Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of oral dexmedetomidine versus oral midazolam as premedication to prevent emergence agitation after sevoflurane anaesthesia in paediatric patients

Background and Aims: Sevoflurane is the most often used inhalational agent in paediatric anaesthesia, but emergence agitation (EA) remains a major concern. Oral midazolam and parenteral dexmedetomidine are known to be effective in controlling EA. We attempted to elucidate whether oral dexmedetomidine is better than midazolam in controlling EA. Methods: Prospective double-blinded study involving ninety patients aged 1–10 years, undergoing elective surgeries of <2 h of expected duration under sevoflurane general anaesthesia, randomised to receive either midazolam (Group A) or dexmedetomidine (Group B) as oral premedication was carried out to record level of sedation before induction, haemodynamic parameters and recovery time. Incidence and severity of EA, post-operative pain and requirement of rescue analgesic were assessed at 0, 5, 15, 30 and 60 min postoperatively. Results: Data were analysed applying Student's t-test and Chi-square test using SPSS software. Mask acceptance was better in Group B (97.8% vs. 73.4%,P< 0.001). Mean arterial pressure was lower in Group B (P < 0.001) though clinically not significant. More rescue analgesic was required in Group A (5.6% vs. 0%). There was no significant difference in adverse effects. Although there was a higher incidence of EA in Group A (Aono's score 3 and 4; 40% vs. 4.4%), none of them required intervention (paediatric anaesthesia emergence delirium score >10; 0 vs. 0). Conclusion: Premedication with oral dexmedetomidine provides smooth induction and recovery, reduces the EA and provides better analgesia and sedation as compared to oral midazolam.
Antigen Targeting to Major Histocompatibility Complex Class II with Streptococcal Mitogenic Exotoxin Z-2 M1, a Superantigen-Based Vaccine Carrier

ABSTRACT Streptococcal mitogenic exotoxin Z-2 (SMEZ-2) is a streptococcal superantigen that primarily stimulates human T cells bearing Vβ8 and mouse T cells bearing Vβ11. Mutagenesis of T cell receptor (TCR)-binding residues (W75L, K182Q, D42C) produced a mutant called M1 that was >105-fold less active toward human peripheral blood lymphocytes and splenocytes from transgenic mice that express human CD4 and either human HLA-DR3-DQ2 or HLA-DR4-DQ8. Similarly, cytokine production in response to M1 in lymphocyte culture was rendered undetectable, and no change in the frequency of Vβ11-bearing T cells in mice receiving M1 was observed. M1 toxoid was tested as a potential vaccine conjugate. Vaccination with 1 to 10 μg M1 conjugated to ovalbumin (M1-ovalbumin) resulted in more rapid and quantitatively higher levels of anti-ovalbumin IgG, with endpoint titers being 1,000- to 10,000-fold greater than those in animals immunized with unconjugated ovalbumin. Substantially higher levels of anti-ovalbumin IgG were observed in mice transgenic for human major histocompatibility complex (MHC) class II. Substitution of M1 with an MHC class II binding mutant (DM) eliminated enhanced immunity, suggesting that M1 enhanced the delivery of antigen via MHC class II-positive antigen-presenting cells that predominate within lymphoid tissue. Immunization of animals with a conjugate consisting of M1 and ovalbumin peptide from positions 323 to 339 generated levels of anti-peptide IgG 100-fold higher than those in animals immunized with peptide alone. Coupling of a TCR-defective superantigen toxoid presents a new strategy for conjugate vaccines with the additional benefit of targeted delivery to MHC class II-bearing cells.
Socialization in Synchronous Computer-Mediated Communication

