Related Uncertainties Research Articles

Communication Within Firms: Evidence from CEO Turnovers

This paper uses novel, firm-level communication measures derived from communications metadata several months before and after a CEO transition for 102 firms to study whether and how this organizational event is reflected in employees’ communication flows. We find that CEO turnover is associated with an initial decrease in intrafirm communication (−20% relative to the pre-CEO transition period), followed by a significant increase approximately five months after the CEO turnover (+20% relative to the pre-CEO transition period). The increase in communication is driven primarily by interdepartmental (i.e., communication involving employees of different functional departments) and vertical (i.e., communication among managers and employees) communication flows. This study suggests that communications metadata are a useful tool to examine how organizational change and related uncertainty impact information flows within firms. This paper was accepted by Alfonso Gambardella, business strategy. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02719 .

Future changes in the influence of the NAO on Mediterranean winter precipitation extremes in the EC-Earth3 large Ensemble: The prominent role of internal variability

One of the largest uncertainties in future climate projections is the interplay between internally generated and externally forced changes. This study investigates the changes in the link between the North Atlantic Oscillation (NAO) and Mediterranean winter extreme rainfall and dry days by the end of the 21st century compared to present day. We compare two different future pathways and estimate the extent to which the NAO imprint is affected by the global warming level using the latest EC-Earth3 large ensemble historical and future experiments. It is shown that the expected range of winter extremes changes due to internal and unpredictable fluctuations of the NAO largely overcomes the signal associated with externally-forced NAO variations. The NAO is found to exert a similar control on European climate variability, regardless of the amount of warming. For most of the Mediterranean region, magnitude and even sign of projected changes in the NAO-congruent precipitation indices vary substantially across the individual ensemble members according to the corresponding evolution of the NAO. Internal variability provides an average basin-wide contribution of up to 90% or more to the total NAO-driven variability in SSP1–1.9, and of about 80% in SSP5–8.5. Sub-regionally, the anthropogenic component of the NAO link is more evident over the Iberian Peninsula and parts of the central Mediterranean. This emphasises the role of internal variability and related uncertainty in determining the future impact of the NAO via the large spread in the circulation responses. However, the NAO is found to exert a weaker influence on the extreme precipitation total variability in both future scenarios given their future marked increase in total intensity and variance as opposed to the negligible NAO-related trends. Opposite conclusions are drawn for dry days, which are projected to decrease in the future, especially in the northern Mediterranean. Thus, this study also highlights how the variability of future extreme precipitation intensity in the Mediterranean basin will be less dependent on the principal mode of internal climate variability, posing further challenges for prediction and adaptation to weather-related hazards.

The effects of discrimination and psychological distress on U.S. Latino/a young adults' relational uncertainty and relationship instability.

Racial/ethnic discrimination is a common and salient stressor for many individuals. Although discrimination can impair personal and relational well-being, little is known about its influences on the process of considering dissolution (i.e., relationship instability). In two studies of Latino/a young adults, we examined associations among discrimination, psychological distress, relational uncertainty, and relationship instability. Study 1 assessed self-reports of 475 participants aged 18-29 (60.2% female, Mage = 24.8, SD = 3.22). Study 2 examined self-reports of 462 participants aged 18-29 (40.9% female, Mage = 25.9, SD = 2.72). Structural equation models evaluated direct and indirect associations among study variables. Discrimination was associated with relationship instability, both directly and indirectly via its associations with psychological distress and, in Study 1, relational uncertainty. Overall results suggest that racial/ethnic discrimination is associated with romantic relationship instability through its associations with psychological distress and uncertainty about the future of a relationship. Prior research demonstrates the resilience of Latino/a communities, and our findings reinforce the need for policies and clinical resources that reduce discrimination and support mental health and relationships. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Can Short-Term Online-Monitoring Improve the Current WFD Water Quality Assessment Regime? Systematic Resampling of High-Resolution Data from Four Saxon Catchments

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of integrated guidance on surface water chemical monitoring (e.g., WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires monthly sampling to assess the chemical quality status of a body of surface water. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data are investigated under different sampling scenarios and compared with current, monthly grab sampling data. About 23 million data points were analyzed for this study. Three chemical parameters (dissolved oxygen, nitrate-nitrogen, and chloride concentration) and discharge data were selected from four catchments of different sizes, ranging from 51,391 km2 to 84 km2 (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper, we propose short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general, we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as a proxy for analyzing event-mobilized pollutants, and (III) investigate the related uncertainties and costs of both sampling methods. Results show that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law, as the probability of catching a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, such as dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, such as nitrogen-nitrate or chloride. The analysis of discharge events as a proxy parameter for event-mobilized pollutants proves that the probability of capturing samples during events is significantly increased by STOM.

