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Introduction: Fontan procedure for single ventricle (SV) is frequently preceded by cardiac catheterization. The impact of pre-Fontan hemodynamics on long-term outcomes is not completely understood. Methods: This is a cohort study of patients undergoing Fontan in the Pediatric Cardiac Care Consortium (PCCC), a US-based registry of congenital heart surgeries. Deaths and transplants were captured through 2019 in the PCCC and by linkage with the National Death Index and the Organ Procurement Transplant Network. The relationship between pre-Fontan hemodynamics and post-Fontan transplant-free survival were evaluated with Kaplan Meier (KM) and Cox regression with adjustment for age at Fontan, sex, era of surgery, Fontan type, and type of systemic ventricle. Results: Between 1986 and 2003, 1498 patients were enrolled in the PCCC and underwent pre-Fontan cardiac catheterization. Table 1 demonstrates the relationship of patient characteristics on the risk of death or transplant after Fontan discharge. After adjustment for other risk factors PVRi (aHR 1.28; 95% CI 1.09 - 1.49) and mPAP (aHR 1.07; 95% CI 1.02- 1.12) were the main factors associated with risk of death or transplant. KM survival curves stratified by PVRi and mPAP tertile depict the loss of transplant-free survival years for the top tertile of mean PAP (>13 mmHg) or PVRi (>2.3 WU m 2 ) (Figures A and B). Conclusions: This study of a large cohort of single ventricle patients demonstrates that abnormal pre-Fontan hemodynamics are associated with increased risk of death or transplant even many years after Fontan procedure. Such data may help to guide therapeutic considerations and monitoring intensity after Fontan completion.

Most females with congenital heart defects (CHD) will reach reproductive age. Our objective was to examine whether presence of disabilities is associated with reproductive health counseling, concerns, and experiences among women with CHD. Methods: We used 2016-2019 population-based data from the Congenital Heart Survey To Recognize Outcomes, Needs, and well-beinG (CH STRONG) among women ages 19 to 38 years with CHD born in Arkansas, Arizona, and Atlanta, Georgia. We examined contraceptive and pregnancy counseling, pregnancy concerns and experiences, and marital history by disability status. Disability was based on six validated questions on vision, hearing, mobility, cognition, self-care, and independent living. Multivariable Poisson regression was used to examine adjusted prevalence ratios (aPR) between reporting ≥ 1 disability and each outcome, adjusted for CHD severity, age, race/ethnicity, place of birth, and insurance type. Results: Of 783 survey respondents with complete data (88% of all respondents), 41.9% were 25-30 years of age, 66.8% were non-Hispanic White, and 41.5% reported ≥1 disability. Women with CHD and disabilities were more likely than women without disabilities to receive clinician counseling on safe contraceptive methods (aPR=1.3) and on avoiding pregnancy because of their CHD (aPR=2.3). They were also more likely to report concern about their ability to have children (aPR=1.2) and having delayed or avoided pregnancy because of their CHD (aPR=2.2). They were less likely to have ever been pregnant (aPR=0.8) or married (aPR=0.7). Associations held across specific disability types and after excluding 71 women with known chromosomal anomalies. Conclusions: Among women with CHD, those with disabilities may be more likely to receive clinician advice to avoid pregnancy and less likely to ever have been pregnant. Evidence-based information may improve services and help women with CHD and disabilities meet their reproductive health goals.

Racial disparities exist in mortality among children with heart conditions, but less is known about disparities in upstream determinants of health. Our objective was to assess differences in economic stability, access to care, and healthcare utilization by race/ethnicity among children with heart conditions. Using caregiver-reported data on 0- to 17-year-olds from the 2016-2019 National Survey of Children’s Health, we calculated prevalence estimates for family economic stability (caregiver educational attainment and work status), child’s healthcare access (insurance type, usual place of care, and problems paying for child’s care), and child’s healthcare utilization (receipt of preventive care, specialty care, and 1 and ≥2 emergency room (ER) visits in the past 12 months) by race/ethnicity (Hispanic, non-Hispanic (NH) Black, and NH White), accounting for complex sampling and weighted to produce national estimates. We used the predicted marginal approach to multivariable logistic regression to generate adjusted prevalence ratios (aPRs) controlling for child’s age and sex. Of 2,596 children with heart conditions, 65.5% were NH White and 52.2% were male. Compared to NH White children, Hispanic and NH Black children, respectively, were 0.9 to 0.8 times less likely to have caregivers who were employed or had more than a high school education. Hispanic and NH Black children were more likely to have public insurance (respective aPRs 1.8, 2.1) and less likely to have a usual place of care (aPRs 0.9, 0.8). Hispanic children were less likely than NH White children to have visited the ER once in the past 12 months, whereas NH Black children were more likely to have visited the ER once (aPR 1.4) and twice or more (aPR 2.5). Among U.S. children with heart conditions, racial/ethnic disparities were seen in indicators of economic stability, access to care, and healthcare utilization.

