Miracle-dz/UniFAR-FTUs huggingface dataset:
Overweight and Severe Acute Maternal Morbidity in a Low-Risk Pregnant Population in The Netherlands

Objective To investigate the association between overweight and severe acute maternal morbidity (SAMM) in a low-risk pregnant population. Design Nationwide case-control study. Setting The Netherlands, august 2004 to august 2006. Population 1567 cases from initially primary care and 2994 women from primary care practices as controls, out of 371 012 women delivering in the Netherlands during the study period Methods Cases were women with SAMM obtained from a nationwide prospective study. All women in this cohort who initially had low-risk pregnancies were compared with low-risk women without SAMM to calculate odd ratios (ORs) to develop SAMM by body mass index (BMI) category. We divided body mass index in three overweight categories and calculated the ORs (95% CI) of total SAMM and per specific endpoint by logistic regression, with normal weight as reference. We adjusted for age, parity and socio-economic status. Main Outcome Measures SAMM, defined as Intensive Care Unit (ICU)-admission, Uterine Rupture, Eclampsia or Major Obstetric Haemorrhage (MOH) Results SAMM was reported in 1567 cases which started as low-risk pregnancies. BMI was available in 1097 (70.0%) cases and 2994 control subjects were included. Analysis showed a dose response relation for overweight (aOR, 1.3; 95% CI, 1.0-1.5), obese (aOR, 1.4; 95% CI, 1.1-1.9) and morbidly obese (aOR, 2.1; 95% CI, 1.3-3.2) women to develop SAMM compared to normal weight. Sub analysis showed the same dose response relation for ICU-admission, Uterine Rupture and Eclampsia. We found no association for MOH. Conclusion Overweight without pre-existent co-morbidity is an important risk-indicator for developing SAMM. This risk increases with an increasing body mass index.
Acceptance yielding and impact: cognitive processes in persuasion.

Communication and persuasion research has been hindered by a lack of attention to the decisive role played by the content of a persuasive communication. To be effective the statements contained in a message must directly or indirectly influence the primary beliefs that determine the behavior targeted for intervention. These primary beliefs include beliefs about the consequences of a given behavior or normative beliefs about that behavior beliefs that link the target to various positive or negative attributes and beliefs that are inferentially related to a certain conclusion. The first step in the construction of a persuasive communication is selection of a set of arguments that attack beliefs about the performance of the targeted behavior. For these arguments to be effective the receiver must accept and yield to the evidence contained in the argument consider the evidence to be relevant and ideally undergo a change in primary beliefs not explicitly mentioned in the argument. The content of the message employed is far more significant than factors such as the power and credibility of the message source the type of appeal (i.e. rational or emotional) and receiver factors such as self-esteem.
Evidence for a Physically Compact Narrow-Line Region in the Seyfert 1 Galaxy NGC 5548

We have combined Hubble Space Telescope/Faint Object Spectrograph and ground-based spectra of the Seyfert 1 galaxy NGC 5548 to study the narrow emission lines over the 1200-10000 Å region. All of the spectra were obtained when the broad emission line and continuum fluxes were at a historically low level, allowing us to determine accurately the contribution of the narrow-line region (NLR) to the emission lines. We have generated multicomponent photoionization models to investigate the relative strength of the high-ionization lines compared to those in Seyfert 2 galaxies and the weakness of the narrow Mg II λ2800 line. We present evidence for a high-ionization component of NLR gas that is very close to the nucleus (~1 pc). This component must be optically thin to ionizing radiation at the Lyman edge (i.e., τ0 ≈ 2.5) to avoid producing [O I] and Mg II in a partially ionized zone. The very high ionization lines (N V, [Ne V], [Fe VII], [Fe X]) are stronger than the predictions of our standard model, and we show that this may be due to supersolar abundances and/or a "blue bump" in the extreme ultraviolet (although recent observations do not support the latter). An outer component of NLR gas (at only ~70 pc from the continuum source) is needed to produce the low-ionization lines. We show that the outer component may contain dust, which further reduces the Mg II flux by depletion and by absorption of the resonance photons after multiple scatterings. We show that the majority of the emission in the NLR of NGC 5548 must arise within ~70 pc from the nucleus. Thus, the NLR in this Seyfert 1 galaxy is very physically compact, compared to the typical NLR in Seyfert 2 galaxies.
Selective anergy of V beta 8+,CD4+ T cells in Staphylococcus enterotoxin B-primed mice

