Liquid propellant rocket engine combustion simulation with a time-accurate CFD method

Time-accurate computational fluid dynamics (CFD) algorithms are among the basic requirements as an engineering or research tool for realistic simulations of transient combustion phenomena, such as combustion instability, transient start-up, etc., inside the rocket engine combustion chamber. A time-accurate pressure based method is employed in the FDNS code for combustion model development. This is in connection with other program development activities such as spray combustion model development and efficient finite-rate chemistry solution method implementation. In the present study, a second-order time-accurate time-marching scheme is employed. For better spatial resolutions near discontinuities (e.g., shocks, contact discontinuities), a 3rd-order accurate TVD scheme for modeling the convection terms is implemented in the FDNS code. Necessary modification to the predictor/multi-corrector solution algorithm in order to maintain time-accurate wave propagation is also investigated. Benchmark 1-D and multidimensional test cases, which include the classical shock tube wave propagation problems, resonant pipe test case, unsteady flow development of a blast tube test case, and H2/O2 rocket engine chamber combustion start-up transient simulation, etc., are investigated to validate and demonstrate the accuracy and robustness of the present numerical scheme and solution algorithm

An evaluation of Thiomicrospira, Hydrogenovibrio and Thioalkalimicrobium: reclassification of 4 species of Thiomicrospira to each Thiomicrorhabdus gen. nov. and Hydrogenovibrio, and reclassification of all 4 species of Thioalkalimicrobium to Thiomicrospira.

Thiomicrospira spp. are small sulfur-oxidising chemolithoautotrophic members of the Gammaproteobacteria. Whilst the type species Tms. pelophila and closely related Tms. thyasirae exhibit canonical spiral morphology under sub-optimal growth conditions, most species are vibrios or rods. The 16S rRNA gene diversity is vast, with identities as low as 91.6 % to Tms. pelophila versus Tms. frisia, for example. Thiomicrospira was examined with closely related genera Hydrogenovibrio and Thioalkalimicrobium and, to rationalise organisms on the basis of the 16S rRNA gene phylogeny, physiology and morphology, we reclassify Tms. kuenenii, Tms. crunogena, Tms. thermophila and Tms. halophila to Hydrogenovibrio kuenenii comb. nov., H. crunogenus corrig. comb. nov., H. thermophilus corrig. comb. nov., and H. halophilus corrig. comb. nov. We reclassify Tms. frisia, Tms. arctica, Tms. psychrophila and Tms. chilensis to Thiomicrorhabdus gen. nov., as Tmr. frisia comb. nov., Tmr. arctica comb. nov., Tmr. psychrophila comb. nov. and Tmr. chilensis comb. nov. – the type species of Thiomicrorhabdus is Tmr. frisia. We demonstrate Thioalkalimicrobium spp. fall in the genus Thiomicrospira sensu stricto, thus reclassifying them to Tms. aerophila corrig. comb. nov., Tms. microaerophila corrig. comb. nov., Tms. cyclica corrig. comb. nov.and Tms. sibirica corrig. comb. nov. We provide emended descriptions of the genera Thiomicrospira and Hydrogenovibrio and of Tms. thyasirae

BMQ

BMQ: Boston Medical Quarterly was published from 1950-1966 by the Boston University School of Medicine and the Massachusetts Memorial Hospitals

Deaths in people from Black, Asian and minority ethnic communities from both COVID-19 and non-COVID causes in the first weeks of the pandemic in London: a hospital case note review

