Miracle-dz/UniFAR-FTUs huggingface dataset:
Frontal lobe-related cognition in the context of self-disgust

Self- disgust is an adverse self-conscious emotion that plays an important role in psychopathology and well-being. However, self-disgust has received little attention in the emotion literature, therefore our understanding of the processes underlying the experience of self-disgust is relatively scarce, although neuropsychological and neuroimaging studies support the idea that this emotion may heavily rely on frontal lobe-related cognition. To test this hypothesis, in two studies we investigated the relationship between state and trait levels of self-disgust, cognition and emotion regulation in healthy adults. Specifically, in Study 1 we tested the hypothesis that emotion regulation strategies (avoidance, suppression, and cognitive reappraisal) mediate the relationship between inhibition ability and state and trait levels of self-disgust. In Study 2, we followed a more comprehensive approach to test the hypothesis that frontal lobe-related cognitive processes (updating, Theory of Mind–ToM-, and self-attention) are closely related to the experience of self-disgust in healthy adults. Overall, across these studies, we found evidence to support the idea that inhibition ability and ToM may play a role in the experience of state and trait self-disgust, respectively. However, we did not find consistent evidence across the two studies to support the notion held in the literature that the experience of self- conscious emotions, in this case self-disgust, is heavily dependent on frontal lobe-related cognition.
Supporting Indigenous students as "smart, not good" knowers and learners: the practices of two teachers

Issues of identity construction can be especially significant for Aboriginal and Torres Strait Islander adolescents in Australian schools as they seek to find a place in a society in which they may not feel valued or represented. However, the concept of Indigenous identity is complex and contested as is the relationship between Indigenous identity and school success. This paper draws on qualitative research in a small urban secondary school. It details the practices of two remarkable teachers as they work to support the diverse identities of their Aboriginal and Torres Strait Islander students in ways which also allow the students to take on identities as knowers and learners in their classrooms. Their understanding of the students' identities involved them in seeing the students in multiple ways, constantly moving between the individual interests and needs of the student, their family connections and contemporary Indigenous life. Their practices in supporting Indigenous students as knowers and learners were based on recognising the complex interactions between race, history, school structures and peer relationships. Through their practices, they intentionally rejected the reproductive tendencies of schooling and created spaces where Indigenous youth could challenge "commonsense" about themselves.
Results in Physics

We develop a Bayesian inference framework to quantify uncertainties in epidemiological models. We use SEIJR and SIJR models involving populations of susceptible, exposed, infective, diagnosed, dead and recovered individuals to infer from Covid-19 data rate constants, as well as their variations in response to lockdown measures. To account for confinement, we distinguish two susceptible populations at different risk: confined and unconfined. We show that transmission and recovery rates within them vary in response to facts, and that the diagnose rate is quite low, which leads to large amounts of undiagnosed infective individuals. A key unknown to predict the evolution of the epidemic is the fraction of the population affected by the virus, including asymptomatic subjects. Our study tracks its time evolution with quantified uncertainty from available official data, limited, however, by the data quality. We exemplify the technique with data from Spain, country in which late drastic lockdowns were enforced for months during the first wave of the current pandemic. In late actions and in the absence of other measures, spread is delayed but not stopped unless a large enough fraction of the population is confined until the asymptomatic population is depleted. To some extent, confinement can be replaced by strong distancing through masks in adequate circumstances.
Interferometric Evaluation of Sentinel-1A TOPS data

The European radar satellite Sentinel 1A was launched in April 2014 as the first of the Copernicus Space Component. The Sentinel 1 system has been conceived to provide repeat-pass interferometric capabilities with wide area coverage for medium resolution applications. Wide-swath is achieved by employing the novel TOPS (Terrain Observation by Progressive Scans) acquisition mode. The contribution of this talk focuses on an interferometric evaluation of Sentinel-1A data. A brief description of the interferometric algorithms of the Integrated Wide Area Processor at DLR is provided. The spectral properties of TOPS data are exposed and the stringent coregistration accuracy emphasized, where a pixelwise ESD-based estimator is proposed. Burst mode data require that repeat-pass acquisitions are synchronized in order to obtain coherence over distributed scatterers. An evaluation of the common Doppler bandwidth for two stack of S1A scenes is provided. By exploiting the high sensitivity of TOPS data to the measurement of the along-track shift, an assessment of the shifts is as well provided for two scenarios. In the first place a temporal analysis is done with two stacks of acquisitions in different acquisiton geometries. Geophysical effects as diferential solid Earth tides are compensated. The outcome of this analysis indicates that a mere geometric coregistration is not enough to obtain accurate interferometric results, being necessary to compensate for orbital timing errors. The second analysis focuses on the systematic evaluation of the along-track shifts for a datatake composed by several slices, where good spatial stability is shown.
Base de datos espacial geomorfológica de la franja litoral de los departamentos de Antioquia y Chocó