The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a power network. DED produces a more dynamic supervisory control policy than traditional economic dispatch (T-ED) that reduces overall generation costs. However, in contrast to T-ED, DED is a nonlinear, non-convex optimization problem that is computationally prohibitive to solve. We introduce a machine learning-based operator-theoretic approach for solving the DED problem efficiently. Specifically, we develop a novel discrete-time Koopman Operator (KO) formulation that embeds domain information into the structure of the KO to learn high-fidelity approximations of the generator dynamics. Using the KO approximation, the DED problem can be reformulated as a computationally tractable linear program (abbreviated DED-KO). We demonstrate the high solution quality and computational-time savings of the DED-KO model over the original DED formulation on a 9-bus test system.

In this paper, we provide an introduction to the Koopman Operator (KO) designed to be accessible to those not already familiar with the field. Our aim is to expose domain experts and controls practitioners to the concept and the capabilities the KO provides in the interest of promoting wider KO use; as such, we deliberately focus more on the uses and computational aspects of the KO than on the wealth of analytical results in the literature. Domain experts may then be able to pose new applications-based research questions for the KO community. We begin by defining the KO and describing its key components. Secondly, we discuss computational methods used to calculate the KO in practice. Thirdly, we provide an overview of different uses for the KO and its associated capabilities. Finally, we discuss some open areas of research for future KO work.

Making a power system more operationally resilient to disruption is an important and hard problem. Modeling decisions must include careful consideration of the interaction between system defenders and potential disruptors, the complex operational nature of the system, and the availability and uncertainty of information. Multi-level optimization defender-attacker-defender models are a suitable choice here since they can express such considerations, quantify resilience, and output prescriptive decisions for reaching resilience. In this paper, we review such models employed by power systems applications, with the aim of demonstrating accessibility and applicability of various formulations. In particular, we highlight modeling choices and assumptions, algorithmic details, and where uncertainty is captured or can be injected within a model.

Understanding aviation transportation infrastructure system behavior and coupling with communication networks is essential for securing and restoring functionality against cyber-enabled threats. While significant progress has been made in the past decade on developing infrastructure resilience theories based on network structure and operations, translating and generalizing them to real-world practice has often been challenging due to imperfect data and inapplicability of modeling assumptions. These typically include: 1) stylized network structures without uncertainty, 2) node homogeneity, 3) static criticality measures, and 4) unrealistic cascade models originating from single points of failure. This paper presents the modeling perspectives and approaches that aim to address these theory-to-practice challenges using a well-grounded network-of-networks (NoN) construct. Real-world modeling challenges are identified and a network theory-guided conceptual NoN model is developed that may be operationalized with the U.S. national airspace system airport network and Federal Aviation Administration (FAA) communication network as an application domain.

