Explicit Measurement Research Articles

Active Measure Reinforcement Learning for Observation Cost Minimization

Markov Decision Processes (MDP) with explicit measurement cost are a class of environments in which the agent learns to maximize the costed return. Here, we define the costed return as the discounted sum of rewards minus the sum of the explicit cost of measuring the next state. The RL agent can freely explore the relationship between actions and rewards but is charged each time it measures the next state. Thus, an optimal agent must learn a policy without making a large number of measurements. We propose the active measure RL framework (Amrl) as a solution to this novel class of problem, and contrast it with standard reinforcement learning under full observability and planning under partially observability. We demonstrate that Amrl-Q agents learn to shift from a reliance on costly measurements to exploiting a learned transition model in order to reduce the number of real-world measurements and achieve a higher costed return. Our results demonstrate the superiority of Amrl-Q over standard RL methods, Q-learning and Dyna-Q, and POMCP for planning under a POMDP in environments with explicit measurement costs.

Revisiting the “manic defence hypothesis”: assessing explicit and implicit cognitive biases in euthymic bipolar disorder

ABSTRACT Objective: The manic defence theory of bipolar disorder suggests that manic symptoms arise from an attempt to overcompensate for underlying depression. This depression avoidance may also be active in euthymia, raising concerns about the accuracy of explicit self-report measurement, and, more importantly, the presence of underlying negative cognitions. Methods: Ninety-six individuals identifying as bipolar-depressed, bipolar-euthymic, unipolar-depressed, unipolar-euthymic (based on self-reported diagnosis and mood state), and 53 non-psychiatric controls completed a series of online questionnaires assessing explicit and implicit measures of activated negative schemata. These included the Dysfunctional Attitudes Scale and the Young Schema Questionnaire, and an implicit measure, the Pragmatic Inference Task. Results: When assessed explicitly, bipolar-euthymic individuals endorsed negative schema content at a level intermediate between depressed individuals (bipolar and unipolar) and controls. However, when assessed implicitly, bipolar-euthymic individuals endorsed the highest levels of negative schema content of all groups. Conclusions: These findings indicate depression avoidance during euthymia, suggesting that implicit measurement may have a role in understanding latent negative cognitions in bipolar euthymia. The results have clinical implications as they suggest that reliance upon explicit self-report may overlook underlying and unconscious affective instability. KEY POINTS (1) People with bipolar euthymia reported low levels of explicit negative schemas, but high implicit signs of negative/depressive cognitions. (2) This implicit negative schema activation was higher than that seen in depression. (3) Bipolar euthymia may not represent wellness but suppression of negative cognitions.

Synergistic evaluation of Sentinel 1 and 2 for biomass estimation in a tropical forest of India

Spatially explicit measurement of Above Ground Biomass (AGB) is crucial for the quantification of forest carbon stock and fluxes. To achieve this, an integration of Optical and Synthetic Aperture Radar (SAR) satellite datasets could provide an accurate estimation of forest biomass. This will also help in removing the uncertainties associated with the single sensor-based estimation approaches. Therefore, the present study attempts to integrate Sentinel-2 optical data with Sentinel-1 SAR dataset to estimate AGB in the Shoolpaneshwar Wildlife Sanctuary (SWS), Gujarat, India. In this study, two non-parametric machine learning algorithms viz Support Vector Machines (SVMs) with different kernel functions—linear, sigmoidal, radial and polynomial and Random Forest (RF) were employed for the prediction of AGB using different combinations of VV, VH, Normalized Difference Vegetation Index (NDVI) and Incidence Angle (IA). Ground based AGB was estimated through allometric equation at 35 sampling sites with the help of tree height and Diameter at Breast’s Height (DBH). Standalone collinearity analysis among different parameters resulted in poor correlation of AGB with VH (r = 0.05) and IA (r = 0.015), whereas a significantly good correlation with NDVI (r = 0.80) and VV (r = 0.74) were observed. Inclusion of NDVI with VV and VH together also resulted in a better correlation (r = 0.85) than other combinations. The SVM with linear kernel utilizing parametric the combinations of VV + VH + NDVI and VV + VH + NDVI + IA were found to be best performing on the basis of evaluation metrics. The outcome of this study highlighted the significance of machine learning techniques and synergistic use of different remote sensing data for an improved AGB quantification in tropical forests.