This paper, based on a qualitative ethnographic study among college of education students, examines the online interactional processes surrounding academic discourse socialization. Data for this paper come from a larger study of an academic classroom community of graduate students and their instructor. In this study, I looked into the ways computer-mediated communication (CMC) contexts factor into graduate students' academic literacy experience in a graduate classroom, therein enculturating them into their new academic community. I focus on cases of nonnative graduate students in a content course in the department of educational psychology at a large southwestern university in the U.S. I explore the agency of the focal participants in terms of the roles they played in the classroom discourse highlighting the dialectical and interactional perspective of academic discourse socialization. This paper focused on the construction of varied participant roles of the focal students. It further examines student reactions and responses to these constructions during synchronous CMC activity.
Cache-conscious sorting of large sets of strings with dynamic tries

Ongoing changes in computer architecture are affecting the efficiency of string-sorting algorithms. The size of main memory in typical computers continues to grow but memory accesses require increasing numbers of instruction cycles, which is a problem for the most efficient of the existing string-sorting algorithms as they do not utilize cache well for large data sets. We propose a new sorting algorithm for strings, burstsort, based on dynamic construction of a compact trie in which strings are kept in buckets. It is simple, fast, and efficient. We experimentally explore key implementation options and compare burstsort to existing string-sorting algorithms on large and small sets of strings with a range of characteristics. These experiments show that, for large sets of strings, burstsort is almost twice as fast as any previous algorithm, primarily due to a lower rate of cache miss.
Elucidation of miRNAs-Mediated Responses to Low Nitrogen Stress by Deep Sequencing of Two Soybean Genotypes

Nitrogen (N) is a major limiting factor in crop production, and plant adaptive responses to low N are involved in many post-transcriptional regulation. Recent studies indicate that miRNAs play important roles in adaptive responses. However, miRNAs in soybean adaptive responses to N limitation have been not reported. We constructed sixteen libraries to identify low N-responsive miRNAs on a genome-wide scale using samples from 2 different genotypes (low N sensitive and low N tolerant) subjected to various periods of low nitrogen stress. Using high-throughput sequencing technology (Illumina-Solexa), we identified 362 known miRNAs variants belonging to 158 families and 90 new miRNAs belonging to 55 families. Among these known miRNAs variants, almost 50% were not different from annotated miRNAs in miRBase. Analyses of their expression patterns showed 150 known miRNAs variants as well as 2 novel miRNAs with differential expressions. These differentially expressed miRNAs between the two soybean genotypes were compared and classified into three groups based on their expression patterns. Predicted targets of these miRNAs were involved in various metabolic and regulatory pathways such as protein degradation, carbohydrate metabolism, hormone signaling pathway, and cellular transport. These findings suggest that miRNAs play important roles in soybean response to low N and contribute to the understanding of the genetic basis of differences in adaptive responses to N limitation between the two soybean genotypes. Our study provides basis for expounding the complex gene regulatory network of these miRNAs.
Title Auto-calibration and motion recovery from silhouettes forturntable sequences

This paper addresses the problem of structure and motion from silhouettes for turntable sequences. Previous works have exploited corresponding points induced by epipolar tangencies to estimate the image invariants under turntable motion and recover the epipolar geometry. In these approaches, however, camera intrinsics are needed in order to obtain Euclidean motion and reconstruction. This paper proposes a novel approach to precisely estimate the image invariants and the rotation angles in the absence of the camera intrinsics, and to perform auto-calibration. By exploiting a special parameterization of the epipoles, it is shown that the imaged circular points can be formulated in terms of the image invariants. A fixed scalar κ, introduced to account for the different scales in the homogeneous representations of the image invariants used in the parameterizations, is found crucial in both calibration and motion estimation. Given the image invariants, namely the horizon, the imaged rotation axis and its orthogonal vanishing point, this scalar can be determined from the epipoles in an image triplet. A robust method for estimatingκ is proposed and the rotation angles can be recovered using this estimated value of κ. All the estimated variables are then refined using bundle-adjustment and auto-calibration is performed using the imaged circular points, the imaged rotation axis and the associated vanishing point. This allows the recovery of the full camera positions and orientations, and hence Euclidean reconstruction. Experimental results demonstrate the simplicity of this novel approach and the high precision in the estimated motion and reconstruction.
A clustering approach to filtering unfair testimonies for reputation systems

