Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Strain of Wolbachia in an Alpine Population of the Viviparous Oreina cacaliae (Coleoptera: Chrysomelidae)

ABSTRACT Microbial symbionts played a central role in insect evolution. Oreina cacaliae (Schrank, 1785) (Coleoptera: Chrysomelidae) is a rare example of a viviparous insect, able to feed on toxic plants and sequester toxic compounds. In the current study, the microbiota associated with O. cacaliae was characterized using a culture-independent approach, targeting the 16S rRNA bacterial gene. The obtained 16S rRNA gene sequences were analyzed and identified at different taxonomic levels. Wolbachia was the dominant bacterium, both in male and female (100 and 91.9%, respectively) individuals; the detected Wolbachia was described as a new sequence type based on multilocus sequence typing (Wolbachia ST375 Ocac_A_wVdO). After phylogenetic analyses, Wolbachia ST375 Ocac_A_wVdO was attributed to the supergroup A. Immunofluorescence assays and electron microscopy confirmed the presence of Wolbachia within O. cacaliae oocytes, confirming its transovarial transmission in this species. Representatives of six species of Oreina were tested for the presence of Wolbachia through specific polymerase chain reaction, and a dendrogram was generated for these species based on coxI gene sequences. The Wolbachia harbored by different species of Oreina were characterized by multilocus sequence typing. Five out of the six examined Oreina species were positive for Wolbachia, with four of these harboring the same sequence type.
Finite Difference Synthetic Acoustic Logs

The finite‐difference method is a powerful technique for studying the propagation of elastic waves in boreholes. Even for the simple case of an open borehole with vertical homogeneity, the snapshot format of the method displays clearly the interaction between the borehole and the rock, and the origin and evolution of phases. We present an outline of the finite‐difference method applied to the acoustic logging problem, including a boundary condition formulation for liquid‐solid cylindrical interfaces which is correct to second order in the space increments. Absorbing boundaries based on the formulations of Reynolds (1978) and Clayton and Engquist (1977) were used to reduce reflections from the grid boundaries. Results for a vertically homogeneous sharp interface model are compared with the discrete‐wavenumber method and excellent agreement is obtained. The technique is also demonstrated by considering sharp and continuous transitions (damaged zones) at the borehole wall and by considering the effects of wa.
American Terrorist: Timothy McVeigh & the Oklahoma City Bombing

April 19, 1995. The Alfred P. Murrah Building in Oklahoma City is ravaged by a vicious bombing that claims 168 innocent lives. Two years later, 29-year-old Timothy McVeigh, a decorated Gulf War veteran, is convicted of the crime and sentenced to death. Most of America knows his name. But only McVeigh himself knows exactly what happened on that ill-starred day. And despite his conviction, he has never gone on record in any forum to discuss the bombing. Until now. Award-winning journalists Lou Michel and Dan Herbeck have been investigating the bombing for more than five years. They have conducted more than 300 interviews, compiling exclusive testimony from federal investigators, family and friends of McVeigh and survivors' and victims' families. And in 1997 they secured an extraordinary coup: in more than 75 hours of interviews, they persuaded Timothy McVeigh to give a complete account of his story -- from his formative childhood experiences, through his days in the Army, to a thorough portrait of the culture of right-wing separatists and gun-show extremism that was the breeding ground for the terrorist plot. It is the deeply unsettling story of an average American son driven to violence by his hatred of government. And its climax -- the first and only inside account of the planning and execution of the bombing -- answers at last the questions that have haunted Oklahoma City and the nation since that April day. At once an explosive work of journalism and a uniquely American story, American Terrorist will help bring closure to a wound left too long open in our national psyche.
Investigating the Influence of the Herding Effect on Consumption Experience: The Case of Online Music

