Miracle-dz/UniFAR-FTUs huggingface dataset:
Frontline: Epitope recognition on the myelin/oligodendrocyte glycoprotein differentially influences disease phenotype and antibody effector functions in autoimmune demyelination

Preliminary observations of humoral immunity against the myelin oligodendrocyte glycoprotein (MOG) in experimental allergic encephalomyelitis (EAE) and human multiple sclerosis (MS) suggest that a subset of anti‐MOG autoantibodies directed against conformational epitopes is of pathogenic predominance. Here, we provide proof that in marmoset EAE, autoantibodies reactive against conformational epitopes of MOG are not only responsible for aggravating demyelination, but also an essential factor for disease dissemination in space within the central nervous system, a hallmark for typicalforms of human MS. In terms of effector mechanisms, IgG deposition and complement activation occur exclusively in association with presence of these conformational antibodies, while microglial/macrophage activation appears to be a common immunopathological finding regardless of the fine determinant specificity of anti‐MOG antibodies. These findings highlight for the first time the complex heterogeneity of function and pathogenicity in the polyclonal anti‐MOG antibody repertoire of outbred species. Because the linear and conformational antibody determinants of MOG are shared between marmosets and humans, these results are directly relevant to understanding effector mechanisms of organ damage in MS.
Microbial food web dynamics during spring phytoplankton blooms in the naturally iron-fertilized Kerguelen area (Southern Ocean)

Microbial food web dynamics were determined during the onset of several spring phytoplankton blooms induced by natural iron fertilization off Kerguelen Island in the Southern Ocean (KEOPS2). The abundances of het-erotrophic bacteria and heterotrophic nanoflagellates, bacterial heterotrophic production, bacterial respiration, and bacterial growth efficiency, were consistently higher in surface waters of the iron-fertilized sites than at the reference site in HNLC (high nutrient low chlorophyll) waters. The abundance of virus-like particles remained unchanged, but viral production increased by a factor of 6 in iron-fertilized waters. Bacterial heterotrophic production was significantly related to heterotrophic nanoflagellate abundance and viral production across all sites, with bacterial production explaining about 70 and 85 %, respectively, of the variance of each in the mixed layer (ML). Estimated rates of grazing and viral lysis, however, indicated that heterotrophic nanoflagellates accounted for a substantially higher loss of bacterial production (50 %) than viruses (11 %). Combining these results with rates of primary production and export determined for the study area, a budget for the flow of carbon through the microbial food web and higher trophic levels during the early (KEOPS2) and the late phase (KEOPS1) of the Kerguelen bloom is provided.
Magnetically promoted rapid immunoreactions using functionalized fluorescent magnetic beads: a proof of principle.

BACKGROUND Accurate detection and monitoring of disease-related biomarkers is important in understanding pathophysiology. We devised a rapid immunoreaction system that uses submicrometer polymer-coated fluorescent ferrite (FF) beads containing both ferrites (magnetic iron oxide) and fluorescent europium complexes. METHODS FF beads were prepared by encapsulation of hydrophobic europium complexes into the polymer layers of affinity magnetic beads using organic solvent. A sandwich immunoassay using magnetic collection of antibody-coated FF beads to a specific place was performed. Brain natriuretic peptide and prostate-specific antigen were selected as target detection antigens to demonstrate the feasibility of this approach. An immunohistochemical staining using magnetic collection of antibody-coated FF beads onto carcinoma cell samples was also performed. RESULTS The sandwich immunoassays, taking advantage of the magnetic collection of antibody-coated FF beads, detected target antigens within 5 min of sample addition. Without magnetic collection, the sandwich immunoassay using antibody-coated FF beads required long times, similar to conventional immunoassays. Using the magnetic collection of antibody-coated FF beads, immunohistochemical staining enabled discrimination of carcinoma cells within 20 min. CONCLUSIONS This proof of principle system demonstrates that immunoreactions involving the magnetic collection of antibody-coated FF beads allow acceleration of the antigen-antibody reaction. The simple magnetic collection of antibody-coated FF beads to a specific space enables rapid detection of disease-related biomarkers and identification of carcinoma cells.
Linear Filtering and Recursive Credibility Estimation