The problem of unfair testimonies remains an open issue in reputation systems for online trading communities. A common attempt is to use binary ratings to model sellers' reputation. However, this attempt leads to that the research of tackling unfair testimonies also focuses on reputation systems using binary ratings. In this extended abstract, we propose a two-stage clustering approach to filter unfair testimonies for reputation systems using multi-nominal ratings. The proposed approach uses clustering to identify unfair testimonies and further contributes to providing buyers a more accurate reputation evaluation regarding the target seller.
STeller: An approach for context-aware story detection using different similarity metrics and dense subgraph mining

The real-time information on the Web changes dynamically and surge quickly, which cause considerable difficulty in access to interested information. How to mine hot events, how to analyze the correlation of events and how to organize information structurally are challenging tasks. In this paper, to address these problems, we propose STeller, an approach to mine context-aware story - a series of correlated events. Firstly, we cluster similar pieces of information text into a meme-a piece of information and all its variants. This is also the process of information flow tracking. We view a meme as a fine-grained event. Then we use three novel efficient similarity metrics to measure content similarity and correlation of events. The social stream can be transformed into co-occurrence graph and we define the context-aware story as a novel dense subgraph type called (λ,d)-Clique. Lastly, two corresponding dense subgraph mining algorithms are developed to extract (λ,d)-Clique structure. We also perform detailed experiments on real news data and the results demonstrate the value of our work.
Deduction Dilemmas: The Taiwan Assignment Mechanism

This paper analyzes the Taiwan mechanism used nationwide for high school assignment starting in 2014. In the Taiwan mechanism, points are deducted from an applicant’s score, with larger penalties for lower-ranked choices. Deduction makes the mechanism a hybrid of the Boston and deferred acceptance mechanisms. Our analysis sheds light on why Taiwan’s new mechanism has led to massive nationwide demonstrations and why it nonetheless remains in use. (JEL D47, I21, I28)
Trace++: A Traceability Approach to Support Transitioning to Agile Software Engineering

Agile methodologies have been introduced as an alternative to traditional software engineering methodologies. However, despite the advantages of using agile methodologies, the transition between traditional and agile methodologies is not an easy task. There are several problems associated with the use of agile methodologies. Examples of these problems are related to (i) lack of metrics to measure the amount of rework that occurs per sprint, (ii) interruption of a project after several iterations, (iii) changes in the requirements, (iv) lack of documentation, and (v) lack of management control. In this paper we present Trace++, a traceability technique that extends traditional traceability relationships with extra information in order to support the transition between traditional and agile software development. The use of Trace++ has been evaluated in two real projects of different software development companies to measure the benefits of using Trace++ to support agile software development.
From the abstract to the concrete – Implementation of an innovative tool in home care

Background The implementation of innovations in practice is a critical factor for change and development processes in health and home care. We therefore analyze how an innovative tool – a mobility agreement to maintain physical mobility of home care clients – was implemented in Finnish home care. Methods Our study involves ethnographic research of 13 home care visits, two years after the mobility agreement was implemented. We analyze the emergence of contradictions, the motives of the actors and the use of artifacts supporting or inhibiting the implementation. Two in-depth cases illustrate the implementation of the mobility agreement in home care visits. Findings Our findings show that, first, to achieve practice change and development, the innovation implementation requires the overcoming of contradictions in the implementation process. Second, it calls for the emergence of a shared motive between the actors to transform the abstract concept of an innovation into a concrete practice. Third, artifacts, customary to the clients are important in supporting the implementation process. Fourth, the implementation brings about a modification of the innovation and the adopting social system. Conclusions Innovation implementation should be seen as a transformation process of an abstract concept into a concrete practice, enabled by the actors involved. Concept design and implementation should be closely linked. In health/home care innovation management, the implementation of innovations needs to be understood as a complex collective learning process. Results can be far reaching – in our case leading to change of home care workers’ professional understanding and elderly clients’ mobility habits.
An Improved IAMB Algorithm for Markov Blanket Discovery