Objective To undertake a case review of deaths in a 6-week period during the COVID-19 pandemic commencing with the first death in the hospital from COVID-19 on 12th of March 2020 and contrast this with the same period in 2019. Setting A large London teaching hospital. Participants Three groups were compared: group 1—COVID-19-associated deaths in the 6-week period (n=243), group 2—non-COVID deaths in the same period (n=136) and group 3—all deaths in a comparison period of the same 6 weeks in 2019 (n=194). Primary and secondary outcome measures This was a descriptive analysis of death case series review and as such no primary or secondary outcomes were pre-stipulated. Results Deaths in patients from the Black, Asian and minority ethnic (BAME) communities in the pandemic period significantly increased both in the COVID-19 group (OR=2.43, 95% CI=1.60–3.68, p<0.001) and the non-COVID group (OR=1.76, 95% CI=1.09–2.83, p=0.02) during this time period and the increase was independent of differences in comorbidities, sex, age or deprivation. While the absolute number of deaths increased in 2020 compared with 2019, across all three groups the distribution of deaths by age was very similar. Our analyses confirm major risk factors for COVID-19 mortality including male sex, diabetes, having multiple comorbidities and background from the BAME communities. Conclusions There was no evidence of COVID-19 deaths occurring disproportionately in the elderly compared with non-COVID deaths in this period in 2020 and 2019. Deaths in the BAME communities were over-represented in both COVID-19 and non-COVID groups, highlighting the need for detailed research in order to fully understand the influence of ethnicity on susceptibility to illness, mortality and health-seeking behaviour during the pandemic

Shaping Intrinsic Neural Oscillations with Periodic Stimulation.

Rhythmic brain activity plays an important role in neural processing and behavior. Features of these oscillations, including amplitude, phase, and spectrum, can be influenced by internal states (e.g., shifts in arousal, attention or cognitive ability) or external stimulation. Electromagnetic stimulation techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, and transcranial alternating current stimulation are used increasingly in both research and clinical settings. Currently, the mechanisms whereby time-dependent external stimuli influence population-scale oscillations remain poorly understood. Here, we provide computational insights regarding the mapping between periodic pulsatile stimulation parameters such as amplitude and frequency and the response dynamics of recurrent, nonlinear spiking neural networks. Using a cortical model built of excitatory and inhibitory neurons, we explored a wide range of stimulation intensities and frequencies systematically. Our results suggest that rhythmic stimulation can form the basis of a control paradigm in which one can manipulate the intrinsic oscillatory properties of driven networks via a plurality of input-driven mechanisms. Our results show that, in addition to resonance and entrainment, nonlinear acceleration is involved in shaping the rhythmic response of our modeled network. Such nonlinear acceleration of spontaneous and synchronous oscillatory activity in a neural network occurs in regimes of intense, high-frequency rhythmic stimulation. These results open new perspectives on the manipulation of synchronous neural activity for basic and clinical research. Oscillatory activity is widely recognized as a core mechanism for information transmission within and between brain circuits. Noninvasive stimulation methods can shape this activity, something that is increasingly capitalized upon in basic research and clinical practice. Here, we provide computational insights on the mechanistic bases for such effects. Our results show that rhythmic stimulation forms the basis of a control paradigm in which one can manipulate the intrinsic oscillatory properties of driven networks via a plurality of input-driven mechanisms. In addition to resonance and entrainment, nonlinear acceleration is involved in shaping the rhythmic response of our modeled network, particularly in regimes of high-frequency rhythmic stimulation. These results open new perspectives on the manipulation of synchronous neural activity for basic and clinical research

Solidification behavior of intensively sheared hypoeutectic Al-Si alloy liquid

The official published version of this article can be found at the link below.The effect of the processing temperature on the microstructural and mechanical properties of Al-Si (hypoeutectic) alloy solidified from intensively sheared liquid metal has been investigated systematically. Intensive shearing gives a significant refinement in grain size and intermetallic particle size. It also is observed that the morphology of intermetallics, defect bands, and microscopic defects in high-pressure die cast components are affected by intensive shearing the liquid metal. We attempt to discuss the possible mechanism for these effects.Funded by the EPSRC

The roles of specialist provision for children with specific speech and language difficulties in England and Wales: a model for inclusion?

Children with specific speech and language difficulties pose a challenge to the education and health systems. In addition to their language difficulties they are also at risk of literacy and social, emotional and behavioural difficulties. The main support for children with more severe difficulties has been enhanced provision in mainstream schools (language units or integrated resources) and special schools. The move to an inclusive education system challenges this tradition. The present paper reports the results of interviews with heads of language units/integrated resources and headteachers of special schools (n=57) as part of a larger study within England and Wales. Their views are considered with reference to criteria for entry to specialist provision, the development of collaborative practice between teachers, teaching assistants and speech and language therapists, and the implications for inclusive education

Statistical Meta-Analysis of Risk Factors for Endometrial Can cer and Development of a Risk Prediction Model Using an Artificial Neural Network Algorithm

