Miracle-dz/UniFAR-FTUs huggingface dataset:
A European perspective on intravascular catheter-related infections: report on the microbiology workload, aetiology and antimicrobial susceptibility (ESGNI-005 Study).

The laboratory workload, microbiological techniques and aetiology of catheter-related infections in European hospitals are mostly unknown. The present study (ESGNI-005) comprised a 1-day (22 October 2001), laboratory-based, point-prevalence survey based on a questionnaire completed by microbiology laboratories in European (European Union (EU) and non-EU) hospitals. Also included were questions requesting retrospective information for the year 2000. In total, 151 hospitals from 26 European countries participated, of which 78.1% were teaching institutions. Overall, the estimated population served by these institutions was 121,363,800, and the estimated number of admissions during 2000 was 6,712,050. The total number of catheter tips processed during 2000 was 142,727, or 21/1,000 admissions, of which 23.7% were considered to be positive in the institutions using semiquantitative or quantitative techniques. Overall, EU centres received significantly more catheter tip samples/1,000 admissions and had a significantly higher rate of 'positivity' (p < 0.0001) than non-EU centres. Of the institutions surveyed, 11.4% (7.2% in EU countries and 23.7% in non-EU countries; p 0.04) used only qualitative techniques for catheter tip sample processing. On the day of the study, 167 microorganisms were recovered from significant catheter tip cultures (122 patients), of which Gram-positive bacteria represented 70.7%, Gram-negative bacteria 22.2%, and yeasts 7.2%. The five most common microorganisms were coagulase-negative staphylococci, Staphylococcus aureus, Candida spp. , Enterococcus spp. and Pseudomonas spp. Overall, 19% of catheter tip cultures were polymicrobial. In the case of S. aureus, 40% of isolates were resistant to oxacillin, as were 63.4% of coagulase-negative staphylococcus isolates. Of 37 Gram-negative isolates, 35% were resistant to cefotaxime, 31% to ceftazidime, and 27% to ciprofloxacin. Imipenem and cefepime had the lowest reported rates of resistance (11%).
Constraints on the transient climate response from observed global temperature and ocean heat uptake

Projections of future transient global temperature increase in climate models for a known forcing depend on the strength of the atmospheric feedbacks and the rate of transient ocean heat uptake. A Bayesian framework and an intermediate complexity climate model are used to calculate a probability density function (PDF) of the transient climate response (TCR), constrained by observations of global surface warming and ocean heat uptake. The PDF constrained by observations is wider than the TCR range of current climate models, and has a slightly lower mean. Uncertainties in the observed ocean warming are shown to potentially affect the TCR. It is proposed, however, that even if models were found to overestimate ocean heat uptake, correcting that bias would lead to revisions in surface temperature projections over the twenty‐first century that are smaller than the uncertainties introduced by poorly quantified atmospheric feedbacks.
Dynamic Response of Ammonia-Oxidizers to Four Fertilization Regimes across a Wheat-Rice Rotation System

Ammonia oxidation by microorganisms is a rate-limiting step of the nitrification process and determines the efficiency of fertilizer utilized by crops. Little is known about the dynamic response of ammonia-oxidizers to different fertilization regimes in a wheat-rice rotation system. Here, we examined ammonia-oxidizing bacteria (AOB) and archaea (AOA) communities across eight representative stages of wheat and rice growth and under four fertilization regimes: no nitrogen fertilization (NNF), chemical fertilization (CF), organic-inorganic mixed fertilizer (OIMF) and organic fertilization (OF). The abundance and composition of ammonia oxidizers were analyzed using quantitative PCR (qPCR) and terminal restriction fragment length polymorphism (T-RFLP) of their amoA genes. Results showed that fertilization but not plant growth stages was the best predictor of soil AOB community abundance and composition. Soils fertilized with more urea-N had higher AOB abundance, while organic-N input showed little effect on AOB abundance. 109 bp T-RF (Nitrosospira Cluster 3b) and 280 bp T-RF (Nitrosospira Cluster 3c) dominated the AOB communities with opposing responses to fertilization regimes. Although the abundance and composition of the AOA community was significantly impacted by fertilization and plant growth stage, it differed from the AOB community in that there was no particular trend. In addition, across the whole wheat-rice rotation stages, results of multiple stepwise linear regression revealed that AOB played a more important role in ammonia oxidizing process than AOA. This study provided insight into the dynamic effects of fertilization strategies on the abundance and composition of ammonia-oxidizers communities, and also offered insights into the potential of managing nitrogen for sustainable agricultural productivity with respect to soil ammonia-oxidizers.
Modelling the effects of the inclusion of pupils with additional support needs (ASN) on attainment and attendance in primary schools

