Innovations in suicide prevention research (INSPIRE): a protocol for a population-based case–control study

Background Suicide deaths have been increasing for the past 20 years in the USA resulting in 45 979 deaths in 2020, a 29% increase since 1999. Lack of data linkage between entities with potential to implement large suicide prevention initiatives (health insurers, health institutions and corrections) is a barrier to developing an integrated framework for suicide prevention. Objectives Data linkage between death records and several large administrative datasets to (1) estimate associations between risk factors and suicide outcomes, (2) develop predictive algorithms and (3) establish long-term data linkage workflow to ensure ongoing suicide surveillance. Methods We will combine six data sources from North Carolina, the 10th most populous state in the USA, from 2006 onward, including death certificate records, violent deaths reporting system, large private health insurance claims data, Medicaid claims data, University of North Carolina electronic health records and data on justice involved individuals released from incarceration. We will determine the incidence of death from suicide, suicide attempts and ideation in the four subpopulations to establish benchmarks. We will use a nested case–control design with incidence density-matched population-based controls to (1) identify short-term and long-term risk factors associated with suicide attempts and mortality and (2) develop machine learning-based predictive algorithms to identify individuals at risk of suicide deaths. Discussion We will address gaps from prior studies by establishing an in-depth linked suicide surveillance system integrating multiple large, comprehensive databases that permit establishment of benchmarks, identification of predictors, evaluation of prevention efforts and establishment of long-term surveillance workflow protocols

Conditioning of the graphite bumper limiter for enhanced confinement discharges in TFTR

A strong pumping effect has been observed with plasma operation on the toroidal graphite bumper limiter on TFTR. The pumping effect was induced by conditioning the limiter with a short series (10 to 20) of low density deuterium- or helium-initiated discharges. The density decay constant (tau/sub p/*) for gas-fueled ohmic discharges was reduced from tau/sub p/* > 10 s before conditioning to a minimum value of tau/sub p/* = 0.15 s after conditioning, corresponding to a reduction in the global recycling coefficient from approx.100% to less than 50%. Coincident with the low recycling conditions, low current neutral-beam-fueled discharges show global energy confinement times which are enhanced by a factor of two over results with an unconditioned limiter. Two models are proposed for the observed pumping effects: (1) a depletion model based on pumping of hydrogenic species in the near-surface region of the limiter after depletion of the normally saturated surface layer by (carbon and helium) ion-induced desorption; and (2) a codeposition model based on pumping of hydrogenic species in carbon films sputtered from the limiter by the conditioning process