Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing a Culture to Facilitate Research Capacity Building for Clinical Nurse Consultants in Generalist Paediatric Practice

This paper reports a research capacity building exercise with a group of CNCs practicing in the speciality of paediatrics in New South Wales (NSW), Australia. It explores the first step in building a research culture, through identifying the research priorities of members of the NSW Child Health Networks Paediatric Clinical Nurse Consultant group, and this forms the major focus of this paper. A nominal group technique (NGT) was utilised with sixteen members to identify research topics for investigation which were considered a priority for improving children's health care. The group reviewed and prioritised 43 research topics in children's health which were identified in the literature. As a result of conducting this research prioritisation exercise, the group chose two research topics to investigate: reasons for children representing to the Emergency Department and a comparison of the use of high-flow and low-flow nasal prongs in children with bronchiolitis. The research team will continue to mentor the nurses throughout their research projects which resulted from the NGT. One bridge to leadership development in enhancing patient care is translating knowledge to practice and policy development. This study leads the way for a group of CNCs in paediatric nursing to combine their research capacity and influence clinical knowledge.
Toward Estimating Others' Transition Models Under Occlusion for Multi-Robot IRL

Multi-robot inverse reinforcement learning (mIRL) is broadly useful for learning, from observations, the behaviors of multiple robots executing fixed trajectories and interacting with each other. In this paper, we relax a crucial assumption in IRL to make it better suited for wider robotic applications: we allow the transition functions of other robots to be stochastic and do not assume that the transition error probabilities are known to the learner. Challenged by occlusion where large portions of others' state spaces are fully hidden, we present a new approach that maps stochastic transitions to distributions over features. Then, the underconstrained problem is solved using nonlinear optimization that maximizes entropy to learn the transition function of each robot from occluded observations. Our methods represent significant and first steps toward making mIRL pragmatic.
Synthesis of a HDC-GFP Promoter-Gene Fusion as a Tool to Identify Histaminergic Cells and Examine HDC Regulation

The promoter region for the Histidine decarboxylase gene (pHdc), which is required for synthesis of the neurotrans-mitter histamine, has been functionally identified in Drosophila melanogaster. A fusion between pHdc and the enhanced Green Fluorescent Protein (eGFP) has been made in a plasmid that will allow generation of transformant flies. These transgenic flies containing the pHdc-eGFP gene fusion can be studied to determine whether the pHdc region causes expression of enhanced Green Fluorescent Protein (eGFP) in hista-minergic cells. This research will allow further analysis of the HDC promoter and be a useful tool for examining the physiology of histaminergic cells. Introduction Histamine is a biogenic amine involved in local immune responses, and it acts as a neurotransmitter (Brown et al., 2001). Histamine is synthesized by the decar-boxylation of the amino acid histidine, catalyzed by the enzyme histidine decarboxylase. In the fruitfly Drosophila melanogaster, histamine is utilized as a functional neurotransmitter for photore-ceptor and mechanosensory cells, but has also been localized by immunocytochem-istry to a few specific cells in the brain The Hdc gene, which codes for this enzyme, has been identified and studied in Drosophila, a model organism well-suited for genetic studies. Mutations in the Hdc gene have been isolated which disrupt function, indicating what the absence of histamine does to the organism. Hdc mutations cause flies to be functionally blind, in addition to other sensory alterations (Burg et al., 1993; Melzig et al., 1996). To further investigate the regulation of the Hdc gene and how expression may be altered throughout development, the Hdc promoter region was identified through a combination of sequence analysis, deletion mapping, and 5' RACE experiments (Sambrook et al., 1989). Through the analysis of deletions constructed in the Hdc promoter region, it was possible to separate the expression of Hdc in photoreceptors from expression in the brain (Burg and Pak, 1996). Recent experiments have identified novel 5' ends of the Hdc cDNA which do coincide with the deletion analysis results, suggesting that the transcriptional promoter for brain Hdc expression is unique from the identified photoreceptor Hdc promoter (M. Burg and S. Smolin-ski, pers.commun.). While deletions in a promoter region can identify regions necessary to guide expression in various tissue types, they cannot identify areas that are sufficient alone for Hdc expression. One method that has been used extensively in promoter analysis studies in Drosophila
Design and implementation of resource management network of constrained device

As sensor networks, embedded and wireless communication technology is constantly developing mature, more and more equipment accesses to the Internet of things. However, most of the Internet of Things equipment called constrained device is limited by its power, memory and CPU. These devices are usually small in size, inexpensive, and have low power consumption. In this article, we propose a new architecture named RMN (Resource Management Network) for constrained device based on Constrained Application Protocol (CoAP). The architecture provides a decentralized peer-to-peer resource management overlay network. It defines the constrained device resource model, designs the methods of resource interaction between user and device and build efficient resource management network. By using the model, the system of IoT devices can be optimized effectively.
A Preliminary Validation Study of the Korean Version of the Minnesota Self-Determination Scales for Adults With Intellectual Disabilities