This thesis applies methods from social statistics to answer the question as to whether pupils with support needs that are additional to those that can be catered for by mainstream educational provision (i.e. pupils with English languages needs or those with Special Educational Needs), exert an effect on the attainment and attendance of their classmates during the second half of primary schooling in England. Including such pupils within mainstream schools has been the dominant policy paradigm since the 1980s, though the effect on other pupils has not been comprehensively assessed, despite being of concern to parents, teachers and policymakers.The main findings of this thesis are:- The effect on pupil attainment of peers with Special Educational Needs, and, to a lesser extent, peers with English language needs, is heterogeneous by a pupil? s own prior attainment. Pupils at the higher end of the prior attainment distribution experience the largest negative effects from such pupils. Such heterogeneity is predicted by theory and this thesis represents the first demonstration of these effects on pupils in England, refining and updating existing research. The size of these effects are however small relative to other influences on a pupil? s attainment. - Peers with Behavioural, Emotional and Social Difficulties have a stronger negative effect on classmates? attainment than do other ASN peer types. This supports the theory that classroom disruption may be a mechanism by which peer effects in schools operate. This finding concurs with studies from the USA and is consistent with concerns of the teaching profession with regard to the inclusion of such pupils within schools. - Peers with Behavioural, Emotional and Social Difficulties are also found to induce absenteeism in their classmates, but only where the classmates are in receipt of free schools meals, a common proxy for low household income. This finding represents one of the first quantitative analyses of pupil absence in England and contributes to a very small but growing literature on non-academic outcomes within schools.The findings have implications for debates on inclusion of ASN pupils within schools and provide evidence of why educational inequalities are present in the English schools system.
A patient with BRAF V600E lung adenocarcinoma responding to vemurafenib.

Journal of Thoracic Oncology • Volume 7, Number 10, October 2012 Vemurafenib is active against metastatic melanoma with BRAF V600E mutation. BRAF mutations were reported in 3% to 5% of non–small-cell lung cancers (NSCLC) by the US Lung Cancer Mutation Consortium and by Italian investigators. In vitro, MEK inhibition in lung cancer cell lines with V600E induced apoptosis, but clinical experience with drugs targeting the RAS/RAF/MEK pathway in V600E-NSCLC is limited.
People like me: increasing likelihood of success for underrepresented minorities in STEM by providing realistic and relatable role models

Seeing themselves represented in the role models they aspire to, has been shown to be important to students’ sense of belonging and success. Underrepresented college students in STEM fields are exposed to only a small set of role models. This set often consist of famous individuals with extraordinary stories (we call these outliers), and represent unfeasible paths to success for a large majority of these students. We aim to remedy this by identifying a set of role models who represent more feasible paths to success (we call these non-outliers) for many underrepresented students. We contend that, despite the less extraordinary success and stories of non-outliers, they share important qualities with outliers. We envision a “People Like Me” website based on profiles of this broader set of role models that can be used as a tool for recruitment and retention. Our current work is to (1) identify role model qualities from the perspective of students, (2) identify and create profiles of non-outlier role models based on these qualities, and (3) test if students are accepting of these nonoutliers as potential role models. We have completed steps (1) and (2), and have found that non-outliers do exhibit the qualities our student sample pool seeks in role models.
Genome-wide association study of chronic periodontitis in a general German population.

