Miracle-dz/UniFAR-FTUs huggingface dataset:
Insulin-like growth factor binding protein-1 as a predictor of glucose-stimulated hyperinsulinemia in prepubertal obese children.

OBJECTIVE The present study was undertaken to examine the association of a glucose-stimulated insulin response with the fasting insulin-like growth factor-binding protein (IGFBP)-1 concentration in prepubertal obese children. SUBJECTS AND METHODS The fasting levels of serum insulin and IGFBP-1 were measured in 17 obese and 16 control children. Furthermore, we performed an oral glucose tolerance test in obese children and examined the association of the area under the curve (AUC) for insulin with the fasting IGFBP-1 level. RESULTS The mean serum level of IGFBP-1 was significantly lower in obese children (41.0 +/- 4.8 micrograms/l. P < 0.005) than in controls (91.2 +/- 9.9 micrograms/l). Although there was an inverse relationship between the fasting levels of serum insulin and IGFBP-1 in all subjects (r = -0.42, P < 0.05), no significant correlation between these two parameters was observed in the obese group alone. In obese children, the fasting IGFBP-1 level correlated inversely with AUC-insulin (r = -0.70, P < 0.005), whereas there was no significant relationship between the fasting insulin level and AUC-insulin. CONCLUSION The present study suggests that the serum level of IGFBP-1 may be an early predictor of insulin resistance in prepubertal obesity.
Dynamics of Negation in the Identity Politics of Cultural Other and Cultural Self

This paper examines the findings of Shi-xu (1995) in terms of how texts that represent a cultural Other may be interpreted as a way of constructing a cultural self. Even when attempting to move beyond colonial and demeaning representations of the cultural Other, these western writers in fact construct a vision of the Other that signifies their own desires and values. Westerners construct their identity dialogically in the texts analyzed by Shi-xu, primarily by defining what the cultural Other is not. The frequency with which western writers define their identities through negations compounded with the demeaning images of the cultural Other points to the difficulty and challenge of constructing a post-colonial discourse and an affirming recognition of the cultural Other.
From Chaos to Safe Transformation: The Emotional Intelligence Learning Environment Model

Self-awareness is a necessary foundation for those seeking to develop emotional intelligence (EI). Yet, the process of developing self-awareness can be deeply disturbing, creating inner turmoil and chaos which EI trainers need to take into consideration and manage in the learning environment. This article describes the nature of this chaos and proposes a learning environment model to assist EI trainers in the design of their EI training programmes, helping trainers to create safe learning environments in which learners can pursue EI training, thereby leading to transformational change. A review of the literature defines EI, constructivism, and chaos theory, as well as exploring elements of a safe learning environment. The literature is considered along with data gathered from a recent study of twenty-one EI trainers in New Zealand, in an effort to identify key characteristics of a safe learning environment, and positive and negative qualities of the trainer and learners which can contribute to creating a safe learning environment. Based on these findings the Emotional Intelligence Learning Environment Model was developed. The article discusses the implications of the model and concludes with suggestions for future research.
Tutor–student interaction in seminar teaching: Implications for professional development

While much of the recent academic literature into university seminar teaching has focused on collaborative learning involving student–student interaction, little research has been done into tutor–student interaction and how tutors interact with students during whole class, group-based and one-to-one teaching. In response to this finding, this exploratory study investigates the quality of tutor–student interaction in the teaching of an undergraduate and postgraduate engineering management class taught by the same tutor. A third-year undergraduate class of home students and a 1-year masters largely made up of international students were observed, video- and audio-recorded and analysed using a systematic interactive observation schedule and lesson transcripts. The analysis of the tutor–student discourse moves revealed the talk was largely lecturer-fronted with an emphasis on knowledge transmission and that there were few differences in the discourse practices of the tutor when teaching home and international students. In the light of the findings, the article argues for more research to be conducted into how tutors can be helped to engage in more dialogic interactions with their students in whole class, group-based and one-to-one interactions to ensure they are given the opportunity to engage in intellectually stimulating classroom talk and deep learning. The implications of the findings for the professional development of university tutors are also considered.
A Hematogenously Disseminated Orientia tsutsugamsushi-Infected Murine Model of Scrub Typhus