The Minnesota Self-Determination Scale (MSDS) was translated into Korean. The Korean version was then validated using a sample of 40 individuals with intellectual disabilities between the ages of 19 and 45 years, the legal age of adults in South Korea. The evidence of the reliability and validity was examined. The test–retest was good (.84-.94). The internal consistency was excellent (.96-.99). The construct validity with other Korean translated self-determination measure (K-SDS) was acceptable (.50-.51). The findings indicated that the K-MSDS was an appropriate measure with acceptable psychometric properties. The Korean version was the first self-determination measure for adults with disabilities.
Challenges in Molecular Diagnostics of Channelopathies in the Next-Generation Sequencing Era: Less Is More?

Inherited arrhythmogenic diseases (IADs – also called cardiac channelopathies) are defined as a group of genetic diseases characterized by electrically unstable substrate in a structurally normal heart (1). Genetic testing in cardiac channelopathies has completed its transition from a research-based activity to that of a clinical genetic service. In parallel, the advancements of the sequencing technologies are providing ways to sequence several genes at a relatively low cost. This is progressively changing the approach to the genetic diagnosis of IADs. Indeed, while Sanger-based genetic testing was traditionally limited to the well characterized, most prevalent genes, next-generation sequencing (NGS) allows screening even the “minor” disease genes with very short turnaround time. This approach to genetic testing is highly efficient, but it is also generating remarkable interpretative problems mostly related to the high prevalence of variants of unknown significance (VUS), i.e., not clearly related to disease pathophysiology. This issue is relevant to several genetic diseases of the heart but is particularly evident in IADs, where the familial co-segregation analysis is hampered by the incomplete penetrance and the variable expressivity. How to design the most appropriate screening approach is challenging and it requires in-depth knowledge of the specific diseases of interest. In this Opinion article, we will review the available NGS approaches and try to outline the available strategies to optimize the performance of this genetic testing methodology.
An Introduction to Implicit Attitudes in Political Science Research

During the past two decades, mounting evidence suggests that much of human social cognition occurs without deliberate effort and largely outside conscious awareness. Dual-process models, which distinguish explicit (conscious, slow, effortful) cognitive processes from implicit (often unconscious, fast, effortless) cognitive processes, “form the dominant paradigm [of social cognition research] for the past 20 years or more” (Evans 2008). Although these advances in social cognition research have begun to be integrated into models of political cognition over the past decade (e.g., Kim, Taber, and Lodge 2010; Lodge and Taber 2013; see Nosek, Graham, and Hawkins 2010 for a review), and are beginning to influence other disciplines like communication (see Hefner et al. 2011), the role of implicit processes in outcomes commonly studied by political scientists deserves more attention. This symposium aims to showcase the diverse set of subject areas within political science to which dual-process models have been and can be applied. We hope that this symposium is a springboard for those who are considering bringing a dual-process approach into their own research by providing an overview of relevant literatures and methods.
Infrastructure analysis from high resolution SAR and InSAR imagery

In this paper, we present a methodology for the extraction of building dimensions from high resolution SAR and 3-d (InSAR) imagery. For flat and sloping roof buildings we show how differing imaging geometries produce fundamental limitations on the structural information that may be obtained. The procedure is applied real imagery and initial results are discussed.
Identification of new potential allergens from Nile perch (Lates niloticus) and cod (Gadus morhua).

BACKGROUND Globalization of the food industry has led to widespread exposure to new nondomestic fish species; therefore, identification of potential allergens is necessary in order to diagnose allergic reactions. OBJECTIVE Contact with a patient who was allergic to Nile perch (Lates niloticus) prompted us to investigate the immunoglobulin (Ig) E-reactive proteins that could be allergens of this species. METHODS 2D gel electrophoresis was used to separate the muscle proteins of L niloticus and Gadus morhua. Immunoblotting was performed with sera from 12 patients with a history of immediate-type allergic reaction to fish and from atopic and nonatopic controls. IgE-reactive proteins were detected and identified using mass spectrometry. RESULTS The index patient had low levels of IgE binding to parvalbumins. However, 8 putative allergens other than parvalbumin from L niloticus and 5 from G morhua were identified. Further investigation revealed cross-sensitivity to enolase 3 from L niloticus in 7 of the 12 fish-allergic individuals (58%), whereas 11 of the 12 patients (92%) were sensitized to enolase 3 from G morhua. However, atopic control patients were also sensitized to enolase 3 from L niloticus and G morhua. CONCLUSION Identification of species-specific allergens and individual sensitization could help us to improve avoidance strategies.
Asymptomatic Hyperlactataemia: Predictive Value, Natural History and Correlates

