Performance-based Metrics Research Articles

Response of urban flood resilience to climate change: An exploration with a novel performance-based metric considering the socioeconomic impacts of damage costs

Climate change stimulates the emergence of floods and increases flood risk for communities, resulting in extensive casualties and economic loss. Thus, flood resilience has been the focus of much attention. Integrated and holistic metrics are important for an accurate urban flood resilience evaluation. However, performance-based metrics involving surface inundation do not consider the socioeconomic impacts of damage costs on the recovery ability of the urban systems. This hinders the investigation of climate change-induced effects on flood resilience. Therefore, this study proposed a performance-based resilience metric considering the negative impacts of flooding damage costs. The proposed metric was then piloted in a highly urbanized area in Osaka City, Japan to explore the responses of flood resilience to climate change. The results suggest that climate change exerts non-negligible pressure on the study area to maintain its economic characteristics during flooding. Rainfall intensity primarily affects the urban system’s most unfavorable state, while the total amount and duration of rainfall mostly impact the relatively stable state following flooding. Climate change severity is positively linked to the reduction in overall flood resilience. Continued climate change will further expand the spatial coverage of flood resilience losses on a global scale. Furthermore, the negative impacts of economic losses on flood resilience are more noticeable during rainfall events with higher rainfall intensities. This study improves the comprehensiveness of performance-based flood resilience evaluations and provides a reference for the effective enhancement of urban flood resilience under climate change.

Disclosures & Disclaimers: Investigating the Impact of Transparency Disclosures and Reliability Disclaimers on Learner-LLM Interactions

Large Language Models (LLMs) are increasingly being used in educational settings to assist students with assignments and learning new concepts. For LLMs to be effective learning aids, students must develop an appropriate level of trust and reliance on these tools. Misaligned trust and reliance can lead to suboptimal learning outcomes and reduced LLM engagement. Despite their growing presence, there is a limited understanding of achieving optimal transparency and reliance calibration in the educational use of LLMs. In a 3x2 between-subjects experiment conducted in a university classroom setting, we tested the effect of two transparency disclosures (System Prompt and Goal Summary) and an in-conversation Reliability Disclaimer on a GPT-4-based chatbot tutor provided to students for an assignment. Our findings suggest that disclaimer messages included in the responses may effectively mitigate learners' overreliance on the LLM Tutor in the presence of incorrect advice. Disclosing System Prompt seemed to calibrate students’ confidence in their answers and reduce the occurrence of copy-pasting the exact assignment question to the LLM tutor. Student feedback indicated that they would like transparency framed in terms of performance-based metrics. Our work provides empirical insights on the design of transparency and reliability mechanisms for using LLMs in classrooms.

Postoperative Rehabilitation and Return-to-Sport Criteria After Distal Triceps Rupture Repair: A Scoping Review.

Distal triceps rupture is a rare injury that is commonly surgically repaired to improve elbow strength and function. Most patients are active and have goals to return to specific activities and sports. There is no gold standard rehabilitation protocol for return to sport (RTS) after distal triceps repair. To identify in the literature any criteria used for RTS after distal triceps repair. Scoping review; Level of evidence, 4. Under PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, level 1 to 4 studies that examined distal triceps repair and had a minimum follow-up duration of 12 months were deemed eligible for study inclusion. Exclusion criteria encompassed studies that employed nonoperative treatment, lacked specific RTS criteria, or involved revision cases. The selected studies underwent assessment regarding RTS outcomes, timelines, rates, and methodological quality. Of the initial 378 unique studies, 6 studies (including 116 patients involved in 16 different sports) met the inclusion criteria. Four of the studies reported RTS rates, with a mean of 89.3%. The duration of time for returning to sport was reported in 2 studies and varied from 4 to 6 months. The parameters most emphasized in the rehabilitation protocols were progressive range of motion exercises, followed by early immobilization and progressive strengthening exercises. Supervised therapy was reported in only 2 (33%) studies. Although all studies included a rehabilitation protocol and 5 studies included a timeline for RTS, only 1 study provided subjective criteria, and no studies utilized specific objective measurement criteria. The overall study quality was fair. This review demonstrated that the overall RTS rate after distal triceps repair was high (89.3%), with no consensus on RTS criteria. Most studies included initial immobilization followed by progressive range of motion and strengthening. Timing after surgery was used as a measure to RTS in the minority of studies and varied between 4 and 6 months. Further research is needed to develop functional and performance-based metrics to better standardize RTS criteria and rehabilitation protocols.