Orientia tsutsugamushi, the etiologic agent of scrub typhus, is a mite-borne rickettsia transmitted by the parasitic larval stage of trombiculid mites. Approximately one-third of the world's population is at risk of infection with Orientia tsutsugamushi, emphasizing its importance in global health. In order to study scrub typhus, Orientia tsutsugamushi Karp strain has been used extensively in mouse studies with various inoculation strategies and little success in inducing disease progression similar to that of human scrub typhus. The objective of this project was to develop a disease model with pathology and target cells similar to those of severe human scrub typhus. This study reports an intravenous infection model of scrub typhus in C57BL/6 mice. This mouse strain was susceptible to intravenous challenge, and lethal infection occurred after intravenous inoculation of 1.25×106 focus (FFU) forming units. Signs of illness in lethally infected mice appeared on day 6 with death occurring ∼6 days later. Immunohistochemical staining for Orientia antigens demonstrated extensive endothelial infection, most notably in the lungs and brain. Histopathological analysis revealed cerebral perivascular, lymphohistiocytic infiltrates, focal hemorrhages, meningoencephalitis, and interstitial pneumonia. Disseminated infection of endothelial cells with Orientia in C57BL/6 mice resulted in pathology resembling that of human scrub typhus. The use of this model will allow detailed characterization of the mechanisms of immunity to and pathogenesis of O. tsutsugamushi infection.
A Custom Accelerator for Homomorphic Encryption Applications

After the introduction of first fully homomorphic encryption scheme in 2009, numerous research work has been published aiming at making fully homomorphic encryption practical for daily use. The first fully functional scheme and a few others that have been introduced has been proven difficult to be utilized in practical applications, due to efficiency reasons. Here, we propose a custom hardware accelerator, which is optimized for a class of reconfigurable logic, for Lopez-Alt, Tromer and Vaikuntanathan's somewhat homomorphic encryption based schemes. Our design is working as a co-processor which enables the operating system to offload the most compute-heavy operations to this specialized hardware. The core of our design is an efficient hardware implementation of a polynomial multiplier as it is the most compute-heavy operation of our target scheme. The presented architecture can compute the product of very-large polynomials in under 6.25 ms which is 102 times faster than its software implementation. In case of accelerating homomorphic applications; we estimate the per block homomorphic AES as 442 ms which is 28.5 and 17 times faster than the CPU and GPU implementations, respectively. In evaluation of Prince block cipher homomorphically, we estimate the performance as 52 ms which is 66 times faster than the CPU implementation.
The Added Worker Effect and Intrahousehold Aspects of Unemployment

The added worker effect states that unemployment of a household member leads to an increase in labour supply of another household member. This paper investigates whether there is such an effect in a developing country. We use a rich data set for urban Ethiopia. We first give a brief description of who is unemployed within the household and find that they are mostly related to the household head. Men are not more likely to be unemployed than women once we control for being family in law. The eldest remaining sons in the household are more likely to be unemployed, but this may be due to a selection bias. The oldest remaining unemployed have no higher job aspirations than their younger brothers, suggesting that if older brothers have more entitlements, waiting in unemployment for a good job is not one of them. We carry out two separate analyses to investigate the added worker effect. First we analyse the effect using actual labour supply and find no evidence for an added worker effect once we take unobserved individual effects into account. We then investigate whether there is an added worker effect using desired labour market participation and find that there is none. The combined evidence indicates that there is no added worker effect. This suggests that households have other ways to cope with unemployment and is consistent with results from previous analysis which shows that the use of savings (by selling assets) and consumption smoothing are important mechanisms to cope with unemployment.
Status in Organization and Management Theory

Status is a pervasive construct in the organizational literature, and a recent surge in interest in the topic testifies to its potential as a field of study. In this article, we review the existing studies on status, and we propose an integrative classification framework based on two distinct dimensions: the level of analysis—macro, meso, or micro—and the role status hierarchies play in extant research. We do so with a view to clarifying the status construct, differentiating it from the cognate concept of reputation, and clearly stating the ways in which status dynamics could inform organizational scholars and their research efforts. We conclude by highlighting underdeveloped theoretical intersections and suggesting potentially fruitful directions for future inquiry.
Single Nucleotide Variant rs2232710 in the Protein Z-Dependent Protease Inhibitor (ZPI, SERPINA10) Gene Is Not Associated with Deep Vein Thrombosis

Rare mutations in PROC, PROS1 or SERPINC1 as well as common variants in F5, F2, F11 and SERPINC1 have been identified as risk factors for deep vein thrombosis (DVT). To identify novel genetic risk factors for DVT, we have developed and applied next-generation DNA sequencing (NGS) of the coding area of hemostatic and proinflammatory genes. Using this strategy, we previously identified a single nucleotide variant (SNV) rs6050 in the FGA gene and novel, rare SNVs in the ADAMTS13 gene associated with DVT. To identify novel coding variants in the genetic predisposition to DVT, we applied NGS analysis of the coding area of 186 hemostatic and proinflammatory genes in 94 DVT cases and 98 controls and we identified 18 variants with putative role in DVT. A group of 585 Italian idiopathic DVT patients and 550 healthy controls was used to genotype all the 18 risk-associated variants identified by NGS. Replication study in the Italian population identified the rs2232710 variant in the protein Z-dependent protease inhibitor (ZPI) gene to be associated with an increased risk of DVT (OR 2.74; 95% CI 1.33–5.65; P = 0.0045; Bonferroni P = 0.081). However, the rs2232710 SNV showed no association with DVT in two Dutch replication cohorts the LETS study (454 patients and 451 controls) and the MEGA study (3799 patients and 4399 controls), indicating that the rs2232710 variant is not a risk factor for DVT.
Querying with Access Patterns and Integrity Constraints