Background The significance of asymptomatic hyperlactataemia is unknown. Methods We measured serial lactate levels in a group of HIV-infected subjects. Objectives were to identify covariates associated with hyperlactataemia, and to explore the natural history of hyperlactataemia. Results Overall, 1487 lactate measurements were performed on 396 subjects; 299 subjects had serial lactate testing, with a median of four performed per patient (range: 2–16). At study entry, lactate was >2.4 mmol/l in 6% of subjects and >3.6 mmol/l in 1%. A multiple logistic regression analysis revealed that cholesterol and current stavudine were the only predictors of hyperlactataemia. Lactate levels were highly reproducible both for short-term (within 3 months) and long-term (>1 year) follow-up. During the study period, 16 subjects were identified with sustained hyperlactataemia; 12/16 remained asymptomatic after a median of 210 days (30–585), and four developed symptoms suggestive of lactic acidosis syndrome. In three of the four, asymptomatic hyperlactataemia had preceded the onset of symptoms by 18–122 days. A longitudinal model showed a rapid rise of lactate levels from 0 to 12 months on nucleoside reverse transcriptase inhibitor (NRTI) and then stabilization. Lactate levels did not correlate with baseline or on-study development of lipoatrophy. Conclusions Even when optimal methods of collection are used, asymptomatic hyperlactataemia does exist and could be sustained in a subset of NRTI-treated subjects for as long as 585 days. A subset of these subjects became symptomatic, after as long as 122 days of asymptomatic hyperlactataemia. Asymptomatic hyperlactataemia is not predictive of lipoatrophy. This work was partly presented at the 9th Conference on Retroviruses & Opportunistic Infections. Seattle, Wash. , USA, February 2002.
The quality of well-being scale: Comparison of the interviewer-administered version with a self-administered questionnaire

Abstract The Quality of Well-being Scale (QWB) is a general measure of health-related quality of life that has been used in a wide variety of population and clinical studies. One of the major disadvantages of the QWB is that it requires a trained interviewer. Recently, a self-administered version of the QWB was developed. The purpose of this study was to compare the self-administered QWB with the established interviewer-administered form. The respondents were 218 English speaking adults who attended primary care clinics. Each respondent was evaluated twice with an interval of one month in-between. At each session respondents were randomly assigned to complete either the interviewer-administered or self-administered QWB, resulting in a 2 × 2 factorial design. Data from the study demonstrated that the self-administered QWB yields scores equivalent to the interviewer-administered form. Further, QWB scores remain stable over the course of a one month interval. The results suggest that an inexpensive self-admi.
PTSD and Pregaming in College Students: A Risky Practice for an At-Risk Group

ABSTRACT Background: College students with trauma exposure and PTSD are at risk for problem drinking. This may include more specific hazardous drinking practices such as pregaming (drinking prior to a social event), which is linked to increased alcohol-related consequences. Objectives: The present study examined the association between pregaming and alcohol consequences and the role of trauma exposure and PTSD in predicting pregaming and alcohol-related consequences in a sample of college students using Multilevel Structural Equation Modeling (MSEM). We also assessed specific risk associated with PTSD relative to trauma exposure alone in relation to our outcomes. Methods: Participants were categorized into groups based on trauma exposure and PTSD symptoms via diagnostic interview: (1) No Trauma, those who had not experienced a Criterion A trauma; (2) Trauma Only, those who experienced a Criterion A trauma but did not currently have PTSD; and (3) PTSD, those with current full or partial PTSD related to a Criterion A trauma. Alcohol consumption and related consequences also were measured via interview (TLFB, B-YAACQ). Results: For all participants, nearly 50% more consequences were reported on pregaming days compared to nonpregaming drinking days. Those with PTSD were significantly more likely to pregame than those in the Trauma Only and No Trauma groups. Moreover, students with PTSD reported more consequences on pregaming days relative to the other two groups. In all analyses, the No Trauma and Trauma Only groups did not differ. Conclusions: PTSD may confer risk both for pregaming and experiencing harmful consequences on pregaming days.
Recommended oral sodium bicarbonate administration for urine alkalinization did not affect the concentration of mitomycin-C in non-muscle invasive bladder cancer patients

