Delayed presentation of a traumatic scalp arteriovenous fistula

Background: Arteriovenous (AV) fistulas of the scalp are extracranial vascular malformations commonly caused by trauma and typically present within 3 years. Although they follow a benign course, they can be esthetically displeasing. Case description: We present an atypical onset of scalp AV fistula in a patient with a 1-year history of the left-sided pulsatile tinnitus and scalp swelling 7 years after a traumatic epidural hematoma evacuation. Our patient was found to have an 8 mm AV fistula supplied by the deep temporal artery. Endovascular embolization was performed using eight coils. There was no complication from the procedure, and the patient's pulsatile tinnitus and swelling resolved immediately after embolization. Follow-up angiogram demonstrated complete obliteration of the AV fistula. Conclusion: Delayed presentation of traumatic scalp AV fistula is very rare, and it is important to keep this in the differential in patients with scalp swelling after head trauma

Probabilistic seismic risk assessment using CRISIS2015 & USERISK2015. Application to buildings of Barcelona, Spain.

The probabilistic models to assess seismic hazard and seismic risk incorporated into the codes CRISIS2015 & USERISK2015, respectively, are applied to compute the seismic risk of buildings of Barcelona. The main procedures required to assess the seismic risk using these codes are briefly described in the present document. A new version of USERISK, which is being developed in the Barcelona Supercomputing Center was used in the present work. According to the results, the levels of seismic risk of the Eixample District of Barcelona are important due mainly to the high levels of seismic vulnerability of its buildings

Thermodynamic formalism for contracting Lorenz flows

We study the expansion properties of the contracting Lorenz flow introduced by Rovella via thermodynamic formalism. Specifically, we prove the existence of an equilibrium state for the natural potential $\hat\phi_t(x,y, z):=-t\log J_{(x, y, z)}^{cu}$ for the contracting Lorenz flow and for $t$ in an interval containing $[0,1]$. We also analyse the Lyapunov spectrum of the flow in terms of the pressure

Transcriptome analyses throughout chili pepper fruit development reveal novel insights into the domestication process

Chili pepper (Capsicum spp.) is an important crop, as well as a model for fruit development studies and domestication. Here, we performed a time-course experiment to estimate standardized gene expression profiles with respect to fruit development for six domesticated and four wild chili pepper ancestors. We sampled the transcriptomes every 10 days from flowering to fruit maturity, and found that the mean standardized expression profiles for domesticated and wild accessions significantly differed. The mean standardized expression was higher and peaked earlier for domesticated vs. wild genotypes, particularly for genes involved in the cell cycle that ultimately control fruit size. We postulate that these gene expression changes are driven by selection pressures during domestication and show a robust network of cell cycle genes with a time shift in expression, which explains some of the differences between domesticated and wild phenotypes

Near-Field Pressure Signature Splicing for Low-Fidelity Design Space Exploration of Supersonic Aircraft

As interest in supersonic overland flight intensifies, new ways to meet government restrictions on sonic boom loudness must be implemented. Low-fidelity aerodynamic tools, such as PANAIR, can estimate the near-field pressure signature that ultimately determines the loudness of the sonic boom at the ground. These tools can greatly benefit the exploration of large design spaces due to their computational efficiency. One of the limitations of low-fidelity tools is the accuracy of the solution produced, which is dependent on the fundamental physical assumptions made in the development of the governing equations. If flow patterns are produced that severely violate these fundamental assumptions, the validity of the near-field pressure signature is compromised. A method is proposed that splices together near-field pressure signatures from a low-fidelity and a higher-fidelity tool by cutting each pressure signature at a critical point and then blending the low-fidelity signature into the higher-fidelity signature. By splicing the signatures together, sections of the low-fidelity signature that represent fundamental violations of the governing equation are removed. This method allows for the exploration of the design space corresponding to areas on the geometry that produce accurate results in a low-fidelity signature. The method is tested on the JAXA Wing Body geometry from the Second AIAA Sonic Boom Prediction Workshop and shows that perturbations to this geometry can produce loudness results that match the high-fidelity results to within 0.4 PLdB

NGC 1624-2: A slowly rotating, X-ray luminous Of?cp star with an extraordinarily strong magnetic field

This paper presents a first observational investigation of the faint Of?cp star NGC 1624-2, yielding important new constraints on its spectral and physical characteristics, rotation, magnetic field strength, X-ray emission and magnetospheric properties. Modeling the spectrum and spectral energy distribution, we conclude that NGC 1624-2 is a main sequence star of mass M {\simeq} 30 M{\odot}, and infer an effective temperature of 35 {\pm} 2 kK and log g = 4.0 {\pm} 0.2. Based on an extensive time series of optical spectral observations we report significant variability of a large number of spectral lines, and infer a unique period of 157.99 {\pm} 0.94 d which we interpret as the rotational period of the star. We report the detection of a very strong - 5.35 {\pm} 0.5 kG - longitudinal magnetic field , coupled with probable Zeeman splitting of Stokes I profiles of metal lines confirming a surface field modulus of 14 {\pm} 1 kG, consistent with a surface dipole of polar strength >~ 20 kG. This is the largest magnetic field ever detected in an O-type star, and the first report of Zeeman splitting of Stokes I profiles in such an object. We also report the detection of reversed Stokes V profiles associated with weak, high-excitation emission lines of O iii, which we propose may form in the close magnetosphere of the star. We analyze archival Chandra ACIS-I X-ray data, inferring a very hard spectrum with an X-ray efficiency log Lx/Lbol = -6.4, a factor of 4 larger than the canonical value for O-type stars and comparable to that of the young magnetic O-type star {\theta}1 Ori C and other Of?p stars. Finally, we examine the probable magnetospheric properties of the star, reporting in particular very strong magnetic confinement of the stellar wind, with {\eta}* {\simeq} 1.5 {\times} 10^4, and a very large Alfven radius, RAlf = 11.4 R*.Comment: 17 pages, MNRAS accepted and in pres

The effect of a one-year vigorous physical activity intervention on fitness, cognitive performance and mental health in young adolescents: the Fit to Study cluster randomised controlled trial.