Social influence has shown to be incredibly powerful in shaping a consumer’s behaviour. An example of this occurs with the “herding effect”, in which consumers ignore any of their own signals in favour of copying the actions or preferences of the majority. Social influence has been shown to be especially strong in online music consumption, due to the fact that music is highly subjective and can only be ascribed value after it has been experienced; therefore, it is not surprising that strong relationships have been found in research looking at herding effects in music consumption. However, past studies have limited their scope to analyzing the effect across situations, and have so far assumed that the herding effect holds for all consumers, and for all types of music. Therefore, this study looks determine whether there are any potential moderators to the herding effect, such as an individual’s personality or the type of music being consumed. Furthermore, while past studies have looked only at product choice as an outcome variable, this study aims to extend our understanding of the strength of the effect to see if it also impacts consumers’ subsequent evaluations of the consumption experience. Results suggest this effect on the consumption experience does exist, and significant effects are found that suggest online social connectedness and self-construal moderate the impact of the herding effect. These results have implications for marketers in the music industry, and also more generally for anyone looking to understand how personality may moderate social influence effects.
The contemporary avant-garde : classification, organization, spatiality and practices of resistance

The intention of the thesis is to explore and make visible the sociological importance of contemporary avant-garde music by investigating the ways in which associated cultures are constituted through the interplay between technologically mediated forms of dialogue and destabilizing practices. Through the case study of hauntology, the present work explores the interrelationship between different participant groups (building on, and problematizing, aspects of Becker's Art Worlds) and how they negotiate and collaborate with one another. Methodologically-speaking, the thesis adopts multiple approaches to data collection and analysis in an effort to develop a series of conceptual research tools predicated on the partial connections and assemblages observed during field work. The research is participant-focused, dealing primarily with the ways in which these groups engage in meaning-making activities within their own interpretive frameworks. The empirical focus of the thesis is fourfold. In the first instance, this involves detailing classificatory work on genre and boundary formation as enacted by participants through differing forms of dialogue in a variety of virtual locations. Secondly, an assessment of the organizational structures developed by artists (such as the record label) and audience members (the archive) is undertaken, in an effort to understand how information is collated and stored and how the development of a mediated 'aesthetic', or metadiscourse, is facilitated by these systems. Thirdly, co-operation between social actors is examined in relation to spatial associations and participant-led acts of destabilization (read through the work of Lefebvre). Fourthly, practices of micro and macro-level resistance - including direct political activities, techniques of composition, intertextuality and engagement with cultural theory - are considered in relation to the other empirical foci.
Process Mining Techniques: an Application to Stroke Care

In a competitive health-care market, hospitals have to focus on ways to streamline their processes in order to deliver high quality care while at the same time reducing costs. To accomplish this goal, hospital managers need a thorough understanding of the actual processes. Diffusion of Information and Communication Technology tools within hospitals, such as electronic clinical charts, computerized guidelines and, more generally, decision support systems, make huge collections of data available, not only for data analysis, but also for process analysis. Process mining can be used to extract process related information (e.g., process models) from data, i.e., process mining describes a family of a-posteriori analysis techniques exploiting the information recorded in the event logs. This process information can be used to understand and redesign processes to become efficient high quality processes. In this paper, we apply process mining on two datasets for stroke patients and present the most interesting results. Above all, the paper demonstrates the applicability of process mining in the health-care domain.
Fast search algorithms for vector quantization of images using multiple triangle inequalities and wavelet transform

The encoding of vector quantization (VQ) needs expensive computation for searching the closest codevector to the input vector. This paper presents several fast encoding algorithms based on multiple triangle inequalities and wavelet transform to overcome this problem. The multiple triangle inequalities confine a search range using the intersection of search areas generated from several control vectors. A systematic way for designing the control vectors is also presented. The wavelet transform combined with the partial distance elimination is used to reduce the computational complexity of the distance calculation of vectors. The proposed algorithms provide the same coding quality as the full search method. The experimental results indicate that the new algorithms perform more efficiently than existing algorithms.
Head pose estimation for wearable robot control

Recent advances in wearable sensing allow active control of the orientation of a body-mounted camera worn by a remote user. In this paper we consider the control of the active camera from head movements. In the context of teleoperation, these may be the head movements of a remote operator, perhaps acting as the wearer’s assistant. The movements are likely to be larger than those in video-conference applications, and so frontal facial features are insufficient. The paper presents a model which incrementally combines a fixed 3D shape model with specific features found on the observed head. Robust methods, including the incorporation of a colour model, are used to mitigate the effect of mismatching, the main contribution being the use of both interest point and colour features within a single random-sampling framework.
Autocalibration of MEMS accelerometers

