Miracle-dz/UniFAR-FTUs huggingface dataset:
Stacks: Building and Genotyping Loci De Novo From Short-Read Sequences

Advances in sequencing technology provide special opportunities for genotyping individuals with speed and thrift, but the lack of software to automate the calling of tens of thousands of genotypes over hundreds of individuals has hindered progress. Stacks is a software system that uses short-read sequence data to identify and genotype loci in a set of individuals either de novo or by comparison to a reference genome. From reduced representation Illumina sequence data, such as RAD-tags, Stacks can recover thousands of single nucleotide polymorphism (SNP) markers useful for the genetic analysis of crosses or populations. Stacks can generate markers for ultra-dense genetic linkage maps, facilitate the examination of population phylogeography, and help in reference genome assembly. We report here the algorithms implemented in Stacks and demonstrate their efficacy by constructing loci from simulated RAD-tags taken from the stickleback reference genome and by recapitulating and improving a genetic map of the zebrafish, Danio rerio.
Framework of an Emergency Management System Using Different Rescue Simulators

An emergency management system (EMS) is extremely important at the time of disasters as it provides the necessary support to rescue commanders. In recent times, people's requirements with regard to an EMS and the technologies that support an EMS have changed, and different systems have been developed for different purposes. For example, there are systems that simulate urban-size disasters and evacuation behaviors. Other systems have been designed to assist the development of rescue robots whose function is to search and rescue victims. This paper presents a framework that links simulations that have been developed independently, and a prototype system that connects two disaster and rescue systems with different features. The prototype system shows a possibility that the framework makes the simulations versatile ones as a part of an EMS.
Sensory Semantic User Interfaces (SenSUI): Position Paper

Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each user adequately. Adaptive user interfaces are able to adapt information and application functionalities to the user context. In contrast, pervasive computing and sensor networks open new opportunities for context aware platforms, one that is able to improve user interface adaptation reacting to environmental and user sensors. Semantic web technologies and ontologies are able to capture sensor data and provide contextual information about the user, their actions, required applications and environment. This paper investigates the viability of an approach where semantic web technologies are used to maximize the efficacy of interface adaptation through the use of available ontology.
Speakers use their own discourse model to determine referents' accessibility during the production of referring expressions.

We report two experiments that investigated the widely-held assumption that speakers use the addressee's discourse model when choosing referring expressions, by manipulating whether the addressee could hear the immediately preceding linguistic context. Experiment 1 showed that speakers increased pronoun use (relative to definite NPs) when the referent was mentioned in the immediately preceding sentence compared to when it was not, but whether their addressee heard that the referent was mentioned had no effect, indicating that speakers use their own, privileged discourse model when choosing referring expressions. The same pattern of results was found in Experiment 2. Speakers produced fewer pronouns when the immediately preceding sentence mentioned a referential competitor than when it mentioned the referent, but this effect did not differ depending on whether the sentence was shared with their addressee. Thus, we conclude that choice of referring expression is determined by the referent's accessibility in the speaker’s own discourse model rather than the addressee's.
DANGEROUSNESS AND VIOLENCE RISK ASSESSMENT

passes or parole, husbands, ex-husbands or boyfriends with domestic violence restraining orders, young people with precocious violence histories or patients with mental disorders released from psychiatric hospitals, commit severe violent acts. These events show the existent of risk for violence in certain individuals (Blackburn, 1999; Buchanan, 1999; Campbell, 1995; Hart, 1998). We are very habituated to considering dangerousness as the key attribute in the estimation of the probability of future violent behaviour, but the development of Criminal Psychology has shown that the predictive capacity of dangerousness is limited and its use is not very efficient for professionals who make prospective decisions in forensic, clinical or penitentiary settings (Webster et al., 1997, Andrews & Bonta, 2003, Scott & Resnick, 2006). In the last 15 years, new techniques for the prediction of violent behaviour have DANGEROUSNESS AND VIOLENCE RISK ASSESSMENT
Interaction balance optimization in multidisciplinary design optimization problems

As a bi-level optimization method, collaborative optimization can solve multidisciplinary design optimization problems in practical engineering effectively. However, if there are high-dimensional couplings in a multidisciplinary design optimization problem, a large number of compatibility constraints will be required in collaborative optimization. In this situation, collaborative optimization will not be suitable to be utilized because of low computational efficiency or divergence issue. To solve this problem, an efficient interaction balance optimization method is proposed in this article. In interaction balance optimization method, the simple coordination strategy of interaction balance principle and the distributed optimization strategy of collaborative optimization can be integrated effectively. Lagrange multipliers are used instead of compatibility constraints to maintain the consistency between any two coupled disciplines. Two examples are given to show the effectiveness of the proposed method.
Consequence-Driven Reasoning for Horn SHIQ Ontologies

