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Distributed Control Scheme for Clusters of Power Quality Compensators in Grid-Tied AC Microgrids
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-11) Martínez-Gómez, Manuel; Burgos-Mellado, Claudio; Morales-Paredes, Helmo Kelis; Gómez, Juan Sebastián; Verma, Anant Kumar; Bonaldo, Jakson Paulo
Modern electrical systems are required to provide increasing standards of power quality, so converters in microgrids need to cooperate to accomplish the requirements efficiently in terms of costs and energy. Currently, power quality compensators (PQCs) are deployed individually, with no capacity to support distant nodes. Motivated by this, this paper proposes a consensus-based scheme, augmented by the conservative power theory (CPT), for controlling clusters of PQCs aiming to improve the imbalance, harmonics and the power factor at multiple nodes of a grid-tied AC microgrid. The CPT calculates the current components that need to be compensated at the point of common coupling (PCC) and local nodes; then, compensations are implemented by using each grid-following converter’s remaining volt-ampere capacity, converting them in PQCs and improving the system’s efficiency. The proposal yields the non-active power balancing among PQCs compounding a cluster. Constraints of cumulative non-active contribution and maximum disposable power are included in each controller. Also, grid-support components are calculated locally based on shared information from the PCC. Extensive simulations show a seamless compensation (even with time delays) of unbalanced and harmonics current (below 20% each) at selected buses, with control convergences of 0.5–1.5 [s] within clusters and 1.0–3.0 [s] for multi-cluster cooperation. © 2023 by the authors.
Evaluation of Machine Learning Techniques for Classifying and Balancing Data on an Unbalanced Mini-Mental State Examination Test Data Collection Applied in Chile
(Institute of Electrical and Electronics Engineers Inc., 2024) Ormeno, Pablo; Marquez, Gaston; Taramasco, Carla
The Mini-Mental State Examination (MMSE) is the most widely used cognitive test for assessing whether suspected symptoms align with cognitive impairment or dementia. The results of this test are meaningful for clinicians but exhibit highly unbalanced distributions in studies and analyses regarding the classification of patients with cognitive impairment. This is a complex problem when a large number of MMSE tests are analysed. Therefore, data balancing and classification techniques are crucial to support decision-making in distinguishing patients with cognitive impairment in an effective and efficient manner. This study explores machine learning techniques for data balancing and classification using a real unbalanced dataset consisting of MMSE test responses collected from 103 elderly patients participating in a Chilean patient monitoring project. We used 8 data classification techniques and five data balancing techniques. We evaluated the performance of the techniques using the following metrics: sensitivity, specificity, F1-score, likelihood ratio (LR+ and LR-), diagnostic odds ratio (DOR), and the area under the ROC curve (AUC). From the set of data balancing and classification techniques used in this study, the results indicate that synthetic minority oversampling and random forest balancing techniques improve the accuracy of cognitive impairment diagnosis. The results obtained in this study support clinical decision-making regarding early classification or exclusion of older adult patients with suspected cognitive impairment. © 2013 IEEE.
Relationship of Community Mobility, Vital Space, and Faller Status in Older Adults
(Multidisciplinary Digital Publishing Institute (MDPI), 0024-12) Robles Cruz, Diego; Lira Belmar, Andrea; Fleury, Anthony; Lam, Méline; Castro Andrade, Rossana M.; Puebla Quiñones, Sebastián; Taramasco Toro, Carla
Community mobility, encompassing both active (e.g., walking) and passive (e.g., driving) transport, plays a crucial role in maintaining autonomy and social interaction among older adults. This study aimed to quantify community mobility in older adults and explore the relationship between GPS- and accelerometer-derived metrics and fall risk. Methods: A total of 129 older adults, with and without a history of falls, were monitored over an 8 h period using GPS and accelerometer data. Three experimental conditions were evaluated: GPS data alone, accelerometer data alone, and a combination of both. Classification models, including Random Forest (RF), Support Vector Machines (SVMs), and K-Nearest Neighbors (KNN), were employed to classify participants based on their fall history. Results: For GPS data alone, RF achieved 74% accuracy, while SVM and KNN reached 67% and 62%, respectively. Using accelerometer data, RF achieved 95% accuracy, and both SVM and KNN achieved 90%. Combining GPS and accelerometer data improved model performance, with RF reaching 97% accuracy, SVM achieving 95%, and KNN 87%. Conclusion: The integration of GPS and accelerometer data significantly enhances the accuracy of distinguishing older adults with and without a history of falls. These findings highlight the potential of sensor-based approaches for accurate fall risk assessment in community-dwelling older adults. © 2024 by the authors.