Traditional query processing involves a search for plans formed by applying algebraic operators on top of primitives representing access to relations in the input query. But many querying scenarios involve two interacting issues that complicate the search. On the one hand, the search space may be limited by access restrictions associated with the interfaces to datasources, which require certain parameters to be given as inputs. On the other hand, the search space may be extended through the presence of integrity constraints that relate sources to each other, allowing for plans that do not match the structure of the user query. In this paper we present the first optimization approach that attacks both these difficulties within a single framework, presenting a system in which classical cost-based join optimization is extended to support both access-restrictions and constraints. Instead of iteratively exploring subqueries of the input query, our optimizer explores a space of proofs that witness the answering of the query, where each proof has a direct correspondence with a query plan.
Engaging Children Using a Digital Living Media System

Digital living media systems consist of living organisms combined with electronic components and can reflect or represent information to users (e.g., as an ambient display). We have developed, Rafigh, a digital living media system that utilizes the growth rate of a living mushroom colony to reflect users' digital application use. We used Rafigh to study how digital living media systems can 1) motivate children to use therapeutic and/or learning digital applications, and 2) increase communication and collaboration in the home setting. We conducted two in situ case studies with four children and their caregivers which showed that the system successfully motivated two of the children to use target applications and created communication and collaboration in the home setting. Additionally, the two children were not deterred by the slow changes in the system. We discuss the implications for using digital living media systems to engage and motivate children through dynamics of caring and responsibility.
Measurement models of factors influencing academic achievement and completion of tertiary studies

Studies involving both technical and further education (TAFE) students and university students have identified social integration, motivation and quality of teaching as important factors influencing non-completion and academic achievement. The aim of the current study was to develop and test a measurement model that captures these constructs in tertiary students. Questionnaire responses were collected from 165 TAFE marketing students and 148 university undergraduate psychology students. A three-factor independent cluster measurement model comprising latent factors for social integration, motivation and teaching was specified and tested using confirmatory factor analysis. While the three-factor model was found to fit the data well for the students from TAFE, contrary to expectations, this model was not valid for university students. The lack of congruence between the results may be partly due to the greater degree of skewness of the items comprising the motivation factor in the university cohort. A two-factor model comprising only the teaching and social integration factors was subsequently specified for the university sample and was found to have adequate fit. Further research is warranted to determine the extent to which the measure might be generalised to other tertiary student populations.
Influence Maximization in Human-Intervened Social Networks

Recently there has been tremendous research on influence analysis in social networks: how to find initial topics or users to maximize the word-of-mouth effect that may be significant for advertising, viral marketing and other applications. Many researchers focus on the problem of influence maximization on the static structure of the network and find a subset of early adopters which activate the influence diffusion across the network. Despite the progress in modeling and techniques, how the incentives improve the network structure to enlarge the influence diffusion has been largely overlooked. In this paper, we introduce a novel problem which extends the influence maximization to the situation that the network structure can be varied in case of some incentives such as fans trading by compensating the web users to be fans in social networks. Providing that the presented problem is NP-hard, we propose two approximate approaches to solve the problem of influence maximization in dynamic networks. The first is a two-stage approach which separates the problem into two sub problems and solves them respectively. The second is a joint influence diffusion algorithm so as to repair the network structure and find the corresponding initial subset of the individuals in the repaired social network simultaneously to maximize the influence. We performed experiments on social network data to provide evidence of the effectiveness of the proposed methods.
Multi-user MIMO with outdated CSI: Training, feedback and scheduling

Conventional MU-MIMO techniques, e.g. Linear Zero-Forced Beamforming (LZFB), require sufficiently accurate channel state information at the transmitter (CSIT) in order to realize spectral efficient transmission (degree of freedom gains). In practical settings, however, CSIT accuracy can be limited by a number of issues including CSI estimation, CSI feedback delay between user terminals to base stations, and the time/frequency coherence of the channel. The latter aspects of CSIT-feedback delay and channel-dynamics can lead to significant challenges in the deployment of efficient MU-MIMO systems. Recently it has been shown by Maddah-Ali and Tse (MAT) that degree of freedom gains can be realized by MU-MIMO even when the knowledge of CSIT is completely outdated. Specifically, outdated CSIT, albeit perfect CSIT, is known for transmissions only after they have taken place. This aspect of insensitivity to CSIT-feedback delay is of particular interest since it allows one to reconsider MU-MIMO design in dynamic channel conditions. Indeed, as we show, with appropriate scheduling, and even in the context of CSI estimation and feedback errors, the proposed MAT scheme can have performance advantages over conventional MU-MIMO in such scenarios.
Integrated Data Management and Analysis Environment for Medical Longitudinal Research with Machine Learning Based Prediction Models