Gait quality in prosthesis users is reflected by force-based metrics when learning to walk on a new research-grade powered prosthesis.

Powered prosthetic feet require customized tuning to ensure comfort and long-term success for the user, but tuning in both clinical and research settings is subjective, time intensive, and the standard for tuning can vary depending on the patient's and the prosthetist's experience levels. Therefore, we studied eight different metrics of gait quality associated with use of a research-grade powered prosthetic foot in seven individuals with transtibial amputation during treadmill walking. We compared clinically tuned and untuned conditions with the goal of identifying performance-based metrics capable of distinguishing between good (as determined by a clinician) from poor gait quality. Differences between the tuned and untuned conditions were reflected in ankle power, both the vertical and anterior-posterior impulse symmetry indices, limb-force alignment, and positive ankle work, with improvements seen in all metrics during use of the tuned prosthesis. Notably, all of these metrics relate to the timing of force generation during walking which is information not directly accessible to a prosthetist during a typical tuning process. This work indicates that relevant, real-time biomechanical data provided to the prosthetist through the future provision of wearable sensors may enhance and improve future clinical tuning procedures associated with powered prostheses as well as their long-term outcomes.

A method for evaluating and verifying biochemical methane potential test completion performed with landfilled municipal solid waste.

The biochemical methane potential (BMP) test is significant for the landfill industry as it provides a means to evaluate the gas potential, and therefore potential degradability, of both incoming and in-place municipal solid waste (MSW). However, the BMP test is not standardized making comparison of BMP results across sites problematic. For example, the BMP test duration has historically ranged from 20 days to several months with most current BMP tests lasting 60 days. However, the gas generation data can potentially be modelled for any of those durations to produce a prediction of the ultimate BMP value (BMPULT). Currently, the predicted BMPULT values of 23 long-duration (115-150 days) BMP tests were used to determine the required quantity of data (i.e. number of days) needed to produce an accurate BMPULT prediction. Results showed that no single test duration produced both accurate and efficient results, so a novel performance-based endpoint was proposed. The relative change in predicted BMPULT values with respect to time (dBMPULT/dt) was chosen as a potential performance-based completion metric. Results indicate that once the absolute normalized dBMPULT/dt value is within <2.5, <1.5 and <0.6% day-1 that the predicted BMPULT is within 20, 10 and 5% of the true BMPULT, respectively. Overall, the use of performance-based metrics for determining BMP test completion will allow for the collection of partial data sets, reduced experimental times and verification of results.

Moving conservation agriculture from principles to a performance-based production system

Abstract Conservation agriculture (CA) is an approach to farming that is defined by three principles: (1) minimal soil disturbance (no-till), (2) crop diversity in time and space, and (3) soil coverage by crop residues and/or cover crops. These principles provide a roadmap to protect and improve soil. However, the narrow criteria for defining CA may fail to account for tradeoffs between soil health and other ecosystem services. A literature review of meta-analyses dealing with CA and an online survey in France were conducted to explore the implementation and performances of CA. Research on CA systems has focused on crop productivity and soil quality whereas research on other dimensions of cropping system sustainability are lacking. The effects of CA on other aspects of sustainability such as biodiversity and profitability are less prevalent in the literature. The online survey results show that 63% of respondents thought that CA helps reduce pesticide use, 91% that CA improves water use efficiency, and 77% that CA helps to store carbon and achieve the objectives of the 4 per 1000 international initiative. Given the prevalence and widespread support for CA, we advocate for moving CA from its current definition based on the means toward a definition that includes performance-based metrics that address different ecosystem services. CA has potential to help address challenges associated with climate change, biodiversity loss, and water pollution, but opportunities may be missed without developing performance targets that go beyond soil conservation.

