Nadir Point Research Articles

Association of office blood pressure with ischemic and bleeding events in patients undergoing percutaneous coronary intervention

Optimal blood pressure (BP) for patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI) remains unclear. This study aims to identify the optimal BP by investigating the association between average office BP and future clinical events in patients undergoing PCI. Consecutive patients undergoing PCI from 2012 to 2016 were included. They were divided into five groups according to the average follow-up BP after discharge. The co-primary outcomes were net adverse clinical events (NACE) and major adverse cardiac and cerebrovascular events (MACCE) up to 5 years. NACE was defined as a composite of MACCE (all-cause death, non-fatal myocardial infarction (MI), non-fatal stroke, or any revascularization) or major bleeding. A total of 2845 patients were included, and among them, 787 (27.7%) experienced the NACE during the follow-up period. Patients in the highest SBP group (adjusted hazard ratio [HR] 1.495, confidence interval [CI] 1.189–1.880) and lowest SBP group (adjusted HR 1.625, CI 1.214–2.176) had a significantly higher risk of 5-year NACE. Similar associations were observed between SBP and the risk of MACCE, and similar results based on DBP categories were also observed. There was a J-curve relationship between SBP and DBP with respect to 5-year NACE and MACCE. The nadir point of risk for NACE and MACCE was found at 121.4/74.8 and 120.4/73.7 mmHg. In patients underwent PCI, there is a significant correlation between office BP level and clinical events, indicates the importance of efforts for optimal BP control to reduce ischemic and bleeding events.Trial registration: HanYang University Medical Center (HYUMC) Registry, NCT05935397.

Trochlear Dysplasia Is Associated With Increased Sagittal Tibial Tubercle Trochlear-Groove Distance in Patients With Patellar Instability

To compare the sagittal position of the tibial tubercle in relation the trochlea groove in patients with and without trochlear dysplasia (TD). Patients with high-grade TD show a significantly increased sagittal position of the tibial tubercle in relation to the trochlear groove (sTTTG) compared with patients without TD. This may affect patellofemoral loading and contribute to the increased prevalence of cartilage lesions seen in the patellofemoral joint of patients with dysplasia of the trochlear groove. All patients between January 2017 and December 2020 with high-grade TD (Dejour type B, C, and D) who underwent patellar-stabilizing surgery for patellar instability at a single institution were included in the current study. Patients without preoperative magnetic resonance imaging (MRI), any previous osteotomy on the affected lower extremity, or cruciate ligament insufficiency were excluded. Patients who underwent knee arthroscopy for meniscal repair/debridement without any signs of TD or any of the aforementioned criteria served as the control group. Preoperative MRI was retrospectively assessed to compare common patellofemoral anatomic parameters including patellar angle, patellar tilt, patella morphology according to Wiberg, Caton-Deschamps index, PF index, trochlear sulcus angle, sulcus depth, lateral inclination angle of the trochlea, tibiofemoral rotation, TTTG, and sTTTG distance between both groups. The sTTTG is measured as the distance between the nadir point of the cartilaginous trochlear groove and the most anterior point of the tibial tubercle on an axial MRI. Independent predictors for the sTTTG were assessed for patients with TD. Patients with high-grade TD (n= 82) showed an increased patellar tilt, Caton-Deschamps index, trochlear sulcus angle, lateral tibiofemoral rotation angle, TTTG, and sTTTG (9.16 ± 4.47 mm vs 2.66 ± 4.21 mm) compared with the control group (n=83) (P < .001). Patellar angle, PF index, sulcus depth, and lateral inclination angle of the trochlear were significantly decreased in the TD group (P < .001). The sTTTG was similar in all TD groups (n.s.). Among patients with TD, both tibiofemoral rotation and patellar height were independent predictors of the sTTTG (P < .05). Patients with high-grade TD show not only abnormal values in common patellofemoral instability risk factors but also a significantly increased sTTTG compared with patients without TD. Level III, retrospective case comparative study.

ASSOCIATION BETWEEN OFFICE BLOOD PRESSURE AND LONG-TERM CLINICAL EVENTS IN PATIENTS WITH CORONARY ARTERY DISEASE AFTER PERCUTANEOUS CORONARY INTERVENTION

Objective: The optimal blood pressure (BP) target for patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI) remains unclear. This study aimed to identify the optimal BP target by investigating the association between average office BP and future clinical events after PCI in patients with CAD. Design and method: Consecutive patients undergoing PCI from 2012 to 2016 were included. They were divided into five groups according to the average follow-up BP after discharge. The co-primary outcome was major adverse cardiac and cerebrovascular event (MACCE: all-cause death, non-fatal myocardial infarction, non-fatal stroke, or any revascularization) and net adverse clinical events (NACE: MACCE, or major bleeding) up to 5 years. Results: A total of 2,845 patients were included in the analyses, and among them, 787 (27.7%) experienced the NACE during the follow-up period. Patients in the highest SBP group (adjusted hazard ratio [HR] 1.495, confidence interval [CI] 1.189–1.880) and lowest SBP group (adjusted HR 1.625, CI 1.214–2.176) had a significantly higher risk of 5-year NACE. Similar associations were observed between SBP and the risk of MACCE, and similar results based on DBP categories were also observed. There was a J-curve relationship observed between SBP and DBP with respect to 5-year NACE and MACCE. The nadir point of risk for NACE and MACCE was found at 121.4/74.8 and 120.4/73.7 mmHg. Conclusions: In patients underwent PCI, there is a significant correlation between office BP level and clinical events, which indicates the importance of efforts for optimal BP control to reduce ischemic and bleeding events.

Investigating normalization in preference-based evolutionary multi-objective optimization using a reference point

Normalization of objectives plays a crucial role in evolutionary multi-objective optimization (EMO) to handle objective functions with different scales, which can be found in real-world problems. Although the effect of normalization methods on the performance of EMO algorithms has been investigated in the literature, that of preference-based EMO (PBEMO) algorithms is poorly understood. Since PBEMO aims to approximate a region of interest, its population generally does not cover the Pareto front in the objective space. This property may make normalization of objectives in PBEMO difficult. This paper investigates the effectiveness of three normalization methods in three representative PBEMO algorithms. We present a bounded archive-based method for approximating the nadir point. First, we demonstrate that the normalization methods in PBEMO perform significantly worse than that in conventional EMO in terms of approximating the ideal point, nadir point, and range of the PF. Then, we show that PBEMO requires normalization of objectives on problems with differently scaled objectives. Our results show that there is no clear “best normalization method” in PBEMO, but an external archive-based method performs relatively well.

Adaptive normal vector guided evolutionary multi- and many-objective optimization

Most existing multi-objective evolutionary algorithms relying on fixed reference vectors originating from an ideal or a nadir point may fail to perform well on multi- and many-objective optimization problems with various convexity or shapes of Pareto fronts. A possible reason could be the inaccurate measurement of the diversity of solutions or the failure of the fixed reference vectors in guiding the rapidly changing population. To meet this challenge, this work develops an adaptive normal reference vector-based decomposition strategy for guiding the search process, which is able to handle various convexity and shapes of Pareto fronts. Specifically, the normal vector passing through the center of each cluster in a constructed hyperplane is adopted as the reference vector for guiding the search process. Then, a selection strategy is put forward based on the positions of solutions in the current population and the normal vectors for the environmental selection. Based on the adaptive normal vectors, the proposed algorithm can not only rapidly adapt to the changing population but also alleviate the influence of the convexity of Pareto fronts on the measurement of diversity. Experimental results show that the proposed algorithm performs consistently well on various types of multi-/many-objective problems having regular or irregular Pareto fronts. In addition, the proposed algorithm is shown to perform well in the optimization of the polyester fiber esterification process.

Comparison Study of Earth Observation Characteristics between Moon-Based Platform and L1 Point of Earth-Moon System

The unceasing quest for a profound comprehension of the Earth system propels the continuous evolution of novel methods for Earth observation. Of these, the Lagrange points situated in the cislunar space proffer noteworthy prospects for space-based Earth observation. Although extant research predominantly centers on Moon-based Earth observation and the L1 point within the Sun-Earth system, the realm of cislunar space remains relatively unexplored. This paper scrutinizes the overarching characteristics of the L1 point within the Earth-Moon system concerning Earth observation. A pivotal enhancement is introduced through the incorporation of the halo orbit. This research comprehensively analyzes the relative motion between the halo orbiter and the Earth, achieved via orbit determination within a rotating coordinate system, followed by a transformation into the Earth coordinate system. Subsequently, numerical simulations employing ephemeris data unveil the observing geometry and Earth observation characteristics, encompassing the distribution of nadir points, viewing angles, and the spatiotemporal ground coverage. As a point of reference, we also present a case study involving a Moon-based platform. Our findings reveal that the motion of the halo orbit, perpendicular to the lunar orbital plane, results in a broader range of nadir point latitudes, which can extend beyond 42°N/S, contingent upon the orbit’s size. Additionally, it manifests a more intricate latitude variation, characterized by the bimodal peaks of the proposed temporal complexity curve. The viewing angles and the spatiotemporal ground coverage closely resemble those of Moon-based platforms, with a marginal enhancement in coverage frequency for polar regions. Consequently, it can be deduced that the Earth observation characteristics of the L1 point within the Earth-Moon system bear a close resemblance to those of Moon-based platforms. Nevertheless, considering the distinct advantages of Moon-based platforms, the lunar surface remains the paramount choice, boasting the highest potential for Earth observation within cislunar space. In summation, this study demonstrates the Earth observation characteristics of the L1 point within the Earth-Moon system, emphasizing the distinctions between this and Moon-based platforms.

The Optimal Transportation Option in an Underground Hard Coal Mine: A Multi-Criteria Cost Analysis

The issue of transport in underground hard coal mines is very rarely described in the literature. The financial aspects of this issue are even less often analyzed. Publications in this area focus on technical issues and the safety of mining crews. More attention is paid to transport in open-pit mines. The above premises and practical needs imply the need to conduct economic analyses of transport systems in underground hard coal mines. This paper is a scientific communication, which presents the concept of a multi-criteria cost analysis as a tool to support the selection of the optimal transportation option in an underground hard coal mine. Considerations in this area have not been carried out in the relevant literature, and the problem of selecting a transportation option is a complex and necessary issue in the practice of underground mines with extensive mine workings. The methodology presented includes five cost criteria (costs of carrying out the transportation task; route expansion costs; rolling stock maintenance costs; depreciation costs; and additional personnel costs). The simultaneous application of criteria relating to utility properties in addition to cost criteria makes it possible to adopt a specific technical and organizational model of the transportation system based on the indication of the optimal solution, resulting from the mathematical construction of functions of objectives relating to utility and cost. The optimal variant of the designed system and configuration of the material transportation system in underground workings takes into consideration the following: (1) seven utility criteria (KU1—transportation task completion time; KU2—compatibility of transportation systems; KU3—continuous connectivity; KU4—co-use with other transportation tasks; KU5—safety; KU6—inconvenience; KU7—operation under overplanning conditions) and (2) five cost criteria (KK1—costs of implementing the transportation task; KK2—costs of route expansion; KK3—rolling stock maintenance costs; KK4—depreciation costs; KK5—additional personnel costs). Based on the aforementioned criteria, two objective functions are built for each option: utility and cost. They present divergent goals; therefore, they are non-cooperative functions. Both utility and costs strive for the maximum. In the developed methodology, an ideal point is usually a fictitious solution representing a set of maximum values among all the achievable values in a set of solutions, but it is impossible to achieve this simultaneously based on all the criteria. This point illustrates the maximum utility and lowest cost among the alternatives considered, which is obviously impossible for any of the variants to meet at the same time, although it indicates the possibilities of the technique and the range of costs. For the developed method, a so-called “PND” nadir point is also determined, representing the least-preferred level of achievement of all goals simultaneously, determined from the set of optimal points in the Pareto sense. The originality of the conceptual considerations undertaken stems from: filling the gap in the economic methodology of complex transportation systems evaluation; embedding considerations in the trend concerning complex transportation systems of underground mines; and focusing considerations on the pre-investment phase, making it possible to optimize costs before expenditures are incurred.

Flavan-3-ol monomers intake is associated with osteoarthritis risk in Americans over 40 years of age: results from the National Health and Nutritional Examination Survey database.

Objectives: Osteoarthritis (OA) stands as the prevailing progressive musculoskeletal disease, serving as the primary cause of chronic pain and activity limitations among adults over 40. Flavan-3-ols, common polyphenolic compounds, are believed to harbor anti-inflammatory and anti-aging properties. This study explores the relationship between flavan-3-ol intake and osteoarthritis risk in individuals over the age of 40 in the US. Methods: This study included 7452 participants over the age of 40 from three cycles (2007-2008, 2009-2010, and 2017-2018) of the National Health and Nutrition Examination Survey. Information on OA history was obtained via home surveys. Information on flavan-3-ol monomers intake was obtained using a survey from the Food and Nutrient Database for Dietary Studies. We used a logistic regression model and restricted cubic spline to analyze the relationships between flavan-3-ol monomers and OA. Stratified analyses were also conducted in this study. Results: There were 1056 participants with OA and 6396 without OA. Compared to the first tertile (T1) group, the adjusted odds ratio with a 95% confidence interval (CI) of logistic regression model 2 for the flavan-3-ol T2 group was 1.296 (0.979-1.715) (p = 0.068), the OR for (-)-epigallocatechin was 1.292 (1.025-1.629) (p = 0.032), and the OR for (-)-epicatechin 3-gallate was 1.348 (1.013, 1.793) (p = 0.042). A dose-response curve indicated a non-linear association (p for non-linearity <0.05) between OA and total flavan-3-ol monomers (nadir point: 483.29 mg, 95% CI: 0.61-0.90). No interaction effects were found in the subgroup analysis. Conclusions: In individuals over 40 in the US, the average daily dietary intake of flavan-3-ol monomers manifests a J-shaped relationship with OA risk.

The impact of circular economy indicators in the optimal planning of energy systems

One of the purposes of the Circular Economy is to promote the optimization of resources; most power systems planning towards renewable energy focus on the operation phase. In this sense, innovative Circular Economy indicators play a fundamental role in planning electricity generation due to the massive electrification of economic activities, offering the option of using fewer material resources in the system infrastructure to reduce the depletion of non-renewable resources. Therefore, when planning a power supply system, it is essential to assess technical, environmental, and economic aspects to guarantee the system's proper functioning and an infrastructure design with the minimum impact. This work presents a mathematical programming approach that aims to introduce rigorous metrics on the requirements of non-renewable resources used during the process and energy self-sufficiency since they have not been studied as one of the aspects of the Circular Economy within the energy sector. In addition, the model determines the optimal selection of the required infrastructure and necessary capacities in energy production to satisfy the energy demand required in a specific period. Together, the quantification of materials is normalized using the Abiotic Depletion Potential as a comparison of the depletion of non-renewable resources. The proposed Mixed Integer Nonlinear Programming (MINLP) multi-objective model is solved using the goal programming technique, allowing to determine the compensations between the total cost, CO2eq emissions (related to the production of energy in the different energy generating technologies) and Circular Economy indicators. A case study for power generation in Mexico is presented and the results show that by implementing Circular Economy indicators as an addition to the economic and environmental functions, “achievement in performance” for the different objectives ranges from 84.00 % and 89.96 %. In addition, the optimization shows a 76.17 % decrease in the total cost and 48.73 % in CO2eq emissions concerning the respective worst case (Nadir point). This paper contributes to the growing body of literature on the integration of Circular Economy metrics, specifically in optimizing the energy sector.

Adapting Decomposed Directions for Evolutionary Multiobjective Optimization.

Decomposition methods have been widely employed in evolutionary algorithms for tackling multiobjective optimization problems (MOPs) due to their good mathematical explanation and promising performance. However, most decomposition methods only use a single ideal or nadir point to guide the evolution, which are not so effective for solving MOPs with extremely convex/concave Pareto fronts (PFs). To solve this problem, this article proposes an effective method to adapt decomposed directions (ADDs) for solving MOPs. Instead of using one single ideal or nadir point, each weight vector has one exclusive ideal point in our method for decomposition, in which the decomposed directions are adapted during the search process. In this way, the adapted decomposed directions can evenly and entirely cover the PF of the target MOP. The effectiveness of our method is analyzed theoretically and verified experimentally when embedding it into three representative multiobjective evolutionary algorithms (MOEAs), which can significantly improve their performance. When compared to seven competitive MOEAs, the experiments also validate the advantages of our method for solving 39 artificial MOPs with various PFs and one real-world MOP.