Secundum atrial septal defect (ASD) is the most common adult congenital heart defect and can present with wide variation in clinical findings. With the intention of preventing morbidity and mortality associated with late presentation of ASD, consensus guidelines have recommended surgical or percutaneous ASD closure in adults with right heart enlargement, with or without symptoms. The aim of the present analysis was to determine if the protective effect of secundum ASD closure in adults could be qualified by pooling data from published studies. A systematic review and meta-analysis were performed by using EMBASE, MEDLINE (through PubMed), and the Cochrane Library databases to assess the effect of secundum ASD percutaneous or surgical closure in unoperated adults ≥18 years of age. Data were pooled across studies with the DerSimonian-Laird random-effects model or a Bayesian meta-analysis model. Between-study heterogeneity was assessed with Cochran’s Q test. Bias assessment was performed with the Newcastle-Ottawa Scale and the Cochrane Risk of Bias Tool, and statistical risk of bias was assessed with Begg and Mazumdar’s test and Egger’s test. A total of 11 nonrandomized studies met the inclusion criteria, contributing 603 patients. Pooled analysis showed a protective effect of ASD closure on New York Heart Association functional class and on right ventricular systolic pressure, volumes, and dimensions. Two additional studies comprising 652 patients were reviewed separately for mortality outcome and primary outcome of interest because they did not meet the inclusion criteria. Those studies showed that ASD closure was associated with a weak protective effect on adjusted mortality rate but no significant impact on atrial arrhythmias in patients >50 years of age. Across all studies, there was significant heterogeneity between studies for nearly all clinical outcomes. The overall body of evidence was limited to observational cohort studies, the limitations of which make for low-strength evidence. Even within the parameters of the included studies, quality of evidence was further diminished by the lack of well-defined clinical outcomes. In conclusion, pooled data analysis on the impact of secundum ASD closure in adults was notably limited because of the lack of randomized controlled trials in patients with only secundum ASD. The few cohort studies in this population demonstrated improvement in functional status and right ventricular size and function as shown by echocardiogram. However, our findings suggest that at the time of this publication, insufficient data are available to determine the impact of ASD repair on mortality rate in adults.

Generating automated cyber resilience policies for real-world settings is a challenging research problem that must account for uncertainties in system state over time and dynamics between attackers and defenders. In addition to understanding attacker and defender motives and tools, and identifying “relevant” system and attack data, it is also critical to develop rigorous mathematical formulations representing the defender's decision-support problem under uncertainty. Game-theoretic approaches involving cyber resource allocation optimization with Markov decision processes (MDP) have been previously proposed in the literature. However, as is the case in strategic card games such as poker, research challenges using game-theoretic approaches for practical cyber defense applications include equilibrium solvability, existence, and possible multiplicity. Moreover, mixed uncertainties associated with player payoffs also need to be accounted for within game settings. This paper proposes an agent-centric approach for cybersecurity decision-support with partial system state observability. Multiple partially observable MDP (POMDP) problems are formulated and solved from a cyber defender's perspective, against a fixed attacker type, using synthetic (notional) system and attack parameters estimated from a Monte Carlo based sampling scheme. The agent-centric problem formulation helps address equilibrium related research challenges and represents a step toward automated and dynamic cyber resilience policy generation and implementation.

Hospital readmissions are increasingly becoming a metric for quality in the current landscape of changing and cost effective medicine. However, no 30-d readmission rates have been established for pediatric cardiac medical patients in the United States. Thus, the objective was to determine 30 d readmission rates and risk factors associated with readmission for pediatric cardiac patients, hypothesizing that pediatric cardiac patients would have significantly higher readmission rates than their general pediatric counterparts.This was a retrospective cohort study.The study took place at a large urban academic children's hospital.The 1124 included patients were discharged from the medical cardiology service and had an unplanned readmission within 30 d during the period of 2012-2014.Admissions, readmissions, diagnoses, demographics, weights, medications, procedures, length of stay, were all measured.There were 1993 visits and 408 (20.5%) 30-d readmissions in our study. Among the 1124 patients, 219 (19.5%) had at least one 30-d readmission. Patient factors associated with increased likelihood of 30-d readmission were younger age (median: 197.5 vs 1365.5 d, P .0001), lower discharge weight (6.2 v 14.5 kg, P .0001) and greater number of diagnoses (P .0001). The encounter factor associated with a 30-d readmission was longer length of stay (4 vs 2 d, P 0.0001). Factors associated with decreased readmissions were having had an electrophysiology procedure during their stay, taking an angiotensin converting enzyme inhibitor/angiotensin receptor blocker or taking an antibiotic.Readmissions within 30 d among pediatric cardiology patients are common. The most common factors associated with readmissions are not likely to be modifiable but may serve as important prognostic indicators and as a basis for counseling.

