Prior Work Research Articles

Parahippocampal neurons encode task-relevant information for goal-directed navigation.

A behavioral strategy crucial to survival is directed navigation to a goal, such as a food or home location. One potential neural substrate for supporting goal-directed navigation is the parahippocampus, which contains neurons that represent an animal's position, orientation, and movement through the world, and that change their firing activity to encode behaviorally relevant variables such as reward. However, little prior work on the parahippocampus has considered how neurons encode variables during goal-directed navigation in environments that dynamically change. Here, we recorded single units from rat parahippocampal cortex while subjects performed a goal-directed task. The maze dynamically changed goal-locations via a visual cue on a trial-to-trial basis, requiring subjects to use cue-location associations to receive reward. We observed a mismatch-like signal, with elevated neural activity on incorrect trials, leading to rate-remapping. The strength of this remapping correlated with task performance. Recordings during open-field foraging allowed us to functionally define navigational coding for a subset of the neurons recorded in the maze. This approach revealed that head-direction coding units remapped more than other functional-defined units. Taken together, this work thus raises the possibility that during goal-directed navigation, parahippocampal neurons encode error information reflective of an animal's behavioral performance.

Memory Systems, the Epistemic Arrow of Time, and the Second Law.

The epistemic arrow of time is the fact that our knowledge of the past seems to be both of a different kind and more detailed than our knowledge of the future. Just like with the other arrows of time, it has often been speculated that the epistemic arrow arises due to the second law of thermodynamics. In this paper, we investigate the epistemic arrow of time using a fully formal framework. We begin by defining a memory system as any physical system whose present state can provide information about the state of the external world at some time other than the present. We then identify two types of memory systems in our universe, along with an important special case of the first type, which we distinguish as a third type of memory system. We show that two of these types of memory systems are time-symmetric, able to provide knowledge about both the past and the future. However, the third type of memory systems exploits the second law of thermodynamics, at least in all of its instances in our universe that we are aware of. The result is that in our universe, this type of memory system only ever provides information about the past. We also argue that human memory is of this third type, completing the argument. We end by scrutinizing the basis of the second law itself. This uncovers a previously unappreciated formal problem for common arguments that try to derive the second law from the "Past Hypothesis", i.e., from the claim that the very early universe was in a state of extremely low entropy. Our analysis is indebted to prior work by one of us but expands and improves upon this work in several respects.

Accompanying study of the development process towards a smart city strategy-with a particular focus on social change

The development of a smart city strategy will take place in 73 selected cities in Germany as the result of a participation competition. The systematics of the requirements of the state as a funding provider and the approach of local actors will be examined in more detail in this study. The Objectives of the work are a supervised process of a model facility, on the basis of which observations for a process model are to be derived. This model is intended to enable various aspects as a starting point for non-subsidized institutions as well. A particular focus lies on the area of social change, which is difficult to quantify, in terms of social aspects. The Prior work shows that there are three different dimensions of strategy elements to be decided on in order to start subsidy-compliant design projects. On one hand, a team must be required that takes care of the smart city projects next to their regular tasks. Their composition and purpose in doing represent the first dimension. Secondly, the question of setting targets and the associated monitoring of results must be determined. Finally, the path of involving citizens and companies lead to the social legitimacy of the project team. The approach is based on a semi-structured participant observation by the authors. Qualitative insights into practical doing and abstracted findings based on an example case serve as practical recommendations for further and thus complementary consolidation and expansion of the findings. The first Results show that defining key performance indicators and objective key results is quite a new system of performance measurement for public institutions. In particular, the social aspects of living together in cities are difficult to put into key figures due to the diverse composition of society. Local differences with incentives and channels in different forms need to be translated into general insights. The Implications include enabling government leaders to initiate and manage transformative approaches to the digitization of public space. Social change as a field of action for the design of digital solutions will be opened up and brought closer by means of best-practice implementations. The value of the work lies in getting an example of steps towards a planning basis for comprehensive smart city agendas. Furthermore, management tools for digital projects are addressed and methods for the participation of service recipients of public authorities are presented. Through the classified experiences of the prime example, challenges, opportunities, risks but also weaknesses of the path to a smart city emerge, which can be a point of orientation for non-subsidized cities in their own roadmap.