Explicit Modeling of Brain State Duration Using Hidden Semi Markov Models in EEG Data
(Institute of Electrical and Electronics Engineers Inc., 2024) Trujillo-Barreto, Nelson J.; Galvez, David Araya; Astudillo, Aland; El-Deredy, Wael
We consider the detection and characterization of brain state transitions based on ongoing electroencephalography (EEG). Here, a brain state represents a specific brain dynamical regime or mode of operation that produces a characteristic quasi-stable pattern of activity at the topography, sources, or network levels. These states and their transitions over time can reflect fundamental computational properties of the brain, shaping human behavior and brain function. The hidden Markov model (HMM) has emerged as a useful tool for uncovering the hidden dynamics of brain state transitions based on observed data. However, the limitations of the Geometric distribution of states' durations (dwell times) implicit in the standard HMM, make it sub-optimal for modeling brain states in EEG. We propose using hidden semi Markov models (HSMM), a generalization of HMM that allows modeling the brain states duration distributions explicitly. We present a Bayesian formulation of HSMM and use the variational Bayes framework to efficiently estimate the HSMM parameters, the number of brain states, and select among candidate brain state duration distributions. We assess HSMM performance against HMM on simulated data and demonstrate that the accurate modeling of state durations is paramount for making reliable inference when the task at hand requires accurate model predictions. Finally, we use actual resting-state EEG data to illustrate the benefits of the approach in practice. We demonstrate that the possibility of modeling brain state durations explicitly provides a new way for investigating the nature of the neural dynamics that generated the EEG data. © 2013 IEEE.
Modeling and Solving the Time-Dependent in-Building Delivery Problem in Last-Mile Logistics
(Institute of Electrical and Electronics Engineers Inc., 2024) Paredes-Belmar, Germán; Latorre-Núñez, Guillermo; Bronfman, Andrés
This article introduces, models, and solves the time-dependent in-building delivery problem in last-mile logistics. It determines efficient travel sequences for a worker (e.g., delivery person, deliveryman, mailman, agent) who delivers goods or provides services directly to customers located within a building using its elevation system. We study, in detail, all the steps involved in a travel sequence inside a building: horizontal trips, unloading products to the customers, waiting for elevators, and vertical trips within elevators. The sequences and their total times vary depending on the building type, the elevation system, the moment of the day, and the arrival time because of the daily building traffic intensity variations. A mixed-integer linear programming model and a genetic algorithm-based metaheuristic are proposed to solve a set of instances in two office buildings. The results show that it is very important to determine the best time to visit a building because of its time dependency. The variation in delivery time between off-peak hours versus peak hours is between 15% and 30% for the set of solved instances. Moreover, the order of customer visits differs drastically depending on the arrival time to the building. © 2013 IEEE.
Harnessing evolutionary algorithms for enhanced characterization of ENSO events
(Springer, 0025-01) Abdulkarimova, Ulviya; Abarca-del-Rio, Rodrigo; Collet, Pierre
The El Niño-Southern Oscillation (ENSO) significantly influences the complexity and variability of the global climate system, driving its variability. ENSO events’ irregularity and unpredictability arise from intricate ocean–atmosphere interactions and nonlinear feedback mechanisms, complicating their prediction of timing, intensity, and geographic impacts. This study applies Genetic Programming and Genetic Algorithms within the EASEA (EAsy Specification of Evolutionary Algorithms) Evolutionary Algorithms (EA) framework to develop a repository of symbolic equations for El Niño and La Niña events, spanning their various intensities. By analyzing data from the Oceanic Niño Index, this approach yields equation-based characterizations of ENSO events. This methodology not only enhances ENSO characterization strategies but also contributes to expanding the use of EAs in climate event analysis. The resulting equations have the potential to offer insights beyond academia, benefiting education, climate policy, and environmental management. This highlights the importance of ongoing refinement, validation, and exploration in these fields through EAs. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Model Sets with Euclidean internal Space
(Cambridge University Press, 0022-11-07) Allendes Cerda, Mauricio; Coronel, Daniel
We give a characterization of inter-model sets with Euclidean internal space. This characterization is similar to previous results for general inter-model sets obtained independently by Baake, Lenz and Moody, and Aujogue. The new ingredients are two additional conditions. The first condition is on the rank of the abelian group generated by the set of internal differences. The second condition is on a flow on a torus defined via the address map introduced by Lagarias. This flow plays the role of the maximal equicontinuous factor in the previous characterizations. © The Author(s), 2023. Published by Cambridge University Press.