Finding an efficient way to discover Markov blanket is one of the core issue s in data mining. This paper first discusses the problems existed in IAMB algorithm which is a typical algorithm for discovering the Markov b lanket of a target variable from the training dat a, and then proposes an improved algorithm λ -IAMB based on the improving approach which contains two aspects: code optimization and the improving strategy for conditional independence testing. E xperimental results show that λ -IAMB algorithm performs better than IAMB by finding Markov blanket of variables in typical Bayesian network and by testing the performance of them as feature selection method on some well-known real world datasets .
Approaches to heterogeneity in meta‐analysis

This paper reviews publications from January 1999 to March 2001 on reproductive health topics that were self‐identified as meta‐analysis or were indexed as meta‐analysis in MEDLINE. It sought to assess whether tests of statistical heterogeneity were done, whether the results were reported, and how a finding of significance for a test of statistical heterogeneity was handled and the results interpreted. The review identified some concerns. Tests of statistical heterogeneity were not done universally even though virtually all writers on the topic emphasize their importance. Even when done, results of these tests were not universally reported. Although the consensus appears to be that heterogeneity tests are conservative for meta‐analysis of studies and a probability value of 0.10 is preferred, many meta‐analyses used the conventional value of 0.05 without providing a reason. The rationale for the choice of a random or fixed effects model was not generally evident. The review also provided some positive models and some recommendations for assessing, reporting and exploring heterogeneity are made considering these models and the published recommendations of experts. Copyright © 2001 John Wiley & Sons, Ltd.
Bioincompatible Impact of Different Peritoneal Dialysis Fluid Components and Therapeutic Interventions as Tested in a Rat Peritoneal Dialysis Model

Peritoneal dialysis (PD) is associated with functional and structural changes of the peritoneal membrane. In this paper, we describe the impact of different factors contributing to peritoneal incompatibility of PD fluid installation including presence of a catheter, volume loading, and the PD fluid components itself. These factors initiate recruitment and activation of peritoneal immune cells such as macrophages and mast cells, as well as activation of peritoneal cells as mesothelial cells in situ. We provide an overview of PD-associated changes as seen in our rat PD-exposure model. Since these changes are partly reversible, we finally discuss therapeutic strategies in the rat PD model with possible consequences of long-term PD in the relevant human setting.
Refining Web authoritative resource by frequent structures

The Web resource is a rich collection of the dynamic information, which is useful in various disciplines. There has also been much research work related to improving the quality of information searching in the Web. However, most of the work is still inadequate to satisfy a diversified demand from users. In this paper, we exploit the hyperlinks in the Web and propose a new approach called SFP in order to improve the quality of research results obtain from search engines. The SFP algorithm evolves from the frequent pattern mining technique, which is a common data mining technique for conventional databases. The essential idea of our approach is to mine the frequent structures of links from a given Web topology. By using the SFP algorithm, we extract the authoritative pages and communities from the complex Web topology. We demonstrate our approach by running several experiments and show that the performance and functionalities of using the SFP in managing search results are better than other known methods such as HITS.
The effects of vitamin B12 deficiency on the cytoplasmic basophilia of rat tissues