Fuzzy Estimators of Drain spacing in Subsoil Drainage using Fuzzy Logic and Possibility Theories

In the permanent flow of subsoil drainage, a lot of equations are used, most of them based on the Dupuit assumption. All related mathematical models present uncertainties and fuzziness, which create problems in the design of drainage networks. Fuzzy Logic deals with this problem and allows the management of uncertain information. This paper presents the solution of the Hooghout equation based on Fuzzy Logic and Possibility theories, using the Reduced Transformation Method for the related numerical calculations. This results in a fuzzy estimator for the drain spacing, whose α-cuts, provide, according to Possibility Theory, the confidence intervals of the drain spacing with a certain strong probability. Results on subsoil drainage in the case of soils with parallel drains located at any position from the impermeable bottom are presented. The possibility theory application enables the engineers and designers of irrigation, drainage, and water resources projects to gain knowledge of hydraulic properties (e.g., water level, outflow volume) and make the right decision for rational and productive engineering studies.

Reducing uncertainty in source area exploration of mineralized glacial erratics using terrestrial cosmogenic radionuclide dating

Mineral exploration often relies on sedimentary indicators as first signs of a potential nearby mineralization in bedrock. The transportation of sediment by glacial and fluvial processes introduces uncertainty into the tracing of potential source areas of the sediment. This is particularly challenging in areas where glacial erosion has been weak, resulting in reworking of sediments and multiple directions of transportation. In this study we explore the use of Terrestrial Cosmogenic Nuclides (TCN) alongside conventional mineral exploration methods to better link indicators with their potential source areas.The study focuses on a mineral exploration project site in northern Finland in a region with stratigraphic evidence of multiple glaciations. The project targets the source of discovered Au mineralized erratic boulders that have been deposited atop the most recent till unit. The superposition suggests transportation in the latest glacial event. However, the 10Be (35.9 ± 1.3 and 30.3 ± 1.1 ka) and 26Al TCN ages analyzed from the mineralized erratics precede the latest glacial event, suggesting the possibility of multiple stages of transportation. The local bedrock TCN inventories (48.9 ± 1.9 and 85.3 ± 2.8 ka) are well preserved, suggestive of weak glacial erosion and therefore short recent transportation distances for the mineralized erratics. By combining the TCN interpretation and historical ice flow directions derived from the till stratigraphy, we suggest a nearby source locating NNW of the dated erratics.We find that TCN dating can limit some of the transportation related uncertainties in glaciated terrain. Through the analysis of TCN inventories from bedrock and boulders it is possible to characterize glacial erosion and boulder transportation, and to identify repeated exposure events, i.e., the possibility of multi-staged transportation. The method benefits from combined use of stratigraphic investigations that can identify both the local transportation directions and local glacial coverage history. TCN sampling has a minimal environmental impact, can be used in remote areas and can provide information about the transport history already in the early stages of exploration. Although the analysis is time consuming, the survey is light to conduct and informative even with a small number of samples.

Commitment, Relational Uncertainty, and the Investment Model

ABSTRACT Based on Rusbult’s investment model and Knobloch and Solomon’s conceptualization of relational uncertainty, this study investigated how uncertainty in romantic relationships affected satisfaction, quality of alternatives, investments, and commitment. 343 adults in romantic relationships completed measures of relational uncertainty, satisfaction, investment size, quality of alternatives, and commitment. Results indicated that relational uncertainty was negatively related to satisfaction, investment, and commitment, and positively related to quality of alternatives. Relational uncertainty moderated the relationship between satisfaction and commitment. The satisfaction-commitment relationship was quite strong at low levels of relational uncertainty, but as relational uncertainty increased the satisfaction-commitment relationship weakened and eventually become nonsignificant.

