Screening for Park Access during a Primary Care Social Determinants Screen.

While there is evidence that access to nature and parks benefits pediatric health, it is unclear how low-income families living in an urban center acknowledge or prioritize access to parks.MethodsWe conducted a study about access to parks by pediatric patients in a health system serving low-income families. Adult caregivers of pediatric patients completed a survey to identify and prioritize unmet social and economic needs, including access to parks. Univariate and multivariate analyses were conducted to explore associations between lack of access to parks and sociodemographic variables. We also explored the extent to which access to parks competed with other needs.ResultsThe survey was completed by 890 caregivers; 151 (17%) identified "access to green spaces/parks/playgrounds" as an unmet need, compared to 397 (45%) who endorsed "running out of food before you had money or food stamps to buy more". Being at or below the poverty line doubled the odds ( Odds ratio 1.96, 95% CI 1.16-3.31) of lacking access to a park (reference group: above the poverty line), and lacking a high school degree nearly doubled the odds. Thirty-three of the 151 (22%) caregivers who identified access to parks as an unmet need prioritized it as one of three top unmet needs. Families who faced competing needs of housing, food, and employment insecurity were less likely to prioritize park access (p < 0.001).ConclusionClinical interventions to increase park access would benefit from an understanding of the social and economic adversity faced by patients

Assembly flow simulation of a radar

A discrete event simulation model has been developed to predict the assembly flow time of a new radar product. The simulation was the key tool employed to identify flow constraints. The radar, production facility, and equipment complement were designed, arranged, and selected to provide the most manufacturable assembly possible. A goal was to reduce the assembly and testing cycle time from twenty-six weeks. A computer software simulation package (SLAM 2) was utilized as the foundation for simulating the assembly flow time. FORTRAN subroutines were incorporated into the software to deal with unique flow circumstances that were not accommodated by the software. Detailed information relating to the assembly operations was provided by a team selected from the engineering, manufacturing management, inspection, and production assembly staff. The simulation verified that it would be possible to achieve the cycle time goal of six weeks. Equipment and manpower constraints were identified during the simulation process and adjusted as required to achieve the flow with a given monthly production requirement. The simulation is being maintained as a planning tool to be used to identify constraints in the event that monthly output is increased. 'What-if' studies have been conducted to identify the cost of reducing constraints caused by increases in output requirement

Treatment of Scarlatina.

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Detectable HIV Viral Load in Kenya: Data from a Population-Based Survey.

IntroductionAt the individual level, there is clear evidence that Human Immunodeficiency Virus (HIV) transmission can be substantially reduced by lowering viral load. However there are few data describing population-level HIV viremia especially in high-burden settings with substantial under-diagnosis of HIV infection. The 2nd Kenya AIDS Indicator Survey (KAIS 2012) provided a unique opportunity to evaluate the impact of antiretroviral therapy (ART) coverage on viremia and to examine the risks for failure to suppress viral replication. We report population-level HIV viral load suppression using data from KAIS 2012.MethodsBetween October 2012 to February 2013, KAIS 2012 surveyed household members, administered questionnaires and drew serum samples to test for HIV and, for those found to be infected with HIV, plasma viral load (PVL) was measured. Our principal outcome was unsuppressed HIV viremia, defined as a PVL ≥ 550 copies/mL. The exposure variables included current treatment with ART, prior history of an HIV diagnosis, and engagement in HIV care. All point estimates were adjusted to account for the KAIS 2012 cluster sampling design and survey non-response.ResultsOverall, 61·2% (95% CI: 56·4-66·1) of HIV-infected Kenyans aged 15-64 years had not achieved virological suppression. The base10 median (interquartile range [IQR]) and mean (95% CI) VL was 4,633 copies/mL (0-51,596) and 81,750 copies/mL (59,366-104,134), respectively. Among 266 persons taking ART, 26.1% (95% CI: 20.0-32.1) had detectable viremia. Non-ART use, younger age, and lack of awareness of HIV status were independently associated with significantly higher odds of detectable viral load. In multivariate analysis for the sub-sample of patients on ART, detectable viremia was independently associated with younger age and sub-optimal adherence to ART.DiscussionThis report adds to the limited data of nationally-representative surveys to report population- level virological suppression. We established heterogeneity across the ten administrative and HIV programmatic regions on levels of detectable viral load. Timely initiation of ART and retention in care are crucial for the elimination of transmission of HIV through sex, needle and syringe use or from mother to child. Further refinement of geospatial mapping of populations with highest risk of transmission is necessary

Amylose in Neurospora.

Amylose in Neurospora

UAV Model-based Flight Control with Artificial Neural Networks: A Survey

Model-Based Control (MBC) techniques have dominated flight controller designs for Unmanned Aerial Vehicles (UAVs). Despite their success, MBC-based designs rely heavily on the accuracy of the mathematical model of the real plant and they suffer from the explosion of complexity problem. These two challenges may be mitigated by Artificial Neural Networks (ANNs) that have been widely studied due to their unique features and advantages in system identification and controller design. Viewed from this perspective, this survey provides a comprehensive literature review on combined MBC-ANN techniques that are suitable for UAV flight control, i.e., low-level control. The objective is to pave the way and establish a foundation for efficient controller designs with performance guarantees. A reference template is used throughout the survey as a common basis for comparative studies to fairly determine capabilities and limitations of existing research. The end-result offers supported information for advantages, disadvantages and applicability of a family of relevant controllers to UAV prototypes

Development of the legitimacy threshold scale

A consensus in the literature supports the premise that legitimacy attainment facilitates favorable judgments from key stakeholders regarding the acceptability, appropriateness and worthiness of entrepreneurs and their efforts in emerging ventures. However, although legitimacy attainment is a milestone that emerging ventures strive to reach, as researchers we do not yet have a measure that examines whether a firm is operating pre- versus post-legitimacy. Accordingly, we develop the legitimacy threshold scale (LTS) that will facilitate the assessment of activities performed pre- and post-legitimacy in emerging ventures

Observing the spin of a free electron

Long ago, Bohr, Pauli, and Mott argued that it is not, in principle, possible to measure the spin components of a free electron. One can try to use a Stern-Gerlach type of device, but the finite size of the beam results in an uncertainty of the splitting force that is comparable with the gradient force. The result is that no definite spin measurement can be made. Recently there has been a revival of interest in this problem, and we will present our own analysis and quantum-mechanical wave-packet calculations which suggest that a spin measurement is possible for a careful choice of initial conditions

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges