Measurement and Prediction of Pressure Drop in Pneumatic Conveying: Effect of Particle Characteristics, Mass Loading, and Reynolds Number

This paper reports the effect of Reynolds number, mass loading, and particle shape and size on pressure drop in a vertical gas-solids pneumatic conveying line. We isolate the effect of one variable while holding all others constant. A commonly used pressure drop correlation and a state-of-the-art multiphase computational fluid dynamics (CFD) models are then assessed by comparing their predictions to experimental data. Deficiencies in the models and the correlation are identified, and possible modifications are proposed. The most notable deficiency is the inability of both the experimental correlation and the CFD model to accurately predict the pressure drop for gas-solids flow with highly aspherical particles

Breakage Modeling of Needle-Shaped Particles Using The Discrete Element Method

This paper models the breakage of large aspect ratio particles in an attrition cell using discrete element method (DEM) and population balance (PB) models. The particles are modeled in DEM as sphero-cylinders. The stresses within each particle are calculated along the particle length using beam theory and the particle breaks into two parts if the stress exceeds a critical value. Thus, the size distribution changes with time within the DEM model. The DEM model is validated against previously published experimental data. The simulations demonstrate that particle breakage occurs primarily in front of the attrition cell blades, with the breakage rate decreasing as the particle sizes decrease. Increasing the particle elastic modulus, decreasing the particle yield strength, and increasing the attrition cell lid stress also increase the rate of breakage. Particles break most frequently at their center and the daughter size distribution normalized by the initial particle size is fit well with a Gaussian distribution. Parametric studies in which the initial particle size distribution varies demonstrate that the particle sizes approach a distribution that is independent of the initial state after a sufficient amount of work is done on the particle bed. A correlation for the specific breakage rate is developed from the DEM simulations and used within a PB model along with the daughter size distribution fit. The PB model also clearly shows that the particle size distribution becomes independent of the initial size distribution and after a sufficiently long time, is fit well with a log-normal distribution

Discrete Element Method Model of Elastic Fiber Uniaxial Compression

A flexible fiber model based on the discrete element method (DEM) is presented and validated for the simulation of uniaxial compression of flexible fibers in a cylindrical container. It is found that the contact force models in the DEM simulations have a significant impact on compressive forces exerted on the fiber bed. Only when the geometry-dependent normal contact force model and the static friction model are employed, the simulation results are in good agreement with experimental results. Systematic simulation studies show that the compressive force initially increases and eventually saturates with an increase in the fiber-fiber friction coefficient, and the fiber-fiber contact forces follow a similar trend. The compressive force and lateral shear-to-normal stress ratio increase linearly with increasing fiber-wall friction coefficient. In uniaxial compression of frictional fibers, more static friction contacts occur than dynamic friction contacts with static friction becoming more predominant as the fiber-fiber friction coefficient increases.Comment: 30 pages, 14 figures, submitted for publicatio

Contraceptive practices, preferences and barriers among abortion clients in North Carolina.

Objectives: Abortion clinics provide an ideal setting for women to receive contraceptive care because the women served may not have other contacts with the health system and are at risk for unintended pregnancies. The objective of this study was to understand practices, preferences, and barriers to use of contraception for women obtaining abortions at clinics in North Carolina. Methods: We conducted a cross-sectional survey of abortion clients and facilities at 10 abortion clinics in North Carolina. We collected data on contraceptive availability at each clinic. We collected individual responses on women’s experiences obtaining contraception before the current pregnancy and their intentions for future use of contraception. Results: From October 2015 to February 2016, 376 client surveys were completed at 9 clinics, and 10 clinic surveys were completed. Almost one-third of women (29%) reported that they had wanted to use contraception in the last year but were unable. Approximately three-fourths of respondents (76%) stated that they intend to use contraception after this pregnancy. Approximately one-fifth of women stated that would like to use long-acting reversible contraception (LARC) after this abortion. Only the clinics that accepted insurance for abortion and other services provided LARC at the time of the abortion (40%). Conclusions: This study provides a unique, statewide view into the contraceptive barriers for women seeking abortion in North Carolina. Addressing the relatively high demand for LARC after abortion could help significantly reduce unintended pregnancy and recourse to abortion in North Carolina

Trends in Abortion Incidence and Service Availability in North Carolina, 1980-2013

Objectives: Abortion incidence has declined nationally during the last decade. In recent years, many states, including North Carolina, have passed legislation related to the provision of abortion services. Despite the changing political environment, there is no comprehensive analysis on past and current trends related to unintended pregnancy and abortion in North Carolina. Methods: This study is a secondary analysis of vital registration data made publicly available by the North Carolina State Center for Health Statistics. Birth and induced abortion records were obtained for the years 1980 to 2013. We describe abortion incidence and demographic characteristics of women obtaining abortions over time. Results: The number of North Carolina abortions declined 36% between 1980 and 2013. The abortion ratio declined from 26/100 pregnancies (live births and abortions) in 1980 to just 14/100 in 2013. These ratios, however, vary across demographic subgroups. In 2013, the abortion ratio was more than 2 times greater for non-Hispanic black women than non-Hispanic white women (22 and 9, respectively). Among non-Hispanic black and Hispanic women, the abortion ratio is greater among women with a previous pregnancy as compared with women in their first pregnancy. For non-Hispanic white women, the abortion ratios are similar for first and higher-order pregnancies. Conclusions: Trends in North Carolina are similar to national trends; however, detailed analyses by race/ethnicity, age, and parity demonstrate important distinctions among abortion patients over time in the state. We discuss these trends in relation to policy changes and increased access to effective contraceptive

Rapid translation of clinical guidelines into executable knowledge : a case study of COVID-19 and online demonstration

Introduction: We report a pathfinder study of AI/knowledge engineering methods to rapidly formalise COVID‐19 guidelines into an executable model of decision making and care pathways. The knowledge source for the study was material published by BMJ Best Practice in March 2020. Methods: The PROforma guideline modelling language and OpenClinical.net authoring and publishing platform were used to create a data model for care of COVID‐19 patients together with executable models of rules, decisions and plans that interpret patient data and give personalised care advice. Results: PROforma and OpenClinical.net proved to be an effective combination for rapidly creating the COVID‐19 model; the Pathfinder 1 demonstrator is available for assessment at https://www.openclinical.net/index.php?id=746. Conclusions: This is believed to be the first use of AI/knowledge engineering methods for disseminating best‐practice in COVID‐19 care. It demonstrates a novel and promising approach to the rapid translation of clinical guidelines into point of care services, and a foundation for rapid learning systems in many areas of healthcare

Factors Associated With the Frequency of Monitoring of Liver Enzymes, Renal Function and Lipid Laboratory Markers Among Individuals Initiating Combination Antiretroviral Therapy: A Cohort Study

Background As the average age of the HIV-positive population increases, there is increasing need to monitor patients for the development of comorbidities as well as for drug toxicities. Methods We examined factors associated with the frequency of measurement of liver enzymes, renal function tests, and lipid levels among participants of the Canadian Observational Cohort (CANOC) collaboration which follows people who initiated HIV antiretroviral therapy in 2000 or later. We used zero-inflated negative binomial regression models to examine the associations of demographic and clinical characteristics with the rates of measurement during follow-up. Generalized estimating equations with a logit link were used to examine factors associated with gaps of 12 months or more between measurements. Results Electronic laboratory data were available for 3940 of 7718 CANOC participants. The median duration of electronic follow-up was 3.5 years. The median (interquartile) rates of tests per year were 2.76 (1.60, 3.73), 2.55 (1.44, 3.38) and 1.42 (0.50, 2.52) for liver, renal and lipid parameters, respectively. In multivariable zero-inflated negative binomial regression models, individuals infected through injection drug use (IDU) were significantly less likely to have any measurements. Among participants with at least one measurement, rates of measurement of liver, renal and lipid tests were significantly lower for younger individuals and Aboriginal Peoples. Hepatitis C co-infected individuals with a history of IDU had lower rates of measurement and were at greater risk of having 12 month gaps between measurements. Conclusions Hepatitis C co-infected participants infected through IDU were at increased risk of gaps in testing, despite publicly funded health care and increased risk of comorbid conditions. This should be taken into consideration in analyses examining factors associated with outcomes based on laboratory parameters

Gut-resident microorganisms and their genes are associated with cognition and neuroanatomy in children

Emerging evidence implicates gut microbial metabolism in neurodevelopmental disorders, but its influence on typical neurodevelopment has not been explored in detail. We investigated the relationship between the microbiome and neuroanatomy and cognition of 381 healthy children, demonstrating that differences in microbial taxa and genes are associated with overall cognitive function and the size of brain regions. Using a combination of statistical and machine learning models, we showed that species including Alistipes obesi, Blautia wexlerae, and Ruminococcus gnavus were enriched or depleted in children with higher cognitive function scores. Microbial metabolism of short-chain fatty acids was also associated with cognitive function. In addition, machine models were able to predict the volume of brain regions from microbial profiles, and taxa that were important in predicting cognitive function were also important for predicting individual brain regions and specific subscales of cognitive function. These findings provide potential biomarkers of neurocognitive development and may enable development of targets for early detection and intervention.publishedVersio