From manual to machine: assessing the efficacy of large language models in content analysis

ABSTRACT This study compares the performance of Large Language Models (LLMs) and human coders in predicting relational uncertainty from textual data. Employing various LLMs (gpt-4.0-turbo, gpt-3.5-turbo, Claude 2, llama7b-v2-chat, and llama13b-v2-chat), we found that these models perform comparably to human coders, with only minor differences in Mean Squared Error (MSE) values. However, not all LLMs performed equally, underscoring the importance of model selection. Our findings highlight the potential of LLMs as a scalable tool for content analysis, but also emphasize their nuanced application based on the specific research context. The study advances the discourse on the use of LLMs in content analysis and provides insights for future research in this rapidly evolving field.

Examining the Coopetition Relationships in Renewable Energy Trade among BRI Countries: Complexity, Stability, and Evolution

The Belt and Road Initiative (BRI) has significantly transformed the traditional energy market and reshaped international cooperation and conflict dynamics through its expanding trade in renewable energy resources. This study focuses on examining the complex and evolving nature of coopetition relationships in the renewable energy trade among BRI countries from 2013 to 2020. Understanding the interplay between cooperation and competition in this sector is crucial for comprehending the dynamics and stability of these trade relationships. Using a signed network approach, the findings of this study reveal that the countries predominantly exhibit a cooperative relationship. However, as time progresses, a notable pattern emerges, characterized by the coexistence of “competitive cooperation” and “cooperative competition”. In addition, coopetition group clustering is strongly influenced by geographical location. China, as a key player in the BRI, demonstrates a coopetition group characterized by a high inflow and low outflow pattern. Furthermore, the implementation of the BRI has greatly improved the overall stability of trade along the route. However, the coexistence of competition and cooperation among nations has increased the uncertainty of trade relations, thereby exerting a certain level of influence on their stability. Based on these findings, this study proposes policy recommendations to strength renewable energy trade relationships along the BRI route.

Convection-permitting climate models offer more certain extreme rainfall projections

Extreme precipitation events lead to dramatic impacts on society and the situation will worsen under climate change. Decision-makers need reliable estimates of future changes as a basis for effective adaptation strategies, but projections at local scale from regional climate models (RCMs) are highly uncertain. Here we exploit the km-scale convection-permitting multi-model (CPM) ensemble, generated within the FPS Convection project, to provide new understanding of the changes in local precipitation extremes and related uncertainties over the greater Alpine region. The CPM ensemble shows a stronger increase in the fractional contribution from extreme events than the driving RCM ensemble during the summer, when convection dominates. We find that the CPM ensemble substantially reduces the model uncertainties and their contribution to the total uncertainties by more than 50%. We conclude that the more realistic representation of local dynamical processes in the CPMs provides more reliable local estimates of change, which are essential for policymakers to plan adaptation measures.

The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) – sensitivity studies and evaluation using airborne measurements of power plant emissions