A Localized High-Fidelity-Dominance-Based Many-Objective Evolutionary Algorithm

The practicality of Pareto-dominance in solving many-objective optimization problems becomes questionable due to its inability to factor the critical Human Decision-making (HDM) elements, including, the number of better objectives, the degree of betterment in objectives, and objectives&#x2019; relative preference. Relevant dominance principles are recently proposed to incorporate the first two HDM elements, often with the need for new tunable parameters. This paper proposes a high-fidelity-dominance principle, that factors all the three HDM elements, explicitly and simultaneously, and without requiring tuning of any parameter. This principle has been implemented in a reference vector based framework, leading to a computationally efficient many-objective Evolutionary Algorithm (MaOEA), namely localized high-fidelity-dominance based EA (LHFiD). Critically, LHFiD also has an inbuilt mechanism for on-the-fly determination of the timing for: (a) intermittent nadir point estimation that enables faster convergence, and (b) its self-termination that bears practically utility. This paper is based on an extensive study involving 41,912 experiments, in which the proposed LHFiD approach is compared with existing competitive MaOEAs. The paper reports statistically better performance in about 60% instances, making it practical and worthy of further investigation and application.

Multi-objective two-stage stochastic unit commitment model for wind-integrated power systems: A compromise programming approach

In this paper, we introduce a compromise programming (CP) framework for solving a multi-objective two-stage stochastic unit commitment problem characterized by high penetration of wind power. The proposed framework aims at finding best-compromise Pareto efficient on/off schedules, accounting for wind and power demand uncertainties: such solutions must trade off the three objectives of operating cost, CO2 emissions, and wind power curtailment in accordance to the decision maker preferences. To achieve this, we introduce a practical procedure to compute the ideal and Nadir points associated to the multi-objective two-stage stochastic unit commitment problem and propose a linearized ℓ1 norm-based compromise program to design best-compromise on/off schedules that correspondingly minimize and maximize their weighted distances to the ideal point and to the Nadir point, considering the preference weights assigned by the decision maker to each of the three objective functions. The proposed CP framework is applied to a case study related to the New England IEEE-39 bus test system. The results show that, compared to the schedule obtained through the traditional minimization of operating cost, the designed best-compromised schedules considerably improve CO2 emissions reduction and wind power curtailment performance by conservatively sacrificing operating cost performance.

가변속 DFIM 시스템의 가상관성 모델링

The variable-speed DFIM system is a next-generation energy storage technology in which a rotor is connected to a back-to-back converter to adjust the active and reactive power of the device to compensate for the output variability of renewable energy sources. However, general DFIM has less inertia than synchronous generators to support the system when a disturbance occurs in the system, and requires an active technology to assist it. In this paper, a steam turbine governor with droop characteristics was modeled to explain the power control of the existing variable speed DFIM and simulate the drop in system frequency, and a virtual inertia controller was used for the variable speed DFIM system. The current and active power of the DFIM and the frequency change is compared by distinguishing the before and after using the virtual inertia. DFIM, which operates as a variable load after using virtual inertia, reduces the rotor current and reduces the active power absorbed from the system from 1p.u to 0.78p.u by using the virtual inertial active power. Accordingly, it was confirmed that the rotor speed was variable, and it was confirmed that the virtual inertia loop using kinetic energy operated effectively. When disturbance occurs in the system frequency due to the dropout of the power source of the system, the frequency nadir point drops to 48.5Hz. When the system frequency inertia was supported using virtual inertia, the frequency nadir increased from 48.5Hz to 48.76Hz, confirming that the system frequency nadir was improved by mimicking the inertial characteristics of the synchronous generator even during pump operation.

True orthophoto mosaic generation: a simple and fast method

UAV-based images are now widely used to generate large-scale orthophoto mosaics. The generation of an orthophoto mosaic is divided into two stages: image registration and image stitching. Using the DSM associated with each image, orthophotos are generated throughout the image registration. The single orthophotos generated are then joined to each other step by step in the second stage, utilizing various methods of image stitching. Image stitching methods depend on the complex and challenging processes of image matching and seamline determination. In addition, the registration and stitching of images in UAV-based mapping projects with a significant number of images is a time-consuming process. In this study, a straightforward method is provided for creating large-scale true orthophoto mosaics from UAV-based images without the requirement to generate single orthophotos, image registration and seamline network determination. Instead of registrating the images and then stitching them step-by-step, this method processes the DSM of the entire area and all of the images simultaneously. First, for each DSM point, the optimal image is determined from among all the visible images based on an optimization procedure. Optimization is based on two criteria: distance from nadir point and distance from the projection center. Using the determined optimal images, the differential rectification procedure is then run, and the orthophoto mosaic cells are filled. The results of this investigation demonstrated that the proposed method yielded a mosaic with minimal changes along the seamline. In addition, the proposed method is compared with the conventional orthophoto mosaic production method, which is based on image matching and determination of seamlines. Evaluations indicate that the proposed method is able to increase the production rate of orthophoto mosaic by 39% and 45% in dataset 1 and 2 respectively. Additionally, the geometric accuracy calculated using the checkpoints in the orthophoto mosaic generated by the suggested method has decreased by an average of 2 cm, indicating more precise results.

A Pareto Front grid guided multi-objective evolutionary algorithm

For multi-objective optimization problems with irregular Pareto Fronts, most widely used decomposition methods in MOEA/D (multi-objective evolutionary algorithms based on decomposition) have shown to be lack of the ability to balance the diversity and the convergence to track the true Pareto Fronts during the search. This research investigates the recently proposed grid-based decomposition methods, which reflect the inherent characteristics of the neighborhood structure in the solution to address the issues of diversity and convergence. The performance of the grid-based decomposition method, however, depends on the size of its grid segmentation, and its time complexity increases with the number of grids. In order to improve the computational efficiency, we propose a new concept of Pareto Front grid to guide the search in MOEA. In order to reduce the computing time, a new nadir point estimation strategy based on statistical analysis has been proposed to estimate the whole population. In addition, based on the idea of knee point, a novel grid-based knee point selection method is proposed in the environmental selection of the next generation. Finally, a grid-based decomposition multi-objective evolutionary algorithm with Pareto Front Grid (PFG-MOEA) is proposed. Extensive experimental analysis demonstrates the effectiveness of the proposed PFG-MOEA against state-of-the-art multi-objective evolution algorithms. As the extension of the CDG-MOEA (Constrained Decomposition approach with Grids MOEA) algorithm in the literature, PFG-MOEA can obtain better performance by consuming much less computing time.

Controlling the Frequency Response in AC/DC Microgrid using an Energy Storage Device

This paper deals with the issue of frequency regulation in a small insulated low inertia grid with a large participation of renewable energy sources (RESs). A strong decentralized control strategy is used, allowing various RESs such as batteries, supercapacitors, and fuel cells to provide additional frequency recovery service. A small grid with a synchronous machine, photovoltaic cells, and fuel cells was developed as generation units to test the effectiveness of the suggested technique. Furthermore, the battery and supercapacitors were added to the system to give additional service to suppliers. Simulating the system response to numerous uncertainty is used to evaluate the controller's performance.&nbsp; the controller's efficiency is displayed in Graphical form. This paper will show how a decentralized method that allows all units to provide active power supports not only adjusts frequency nadir points but also minimizes the amount of active power required in the process. As a result, the electrical pressure on each element that supports the network against the heavy usage of RESs is reduced.

Validation of the TOA Products of the Baotou Sandy Site With Landsat8/OLI Considering BRDF Correction

The Baotou sandy site in China is an important field site in the Committee on Earth Observation Satellites radiometric calibration network (RadCalNet), which freely releases the bottom-of-atmosphere (BOA) and top-of-atmosphere (TOA) spectral reflectance products in the spectral range from 400 nm to 1000 nm at 10 nm intervals with the aid of a set of automatic spectral and atmospheric parameter measurement devices. However, the released TOA and BOA spectral reflectance products are nadir-view spectral reflectance, which could produce errors if the Baotou sandy site is offset from the nadir point when they are utilized to calibrate one satellite sensor with the vicarious calibration method or to detect radiometric performance changes in the target sensor. Therefore, to address this problem and further broaden the applicable scopes of TOA spectral reflectance products, this article develops TOA and BOA bidirectional reflectance distribution function (BRDF) models using valid time-series TOA and BOA spectral reflectance products to fulfil BRDF correction. Then, the corrected TOA spectral reflectance is validated with the on-orbit measured TOA spectral reflectance of the Landsat8 Operational Land Imager (OLI) sensor with high and stable radiometric performance. After analysing the fitting accuracies of the BOA and TOA BRDF models, the influences of the filter criteria of valid time-series nadir-view BOA and TOA spectral reflectance, geo-positioning error of Landsat8/OLI, and aerosol type in the BOA BRDF correction process on the validation results are discussed. The results show that the BOA BRDF model obtains a better correction effect and is more stable than the TOA BRDF model.

Abstract 11084: Procedural Parameters During Cryoballoon Ablation Predict Early Pulmonary Vein Reconnection and Atrial Fibrillation Recurrence

Introduction: Cryoballoon ablation (CBA) is an established procedure for the management of atrial fibrillation (AF). We sought to assess procedural parameters as predictors of early PV reconnection and AF recurrence following CBA. Methods: 119 patients undergoing CBA for AF were included. Balloon temperature (BT) recorded by the console during CBA targeting each of the four pulmonary veins (PV) was monitored to determine the time needed to reach -15°C and -40°C from the start of the freeze. BT at 30 seconds (s), 60 s and the temperature nadir point were also recorded. Rewarming (thaw) time from the nadir point to 0 °C, was also determined. PVs were assessed for early reconnection and patients were followed for arrhythmia recurrence. Results: Early PV reconnection was identified in 39 (8.3%) of 471 PVs. BT was significantly colder in the absence of early PV reconnection (30 s: -33.5°C vs -29.5°C, p=0.001; 60 s: -41°C vs -36.5°C, p&lt;0.001; nadir: -47°C vs -41.5°C, p&lt;0.001). Early PV reconnection was associated with significantly shorter time to reach -15°C and -40°C (12s vs 14.5s, p=0.023; and 46s vs 75s, p=0.005) and longer rewarming time (7s vs 5.75s, p=0.012) (Panel A). A logistic regression model with the procedural parameters was created to predict early PV reconnection and the corresponding ROC analysis had an AUC=0.71 (Panel B). During an average follow-up period of 559 days, AF recurrence occurred in 51 (49%) patients. Kaplan Meier analysis showed better arrhythmia free survival for patients in whom BT decreased below -40°C in all PVs and patients who had no early PV reconnections, compared to patients where BT below -40°C was not achieved in at least one PV (Log Rank = 6.3, p=0.012) and patients who had PV reconnections (Log Rank = 4.1, p=0.043) (Panel C). Conclusions: Slower BT decline, warmer BT nadir, and faster rewarming time predict early PV reconnection. A lower rate of AF recurrence was associated with absence of early PV reconnections and achieving a BT below -40 °C in all PVs.

Bayesian Optimization-Based Tasking Method for an Ozone Observation Satellite with Maneuverable Sensors

This paper presents a novel method to guide an Earth observation satellite equipped with maneuverable sensors for remote sensing using the measurement of the total column ozone (TCO) as the application. The resulting task planning can interpret the measurements in real time and balance the exploration and exploitation of the area of interest intelligently. A Bayesian optimization (BO)-based method is developed to achieve this goal. For comparison, by the nadir-pointing strategy, the satellite always points to and measures the nadir points; whereas by the offset-pointing strategy, the satellite is guided by the BO-based tasking method to measure the location with either larger TCO values or higher model uncertainties. As demonstrated by the simulation results, the proposed tasking method leads to both better prediction accuracy and better precision of the TCO distribution. This reveals that the proposed observation strategy can enhance the efficiency and accuracy of the remote sensing satellite. A comparison with a deterministic offset-pointing method is also presented to demonstrate that the BO-based tasking method is indeed superior.

Grid-Forming Inverter Enabled Virtual Power Plants With Inertia Support Capability

Modern energy systems are experiencing the transition towards renewable-powered ones. Some conventional thermal units based on synchronous machines are gradually decommissioned and replaced by power electronics interfaced renewables. Thus, the lack of natural inertia and governor damping, which are the features of synchronous machines, raises significant concern about system frequency stability, including the faster rate of change and lower nadir point of frequency. Meanwhile, with the rapid development of communication and Internet of Things technologies, distributed energy resources can be aggregated as a virtual power plant to help balance real-time electricity demand and supply. However, the capability of utilizing the whole virtual power plant to provide adjustable inertia support has not been explored yet. In this paper, we propose a framework of the synchronous virtual power plant based on grid-forming inverter interfaced distributed energy resources. By coordinating the parameter settings of grid-forming inverters, the virtual power plant provides inertia support. Also, we design an online learning-based parameter settings method that makes the inertia of the virtual power plant adjustable. A case study in IEEE 34 nodes system illustrates the effectiveness of the proposed method.