In a longitudinal medical study, various types of data and biomaterial samples are collected in frequent intervals, and are used to analyze factors and pathways leading to a defined disease or a group of diseases. Large volume of complex data consisting of medical history and biochemical analysis results are typically collected in such studies.Our research shows that if the appropriate data model is co-designed with the research goals, it is possible to create a generalized model which allows integrating six tasks of the study: collecting, storing, managing, and analyzing data and samples, and introducing machine learning tools to create predictive models, which in turn assist in the previous tasks. We have implemented this model as a system, which integrates individual processes, minimizes human error, and conforms to changes in the study. This clearly improves the quality, interpretability, reliability and efficiency in understanding the development of the disease.
Big Data Small Data, In Domain Out-of Domain, Known Word Unknown Word: The Impact of Word Representations on Sequence Labelling Tasks

Word embeddings -- distributed word representations that can be learned from unlabelled data -- have been shown to have high utility in many natural language processing applications. In this paper, we perform an extrinsic evaluation of five popular word embedding methods in the context of four sequence labelling tasks: POS-tagging, syntactic chunking, NER and MWE identification. A particular focus of the paper is analysing the effects of task-based updating of word representations. We show that when using word embeddings as features, as few as several hundred training instances are sufficient to achieve competitive results, and that word embeddings lead to improvements over OOV words and out of domain. Perhaps more surprisingly, our results indicate there is little difference between the different word embedding methods, and that simple Brown clusters are often competitive with word embeddings across all tasks we consider.
Phonemes frequency based PLLR dimensionality reduction for language recognition

This paper presents a new approach to reduce the dimensionality of Phone Log likelihood Ratio (PLLR) features, which have been shown to be effective for language recognition, by removing the likelihoods corresponding to less frequent phonemes. In this work, phoneme frequencies are estimated using a suitable phoneme recogniser. Following this, an i-vector framework is used to represent the total variability in the reduced dimensional PLLR feature space. This paper also proposes the use of Gaussian probabilistic linear discriminant analysis (GPLDA) as a backend for Language Recognition Evaluation (LRE) tasks. The suitability of both, the proposed dimensionality reductions technique and the GPLDA back-end has been evaluated on NIST 2007 and 2011 LRE tasks. The results show that the novel dimensionality reduction method outperforms PCA based dimensionality reduction by 7%. Further the results also show that GPLDA outperform generatively trained Gaussian back-ends, which have previously been used in conjunction with PLLR feature, by 14.6%.
Platelet Activation Receptor CLEC-2 Regulates Blood/Lymphatic Vessel Separation by Inhibiting Proliferation, Migration, and Tube Formation of Lymphatic Endothelial Cells*

Background: Mice deficient in the platelet receptor CLEC-2 for podoplanin showed impaired blood/lymphatic vessel separation. Results: Functions of lymphatic endothelial cells are inhibited by platelet releasates and BMP-9, which we identified as a novel releasate. Conclusion: Granule contents including BMP-9 released upon platelet activation by CLEC-2-podoplanin interaction may contribute to the separation in vivo. Significance: We proposed a novel mechanism of platelet-mediated blood/lymphatic vessel separation. The platelet activation receptor CLEC-2 plays crucial roles in thrombosis/hemostasis, tumor metastasis, and lymphangiogenesis, although its role in thrombosis/hemostasis remains controversial. An endogenous ligand for CLEC-2, podoplanin, is expressed in lymphatic endothelial cells (LECs). We and others have reported that CLEC-2-deficiency is lethal at mouse embryonic/neonatal stages associated with blood-filled lymphatics, indicating that CLEC-2 is essential for blood/lymphatic vessel separation. However, its mechanism, and whether CLEC-2 in platelets is necessary for this separation, remains unknown. We found that specific deletion of CLEC-2 from platelets leads to the misconnection of blood/lymphatic vessels. CLEC-2+/+ platelets, but not by CLEC-2−/− platelets, inhibited LEC migration, proliferation, and tube formation but had no effect on human umbilical vein endothelial cells. Additionally, supernatants from activated platelets significantly inhibited these three functions in LECs, suggesting that released granule contents regulate blood/lymphatic vessel separation. Bone morphologic protein-9 (BMP-9), which we found to be present in platelets and released upon activation, appears to play a key role in regulating LEC functions. Only BMP-9 inhibited tube formation, although other releasates including transforming growth factor-β and platelet factor 4 inhibited proliferation and/or migration. We propose that platelets regulate blood/lymphatic vessel separation by inhibiting the proliferation, migration, and tube formation of LECs, mainly because of the release of BMP-9 upon activation by CLEC-2/podoplanin interaction.