Abstract. The Atmospheric Radionuclide Transport Model (ARTM) operates at the meso-γ scale and simulates the dispersion of radionuclides originating from nuclear facilities under routine operation within the planetary boundary layer. This study presents the extension and validation of this Lagrangian particle dispersion model and consists of three parts: (i) a sensitivity study that aims to assess the impact of key input parameters on the simulation results, (ii) the evaluation of the mixing properties of five different turbulence models using the well-mixed criterion, and (iii) a comparison of model results to airborne observations of carbon dioxide (CO2) emissions from a power plant and the evaluation of related uncertainties. In the sensitivity study, we analyse the effects of the stability class, roughness length, zero-plane displacement factor, and source height on the three-dimensional plume extent as well as the distance between the source and maximum concentration at the ground. The results show that the stability class is the most sensitive input parameter as expected. The five turbulence models are the default turbulence models of ARTM 2.8.0 and ARTM 3.0.0, one alternative built-in turbulence model of ARTM, and two further turbulence models implemented for this study. The well-mixed condition tests showed that all five turbulence models are able to preserve an initially well-mixed atmospheric boundary layer reasonably well. The models deviate only 6 % from the expected uniform concentration below 80 % of the mixing layer height, except for the default turbulence model of ARTM 3.0.0 with deviations of up to 18 %. CO2 observations along a flight path in the vicinity of the lignite power plant Bełchatów, Poland, measured by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Cessna aircraft during the Carbon Dioxide and Methane Mission (CoMet) campaign in 2018 allowed for evaluation of model performance for the different turbulence models under unstable boundary layer conditions. All simulated mixing ratios are of the same order of magnitude as the airborne in situ data. An extensive uncertainty analysis using probability distribution functions, statistical tests, and direct spatio-temporal comparisons of measurements and model results help to quantify the model uncertainties. With the default turbulence setups of ARTM versions 2.8.0 and 3.0.0, the plume widths are underestimated by up to 50 %, resulting in a strong overestimation of the maximum plume CO2 mixing ratios. The comparison of the three alternative turbulence models shows good agreement of the peak plume CO2 concentrations, the CO2 distribution within the plumes, and the plume width, with a 30 % deviation in the peak CO2 concentration and a less than 25 % deviation in the measured CO2 plume width. Uncertainties in the simulations may arise from the different spatial and temporal resolutions of simulations and measurements in addition to the turbulence parametrisation and boundary conditions. The results of this work may help to improve the accurate representation of real plumes in very unstable atmospheric conditions through the selection of distinct turbulence models. Further comparisons at different stability regimes are required for a final assessment of model uncertainties.

Surrogate-Based Uncertainty Analysis for Groundwater Contaminant Transport in a Chromium Residue Site Located in Southern China

Numerical modeling is widely acknowledged as a highly precise method for understanding the dynamics of contaminant transport in groundwater. However, due to the intricate characteristics of environmental systems and the lack of accurate information, the results are susceptible to a significant degree of uncertainty. Numerical models must explicitly consider related uncertainties in parameters to facilitate robust decision-making. In a Chromium Residue Site located in southern China (the study area), this study employed Monte Carlo simulation to assess the impact of variability in key parameters uncertainty on the simulation outcomes. Variogram analysis of response surface (VARS), global sensitivity analysis, and an XGBoost (version 2.0.0)-based surrogate model was employed to overcome the substantial computational cost of Monte Carlo simulation. The results of numerical simulation indicate that the contaminant is spreading downstream towards the northern boundary of contaminated site near Lianshui River, threatening water quality. Furthermore, migration patterns are complex due to both downstream convection and upstream diffusion. Sensitivity analysis identified hydraulic conductivity, recharge rate, and porosity as the most influential model parameters, selected as key parameters. Moreover, uncertainty analysis indicated that the variability in key parameters has a minimal impact on the simulation outcomes at monitoring wells near the contaminant source. In contrast, at wells positioned a considerable distance from the contaminant source, the variability in key parameters significantly influences the simulation outcomes. The surrogate model markedly mitigated computational workload and calculation time, while demonstrating superior precision and effectively capture the non-linear correlations between input and output of the simulation model.

An Observational Study of Dialogue about Uncertainty in Clinician-Family Counseling Conversations Following Prenatal Diagnosis of Complex Congenital Heart Disease

ObjectiveFamilies who receive a prenatal diagnosis of complex congenital heart disease (cCHD) often experience severe psychological distress and identify uncertainty as a key source of that distress. This study examined clinician-family conversations during initial fetal cardiology consultations to identify the topics of uncertainty discussed. MethodsIn this observational, qualitative study, initial fetal cardiology consultations were audio-recorded, transcribed verbatim, and coded by two independent coders. A codebook was inductively and deductively developed and applied. This content analysis focused on uncertainty-related codes and associated themes. ResultsDuring 19 consultations including five clinicians, 13 different cardiac diagnoses were discussed (seven with high mortality risk). Median consultation length was 37 min (IQR: 26–51), with only 11% of words spoken by families. On average, 51% of total words spoken focused on uncertainty in relation to cardiac diagnosis, etiology, comorbidities, prognosis, childbirth, therapeutics, and logistics. Family-initiated discussion on uncertainty largely focused on childbirth and pregnancy and postpartum logistics. ConclusionsHalf of dialogue within initial fetal cardiology encounters discussed uncertainty surrounding prenatally diagnosed cCHD. Parent and clinician perspectives should be gathered on the essential content and optimal delivery of uncertainty-related topics. InnovationThis study is conceptually and methodologically innovative as one of the first to examine audio-recorded dialogue between fetal cardiology clinicians and families.

