Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlations of Pituitary Tumor Transforming Gene Expression with Human Pituitary Adenomas: A Meta-Analysis

Objective Pituitary tumor transforming gene (PTTG) is an important paracrine growth factor involved in early lactotrope transformation and early onset of angiogenesis in pituitary hyperplasia. Emerging evidences have shown that PTTG expression may contribute to the etiology of pituitary adenomas; but individually published studies showed inconclusive results. This meta-analysis aimed to derive a more precise estimation of the correlations of PTTG expression with human pituitary adenomas. Methods A range of electronic databases were searched: MEDLINE (1966∼2013), the Cochrane Library Database (Issue 12, 2013), EMBASE (1980∼2013), CINAHL (1982∼2013), Web of Science (1945∼2013) and the Chinese Biomedical Database (CBM) (1982∼2013) without language restrictions. Meta-analysis was performed using the STATA 12.0 software. Crude odds ratio (OR) or standard mean difference (SMD) with its corresponding 95% confidence interval (95%CI) were calculated. Results Twenty-four clinical cohort studies were included with a total of 1,464 pituitary adenomas patients. The meta-analysis results revealed that patients with invasive pituitary adenomas had higher positive expression of PTTG than those of non-invasive patients (OR = 6.68, 95%CI = 3.72–11.99, P<0.001). We also found a significant difference in microvessel density between invasive and non-invasive patients (SMD = 1.81, 95%CI = 0.39–3.23, P = 0.013). However, there were no significant difference in PTTG expression between functional and non-functional patients with pituitary adenomas (OR = 1.11, 95%CI = 0.58–2.10, P = 0.753). No publication bias was detected in this meta-analysis (all P>0.05). Conclusion This present meta-analysis suggests that PTTG expression may be associated with tumor invasiveness and microvessel density of pituitary adenomas, while no correlations with functional status was found.
Concentrated Language Encounter Approach in Practice for Global Teaching of Literacy: Lighthouse Strategy Implementation.

This article presents the lighthouse literacy strategies model using the concentrated language encounter (CLE) approach that has been successfully replicated in many countries in different languages and cultures. A review of CLE research studies and the project implementation in Thailand showed highly significant results in students’ literacy skill improvement. The theoretical bases were derived from the research on language education in Australia with aboriginal children. Through the implementation program in Thailand, three CLE models/stages in teaching language and a specific ‘train the trainers’ program were developed at different levels of literacy skills. Four different types of CLE literacy programs that include formal, informal, special education, and ethnic groups were successfully implemented.
Comparing the Performance of NoSQL Approaches for Managing Archetype-Based Electronic Health Record Data

This study provides an experimental performance evaluation on population-based queries of NoSQL databases storing archetype-based Electronic Health Record (EHR) data. There are few published studies regarding the performance of persistence mechanisms for systems that use multilevel modelling approaches, especially when the focus is on population-based queries. A healthcare dataset with 4.2 million records stored in a relational database (MySQL) was used to generate XML and JSON documents based on the openEHR reference model. Six datasets with different sizes were created from these documents and imported into three single machine XML databases (BaseX, eXistdb and Berkeley DB XML) and into a distributed NoSQL database system based on the MapReduce approach, Couchbase, deployed in different cluster configurations of 1, 2, 4, 8 and 12 machines. Population-based queries were submitted to those databases and to the original relational database. Database size and query response times are presented. The XML databases were considerably slower and required much more space than Couchbase. Overall, Couchbase had better response times than MySQL, especially for larger datasets. However, Couchbase requires indexing for each differently formulated query and the indexing time increases with the size of the datasets. The performances of the clusters with 2, 4, 8 and 12 nodes were not better than the single node cluster in relation to the query response time, but the indexing time was reduced proportionally to the number of nodes. The tested XML databases had acceptable performance for openEHR-based data in some querying use cases and small datasets, but were generally much slower than Couchbase. Couchbase also outperformed the response times of the relational database, but required more disk space and had a much longer indexing time. Systems like Couchbase are thus interesting research targets for scalable storage and querying of archetype-based EHR data when population-based use cases are of interest.
Sequential information bottleneck for finite data

The sequential information bottleneck (sIB) algorithm clusters co-occurrence data such as text documents vs. words. We introduce a variant that models sparse co-occurrence data by a generative process. This turns the objective function of sIB, mutual information, into a Bayes factor, while keeping it intact asymptotically, for non-sparse data. Experimental performance of the new algorithm is comparable to the original sIB for large data sets, and better for smaller, sparse sets.
Reformulation Behavior