Statistical Analysis to Quantify the Impact of Map Type on Estimating Peak Discharge in Non-Instrumented Basins
(Universidad Tecnologica de Bolivar, 0023-08-11) Sierra-Sánchez, Alexandra; Gatica, Gustavo; Paternina-Verona, Duban A; Ramos, Helena M.
The calculation of peak discharge in non-instrumented basins requires including morphometric parameters, which in turn depend on the map type used. This study analyses the impact of and variation in peak discharges of the Caño Ricaurte basin, Colombia, based on three types of maps at different resolution scales. The reference map used was the map made for the detailed designs of the channel analysed, which was extracted from the Master Plan of the City. Additionally, maps from a 90 × 90 m digital elevation model and contour lines extracted from Google Earth were used. The time of concentration was determined by different equations (Kirpich, Témez, Bureau, and TR-55) using the mapping methods described above, and the peak discharge was determined using rainfall-runoff models. © 2023 by the authors.
Improving and measuring the solubility of favipiravir and montelukast in SC-CO2 with ethanol projecting their nanonization
(Royal Society of Chemistry, 2023-11) Rojas, Adrián; Sajadian, Seyed Ali; López-De-Dicastillo, Carol; Ardestani, Nedasadat Saadati; Aguila, Gonzalo; Jouyban, Abolghasem
Supercritical carbon dioxide (SC-CO2)-based approaches have become more popular in recent years as alternative methods for creating micro- or nanosized medicines. Particularly, high drug solubility is required in those techniques using SC-CO2 as a solvent. During the most recent pandemic years, favipiravir and montelukast were two of the most often prescribed medications for the treatment of COVID-19. In this study, ethanol at 1 and 3 mol% was utilized as a cosolvent to increase the solubility of both medicines in SC-CO2 by a static approach using a range of temperatures (308 to 338 K) and pressure (12 to 30 MPa) values. The experimentally determined solubilities of favipiravir and montelukast in SC-CO2 + 3 mol% ethanol showed solubility values up to 33.3 and 24.5 times higher than that obtained for these drugs with only SC-CO2. The highest values were achieved in the pressure of 12 MPa and temperature of 338 K. Last but not least, six density-based semi-empirical models with various adjustable parameters were used to perform the modeling of the solubility of favipiravir and montelukast. © 2023 The Royal Society of Chemistry.
Correction to: Short-Term Meteorological and Environmental Signals Recorded in a Firn Core from a High-Accumulation Site on Plateau Laclavere, Antarctic Peninsula (Geosciences, (2021), 11, 10, (428), 10.3390/geosciences11100428)
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Hoffmann-Abdi, Kirstin; Fernandoy, Francisco; Meyer, Hanno; Freitag, Johannes; Opel, Thomas; McConnell, Joseph R.; Schneider, Christoph
The authors would like to make the following corrections to the published article [1]. In Section 1, fourth paragraph: In the sentence “Proxy Proxy data, such as glacio-chemical data from firn and ice cores, may partly compensate for the lack of direct observations.” the word “Proxy” should be deleted as it occurs twice. The sentence should have read: “Proxy data, such as glacio-chemical data from firn and ice cores, may partly compensate for the lack of direct observations.”. In Section 3.4, second paragraph: In the sentence “The slope of the δ18O–δD relationship (7.94) is close to that of the Global Meteoric Water Line (GMWL) [49] and is of the same order of magnitude as the slope of the site-specific LMWL (m = 7.76).” the “m =” should be deleted before “7.76” and “, 8” should be inserted after “GMWL”. The sentence should have read: “The slope of the δ18O–δD relationship (7.94) is close to that of the Global Meteoric Water Line (GMWL, 8) [49] and is of the same order of magnitude as the slope of the site-specific LMWL (7.76).”. In Section 4.5, first paragraph: In the sentence “Figure 8c,e visualise the anti-correlation between MLT and SIE in both the Bellingshausen-Amundsen Sea and the Weddell Sea (r > −0.6, p = 0; Table 5).” the “>” in the parenthesis should be replaced by “=”. The sentence should have read: “Figure 8c,e visualise the anti-correlation between MLT and SIE in both the Bellingshausen-Amundsen Sea and the Weddell Sea (r = −0.6, p = 0; Table 5).”. In the original publication, there was a mistake in Table 1 [1]. The order of the values in the column “Accumulation Rate (kg m−2 a−1)” was reversed for the years 2012 to 2015. The authors state that the scientific results for the accumulation rates in Table 1, which are presented and discussed in Sections 3.2 and 4.2 of the original publication, are not affected by this mistake, as all values were used correctly there. The corrected Table 1 is as follows: Annual accumulation rates calculated for the OH-12 drill site for the period 2012–2015. In the original publication, there was a mistake in Figure 6 [1]. The intercept in the equation for the δ18O−δD relationship of firn core OH-12 should be +6.01 and not −6.01. The corrected equation is δD = 7.94 × δ18O + 6.01. A correction was also made to the second paragraph in Section 3.4, where in the sentence “However, intercepts differ significantly (OH-12: −6.01; LMWL: −1.52; GMWL: +10), which is also reflected by the position of the OH-12 samples in the δ18O–δD plot (Figure 6a).” the intercept of the δ18O−δD relationship of firn core OH-12 should accordingly be +6.01 and not −6.01. In addition, in the same sentence the word “the” should be inserted before the word “intercepts”. The sentence should have read: ”However, the intercepts differ significantly (OH-12: +6.01; LMWL: −1.52; GMWL: +10), which is also reflected by the position of the OH-12 samples in the δ18O–δD plot (Figure 6a).”. The updated Figure 6 is as follows: (a) δ18O–δD relationship of all considered precipitation samples collected at Bernardo O’Higgins station (OH) between 2008 and 2017 (n = 294; coloured dots) compared to the δ18O–δD relationship of firn core OH-12 (n = 414; white dots). The Global Meteoric Water Line (GMWL) is indicated in blue. The Local Meteoric Water Line (LMWL) established for the study site by Fernandoy et al. [31,32] is shown as a dashed red line and the LMWL derived in this study as a solid red line. For each δ18O–δD relationship, the equation, the coefficient of determination (R2) and the p-value (p) are given. (b) Time series of δ18O, δD and d excess of OH-12 constructed based on the weighted age scale. High-resolution data are shown as light-coloured lines and monthly means as bold lines. The authors apologize for any inconvenience these mistakes may have caused the readers. The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated. © 2023 by the authors.
Voltage Regulation Enhancement of DC-MG Based on Power Accumulator Battery Test System: MPC-Controlled Virtual Inertia Approach
(Institute of Electrical and Electronics Engineers Inc., 2022-01-01) Long, Bo; Zeng, Wei; Rodriguez, Jose; Guerrero, Josep M.; Chong, Kil To
In a DC-microgrid (DC-MG) composed of a power accumulator battery test system (PABTS), owing to the low inertia of DC capacitance, the charging and discharging of a PABTS can easily cause DC-link voltage fluctuations, which may jeopardize the system stability. Hence, a virtual inertia control (VIC) strategy is proposed to suppress these fluctuations and enhance the stability of the DC-MG. The VIC method is realized in a bidirectional grid-connected converter (BGCC), which combines VIC and model predictive control (MPC). The proposed method can provide inertia support during the transient state and enhance the dynamic characteristics of the DC-link voltage. A prediction model is established that uses the variation range of the DC-link voltage as the constraint, and the output of VIC as well as voltage deviations as optimization objectives. The desired DC-link current increment is calculated using the prediction model to change the input DC current reference of the VIC. To validate the effectiveness of the proposed method, hardware-in-the-loop (HIL) experiments are performed, and the results indicate that MPC-VIC is superior to the existing VIC methods in terms of inertia support and the DC-link voltage variation suppression of PABTS DC-MGs. © 2010-2012 IEEE.
On stochastic aspects of impact modeling of the innovation incentive system and business internationalization: evidence from Portuguese SMEs
(Taylor and Francis Ltd., 2024) Grilo L.M.; Pereira E.J; Maidana J.P.; Stehlík M.