Investigating the protective effects of mindfulness-based attention training on mind wandering in applied settings.

Mind wandering, a phenomenon in which attention drifts away from the task-at-hand, is associated with deleterious effects on performance and well-being. As such, efforts to curb mind wandering are warranted. Recently, mindfulness training (MT) has been found to protect against mind wandering. Yet, many MT programs are at risk of falling off the implementation cliff due to challenges implementing these programs in applied settings. To mitigate against this, early-stage research in small convenience samples may be necessary to spur stakeholder engagement and collaboration. Herein, the effects of MT on mind wandering were examined via an internal meta-analysis of early-stage studies of a manualized, context-adaptable short-form MT program, referred to as Mindfulness-Based Attention Training (MBAT). Five longitudinal studies (N = 304) were conducted in a variety of organizational cohorts. Self-reported mind wandering and meta-awareness, as well as accuracy (A') and response time variability (intra-individual coefficient of variation, ICV) during performance of the sustained attention to response task (SART) were assessed at baseline (T1) and 4 weeks later (T2) in MBAT and no-training participants. Standardized mean change (SMC) from T1 to T2 significantly differed between MBAT and no-training groups for mind wandering (ΔSMC = -0.387, p < 0.001), meta-awareness (ΔSMC = -0.374, p < 0.001), and ICV (ΔSMC = -0.376, p = 0.043), suggesting potential protective effects in self-reported and performance-based metrics of mind wandering. These results serve as preliminary proof-of-concept support for MBAT's protective effects on mind wandering. Further, they suggest that MBAT is amenable to implementation across a variety of applied and organizational settings and warrants additional research employing larger sample sizes in randomized controlled designs.

A Comparative Analysis of Performance-Based Resilience Metrics via a Quantitative-Qualitative Combined Approach: Are We Measuring the Same Thing?

Since the proposal of the pioneering “resilience triangle” paradigm, various time-series performance-based metrics have been devised for resilience quantification. The numerous choices diversify the toolbox for measuring this compound system concept; however, this multiplicity causes intractable questions for applications, including “Do these metrics measure the same resilience?” and “Which one to pick under what circumstance?” In this study, we attempted to address these two fundamental issues using a comprehensive comparative investigation. Through a quantitative-qualitative combined approach, 12 popular performance-based resilience metrics are compared using empirical data from China’s aviation system under the disturbance of COVID-19. Quantitative results indicate that only 12 of the 66 metric pairs are strongly positively correlated and with no significant differences in quantification outcomes; qualitative results indicate that the majority of the metrics are based on different definition interpretations, basic components, and expression forms, and thus essentially measure different resilience. The advantages and disadvantages of each metric are comparatively discussed, and a “how to choose” guideline for metric users is proposed. This study is an introspective investigation of resilience quantification studies, aiming to offer a new perspective to scrutinize those benchmarking metrics.

Explainability in process outcome prediction: Guidelines to obtain interpretable and faithful models

Process outcome prediction pertains to the classification of ongoing cases of (business) processes into a given set of categorical outcomes. This field of research has seen a strong uptake in recent years due to advances in machine and deep learning. Although a recent shift has been made in the field of process outcome prediction to use models from the explainable artificial intelligence field, the evaluation still occurs mainly through predictive performance-based metrics, thus not accounting for the explainability, actionability, and the implications of the results of the models. This paper addresses explainability through the properties interpretability and faithfulness in the field of process outcome prediction. We introduce metrics to analyse these properties along the main dimensions of process data: the event, case, and control flow attributes. This allows for comparing explanations produced by transparent models with explanations generated by (post-hoc) explainability techniques on top of opaque black box models. We utilise thirteen real-life event logs and seven classifiers, encompassing a variety of transparent and non-transparent machine learning and deep learning models, complemented with (post-hoc) explainability techniques. Next, this paper contributes a set of guidelines named X-MOP for obtaining explainable models for outcome prediction, which helps to select the most suitable model by providing insight into how the varying preprocessing, model complexity, and explainability techniques typical in process outcome prediction influence the explainability of the model.