Abstract Recursive credibility estimation is discussed from the viewpoint of linear filtering theory. A conjunction of geometric interpretation and the innovation approach leads to general algorithms not developed before. Moreover, covariance characterizations considered by other researchers drop our elegantly as a result of geometric considerations. Examples are presented of Kalman type filters valid for non-Gaussian measurements.
JAS: JAVA AGENT-BASED SIMULATION LIBRARY, AN OPEN FRAMEWORK FOR ALGORITHM-INTENSIVE SIMULATIONS

AbstractThis paper shows how agent-based modelling technique is a suitable approach for social scientists to model complex adaptive systems, using computer as experimental environment. Unfortunately advanced tools are lacking as well as an unified language supporting its development. We present JAS, a new agent-based simulation tool, developed with the aim to improve AB models designing. We give a brief methodological introduction to its use and a short description of its architecture.
Towards a Consensus-Based Classification of Childhood Arterial Ischemic Stroke

Background and Purpose— The implementation of uniform nomenclature and classification in adult arterial ischemic stroke (AIS) has been critical for defining outcomes and recurrence risks according to etiology and in developing risk-stratified treatments. In contrast, current classification and nomenclature in childhood AIS are often overlapping or contradictory. Our purpose was to develop a comprehensive consensus-based classification system for childhood AIS. Methods— Using a modified-Delphi method, members of the International Pediatric Stroke Study (IPSS) developed the Childhood AIS Standardized Classification And Diagnostic Evaluation (CASCADE) criteria. Two groups of pediatric stroke specialists from the IPSS classified 7 test cases using 2 methods each: (1) classification typical of the individual clinician's current clinical practice; and (2) classification based on the CASCADE criteria. Group 1 underwent in-person training in the utilization of the CASCADE criteria. Group 2 classified the same cases via an online survey, including definitions but without training. Inter-rater reliability (IRR) was assessed via multi-rater unweighted &kgr;-statistic. Results— In Group 1 (with training), IRR was improved using CASCADE criteria (&kgr;=0.78, 95% CI=[0.49, 0.94]), compared with typical clinical practice (&kgr;=0.40, 95% CI=[0.11, 0.60]). In Group 2 (without training), IRR was lower than among trained raters (&kgr;=0.61, 95% CI=[0.29, 0.77]), but higher than current practice (&kgr;=0.23, 95% CI=[0.03, 0.36]). Conclusions— A new, consensus-based classification system for childhood AIS, the CASCADE criteria, can be used to classify cases with good IRR. These preliminary findings suggest that the CASCADE criteria may be particularity useful in the setting of prospective multicenter studies in childhood-onset AIS, where standardized training of investigators is feasible.
The Development of an Educational and Career Outcome Expectancy Scale.

The development of an educational outcome expectations scale was prompted by a need for a measure tailored to college students' expected level of educational attainment. Studies were conducted in an undergraduate psychology course at a midwestern university. Participants (383 women, 276 males) attending a group counseling session completed a demographic questionnaire, the Educational Outcome Expectancy (EOE) Measure, and the Career Outcome Expectancy (COE) Measure. In study 1, in which the Educational Outcome Expectancy Scale and Career Outcome Expectancy Scale were administered to students (N=659), results demonstrated moderately high factor loadings for all items on the EOE Measure and for all items on the COE Measure. In study 2, which employed a similar protocol using a sample of undergraduates (N=938), the EOE Measure obtained robust factor loadings. The COE Measure obtained moderately high factor loadings across items without losing items that provide a well-rounded picture of the importance of education and work values. For study 3, a 1-month lapse was used to obtain reliability figures in a test-retest design. Results show that students' educational and career outcome expectancies are generally somewhat in flux, which can be expected for a college freshman sample. Results are promising as a way to-test educational and career outcome expectancies. (Contains 3 tables and 28 references.) (JDM) Reproductions supplied by EDRS are the best that can be made from the original document. The Development of an Educational and Career Outcome Expectancy Scale Shauna H. Springer, A. B. Lisa M. Larson, Ph.D. Brian P. Tilley, B. A. Courtney E. Gasser, B. A. Aaron C. Quinn, B. A. Iowa State University
Developing a dialogic practice of storytelling with adolescents : encounter in the space of story