Inflammasome modulation with P2X7 inhibitor A438079-loaded dressings for diabetic wound healing.

The inflammasome is a multiprotein complex critical for the innate immune response to injury. Inflammasome activation initiates healthy wound healing, but comorbidities with poor healing, including diabetes, exhibit pathologic, sustained activation with delayed resolution that prevents healing progression. In prior work, we reported the allosteric P2X7 antagonist A438079 inhibits extracellular ATP-evoked NLRP3 signaling by preventing ion flux, mitochondrial reactive oxygen species generation, NLRP3 assembly, mature IL-1β release, and pyroptosis. However, the short half-life in vivo limits clinical translation of this promising molecule. Here, we develop a controlled release scaffold to deliver A438079 as an inflammasome-modulating wound dressing for applications in poorly healing wounds. We fabricated and characterized tunable thickness, long-lasting silk fibroin dressings and evaluated A438079 loading and release kinetics. We characterized A438079-loaded silk dressings in vitro by measuring IL-1β release and inflammasome assembly by perinuclear ASC speck formation. We further evaluated the performance of A438079-loaded silk dressings in a full-thickness model of wound healing in genetically diabetic mice and observed acceleration of wound closure by 10 days post-wounding with reduced levels of IL-1β at the wound edge. This work provides a proof-of-principle for translating pharmacologic inhibition of ATP-induced inflammation in diabetic wounds and represents a novel approach to therapeutically targeting a dysregulated mechanism in diabetic wound impairment.

No evidence for relationship between paternal post-partum depressive symptoms and testosterone or cortisol in first-time fathers.

Male life history strategies are regulated by the neuroendocrine system. Testosterone (T) and cortisol regulate male behaviors including parenting and facilitate managing tradeoffs at key transitions in development such as first-time fatherhood. Both hormones demonstrate marked fluctuations in the postnatal period, and this presents an opportunity to investigate the role of T and cortisol in postpartum depressive symptoms-comparably less studied in fathers than in mothers in the evolutionary literature. Prior work on depressive symptoms has yet to integrate insights from the "dual hormone hypothesis (DHH)" which has focused on how T and cortisol interact to jointly regulate traits associated with dominance and status-seeking (i.e., mating effort) but has yet to be included in models of parenting effort. In this research, we use secondary data to investigate the relationship between DHH and traits ostensibly opposed to status seeking (i.e., depressive symptoms). First-time fathers (n = 193) provided morning saliva samples 10 months following parturition and reported on the presence of depressive symptoms (BDI-II). Responses were decomposed into three factors: cognitive, affective, and somatic. Using hybrid latent variable structural equation modeling, we did not find evidence that T predicted variability in cognitive, affective, or somatic depressive symptom factors. We found a null effect for cortisol as well. Finally, we could not find evidence that the DHH variable (T × cortisol interaction) predicted any variability in cognitive, affective, or somatic depressive symptoms. While we did not find evidence to support our hypotheses using a secondary data set, this study contributes to research on the neuroendocrinology of depression in fathers. Discussion focuses on the limitations of sample demographics, timing of saliva and self-report collection, and the lack of extant theory specific to paternal postpartum depression.

Healthy aging alters the oscillatory dynamics and fronto-parietal connectivity serving fluid intelligence.

Fluid intelligence (Gf) involves logical reasoning and novel problem-solving abilities. Often, abstract reasoning tasks like Raven's progressive matrices are used to assess Gf. Prior work has shown an age-related decline in fluid intelligence capabilities, and although many studies have sought to identify the underlying mechanisms, our understanding of the critical brain regions and dynamics remains largely incomplete. In this study, we utilized magnetoencephalography (MEG) to investigate 78 individuals, ages 20-65 years, as they completed an abstract reasoning task. MEG data was co-registered with structural MRI data, transformed into the time-frequency domain, and the resulting neural oscillations were imaged using a beamformer. We found worsening behavioral performance with age, including prolonged reaction times and reduced accuracy. MEG analyses indicated robust oscillations in the theta, alpha/beta, and gamma range during the task. Whole brain correlation analyses with age revealed relationships in the theta and alpha/beta frequency bands, such that theta oscillations became stronger with increasing age in a right prefrontal region and alpha/beta oscillations became stronger with increasing age in parietal and right motor cortices. Follow-up connectivity analyses revealed increasing parieto-frontal connectivity with increasing age in the alpha/beta frequency range. Importantly, our findings are consistent with the parieto-frontal integration theory of intelligence (P-FIT). These results further suggest that as people age, there may be alterations in neural responses that are spectrally specific, such that older people exhibit stronger alpha/beta oscillations across the parieto-frontal network during abstract reasoning tasks.

