Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Visualisations and Automatic Warning Cues for Visual Search in Vascular Images

Visual search is a task that is performed in various application domains. We examine it in the domain of radiological analysis of 3D vascular images. We compare several major visualisations used in this domain, and we study the possible benefits of automatic warning systems that highlight the sections that may contain visual targets and hence require the user’s attention. With help of a literature study, we present some theory about what result can be expected given the accuracy of a particular visual cue. We present the results of two experiments, in which we find that the Curved Planar Reformation visualisation, which presents a cross-section based on knowledge about the position of the blood vessel, is significantly more efficient than regular 3D visualisations, and that automatic warning systems that produce false alarms could work if they do not miss targets.
The Relationship between Maternal Plasma Leptin and Adiponectin Concentrations and Newborn Adiposity

Increased maternal blood concentrations of leptin and decreased adiponectin levels, which are common disturbances in obesity, may be involved in offspring adiposity by programming fetal adipose tissue development. The aim of this study was to assess the relationship between maternal leptin and adiponectin concentrations and newborn adiposity. This was a cross-sectional study involving 210 healthy mother-newborn pairs from a public maternity hospital in São Paulo, Brazil. Maternal blood samples were collected after delivery and leptin and adiponectin concentrations were measured by enzyme-linked immunosorbent assay. Newborn body composition was estimated by air displacement plethysmography. The association between maternal leptin and adiponectin concentrations and newborn adiposity (fat mass percentage, FM%) was evaluated by multiple linear regression, controlling for maternal age, socioeconomic status, parity, pre-pregnancy body mass index (BMI), weight gain, gestational age, and newborn age at the time of measurement. No relationship was found between maternal leptin and FM% of male or female newborn infants. Maternal adiponectin (p = 0.001) and pre-pregnancy BMI (p < 0.001; adj. R2 = 0.19) were positively associated with FM% of newborn males, indicating that maternal adiponectin is involved in fetal fat deposition in a sex-specific manner. Large-scale epidemiological, longitudinal studies are necessary to confirm our results.
Ethanol Consumption during Early Pregnancy Alters the Disposition of Tangentially Migrating GABAergic Interneurons in the Fetal Cortex

Consumption of alcohol (ethanol) during pregnancy can lead to developmental defects in the offspring, the most devastating being the constellation of symptoms collectively referred to as fetal alcohol syndrome (FAS). In the brain, a hallmark of FAS is abnormal cerebral cortical morphology consistent with insult during corticogenesis. Here, we report that exposure to a relatively low level of ethanol in utero (average maternal and fetal blood alcohol level of 25 mg/dl) promotes premature tangential migration into the cortical anlage of primordial GABAergic interneurons, including those originating in the medial ganglionic eminence (MGE). This ethanol-induced effect was evident in vivo at embryonic day 14.5 (E14.5) in GAD67 knock-in and BAC-Lhx6 embryos, as well as in vitro in isotypic telencephalic slice cocultures obtained from E14.5 embryos exposed to ethanol in utero. Analysis of heterotypic cocultures indicated that both cell-intrinsic and -extrinsic factors contribute to the aberrant migratory profile of MGE-derived cells. In this light, we provide evidence for an interaction between ethanol exposure in utero and the embryonic GABAergic system. Exposure to ethanol in utero elevated the ambient level of GABA and increased the sensitivity to GABA of MGE-derived cells. Our results uncovered for the first time an effect of ethanol consumption during pregnancy on the embryonic development of GABAergic cortical interneurons. We propose that ethanol exerts its effect on the tangential migration of GABAergic interneurons extrinsically by modulating extracellular levels of GABA and intrinsically by altering GABAA receptor function.
Mothers' experiences of serious life events increase the risk of diabetes-related autoimmunity in their children.