Current multimedia Web search engines still use keywords as the primary means to search. Due to the richness in multimedia contents, general users constantly experience some difficulties in formulating textual queries that are representative enough for their needs. As a result, query reformulation becomes part of an inevitable process in most multimedia searches. Previous Web query formulation studies did not investigate the modification sequences and thus can only report limited findings on the reformulation behavior. In this study, we propose an automatic approach to examine multimedia query reformulation using large-scale transaction logs. The key findings show that search term replacement is the most dominant type of modifications in visual searches but less important in audio searches. Image search users prefer the specified search strategy more than video and audio users. There is also a clear tendency to replace terms with synonyms or associated terms in visual queries. The analysis of the search strategies in different types of multimedia searching provides some insights into user’s searching behavior, which can contribute to the design of future query formulation assistance for keyword-based Web multimedia retrieval systems.
Retrospective intermodality registration techniques for images of the head: surface-based versus volume-based

A blinded evaluation of two groups of retrospective image registration techniques was performed using as a gold standard a prospective marker-based registration method, and we compared the performance of one group with the other. By grouping the techniques as volume-based or surface-based, we could make some interesting conclusions. In order to ensure blindness, all retrospective registrations were performed by participants who had no knowledge of the gold-standard results until after their results had been submitted. Image volumes of three modalities (X-ray CT, MRI and PET) were obtained from patients undergoing neurosurgery on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to outside collaborators, who then performed retrospective registrations on the volumes, calculating transformations from CT to MRI and/or from PET to MRI. The accuracy of each registration was then evaluated. The accuracy is measured at multiple volumes of interest. The volume-based techniques in this study tended to give substantially more accurate and reliable results than the surface-based ones for the CT-to-MRI registration tasks, and slightly more accurate results for the PET-to-MRI tasks. Analysis of these results revealed that the rotational component of error was more pronounced for the surface-based group. It was also apparent that all of the registration techniques we examined have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.
Geometric programming for aggregation of binary classifiers

Multiclass classification problems are often decomposed into multiple binary problems that are solved by individual binary classifiers whose results are integrated into a final answer. We present a convex optimization-based method for aggregating results of binary classifiers in an optimal way to estimate class membership probabilities. We model the class membership probability as a softmax function whose input argument is a conic combination of discrepancies induced by individual binary classifiers. With this model, we formulate the ℓ1-regularized maximum likelihood estimation as a convex optimization that is solved by geometric programming. Numerical experiments on several UCI datasets demonstrate the high performance of our method, compared to existing methods.
Semi-Supervised Nonlinear Distance Metric Learning via Forests of Max-Margin Cluster Hierarchies

Metric learning is a key problem for many data mining and machine learning applications, and has long been dominated by Mahalanobis methods. Recent advances in nonlinear metric learning have demonstrated the potential power of non-Mahalanobis distance functions, particularly tree-based functions. We propose a novel nonlinear metric learning method that uses an iterative, hierarchical variant of semi-supervised max-margin clustering to construct a forest of cluster hierarchies, where each individual hierarchy can be interpreted as a weak metric over the data. By introducing randomness during hierarchy training and combining the output of many of the resulting semi-random weak hierarchy metrics, we can obtain a powerful and robust nonlinear metric model. This method has two primary contributions: first, it is semi-supervised, incorporating information from both constrained and unconstrained points. Second, we take a relaxed approach to constraint satisfaction, allowing the method to satisfy different subsets of the constraints at different levels of the hierarchy rather than attempting to simultaneously satisfy all of them. This leads to a more robust learning algorithm. We compare our method to a number of state-of-the-art benchmarks on $k$-nearest neighbor classification, large-scale image retrieval and semi-supervised clustering problems, and find that our algorithm yields results comparable or superior to the state-of-the-art.
Reflective verbalization improves solutions: The effects of question-based reflection in design problem solving

SUMMARY In this experimental study (N ¼ 60), the impact of question-based reflective verbalization on the quality of a design solution was investigated. Participants first designed an everyday object (garden grill) using various design strategies and then either answered questions of a naive partner, where they had to verbally describe, explain, justify and evaluate their solution (experimental group), or were given a filler task (control group). After the intervention, participants continued their design. The improvement in the design quality was significantly larger for the experimental group than for the control group. Significantly more participants of the experimental group developed new principles and added new explanations of functions to their design, whereas in the control group only corrections were made. We suggest that the dialogue specific style of reflective verbalization in the experimental group is linked to a specific way of thinking which is important for solving complex problems. Copyright # 2004 John Wiley & Sons, Ltd. Design problems are highly complex and often ill-defined. The structure of a new object that fulfils specific functions has to be developed on the basis of a specification that is often not clear. In addition, there are many possibilities to meet the specification.
ACCELERATED READER AND ITS EFFECT ON FIFTH-GRADE STUDENTS' READING COMPREHENSION