Calibration of agent based models for monophasic and biphasic tumour growth using approximate Bayesian computation

Agent-based models (ABMs) are readily used to capture the stochasticity in tumour evolution; however, these models are often challenging to validate with experimental measurements due to model complexity. The Voronoi cell-based model (VCBM) is an off-lattice agent-based model that captures individual cell shapes using a Voronoi tessellation and mimics the evolution of cancer cell proliferation and movement. Evidence suggests tumours can exhibit biphasic growth in vivo. To account for this phenomena, we extend the VCBM to capture the existence of two distinct growth phases. Prior work primarily focused on point estimation for the parameters without consideration of estimating uncertainty. In this paper, approximate Bayesian computation is employed to calibrate the model to in vivo measurements of breast, ovarian and pancreatic cancer. Our approach involves estimating the distribution of parameters that govern cancer cell proliferation and recovering outputs that match the experimental data. Our results show that the VCBM, and its biphasic extension, provides insight into tumour growth and quantifies uncertainty in the switching time between the two phases of the biphasic growth model. We find this approach enables precise estimates for the time taken for a daughter cell to become a mature cell. This allows us to propose future refinements to the model to improve accuracy, whilst also making conclusions about the differences in cancer cell characteristics.

Shades of support: An empirical assessment of D&I policy support in organizations

AbstractIn this research, we aim to develop a better understanding of the different ways in which employees can advance or resist the diversity and inclusion (D&I) policies implemented by their organization. To this end, we complement prior work by distinguishing between employees' attitudinal and behavioral opposition versus support for D&I policies. We combine these to distinguish different combinations of attitudinal and behavioral responses that characterize specific groups of employees, which we label opponents, bystanders, reluctants, and champions. In a large‐scale survey study conducted among employees from seven organizations located in the Netherlands (n = 2913), we find empirical support for the validity of this taxonomy and its value in understanding the likelihood that employees advance or resist D&I policies. Furthermore, we find more convergence between attitudinal and behavioral support when employees perceive a more positive climate for inclusion. Together, these results advance existing scholarly work by providing both a theoretical account of and empirical evidence for the different ways in which D&I policies may find support or resistance from employees. In addition, our work offer practitioners a practical tool to examine the likelihood that D&I policies meet support or opposition from their employees and therefore enables them to design and implement more effective D&I interventions.

Auditory Category Learning in Children With Dyslexia.

Developmental dyslexia is proposed to involve selective procedural memory deficits with intact declarative memory. Recent research in the domain of category learning has demonstrated that adults with dyslexia have selective deficits in Information-Integration (II) category learning that is proposed to rely on procedural learning mechanisms and unaffected Rule-Based (RB) category learning that is proposed to rely on declarative, hypothesis testing mechanisms. Importantly, learning mechanisms also change across development, with distinct developmental trajectories in both procedural and declarative learning mechanisms. It is unclear how dyslexia in childhood should influence auditory category learning, a critical skill for speech perception and reading development. We examined auditory category learning performance and strategies in 7- to 12-year-old children with dyslexia (n = 25; nine females, 16 males) and typically developing controls (n = 25; 13 females, 12 males). Participants learned nonspeech auditory categories of spectrotemporal ripples that could be optimally learned with either RB selective attention to the temporal modulation dimension or procedural integration of information across spectral and temporal dimensions. We statistically compared performance using mixed-model analyses of variance and identified strategies using decision-bound computational models. We found that children with dyslexia have an apparent selective RB category learning deficit, rather than a selective II learning deficit observed in prior work in adults with dyslexia. These results suggest that the important skill of auditory category learning is impacted in children with dyslexia and throughout development, individuals with dyslexia may develop compensatory strategies that preserve declarative learning while developing difficulties in procedural learning. https://doi.org/10.23641/asha.25148519.