Oral storytelling has been widely employed with adolescents, often applied to educational, therapeutic or other purposes. The unique contribution of this research is to articulate what storytelling can offer this age group as an open-ended participatory artistic practice, informed by an understanding of the anatomy of narrative knowledge, or ‘storyknowing’. Long-term, reflective Practice as Research (PaR) in educational, mental health, youth theatre and youth work settings has provided me with a powerful methodology to shape storytelling practice around adolescents, and simultaneously to theorise and disseminate this practice. I contend that storytelling practice with adolescents has evolved through different ‘chronotopes’. I both identify, and develop further, an emergent dialogic chronotope which enables dialogue between traditional repertoire and reality, enchantment and empowerment, and storyteller and young people. Such dialogue, conducted through narrative, is responsive to adolescents’ interests without intruding upon their personal challenges. Using my practice as both evidence and methodology, this exegesis explores the complex dynamics of the intersubjective space ‘between’ storyteller and adolescent participants, the demands this makes on the storyteller, and the different roles played by story in facilitating this encounter. In particular I find the sparse and otherworldly nature of myth and folktale to make a strong invitation, or even provocation, to young people to enter into collaborative creative processes. I depart from Bakhtin’s (1981) view of epic to describe how adolescents both ‘knock down’ and ‘raise up’ these stories, to articulate their own perspectives and dignify their life experiences. I consider the extent to which my practice has established dialogic fora (Delanty 2007) contributing to the regeneration of youth institutions, and ‘resingularising’ (Guattari 1995) roles and relationships within them. Given the relatively rigid institutional structures and cultural constructions surrounding contemporary adolescents, I propose that dialogic storytelling entails a conscious orientation to open-endedness, intersubjective meaning-making and singularity.
Affinity maturation of a novel antagonistic human monoclonal antibody with a long VH CDR3 targeting the Class A GPCR formyl-peptide receptor 1

Therapeutic monoclonal antibodies targeting G-protein-coupled receptors (GPCRs) are desirable for intervention in a wide range of disease processes. The discovery of such antibodies is challenging due to a lack of stability of many GPCRs as purified proteins. We describe here the generation of Fpro0165, a human anti-formyl peptide receptor 1 (FPR1) antibody generated by variable domain engineering of an antibody derived by immunization of transgenic mice expressing human variable region genes. Antibody isolation and subsequent engineering of affinity, potency and species cross-reactivity using phage display were achieved using FPR1 expressed on HEK cells for immunization and selection, along with calcium release cellular assays for antibody screening. Fpro0165 shows full neutralization of formyl peptide-mediated activation of primary human neutrophils. A crystal structure of the Fpro0165 Fab shows a long, protruding VH CDR3 of 24 amino acids and in silico docking with a homology model of FPR1 suggests that this long VH CDR3 is critical to the predicted binding mode of the antibody. Antibody mutation studies identify the apex of the long VH CDR3 as key to mediating the species cross-reactivity profile of the antibody. This study illustrates an approach for antibody discovery and affinity engineering to typically intractable membrane proteins such as GPCRs.
Performing Critical Work: The Challenges of Emancipatory Scholarship in the Academic Marketplace.

