NON-DIMENSIONALISATION OF LATERAL DISTANCES BETWEEN VESSELS OF DISSIMILAR SIZES FOR INTERACTION EFFECT STUDIES

To date, most of the hydrodynamic interaction studies between a tug and a ship during ship assist manoeuvers have been carried out using model scale investigations. It is however difficult to establish how well results from these studies represent full scale interaction behaviour. This is further exacerbated by the lack of proven methodologies to non- dimensionalise the relative distances between the two vessels, enabling the comparison of model and full scale interaction effect data, as well as between vessels of dissimilar size ratios. This study investigates a suitable correlation technique to non-dimensionalise the lateral distance between vessels of dissimilar sizes, and a scaling option for interaction effect studies. It focuses on the interaction effects on a tug operating around the forward shoulder of a tanker at different lateral distances during ship assist operations. The findings and the non-dimensioning method presented in this paper enable the interaction effects determined for a given ship-to-tug ratio to be used to predict the safe operational distances for other ship-to-tug ratios.

Prediction and Selection of Appropriate Landscape Metrics and Optimal Scale Ranges Based on Multi-Scale Interaction Analysis

Landscape metrics are widely used in landscape planning and land use management. Understanding how landscape metrics respond with scales can provide more accurate prediction information; however, ignoring the interference of multi-scale interaction may lead to a severe systemic bias. In this study, we quantitatively analyzed the scaling sensitivity of metrics based on multi-scale interaction and predict their optimal scale ranges. Using a big data method, the multivariate adaptive regression splines model (MARS), and the partial dependence model (PHP), we studied the scaling relationships of metrics to changing scales. The results show that multi-scale interaction commonly exists in most landscape metric scaling responses, making a significant contribution. In general, the scaling effects of the three scales (i.e., spatial extent, spatial resolution, and classification of land use) are often in a different direction, and spatial resolution is the primary driving scale in isolation. The findings show that only a few metrics are highly sensitive to the three scales throughout the whole scale spectrum, while the other metrics are limited within a certain threshold range. This study confirms that the scaling-sensitive scalograms can be used as an application guideline for selecting appropriate landscape metrics and optimal scale ranges.

Connecting heavy precipitation events to outgoing longwave radiation variability scales: case analysis in Brazil

Spatial fields of outgoing longwave radiation (OLR) spectrum variance are analyzed in different time-scales: synoptic, sub-monthly, intra-seasonal, during the 1979-2016 austral summer months in southern Brazil. Variability fields differ both in intensity and location and highlight dominant convection cycles in the study area. The results show that the amplitude of sub-monthly variability is greater than the other scales in the southeastern region of Brazil, while the synoptic scale prevails in the southern region. The above-mentioned scales show higher amplitudes over the western Pacific Ocean where the Madden-Julian Oscillation plays an important role, along the South Pacific Convergence Zone, and over the storm track areas over the South Pacific Ocean. The influence of spectral OLR scale interaction is also analyzed, associated to the occurrence of two intense rainfall events over the southeastern Brazil in the austral summers of 2011 and 2014 when the South Atlantic Convergence Zone was involved in both events. The results obtained suggest that spectral OLR scale interaction takes place in such way that it strengthens the South Atlantic Convergence Zone, since the spatial pattern footprints of the 2 to 8-day timescale (synoptic), 10 to 30-day timescale (sub-monthly) and 30 to 60-day timescale (intra-seasonal) overlap in the study region.

Smoking may be more harmful to vasospastic angina patients who take antiplatelet agents due to the interaction: Results of Korean prospective multi-center cohort

Background The interaction between smoking and the use of antiplatelet agents on the prognosis of vasospastic angina (VA) is rarely investigated. Methods VA-Korea is a nation-wide multi-center registry with prospective design (n = 1812). The primary endpoint was the composite occurrence of acute coronary syndrome (ACS), symptomatic arrhythmia, and cardiac death. Log-rank test and Cox proportional hazard model were for statistical analysis. Also, we conducted interaction analysis in both additive and multiplicative scales between smoking and antiplatelet agents among VA patients. For additive scale interaction, relative excess risk due to interaction (RERI) was calculated and for multiplicative scale interaction, the ratio of hazard ratio (HR) was calculated. All statistical analysis conducted by Stata Ver 16.1. Results Patients who were smoking and using antiplatelet agents had the highest incidence rate in the primary composite outcome. The incidence rate was 3.49 per 1,000 person-month (95% CI: 2.30-5.30, log-rank test for primary outcome p = 0.017) and HR of smoking and using antiplatelet agents was 1.66 (95%CI: 0.98-2.81). The adjusted RERI of smoking and using antiplatelet agents was 1.10 (p = 0.009), and the adjusted ratio of HR of smoking and using antiplatelet agents was 3.32 (p = 0.019). The current study observed the interaction between smoking and using antiplatelet agents in both additive and multiplicative scales. Conclusions Smoking was associated with higher rates of unfavorable clinical outcomes among VA patients taking antiplatelet agents. This suggested that VA patients, especially those using antiplatelet agents should quit smoking.