In I-eccii t years, the employmeiit of ultraviolet microspect~opliotoiiictric methods, ultracexiti,ifuKatioii, iriicrocl~emical analysis and enzyme studies have led to tlic finding that tlie tilietorial basophilia cxhibitrd hy the cytopli~sin of rriwriy cells is due to thc presence of riuclcic acids. Tliis includes Sissl bodies of nerve cells (Bodian, '47; Gersh and Bodian, '4.7 ; Hyclh, '47), inclusion granules of li~reicclls (Claude, '43 ; Davidson mid Tl'apniouth, '44; Daridson, '47 ; Opie and Lavin, '46), basal chromophilic substance of the alveolar cells of the pancreas, salivary and mammary glaii~ls (Rrachet, '40 ; Dernpsty, Bunting a i d Wislocki, '47 ; Soback and Xontagna, '47), a i d thc basophilic granules of tlie pituitary and placenta (Deriipsey and TYislocki, '45). The amount of cytoplasmic rinclei acid (ribose nucleic acid; RNA) per cell is variable f o r different tissues. The following tissues a i ~ arranged in tlie order of amount of RNA/unit weight, weording to Rraehet ( '50a) : pancreas > intestinal and gastric imcosa > liver > spleen > lympli nodes > testis > kidney, muscle, heart, lung. As iiiiglit he cspected, microcliemic~al estimations closely approximate the visiblc basophilia of tliese tissues. T n a variet-\. of tissues studied by Davidson ('47), it was also found that them existed very little difference in the
European Conference on Information Systems ( ECIS ) 1-1-2008 Predicting SMEs Willingness to Adopt ERP , CRM , SCM & E-Procurement Systems

The attention of software vendors has moved recently to Small to Medium-sized Enterprises (SMEs) offering them a vast range of Enterprise Systems (ES) including ERP, CRM, SCM and E-Procurement systems, which were formerly adopted by large firms only. From reviewing the literature on the adoption and diffusion of Information Systems’ (IS) innovations, the question of ‘why some SMEs choose to adopt ES while seemingly similar others facing the same market conditions do not’ is still under-studied. This paper intends to fill this gap by developing a model that can be used to predict which SMEs are more likely to become adopters of ES. Using direct interviews, data was collected from 102 SMEs located in the Northwest of England. Logistic regression was used to analyse the data. Results reveal that factors influencing SMEs’ adoption of ES are different from factors influencing SMEs’ adoption of other previously studied IS innovations. SMEs were found to be more influenced by technological and organisational factors than environmental factors. Moreover, results indicate that firms with a greater perceived relative advantage, a greater ability to experiment with ES before adoption, a greater top management support, a greater organisational readiness and a larger size are predicted to become adopters of ES.
A feature-driven approach to locating optimal viewpoints for volume visualization

Optimal viewpoint selection is an important task because it considerably influences the amount of information contained in the 2D projected images of 3D objects, and thus dominates their first impressions from a psychological point of view. Although several methods have been proposed that calculate the optimal positions of viewpoints especially for 3D surface meshes, none has been done for solid objects such as volumes. This paper presents a new method of locating such optimal viewpoints when visualizing volumes using direct volume rendering. The major idea behind our method is to decompose an entire volume into a set of feature components, and then find a globally optimal viewpoint by finding a compromise between locally optimal viewpoints for the components. As the feature components, the method employs interval volumes and their combinations that characterize the topological transitions of isosurfaces according to the scalar field. Furthermore, opacity transfer functions are also utilized to assign different weights to the decomposed components so that users can emphasize features of specific interest in the volumes. Several examples of volume datasets together with their optimal positions of viewpoints are exhibited in order to demonstrate that the method can effectively guide naive users to find optimal projections of volumes.
oping with Islamophobia : The effects of religious stigma on Muslim inorities ’ identity formation

Islamophobic sentiments in the Western world have gained scientific attention, particularly after the terrorist attacks of September 11, 2001. However, the effects of religious stigma on Muslim minorities’ identity formation have rarely been studied. Using structural equation modeling, this cross-sectional study examined direct and indirect effects of different forms of religious stigma on the national affiliation of 210 Norwegian-Pakistani and 216 GermanTurkish Muslims. Furthermore, the study examined the mediator role of religious identity. Our results suggest that being a Muslim in Norway is more reconcilable with affiliating with the nation than being a Muslim in Germany. However, across the samples, the results indicated that various forms of religious stigma affected Muslims’ national identity and engagement in the public and private sphere in distinct ways. These effects were both positive and negative, differed between the two samples, and in Germany, were mediated by the participants’ religious identity. The findings indicated that the ways in which religious stigma influences Muslims’ national affiliation is context and culture bound. © 2012 Elsevier Ltd. All rights reserved.