Prediction of Feed Efficiency and Performance-Based Traits in Fish via Integration of Multiple Omics and Clinical Covariates.

Fish aquaculture is a rapidly expanding global industry, set to support growing demands for sources of marine protein. Enhancing feed efficiency (FE) in farmed fish is required to reduce production costs and improve sector sustainability. Recognising that organisms are complex systems whose emerging phenotypes are the product of multiple interacting molecular processes, systems-based approaches are expected to deliver new biological insights into FE and growth performance. Here, we establish 14 diverse layers of multi-omics and clinical covariates to assess their capacities to predict FE and associated performance traits in a fish model (Oncorhynchus tshawytscha) and uncover the influential variables. Inter-omic relatedness between the different layers revealed several significant concordances, particularly between datasets originating from similar material/tissue and between blood indicators and some of the proteomic (liver), metabolomic (liver), and microbiomic layers. Single- and multi-layer random forest (RF) regression models showed that integration of all data layers provide greater FE prediction power than any single-layer model alone. Although FE was among the most challenging of the traits we attempted to predict, the mean accuracy of 40 different FE models in terms of root-mean square errors normalized to percentage was 30.4%, supporting RF as a feature selection tool and approach for complex trait prediction. Major contributions to the integrated FE models were derived from layers of proteomic and metabolomic data, with substantial influence also provided by the lipid composition layer. A correlation matrix of the top 27 variables in the models highlighted FE trait-associations with faecal bacteria (Serratia spp.), palmitic and nervonic acid moieties in whole body lipids, levels of free glycerol in muscle, and N-acetylglutamic acid content in liver. In summary, we identified subsets of molecular characteristics for the assessment of commercially relevant performance-based metrics in farmed Chinook salmon.

The Influence of Anti-LGBTQIA+ Legislation on Graduate Medical Education

The Influence of Anti-LGBTQIA+ Legislation on Graduate Medical Education

Visual search as effortful work.

Tasks that involve more demanding cognitive operations, such as working memory maintenance and rule switching, tend to be perceived as effortful. People will make choices that minimize the need to perform such tasks and will even accept some measure of physical pain in exchange for the ability to avoid them. Nearly all tasks require that people find and extract relevant perceptual information from their environment, but demands of this nature are often ignored in the study of mental effort. Visual search is sometimes described as "difficult" or "easy" on the basis of search slopes or other performance-based metrics, but how such performance differences map onto conceptions of cognitive demand is unclear. In the present study, we examined whether people would be willing to exert physical effort in exchange for the opportunity to minimize the number of items they needed to search through in a visual search task and whether they would be more willing to endure physical effort demands if it resulted in fewer items needing to be searched. Our results are broadly consistent with the idea that the performance of visual search constitutes effortful work that can trade-off with physical effort demands, which has broad implications for theories of visual information processing and practical considerations for professions that tax peoples' ability to search. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

DLBench+: A benchmark for quantitative and qualitative data lake assessment

In the last few years, the concept of data lake has become trendy for data storage and analysis. Thus, several approaches have been proposed to build data lake systems. However, such proposals are difficult to evaluate as there are no commonly shared criteria for comparing data lake systems. Thus, we introduce in this paper DLBench+, a benchmark to evaluate and compare data lake implementations that support textual and/or tabular contents. More concretely, we propose a data model made of both textual and CSV documents, a workload model composed of a set of various tasks, as well as a set of performance-based metrics, all relevant to the context of data lakes. Beyond a purely quantitative assessment, we also propose a methodology to qualitatively evaluate data lake systems through the assessment of user experience. As a proof of concept, we use DLBench+ to evaluate an open source data lake system we developed.