Multivariate normal distribution is base for many statistical techniques, including ordinary least square inference. Here we show that in order to make research on Internationalization of Companies, more flexible approach is needed, namely partial least squares (PLS). It is a nonparametric technique, used in Structural Equation Modeling (SEM), which makes no distributional assumptions and also may be applied with small sample sizes. In this study we discuss on regularity conditions for PLS from the perspective of semi-continuous covariance which fills the gap in the current studies. The stochastic aspects, especially those related to usage of PLS-SEM, can be well integrated to the topologically grounded regression, where jumps in the covariances can occur. The purpose of the research is to analyze and understand the impact of the Incentive System (IS) for Innovation, within the scope of the National Strategic Reference Framework (QREN) 2014-2020, on the Internationalization of Portuguese Small and Medium Enterprises (SMEs). We study stochastic aspects of theoretical model which aggregates the variables Product Innovation, Marketing Innovation, Organizational Innovation and Working Conditions as determinants of Internationalization of Companies. Data were collected based on a quantitative methodology, through a self-completion questionnaire using the Likert psychometric scale, which registered 120 participants. Organizational Innovation (exogenous latent construct) and Product Innovation have shown a statistically significant indirect effect on the Internationalization of Companies (endogenous latent construct) through Marketing Innovation. The latter has a direct effect on the Internationalization (target construct). However, Working Conditions has the greatest impact on Internationalization, meaning that measures such as increasing wages, decreasing the use of temporary work and precarious work conversion into labor effective relations have a very relevant direct effect on the Internationalization of Portuguese SMEs. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.
School Greenness and Student-Level Academic Performance: Evidence From the Global South
(John Wiley and Sons Inc, 2023-08) Jimenez, Raquel B; Bozigar, Matthew; Janulewicz, Patricia; Lane, Kevin J.; Hutyra, Lucy R.; Fabian, M. Patricia
Greenspace in schools might enhance students' academic performance. However, the literature—dominated by ecological studies at the school level in countries from the Northern Hemisphere—presents mixed evidence of a beneficial association. We evaluated the association between school greenness and student-level academic performance in Santiago, Chile, a capital city of the Global South. This cross-sectional study included 281,695 fourth-grade students attending 1,498 public, charter, and private schools in Santiago city between 2014 and 2018. Student-level academic performance was assessed using standardized test scores and indicators of attainment of learning standards in mathematics and reading. School greenness was estimated using Normalized Difference Vegetation Index (NDVI). Linear and generalized linear mixed-effects models were fit to evaluate associations, adjusting for individual- and school-level sociodemographic factors. Analyses were stratified by school type. In fully adjusted models, a 0.1 increase in school greenness was associated with higher test scores in mathematics (36.9 points, 95% CI: 2.49; 4.88) and in reading (1.84 points, 95% CI: 0.73; 2.95); as well as with higher odds of attaining learning standards in mathematics (OR: 1.20, 95% CI: 1.12; 1.28) and reading (OR: 1.07, 95% CI: 1.02; 1.13). Stratified analysis showed differences by school type, with associations of greater magnitude and strength for students attending public schools. No significant associations were detected for students in private schools. Higher school greenness was associated with improved individual-level academic outcomes among elementary-aged students in a capital city in South America. Our results highlight the potential of greenness in the school environment to moderate educational and environmental inequalities in urban areas. © 2023 The Authors. GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union.
Distributed Predictive Secondary Control for Imbalance Sharing in AC Microgrids
(Institute of Electrical and Electronics Engineers Inc., 2022-01-01) Navas-Fonseca, Alex; Burgos-Mellado, Claudio; Gomez, Juan S.; Donoso, Felipe; Tarisciotti, Luca; Saez, Doris; Cardenas, Roberto; Sumner, Mark
This paper proposes a distributed predictive secondary control strategy to share imbalance in three-phase, three-wire isolated AC Microgrids. The control is based on a novel approach where the imbalance sharing among distributed generators is controlled through the control of single-phase reactive power. The main characteristic of the proposed methodology is the inclusion of an objective function and dynamic models as constraints in the formulation. The controller relies on local measurements and information from neighboring distributed generators, and it performs the desired control action based on a constrained cost function minimization. The proposed distributed model predictive control scheme has several advantages over solutions based on virtual impedance loops or based on the inclusion of extra power converters for managing single-phase reactive power among distributed generators. In fact, with the proposed technique the sharing of imbalance is performed directly in terms of single-phase reactive power and without the need for adding extra power converters into the microgrid. Contrary to almost all reported works in this area, the proposed approach enables the control of various microgrid parameters within predefined bands, providing a more flexible control system. Extensive simulation and Hardware in the Loop studies verify the performance of the proposed control scheme. Moreover, the controller's scalability and a comparison study, in terms of performance, with the virtual impedance approach were carried out. © 2010-2012 IEEE.