Psychometric Properties of Two Implicit Associations Tests measuring Adult Attachment.

Adult attachment style has consequences for mental health, interpersonal functioning and emotion regulation. This occurs partly deliberately, also referred to as explicit, and partly on an automatic level outside of conscious awareness, also referred to as implicit. Whereas explicit adult attachment can be assessed with self-report instruments, measurement of implicit adult attachment requires indirect methods. This paper describes the psychometric properties of two Implicit Association Tests measuring general adult attachment in a population sample. The study evaluated the reliability and the validity of the Avoidant Attachment IAT (ANX-IAT) and the Anxious Attachment IAT (AVOID-IAT). Validity was evaluated against self-report measures of adult attachment style (RQ), psychopathology (SQ-48), and well-being (MHC-SF). The split-half reliabilities of both IATs were good; the test-retest reliability of the ANX-IAT was adequate; however the AVOID-IAT had low test-retest reliability. Both IATs did not explain variance in psychopathology additional to explicit measures. The AVOID-IAT showed added value over explicit measurement of avoidant attachment in explaining variance in well-being, particularly regarding emotional and psychological well-being. The ANX-IAT did not explain variance in any measure of well-being additional to the explicit measure of anxious attachment. Our findings provide a basis from which more valid IATs measuring general adult attachment can be developed. Furthermore, they suggest that implicit avoidant attachment might be related to well-being, particularly emotional and psychological well-being. However, further research is needed to investigate the role of implicit general adult attachment in mental health and to optimize the two IATs in terms of validity before clinical use is recommended.

Self-Reported Emotions and Facial Expressions on Consumer Acceptability: A Study Using Energy Drinks.

Emotional responses elicited by foods are of great interest for new product developers and marketing professionals, as consumer acceptance proved to be linked to the emotions generated by the product in the consumers. An emotional measurement is generally considered an appropriate tool to differentiate between the products of similar nutritional value, flavour, liking and packaging. Novel methods used to measure emotions include self-reporting verbal and visual measurements, and facial expression techniques. This study aimed to evaluate the explicit and implicit emotional response elicited during the tasting of two different brands (A and B) of energy drinks. The explicit response of consumers was assessed using liking (nine-point hedonic scale), and emotions (EsSense Profile®—Check-All-That-Apply questionnaire), and implicit emotional responses were evaluated by studying facial expressions using the Affectiva Affdex® software. The familiarity of the product and purchase intent were also assessed during the study. The hedonic rating shows a significant difference in liking between the two brands of energy drink during the tasting session. For the explicit emotional responses, participants elicited more positive emotions than the negative emotions for both energy drinks. However, participants expressed “happy”, “active” and “eager” emotions more frequently for energy drink A. On the other hand, the implicit emotional responses through facial expressions indicated a high level of involvement of the participants with energy drink B as compared to energy drink A. The study showed that overall liking and the explicit and implicit emotional measurements are weakly to moderately correlated.

Twirling and Hamiltonian engineering via dynamical decoupling for Gottesman-Kitaev-Preskill quantum computing

I introduce an energy constrained approximate twirling operation that can be used to diagonalize effective logical channels in Gottesman-Kitaev-Preskill (GKP) quantum error correction, project states into the GKP code space and construct a dynamical decoupling sequence with fast displacements pulses to distill the GKP stabilizer Hamiltonians from a suitable substrate Hamiltonian. The latter is given by an LC oscillator comprising a superinductance in parallel to a Josephson Junction. This platform, in principle, allows for protected GKP quantum computing without explicit stabilizer measurements or state reset by dynamically generating a ``passively'' stabilized GKP qubit.

Explicit and implicit measurement of nonsuicidal self-injury in the prediction of concurrent and prospective self-injury.