We present a novel reasoning procedure for Horn SHIQ ontologies--SHIQ ontologies that can be translated to the Horn fragment of first-order logic. In contrast to traditional reasoning procedures for ontologies, our procedure does not build models or model representations, but works by deriving new consequent axioms. The procedure is closely related to the so-called completion-based procedure for EL++ ontologies, and can be regarded as an extension thereof. In fact, our procedure is theoretically optimal for Horn SHIQ ontologies as well as for the common fragment of EL++ and SHIQ. A preliminary empirical evaluation of our procedure on large medical ontologies demonstrates a dramatic improvement over existing ontology reasoners. Specifically, our implementation allows the classification of the largest available OWL version of Galen. To the best of our knowledge no other reasoner is able to classify this ontology.
Effect of Training with and without a Load on Military Fitness Tests and Marksmanship

Swain, DP, Ringleb, SI, Naik, DN, and Butowicz, CM. Effect of training with and without a load on military fitness tests and marksmanship. J Strength Cond Res 25(7): 1857-1865, 2011—The purpose of this study was to determine whether military-style training performed while carrying a weighted vest and backpack (Load condition) resulted in superior training adaptations (specifically, changes in military fitness and marksmanship) than did more conventional training (No-Load condition). A total of 33 college-aged men and women (16 Load, 17 No-Load) completed all testing and 9 weeks of training (1 h·d−1, 4 d·wk−1). No-Load training consisted of military calisthenics, sprints, agility drills, and running. Load training was similar except that running was replaced with stair climbing, and Load increased across the 9 weeks to 20 kg for women and 30 kg for men. Pretraining and posttraining, all subjects performed an uphill treadmill test with full load to determine peak oxygen consumption (&OV0312;o2peak), the marine physical fitness test (PFT) and combat fitness test (CFT) without load, other fitness tests, and an indoor marksmanship test using a laser-fitted carbine. The marksmanship test was performed with full load and done before and immediately after a 200-m shuttle run performed in 60 seconds. Both groups significantly improved their &OV0312;o2peak, PFT, and CFT scores by similar amounts. Pretraining, shooting score decreased significantly after the 200-m run and then rapidly recovered, with no difference between groups. A similar, but nonsignificant, pattern in shooting scores was seen in both groups posttraining. In conclusion, loaded training did not produce measurable advantages compared with unloaded training in this population. A strenuous anaerobic challenge caused a temporary reduction in marksmanship.
ANAWIKI: Creating Anaphorically Annotated Resources through Web Cooperation

The ability to make progress in Computational Linguistics depends on the availability of large annotated corpora, but creating such corpora by hand annotation is very expensive and time consuming; in practice, it is unfeasible to think of annotating more than one million words. However, the success of Wikipedia and other projects shows that another approach might be possible: take advantage of the willingness of Web users to contribute to collaborative resource creation. AnaWiki is a recently started project that will develop tools to allow and encourage large numbers of volunteers over the Web to collaborate in the creation of semantically annotated corpora (in the first instance, of a corpus annotated with information about anaphora).
Tula Hantavirus Infection in Immunocompromised Host, Czech Republic

We report molecular evidence of Tula hantavirus as an etiologic agent of pulmonary-renal syndrome in an immunocompromised patient. Acute hantavirus infection was confirmed by using serologic and molecular methods. Sequencing revealed Tula virus genome RNA in the patient’s blood. This case shows that Tula virus can cause serious disease in humans.
Automatic mapping of Wikipedia categories into OpenCyc types

The aim of the research presented in the article is the mapping between the English Wikipedia categories and OpenCyc types. The mapping algorithm is heuristic and it takes into account structural similarities between the categories and the corresponding types. The achieved mapping precision ranges from 82 to 92 % (depending on the evaluation scheme), recall from 67 to 76%. The results of the algorithm and its code are available at http://cycloped.io.
Estimating the size of an illicit‐drug‐using population