An Asymmetric Switched-Capacitor Multicell Inverter With Low Number of DC Source and Voltage Stress for Renewable Energy Sources
(Institute of Electrical and Electronics Engineers Inc., 2022) Hosseinzadeh, Mohammad Ali; Sarebanzadeh, Maryam; Garcia, Cristian F.; Babaei, Ebrahim; Rodriguez, Jose
Asymmetric multilevel inverters generate high-quality output voltage using the same number of components as symmetric multilevel inverters. The main drawback of these topologies is that they require many DC voltage sources, and the power switches must endure high voltage stress. In this paper, a switched-capacitor sub-module inverter topology is proposed to reduce the number of DC voltage sources and the voltage stress on the switches of asymmetric multilevel inverters. The proposed sub-module inverter can generate 15 voltage levels by using two DC power supplies and a capacitor. The voltage of the capacitor can be automatically charged at half of the input DC power supply without the need for any sensors. In addition, the capacitor charging operation does not produce an inrush current because it is charged by the direction of the output current; this is an advantage over switched capacitor multilevel inverters. A modular topology is also presented based on the proposed sub-module inverter to achieve high voltage levels while reducing the number of elements. A comprehensive comparison between the proposal and other multilevel inverter topologies is performed to validate the design of the proposed inverter. In addition, thermal and loss distribution simulations of the proposed sub-module inverter are performed. Finally, the performance, efficiency, and accuracy of the proposed inverter are confirmed through laboratory prototyping. © 2013 IEEE.
Quality of automatic geocoding tools: a study using addresses from hospital record files in Temuco, Chile
(Fundacao Oswaldo Cruz, 2022) Quinteros, Maria Elisa; Blazquez, Carola; Rosas, Felipe; Ayala, Salvador; Ossa García, Ximena Marcela; Delgado-Saborit, Juana Maria; Harrison, Roy M.; Ruiz-Rudolph, Pablo; Yohannessen, Karla
Automatic geocoding methods have become popular in recent years, facilitating the study of the association between health outcomes and the place of living. However, rather few studies have evaluated geocoding quality, with most of them being performed in the US and Europe. This article aims to compare the quality of three automatic online geocoding tools against a reference method. A subsample of 300 handwritten addresses from hospital records was geocoded using Bing, Google Earth, and Google Maps. Match rates were higher (> 80%) for Google Maps and Google Earth compared with Bing. However, the accuracy of the addresses was better for Bing with a larger proportion (> 70%) of addresses with positional errors below 20m. Generally, performance did not vary for each method for different socioeconomic status. Overall, the methods showed an acceptable, but heterogeneous performance, which may be a warning against the use of automatic methods without assessing quality in other municipalities, particularly in Chile and Latin America. © 2022 Fundacao Oswaldo Cruz. All rights reserved.
Rainfall-Induced Landslide Assessment under Different Precipitation Thresholds Using Remote Sensing Data: A Central Andes Case
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-07) Maragaño-Carmona, Gonzalo; Fustos Toribio, Ivo J.; Descote, Pierre-Yves; Robledo, Luis F.; Villalobos, Diego; Gatica, Gustavo
The determination of susceptibility to rainfall-induced landslides is crucial in developing a robust Landslide Early Warning System (LEWS). With the potential uncertainty of susceptibility changes in mountain environments due to different precipitation thresholds related to climate change, it becomes important to evaluate these changes. In this study, we employed a machine learning approach (logistic models) to assess susceptibility changes to landslides in the Central Andes. We integrated geomorphological features such as slope and slope curvature, and precipitation data on different days before the landslide. We then split the data into a calibration and validation database in a 50/50% ratio, respectively. The results showed an area under the curve (AUC) performance of over 0.790, indicating the model’s capacity to represent prone-landslide changes based on geomorphological and precipitation antecedents. We further evaluated susceptibility changes using different precipitation scenarios by integrating Intensity/Duration/Frequency (IDF) products based on CHIRPS data. We concluded that this methodology could be implemented as a Rainfall-Induced Landslides Early Warning System (RILEWS) to forecast RIL occurrence zones and constrain precipitation thresholds. Our study estimates that half of the basin area in the study zone showed a 59% landslide probability for a return of two years at four hours. Given the extent and high population in the area, authorities must increase monitoring over unstable slopes or generate landslide early warning at an operational scale to improve risk management. We encourage decision-makers to focus on better understanding and analysing short-duration extreme events, and future urbanization and public infrastructure designs must consider RIL impact. © 2023 by the authors.
