves survived. During 96 h of culture in vitro the fragments were inspected once daily and finally examined in air-dried preparations. Eighty-seven per cent of halves underwent first cleavage but their further development was to a large extent affected by extrinsic factors connected with experimental procedure (mainly by suboptimal and variable culture conditions) and by the origin of eggs (those from spontaneous ovulation being superior). For this reason developmental capabilities of egg halves were assessed in a selected group of pairs in which at least one partner reached the stage of four or more blastomeres. The observed ratio between pairs with both or only one sister embryo developing successfully suggests that androgenetic embryos carrying Y rather than X chromosome can cleave twice but do not survive beyond 4-cell stage. None of the metaphase plates from older embryos contained a Y chromosome. These observations imply that the X chromosome is genetically active during early cleavage and that a full haploid set is required for preimplantation development to be completed. Formation of blastocysts varied from batch to batch, with an average of 12·8% and maximal incidence of 29·5% . In 34 pairs both fragments developed beyond the 4-cell stage but in only one case did both form blastocysts. Haploid blastocysts were composed of 27 cells on average which was about a half of the number of cells in control diploid zona-free whole eggs. Ten out of 51 embryos with metaphase plates proved to be haploid/diploid mosaics.
Informational Cascades Elicit Private Information * by

Informational Cascades Elicit Private Information* by Olivier Gossner and Nicolas Melissas We introduce cheap talk in a dynamic investment model with information externalities. We first show how social learning adversely affects the credibility of cheap talk messages. Next, we show how an informational cascade makes thruthtelling incentive compatible. A separating equilibrium only exists for high surplus projects. Both an investment subsidy and an investment tax can increase welfare. The more precise the sender’s information, the higher her incentives to truthfully reveal her private information.
Distributed Compressed Estimation Based on Compressive Sensing

This letter proposes a novel distributed compressed estimation scheme for sparse signals and systems based on compressive sensing techniques. The proposed scheme consists of compression and decompression modules inspired by compressive sensing to perform distributed compressed estimation. A design procedure is also presented and an algorithm is developed to optimize measurement matrices, which can further improve the performance of the proposed distributed compressed estimation scheme. Simulations for a wireless sensor network illustrate the advantages of the proposed scheme and algorithm in terms of convergence rate and mean square error performance.
IMPACT OF MOBILE EMAIL IN CORPORATE ENVIRONMENTS

Mobile email is the extension of Internet email on mobile devices. It is a recent phenomenon, and has not been researched broadly yet. This paper provides a contribution to fill this gap and investigates the domestication of mobile email in Swiss companies. The research showed that mobile email is becoming an important tool, in particular for mobile workers. It enables an efficient use of short down times; it is used for communication, coordination, collaboration, and even for dealing with complex matters on the move. Due to an increased dynamism in communication, mobile email results in improved relationships with customers, co-workers and supervisors.
An Automata-based algorithm for description logics around SRIQ

In this paper we use automata-theoretic techniques to tightly characterize the worst-case complexity of the knowledge base satisfiability problem for the very expressive Description Logics (DLs) ALCQIb+reg and SRIQ. The logic ALCQIb + reg extends ALC with qualified number restrictions, inverse roles, safe Boolean role expressions, regular expressions over roles, and concepts of the form ∃P.Self in the style of SRIQ, a well known DL closely related to the new Semantic Web Standard OWL 2. By reducing its knowledge base satisfiability problem to the emptiness test of an automaton on infinite trees, we show that all these additions do not increase the worst case complexity of ALC and provide a decision procedure for one of the most expressive DLs that have been shown to be decidable in exponential time. We also close the open question of the precise complexity of reasoning in SRIQ, exploiting a reduction from the SRIQ knowledge base satisfiability problem into the ALCQIb+reg one.
SAR Image Despeckling Using Refined Lee Filter

The presence of speckle noise in Synthetic Aperture Radar (SAR) images makes the interpretation of the contents difficult, thereby degrading the quality of the image. Therefore an efficient speckle noise removal technique needs to be sought. In this paper, we present a SAR image despeckling method known as Refined Lee Filter (RLF). The method is based on the well-known Lee filter. In this method the K-Nearest Neighbour (KNN) algorithm is employed to adjust the number of neighbour pixels used within the sliding window. Simulation results obtained from the performance evaluation metrics used showed that the proposed method improved the performance of the original Lee filter when they were both used to despeckle standard test images contaminated with speckle noise and SAR images.
Amygdalar and Hippocampal Theta Rhythm Synchronization During Fear Memory Retrieval