Cyber-system security on a continual basis against a multitude of adverse events is a challenging undertaking. Cybersystem administrators operating with limited protective resources need to account for uncertainties associated with system behavior and types of attackers targeting a system. These uncertainties may arise due to inherent randomness or incomplete knowledge about system behavior and events affecting the system. As a result, uncertainty quantification of attacker payoff functions within stochastic cybersecurity games is a critical area of research interest. This study focuses on operationalizing a probabilistic framework for quantifying attacker payoffs, within a notional case study, through: (1) representation of uncertain attacker and system-related modeling variables as probability distributions and mathematical intervals, and (2) exploration of uncertainty propagation techniques including two-phase Monte Carlo sampling and probability bounds analysis. Enhanced uncertainty representations of payoffs may contribute to further understanding of dynamics between cyber attackers and defenders and advance the state-of-the-art in proactive cyber-system defense and strategic decision-making.

Introduction: While children with congenital heart disease (CHD) are known to have neurodevelopmental challenges, how these challenges translate to school performance is unknown. The purpose of our study was to compare the academic achievement of children with CHD to that of children without known birth defects. Hypothesis: Children with CHD would have lower standardized test performance scores and greater need for grade retention than their peers without birth defects. Methods: We performed a retrospective cohort study comparing educational outcomes for children born 1998-2003 with CHD, identified from the North Carolina (NC) Birth Defects Registry, vs. those without a known birth defect, randomly sampled from NC birth certificates. All children were linked to 3rd grade public school records from the NC Department of Public Instruction through 2012. We performed logistic regression to compare our outcomes of interest: a) meeting standards on the reading and math portions of 3rd grade End of Grade Testing, and b) 3rd grade retention. Models were adjusted for maternal education, public pre-K enrollment, and race/ethnicity. Results: Of the 5624 subjects with CHD and 10,832 with no birth defect, 51% and 60% were linked, respectively, to 3rd grade standard End of Grade testing records. Compared to children without a birth defect, those with CHD were more likely not to meet proficiency standards in reading (OR 1.4, 95% CI 1.3-1.6), math (OR 1.2, 95% CI 1.1-1.4), or both (OR 1.5, 95% CI 1.3-1.7). (Figure) Similarly, children with CHD were more likely to be retained in 3rd grade (2.8% vs. 1.9%, OR 1.4, 95% CI 1.1-1.9). Conclusions: Children with CHD have poorer educational achievement as compared to their peers without birth defects. History of CHD should be considered an important factor in determining a student’s need for specialized education services.

Introduction: Screening for critical congenital heart disease (CCHD) using pulse oximetry is performed with various algorithms in the United States, with none of these based on robust data, including the one endorsed by the AHA and other organizations. Hypothesis: Existing algorithms will have differing results for CCHD screening, and the test characteristics of these algorithms can be improved through modifications. Methods: After collecting de-identified, patient-level pulse oximetry values from existing national and international screening programs, we compared the commonly used algorithms in the US: the American Academy of Pediatrics (AAP) algorithm (endorsed by the AHA), the New Jersey (NJ) algorithm (slight modification of the AAP algorithm), and the Tennessee (TN) algorithm (screening first on the foot only). We then considered alternate algorithms by modifying the pulse oximetry values that would be considered a pass, fail, or retest result in the existing algorithms. We compared the algorithms according to sensitivity (Se), false positive rate (FP), and area under the curve (AUC). Results: There were 75,748 screenings, with 57 true positives. Performance characteristics of the 3 common algorithms are summarized in the Table. The NJ algorithm had the greatest Se but also the highest FP, and the TN algorithm had the lowest Se but also the lowest FP. Modifications of these algorithms yielded 2632 potential algorithms with Se ranging from 28% to 91%, FP from 0.05% to 60%, and AUC from 0.64 to 0.82. Of these, 224 algorithms met our optimal algorithm criteria of Se >50%, FP 0.75. Conclusions: Current algorithms for CCHD screening vary in their test performance characteristics, and there are opportunities to modify these algorithms to improve test performance. Before identifying an optimal algorithm, further work is needed to collect more data (including more robust data on false negatives) and to compare the cost and ease of use of potential algorithms.