This paper describes a new method for estimating the size of an illicit‐drug‐using population. It is designed to overcome certain limitations of registry‐based techniques that require both comprehensive site coverage and unique case identifiers, and which do not typically provide estimates of the number of drug users who are currently active. The approach involves collecting retrospective self‐report data on the careers of individuals who appear at drug treatment programmes. A model is developed that corrects for the selection bias introduced by the sampling plan, and which allows us to estimate the rate at which drug users generate treatment admission events during spells of use. The size of the drug‐using population is estimated by dividing the estimated total number of treatment admissions that are generated during some fixed interval of time by the estimated rate at which individuals generate such events. The technique is tested in a series of simulation studies which demonstrate that accurate estimates of the size of the drug using population can be obtained in this manner. Analytical expressions for confidence intervals about the population estimates are derived as part of the exercise. Limitations of the approach and other potential applications are discussed. Copyright © 2003 John Wiley & Sons, Ltd.
Multiple Quantitative Trait Analysis Using Bayesian Networks

Models for genome-wide prediction and association studies usually target a single phenotypic trait. However, in animal and plant genetics it is common to record information on multiple phenotypes for each individual that will be genotyped. Modeling traits individually disregards the fact that they are most likely associated due to pleiotropy and shared biological basis, thus providing only a partial, confounded view of genetic effects and phenotypic interactions. In this article we use data from a Multiparent Advanced Generation Inter-Cross (MAGIC) winter wheat population to explore Bayesian networks as a convenient and interpretable framework for the simultaneous modeling of multiple quantitative traits. We show that they are equivalent to multivariate genetic best linear unbiased prediction (GBLUP) and that they are competitive with single-trait elastic net and single-trait GBLUP in predictive performance. Finally, we discuss their relationship with other additive-effects models and their advantages in inference and interpretation. MAGIC populations provide an ideal setting for this kind of investigation because the very low population structure and large sample size result in predictive models with good power and limited confounding due to relatedness.
CHANGING BODIES: SYMPTOMS, BODY IMAGE, HEALTH AND WELLBEING OVER THE MENOPAUSAL TRANSITION

Aim: To undertake exploratory work examining the relationship between menopausal symptoms, body image, exercise and wellbeing. Method: A mixed methods approach was used, including a systematic scoping review, the development of a synchronous text-based online interviewing tool; a qualitative Interpretative Phenomenological Analysis study, and mixed methods study. Results: The review showed that women’s experiences of the menopause and body image can be both positive and negative simultaneously, which has implications for the way these concepts are quantitatively measured. A synchronous online interviewing tool is an additional method to be added to the researchers’ tool kit, especially if the topic is sensitive and an extra level of anonymity is needed. The IPA study focused on experiences of body image concerns and identified a range of ways menopausal women cope with such changes. Through Structural Equation Modelling and interviews, we identified that menopausal symptoms may act as a barrier to exercise participation by decreasing a woman’s subjective vitality, and reducing perceptions of attractiveness, life satisfaction and self-esteem. Conclusion: Health psychology of the menopausal transition is in its infancy. It is not only important to consider methods to reduce symptoms, but also the impact symptoms have on health behaviour, body image and wellbeing.
Focus groups : a practical guide for applied research

Foreword - Michael Quinn Patton PART ONE: GROUPS AND FOCUS GROUPS Groups Focus Groups PART TWO: THE PROCESS OF CONDUCTING FOCUS GROUPS Conceptualizing the Focus Group Asking Questions in a Focus Group Moderating Skills Participants in a Focus Group Analyzing Focus Group Results Reporting Focus Group Results PART THREE: ISSUES AND CONCERNS USING NONRESEARCHERS IN FOCUS GROUPS Focus Groups Special Situations Contracting for Focus Groups A Consumer's Guide Postscript The Future of Focus Groups
Performance Prediction for Graph Queries

Query performance prediction has shown benefits to query optimization and resource allocation for relational databases. Emerging applications are leading to search scenarios where workloads with heterogeneous, structure-less analytical queries are processed over large-scale graph and network data. This calls for effective models to predict the performance of graph analytical queries, which are often more involved than their relational counterparts. In this paper, we study and evaluate predictive techniques for graph query performance prediction. We make several contributions. (1) We propose a general learning framework that makes use of practical and computationally efficient statistics from query scenarios and employs regression models. (2) We instantiate the framework with two routinely issued query classes, namely, reachability and graph pattern matching, that exhibit different query complexity. We develop modeling and learning algorithms for both query classes. (3) We show that our prediction models readily apply to resource-bounded querying, by providing a learning-based workload optimization strategy. Given a query workload and a time bound, the models select queries to be processed with a maximized query profit and a total cost within the bound. Using real-world graphs, we experimentally demonstrate the efficacy of our framework in terms of accuracy and the effectiveness of workload optimization.
Machine Translation with Many Manually Labeled Discourse Connectives