Religious Conversations and Surface Acting as Predictors of Relational Uncertainty in (Dis)confirming Sibling Relationships

ABSTRACT This study examined the associations among frequency and comfort of siblings’ religious conversations and their relational uncertainty (RU), as well as the degree to which the associations depended upon surface acting and sibling confirmation (i.e. acceptance and challenge). Participants included 218 young adult siblings who completed an online survey about the sibling with whom they were closest to in age. Results indicated that frequency and comfort of discussing religious topics were inversely associated with sibling RU. After controlling for similarity in religious affiliations and beliefs between siblings, regression models revealed significant two-way interaction effects between surface acting and frequency of discussing religion, as well as between confirmation and both frequency and comfort of discussing religion. Consequently, how family members talk about sensitive topics involving matters of identity divergence may be as important, if not more important, than the content of those conversations.

Time and frequency dynamics between NFT coins and economic uncertainty

Non-fungible tokens (NFTs) are one-of-a-kind digital assets that are stored on a blockchain. Examples of NFTs include art (e.g., image, video, animation), collectables (e.g., autographs), and objects from games (e.g., weapons and poisons). NFTs provide content creators and artists a way to promote and sell their unique digital material online. NFT coins underpin the ecosystems that support NFTs and are a new and emerging asset class and, as a new and emerging asset class, NFT coins are not immune to economic uncertainty. This research seeks to address the following questions. What is the time and frequency relationship between economic uncertainty and NFT coins? Is the relationship similar across different NFT coins? As an emerging asset, do NFT coins exhibit explosive behavior and if so, what role does economic uncertainty play in their formation? Using a new Twitter-based economic uncertainty index and a related equity market uncertainty index it is found that wavelet coherence between NFT coin prices (ENJ, MANA, THETA, XTZ) and economic uncertainty or market uncertainty is strongest during the periods January 2020 to July 2020 and January 2022 to July 2022. Periods of high significance are centered around the 64-day scale. During periods of high coherence, economic and market uncertainty exhibit an out of phase relationship with NFT coin prices. Network connectedness shows that the highest connectedness occurred during 2020 and 2022 which is consistent with the findings from wavelet analysis. Infectious disease outbreaks (COVID-19), NFT coin price volatility, and Twitter-based economic uncertainty determine bubbles in NFT coin prices.

The 1886 Charleston, South Carolina, Earthquake: Intensities and Ground Motions

ABSTRACT The 1 September 1886 Charleston, South Carolina, earthquake was one of the largest preinstrumental earthquakes in eastern North America for which extensive contemporaneous observations were documented. The distribution of shaking was mapped shortly after the earthquake, and reconsidered by several authors in the late twentieth century, but has not been reconsidered with a modern appreciation for issues associated with macroseismic data interpretation. Detailed contemporary accounts have also never been used to map the distribution of numerical shaking intensities in the near field. In this study we reconsider macroseismic data from far-field accounts as well as detailed accounts of damage in the near field, estimating modified Mercalli intensity values at 1297 locations including over 200 definite “not felt” reports that delineate the overall felt extent. We compare the results to the suite of ground-motion models for eastern North America selected by the National Seismic Hazard Model, using a recently proposed mainshock rupture model and an average site condition for the locations at which intensities are estimated. The comparison supports the moment magnitude estimate, 7.3, from a recently proposed rupture model (Bilham and Hough, 2023). A ShakeMap constrained by model predictions and estimated intensities further illustrates this consistency, which we show is insensitive to rupture model details. Given the uncertainty of calibration relations for magnitudes close to 7, the overall intensity distribution provides a good characterization of shaking but cannot improve the independent moment magnitude estimate. We also identify a previously unrecognized early large aftershock that occurred 9–10 min after the mainshock, for which we estimate magnitude ∼5.6.