OBJECTIVE Stressful life events have been shown to constitute a risk factor for type 1 diabetes during childhood. Our aim was to investigate in the general child population (i.e., irrespective of genetic risk for type 1 diabetes) whether mothers' experiences of serious life events, such as divorce and violence, were associated with diabetes-related autoimmunity in their children at age 2.5 years. RESEARCH DESIGN AND METHODS The study cohort was comprised of the first 5,986 consecutive children and their families from the prospective population-based All Babies in Southeast Sweden project for whom 2.5-year study data were available. Data were drawn from parental questionnaires that included questions about experiences of serious life events and the blood samples taken from the children when the children were age 2.5 years. The blood samples were analyzed for diabetes-related autoantibodies against tyrosine phosphatase and GAD. RESULTS Mothers' experiences of divorce (odds ratio 3.6, 95% CI 1.4-9.6, P < 0.05) and violence (2.9, 1.0-7.8, P < 0.05) were associated with diabetes-related autoimmunity in the children, independent of a family history of type 1 diabetes. CONCLUSIONS The results support the beta-cell stress hypothesis and suggest that maternal experiences of serious life events such as divorce and violence seem to be involved in the induction or progression of diabetes-related autoimmunity in children at age 2.5 years, independent of family history of type 1 diabetes.
Measuring Inappropriate Sexual Behavior Among University Students: Using the Randomized Response Technique to Enhance Self-Reporting

This article analyzes the efficacy of the randomized response technique (RRT) in achieving honest self-reporting about sexual behavior, compared with traditional survey techniques. A complex survey was conducted of 1,246 university students in Spain, who were asked sensitive quantitative questions about their sexual behavior, either via the RRT (n = 754) or by direct questioning (DQ) (n = 492). The RRT estimates of the number of times that the students were unable to restrain their inappropriate sexual behavior were significantly higher than the DQ estimates, among both male and female students. The results obtained suggest that the RRT method elicits higher values of self-stigmatizing reports of sexual experiences by increasing privacy in the data collection process. The RRT is shown to be a useful method for investigating sexual behavior.
A study of stress as a predictor of irrational decision making for workers in the financial services sector

The purpose of this paper is to investigate the relationship between stress and decision making in the financial services industry. To this end, this paper examines whether individuals who record a high score on the Perceived Stress Scale are more prone to irrational decision making. According to rational choice theory, the preference between options should not change or reverse due to changes in how the option is framed. This paper adopts a cross-sectional research design and takes a quantitative approach, with a questionnaire administered to 264 people, of which 168 are employed in financial services, with the latter group forming the sample population. A snowball and convenience approach was taken to distribute the survey. Data analysis is performed, with hypotheses supported that a higher stressed group are more likely to make irrational decisions on framing effect experiments replicated from studies by Tversky and Kahneman (1981) and Rubinstein (2003). The results show that higher stress levels can be a predictor of irrational decision making. A logistic regression model is built to test the data, but does not account for a high degree of variance. As the findings point towards a positive relationship between stress and cognitive bias in decision making, this paper adds to existing research on how employee performance and decision-making capabilities are being impacted by stress, and supports the validity of the existing framing experiments.
Dynamic Input Conductances Shape Neuronal Spiking1,2

Reliable neuron activity is ensured by a tight regulation of the ion channels that resides in the neuron’s membrane. Understanding the causal mechanisms that relate this regulation to physiological and pathological neuronal activity is a necessary step for developing efficient therapies for neurological diseases associated with abnormal nervous system activity. Abstract Assessing the role of biophysical parameter variations in neuronal activity is critical to the understanding of modulation, robustness, and homeostasis of neuronal signalling. The paper proposes that this question can be addressed through the analysis of dynamic input conductances. Those voltage-dependent curves aggregate the concomitant activity of all ion channels in distinct timescales. They are shown to shape the current−voltage dynamical relationships that determine neuronal spiking. We propose an experimental protocol to measure dynamic input conductances in neurons. In addition, we provide a computational method to extract dynamic input conductances from arbitrary conductance-based models and to analyze their sensitivity to arbitrary parameters. We illustrate the relevance of the proposed approach for modulation, compensation, and robustness studies in a published neuron model based on data of the stomatogastric ganglion of the crab Cancer borealis.
Structure of YciI from Haemophilus influenzae (HI0828) reveals a ferredoxin‐like α/β‐fold with a histidine/aspartate centered catalytic site

Mark A. Willis, Feng Song, Zhihao Zhuang, Wojciech Krajewski, Vani Rao Chalamasetty, Prasad Reddy, Andrew Howard, Debra Dunaway-Mariano, and Osnat Herzberg* Center for Advanced Research in Biotechnology, University of Maryland Biotechnology Institute, Rockville, Maryland Department of Chemistry, University of New Mexico, Albuquerque, New Mexico The National Institute of Standards and Technology, Gaithersburg, Maryland Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois Biological, Chemical, and Physical Sciences, Illinois Institute of Technology, Chicago, Illinois
Subnormalized states and trace-nonincreasing maps

We investigate the set of completely positive, trace-nonincreasing linear maps acting on the set MN of mixed quantum states of size N. Extremal point of this set of maps are characterized and its volume with respect to the Hilbert-Schmidt (HS) (Euclidean) measure is computed explicitly for an arbitrary N. The spectra of partially reduced rescaled dynamical matrices associated with trace-nonincreasing completely positive maps belong to the N cube inscribed in the set of subnormalized states of size N. As a by-product we derive the measure in MN induced by partial trace of mixed quantum states distributed uniformly with respect to the HS measure in MN2.
Bounds on the maximum likelihood decoding error probability of low density parity check codes

We derive bounds on the error probability of ML decoded LDPC (low density parity check) codes, for any binary-input symmetric-output channel. For appropriately chosen ensembles of LDPC codes, reliable communication is possible up to channel capacity. The lower and upper bounds coincide asymptotically, indicating a polynomially decreasing ensemble averaged error probability. For ensembles with suitably chosen parameters, the error probability of almost all codes is exponentially decreasing. Furthermore, the error exponent can be set arbitrarily close to the standard random coding exponent.
Gestational Diabetes Mellitus: Clinical Predictors and Long-Term Risk of Developing Type 2 Diabetes

OBJECTIVE—We sought to determine the long-term risk of type 2 diabetes following a pregnancy complicated by gestational diabetes mellitus (GDM) and assess what maternal antepartum, postpartum, and neonatal factors are predictive of later development of type 2 diabetes. RESEARCH DESIGN AND METHODS—This was a retrospective cohort study using survival analysis on 5,470 GDM patients and 783 control subjects who presented for postnatal follow-up at the Mercy Hospital for Women between 1971 and 2003. RESULTS—Risk of developing diabetes increased with time of follow-up for both groups and was 9.6 times greater for patients with GDM. The cumulative risk of developing type 2 diabetes for the GDM patients was 25.8% at 15 years postdiagnosis. Predictive factors for the development of type 2 diabetes were use of insulin (hazard ratio 3.5), Asian origin compared with Caucasian (2.1), and 1-h blood glucose (1.3 for every 1 mmol increase above 10.1 mmol). BMI was associated with an increased risk of developing type 2 diabetes but did not meet the assumption of proportional hazards required for valid inference when using Cox proportional hazards. CONCLUSIONS—While specific predictive factors for the later development of type 2 diabetes can be identified in the index pregnancy, women with a history of GDM, as a group, are worthy of long-term follow-up to ameliorate their excess cardiovascular risk.
The generalized temporal role mining problem

Role mining, the process of deriving a set of roles from the available user-permission assignments, is considered to be an essential step in successful implementation of Role-Based Access Control RBAC systems. Traditional role mining techniques, however, are not equipped to handle temporal extensions of RBAC like the Temporal-RBAC TRBAC model. In this paper, we formally define the problem of finding a minimal set of roles from temporal user-permission assignments, such that in the resulting TRBAC system, users acquire either the same or a subset of the permissions originally assigned to them for the complete or partial durations of time as specified in the input. We show that the problem is NP-complete and propose a greedy algorithm for solving it. Our algorithm first derives a set of candidate roles from the temporal user-permission assignments and then selects the least possible number of roles from the candidate role set. The final output consists of a set of roles, a user-to-role assignment relation, a role-to-permission assignment relation and a role enabling base describing the time durations for which each role is enabled. Performance of the proposed approach has been evaluated on a number of synthetic as well as real-world datasets.
Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography

Functional neuroimaging is a vital element of neuroscience and cognitive research and, increasingly, is an important clinical tool. Diffuse optical imaging is an emerging, noninvasive technique with unique portability and hemodynamic contrast capabilities for mapping brain function in young subjects and subjects in enriched or clinical environments. We have developed a high-performance, high-density diffuse optical tomography (DOT) system that overcomes previous limitations and enables superior image quality. We show herein the utility of the DOT system by presenting functional hemodynamic maps of the adult human visual cortex. The functional brain images have a high contrast-to-noise ratio, allowing visualization of individual activations and highly repeatable mapping within and across subjects. With the improved spatial resolution and localization, we were able to image functional responses of 1.7 cm in extent and shifts of <1 cm. Cortical maps of angle and eccentricity in the visual field are consistent with retinotopic studies using functional MRI and positron-emission tomography. These results demonstrate that high-density DOT is a practical and powerful tool for mapping function in the human cortex.
Sparsity-Based DOA Estimation of Coherent and Uncorrelated Targets With Flexible MIMO Radar

This paper considers the direction of arrival (DOA) estimation of coherent and uncorrelated targets by exploiting a flexible multiple input multiple output radar. First, the proposed radar is generalized with two coprime expansion factors for enlarging the inter-element spacing of transmit and receive arrays, referred to as sparse arrays with flexible inter-element spacing (SA-FIS), which shows that the conventional nested or coprime ones are the special cases. The range of consecutive lags and the number of unique lags in the sum-difference coarray are derived in closed form. It is verified that SA-FIS can obtain the maximum unique lags and also suppress the mutual coupling effects. We then extend the FIS viewpoint to sparse nonuniform linear arrays, where the two-level nested and coprime arrays are employed to achieve a significant increase in degrees of freedom (DOFs). Furthermore, to fully utilize these unique lags, we propose a reduced-complexity two-step sparse representation algorithm. By modifying and removing the off-diagonal elements of the estimated target covariance matrix, the proposed method can just identify the diagonal ones, thereby leading to further improved performance with much lower computational complexity. Finally, the Cramér-Rao bound on DOAs and correlated coefficients for SA-FIS is derived. Numerical simulations demonstrate the superiority of the proposed method with SA-FIS in terms of DOFs, computations, estimation accuracy, and resolution capability compared with previous ones.
Likey: Unsupervised Language-Independent Keyphrase Extraction

Likey is an unsupervised statistical approach for keyphrase extraction. The method is language-independent and the only language-dependent component is the reference corpus with which the documents to be analyzed are compared. In this study, we have also used another language-dependent component: an English-specific Porter stemmer as a preprocessing step. In our experiments of keyphrase extraction from scientific articles, the Likey method outperforms both supervised and unsupervised baseline methods.
A Directory Cache with Dynamic Private-Shared Partitioning