Objectives: In this study we wished to determine the rank order of risk factors for endometrial cancer and calculate a pooled risk and percentage risk for each factor using a statistical meta-analysis approach. The next step was to design a neural network computer model to predict the overall increase or decreased risk of cancer for individual patients. This would help to determine whether this prediction could be used as a tool to decide if a patient should be considered for testing and to predict diagnosis, as well as to suggest prevention measures to patients. Design: A meta-analysis of existing data was carried out to calculate relative risk, followed by design and implementation of a risk prediction computational model based on a neural network algorithm. Setting: Meta-analysis data were collated from various settings from around the world. Primary data to test the model were collected from a hospital clinic setting. Participants: Data from 40 patients notes currently suspected of having endometrial cancer and undergoing investigations and treatment were collected to test the software with their cancer diagnosis not revealed to the software developers. Main outcome measures: The forest plots allowed an overall relative risk and percentage risk to be calculated from all the risk data gathered from the studies. A neural network computational model to determine percentage risk for individual patients was developed, implemented, and evaluated. Results: The results show that the greatest percentage increased risk was due to BMI being above 25, with the risk increasing as BMI increases. A BMI of 25 or over gave an increased risk of 2.01%, a BMI of 30 or over gave an increase of 5.24%, and a BMI of 40 or over led to an increase of 6.9%. PCOS was the second highest increased risk at 4.2%. Diabetes, which is incidentally also linked to an increased BMI, gave a significant increased risk along with null parity and noncontinuous HRT of 1.54%, 1.2%, and 0.56% respectively. Decreased risk due to contraception was greatest with IUD (intrauterine device) and IUPD (intrauterine progesterone device) at −1.34% compared to −0.9% with oral. Continuous HRT at −0.75% and parity at −0.9% also decreased the risk. Using open-source patient data to test our computational model to determine risk, our results showed that the model is 98.6% accurate with an algorithm sensitivity 75% on average. Conclusions: In this study, we successfully determined the rank order of risk factors for endometrial cancer and calculated a pooled risk and risk percentage for each factor using a statistical meta-analysis approach. Then, using a computer neural network model system, we were able to model the overall increase or decreased risk of cancer and predict the cancer diagnosis for particular patients to an accuracy of over 98%. The neural network model developed in this study was shown to be a potentially useful tool in determining the percentage risk and predicting the possibility of a given patient developing endometrial cancer. As such, it could be a useful tool for clinicians to use in conjunction with other biomarkers in determining which patients warrant further preventative interventions to avert progressing to endometrial cancer. This result would allow for a reduction in the number of unnecessary invasive tests on patients. The model may also be used to suggest interventions to decrease the risk for a particular patient. The sensitivity of the model limits it at this stage due to the small percentage of positive cases in the datasets; however, since this model utilizes a neural network machine learning algorithm, it can be further improved by providing the system with more and larger datasets to allow further refinement of the neural network

Substantiating a political public sphere in the Scottish press : a comparative analysis

This article uses content analysis to characterize the performance of the media in a national public sphere, by setting apart those qualities that typify internal press coverage of a political event. The article looks at the coverage of the 1999 devolved Scottish election from the day before the election until the day after. It uses a word count to measure the election material in Scottish newspapers the Herald, the Press and Journal and the Scotsman, and United Kingdom newspapers the Guardian, the Independent and The Times, and categorizes that material according to discourse type, day and page selection. The article finds a number of qualities that typify the Scottish sample in particular, and might be broadly indicative of a political public sphere in action. Firstly, and not unexpectedly, it finds that the Scottish newspapers carry significantly more election coverage. Just as tellingly, though, the article finds that the Scottish papers offer a greater proportion of advice and background information, in the form of opinion columns and feature articles. It also finds that the Scottish papers place a greater concentration of both informative and evaluative material in the period before the vote, consistent with their making a contribution to informed political action. Lastly, the article finds that the Scottish sample situates coverage nearer the front of the paper and places a greater proportion on recto pages. The article therefore argues that the Scottish papers display features that distinguish them from the UK papers, and are broadly consistent with their forming part of a deliberative public sphere, and suggests that these qualities might be explored as a means of judging future media performance