AIM To identify loci associated with chronic periodontitis through a genome-wide association study (GWAS). MATERIALS AND METHODS A GWAS was performed in 4032 individuals of two independent cross-sectional studies of West Pomerania (SHIP n = 3365 and SHIP-TREND n = 667) with different periodontal case definitions. Samples were genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 or the Illumina Human Omni 2.5 array. Imputation of the HapMap as well as the 1000 Genome-based autosomal and X-chromosomal genotypes and short insertions and deletions (INDELs) was performed in both cohorts. Finally, more than 17 million SNPs and short INDELs were analysed. RESULTS No genome-wide significant associations were found for any periodontitis case definition, regardless of whether individuals aged >60 years where excluded or not. Despite no single SNP association reached genome-wide significance, the proportion of variance explained by additive effects of all common SNPs was around 23% for mean proximal attachment loss. Excluding subjects aged >60 years increased the explained variance to 34%. CONCLUSIONS No single SNPs were found to be genome-wide significantly associated with chronic periodontitis in this study.
Tissue is alive: New technologies are needed to address the problems of protein biomarker pre‐analytical variability

Instability of tissue protein biomarkers is a critical issue for molecular profiling. Pre‐analytical variables during tissue procurement, such as time delays during which the tissue remains stored at room temperature, can cause significant variability and bias in downstream molecular analysis. Living tissue, ex vivo, goes through a defined stage of reactive changes that begin with oxidative, hypoxic and metabolic stress, and culminate in apoptosis. Depending on the delay time ex vivo, and reactive stage, protein biomarkers, such as signal pathway phosphoproteins will be elevated or suppressed in a manner which does not represent the biomarker levels at the time of excision. Proteomic data documenting reactive tissue protein changes post collection indicate the need to recognize and address tissue stability, preservation of post‐translational modifications, and preservation of morphologic features for molecular analysis. Based on the analysis of phosphoproteins, one of the most labile tissue protein biomarkers, we set forth tissue procurement guidelines for clinical research. We propose technical solutions for (i) assessing the state of protein analyte preservation and specimen quality via identification of a panel of natural proteins (surrogate stability markers), and (ii) using multi‐purpose fixative solution designed to stabilize, preserve and maintain proteins, nucleic acids, and tissue architecture.
Evaluating the impact of adjunctive integrated case-based dental teaching and learning on clinical reasoning in a discipline-based teaching and learning environment

Problem-solving and integration of knowledge are key objectives of the undergraduate dental curriculum of the School of Dentistry, University of Pretoria, which aims to develop the clinical reasoning skills of students. For practical reasons the School provides discipline-based teaching and learning, which, according to the literature, might limit a student’s ability to integrate knowledge during clinical reasoning processes. The literature suggests that problem-solving by means of case studies – an active teaching and learning strategy– might be a useful method to develop and integrate knowledge at undergraduate level, and that earlier exposure to clinical cases might assist in the attainment of clinical reasoning skills at an earlier stage. Hence, this action research study describes the planning, design, implementation and evaluation of a “new” Comprehensive Patient Care curriculum over a three-year period (2009 2011) based on Kern’s “six-step approach to curriculum development”. The new curriculum employs an adjunctive integrated case-based approach according to the principles described in the “Four Component Instructional Design Model” and a new variant of the so-called “progress test”, starting already in the preclinical (third) year of study, to develop and test students’ clinical reasoning skills over time. The exit-level progress test results of dental students who had been taught by following an adjunctive integrated case-based approach were statistically analysed, using mixed model statistics, and were compared with the clinical decision-making skills of cohorts who had been taught by following the traditional discipline-based approach. These analyses were complemented by bivariate and multivariate quantitative analyses and qualitative student feedback (mixed methods). The validity of the progress test results was also examined by comparing the results of different cohorts. The fifth-year cohort who had been exposed to integrated case-based teaching and learning from their preclinical year performed significantly better in the progress test at exit level than the cohorts who had received only discipline© University of Pretoria
Neurological involvement in hemolytic‐uremic syndrome