Introduction: Despite medical and surgical advances over the past few decades, mortality for infants with single ventricle congenital heart disease remains as high as 8-12% during the interstage period, the time between discharge after the Norwood procedure and before the stage II palliation. The objective of our study was to determine the effect of digoxin use on interstage mortality in infants with single ventricle congenital heart disease. Hypothesis: We hypothesized that digoxin would be associated with lower interstage mortality. Methods: We conducted a retrospective cohort study using the Pediatric Heart Network Single Ventricle Reconstruction Trial public use dataset, which includes data on infants with single right ventricle congenital heart disease randomized to receive either a Blalock-Taussig shunt or right ventricle-to-pulmonary artery shunt during the Norwood procedure at 15 institutions in North America from 2005-2008. Parametric survival models were used to compare the risk of interstage mortality between those discharged to home on digoxin vs. those discharged to home not on digoxin, adjusting for center volume, ascending aorta diameter, shunt type, and socioeconomic status. Further comparisons were made to compare the number of other adverse events in the two groups. Results: Of the 330 infants eligible for this study, 102 (31%) were discharged home on digoxin. Interstage mortality for those not on digoxin was 12.3%, compared to 2.9% among those on digoxin (Figure), with a number needed to treat of 11 patients to prevent one death. The adjusted hazard ratio was 3.5 (95%CI 1.1-11.7, p=0.04). There were no differences in complications between the two groups during the interstage period. Conclusions: Digoxin use in infants with single ventricle congenital heart disease is associated with significantly reduced interstage mortality and should be considered for all such infants unless otherwise contraindicated.

Representation and propagation of uncertainty in cyber attacker payoffs is a key aspect of security games. Past research has primarily focused on representing the defender's beliefs about attacker payoffs as point utility estimates. More recently, within the physical security domain, attacker payoff uncertainties have been represented as Uniform and Gaussian probability distributions, and intervals. Within cyber-settings, continuous probability distributions may still be appropriate for addressing statistical (aleatory) uncertainties where the defender may assume that the attacker's payoffs differ over time. However, systematic (epistemic) uncertainties may exist, where the defender may not have sufficient knowledge or there is insufficient information about the attacker's payoff generation mechanism. Such epistemic uncertainties are more suitably represented as probability boxes with intervals. In this study, we explore the mathematical treatment of such mixed payoff uncertainties.

Background: Tachyarrhythmias are an important contributor to morbidity following the Norwood procedure for single ventricle congenital heart disease. The purpose of this study was to determine what demographic, preoperative, or operative factors may be associated with the development of postoperative tachyarrhythmias in this population. Methods: We performed a retrospective analysis of data collected prospectively through the multicenter Pediatric Heart Network Single Ventricle Reconstruction Trial for infants undergoing a Norwood procedure in 2005-2008. Our primary outcome of interest was any documented tachyarrhythmia requiring treatment or intervention during the inpatient postoperative stay. Subjects with a documented preoperative tachyarrhythmia (n=15) were excluded. After performing univariate chi-square analyses on a variety of candidate factors, we conducted multivariate stepwise logistic regression, including spline terms for nonlinearly associated variables, to calculate the adjusted odds ratios for the final variables. Results: Of 529 subjects, 108 (20%) had at least one documented tachyarrhythmia, with 11 having more than one. Tachyarrhythmias included: 77 supraventricular tachycardia, 23 junctional ectopic tachycardia, 10 atrial flutter, 7 ventricular tachycardia, and 2 atrial fibrillation. In the final multivariate model (c-statistic=0.65), significant factors associated with arrhythmia included receiving a modified Blalock-Taussig shunt, use of ultrafiltration, and age. (Table) Conclusions: Tachyarrhythmias are common following the Norwood procedure and are associated with the modifiable risk factors of shunt type and use of ultrafiltration. In addition, when surgery is performed between 8 and 20 days of age, older age is associated with a decreasing risk for tachyarrhythmia.

We present an algorithm to maintain the connected components of a graph that arrives as an infinite stream of edges. We formalize the algorithm on X-stream, a new parallel theoretical computational model for infinite streams. Connectivity-related queries, including component spanning trees, are supported with some latency, returning the state of the graph at the time of the query. Because an infinite stream may eventually exceed the storage limits of any number of finite-memory processors, we assume an aging command or daemon where "uninteresting" edges are removed when the system nears capacity. Following an aging command the system will block queries until its data structures are repaired, but edges will continue to be accepted from the stream, never dropped. The algorithm will not fail unless a model-specific constant fraction of the aggregate memory across all processors is full. In normal operation, it will not fail unless aggregate memory is completely full.Unlike previous theoretical streaming models designed for finite graphs that assume a single shared memory machine or require arbitrary-size intemediate files, X-stream distributes a graph over a ring network of finite-memory processors. Though the model is synchronous and reminiscent of systolic algorithms, our implementation uses an asynchronous message-passing system. We argue the correctness of our X-stream connected components algorithm, and give preliminary experimental results on synthetic and real graph streams.