Johanna Prussmann-Uribe1,2 & Ivan Dario Correa-Arango1 1Area de Ciencias del Mar, Departamento de Geologia, Facultad de Ingenieria, Universidad EAFIT, sede Medellin, A.A. 3300, 2Docente de catedra, Universidad de Antioquia, Colombia jprussmann@eafit.edu. co, icorrea@eafit.edu. co Con el fin de generar informacion para el manejo integrado y el desarrollo sostenible de la franja litoral Caribe de los departamentos de Antioquia y Choco, se creo una base de datos espacial llamada GEOURABA, a partir de la fotointerpretacion y restitucion de una ortofoto tomada en el ano 2009; esta base de datos recopila la informacion geomorfologica a escala 1:10000, de los 600km del contorno litoral del sector en estudio, con una geomorfologia sumamente variada que obedece a multiples factores naturales y antropicos, incluyendo: a) la litologia y tectonica, b) los cambios en el nivel relativo del mar, c) la extraccion de materiales de playas y zonas aledanas y d) el drenaje/colmatacion de los pantanos de manglares.
Multiobjective Evolutionary Feature Selection for Fuzzy Classification

The interpretability of classification systems refers to the ability of these to express their behavior in a way that is easily understandable by a user. Interpretable classification models allow for external validation by an expert and, in certain disciplines, such as medicine or business, providing information about decision making is essential for ethical and human reasons. Fuzzy rule based classification systems are consolidated powerful classification tools based on fuzzy logic and designed to produce interpretable models; however, in presence of a large number of attributes, even rule-based models tend to be too complex to be easily interpreted. In this paper, we propose a novel multivariate feature selection method in which both search strategy and classifier are based on multiobjective evolutionary computation. We designed a set of experiments to establish an acceptable setting with respect to the number of evaluations required by the search strategy and by the classifier. We tested our strategy on a real-life dataset and compared the results against a wide range of feature selection methods that includes filter, wrapper, multivariate, and univariate methods, with deterministic and probabilistic search strategies, and with evaluators of diverse nature. Finally, the fuzzy rule based classification model obtained with the proposed method has been evaluated with standard performance metrics and compared with other well-known fuzzy rule based classifiers. We have used two real-life datasets extracted from a contact center; in one case, with the proposed method, we obtained an accuracy of 0.7857 with eight rules, while the best fuzzy classifier compared obtained 0.7679 with eight rules, and in the second case, we obtained an accuracy of 0.7403 with five rules, while the best fuzzy classifier compared obtained 0.6364 with four rules.
Field density, gradation, and triaxial testing of large-size rockfill for little blue run dam

The results of field density and gradation tests involving large-size compacted rockfill (sedimentary rocks) were used to establish gradation and compaction requirements for large-size (38-cm-diameter) and conventional (15-cm-diameter) triaxial tests. The gradation requirements were that the gradation curves for triaxial test materials should be parallel to the corresponding field gradation curve, except for minor modifications to avoid excessive inclusion of fines. The angle of internal friction decreased as maximum particle size increased, in a manner similar to that reported by others. Extrapolation was used to check the Φ-values used in design.
Clarifying Cognitive Control Deficits in Psychosis via Drift Diffusion Modeling

Cognitive control deficits are consistently identified in individuals with schizophrenia and other psychotic psychopathologies. In this analysis, we delineated proactive and reactive control deficits in psychotic psychopathology via hierarchical Drift Diffusion Modeling (hDDM). People with psychosis (PwP; N=123), their first-degree relatives (N=79), and controls (N=51) completed the Dot Pattern Expectancy task, which allows differentiation between proactive and reactive control. PwP demonstrated slower drift rates on proactive control trials suggesting less efficient use of cue information for proactive control. They also showed longer non-decision times than controls on infrequent stimuli sequences suggesting slower perceptual processing. An explainable machine learning analysis indicated that the hDDM parameters were able to differentiate between the groups better than conventional measures. Through DDM, we found that cognitive control deficits in psychosis are characterized by slower motor/perceptual time and slower evidence-integration primarily in proactive control.
Mid-Level Vorticity in Mesoscale Convective Systems.

