Wave propagation and growth on a surface front in a two-layer geostrophic current

We study analytically and numerically small amplitude perturbations of a geostrophically balanced semi-infinite layer of light water having a surface front and lying above a heavier layer of finite vertical thickness which is at rest in the mean. In contrast with previous studies where the latter layer was infinitely deep we find that the equilibrium is always unstable regardless of the distribution of potential vorticity, and the maximum growth rates are generally much larger than in the one-layer case. The amplifying ageostrophic wave transfers kinetic energy from the basic shear flow as well as potential energy. Good quantitative agreement is found with the laboratory experiments of Griffiths and Linden (1982), and our model seems to be the simplest one for future investigations of cross frontal mixing processes by finite amplitude waves. The propagation speed of very low frequency and nondispersive frontal waves is also computed and is shown to decrease with increasing bottom layer depth

The relationship between worry, rumination, and comorbidity: Evidence for repetitive negative thinking as a transdiagnostic construct

Background: Repetitive negative thinking (RNT) increases vulnerability to multiple anxiety and depressive disorders and, as a common risk factor, elevated RNT may account for the high levels of comorbidity observed between emotional disorders. The aims of this study were to (a) compare two common forms of RNT (worry and rumination) across individuals with non-comorbid anxiety or depressive disorders, and (b) to examine the relationship between RNT and comorbidity.Methods: A structured diagnostic interview and measures of rumination, worry, anxiety, and depression were completed by a large clinical sample with an anxiety disorder or depression (N=513) presenting at a community mental health clinic.Results: Patients without (n=212) and with (n=301) comorbid diagnoses did not generally differ across the principal diagnosis groups (depression, generalised anxiety disorder, social anxiety disorder, panic disorder) on worry or rumination. As predicted, comorbidity was associated with a higher level of RNT.Limitations: Cross-sectional design precluded causal conclusions and findings may not generalize to excluded anxiety disorders.Conclusions: Consistent with the transdiagnostic hypothesis, RNT was associated with a range of anxiety disorders and depression and with comorbidity for those with a principal depressive disorder, supporting recent evidence that RNT is a transdiagnostic process. The presence of RNT, specifically worry and rumination, should be assessed and treated regardless of diagnostic profile. Future research may show that both pure and comorbid depressed or anxious patients receive incremental benefit from transdiagnostic protocols developed to treat core pathological processes of RNT traditionally associated with separate disorders

Thermal modeling of subduction zones with prescribed and evolving 2D and 3D slab geometries

The determination of the temperature in and above the slab in subduction zones, using models where the top of the slab is precisely known, is important to test hypotheses regarding the causes of arc volcanism and intermediate-depth seismicity. While 2D and 3D models can predict the thermal structure with high precision for fixed slab geometries, a number of regions are characterized by relatively large geometrical changes. Examples include the flat slab segments in South America that evolved from more steeply dipping geometries to the present day flat slab geometry. We devise, implement, and test a numerical approach to model the thermal evolution of a subduction zone with prescribed changes in slab geometry over time. Our numerical model approximates the subduction zone geometry by employing time dependent deformation of a B\'ezier spline which is used as the slab interface in a finite element discretization of the Stokes and heat equations. We implement the numerical model using the FEniCS open source finite element suite and describe the means by which we compute approximations of the subduction zone velocity, temperature, and pressure fields. We compute and compare the 3D time evolving numerical model with its 2D analogy at cross-sections for slabs that evolve to the present-day structure of a flat segment of the subducting Nazca plate

Postmortem tissue distribution of morphine and its metabolites in a series of heroin related deaths

The abuse of heroin (diamorphine) and heroin deaths are growing around the world. The interpretation of the toxicological results from suspected heroin deaths is notoriously difficult especially in cases where there may be limited samples. In order to help forensic practitioners with heroin interpretation we determined the concentration of morphine (M), morphine‐3‐glucuronide (M3G) and morphine‐6‐glucuronide (M6G) in blood (femoral and cardiac), brain (thalamus), liver (deep right lobe), bone marrow (sternum), skeletal muscle (psoas) and vitreous humor in 44 heroin related deaths. The presence of 6‐monoacetylmorphine (6‐MAM) in any of the postmortem samples was used as confirmation of heroin use. Quantitation was carried out using a validated LC‐MS/MS method with solid phase extraction. We also determined the presence of papaverine, noscapine and codeine in the samples, substances often found in illicit heroin and that may help determine illicit heroin use. The results of this study show that vitreous is the best sample to detect 6‐MAM (100% of cases), and thus heroin use. The results of the M, M3G and M6G quantitation in this study allow a degree of interpretation when samples are limited. However in some cases it may not be possible to determine heroin/morphine use as in 4 cases in muscle (3 cases in bone marrow) no morphine, morphine‐3‐glucuronide or morphine‐6‐glucuronide was detected, even though they were detected in other case samples. As always postmortem cases of suspected morphine/heroin intoxication should be interpreted with care and with as much case knowledge as possible