Many adults with transposition of the great arteries have an anatomic right ventricle functioning as the systemic ventricle and are known to develop congestive heart failure, premature cardiac death, and need for cardiac transplantation. Predictors of poor clinical outcome and functional status in patients with left ventricular failure do not always apply to these patients. We aimed to identify predictors of poor functional status in those patients with a systemic right ventricle.We performed a prospective study of 51 adults with transposition of the great arteries and systemic right ventricles. Demographic, clinical, laboratory, and imaging data were collected, and patients completed a Minnesota Living with Heart Failure Questionnaire (MLHFQ). Comparisons were made between those patients with d-type transposition of the great arteries (dTGA) who have undergone prior atrial switch and those with congenitally corrected transposition (ccTGA). A correlation analysis was performed to identify predictors of poor functional status, as determined by a 6-minute walk distance test.Median age was 30 years (range 19-65). Median B-type natriuretic peptide was 48 pg/mL (range 16-406). There were 27 patients (53%) with moderate-severe right ventricular dysfunction and 10 (20%) with moderate-severe tricuspid valve regurgitation. The median MLHFQ score was 9 (range 0-78) and 6-minute walk test was 510 m (range 231-703). Forty-one patients had a diagnosis of dTGA atrial switch and 11 patients had ccTGA. Patients with ccTGA were significantly older (40 vs. 28 years, P =.004) and had more tricuspid valve regurgitation (P =.02). Despite this, their MLHFQ scores were significantly lower (2.5 vs. 17, P =.04) and they walked further (635 vs. 504 m, P =.02). Predictors of a short 6-minute walk distance included short stature (P =.009) and dTGA (P =.002). The patient's self-assessment of poor health, as measured by an increased New York Heart Association class (P =.003) and a decreased MLHFQ score (P.0001) also correlated. B-type natriuretic peptide levels, right ventricular dysfunction, severity of tricuspid valve regurgitation, need for pacemaker, and clinical signs of heart failure did not correlate with exercise tolerance.Traditional parameters used to predict outcomes in patients with left ventricular failure are not predictive in patients with a systemic right ventricle. Instead, patient's self-assessment of functional status did correlate with objective functional status.

Introduction: Pulse oximetry screening for critical congenital heart disease (CCHD: hypoplastic left heart syndrome, transposition of the great arteries, tricuspid atresia, truncus arteriosus, tetralogy of Fallot, total anomalous pulmonary venous return, and pulmonary atresia) was added to the Recommended Uniform Screening Panel for newborns in 2011. However, population-based data on trends in survival and prognostic factors for infants with CCHD are limited. Methods: We performed a retrospective cohort study of infants born with structural congenital heart disease (CHD) between 1979 and 2005 and identified through the Metropolitan Atlanta Congenital Defects Program. Survival was determined via linkage with state vital records and the National Death Index. We estimated Kaplan-Meier survival probabilities for CCHD by birth era and timing of diagnosis, and we used proportional hazards models to assess several prognostic factors, including birth era, timing of diagnosis, maternal age, birth weight, race/ethnicity, sex, socioeconomic status, and presence of non-cardiac defects. Results: Overall 1-year survival was 65.2% for those with CCHD (n=1204) vs. 89.9% for those with other forms of CHD (n=5761; p Conclusions: One-year survival for infants with CCHD has been improving over time, yet mortality remains high. Identification of prognostic factors for CCHD may aid future evaluations of the impact of pulse oximetry screening on survival from CCHD.

The volume of streaming data for cyber analysis is increasing at a rate much greater than any organization's ability to hire human analysts. As a preliminary step to automating significant portions of analysis workload, we consider the problem of modeling cyber data. Since the latter tends to be relational in nature, graphs are a natural abstraction. This motivates future research into efficient algorithms for fundamental graph problems in a high-volume, streaming environment. Algorithms designed using current theoretical models for streaming graph algorithms are not directly suitable for operations. In this talk, we propose a new streaming model that can be implemented on a parallel system with extremely simple topology. Our model assumes an infinite stream which must be analyzed using finite resources. We illustrate the associated challenges by giving an algorithm for maintaining and querying the connected components of a graph in which edges may be expired periodically.