The relationship between explicit nonsuicidal self-injury (NSSI) behavior and implicit identification with NSSI is important to understand considering the under-reported nature of NSSI and the subsequent elevated risk of more severe NSSI. It was expected that implicit assessment of NSSI at baseline would be associated with past-year NSSI frequency assessed at baseline and that it would more strongly associate with NSSI frequency than self-reported future likelihood of NSSI at a 6-month follow-up. Data were collected from 420 young adults (mean age=19; 83% women, 87% White) with recent NSSI at baseline, and 324 were assessed at 6-month follow-up. Participants completed self-report measures and the Self-Injury Implicit Association Task (SI-IAT) at each time point. Baseline implicit NSSI scores significantly predicted NSSI frequency at baseline but not at 6-month follow-up. However, explicit ratings were strongly and significantly associated with future NSSI frequency. These findings suggest that although implicit identification with oneself and NSSI is important to understand, there are limitations regarding the possible utility of the SI-IAT in predicting future NSSI engagement and further research is needed to fully understand why NSSI continues to be such a strong predictor of future NSSI behavior, and suicidal ideation and behavior.

Large-diameter trees, snags, and deadwood in southern Utah, USA

BackgroundThe epidemic Dendroctonus rufipennis (spruce beetle) outbreak in the subalpine forests of the Colorado Plateau in the 1990s killed most larger Picea engelmannii (Engelmann spruce) trees. One quarter century later, the larger snags are beginning to fall, transitioning to deadwood (down woody debris) where they may influence fire behavior, regeneration, and habitat structure.MethodsWe tracked all fallen trees ≥ 1 cm in diameter at breast height (1.37-m high) and mapped all pieces of deadwood ≥ 10-cm diameter and ≥ 1 m in length within 13.64 ha of a high-elevation mixed-species forest in the Picea–Abies zone annually for 5 years from 2015 through 2019. We examined the relative contribution of Picea engelmannii to snag and deadwood pools relative to other species and the relative contributions of large-diameter trees (≥ 33.2 cm at this subalpine site). We compared spatially explicit mapping of deadwood to traditional measures of surface fuels and introduce a new method for approximating vertical distribution of deadwood.ResultsIn this mixed-species forest, there was relatively high density and basal area of live Picea engelmannii 20 years after the beetle outbreak (36 trees ha−1 and 1.94 m2 ha−1 ≥ 10-cm diameter) contrasting with the near total mortality of mature Picea in forests nearby. Wood from tree boles ≥ 10-cm diameter on the ground had biomass of 42 Mg ha−1, 7 Mg ha−1 of Picea engelmannii, and 35 Mg ha−1 of other species. Total live aboveground biomass was 119 Mg ha−1, while snag biomass was 36 Mg ha−1. Mean total fuel loading measured with planar transects was 63 Mg ha−1 but varied more than three orders of magnitude (0.1 to 257 Mg ha−1). Planar transects recorded 32 Mg ha−1 of wood ≥ 7.62-cm diameter compared to the 42 Mg ha−1 of wood ≥ 10-cm diameter recorded by explicit mapping. Multiple pieces of deadwood were often stacked, forming a vertical structure likely to contribute to active fire behavior.ConclusionBark beetle mortality in the 1990s has made Picea an important local constituent of deadwood at 20-m scales, but other species dominate total deadwood due to slow decomposition rates and the multi-centennial intervals between fires. Explicit measurements of deadwood and surface fuels improve ecological insights into biomass heterogeneity and potential fire behavior.

Reliability of cotton fiber length distributions measured by dual-beard fibrography and advanced fiber information system

Fiber length distribution (FLD) is one of the fundamental properties of cotton fibers, which determines cotton length attributes, such as upper half mean length and short fiber content, and thus fiber processability and yarn properties. For decades, the Advanced Fiber Information System (AFIS) has been the only instrument that can provide explicit FLD measurements. However, the reliability of AFIS’s FLD has not been carefully inspected although important issues (e.g., excessive short fiber contents and super long fibers) were raised before. Recently, the dual-beard fibrography (DBF) emerged as a novel approach for direct FLD measurements. It provides non-destructive testing that enables repeatability analysis on FLDs. In this paper, we intend to conduct a thorough repeatability study on DBF with different testing scenarios to verify if DBF is a reliable method for FLD measurements or not, and then use DBF’s FLDs to examine AFIS’s FLDs to develop a better understanding of the existing problems associated with AFIS. The testing scenarios with DBF included multiple tests with one dual-beard sample at the same scanning position, the same sample at different positions, different sample reps by one scanner, and one sample rep by different scanners. The comparison tests between DBF and AFIS were performed on 29 selected cotton samples with a wide range of length uniformity. It was found that DBF’s FLDs are highly repeatable on one scanner (r > 0.99, P = 0, and SSE 0.99, P = 0, and SSE < 0.51). It was demonstrated that the FLDs produced by AFIS and DBF with the same samples are highly correlated (r ≥ 0.87 and P < 5.48e−9), even if AFIS’s FLDs have consistently higher frequencies in the short fiber range (0–12.7 mm) and in a super-long fiber range (40–60 mm) unrealistic to U.S. upland cotton.

