Change in incidents of suicidal acts after intervention on a bridge in South Korea.

PURPOSE: To investigate whether two novel interventions on a bridge - a Video Incident Detection System (VIDS) and spinning bar barriers - have an impact on suicidal behaviour on the bridge. METHODS: A total of 146 suicidal acts were retrieved for analyses; 108 interventions before suicidal acts, 35 suicide deaths and 3 suicide attempts. Incident rate ratios (IRR) were calculated to estimate the change in incident rate associated with implementation of the two interventions: VIDS and the spinning bar 2-metre high barrier. RESULTS: The results of the Poisson regression showed that the rate of suicide deaths, after installation the VIDS, did not change significantly (IRR: 1.23, 95% Confidence Interval [95% CI]: 0.59-2.56), although the rate of intervened suicidal acts increased (IRR: 2.40, 95% CI: 1.65-3.47). The results showed that subsequent spinning bar installation resulted in a decrease in the incident rate of intervened suicidal acts (IRR: 0.37, 95% CI: 0.25-0.57) as well as suicide deaths (IRR: 0.23, 95% CI: 0.07-0.71). Comparison of the period when both interventions were in place with the period with no interventions indicated a reduction in suicide deaths (IRR: 0.28, 95% CI: 0.10-0.82), but no change in intervened suicidal acts (IRR: 0.90, 95% CI: 0.59-1.38). CONCLUSION: The rate of suicide death decreased after the installation of the spinning bar barrier but not after the implementation of VIDS alone. Our findings reinforce that restricting access to means is a highly effective way of preventing suicide on bridges and that spinning bars may be a helpful way to design barriers.

High-Risk Suicide Locations in Australia.

Importance: Although several interventions have been shown to be effective in preventing suicide at high-risk locations, the potential for these interventions to be deployed is limited by a lack of knowledge about where high-risk locations are and the factors associated with choosing these locations. Objective: To identify high-risk suicide locations in Australia and the factors associated with choosing these locations. Design, Setting, and Participants: This case-control study included data on individuals who died by suicide in Australia between January 2001 and December 2017, obtained from the National Coronial Information System. Data analysis was conducted from February to December 2021. Exposures: Sociodemographic, residential, incident time, and incident location variables. Main Outcomes and Measures: The scan statistic was used to detect spatial clusters of suicides in public locations. Suicide locations within significant clusters with at least 0.5 suicides per year were defined as high-risk locations. Multivariable logistic regression analyses were performed to examine the factors associated with choosing a high-risk location. Results: Over the study period, 10 701 suicides took place in public places. The individuals who died of suicide in public places included 8602 (80.4%) male individuals, and most were aged 25 to 49 years (5825 [54.5%]). A total of 17 high-risk suicide locations in Australia were detected. These involved 495 suicides, which accounted for 4.6% of suicides in public locations. For suicides at high-risk locations, 82.2% (407 of 495) occurred at cliffs and bridges. Being female (adjusted odds ratio [aOR], 1.73; 95% CI, 1.41-2.13), employed (aOR, 1.57; 95% CI, 1.20-2.04), never married (aOR, 1.64; 95% CI, 1.26-2.13), and from a major city (aOR, 3.94; 95% CI, 2.94-5.28) were associated with the choice of a high- over low-risk suicide location. High-risk locations tended to be in major cities. Conclusions and Relevance: This case-control study found 17 high-risk suicide locations in Australia and the factors associated with the choice of these locations. Actions should be taken to prevent suicide at these locations where possible.

Biomedical Applications of CNT-Based Fibers.

Carbon nanotubes (CNTs) have been regarded as emerging materials in various applications. However, the range of biomedical applications is limited due to the aggregation and potential toxicity of powder-type CNTs. To overcome these issues, techniques to assemble them into various macroscopic structures, such as one-dimensional fibers, two-dimensional films, and three-dimensional aerogels, have been developed. Among them, carbon nanotube fiber (CNTF) is a one-dimensional aggregate of CNTs, which can be used to solve the potential toxicity problem of individual CNTs. Furthermore, since it has unique properties due to the one-dimensional nature of CNTs, CNTF has beneficial potential for biomedical applications. This review summarizes the biomedical applications using CNTF, such as the detection of biomolecules or signals for biosensors, strain sensors for wearable healthcare devices, and tissue engineering for regenerating human tissues. In addition, by considering the challenges and perspectives of CNTF for biomedical applications, the feasibility of CNTF in biomedical applications is discussed.

Bayesian Optimization of Wet-Impregnated Co-Mo/Al2O3 Catalyst for Maximizing the Yield of Carbon Nanotube Synthesis.

Multimetallic catalysts have demonstrated their high potential for the controlled synthesis of carbon nanotubes (CNTs), but their development requires a more complicated optimization than that of monometallic catalysts. Here, we employed Bayesian optimization (BO) to optimize the preparation of Co-Mo/Al2O3 catalyst using wet impregnation, with the goal of maximizing carbon yield in the chemical vapor deposition (CVD) synthesis of CNTs. In the catalyst preparation process, we selected four parameters to optimize: the weight percentage of metal, the ratio of Co to Mo in the catalyst, the drying temperature, and the calcination temperature. We ran two parallel BO processes to compare the performance of two types of acquisitions: expected improvement (EI), which does not consider noise, and one-shot knowledge gradient (OKG), which takes noise into account. As a result, both acquisition functions successfully optimized the carbon yield with similar performance. The result suggests that the use of EI, which has a lower computational load, is acceptable if the system has sufficient robustness. The investigation of the contour plots showed that the addition of Mo has a negative effect on carbon yield.