Critical scholarship in the social sciences usually focuses on the social sphere outside of the academy. However, for higher education researchers, critical research is often undertaken within and for the academy, which in turn may endanger one’s career if the dominant power structures are threatened. How might we enact and perform critical research within the academy when the academy itself is our focus? In this piece, we script our dramaturgical relationship with critical theories, to question the meaning of these paradigms in our own work and in our field (of education) as well as to explore the potentials of and limits to the use of critical theories and paradigms that may move beyond critical.
Glaucoma Images Classification Using Fuzzy Min-Max Neural Network Based On Data-Core

—Glaucoma is the major cause of blindness in worldwide. It is an ophthalmologist disease characterized by an increase in Intraocular Pressure (IOP). The types of glaucoma are primary open angle or chronic glaucoma (POAG) and closed angle (or) acute glaucoma (CAG) which causes a slow (or) rapid rise in Intraocular Pressure (IOP). The iridocorneal angle between the iris and the cornea is the key used to differentiate OAG and CAG. The stratus Anterior Optical Coherence Tomography (AS-OCT) images with these diseases are detected and classified from the normal images using the proposed fuzzy min-max neural network based on Data-Core (DCFMN). Data-core fuzzy min-max neural network (DCFMN) has strong robustness and high accuracy in classification. DCFMN contains two classes of neurons: classifying neurons (CNs) and overlapping neurons (OLNs). CNs are used to classify the patterns of data. The OLN can handle all kinds of overlap in different hyper boxes. A new type of membership function considering the characteristics of data and the influence of noise is designed for CNs in the DCFMN. The membership function of Overlapping Neurons (OLNs) deals with the relative position of data in the hyper boxes. This algorithm is performed on a batch of 39 anterior segment-Optical Coherence Tomography (AS-OCT) images obtained from the Vasan Eye Care Hospital, Chennai. The performance of the proposed system is excellent and a classification rate of 97% is achieved. Hence using this neural network, the performance of classification of normal or abnormal (glaucoma affected images) is improved. This method also reduces the time taken for the diagnosis by the ophthalmologist.
Prevalence of chronic obstructive pulmonary disease among patients with systemic arterial hypertension without respiratory symptoms

Background The diagnosis of chronic obstructive pulmonary disease (COPD) is often delayed until later stages of the disease. The purpose of the present study was to determine the prevalence of COPD among adults on treatment for systemic arterial hypertension independently of the presence of respiratory symptoms. Methods This cross-sectional study included adults aged ≥40 years with tobacco/occupational exposure and systemic arterial hypertension diagnosed at three Primary Health Care facilities in Goiania, Brazil. Patients were evaluated using a standardized respiratory questionnaire and spirometry. COPD prevalence was measured considering the value of forced vital capacity and/or forced expiratory volume in 1 second <0.70. Results Of a total of 570 subjects, 316 (55%) met inclusion criteria and were invited to participate. Two hundred and thirty-three (73.7%) patients with arterial hypertension reported at least one respiratory symptom, while 83 (26.3%) reported no respiratory symptoms; 41 (17.6%) patients with arterial hypertension and at least one respiratory symptom, and 10 (12%) patients with arterial hypertension but no respiratory symptoms were diagnosed with COPD (P=0.24). The prevalence of COPD in people with no previous COPD diagnosis was greater among those with no respiratory symptoms (100%) than among those with respiratory symptoms (56.1%) (P=0.01). Conclusion Our findings suggest that regardless of the presence of respiratory symptoms, individuals aged ≥40 years with tobacco/occupational exposure and arterial hypertension may benefit from spirometric evaluation.
Model-based subsampling : Theory

This paper summarizes the theoretical background that is used in several applications listed in the sibling conference paper [1]. We investigate object simplification methods based on Centroidal Voronoi Tesselation (CVT) that share the possibility of great speed-ups in various scenarios. We propose Constrained CVT to sample points from the object boundary and the Region-based CVT to be able to subsample lower dimensional objects, as well. Moreover we introduce custom weight functions based on object properties. Thus, we can be more specific on what are the important parts of the object to be subsampled.
Coupled Deep Learning for Heterogeneous Face Recognition

Heterogeneous face matching is a challenge issue in face recognition due to large domain difference as well as insufficient pairwise images in different modalities during training. This paper proposes a coupled deep learning (CDL) approach for the heterogeneous face matching. CDL seeks a shared feature space in which the heterogeneous face matching problem can be approximately treated as a homogeneous face matching problem. The objective function of CDL mainly includes two parts. The first part contains a trace norm and a block-diagonal prior as relevance constraints, which not only make unpaired images from multiple modalities be clustered and correlated, but also regularize the parameters to alleviate overfitting. An approximate variational formulation is introduced to deal with the difficulties of optimizing low-rank constraint directly. The second part contains a cross modal ranking among triplet domain specific images to maximize the margin for different identities and increase data for a small amount of training samples. Besides, an alternating minimization method is employed to iteratively update the parameters of CDL. Experimental results show that CDL achieves better performance on the challenging CASIA NIR-VIS 2.0 face recognition database, the IIIT-D Sketch database, the CUHK Face Sketch (CUFS), and the CUHK Face Sketch FERET (CUFSF), which significantly outperforms state-of-the-art heterogeneous face recognition methods.
A POS Tagger for Social Media Texts Trained on Web Comments

Using social media tools such as blogs and forums have become more and more popular in recent years. Hence, a huge collection of social media texts from different communities is available for accessing user opinions, e.g., for marketing studies or acceptance research. Typically, methods from Natural Language Processing are applied to social media texts to automatically recognize user opinions. A fundamental component of the linguistic pipeline in Natural Language Processing is Part-of-Speech tagging. Most state-of-the-art Part-of-Speech taggers are trained on newspaper corpora, which differ in many ways from non-standardized social media text. Hence, applying common taggers to such texts results in performance degradation. In this paper, we present extensions to a basic Markov model tagger for the annotation of social media texts. Considering the German standard Stuttgart/T¨ ubinger TagSet (STTS), we distinguish 54 tag classes. Applying our approach improves the tagging accuracy for social media texts considerably, when we train our model on a combination of annotated texts from newspapers and Web comments. standardized text, since they are characterized by a spoken language, a dialogic and an informal writing style. This poses some special challenges to deal with in developing methods for automatic POS tagging of Web comments. These are particularly, the treatment of unknown (out-of-vocabulary) words and the different grammatical structure of social media texts in contrast to newspaper text. Furthermore, text genre specific manually annotated corpora, i.e., Web comments are required for training and testing. To the best of our knowledge all large manually annotated corpora are exclusively newspaper texts. In this work, we propose a Markov model tagger with parameter estimation enhancements for the POS annotation of social media texts. We apply and evaluate the tagger for German social media texts exemplarily. In order to make our method usable for NLP methods requiring POS information, e.g., syntactical parsing, we use the 54 Stuttgart/T¨ ubinger
Seeded Laplacian: An interactive image segmentation approach using eigenfunctions

In this paper, we cast the scribbled-based interactive image segmentation as a semi-supervised learning problem. Our novel approach alleviates the need to solve an expensive generalized eigenvector problem by approximating the eigenvectors using a more efficiently computed eigenfunctions. The smoothness operator defined on feature densities at the limit n → ∞ recovers the exact eigenvectors of the graph Laplacian, where n is the number of nodes in the graph. In our experiments scribble annotation is applied, where users label few pixels as foreground and background to guide the foreground/background segmentation. Experiments are carried out on standard data-sets which contain a wide variety of natural images. We achieve better qualitative and quantitative results compared to state-of-the-art algorithms.
Vigilance estimation by using electrooculographic features

This study aims at using electrooculographic (EOG) features, mainly slow eye movements (SEM), to estimate the human vigilance changes during a monotonous task. In particular, SEMs are first automatically detected by a method based on discrete wavelet transform, then linear dynamic system is used to find the trajectory of vigilance changes according to the SEM proportion. The performance of this system is evaluated by the correlation coefficients between the final outputs and the local error rates of the subjects. The result suggests that SEMs perform better than rapid eye movements (REM) and blinks in estimating the vigilance. Using SEM alone, the correlation can achieve 0.75 for off-line, while combined with a feature from blinks it reaches 0.79.