Fast Solver for Implicit Continuous Set Model Predictive Control of Electric Drives
(Institute of Electrical and Electronics Engineers Inc., 2022) Favato, Andrea; Carlet, Paolo Gherardo; Toso, Francesco; Torchio, Riccardo; Ortombina, Ludovico; Bruschetta, Mattia; Carli, Ruggero; Alotto, Piergiorgio; Bolognani, Silverio; Rodriguez, Jose
This paper proposes a fast and accurate solver for implicit Continuous Set Model Predictive Control for the current control loop of synchronous motor drives with input constraints, allowing for reaching the maximum voltage feasible set. The related control problem requires an iterative solver to find the optimal solution. The real-time certification of the algorithm is of paramount importance to move the technology toward industrial-scale applications. A relevant feature of the proposed solver is that the total number of operations can be computed in the worst-case scenario. Thus, the maximum computational time is known a priori. The solver is deeply illustrated, showing its feasibility for real-time applications in the microseconds range by means of experimental tests. The proposed method outperforms general-purpose algorithms in terms of computation time, while keeping the same accuracy. © 2013 IEEE.
Sensitivity of Simulated Conditions to Different Parameterization Choices Over Complex Terrain in Central Chile
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-01) Arévalo, Jorge; Marín, Julio C.; Díaz, Mailiu; Raga, Graciela; Pozo, Diana; Córdova, Ana María; Baumgardner, Darrel
This study evaluates the performance of fourteen high-resolution WRF runs with different combinations of parameterizations in simulating the atmospheric conditions over the complex terrain of central Chile during austral winter and spring. We focus on the validation of results for coastal, interior valleys, and mountainous areas independently, and also present an in-depth analysis of two synoptic-scale events that occurred during the study period: a frontal system and a cut-off low. The performance of the simulations decreases from the coast to higher altitudes, even though the differences are not very clear between the coast and interior valleys for 10 m wind speeds and precipitation. The simulated vertical profiles show a warmer and drier boundary layer and a cooler and moister free atmosphere than observed. The choice of the land-surface model has the largest positive impact on near-surface variables with the five-layer thermal diffusion scheme showing the smallest errors. Precipitation is more sensitive to the choice of cumulus parameterizations, with the simplified Arakawa–Schubert scheme generally providing the best performance for absolute errors. When examining the performance of the model simulating rain/no-rain events for different thresholds, also the cumulus parameterizations better represented the false alarm ratio (FAR) and the bias score (BS). However, the Morrison microphysics scheme resulted in the best critical success index (CSI), while the probability of detection (POD) was better in the simulation without analysis nudging. Overall, these results provide guidance to other researchers and help to identify the best WRF configuration for a specific research or operational goal. © 2023 by the authors.
Recognition and conversion of electric field representations: The case of electric field lines
(American Physical Society, 2023-07) Campos, Esmeralda; Zuza, Kristina; Guisasola, Jenaro; Zavala, Genaro
We conducted a study with introductory and upper-division physics students in a Mexican university to learn how students independently recognize the electric field’s main characteristics in the electric field lines diagram and as a source or target representation in conversion processes. We used the theory of registers of semiotic representations and a phenomenographic approach as a framework to analyze data. The recognition and conversion abilities were explored through interpretation and construction tasks. We identified students’ main difficulties in recognition and conversion in the interpretation and construction tasks. In conversion processes, we found that when the electric field lines diagram is the source representation, students do not interpret the field lines’ density as the magnitude of the electric field. The difficulties of interpretation that arise in these conversion processes depend partially on the target representation. We also found that constructing electric field lines is especially difficult for students at both introductory and upper-division levels. Most students would prefer to draw vector field plots instead. We recommend that electricity and magnetism teachers and researchers be aware of the difficulties that the recognition and conversion in interpretation and construction tasks may represent for their students in understanding the electric field concept. © Published by the American Physical Society.

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