An Analytic Hierarchy Process for Selection of Blockchain-Based Platform for Product Lifecycle Management

Blockchain technology has disrupted traditional business processes and hence gained significant attention and popularity in recent years. Consequently, a number of blockchain-based platforms are available today that offer vast applications across multiple sectors and industries. Implementing these blockchain-based platforms as an alternative to traditional product lifecycle management systems (PLMs) is one of the applications. However, before any platform is adopted, its nature, functionalities, and adaptability need to be clearly defined, evaluated, and verified. In this context, the proposed work explores the available blockchain-based platforms that can be used for the purpose of product lifecycle management. We then apply one of the multi-criteria decision-making techniques, i.e., the analytic hierarchy process (AHP), to select the best possible blockchain-based platform for PLM. As transaction speed, data privacy, and scalability are our prime concerns in PLM, we only considered the permissioned (private) blockchain platforms as available alternatives in the final selection process. Results achieved on the basis of considered criteria show that Hyperledger Fabric is the top-ranked among available alternatives to be used for PLM. Furthermore, as blockchain is a new technology, a clear comparison of the available platforms based on the performance-based metrics and key performance indicators is not completely matured and is still in the development stage. However, our proposed approach can be considered an attempt to create a procedure for evaluating blockchain-based platform implementation in any sector.

Executive function measurement in urban schools: Exploring links between performance-based metrics and teacher ratings.

When compared to research centered on the executive function development of white, middle-class children, relatively little is known about their non-white, low socioeconomic status peers. In an effort to harmonize how executive functions are measured within under-represented contexts, the present study addresses gaps in the evaluation of everyday executive functioning to better understand whether behavior rating scales completed by teachers (BASC2EF - BASC executive function scale, 2nd edition; BASC3EF - BASC executive function scale, 3rd edition) capture distinctions between performance-based measures. This study includes two large samples of older, ethnic minority children from high-poverty backgrounds (Sample 1. N=243; Mage =9.28 years, SDage =0.80; nfemale =125; nAfricanAmerican =216, nLatinAmerican =15, nAsianAmerican =6; Sample 2. N=229; Mage =10.02 years, SDage =1.01; nfemale =120;nAfricanAmerican =132, nLatinAmerican =92, nWhite =3, nPacificIslander =1). Based on structural equation models testing the links between computerized performance-based measures and the teacher rating scales, the results indicate that BASC2EF in its original form might be a good fit for some populations but there is not a strong factor structure for the current high-poverty samples. In addition, post-hoc analyses suggest that only including BASC2EF items also in BASC3EF or using BASC3EF is best practice for high-poverty populations. BASC3EF seems better able to capture different components of performance-driven tasks, whereas BASC2EF captures overall executive functioning better than individual tasks. These findings encourage continued questioning surrounding metrics used to assess everyday executive functions in older children from diverse backgrounds. HIGHLIGHTS: This study explores whether teacher ratings of children's everyday executive functioning (using standardized behavior rating scales) capture distinctions between performance-based measures. Results indicate that BASC2EF teacher rating scale (Karr & Garcia-Barrera, 2017) is not a good representation of everyday executive function behaviors by children from schools in high-poverty communities. The findings suggest that restricting BASC2EF analyses to only items included in BASC3EF (Reynolds & Kamphaus, 2015) or using BASC3EF for high-poverty populations. BASC3EF seems better able to capture the different components of performance-driven tasks, whereas BASC2EF captures overall executive functioning better than individual tasks.