The cellular basis of the in vitro and in vivo T cell responses to Staphylococcus enterotoxin B (SEB) has been investigated. The proliferation and cytotoxicity of V beta 8.1,2+,CD4+ and CD8+ T cells were observed in in vitro response to SEB. In primary cytotoxicity assays, CD4+ T cells from control spleens were more active than their CD8+ counterparts, however, in cells derived from SEB-primed mice, CD8+ T cells were dominant in SEB-specific cytotoxicity. In vivo priming with SEB abrogated the response of V beta 8.1,2+,CD4+ T cells despite the fact that these cells exist in significant number. This SEB- specific anergy occurred only in V beta 8.1,2+,CD4+ T cells but not in CD8+ T cells. These findings indicate that the requirement for the induction of antigen-specific anergy is different between CD4+ and CD8+ T cells in post-thymic tolerance, and the existence of coanergic signals for the induction of T cell anergy is suggested.
Does injustice reduce cognitive performance? An experimental test / ¿Provoca la injusticia una disminución en el rendimiento cognitivo? Una prueba empírica

Abstract In this paper we report two experimental studies showing for the first time that injustice causes a reduction in cognitive performance in complex tasks. The two experiments (Study 1, n = 106, Study 2, n = 90) used two different paradigms. In Study 1 participants were exposed to injustice happening to other people. In Study 2 participants themselves were the targets of injustice. In both studies the dependent variable was cognitive performance in a complex task. Specifically, in Study 1, participants solved anagrams, and in Study 2, they solved several Raven matrices. The dependent measures were the number of anagrams and Raven matrices solved correctly. We found that cognitive performance was worse in the unjust condition compared to the just condition (i.e., fewer items solved correctly). These results imply that unfairness in everyday life may have a deleterious effect on individuals’ capacity to think in a complex way. Possible mediators for this effect are proposed.
Aggregation of MBP in chronic demyelination

Misfolding of key disease proteins to an insoluble state is associated with most neurodegenerative conditions, such as prion, Parkinson, and Alzheimer's diseases. In this work, and by studying animal models of multiple sclerosis, we asked whether this is also the case for myelin basic protein (MBP) in the late and neurodegenerative phases of demyelinating diseases.
High Frequency Quoting: Short-Term Volatility in Bids and Offers

At subsecond horizons bids and offers in US equity markets are more volatile than what would be implied by long-term fundamentals. In considering underlying causes, the evidence suggests that this volatility is not likely to arise from quote-stuffing, spoofing, or mixed-strategy behavior, but more likely reflects Edgeworth cycles (recurrent phases of undercutting). To assess costs and consequences, the paper proposes a model wherein traders’ random delays (latencies) interact with quote volatility to generate execution price risk and relative latency costs. Finally, over the 2001-2011 period, despite high growth in quote traffic, quote volatility does not display a strong trend.
Transfer Learning Based on AdaBoost for Feature Selection from Multiple ConvNet Layer Features

Convolutional Networks (ConvNets) are powerful models that learn hierarchies of visual features, which could also be used to obtain image representations for transfer learning. The basic pipeline for transfer learning is to first train a ConvNet on a large dataset (source task) and then use feed-forward units activation of the trained ConvNet as image representation for smaller datasets (target task). Our key contribution is to demonstrate superior performance of multiple ConvNet layer features over single ConvNet layer features. Combining multiple ConvNet layer features will result in more complex feature space with some features being repetitive. This requires some form of feature selection. We use AdaBoost with single stumps to implicitly select only distinct features that are useful towards classification from concatenated ConvNet features. Experimental results show that using multiple ConvNet layer activation features instead of single ConvNet layer features consistently will produce superior performance. Improvements becomes significant as we increase the distance between source task and the target task.
Portfolio Choice in the Presence of Non-Tradable Income: An Experimental Analysis

Abstract This paper reports the results of an experiment on portfolio choice in the presence of non-tradable income. The non-tradable income part could either be riskless or risky (background risk). In many cases, we observe behavior that is qualitatively consistent with the predictions of normative theory. However, correlations between financial and non-tradable wealth are neglected. The computation of aggregated risk profiles helps subjects to partly overcome the deviations from normative theory due to neglect of correlations.
The Learning and Educational Capital of Male and Female Students in STEM Magnet Schools and in Extracurricular STEM Programs: A Study in High-Achiever-Track Secondary Schools in Germany