The amygdalohippocampal circuit plays a pivotal role in Pavlovian fear memory. We simultaneously recorded electrical activity in the lateral amygdala (LA) and the CA1 area of the hippocampus in freely behaving fear-conditioned mice. Patterns of activity were related to fear behavior evoked by conditioned and indifferent sensory stimuli and contexts. Rhythmically synchronized activity at theta frequencies increased between the LA and the CA1 after fear conditioning and became significant during confrontation with conditioned fear stimuli and expression of freezing behavior. Synchronization of theta activities in the amygdalohippocampal network represents a neuronal correlate of conditioned fear, apt to improve neuronal communication during memory retrieval.
Teager energy based blood cell segmentation

A new method for fast and simple segmentation of peripheral blood smears using the Teager energy operator (TEO) is presented. The two-part algorithm efficiently segments leucocytes present in the smear into nucleus and cytoplasm. The local mean weighted high pass filtering property of the Teager energy operator is used to identify and distinguish the nucleus of white blood cells. Cytoplasm present in the white blood cells is segmented using selective mathematical morphology. Experimental results are shown for a blood smear containing multiple nuclei. It was observed that modified histogram developed using the TEO can efficiently segment even multiple nuclei. Experiments have been conducted to verify the accuracy of the proposed segmentation scheme for all the major types of leucocytes. Simulation results have shown that our algorithm segments nuclei effectively even at low percentage of impulse noise.
The quasi‐randomness of hypergraph cut properties

Let $\alpha_1,\ldots,\alpha_k$ satisfy $\sum_i\alpha_i=1$ and suppose a k‐uniform hypergraph on n vertices satisfies the following property; in any partition of its vertices into k sets $A_1,\ldots,A_k$ of sizes $\alpha_1n,\ldots,\alpha_kn$, the number of edges intersecting $A_1,\ldots,A_k$ is (asymptotically) the number one would expect to find in a random k‐uniform hypergraph. Can we then infer that H is quasi‐random? We show that the answer is negative if and only if $\alpha_1=\cdots=\alpha_k=1/k$. This resolves an open problem raised in 1991 by Chung and Graham [J AMS 4 (1991), 151–196].
Dynamics of charged particles in the radio emission region of pulsar magnetosphere

We consider the classical picture of three dimensional motion of charged particles in pulsar magnetosphere. We adopt a perturbative method to solve the equation of motion, and find the trajectory of particles as they move along the rotating dipolar magnetic field lines. Our aim is to study the influence of rotation on the pulsar radio emission by considering the constrained motion of particles along the open dipolar magnetic field lines. We find that the rotation induces a significant curvature into the particle trajectories. Our model predicts the intensity on leading side dominates over that of trailing side. We expect that if there is any curvature induced radio emission from the region close to the magnetic axis then it must be due to the rotation induced curvature. Our model predicts the radius-to-frequency mapping (RFM) in the conal as well as core emissions.
The Effect of Dependency Representation Scheme on Syntactic Language Modelling

There has been considerable work on syntactic language models and they have advanced greatly over the last decade. Most of them have used a probabilistic contextfree grammar (PCFG) or a dependency grammar (DG). In particular, DG has attracted more and more interest in the past years since dependency parsing has achieved great success. While much work has evaluated the effects of different dependency representations in the context of parsing, there has been relatively little investigation into them on a syntactic language model. In this work, we conduct the first assessment of three dependency representations on a transition-based dependency parsing language model. We show that the choice of dependency representation has an impact on overall performance from the perspective of language modelling.
Separate training for conditional random fields using co-occurrence rate factorization