A longitudinal investigation of parental ratings and performance metrics for executive functioning and symptom severity in clinically referred youth with ADHD

There remains a knowledge gap concerning the persistence of attention deficit hyperactivity disorder (ADHD) over the longer term. The current study aimed to investigate the change in parent-rated, and performance-based metrics of executive functioning (EF) and the relationship between these EF metrics and ADHD symptoms in individuals with ADHD from childhood/adolescence to young adulthood. This was done by examining possible improvements in parent-rated EF and performance-based measures of inattention and inhibition over a three-year interval and their relationship to ADHD outcomes in 137 clinically referred youth with ADHD (mean age = 12.4 years, SD = 3.1). Participants’ parents completed the Behavior Rating Inventory of Executive Function (BRIEF) and the Swanson-Nolan-Pelham Scale at baseline and follow-up. Participants completed the Conners’ Continuous Performance Test, Version II (CPT II) at baseline and follow-up. Statistical analyses were performed with Linear Mixed Models. The sex- and age-standardized measures Commission and Hit reaction time (RT) subscales of the CPT II and parent-rated metacognitive, and behavior regulation composites of the BRIEF were largely stable between measuring points. CPT Omissions, Hit RT standard error (reaction time variability), and parent-rated ADHD symptom scores improved slightly. BRIEF composites and reaction time variability were related to ADHD symptoms using longitudinal data. Overall, behavioral aspects of EF, as observed by parents in the home context, appear to play a significant role in the trajectory of childhood ADHD.

Phase-Specific Force And Time Metrics During Vertical Hopping In Chronic Ankle Instability

Single limb hopping tests are used to identify motor-behavioral impairments of the lower limb associated with chronic ankle instability (CAI). Impairments are often presumed by the homogeneity of CAI cohorts with aggregate group comparisons and limited by performance-based metrics. PURPOSE: To compare phase-specific force and time metrics during single limb vertical hopping in participants with and without CAI with single-subject analyses to reveal patient-specific movement adaptations. METHODS: Individuals with CAI (n = 25; 13 M, 12F; age = 24 ± 3 y; height = 168.3 ± 12.9 cm; mass = 72.2 ± 15.2 kg) and matched controls (CON) (n = 25; 13 M, 12F; age = 24 ± 4 y; height = 172.5 ± 6.1 cm; mass = 70.8 ± 9.7 kg) completed 3 trials of 5 consecutive single limb vertical hops on a force platform on the affected and preferred limb, respectively. Eccentric and concentric phases were identified for each vertical hop from ground reaction force data and the middle 3 hops were analyzed. Peak vertical force (PVF), time to peak vertical force (TTP), vertical impulse (VI), and phase time (PT) were obtained for each phase. Groups were compared with an unpaired t-test. The Model Statistic procedure was used to test for CAI individual differences with an aggregate CON mean. RESULTS: Concentric PT (p = .041; CAI: 0.23 ± 0.09 s; CON: 0.19 ± 0.0 s; d = 0.53) and TTP (p = .020; CAI: 0.08 ± 0.19 s; CON: 0.03 ± 0.02; d = 0.71) were longer in CAI. While not significant (p = .066), a moderate effect (d = 0.45) was observed for concentric VI between CAI (3.04 ± 0.56 Ns/kg) and CON (3.40 ± 0.91 Ns/kg). Ten CAI participants exhibited less concentric PVF (CAIrange: 15.16-21.07 N/kg; Mdiff = 4.38 ± 1.99 N/kg; d = 0.80-3.39). Eight CAI participants displayed longer concentric TTP (CAIrange: 0.06 - 0.43 s; Mdiff = 0.11 ± 0.05 s; d = 1.58 - 8.03) and longer PT (CAIrange: 0.22 - 0.56 s; Mdiff = 0.15 ± 0.12 s; d = 0.82 - 4.21) compared to CON. Additionally, 10 CAI participants displayed less eccentric TTP (CAIrange: 0.07 - 0.11 s; Mdiff = 0.04 ± 0.02 s; d = 1.00 - 2.91) than CON. CONCLUSION: Individuals with CAI displayed differences during the propulsion phase of repetitive hopping on the affected limb and suggests difficulty transitioning from eccentric to concentric phases. This could reveal a less efficient transfer of lower limb mechanical output from the affected limb during repetitive vertical hopping.