In this paper a new approach of an auto calibration method for micromechanical sensors is proposed. In particular, recalibration of acceleration sensors without any additional laboratory equipment is considered. If the device is stationary, the proposed procedure exploits the fact that the output vector of the acceleration sensor should match the gravity acceleration. The calibration method computes the scale factors and the bias components of the unbalanced acceleration sensor. These parameters are computed through nonlinear optimization. The applied optimization method is a nonlinear parameter estimator based on the Unscented Transformation. This methodology uses the robust statistical linearization instead of the common analytical linearization. In addition, the applied methodology minimizes the amount of temporarily stored measurement data which are mandatory to launch the recalibration algorithm. Reducing the amount of temporarily stored data is equivalent to reducing the memory space and the power required for the algorithm. An effective method for rejecting disturbance acceleration is also included in order to apply user generated data for the recalibration. First the calibration method is evaluated through simulations and second with real data generated by an acceleration sensor. The simulation results show that the algorithm estimates the offset and sensitivity parameters more precisely than the uncertainty introduced through the measurement noise.
Follow-up utterances in QA dialogue

The processing of user follow-up utterances by a QA system is a topic which is still in its infant stages, but enjoys growing interest in the QA community. In this paper, we discuss the broader issues related to handling follow-up utterances in a real-life "information kiosk" setting. With help of a corpus of follow-up utterances, we lay out a general framework for QA dialogue, and propose a general-coverage classication of real user reactions, based on their function in the dialogue, and their relation to the context of previous utterances. We discuss a dialogue manager we have developed that handles the identied types of follow-up utterances. It uses existing NLP and IR techniques to handle follow-up questions, and generates appropriate dialogue reactions to handle non-follow-up questions. Our main conclusion is that a large part of follow-up utterances can be handled by a set of simple techniques, even though we found it is not easy to determine the exact context in which follow-up questions are to be understood.
American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer.

PURPOSE To update the recommendations for the use of tumor marker tests in the prevention, screening, treatment, and surveillance of breast cancer. METHODS For the 2007 update, an Update Committee composed of members from the full Panel was formed to complete the review and analysis of data published since 1999. Computerized literature searches of MEDLINE and the Cochrane Collaboration Library were performed. The Update Committee's literature review focused attention on available systematic reviews and meta-analyses of published tumor marker studies. In general, significant health outcomes (overall survival, disease-free survival, quality of life, lesser toxicity, and cost-effectiveness) were used for making recommendations. Recommendations and CONCLUSIONS Thirteen categories of breast tumor markers were considered, six of which were new for the guideline. The following categories showed evidence of clinical utility and were recommended for use in practice: CA 15-3, CA 27.29, carcinoembryonic antigen, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, urokinase plasminogen activator, plasminogen activator inhibitor 1, and certain multiparameter gene expression assays. Not all applications for these markers were supported, however. The following categories demonstrated insufficient evidence to support routine use in clinical practice: DNA/ploidy by flow cytometry, p53, cathepsin D, cyclin E, proteomics, certain multiparameter assays, detection of bone marrow micrometastases, and circulating tumor cells.
A General Stochastic Information Diffusion Model in Social Networks based on Epidemic Diseases

Social networks are an important infrastructure for information, viruses and innovations propagation. Since users behavior has influenced by other users activity, some groups of people would be made regard to similarity of users interests. On the other hand, dealing with many events in real worlds, can be justified in social networks; spreading disease is one instance of them. People manner and infection severity are more important parameters in dissemination of diseases. Both of these reasons derive, whether the diffusion leads to an epidemic or not. SIRS is a hybrid model of SIR and SIS disease models to spread contamination. A person in this model can be returned to susceptible state after it removed. According to communities which are established on the social network, we use the compartmental type of SIRS model. During this paper, a general compartmental information diffusion model would be proposed and extracted some of the beneficial parameters to analyze our model. To adapt our model to realistic behaviors, we use Markovian model, which would be helpful to create a stochastic manner of the proposed model. In the case of random model, we can calculate probabilities of transaction between states and predicting value of each state. The comparison between two mode of the model shows that, the prediction of population would be verified in each state.
Two cases of paraneoplastic limbic encephalitis associated with small cell lung cancer and a literature review