BackgroundPhysical activity (PA) may positively stimulate the brain, cognition and mental health during adolescence, a period of dynamic neurobiological development. High-intensity interval training (HIIT) or vigorous PA interventions are time-efficient, scalable and can be easily implemented in existing school curricula, yet their effects on cognitive, academic and mental health outcomes are unclear. The primary aim of the Fit to Study trial was to investigate whether a pragmatic and scalable HIIT-style VPA intervention delivered during school physical education (PE) could improve attainment in maths. The primary outcome has previously been reported and was null. Here, we report the effect of the intervention on prespecified secondary outcomes, including cardiorespiratory fitness, cognitive performance, and mental health in young adolescents.MethodsThe Fit to Study cluster randomised controlled trial included Year 8 pupils (n = 18,261, aged 12-13) from 104 secondary state schools in South/Mid-England. Schools were randomised into an intervention condition (n = 52), in which PE teachers delivered an additional 10 min of VPA per PE lesson for one academic year (2017-2018), or into a "PE as usual" control condition. Secondary outcomes included assessments of cardiorespiratory fitness (20-m shuttle run), cognitive performance (executive functions, relational memory and processing speed) and mental health (Strength and Difficulties Questionnaire and self-esteem measures). The primary intention-to-treat (ITT) analysis used linear models and structural equation models with cluster-robust standard errors to test for intervention effects. A complier-average causal effect (CACE) was estimated using a two-stage least squares procedure.ResultsThe HIIT-style VPA intervention did not significantly improve cardiorespiratory fitness, cognitive performance (executive functions, relational memory or processed speed), or mental health (all p > 0.05). Subgroup analyses showed no significant moderation of intervention effects by sex, socioeconomic status or baseline fitness levels. Changes in cardiorespiratory fitness were not significantly related to changes in cognitive or mental health outcomes. The trial was marked by high drop-out and low intervention compliance. Findings from the CACE analysis were in line with those from the ITT analysis.ConclusionThe one-academic year HIIT-style VPA intervention delivered during regular school PE did not significantly improve fitness, cognitive performance or mental health, but these findings should be interpreted with caution given low implementation fidelity and high drop-out. Well-controlled, large-scale, school-based trials that examine the effectiveness of HIIT-style interventions to enhance cognitive and mental health outcomes are warranted.Trial registrationISRCTN registry, 15,730,512 . Trial protocol and analysis plan for primary outcome prospectively registered on 30th March 2017. ClinicalTrials.gov , NCT03286725 . Secondary measures (focus of current manuscript) retrospectively registered on 18 September 2017

Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study.

OBJECTIVE: To derive and validate a risk prediction algorithm to estimate hospital admission and mortality outcomes from coronavirus disease 2019 (covid-19) in adults. DESIGN: Population based cohort study. SETTING AND PARTICIPANTS: QResearch database, comprising 1205 general practices in England with linkage to covid-19 test results, Hospital Episode Statistics, and death registry data. 6.08 million adults aged 19-100 years were included in the derivation dataset and 2.17 million in the validation dataset. The derivation and first validation cohort period was 24 January 2020 to 30 April 2020. The second temporal validation cohort covered the period 1 May 2020 to 30 June 2020. MAIN OUTCOME MEASURES: The primary outcome was time to death from covid-19, defined as death due to confirmed or suspected covid-19 as per the death certification or death occurring in a person with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the period 24 January to 30 April 2020. The secondary outcome was time to hospital admission with confirmed SARS-CoV-2 infection. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance, including measures of discrimination and calibration, was evaluated in each validation time period. RESULTS: 4384 deaths from covid-19 occurred in the derivation cohort during follow-up and 1722 in the first validation cohort period and 621 in the second validation cohort period. The final risk algorithms included age, ethnicity, deprivation, body mass index, and a range of comorbidities. The algorithm had good calibration in the first validation cohort. For deaths from covid-19 in men, it explained 73.1% (95% confidence interval 71.9% to 74.3%) of the variation in time to death (R2); the D statistic was 3.37 (95% confidence interval 3.27 to 3.47), and Harrell's C was 0.928 (0.919 to 0.938). Similar results were obtained for women, for both outcomes, and in both time periods. In the top 5% of patients with the highest predicted risks of death, the sensitivity for identifying deaths within 97 days was 75.7%. People in the top 20% of predicted risk of death accounted for 94% of all deaths from covid-19. CONCLUSION: The QCOVID population based risk algorithm performed well, showing very high levels of discrimination for deaths and hospital admissions due to covid-19. The absolute risks presented, however, will change over time in line with the prevailing SARS-C0V-2 infection rate and the extent of social distancing measures in place, so they should be interpreted with caution. The model can be recalibrated for different time periods, however, and has the potential to be dynamically updated as the pandemic evolves