Jan Shelton Nichols. ACCELERATED READER AND ITS EFFECT ON FIFTHGRADE STUDENTS’ READING COMPREHENSION. School of Education, March, 2013. Schools in the United States have been using the Accelerated Reader (AR) program since the mid-1980s. A search of the literature related to the effectiveness of the AR program revealed that many of the studies were conducted more than a decade ago, and a large number of those studies failed to utilize a control group to provide comparative data. Researchers and educators have examined the use of the AR program, whose parent company is Renaissance Learning, for more than 20 years, yet there is still little definitive data on whether the system positively affects student reading comprehension and motivation to read. This causal-comparative design, in the form of an ex post facto study, examined two groups of fifth-grade students to determine if the addition of AR showed statistically significant effects on their reading comprehension. Data were gathered from both an experimental and a control group; the control group utilized the school system’s literacy plan for reading instruction, while the experimental group utilized the literacy plan along with mandatory use of AR. Independent t-tests were used to determine if the treatment (AR) had any effect on reading comprehension by group or by gender. The results from the independent t-tests showed no statistically significant effect for reading method by group and no statistically significant effect for gender by group. Copyright © 2013 by Jan Shelton Nichols
Correlates of orthographic learning in third‐grade children's silent reading

This study examined word identification, phonological recoding efficiency, familiar word reading efficiency, orthographic choice for familiar words and serial naming speed as potential correlates of orthographic learning following silent reading in third-grade children. Children silently read a series of short stories, each containing six repetitions of a different target non-word. They subsequently read target non-words faster than homophones and preferred target non-words to homophones in an orthographic choice task, indicating that they had formed functional orthographic representations of the target non-words through phonologically recoding them during silent story reading. Target non-word orthographic choice was correlated with all measures bar non-symbol naming speed. The association between phonological recoding efficiency and orthographic learning lends support to the hypothesis that self-teaching occurs through phonological recoding even in silent reading. Our findings were not generally consistent with the view that serial naming speed assesses orthographic learning aptitude.
Novel Organic Membrane-based Thin-film Microsensors for the Determination of Heavy Metal Cations

A first step towards the fabrication and electrochemical evaluation of thin-film microsensors based on organic PVC membranes for the determination of Hg(II), Cd(II), Pb(II) and Cu(II) ions in solutions has been realised. The membrane-coating mixture used in the preparation of this new type of microsensors is incorporating PVC as supporting matrix, o-nitrophenyloctylether (o-NPOE) as solvent mediator and a recently synthesized Hg[dimethylglyoxime(phene)]2+ and Bis-(4-hydroxyacetophenone)-ethylenediamine as electroactive materials for Hg(II) and Cd(II), respectively. A set of three commercialised ionophores for Cd(II), Pb(II) and Cu(II) has been also used for comparison. Thin-film microsensors based on these membranes showed a Nernstian response of slope (26-30 mV/dec.) for the respective tested cations. The potentiometric response characteristics (linear range, pH range, detection limit and response time) are comparable with those obtained by conventional membranes as well as coated wire electrodes prepared from the same membrane. The realisation of the new organic membrane-based thin-film microsensors overcomes the problem of an insufficient selectivity of solid-state-based thin-film sensors.
Send Orders of Reprints at Reprints@benthamscience.org Manipulating Task Constraints in Small-sided Soccer Games: Performance Analysis and Practical Implications

Since an awareness of key task constraints can be extremely beneficial for coaches, the lack of scientific background about the effects of altered game rules/conditions on individual or team performances during soccer practice is surprising. The aim of the present study was to analyze the influence of different small-sided game (SSG) playing rules (" free-form " , " two touches " and " four passes to score ") on the offensive performance of young soccer players. Eight U-13 male soccer players were divided into two balanced teams. The experimental protocol consisted of three testing sessions separated by one-week intervals. In each session, teams faced each other in the three SSG conditions (3vs.3+goalkeepers) during periods of ten minutes interspersed with five minutes of passive recovery.Shots) performance indicators were used to characterize the offensive performance of both teams. Results revealed that the factor " playing rule " had a significant effect on simple and composite indicators (p<0.05). It was concluded that manipulating task constraints, such as game rules, can direct practitioners towards intended behaviors , and consequently promote skill acquisition and improve performance in youth soccer. Further research is needed to extend the knowledge about the modification of playing rules in team sports practice.
Automated Taxonomy Generation for Summarizing Multi-Type Relational Datasets