Conditional Random Fields (CRFs) are undirected graphical models which are well suited to many natural language processing (NLP) tasks, such part-of-speech (POS) tagging and named entity recognition (NER). The standard training method of CRFs can be very slow for large-scale applications. As an alternative to the standard training method, piecewise training divides the full graph into pieces, trains them independently, and combines the learned weights at test time. But piecewise training does not scale well in the variable cardinality. In this paper we present separate training for undirected models based on the novel Co-occurrence Rate factorization (CR- F). Separate training is a local training method without global propagation. In contrast to directed markov models such as MEMMs, separate training is unaff ected by the label bias problem even it is a local normalized method. We do experiments on two NLP tasks, i.e., POS tagging and NER. Results show that separate training (i) is unaffected by the label bias problem; (ii) reduces the training time from weeks to seconds; and (iii) obtains competitive results to the standard and piecewise training on linear-chain CRFs. Separate training is a promising technique for scaling undirected models for natural language processing tasks. (More details can be found here: http://eprints.eemcs.utwente.nl/22600/)
Artificial Neural Network Analysis of DNA Microarray-based Prostate Cancer Recurrence

DNA microarray-based gene expression profiles have been established for a variety of adult cancers. This paper addresses application of an artificial neural network (ANN) with leave-one-out testsing and 8-fold cross-validation for analyzing DNA microarray data to identify genes predictive of recurrence after prostatectomy. Among 725 genes screened for ANN input, a 16-gene model resulted in 99-100% diagnostic sensitivity and specificity: DGCR5, FLJ10618, RIS1, PRO1855, ABCB9, AK057203, GOLGA5, HARS, AK024152, HEP27, PPIA, SNRPF, SULT1A3, SECTM1, EIF4EBP1, and S71435. Genes identified with ANN that are prognostic of prostate cancer recurrence may be either causal for prostate cancer or secondary to the disease. Nevertheless, the genes identified may be confirmed in the future to be markers of early detection and/or therapy.
ArcheOpterix: An extendable tool for architecture optimization of AADL models

For embedded systems quality requirements are equally if not even more important than functional requirements. The foundation for the fulfillment of these quality requirements has to be set in the architecture design phase. However, finding a suitable architecture design is a difficult task for software and system architects. Some of the reasons for this are an ever-increasing complexity of today's systems, strict design constraints and conflicting quality requirements. To simplify the task, this paper presents an extendable Eclipse-based tool, called ArcheOpterix, which provides a framework to implement evaluation techniques and optimization heuristics for AADL specifications. Currently, evolutionary strategies have been implemented to identify optimized deployment architectures with respect to multiple quality objectives and design constraints. Experiments with a set of initial deployment architectures provide evidence that the tool can successfully find architecture specifications with better quality.
Parents learning language together: The case of a bilingual parent group

ABSTRACT Diálogos is an English/Spanish parent group at a bilingual school in California that offers language classes to parents of varying socioeconomic and cultural backgrounds. Situated within Yosso’s (2005) model of community cultural wealth, this case study argues that parents positively evaluate Diálogos as a space that builds community through language learning, promotes bilingualism, and leverages Latino immigrant parents’ existing linguistic and social capital. As such, Diálogos challenges dominant discourses of English-only and deficit theorizing. The positive outcomes of this grassroots parent group has implications for bilingual education and parental involvement at schools.
Query word deletion prediction

Web search query logs contain traces of users' search modifications. One strategy users employ is deleting terms, presumably to obtain greater coverage. It is useful to model and automate term deletion when arbitrary searches are conjunctively matched against a small hand constructed collection, such as a hand-built hierarchy, or collection of high-quality pages matched with key phrases. Queries with no matches can have words deleted till a match is obtained. We provide algorithms which perform substantially better than the baseline in predicting which word should be deleted from a reformulated query, for increasing query coverage in the context of web search on small high-quality collections.
Prevalence and risk factors for obstructive sleep apnoea in Dar es Salaam , Tanzania