Clinical mobility metrics estimate and characterize physical activity following lower-limb amputation

BackgroundRegular physical activity following a lower-limb amputation is essential for maintaining health and a high quality of life. Most adults with a lower-limb amputation, however, participate in insufficient daily physical activity, and thus, are predisposed to poor health outcomes. Estimating physical activity after lower-limb amputation via common mobility metrics may aid in clinical decisions regarding treatment prioritization and prosthesis prescription. The objectives of this study were (a) to examine associations between daily physical activity and patient-reported and performance-based mobility metrics among adults with lower-limb amputation, and (b) to determine whether patient-reported and performance-based mobility metrics can distinguish between physical activity status [i.e., sedentary (< 5000 steps/day) or non-sedentary (≥ 5000 steps/day)] of adults with lower-limb amputation.MethodsA cross-sectional study involving 35 adults with a unilateral transtibial (N = 23; 63.0 ± 10.4 years) or transfemoral amputation (N = 12; 58.8 ± 9.5 years) was conducted. Participants completed patient-reported (Prosthesis Evaluation Questionnaire-Mobility Subscale) and performance-based mobility metrics (L-Test, 10-m Walk Test, 6-min Walk Test). Physical activity, i.e., average steps/day, was measured with an accelerometer.ResultsPatient-reported and performance-based mobility metrics were associated with daily physical activity (p < 0.050). Prosthesis Evaluation Questionnaire-Mobility Subscale scores, L-Test time, 10-m Walk Test speed and 6-min Walk Test distance independently explained 11.3%, 31.8%, 37.6% and 30.7% of the total variance in physical activity. Receiver operating characteristic curves revealed patient-reported and performance-based mobility metrics significantly distinguish between physical activity status, i.e., sedentary (< 5000 steps/day) versus non-sedentary (≥ 5000 steps/day). Preliminary cut-points for mobility metrics to classify physical activity status were determined.ConclusionsFollowing a lower-limb amputation, patient-reported and performance-based mobility metrics may estimate daily physical activity, thereby aiding clinical decisions regarding treatment prioritization as well as prosthesis selection.

Comparative assessment of four low voltage fault ride through techniques (LVFRT) for wind energy conversion systems (WECSs)

This paper presents a comparative assessment of four low voltage fault ride through (LVFRT) techniques that alleviate the effects of power imbalance during AC network faults for voltage source converter (VSC)-based wind energy conversion systems (WECSs). The techniques appraised include a software-based coordinated control (CC) technique, commercially available dumping resistor (DR) technique, and two energy storage techniques, namely, superconductive magnetic energy storage (SMES) and supercapacitor energy storage (SCES). The techniques presented are technically viable solutions for alleviating impacts of AC network faults on the WECS. The techniques have previously been assessed by performance-based metrics, whereas this paper aims to form a more comprehensive assessment by expanding the scope from the performance-based comparison to include economic considerations and practical limitations. Based on qualitative review of technically viable designs, this study presents quantitative substantiation with time-domain simulations of symmetrical and asymmetrical AC network faults. The comparative assessment is formulated based on assessing key performance metrics including grid code compliance, electrical and mechanical stress reduction, LVFRT response speed, hardware implementation, system efficiency and investment reduction. The assessment findings suggest that a performance-based study fails to highlight the potential financial and practical barriers that may exist regarding the implementation of the LVFRT solutions especially with energy storage-based techniques. However, the flexibility, benefits and increasing feasibility regarding energy storage systems may make them a preferred option for LVFRT of critical WECSs.

501 - Do PROs Tell the Whole Story? Differential Outcomes Based on Patient-Reported Outcomes (PROs) Versus Performance-Based Metrics (PBM) on Cognition for Patients Receiving Chimeric Antigen Receptor (CAR)-T Cell Therapy

501 - Do PROs Tell the Whole Story? Differential Outcomes Based on Patient-Reported Outcomes (PROs) Versus Performance-Based Metrics (PBM) on Cognition for Patients Receiving Chimeric Antigen Receptor (CAR)-T Cell Therapy