Absolute radiance calibration in the UV and visible spectral range using atmospheric observations during twilight

Abstract. We present an improved radiance calibration method for UV–Vis spectroscopic instruments with a narrow field of view (up to a few degrees) based on the calibration method by Wagner et al. (2015). The updated method uses only measurements during the twilight period instead of several hours as for the original method. The calibration is based on the comparison of measurements and simulations of the radiance of zenith-scattered sunlight. The main advantage of our method compared to radiance calibration methods in the laboratory is that the calibration can be directly applied in the field. This allows routine radiance calibrations whenever the sky is clear during twilight. The calibration can also be performed retrospectively and will thus be applicable for the large number of existing data sets. Also, potential changes in the instrument properties during transport from the laboratory to the field are avoided. The new version of the calibration method presented here has two main advantages. First, the required measurement period can be rather short (only a few minutes during twilight for cloud-free conditions). Second, even without knowledge of the aerosol optical depth (AOD), the errors in the calibration method are rather small, especially in the UV spectral range where they range from about 4 % at 340 nm to 8 % at 420 nm. If the AOD is known, the uncertainties are even smaller (about 3 % at 340 nm to 4 % at 420 nm). For visible wavelengths, good accuracy is only obtained if the AOD is approximately known with uncertainties from about 4 % at 420 nm to 10 % between about 550 and 700 nm (generally the AOD is nevertheless smaller in the visible than in the UV spectral range). One shortcoming of the method is that it is not possible to determine the AOD exactly at the time of the (twilight) measurements because AOD observations from sun photometer measurements or the MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) measurements are usually not meaningful for such high solar zenith angle (SZA). But the related uncertainty can be minimised by repeating the radiance calibrations during the twilight periods of several days.

SELF-EFFICACY, JOB PERFORMANCE, AND TRANSFORMATIONAL LEADERSHIP: A STRUCTURAL EQUATION MODEL ON ORGANIZATIONAL COMMITMENT AMONG PUBLIC SCHOOL TEACHERS

<p>The study aimed to investigate the influence of self-efficacy, job performance, and transformational leadership style on organizational commitment using Structural Equation Modelling (SEM) to 400 public school teachers in Region XI, Philippines. Findings revealed a high level of self-efficacy, a very high level of job performance, and high levels of transformational leadership and organizational commitment. There is a strong, positive, and significant correlation between self-efficacy and organizational commitment; job performance and organizational commitment; and transformational leadership and organizational commitment. Further results showed that the best-fit model was model 3 showing the direct causal relationships of Self-Efficacy, Job Performance, and Transformational Leadership Style on Organizational Commitment. Moreover, the Organizational Commitment of the respondents was defined by the retained indicators, namely: Affective Commitment and Individual Performance. Self-efficacy was described with the following retained indicators: Disciplinary Self-efficacy, and Creative Positive School Climate. On the other hand, Job performance was described in terms of the indicators Workload and Working Environment. Finally, Transformational Leadership retained the following indicators: Political Skill Inventory, and Perception of Relational Uncertainty. Findings suggest that the policy-making body of the Department of Education should look into the provision of professional development, workload allocations, and benefits of the teachers to further improve their organizational commitment.</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0517/a.php" alt="Hit counter" /></p>

Special cases of the minimum spanning tree problem under explorable edge and vertex uncertainty

AbstractThis article studies the Minimum Spanning Tree Problem under Explorable Uncertainty as well as a related vertex uncertainty version of the problem. We particularly consider special instance types, including cactus graphs, for which we provide randomized algorithms. We introduce the problem of finding a minimum weight spanning star under uncertainty for which we show that no algorithm can achieve constant competitive ratio.

Data‐driven model‐free modified nodal analysis circuit solver

AbstractThis work introduces a novel data‐driven model‐free modified nodal analysis (MNA) circuit solver. The solver is capable of handling circuit problems featuring elements for which solely measurement data are available. Rather than utilizing hard‐coded phenomenological model representations, the data‐driven MNA solver reformulates the circuit problem such that the solution is found by minimizing the distance between circuit states that fulfill Kirchhoff's laws, and states belonging to the measurement data. In this way, the formerly inevitable demand for model representations is eliminated, thus avoiding the introduction of related modeling errors and uncertainties. The proposed solver is applied to linear and nonlinear RC‐circuits and to a half‐wave rectifier.