Of 44 children with hemolytic‐uremic syndrome seen at Milwaukee Children's Hospital, 15 (34%) had neurological involvement. This group contained 8 boys and 7 girls, with a mean age of 3 1/4 years. Twelve patients had seizures within 48 hours of admission. Seizures were associated with hypertension, fever, hyponatremia, or hypocalcemia. Other neurological symptoms included altered consciousness, behavioral changes, diplopia, and dizziness. Hemiparesis (4 patients), eye involvement (7 patients), decerebrate posturing (2 patients), and ataxia (1 patient) were present on physical examination. Cerebrospinal fluid examination showed increased protein in 4 of 11 patients. Electroencephalograms were abnormal in all 9 patients tested. Computed tomographic and radionuclide scans showed evidence of vascular abnormalities in 4 of the 14 patients studied. Complete neurological recovery occurred in only 6 of the 15 children, while the remaining 6 demonstrated residual hemiparesis, seizures, and cortical visual defect. In those children with neurological involvement, there was a higher incidence of residual hypertension (49% versus 11%), chronic renal damage (40% versus 3.5%), and death (28% versus 0%), suggesting that central nervous system involvement indicates severe hemolytic‐uremic syndrome.
Fiber Optic pH Sensor with Self-Assembled Polymer Multilayer Nanocoatings

A fiber-optic pH sensor based on a tilted fiber Bragg grating (TFBG) with electrostatic self-assembly multilayer sensing film is presented. The pH sensitive polymeric film, poly(diallyldimethylammonium chloride) (PDDA) and poly(acrylic acid) (PAA) was deposited on the circumference of the TFBG with the layer-by-layer (LbL) electrostatic self-assembly technique. The PDDA/PAA film exhibits a reduction in refractive index by swelling in different pH solutions. This effect results in wavelength shifts and transmission changes in the spectrum of the TFBG. The peak amplitude of the dominant spectral fringes over a certain window of the transmission spectrum, obtained by FFT analysis, has a near-linear pH sensitivity of 117 arbitrary unit (a.u.)/pH unit and an accuracy of ±1 a.u. (in the range of pH 4.66 to pH 6.02). The thickness and surface morphology of the sensing multilayer film were characterized to investigate their effects on the sensor's performance. The dynamic response of the sensor also has been studied (10 s rise time and 18 s fall time for a sensor with six bilayers of PDDA/PAA).
Identifying and Following Expert Investors in Stock Microblogs

Information published in online stock investment message boards, and more recently in stock microblogs, is considered highly valuable by many investors. Previous work focused on aggregation of sentiment from all users. However, in this work we show that it is beneficial to distinguish expert users from non-experts. We propose a general framework for identifying expert investors, and use it as a basis for several models that predict stock rise from stock microblogging messages (stock tweets). In particular, we present two methods that combine expert identification and per-user unsupervised learning. These methods were shown to achieve relatively high precision in predicting stock rise, and significantly outperform our baseline. In addition, our work provides an in-depth analysis of the content and potential usefulness of stock tweets.
Improving Spatial Perception for Augmented Reality X-Ray Vision

Augmented reality x-ray vision allows users to see through walls and view real occluded objects and locations. We present an augmented reality x-ray vision system that employs multiple view modes to support new visualizations that provide depth cues and spatial awareness to users. The edge overlay visualization provides depth cues to make hidden objects appear to be behind walls, rather than floating in front of them. Utilizing this edge overlay, the tunnel cut-out visualization provides details about occluding layers between the user and remote location. Inherent limitations of these visualizations are addressed by our addition of view modes allowing the user to obtain additional detail by zooming in, or an overview of the environment via an overhead exocentric view.
Altered global brain signal in schizophrenia

