ImportanceIn patients with coronary artery disease, some guidelines recommend initial statin treatment with high-intensity statins to achieve at least a 50% reduction in low-density lipoprotein cholesterol (LDL-C). An alternative approach is to begin with moderate-intensity statins and titrate to a specific LDL-C goal. These alternatives have not been compared head-to-head in a clinical trial involving patients with known coronary artery disease.ObjectiveTo assess whether a treat-to-target strategy is noninferior to a strategy of high-intensity statins for long-term clinical outcomes in patients with coronary artery disease.Design, Setting, and ParticipantsA randomized, multicenter, noninferiority trial in patients with a coronary disease diagnosis treated at 12 centers in South Korea (enrollment: September 9, 2016, through November 27, 2019; final follow-up: October 26, 2022).InterventionsPatients were randomly assigned to receive either the LDL-C target strategy, with an LDL-C level between 50 and 70 mg/dL as the target, or high-intensity statin treatment, which consisted of rosuvastatin, 20 mg, or atorvastatin, 40 mg.Main Outcomes and MeasuresPrimary end point was a 3-year composite of death, myocardial infarction, stroke, or coronary revascularization with a noninferiority margin of 3.0 percentage points.ResultsAmong 4400 patients, 4341 patients (98.7%) completed the trial (mean [SD] age, 65.1 [9.9] years; 1228 females [27.9%]). In the treat-to-target group (n = 2200), which had 6449 person-years of follow-up, moderate-intensity and high-intensity dosing were used in 43% and 54%, respectively. The mean (SD) LDL-C level for 3 years was 69.1 (17.8) mg/dL in the treat-to-target group and 68.4 (20.1) mg/dL in the high-intensity statin group (n = 2200) (P = .21, compared with the treat-to-target group). The primary end point occurred in 177 patients (8.1%) in the treat-to-target group and 190 patients (8.7%) in the high-intensity statin group (absolute difference, –0.6 percentage points [upper boundary of the 1-sided 97.5% CI, 1.1 percentage points]; P < .001 for noninferiority).Conclusions and RelevanceAmong patients with coronary artery disease, a treat-to-target LDL-C strategy of 50 to 70 mg/dL as the goal was noninferior to a high-intensity statin therapy for the 3-year composite of death, myocardial infarction, stroke, or coronary revascularization. These findings provide additional evidence supporting the suitability of a treat-to-target strategy that may allow a tailored approach with consideration for individual variability in drug response to statin therapy.Trial RegistrationClinicalTrials.gov Identifier: NCT02579499

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In this paper, a characteristic load decomposition (CLD)-based day-ahead load forecasting scheme is proposed for a mixed-use complex. The aggregated load of the complex is composed of the mixtures of different electricity usage patterns, and short-term load forecasting can be implemented by summing disaggregated sub-load predictions. However, tracing all usage patterns of sub-loads for prediction may be infeasible because of limited resources for measurement and analysis. To prevent this infeasibility, the proposed scheme focuses on effective decomposition using the sub-loads of typical characteristic load profiles and their representative pilot signals. Separate forecasts are obtained for the decomposed characteristic sub-loads using a hybrid scheme, which combines day-type conditioned linear prediction with long short-term memory regressions. Complex campus load data are considered to evaluate the proposed CLD-based hybrid forecasting. The evaluation results show that the proposed scheme outperforms conventional hybrid or similar-day-based forecasting approaches. Even when sub-load measurements are available only for a limited period, the CLD scheme can be applied for the extended training data through virtual disaggregations. INDEX TERMS Day-ahead load forecasting, time series analysis, long short-term memory, hybrid forecasting model, characteristic load decomposition, hierarchical load forecasting.

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Paramagnetic colloidal particles move in the potential energy landscape of a magnetically modulated bubble lattice of a magnetic garnet film. The modulation causes the energy minima to alternate between positions above the centres of the bubbles and interstitial positions. The particles deterministically follow the time-dependent positions of the energy minima until the minima become unstable in one or several directions and allow the particles to hop to a new minimum. We control the time delay between instabilities of the minima in alternative directions by the angle of the external magnetic field with the crystallographic directions of the bubble lattice. When the time delay is large, the particles deterministically hop to the next minimum along the direction that becomes unstable first. When the time delay is short, diffusion of the particle in the marginal potential randomizes the choice of the hopping directions or the choice of the transport network. Gradual changes of the external field direction from 0 • to 30 • lead to a continuous crossover from a deterministic to a fully stochastic path of the colloids.

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