As the core counts increase in each chip multiprocessor generation, coherence protocols should improve scalability inperformance, area, and energy consumption to meet the demandsof larger core counts. Directory-based protocols constitute themost scalable alternative. A conventional directory, however, suffers from an inefficient use of storage and energy. First, thelarge, non-scalable, sharer vectors consume unnecessary area andleakage, especially considering that most of the blocks trackedin a directory are cached by a single core. Second, althoughincreasing directory size and associativity could boost systemperformance, it would come at expenses of energy consumption. This paper proposes the Dynamic Way Partitioning (DWP) Directory, a directory structure that exploits three main workloadcharacteristics to achieve area and energy reductions. First, it iswidely known that even in parallel workloads most of the accessedcache blocks are private. Second, most directory accesses targetthe small number of shared blocks. Third, the shared/privateratio of entries in the directory varies across applications andacross different execution phases within the applications. To takeadvantage of these three characteristics, DWP-Directory reducesthe number of ways with storage for shared blocks and it allowsthis storage to be powered off or on at run-time according to thedynamic requirements of the applications. DWP-Directory is compared to a conventional directory cachewith different associativity degrees and with two state-of-the-artschemes: PS-Directory and Hybrid Representation. Experimentalresults for 32-core CMPs show that DWP-Directory achievesthe best of both worlds: similar performance as a traditionaldirectory with high associativity, and similar area as recentstate-of-the-art schemes. In addition, DWP-Directory reducesstatic and dynamic power consumption by 38.0% and 67.4%,respectively compared to conventional sparse directories.
Tooth agenesis patterns and phenotype variation in a cohort of Belgian patients with hypodontia and oligodontia clustered in 79 families with their pedigrees.

BACKGROUND Even though tooth agenesis is the most common developmental anomaly of the human dentition, its genetic background and pathogenic mechanism(s) still remain poorly understood. Syndromic and isolated forms of hypodontia have been described and can occur sporadically or in families. OBJECTIVES We describe and analyse the hypo-/oligodontia phenotype variations in families. The index patient suffers from severe or mild hypodontia; case-parents/sib records are available. Furthermore, we aim to evaluate whether the different agenesis patterns in the pedigrees are predictive of mutations in specific genes based on reported genotype-phenotype associations. MATERIALS AND METHODS Dental records and pedigrees were collected from 79 families. In 67 families, the index patient presented with oligodontia while in 12 families with hypodontia. The phenotype data of 66 oligodontia index patients were analysed with the Tooth Agenesis Code software. RESULTS Nine families counted two members; one family counted three members affected with oligodontia. Twenty-four oligodontia families respectively had one (n = 17), two (n = 4), three (n = 2) or four (n = 1) additional family members presenting with hypodontia. Of the 77 oligodontia cases, two showed the same tooth agenesis pattern, while 75 patients showed unique tooth agenesis patterns. CONCLUSIONS Despite familial aggregation and expected Mendelian segregation, the number of missing teeth in the familial hypo-/oligodontia phenotypes and the tooth agenesis patterns are highly variable between the affected family members. Therefore, we hypothesize that tooth agenesis is not (always) a simple monogenic condition, but additional genetic or environmental factors can modify the expression of the phenotype.
Prognostic implications of autonomic function assessed by analyses of catecholamines and heart rate variability in stable angina pectoris

Objective: To assess the prognostic impact of autonomic activity, as reflected by catecholamines and heart rate variability (HRV), in patients with stable angina pectoris. Design: Double blind, randomised treatment with metoprolol or verapamil. 24 hour ambulatory ECG, used for frequency domain analyses of HRV, and symptom limited exercise tests at baseline and after one month of treatment. Catecholamine concentrations were measured in plasma (rest and exercise) and urine. Setting: Single centre at a university hospital. Patients: 641 patients (449 men) with stable angina pectoris. Main outcome measures: Cardiovascular (CV) death, non-fatal myocardial infarction (MI). Results: During follow up (median 40 months) there were 27 CV deaths and 26 MIs. Patients who died of CV causes had lower total power and high (HF), low (LF), and very low (VLF) frequency components of HRV. HRV was not altered in patients who suffered non-fatal MI. Catecholamines did not differ between patients with and those without events. Metoprolol increased HRV. Verapamil decreased noradrenaline (norepinephrine) excretion. Multivariate Cox analyses showed that total power, HF, LF, and VLF independently predicted CV death (also non-sudden death) but not MI. LF:HF ratios and catecholamines were not related to prognosis. Treatment effects on HRV did not influence prognosis. Conclusions: Low HRV predicted CV death but not non-fatal MI. Neither the LF:HF ratio nor catecholamines carried any prognostic information. Metoprolol and verapamil influenced LF, HF, and catecholamines differently but treatment effects were not related to prognosis.