A divergence free C0C^0-RIPG stream function formulation of the incompressible Stokes system with variable viscosity

Pointwise divergence free velocity field approximations of the Stokes system are gaining popularity due to their necessity in precise modelling of physical flow phenomena. Several methods have been designed to satisfy this requirement; however, these typically come at a greater cost when compared with standard conforming methods, for example, because of the complex implementation and development of specialized finite element bases. Motivated by the desire to mitigate these issues for 2D simulations, we present a $C^0$-interior penalty Galerkin (IPG) discretization of the Stokes system in the stream function formulation. In order to preserve a spatially varying viscosity this approach does not yield the standard and well known biharmonic problem. We further employ the so-called robust interior penalty Galerkin (RIPG) method; stability and convergence analysis of the proposed scheme is undertaken. The former, which involves deriving a bound on the interior penalty parameter is particularly useful to address the $\mathcal{O}(h^{-4})$ growth in the condition number of the discretized operator. Numerical experiments confirming the optimal convergence of the proposed method are undertaken. Comparisons with thermally driven buoyancy mantle convection model benchmarks are presented

A new and unusual LBV-like outburst from a Wolf–Rayet star in the outskirts of M33

MCA-1B (also called UIT003) is a luminous hot star in the western outskirts of M33, classified over 20 yr ago with a spectral type of Ofpe/WN9 and identified then as a candidate luminous blue variable (LBV). Palomar Transient Factory data reveal that this star brightened in 2010, with a light curve resembling that of the classic LBV star AF And in M31. Other Ofpe/WN9 stars have erupted as LBVs, but MCA-1B was unusual because it remained hot. It showed a WN-type spectrum throughout its eruption, whereas LBVs usually get much cooler. MCA-1B showed an almost four-fold increase in bolometric luminosity and a doubling of its radius, but its temperature stayed ≳29 kK. As it faded, it shifted to even hotter temperatures, exhibiting a WN7/WN8-type spectrum, and doubling its wind speed. MCA-1B is reminiscent of some supernova impostors, and its location resembles the isolated environment of SN 2009ip. It is most similar to HD 5980 (in the Small Magellanic Cloud) and GR 290 (also in M33). Whereas these two LBVs exhibited B-type spectra in eruption, MCA-1B is the first clear case where a Wolf–Rayet (WR) spectrum persisted at all times. Together, MCA-1B, HD 5980, and GR 290 constitute a class of WN-type LBVs, distinct from S Doradus LBVs. They are most interesting in the context of LBVs at low metallicity, a possible post-LBV/WR transition in binaries, and as likely Type Ibn supernova progenitors

Timing of Intervention Affects Brain Electrical Activity in Children Exposed to Severe Psychosocial Neglect

Background: Early psychosocial deprivation has profound effects on brain activity in the young child. Previous reports have shown increased power in slow frequencies of the electroencephalogram (EEG), primarily in the theta band, and decreased power in higher alpha and beta band frequencies in infants and children who have experienced institutional care. Methodology/Principal Findings: We assessed the consequences of removing infants from institutions and placing them into a foster care intervention on brain electrical activity when children were 8 years of age. We found the intervention was successful for increasing high frequency EEG alpha power, with effects being most pronounced for children placed into foster care before 24 months of age. Conclusions/Significance: The dependence on age of placement for the effects observed on high frequency EEG alpha power suggests a sensitive period after which brain activity in the face of severe psychosocial deprivation is less amenable to recover

Enabling scalable clinical interpretation of ML-based phenotypes using real world data

The availability of large and deep electronic healthcare records (EHR) datasets has the potential to enable a better understanding of real-world patient journeys, and to identify novel subgroups of patients. ML-based aggregation of EHR data is mostly tool-driven, i.e., building on available or newly developed methods. However, these methods, their input requirements, and, importantly, resulting output are frequently difficult to interpret, especially without in-depth data science or statistical training. This endangers the final step of analysis where an actionable and clinically meaningful interpretation is needed.This study investigates approaches to perform patient stratification analysis at scale using large EHR datasets and multiple clustering methods for clinical research. We have developed several tools to facilitate the clinical evaluation and interpretation of unsupervised patient stratification results, namely pattern screening, meta clustering, surrogate modeling, and curation. These tools can be used at different stages within the analysis. As compared to a standard analysis approach, we demonstrate the ability to condense results and optimize analysis time. In the case of meta clustering, we demonstrate that the number of patient clusters can be reduced from 72 to 3 in one example. In another stratification result, by using surrogate models, we could quickly identify that heart failure patients were stratified if blood sodium measurements were available. As this is a routine measurement performed for all patients with heart failure, this indicated a data bias. By using further cohort and feature curation, these patients and other irrelevant features could be removed to increase the clinical meaningfulness. These examples show the effectiveness of the proposed methods and we hope to encourage further research in this field.Comment: 27 pages, 14 figure