Background: Obstructive sleep apnoea (OSA) is a common cause of daytime sleepiness, a condition associated with accidents, antisocial behaviour, mood disturbances, cognitive dysfunctions and inefficiency at work. This study was carried out to determine the prevalence and risk factors for obstructive sleep apnoea in Dar es Salaam, Tanzania. Methods: Multistage random sampling of households was done. Eligible members were interviewed and underwent anthropometric measurements. Epworth sleepiness scale was used to asses one’s likelihood of daytime sleepiness. OSA was defined as the presence of 2 of the following: symptoms of obstructive sleep apnoea, a Body Mass Index (BMI) ≥ 28 kg/ m2 and a total Epworth score≥ 15. Results: A total of 1249 people were involved in the study. Of these, 65.2% were females. Night snoring was reported by 9.3% of the respondents. The prevalence of OSA was 11.5% (144/1249). OSA was significantly more common among females (12.9%) (p = 0.038) than males. OSA prevalence increased significantly with increasing age (p <0.001) and increasing BMI (pvalue < 0.001). Respondents with hypertension, central obesity and those who snored at night significantly presented with high prevalence of OSA, being 26.5%, 34% and 29.3%, respectively (pvalue <0.001 for each). OSA was found in 26.3% of diabetics (p= 0.042). The odds of OSA were significantly higher among females, OR (95% CI) = 2.0 (1.2-3.2), among age group 45-54 years, OR (95% CI) = 2.2 (1.1-4.3), among those with central obesity OR (95% CI) = 3.4 (2.15.4) and among night snorers OR (95% CI) = 2.8(1.7-4.6). Socio-economic status, cigarette smoking, alcohol consumption, hypertension and diabetes mellitus could not predict OSA. Conclusions: OSA is prevalent among residents of Dar es Salaam and significantly associated with age 45 years or older, female gender, high socioeconomic status, obesity and overweight and night snoring. Predictors of OSA were female gender, age above 45 years, central obesity, and night snoring. Clinicians should therefore actively look for OSA in patients with these characteristics.
Segmentation of Multiple Salient Closed Contours from Real Images

Using a saliency measure based on the global property of contour closure, we have developed a segmentation method which identifies smooth closed contours bounding objects of unknown shape in real images. The saliency measure incorporates the Gestalt principles of proximity and good continuity that previous methods have also exploited. Unlike previous methods, we incorporate contour closure by finding the eigenvector with the largest positive real eigenvalue of a transition matrix for a Markov process where edges from the image serve as states. Element (i, j) of the transition matrix is the conditional probability that a contour which contains edge j will also contain edge i. We show how the saliency measure, defined for individual edges, can be used to derive a saliency relation, defined for pairs of edges, and further show that strongly-connected components of the graph representing the saliency relation correspond to smooth closed contours in the image. Finally, we report for the first time, results on large real images for which segmentation takes an average of about 10 seconds per object on a general-purpose workstation.
Generation of test cases from functional requirements. A survey

: One of the major quality criteria of a software system is how well it fulfils the needs of users or customers. One technique to verify and improve the grade of fulfilment is system testing. System test cases might be derived from the requirements of the system under test. This paper presents the results of a survey among 13 approaches to drive the generation of test cases from functional requirements.
Computational Linkuistics : Content diffusion on the Web graph

We show that the probability of a word to appearin a Web document dependsonthepresenceof in documents pointing to . We backour claim using two experimentswhich deal with single wordandtwo wordqueriesfrom thequery log of a major commercialsearchengine and discussthe implicationsof the findings to LanguageModeling andInformation Retrieval. In LanguageModeling,we will proposethe useof a correctionfactor, , which indicateshow much more likely a word is to appearin a document given that anotherdocumentcontaining the sameword is linked to it. In InformationRetrieval, we suggestthe concept of a documentclosurewhich can be automaticallycomputedin orderto identify wordsthat arenot presentin a document, but by virtue of their presencein documentslinked to the document,shouldbe addedto theindex for it.
Predicting Bugs' Components via Mining Bug Reports

The number of bug reports in complex software increases dramatically. Now bugs are triaged manually, bug triage or assignment is a labor-intensive and time-consuming task. Without knowledge about the structure of the software, testers often specify the component of a new bug wrongly. Meanwhile, it is difficult for triagers to determine the component of the bug only by its description. We dig out the components of 28,829 bugs in Eclipse bug project have been specified wrongly and modified at least once. It results in these bugs have to be reassigned and delays the process of bug fixing. The average time of fixing wrongly-specified bugs is longer than that of correctly-specified ones. In order to solve the problem automatically, we use historical fixed bug reports as training corpus and build classifiers based on support vector machines and Na\"ive Bayes to predict the component of a new bug. The best prediction accuracy reaches up to 81.21% on our validation corpus of Eclipse project. Averagely our predictive model can save about 54.3 days for triagers and developers to repair a bug. Keywords: bug reports; bug triage; text classification; predictive model