Abstract : The objective of this study has been to examine and document the development of mid-level Mesoscale Convective Vortices (MCVs) within Mesoscale Convective Systems (MCSs) and Mesoscale Convective Complexes (MCCs) using the Central Plains Wind Profiler Demonstration Network (WPDN). Nine MCSs from the summer of 1993 were picked for this study based on their formation and lifetime spent over the WPDN. Bartels and Maddox's (1991) climatological study of MCVs for 1981 - 1988 estimated that less than 5% of MCSs exhibit a vortex whose clouds persist long enough after the dissipation of the MCSs high-level obscuring cirrus cloud to become apparent in visible satellite imagery. This low estimate of MCVs in MCSs leads to the question of how many MCSs produce MCVs. Some researchers state that the MCV is an inherent part of the MCC circulation (Velasco and Fritsch, 1987; Menard and Fritsch, 1989).
Distinctive Roles of Medial Prefrontal Cortex Subregions in Strategic Conformity to Social Hierarchy

People often align their behaviors and decisions with others' expectations, especially those of higher social positions, when they are being observed. However, little attention has been paid to the neural mechanisms underlying increased conformity to the social hierarchy under social observation. Using a preference rating task, we investigated whether and how individual preferences for novel stimuli were influenced by others' preferences by manipulating others' social hierarchy and observational context. The behavioral results showed that human participants of both sexes were more likely to change their preferences to match those of a superior partner in a public than in a private context. fMRI data revealed distinct contributions of the subregions of the medial prefrontal cortex (mPFC) to increased conformity to social hierarchy under observation. Specifically, the ventral mPFC showed increased activity when participants' preferences aligned with those of superior partners, regardless of behavioral manifestation. The rostral mPFC showed increased activity when conforming to a superior partner and nonconforming to an inferior one, indicating goal-dependent valuation. The dorsal mPFC showed increased activity in private conditions with a superior partner but only in those with a higher tendency to conform. These findings support the hierarchical allostatic regulation model of the mPFC function for social valuation and suggest strategic conformity as a way to minimize metabolic costs. SIGNIFICANCE STATEMENT This study revealed distinct roles of subregions of the mPFC in increased conformity to individuals of different social ranks under observation. Specifically, the ventral mPFC showed increased activity when participants' preferences aligned with those of higher-ranking partners, whereas the rostral mPFC showed increased activity when conforming to a superior partner and nonconforming to an inferior partner, indicating goal-dependent valuation. The dorsal mPFC was more active in private conditions with a superior partner but only in those with a higher tendency to conform. These findings support the hierarchical allostatic regulation model of the mPFC function for social valuation and suggest strategic conformity as a way to minimize metabolic costs.
Computational facial analysis for rare Mendelian disorders

With the advances in computer vision, computational facial analysis has become a powerful and effective tool for diagnosing rare disorders. This technology, also called next‐generation phenotyping (NGP), has progressed significantly over the last decade. This review paper will introduce three key NGP approaches. In 2014, Ferry et al. first presented Clinical Face Phenotype Space (CFPS) trained on eight syndromes. After 5 years, Gurovich et al. proposed DeepGestalt, a deep convolutional neural network trained on more than 21,000 patient images with 216 disorders. It was considered a state‐of‐the‐art disorder classification framework. In 2022, Hsieh et al. developed GestaltMatcher to support the ultra‐rare and novel disorders not supported in DeepGestalt. It further enabled the analysis of facial similarity presented in a given cohort or multiple disorders. Moreover, this article will present the usage of NGP for variant prioritization and facial gestalt delineation. Although NGP approaches have proven their capability in assisting the diagnosis of many disorders, many limitations remain. This article will introduce two future directions to address two main limitations: enabling the global collaboration for a medical imaging database that fulfills the FAIR principles and synthesizing patient images to protect patient privacy. In the end, with more and more NGP approaches emerging, we envision that the NGP technology can assist clinicians and researchers in diagnosing patients and analyzing disorders in multiple directions in the near future.
A History of Suicide Attempt Is Associated with Increased Sympathetic Activation in Bipolar Disorder

Objective Suicide risk in bipolar disorder (BD) is estimated to be up to 20 times higher than in the general population. While there is a large body of evidence suggesting that increased sympathetic activation is associated with disease and death, there is a paucity of research on the role of autonomic nervous system (ANS) dysfunction in patients with BD who have attempted suicide. Methods Fifty-three participants with BD used a wearable device to assess the association between history of suicide attempt, current suicidal ideation, and ANS dysfunction, including measures of heart rate variability (HRV) and respiratory rate. Data were analyzed in a series of unadjusted and adjusted bivariate models of association controlling for relevant variables. Results A history of suicide attempts was significantly associated with an increase in respiratory rate (p < 0.01). These results remained significant after adjusting for age, BMI, and current mood state. There was no association between current suicidal ideation and heart rate or respiratory rate. In the frequency domain, HRV parameters suggest reduced parasympathetic (i.e., vagal) activity in participants with a history of suicide attempts and in those with current suicidality, suggesting changes in sympathicovagal balance in BD. Conclusions Our results suggest that changes in the ANS in patients with BD and a history of suicide attempt are not restricted to pure vagally mediated HRV parameters, but rather signal a general ANS dysregulation. This ANS imbalance may be contributing to illness burden and cardiovascular disease. Further research on the relationship between ANS and suicidality in BD is needed.
Longitudinal profiling of the intestinal microbiome in children with cystic fibrosis treated with elexacaftor-tezacaftor-ivacaftor

