Overburdening associations: the dependency of psychopathy- related acquisitional learning deficits on processing load

Psychopathic personality traits have been identified as an important individual predictor of associative learning capacity. Prior work has associated psychopathy with deficits when adapting learned associations in response to novel information. However, findings are inconsistent and are hypothesised to vary as a function of the processing load created by different experimental paradigms. We tested this hypothesis by examining the association between psychopathic traits and Stimulus-Response-Outcome contingency learning whilst manipulating contextual processing load. In experiment one and two, participants completed three versions of a configural object discrimination task that required participants to use increasingly multidimensional learning cues. Across both experiments, it was found that elevated levels of psychopathic traits were associated with a lesser capacity to form S-R-O associations in the bidimensional but not tridimensional versions of the learning task. This suggests psychopathy-related learning deficits may vary as a function of processing load inherent to the bidimensional learning environment, rather than the type of learning taking place. This provides some of the first experimental evidence that psychopathic learning deficits are detectable during the acquisition phase of learning

Hidden Markov Models and their Application for Predicting Failure Events

We show how Markov mixed membership models (MMMM) can be used to predict the degradation of assets. We model the degradation path of individual assets, to predict overall failure rates. Instead of a separate distribution for each hidden state, we use hierarchical mixtures of distributions in the exponential family. In our approach the observation distribution of the states is a finite mixture distribution of a small set of (simpler) distributions shared across all states. Using tied-mixture observation distributions offers several advantages. The mixtures act as a regularization for typically very sparse problems, and they reduce the computational effort for the learning algorithm since there are fewer distributions to be found. Using shared mixtures enables sharing of statistical strength between the Markov states and thus transfer learning. We determine for individual assets the trade-off between the risk of failure and extended operating hours by combining a MMMM with a partially observable Markov decision process (POMDP) to dynamically optimize the policy for when and how to maintain the asset.Comment: Will be published in the proceedings of ICCS 2020; @Booklet{EasyChair:3183, author = {Paul Hofmann and Zaid Tashman}, title = {Hidden Markov Models and their Application for Predicting Failure Events}, howpublished = {EasyChair Preprint no. 3183}, year = {EasyChair, 2020}

New first trimester crown-rump length's equations optimized by structured data collection from a French general population

--- Objectives --- Prior to foetal karyotyping, the likelihood of Down's syndrome is often determined combining maternal age, serum free beta-HCG, PAPP-A levels and embryonic measurements of crown-rump length and nuchal translucency for gestational ages between 11 and 13 weeks. It appeared important to get a precise knowledge of these scan parameters' normal values during the first trimester. This paper focused on crown-rump length. --- METHODS --- 402 pregnancies from in-vitro fertilization allowing a precise estimation of foetal ages (FA) were used to determine the best model that describes crown-rump length (CRL) as a function of FA. Scan measures by a single operator from 3846 spontaneous pregnancies representative of the general population from Northern France were used to build a mathematical model linking FA and CRL in a context as close as possible to normal scan screening used in Down's syndrome likelihood determination. We modeled both CRL as a function of FA and FA as a function of CRL. For this, we used a clear methodology and performed regressions with heteroskedastic corrections and robust regressions. The results were compared by cross-validation to retain the equations with the best predictive power. We also studied the errors between observed and predicted values. --- Results --- Data from 513 spontaneous pregnancies allowed to model CRL as a function of age of foetal age. The best model was a polynomial of degree 2. Datation with our equation that models spontaneous pregnancies from a general population was in quite agreement with objective datations obtained from 402 IVF pregnancies and thus support the validity of our model. The most precise measure of CRL was when the SD was minimal (1.83mm), for a CRL of 23.6 mm where our model predicted a 49.4 days of foetal age. Our study allowed to model the SD from 30 to 90 days of foetal age and offers the opportunity of using Zscores in the future to detect growth abnormalities. --- Conclusion --- With powerful statistical tools we report a good modeling of the first trimester embryonic growth in the general population allowing a better knowledge of the date of fertilization useful in the ultrasound screening of Down's syndrome. The optimal period to measure CRL and predict foetal age was 49.4 days (9 weeks of gestational age). Our results open the way to the detection of foetal growth abnormalities using CRL Zscores throughout the first trimester

Interindividual differences in neonatal sociality and emotionality predict juvenile social status in rhesus monkeys

In humans, socioeconomic status (SES) has profound outcomes on socio-emotional development and health. However, while much is known about the consequences of SES, little research has examined the predictors of SES due to the longitudinal nature of such studies. We sought to explore whether interindividual differences in neonatal sociality, temperament, and early social experiences predicted juvenile social status in rhesus monkeys (Macaca mulatta), as a proxy for SES in humans. We performed neonatal imitation tests in infants’ first week of life and emotional reactivity assessments at 2 and 4 weeks of age. We examined whether these traits, as well the rearing environment in the first 8 months of life (with the mother or with same-aged peers only) and maternal social status predicted juvenile (2-3 years old) social status following the formation of peer social groups at 8 months. We found that infants who exhibited higher rates of neonatal imitation and newborn emotional reactivity achieved higher social status as juveniles, as did infants who were reared with their mothers, compared to infants reared with peers. Maternal social status was only associated with juvenile status for infant dyads reared in the same maternal group, indicating that relative social relationships were transferred through social experience. These results suggest that neonatal imitation and emotional reactivity may reflect ingrained predispositions towards sociality that predict later outcomes, and that non-normative social experiences can alter socio-developmental trajectories. Our results indicate that neonatal characteristics and early social experiences predict later social outcomes in adolescence, including gradients of social stratification