Estimation of non-constant variance in isothermal titration calorimetry using an ITC measurement model.

Isothermal titration calorimetry (ITC) is the gold standard for accurate measurement of thermodynamic parameters in solution reactions. In the data processing of ITC, the non-constant variance of the heat requires special consideration. The variance function approach has been successfully applied in previous studies, but is found to fail under certain conditions in this work. Here, an explicit ITC measurement model consisting of main thermal effects and error components has been proposed to quantitatively evaluate and predict the non-constant variance of the heat data under various conditions. Monte Carlo simulation shows that the ITC measurement model provides higher accuracy and flexibility than variance function in high c-value reactions or with additional error components, for example, originated from the fluctuation of the concentrations or other properties of the solutions. The experimental design of basic error evaluation is optimized accordingly and verified by both Monte Carlo simulation and experiments. An easy-to-run Python source code is provided to illustrate the establishment of the ITC measurement model and the estimation of heat variances. The accurate and reliable non-constant variance of heat is helpful to the application of weighted least squares regression, the proper evaluation or selection of the reaction model.

Using GatorEye UAV-Borne LiDAR to Quantify the Spatial and Temporal Effects of a Prescribed Fire on Understory Height and Biomass in a Pine Savanna

In the pine savannas of the southeastern United States, prescribed fire is commonly used to manipulate understory structure and composition. Understory characteristics have traditionally been monitored with field sampling; however, remote sensing could provide rapid, spatially explicit monitoring of understory dynamics. We contrasted pre- vs. post-fire understory characteristics collected with fixed area plots with estimates from high-density LiDAR point clouds collected using the unmanned aerial vehicle (UAV)-borne GatorEye system. Measuring within 1 × 1 m field plots (n = 20), we found average understory height ranged from 0.17–1.26 m and biomass from 0.26–4.86 Mg C ha−1 before the fire (May 2018), and five months after the fire (November 2018), height ranged from 0.11–1.09 m and biomass from 0.04–3.03 Mg C ha−1. Understory heights estimated with LiDAR were significantly correlated with plot height measurements (R2 = 0.576, p ≤ 0.001). Understory biomass was correlated with in situ heights (R2 = 0.579, p ≤ 0.001) and LiDAR heights (R2 = 0.507, p ≤ 0.001). The biomass estimates made with either height measurement did not differ for the measurement plots (p = 0.263). However, for the larger research area, the understory biomass estimated with the LiDAR indicated a smaller difference after the burn (~12.7% biomass reduction) than observed with in situ measurements (~16% biomass reduction). The two approaches likely differed because the research area’s spatial variability was not captured by the in-situ measurements (0.2% of the research area measured) versus the wall-to-wall coverage provided by LiDAR. The additional benefit of having spatially explicit measurements with LiDAR, and its ease of use, make it a promising tool for land managers wanting greater spatial and temporal resolution in tracking understory biomass and its response to prescribed fire.

Sustainable and inclusive – Evaluating urban sustainability indicators’ suitability for measuring progress towards SDG-11

The adoption of the sustainable development goals marks a transition in the global sustainability discourse to a growing focus on equity, with urban areas’ role in achieving sustainable and inclusive growth more explicit in sustainable development goal-11. Within this discourse, urban sustainability indicators could be used to monitor environmental quality and equity within individual cities, while promising to deepen our understanding of how urban areas contribute to global environmental sustainability. We examine 484 indicators of urban and regional environmental sustainability sourced from 40 indexes and online data repositories to determine their suitability for measuring both urban environmental performance and equity. Despite the large number of existing indicators related to urban environmental monitoring, we find that they are inadequate as tools for evaluating progress towards sustainable development goal-11’s integrated goal of sustainable and inclusive (i.e. equitable) urban areas, due to a lack of benchmarks, targets, and explicit measurement of equity considerations. Future research should emphasize data collection that can be disaggregated geographically to make it possible to measure distributional equity and establish locally appropriate benchmarks and realistic targets for urban sustainability indicators. Lastly, we argue that utilizing large-scale, high-resolution datasets has the potential to help overcome these data collection challenges.