Taxonomy construction provides an efficient navigating and browsing mechanism to people by organizing large amounts of information into a small number of hierarchical clusters. Compared with manually editing taxonomies, Automated Taxonomy Generation has numerous advantages and has therefore been applied to categorize document collections. However, the utility of this technique to organize and represent relational datasets has not been investigated, because of its unaffordable computational complexity. In this paper we propose a new ATG method based on the relational clustering framework DIVA. By incorporating the idea of Representative Objects, the computational complexity can be greatly reduced. Moreover, we analyze the divergence of the data attributes and label the taxonomic nodes accordingly. The quality of the derived taxonomy is quantitatively evaluated by a synthesized criterion that considers both the intra-node homogeneity and inter-node heterogeneity. Theoretical analysis and experimental results prove that our approach is comparably effective and more efficient than other ATG algorithms.
Writing for Publication and the Role of the Library: “Do Have a Cow, Man!” (“Don't Have a Cow, Man”-Bart Simpson)

The aim of this small-scale research project was to identify the main concerns of editors, academics, researchers, and librarians involved in the writing for publication (WfP) process. This would provide library and information services (LIS) staff with a clearer understanding of the process to enable them to articulate and develop their own role in supporting this activity. A novel “one thing” approach was used to determine the perspectives of editors, researchers, librarians, and research students on key issues surrounding WfP. The results indicate that there are many opportunities for LIS staff to contribute to the WfP process. One major concern which emerged was just how isolated researchers could feel. Suggestion: Having a CoW (Community of Writers) in the library could provide a potential LIS role. Another best practice to support WfP is also identified.
Reconceptualizing Research and Scholarship in Educational Administration: Learning to Know, Knowing to Do, Doing to Learn

In this article, the authors explore common and emerging conceptions of what consti-tutes knowledge in educational administration, how knowledge relates to practice, and how individuals in universities and schools can engage in a particular kind of knowledge work—research. The authors suggest that a fully articulated perspective on research in educational administration might characterize research as occupying a multidimen-sional space delineated along three dimensions: why the research is done, who conducts the research, and how the research is done. Productive, interesting, and generative research can be situated anywhere on these dimensions, and five principles can be used to guide various forms of research. The implication is that although currently the field of educational administration encompasses two communities of practice, we should strive toward becoming one community of scholars. The authors discuss how doctoral pro -grams might develop students for this community of scholars and provide a case example from one university.
Reconciling Multiple Researcher Positionalities and Languages in International Research

Through the development of a set of ideas combining Merton's conceptions of the ‘Insider and Outsider’ with Lacan's notions of identity construction, the article examines: (1) the role of multiple researcher identities and positionalities, and (2) working in more than one language during data collection and analysis. The article aims to fill a surprising gap in existing literature on such issues in international educational research. Through a reflexive exercise on the fieldwork and data analysis process in one study, the article puts forward the concept of ‘currencies’ as a way to mediate researcher positionality and achieve temporary shared positionalities with research participants. It also highlights the need to mediate different languages during data analysis and presentation, introducing the concept of ‘analytic languages’ as a potentially useful construct in doing so.
The hypoxia‐induced dehydrogenase HorA is required for coenzyme Q10 biosynthesis, azole sensitivity and virulence of Aspergillus fumigatus

Aspergillus fumigatus is the predominant airborne pathogenic fungus causing invasive aspergillosis in immunocompromised patients. During infection A. fumigatus has to adapt to oxygen‐limiting conditions in inflammatory or necrotic tissue. Previously, we identified a mitochondrial protein to be highly up‐regulated during hypoxic adaptation. Here, this protein was found to represent the novel oxidoreductase HorA. In Saccharomyces cerevisiae a homologue was shown to play a role in biosynthesis of coenzyme Q. Consistently, reduced coenzyme Q content in the generated ΔhorA mutant indicated a respective function in A. fumigatus. Since coenzyme Q is involved in cellular respiration and maintaining cellular redox homeostasis, the strain ΔhorA displayed an impaired response to both oxidative and reductive stress, a delay in germination and an accumulation of NADH. Moreover, an increased resistance against antifungal drugs was observed. All phenotypes were completely reversed by the addition of the synthetic electron carrier menadione. The deletion strain ΔhorA showed significantly attenuated virulence in two murine infection models of invasive pulmonary aspergillosis. Therefore, the biosynthesis of coenzyme Q and, particularly, the fungal‐specific protein HorA play a crucial role in virulence of A. fumigatus. Due to its absence in mammals, HorA might represent a novel therapeutic target against fungal infections.