The paper presents machine translation experiments from English to Czech with a large amount of manually annotated discourse connectives. The gold-standard discourse relation annotation leads to better translation performance in ranges of 4‐60% for some ambiguous English connectives and helps to find correct syntactical constructs in Czech for less ambiguous connectives. Automatic scoring confirms the stability of the newly built discourseaware translation systems. Error analysis and human translation evaluation point to the cases where the annotation was most and where less helpful.
Plagiarism Detection in Web based Learning Management Systems and Intellectual Property Rights in the Academic Environment

his paper presents a background of a project undertaken at Sohar University to implement a web based plagiarism detection system for academic activities. Digital content in academic environments are created by academics and students. This Digital content is research publications and assessment submissions - assignments. Academic Digital content once created needs to be verified for non-violation of IPR issues and compliance to academic plagiarism policies followed by the institution.
Maximum Entropy Approach based Named Entity Recognition in Punjabi Language

Named Entity Recognition is the task of identifying and classifying named entities into some predefine categories like person, location, organization etc. NER is used in many applications like text summarization, text classification, question answering and machine translation systems etc. For English a lot of work has already been done in the field of NER, where capitalization is a major key for rules, whereas Indian languages do not have such feature. This makes the task difficult for Indian Languages. This work reports about the evaluation of a Named Entity Recognition (NER) system for Punjabi language using the Maximum Entropy Approach (MAXENT). A manually tagged Punjabi news corpus is used for the evaluation which was developed from Punjabi newspaper available online. The training set annotated with a NE tagset of 12 tags is used. A MAXENT based NER system for Punjabi has reported an overall Precision, Recall and FScore values of 90.92%, 72.30% and 80.55% respectively with feature set context word, Part of Speech (POS) information, NE tag of previous word and First name Gazetteer list.
Calcineurin inhibitor minimization protocols in liver transplantation

Liver transplant recipients are at increasingly high risk for suffering from impaired renal function and probable need of renal replacement therapy. Extended criteria organs and transplantation of patients with higher model for end‐stage liver disease scores further increase this problem. Acute and chronic nephrotoxicity are the trade‐off in immunosuppression with potent calcineurin inhibitors (CNIs). As a good renal function is associated with better graft and patient survival, CNI minimization protocols have been developed. Current strategies to overcome CNI toxicity include reduction or withdrawal of CNIs concurrently with switching over to mammalian target of rapamycin inhibitor or mycophenolate mofetil (MMF)‐based regimens. This strategy caused an improvement in renal function in a significant number of liver transplantation patients according to several studies. However, total CNI avoidance seems to result in higher rejection rates. To prevent chronic renal dysfunction in patients prone to or with acute renal failure, CNI delay – with induction therapy for bridging – followed by low‐dose CNI in combination with MMF are proven strategies without risking higher rejection rates. An individualized, tailor‐made immunosuppressive regime, with a special focus on renal function is recommended. This review gave an overview on CNI minimization protocols in liver transplantation also focusing on recently analyzed studies.
Consequences of loss of PINCH 2 expression in mice

Integrins are heterodimeric transmembrane glycoproteins that mediate cell-cell and cell-extracellular matrix adhesion (Hynes, 2002). They play pivotal roles in many biological processes including cell shape modulation, proliferation, survival and differentiation (van der Flier and Sonnenberg, 2001). Integrins execute these functions by recruiting a large number of intracellular adaptor and signaling molecules to their short cytoplasmic domain (Zamir and Geiger, 2001). They link integrins with different signaling pathways and connect integrin adhesion sites to the actin cytoskeleton. Integrin-associated molecules can also modulate integrin activation (affinity) and their clustering in focal adhesion sites (FAs; avidity). One FA protein is PINCH (also known as Lims), which is composed of five LIM domains followed by a short C-terminal tail containing putative nuclear localization/export signals. Each LIM domain is composed of two zinc-finger motifs, which are able to engage in protein interactions (Kadrmas and Beckerle, 2004). The second zinc-finger of the LIM1 domain of PINCH binds integrin-linked kinase (ILK) (Li et al., 1999). The LIM4 domain binds the adaptor protein NCK2, which interacts with several tyrosine kinase receptors thereby linking integrins and growth factor signaling (Tu et al.