A Worldwide Internet Study Based on Implicit Association Test Revealed a Higher Prevalence of Adult Males' Androphilia than Ever Reported Before

BackgroundSocial constrictions or the lack of a clear awareness about one's sexual orientation may influence the ability of individuals to explicitly declare their sexual preferences. Thus, the actual prevalence of males’ sexual attraction toward adult males, which is estimated by studies relying only on explicit questionnaires, may be biased. Conversely, the implicit measurement of androphilia may be a promising method to obtain more reliable data. AimIn the present work, explicit and implicit methods have been used to investigate the rates of explicit nonheterosexuality and implicit androphilia in a large sample of adult males from all around the world. For implicit androphilia, a rate consistent across the continents and close to that predicted by recent genetic models (about 15%) was expected. In contrast, for self-declared homosexuality, a lower and more variable rate was expected. MethodsA sample of 1,050 participants was recruited through an online platform. All participants completed a short biographical questionnaire, an Autobiographical-Implicit Association Test, the Sexual Preference-Implicit Association Test, and an explicit measure of sexual orientation. The answers to these measures were used to explore explicit sexual orientation and implicit androphilia across six main geographical areas (Middle East and Africa, South America, North America, Asia, Europe, and Oceania). OutcomesThe main outcome measures were the D score at the Sexual Preference-Implicit Association Test and the scores at the explicit measure of sexual orientation. ResultsThe rate of nonheterosexuality, which can be found using explicit measures, is rather low, variable (from 6.3% to 11.4%), and influenced by cultural factors. In contrast, the prevalence of androphilia resulting from implicit methods is higher and consistent across geographical areas (from 14.4% to 17.6%). Clinical ImplicationsStudying the diffusion of adult males’ androphilia may be useful to better understand sexual behaviors and preferences and to develop effective health promotion programs among males who have sex with males. Strengths & LimitationsThe large and cross-cultural sample and the use of both implicit and explicit measures allowed for obtaining a detailed picture of adult males’ sexual orientation and androphilia. The main limitations were the Web-based characteristics of the protocol and the lack of an investigation of actual sexual behaviors. ConclusionCompared with the explicit measurement of nonheterosexuality, the implicit measurement of sexual preferences showed a prevalence of androphilia among adult males that is higher, more stable across continents, and more consistent with the predictions of recent genetic models.Colledani D,A. Camperio Ciani Worldwide Internet Study Based on Implicit Association Test Revealed a Higher Prevalence of Adult Males' Androphilia than Ever Reported Before. J Sex Med 2021;18:4–16.

SOS small pelagics: A safe operating space for small pelagic fish in the western Mediterranean Sea

Sustainable fishing practices must ensure human wellbeing by safeguarding the integrity of marine life-supporting systems. Unfortunately, a significant challenge to fisheries management is that sustainable fishing levels can decline, often synergistically, by co-occurring with climate-driven environmental stressors. Within one of the most impacted marine areas in the world, and encompassing a number of highly targeted commercial species, the small pelagic fish community of the western Mediterranean Sea has recently shown signs of collapse. In this study, we identify a worrying coincidence where fishing hotspots for the commercially valuable European sardine Sardina pilchardus and anchovy Engraulis encrasicolus occur in marine areas mostly affected by climate change. To identify these areas, we overlayed detailed, spatially explicit measurements of fishing pressure with the finest-scale maps of cumulative climate change impacts onto these species. According to our results, doubly impacted marine areas largely occur in the north-western Mediterranean Sea, with climate and fisheries mostly affecting European sardine. Reducing local stressors (i.e., fishing pressure) in highly impacted areas may contribute to maintain these communities within a “safe operating space” (SOS), where they remain resilient to climate change. Accordingly, the redistribution and/or reduction of fishing intensity may alleviate pressure in those areas already affected by climate change. Sustainable fishing strategies may benefit, therefore, from the SOS concept and the spatial assessments provided in this study.

Implicit and Explicit Measurement of Work-Related Age Attitudes and Age Stereotypes.