Magnet schools focused on science, technology, engineering, and mathematics (STEM) as well as extracurricular programs in STEM support talented students and help increase their participation rates in those domains. We examined whether and the extent to which the learning and educational capital of male and female students (N = 801) enrolled in high-achiever-track secondary schools in Germany with and without a STEM focus differed. We found both school and gender differences for some types of learning and educational capital but no interaction effect of type of school and gender. We also assessed the relationship between school status as a STEM magnet school, students’ gender, and students’ learning and educational capital, on the one hand, and registration for a 1-year extracurricular program in STEM, on the other hand. Students enrolled in high-achiever-track STEM magnet schools, as well as male students, were more likely to register for the extracurricular program. Some types of learning and educational capital also predicted registration in a regression analysis.
Fingerprint Recognition with Artificial Neural Networks: Application to E-Learning

Fingerprint recognition is a mature biometric technique for identification or authentication application. In this work, we describe a method based on the use of neural network to authenticate people who want to accede to an automated fingerprint system for E-learning. The idea is to apply back propagation algorithm on a multilayer perceptron during the training stage. One of the advantages of this technique is the use of a hidden layer which allows the network to make comparison by calculating probabilities on template which are invariant to translation and rotation. Results come both from the NIST special database 4 and a local database, and show that a proposed method gives good results in some cases.
Once an Impression Manager, Always an Impression Manager? Antecedents of Honest and Deceptive Impression Management Use and Variability across Multiple Job Interviews

Research has examined the antecedents of applicants' use of impression management (IM) tactics in employment interviews. All existing empirical studies have measured IM in one particular interview. Yet, applicants generally interview multiple times for different positions, and thus have multiple opportunities to engage in IM, before they can secure a job. Similarly, recent theoretical advances in personnel selection and IM research have suggested that applicant behaviors should be considered as dynamic and adaptive in nature. In line with this perspective, the present study is the first to examine the role of individual differences in both applicants' use of IM tactics and the variability in IM use across multiple interviews. It also highlights which honest and deceptive IM tactics remain stable vs. vary in consecutive interviews with different interviewers and organizations. Results suggest that applicants high in Extraversion or core self-evaluations tend to engage in more honest self-promotion but do not adapt their IM approach across interviews. In contrast, applicants who possess more undesirable personality traits (i.e., low on Honesty-Humility and Conscientiousness, but high on Machiavellianism, Narcissism, Psychopathy, or Competitive Worldviews) tend to use more deceptive IM (and especially image creation tactics) and are also more likely to adapt their IM strategy across interviews. Because deceptive IM users can obtain better evaluations from interviewers and the personality profile of those users is often associated with undesirable workplace outcomes, this study provides additional evidence for the claim that deceptive IM (or faking) is a potential threat for organizations.
Las identidades de género según las y los adolescentes. Percepciones, desigualdades y necesidades educativas

This article gathers some of the findings from a doctoral thesis whose theoretical foundations defend that identities are symbolic constructions arising from the categories that each society establishes, and is based on the proposition that our western society just legitimizes the gender identities “man” and “woman”, presenting them as natural. In this way, we point out that this binary categorization causes inequalities between persons; both among those included in them, and, especially, among those who don’t fit into the binomial. From this perspective, we develop a qualitative research based on the information provided by adolescents trained as mediators in health and sexuality by the educational program Forma Joven of the Regional Government of Andalusia, which is materialized in four case studies. Specifically, in our work we show how our subjects of study understand that they have built their sexual identities and have become the persons who they are, besides analyzing the assessment they make, both those identities of their own and those assumed by other children and girls of her age. In conclusion, we provide a reflection on the educational needs related to gender that are extracted from the discourses of these adolescents.
Combining a bottom up and top down classifiers for the segmentation of the left ventricle from cardiac imagery

The segmentation of anatomical structures is a crucial first stage of most medical imaging analysis procedures. A primary example is the segmentation of the left ventricle (LV), from cardiac imagery. Accuracy in the segmentation often requires a considerable amount of expert intervention and guidance which are expensive. Thus, automating the segmentation is welcome, but difficult because of the LV shape variability within and across individuals. To cope with this difficulty, the algorithm should have the skills to interpret the shape of the anatomical structure (i.e. LV shape) using distinct kinds of information, (i.e. different views of the same feature space). These different views will ascribe to the algorithm a more general capability that surely allows for the robustness in the segmentation accuracy. In this paper, we propose an on-line co-training algorithm using a bottom-up and top-down classifiers (each one having a different view of the data) to perform the segmentation of the LV. In particular, we consider a setting in which the LV shape can be partitioned into two distinct views and use a co-training as a way to boost each of the classifiers, thus providing a principled way to use both views together. We testify the usefulness of the approach on a public data base illustrating that the approach compares favorably with other recent proposed methodologies.
Estimating and Modeling Relative Survival