ABSTRACT The intestinal microbiome influences growth and disease progression in children with cystic fibrosis (CF). Elexacaftor-tezacaftor-ivacaftor (ELX/TEZ/IVA), the newest pharmaceutical modulator for CF, restores the function of the pathogenic mutated CF transmembrane conductance regulator (CFTR) channel. We performed a single-center longitudinal analysis of the effect of ELX/TEZ/IVA on the intestinal microbiome, intestinal inflammation, and clinical parameters in children with CF. Following ELX/TEZ/IVA, children with CF had significant improvements in body mass index and percent predicted forced expiratory volume in one second, and required fewer antibiotics for respiratory infections. Intestinal microbiome diversity increased following ELX/TEZ/IVA coupled with a decrease in the intestinal carriage of Staphylococcus aureus, the predominant respiratory pathogen in children with CF. There was a reduced abundance of microbiome-encoded antibiotic resistance genes. Microbial pathways for aerobic respiration were reduced after ELX/TEZ/IVA. The abundance of microbial acid tolerance genes was reduced, indicating microbial adaptation to increased CFTR function. In all, this study represents the first comprehensive analysis of the intestinal microbiome in children with CF receiving ELX/TEZ/IVA. IMPORTANCE Cystic fibrosis (CF) is an autosomal recessive disease with significant gastrointestinal symptoms in addition to pulmonary complications. Recently approved treatments for CF, CF transmembrane conductance regulator (CFTR) modulators, are anticipated to substantially improve the care of people with CF and extend their lifespans. Prior work has shown that the intestinal microbiome correlates with health outcomes in CF, particularly in children. Here, we study the intestinal microbiome of children with CF before and after the CFTR modulator, ELX/TEZ/IVA. We identify promising improvements in microbiome diversity, reduced measures of intestinal inflammation, and reduced antibiotic resistance genes. We present specific bacterial taxa and protein groups which change following ELX/TEZ/IVA. These results will inform future mechanistic studies to understand the microbial improvements associated with CFTR modulator treatment. This study demonstrates how the microbiome can change in response to a targeted medication that corrects a genetic disease.
Clinical efficacy and safety of chimeric antigen receptor T‐cell therapy for mantle cell lymphoma with secondary central nervous system involvement

Data describing outcomes of chimeric antigen receptor (CAR) T‐cell therapy in patients with secondary central nervous system (SCNS) involvement of mantle cell lymphoma (MCL) are limited. We identified 10 patients with MCL and SCNS involvement treated with anti‐CD19 CAR T‐cell therapy at three US academic centres. Frequent objective responses were observed in the CNS (86%) and systemically (90%), and the 1‐year progression‐free survival was 47%. Seven patients developed immune‐effector‐cell‐associated‐neurotoxicity‐syndrome (n = 2 Grade 1, n = 5 Grade 3). Our results suggest that anti‐CD19 CAR T‐cell therapy in this setting is feasible and additional data regarding neurotoxicity in this population may be warranted.
Integration of Person-Centered Narratives Into the Electronic Health Record

Background Care delivery that is not person-centered has been called discordant care. There has been a shift to incorporate more of a person’s narrative into their individual healthcare treatment plan to reduce discordant care. Aligning with this shift in healthcare delivery, we developed a person-centered narrative intervention (PCNI) to address existing gaps in delivery of person-centered care. Objectives This study aimed to evaluate the feasibility of conducting a randomized study and describe the outcomes of PCNI to usual care on the following person (patient)-reported outcomes: perceptions of the quality of communication with their nurses and their psychosocial and existential well-being. Methods This study’s design was an Obesity-Related Behavioral Intervention Trials model Phase II proof-of-concept randomized study. The participants were people admitted to an acute care hospital diagnosed with heart failure and/or end-stage renal disease. Results Despite COVID-19 challenges, the PCNI was feasible in an acute care setting; it showed a moderate positive difference between conditions in the person’s perception of their quality of communication and a small positive difference in their perception of feeling heard and understood. For our secondary outcomes of anxiety, depression, and psychosocial illness effect, there were small or no effects in the acute care setting. Discussion Using a person-centered narrative, such as the PCNI, can help inform delivery of care that incorporates a person’s (patient’s) beliefs, values, and preferences into their healthcare. This study used a pragmatic approach to evaluate the PCNI in real time in an acute care setting to assess patient-reported outcomes. These positive results in a small sample indicate the need for continued testing of the PCNI. These promising effects require further testing in a Phase III efficacy study within a larger randomized controlled clinical trial.