In the present study, two cases of paraneoplastic limbic encephalitis (PLE) associated with small cell lung cancer were reported. Using avidin-biotin immunoperoxidase methods, purified recombinant HuD western blotting and Euroline Neuronal Antigens Profile 2 immunoglobulin G western blotting, it was found that the well-characterized anti-Hu and anti-amphiphysin onconeuronal antibodies were present in the serum/cerebrospinal fluid of the patients. With a review of the literature, it was found that patients with PLE of Chinese Han nationality had two types of clinical manifestations, simple and complex, and that the lesions could also be divided into focal and scalable lesions. Furthermore, the clinical manifestations and lesion scopes were associated with certain types of cancer and antibodies. In addition, it was found that the prognosis for patients with PLE with autoantibodies targeting membrane antigens is improved compared with that for patients with PLE with autoantibodies targeting intracellular antigens, due to an increased sensitivity to immunomodulatory treatments and anti-cancer therapy.
Visuocode: A software development environment that supports spatial navigation and composition

Navigating through software is an integral part of software development. Studies have identified that during navigation programmers often become disoriented and lose task awareness. To mitigate this, the method-flow visualisation technique displays traversed methods in adjacent editor columns. This paper presents the Visuocode software development environment, which is an implementation of method-flow that, in addition to navigation, supports program composition.
Pattern-based analysis of windows workflow

The Windows Workflow Foundation (WF) has been introduced as part of the . NET framework as a means of creating workflow-centric applications. Its intended field of application is broad, ranging from fat-client applications and web applications to enterprise application integration solutions. Unlike other approaches, Windows Workflow supports two distinct approaches to workflow specification - sequential workflows and state machine workflows - which deal with fundamentally different types of business scenarios. To date there has been minimal investigation into its capabilities and limitations, especially with respect to the two different control-flow styles it offers. To remedy this, in this paper we present a rigorous analysis of Windows Workflows’s ability to deal with common control-flow scenarios. As a framework for this evaluation we use the Workflow Patterns. Our analysis outlines the strength and shortcomings of Windows Workflow’s control-flow expressiveness and compares it to BPEL and jBPM - two other popular approaches for the design and implementation of business processes in a service-oriented context.
Side‐chain conformational entropy in protein folding

An important, but often neglected, contribution to the thermodynamics of protein folding is the loss of entropy that results from restricting the number of accessible side‐chain conformers in the native structure. Conformational entropy changes can be found by comparing the number of accessible rotamers in the unfolded and folded states, or by estimating fusion entropies. Comparison of several sets of results using different techniques shows that the mean conformational free energy change (TΔS) is 1 kcal‐mol−1 per side chain or 0.5 kcal‐mol−1 per bond. Changes in vibrational entropy appear to be negligible compared to the entropy change resulting from the loss of accessible rotamers. Side‐chain entropies can help rationalize α‐helix propensities, predict protein/inhibitor complex structures, and account for the distribution of side chains on the protein surface or interior.
New compact formulations for choice network revenuemanagement

The choice network revenue management model incorporates customer purchase behavior as a function of the offered products, and is the appropriate model for airline and hotel network revenue management, dynamic sales of bundles, and dynamic assortment optimization. The optimization problem is a stochastic dynamic program and is intractable, and a linear program approximation called choice deterministic linear program (CDLP) is usually used to generate dynamic controls. Recently a compact linear programming formulation of CDLP for the multinomial logit (MNL) model of customer choice has been proposed. In this paper we obtain a better approximation to the dynamic program than CDLP while retaining the appealing properties of a compact linear programming representation. Our formulation is based on the affine relaxation of the dynamic program. We first show that the affine relaxation is NP-complete even for a single-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive new linear programs that approximate the dynamic programming value function provably better, between the CDLP value and the affine relaxation, and often coming close to the latter in our numerical experiments. We give extensions to the case with multiple customer segments where choice by each segment is according to the MNL model. Finally we perform extensive numerical comparisons on the various methods to evaluate their performance.