Significance This study identified elevated global brain signal variability in schizophrenia, but not bipolar illness. This variability was related to schizophrenia symptoms. A commonly used analytic procedure in neuroimaging, global signal regression, attenuated clinical effects and altered inferences. Furthermore, local voxel-wise variance was increased in schizophrenia, independent of global signal regression. Finally, neurobiologically grounded computational modeling suggests a putative mechanism, whereby altered overall connection strength in schizophrenia may underlie observed empirical results. Neuropsychiatric conditions like schizophrenia display a complex neurobiology, which has long been associated with distributed brain dysfunction. However, no investigation has tested whether schizophrenia shows alterations in global brain signal (GS), a signal derived from functional MRI and often discarded as a meaningless baseline in many studies. To evaluate GS alterations associated with schizophrenia, we studied two large chronic patient samples (n = 90, n = 71), comparing them to healthy subjects (n = 220) and patients diagnosed with bipolar disorder (n = 73). We identified and replicated increased cortical power and variance in schizophrenia, an effect predictive of symptoms yet obscured by GS removal. Voxel-wise signal variance was also increased in schizophrenia, independent of GS effects. Both findings were absent in bipolar patients, confirming diagnostic specificity. Biologically informed computational modeling of shared and nonshared signal propagation through the brain suggests that these findings may be explained by altered net strength of overall brain connectivity in schizophrenia.
An empirical model of heliospheric cosmic ray modulation on long-term time scale

Galactic Cosmic Rays (GCRs) entering the heliosphere are subject to modulation processes due to variable solar magnetic activity. Finding a relationship between cosmic-ray variations and the heliospheric parameters is important for reconstruction of solar activity in the past. Here, we develop a semi-empirical model describing the heliospheric modulation of GCRs in terms of heliospheric parameters such as the open solar magnetic flux, the tilt angle of the heliospheric current sheet and the polarity of the large scale solar magnetic field. Our model is fitted using annual data obtained for the period 1976–2013, which includes the very weak solar minimum during 2008–2010. The model shows a good agreement with the data, and therefore, can be used for reconstructions of the modulation potential at different levels of solar activity. The model’s validity is also tested using the cosmogenic radionuclides 14 C and 10 Be stored in terrestrial archives. The tilt angle used to fit the parameters in our semi-empirical modulation model is reconstructed by a mathematical model described here.
Alternating Decision Forests

This paper introduces a novel classification method termed Alternating Decision Forests (ADFs), which formulates the training of Random Forests explicitly as a global loss minimization problem. During training, the losses are minimized via keeping an adaptive weight distribution over the training samples, similar to Boosting methods. In order to keep the method as flexible and general as possible, we adopt the principle of employing gradient descent in function space, which allows to minimize arbitrary losses. Contrary to Boosted Trees, in our method the loss minimization is an inherent part of the tree growing process, thus allowing to keep the benefits of common Random Forests, such as, parallel processing. We derive the new classifier and give a discussion and evaluation on standard machine learning data sets. Furthermore, we show how ADFs can be easily integrated into an object detection application. Compared to both, standard Random Forests and Boosted Trees, ADFs give better performance in our experiments, while yielding more compact models in terms of tree depth.
Effect of precoding on the convergence of turbo equalization for partial response channels

The effect of the precoder on the convergence of turbo equalization for precoded partial response channels is studied. The idea is to consider the turbo decoding algorithm as a one parameter dynamical system and to study the effect of the precoder on the fixed points of the system. It is shown that precoding results in a loss in reliability during the first iteration and that this loss depends on the precoder. Further, the rate at which the extrinsic information increases is also dependent on the precoder. The net result of these two effects is used to explain several existing results in the literature about the performance of different precoders. A design criteria based on the convergence is then proposed. The impact of precoding on the design of the outer code is then studied. Finally, the design of precoders when an error correcting code such as a Reed-Solomon code is studied.