When estimating patient survival using data collected by population-based cancer registries, it is common to estimate net survival in a relative-survival framework. Net survival can be estimated using the relative-survival ratio, which is the ratio of the observed survival of the patients (where all deaths are considered events) to the expected survival of a comparable group from the general population. In this article, we describe a command, strs, for life-table estimation of relative survival. We discuss three methods for estimating expected survival, as well as the cohort, period, and hybrid approaches for estimating relative survival. We also implement a life-table version of the Pohar Perme (2012, Biometrics 68: 113–120) estimator of net survival, and we describe two methods for age standardization. We also explain how, in addition to net probabilities of death, crude probabilities of death due to cancer and due to other causes can be estimated using the method of Cronin and Feuer (2000, Statistics in Medicine 19: 1729–1740). We conclude this article with discussion and examples of modeling excess mortality using various approaches, including the full-likelihood approach (using the ml command) and Poisson regression (using the glm command with a user-specified link function).
Genes predict long distance migration and large body size in a migratory fish, Pacific lamprey

Elucidation of genetic mechanisms underpinning migratory behavior could help predict how changes in genetic diversity may affect future spatiotemporal distribution of a migratory species. This ability would benefit conservation of one such declining species, anadromous Pacific lamprey (Entosphenus tridentatus). Nonphilopatric migration of adult Pacific lamprey has homogenized population‐level neutral variation but has maintained adaptive variation that differentiates groups based on geography, run‐timing and adult body form. To investigate causes for this adaptive divergence, we examined 647 adult lamprey sampled at a fixed location on the Columbia River and radiotracked during their subsequent upstream migration. We tested whether genetic variation [94 neutral and adaptive single nucleotide polymorphisms (SNPs) previously identified from a genomewide association study] was associated with phenotypes of migration distance, migration timing, or morphology. Three adaptive markers were strongly associated with morphology, and one marker also correlated with upstream migration distance and timing. Genes physically linked with these markers plausibly influence differences in body size, which is also consistently associated with migration distance in Pacific lamprey. Pacific lamprey conservation implications include the potential to predict an individual's upstream destination based on its genotype. More broadly, the results suggest a genetic basis for intrapopulation variation in migration distance in migratory species.
Computational Identification of Phospho-Tyrosine Sub-Networks Related to Acanthocyte Generation in Neuroacanthocytosis

Acanthocytes, abnormal thorny red blood cells (RBC), are one of the biological hallmarks of neuroacanthocytosis syndromes (NA), a group of rare hereditary neurodegenerative disorders. Since RBCs are easily accessible, the study of acanthocytes in NA may provide insights into potential mechanisms of neurodegeneration. Previous studies have shown that changes in RBC membrane protein phosphorylation state affect RBC membrane mechanical stability and morphology. Here, we coupled tyrosine-phosphoproteomic analysis to topological network analysis. We aimed to predict signaling sub-networks possibly involved in the generation of acanthocytes in patients affected by the two core NA disorders, namely McLeod syndrome (MLS, XK-related, Xk protein) and chorea-acanthocytosis (ChAc, VPS13A-related, chorein protein). The experimentally determined phosphoproteomic data-sets allowed us to relate the subsequent network analysis to the pathogenetic background. To reduce the network complexity, we combined several algorithms of topological network analysis including cluster determination by shortest path analysis, protein categorization based on centrality indexes, along with annotation-based node filtering. We first identified XK- and VPS13A-related protein-protein interaction networks by identifying all the interactomic shortest paths linking Xk and chorein to the corresponding set of proteins whose tyrosine phosphorylation was altered in patients. These networks include the most likely paths of functional influence of Xk and chorein on phosphorylated proteins. We further refined the analysis by extracting restricted sets of highly interacting signaling proteins representing a common molecular background bridging the generation of acanthocytes in MLS and ChAc. The final analysis pointed to a novel, very restricted, signaling module of 14 highly interconnected kinases, whose alteration is possibly involved in generation of acanthocytes in MLS and ChAc.
An Investigation of Neuronal Integrity in Severe Paediatric Traumatic Brain Injury

Magnetic Resonance Spectroscopy (MRS) and its association with neuropsychological functioning was examined in the chronic injury phase of paediatric traumatic brain injury (TBI). Fifteen children, aged 10-16 years, with severe TBIs were compared with 15 controls, matched for age and gender. The TBI group was found to have significantly lower levels of N-acetyl aspartate (NAA) and Choline (Cho) in the right frontal lobe and generally displayed reduced performances on neuropsychological tests. A correlation between metabolites and reaction times was also obtained. Findings indicate a role of proton MRS as a measure of neuronal integrity following severe paediatric TBI and suggest a potential association of MRS with specific neuropsychological impairments.