Objective Sodium bicarbonate has been reported to maximize the efficacy of intravesical instillation of mitomycin-C (IVI-MMC) therapy by urine alkalinization in non-muscle-invasive bladder cancer (NMIBC). This study aimed to analyze the changes in MMC concentration according to urinary pH and evaluate the efficacy of sodium bicarbonate to maintain the concentration of active form of MMC during IVI-MMC. Methods We prospectively enrolled 26 patients with NMIBC after transurethral resection of bladder tumor. Patients with very high-risk and low-risk NMIBC were excluded. Urinary creatinine, volume, pH, and concentrations of MMC and its degraded form were measured immediately before and after IVI-MMC. The patients were administered 1.5 g of oral sodium bicarbonate during the preceding evening, in the morning, and immediately before the fourth cycle of the six-cycle IVI-MMC. The correlation between MMC concentration and urinary pH changes was explored with or without oral bicarbonate therapy. Results Recurrence without progression to muscle-invasive disease was noted in 4 of 26 patients in a 23.7-month follow-up. The mean urinary pH before and after the therapy increased from 6.03 to 6.50, and 6.46 to 7.24, without or with oral SB therapy, respectively. Despite this increase, the concentration of active form of MMC did not change significantly. No correlation was found between urinary pH and MMC concentration. Urine alkalinization by SB administration did not maintain the high concentration of urinary MMC. Conclusions Urine alkalinization by sodium bicarbonate administration for IVI-MMC did not maintain the high concentration of active urinary MMC in NMIBC.
Illness in the context of older age: the case of stroke.

Stroke is popularly conceived of as an illness which shatters lives. The discourse of shattered lives, articulated more generally within the sociological literature on chronic illness as ‘biographical disruption’, is examined with reference to the experience of a sample of predominantly elderly, working class people living in the East End of London. We begin by exploring the interviewees’ responses to the stroke as something which was ‘not that bad’, before going on to examine the place of the stroke within the context of these peoples’ lives. Particular attention is paid to the ways in which age may mediate illness experience.
Optimization of Narrow Band Filters in Metallic Waveguides using the Genetic Algorithm

An optimization procedure based on the genetic algorithm (GA) technique for the design of narrow band-pass filters in rectangular waveguides is presented. The characterization of the filters is carried out by the mode-matching method associated with the generalized scattering matrix technique. Higher order mode interactions between waveguide uniaxial discontinuities are included in the design procedure. The GA is employed to optimize the choice of geometrical parameters of the filter in order to improve theirs performances in pass-band. Results of optimization shows also that filter dimensions are reduced in comparison with reference data.
Partial zero-forcing adaptive MMSE receiver for DS-CDMA uplink in multicell environments

Adaptive multi-user detection techniques for interference suppression in direct-sequence code division multiple access (DS-CDMA) systems have gained much attention since they do not require any information on interfering users. In the uplink of DS-CDMA systems, however, the base station receiver typically knows the spreading waveforms of the users within its cell but does not know those of the users in other cells. We propose a partial zero-forcing adaptive minimum mean squared error (MMSE) receiver for the DS-CDMA uplink utilizing the spreading waveforms known at the base station as well as training data. The proposed receiver first removes the intracell interference using a linear filter based on the knowledge of the spreading waveforms of the interfering users within the cell. Then the intercell interference remaining in the output of the linear filter is mitigated by adaptive MMSE detection. To speed up the convergence of the adaptive filter weights without loss of the steady-state performance, we develop a modified least mean square (LMS) algorithm based on the canonical representation of the filter weights. It is shown through analysis and simulation results that the proposed receiver improves the convergence speed and the steady-state performance.
Colour Constrained 4D Flow

The addition of colour information to the computation of range/scene flow is proposed to improve its accuracy and robustness to ambiguities. This is applied in the form of additional optical flow constraints from aligned colour image data. Combining constraints gives improved velocity displacement fields for both synthetic and real datasets over using depth alone, or in using depth plus intensity. This ultimately has benefits for the processing of dense, temporal depth data obtainable from novel video-rate 3D capture systems.
Regularized latent semantic indexing

Topic modeling can boost the performance of information retrieval, but its real-world application is limited due to scalability issues. Scaling to larger document collections via parallelization is an active area of research, but most solutions require drastic steps such as vastly reducing input vocabulary. We introduce Regularized Latent Semantic Indexing (RLSI), a new method which is designed for parallelization. It is as effective as existing topic models, and scales to larger datasets without reducing input vocabulary. RLSI formalizes topic modeling as a problem of minimizing a quadratic loss function regularized by l₂ and/or l₁ norm. This formulation allows the learning process to be decomposed into multiple sub-optimization problems which can be optimized in parallel, for example via MapReduce. We particularly propose adopting l₂ norm on topics and l₁ norm on document representations, to create a model with compact and readable topics and useful for retrieval. Relevance ranking experiments on three TREC datasets show that RLSI performs better than LSI, PLSI, and LDA, and the improvements are sometimes statistically significant. Experiments on a web dataset, containing about 1.6 million documents and 7 million terms, demonstrate a similar boost in performance on a larger corpus and vocabulary than in previous studies.