Sex and rank affect how infant rhesus macaques look at faces

We investigated how differences in infant sex and mothers’ dominance status affect infant rhesus macaques’ (Macaca mulatta) interest in visually exploring emotional facial expressions. Thirty-eight infants were presented with animated avatars of macaque facial expressions during the first month of life. Sons of high-ranking mothers looked more at faces, especially the eye region, than sons of low-ranking mothers, but no difference in looking duration was found for daughters. Males looked significantly more at eyes than females, but this effect was reversed in infants who were reared without mothers in a primate nursery facility. In addition, in mother-infant interactions, mothers of sons were more likely to gaze at their infant’s face compared to mothers of daughters. Combined with previous research indicating that rhesus macaque mothers interact differently with infants based on their own rank and infant’s sex, these results support the view that social experiences shape early face preferences in rhesus macaques

Defining Medical Futility and Improving Medical Care

It probably should not be surprising, in this time of soaring medical costs and proliferating technology, that an intense debate has arisen over the concept of medical futility. Should doctors be doing all the things they are doing? In particular, should they be attempting treatments that have little likelihood of achieving the goals of medicine? What are the goals of medicine? Can we agree when medical treatment fails to achieve such goals? What should the physician do and not do under such circumstances? Exploring these issues has forced us to revisit the doctor-patient relationship and the relationship of the medical profession to society in a most fundamental way. Medical futility has both a quantitative and qualitative component. I maintain that medical futility is the unacceptable likelihood of achieving an effect that the patient has the capacity to appreciate as a benefit. Both emphasized terms are important. A patient is neither a collection of organs nor merely an individual with desires. Rather, a patient (from the word “to suffer”) is a person who seeks the healing (meaning “to make whole”) powers of the physician. The relationship between the two is central to the healing process and the goals of medicine. Medicine today has the capacity to achieve a multitude of effects, raising and lowering blood pressure, speeding, slowing, and even removing and replacing the heart, to name but a minuscule few. But none of these effects is a benefit unless the patient has at the very least the capacity to appreciate it. Sadly, in the futility debate wherein some critics have failed or refused to define medical futility an important area of medicine has in large part been neglected, not only in treatment decisions at the bedside, but in public discussions—comfort care—the physician’s obligation to alleviate suffering, enhance well being and support the dignity of the patient in the last few days of life

Field Deployment of an Ambient Vibration-Based Scour Monitoring System at Baildon Bridge, UK

Scour, the loss of material around bridge foundations due to hydraulic action, is the main cause of bridge failures in the United Kingdom and in many other parts of the world. Various techniques have been used to monitor bridge scour, ranging from scuba divers using crude depth measuring instrumentation to high-tech sonar and radar-based systems. In contrast to most other techniques, vibration-based scour monitoring uses accelerometers to provide real-time monitoring whilst also being robust and relatively simple to install. This is an indirect technique that aims to measure changes in the dynamic response of the structure due to the effects of scour, rather than attempting to measure scour directly. To date, research on vibration-based scour monitoring has been limited to laboratory-based experiments and numerical simulations, both of which have indicated that the natural frequencies of bridges should indeed be sensitive to scour. Due to pre-existing scouring, and planned repair work, Baildon Bridge in Shipley, Yorkshire provided a rare opportunity to validate vibration-based scour monitoring in both a scoured and a repaired state. A sensor system was deployed with 10 Epson low-noise, high-sensitivity accelerometers to measure the ambient vibration of the bridge before, during, and after the repair. This paper describes the installation of the accelerometer-based system, the numerical modelling of the bridge and the model updating carried out with the initial findings. Initial operational modal analysis has found two consistent vibration modes of the bridge that were scour sensitive according to the updated numerical model. But the variability of the measured frequencies, compared to the expected scour induced change in frequency, indicates a potential challenge for monitoring scour of small span bridges with vibration-based methods

Detecting the orientation of magnetic fields in galaxy clusters

Clusters of galaxies, filled with hot magnetized plasma, are the largest bound objects in existence and an important touchstone in understanding the formation of structures in our Universe. In such clusters, thermal conduction follows field lines, so magnetic fields strongly shape the cluster's thermal history; that some have not since cooled and collapsed is a mystery. In a seemingly unrelated puzzle, recent observations of Virgo cluster spiral galaxies imply ridges of strong, coherent magnetic fields offset from their centre. Here we demonstrate, using three-dimensional magnetohydrodynamical simulations, that such ridges are easily explained by galaxies sweeping up field lines as they orbit inside the cluster. This magnetic drape is then lit up with cosmic rays from the galaxies' stars, generating coherent polarized emission at the galaxies' leading edges. This immediately presents a technique for probing local orientations and characteristic length scales of cluster magnetic fields. The first application of this technique, mapping the field of the Virgo cluster, gives a startling result: outside a central region, the magnetic field is preferentially oriented radially as predicted by the magnetothermal instability. Our results strongly suggest a mechanism for maintaining some clusters in a 'non-cooling-core' state.Comment: 48 pages, 21 figures, revised version to match published article in Nature Physics, high-resolution version available at http://www.cita.utoronto.ca/~pfrommer/Publications/pfrommer-dursi.pd