Age attitudes and age stereotypes in the workplace can lead to discrimination and impaired productivity. Previous studies have predominantly assessed age stereotypes with explicit measures. However, sole explicit measurement is insufficient because of social desirability and potential inaccessibility of stereotypical age evaluations to introspection. We aimed to advance the implicit and explicit assessment of work-related evaluations of age groups and age stereotypes and report data collected in three samples: students (n = 50), older adults (n = 53), and workers (n = 93). Evaluative age attitudes were measured implicitly with an Implicit Association Test. Regardless of group, age, and condition (neutral or semantically biased stimuli), the results confirm a stable, moderate implicitly measurable preference for younger over older workers. Whereas explicit measures of general age preferences showed no clear age preference, differentiated explicit measures of work-related age stereotypes also revealed stable preferences in all three samples: Younger workers were rated higher on performance and adaptability and older workers were rated higher on competence, reliability, and warmth. The explicit-implicit correlations were relatively low. Although explicit work-related age stereotypes are differentiated, the stable implicitly measured age bias raises concern. We suggest to apply implicit and explicit measures in the field of ageism in the workplace.

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics.

Sexually antagonistic (SA) genetic variation—in which alleles favored in one sex are disfavored in the other—is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research—including F ST and F IS statistics, genome‐wide association studies, pedigree analyses, reciprocal transplant studies, and evolve‐and‐resequence experiments—to evaluate methods for identifying SA genes and genome‐wide signals of SA genetic variation. We begin by developing theoretical models for between‐sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex‐specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.

Confronting Racism in Chemistry Journals

Confronting Racism in Chemistry Journals

Experimental Evidence of Enhanced Adsorption Dynamics at Liquid-Liquid Interfaces under an Electric Field.

In this work, we investigate the adsorption of surface-active compounds at the water-oil interface subjected to an electric field. A fluid system comprising a pendent water drop surrounded by an asphaltene-rich organic phase is exposed to a DC uniform electric field. Two subfractions of asphaltenes having contrasting affinities to the water-oil interface are used as surface-active compounds. The microscopic changes in the drop shape, as a result of asphaltene adsorption, are captured and the drop profiles are analyzed using our in-house code for axisymmetric drop shape analysis (ADSA) under an electric field. The estimates of dynamic interfacial tension under different strengths of the field (E0) and concentrations of the asphaltene subfractions (C) are used to calculate adsorption dynamics and surface excess. The experimental observations and careful analyses of the data suggest that the externally applied electric field significantly stimulates the mass-transfer rate at the liquid-liquid interface. The enhancement in mass transport at the water-oil interface can be attributed to the axisymmetric electrohydrodynamic fluid flows generated on either side of the interface. The boost in mass transport is evident from the growing decay in equilibrium interfacial tension (γeq) and increased surface excess (Γeq) upon increasing strength of the applied electric field. The mass-transfer intensification does not increase monotonously with the electric field strength above an optimum E0, which is in agreement with the previous theoretical studies in the literature. However, these first explicit experimental measurements of adsorption at an interface under an electric field suggest that the optimum E0 is determined by characteristics of the surface-active molecules.

Confronting Racism in Chemistry Journals

Confronting Racism in Chemistry Journals

Lifetime Considerations for Electrospray Thrusters

Ionic liquid electrospray thrusters are capable of producing microNewton precision thrust at a high thrust–power ratio but have yet to demonstrate lifetimes that are suitable for most missions. Accumulation of propellant on the extractor and accelerator grids is thought to be the most significant life-limiting mechanism. In this study, we developed a life model to examine the effects of design features, operating conditions, and emission properties on the porous accelerator grid saturation time of a thruster operating in droplet emission mode. Characterizing a range of geometries and operating conditions revealed that modifying grid aperture radius and grid spacing by 3–7% can significantly improve thruster lifetime by 200–400%, though a need for explicit mass flux measurement was highlighted. Tolerance analysis showed that misalignment can result in 20–50% lifetime reduction. In addition, examining the impact of electron backstreaming showed that increasing aperture radius produces a significant increase in backstreaming current compared to changing grid spacing. A study of accelerator grid bias voltages revealed that applying a reasonably strong accelerator grid potential (in the order of a kV) can minimize backstreaming current to negligible levels for a range of geometries.