Blood Pressure Variability and Plasma Alzheimer's Disease Biomarkers in the SPRINT Trial.

Recent observational studies suggest higher blood pressure (BP) variability (BPV) is associated with Alzheimer's disease (AD) biomarkers amyloid-beta (Aβ) and tau. Less is known about relationships in interventional cohorts with strictly controlled mean BP levels. Investigate the longitudinal relationship between BPV and change in plasma AD biomarkers under standard versus intensive BP treatment. In this post hoc analysis of the SPRINT trial, 457 participants (n = 206 in standard group, n = 251 in intensive group) underwent repeated BP measurement between baseline and 12-months follow-up, and venipuncture at baseline and median (IQR) 3.5 (3.0-4.0) years later to determine plasma AD biomarkers total tau and Aβ1-42:Aβ1-40 ratio. BPV was calculated as tertiles of variability independent of mean. Linear mixed models investigated the effect of BPV×time on AD biomarker levels. Higher BPV was associated with increased levels of total tau in the standard group (β [95% CI] 1st versus 3rd tertiles of BPV: 0.21 [0.02, 0.41], p = 0.035), but not in the intensive group (β [95% CI] 1st versus 3rd tertiles of BPV: -0.02 [-0.19, 0.16], p = 0.843). BPV was not associated with Aβ 1-42:Aβ 1-40 ratio in either group. Mean BP was not associated with biomarkers. Higher BPV was associated with increased plasma total tau under standard BP treatment. Findings add new evidence to prior observational work linking BPV to AD pathophysiology and suggest that, despite strict control of mean BP, BPV remains a risk for pathophysiological change underlying risk for AD.

Cleaning up while Changing Gears: The Role of Battery Design, Fossil Fuel Power Plants, and Vehicle Policy for Reducing Emissions in the Transition to Electric Vehicles.

Plug-in electric vehicles (PEVs) can reduce air emissions when charged with clean power, but prior work estimated that in 2010, PEVs produced 2 to 3 times the consequential air emission externalities of gasoline vehicles in PJM (the largest US regional transmission operator, serving 65 million people) due largely to increased generation from coal-fired power plants to charge the vehicles. We investigate how this situation has changed since 2010, where we are now, and what the largest levers are for reducing PEV consequential life cycle emission externalities in the near future. We estimate that PEV emission externalities have dropped by 17% to 18% in PJM as natural gas replaced coal, but they will remain comparable to gasoline vehicle externalities in base case trajectories through at least 2035. Increased wind and solar power capacity is critical to achieving deep decarbonization in the long run, but through 2035 we estimate that it will primarily shift which fossil generators operate on the margin at times when PEVs charge and can even increase consequential PEV charging emissions in the near term. We find that the largest levers for reducing PEV emissions over the next decade are (1) shifting away from nickel-based batteries to lithium iron phosphate, (2) reducing emissions from fossil generators, and (3) revising vehicle fleet emission standards. While our numerical estimates are regionally specific, key findings apply to most power systems today, in which renewable generators typically produce as much output as possible, regardless of the load, while dispatchable fossil fuel generators respond to the changes in load.

Advancing Human Motion Recognition with SkeletonCLIP++: Weighted Video Feature Integration and Enhanced Contrastive Sample Discrimination.

This paper introduces 'SkeletonCLIP++', an extension of our prior work in human action recognition, emphasizing the use of semantic information beyond traditional label-based methods. The innovation, 'Weighted Frame Integration' (WFI), shifts video feature computation from averaging to a weighted frame approach, enabling a more nuanced representation of human movements in line with semantic relevance. Another key development, 'Contrastive Sample Identification' (CSI), introduces a novel discriminative task within the model. This task involves identifying the most similar negative sample among positive ones, enhancing the model's ability to distinguish between closely related actions. Incorporating the 'BERT Text Encoder Integration' (BTEI) leverages the pre-trained BERT model as our text encoder to refine the model's performance. Empirical evaluations on HMDB-51, UCF-101, and NTU RGB+D 60 datasets illustrate positive improvements, especially in smaller datasets. 'SkeletonCLIP++' thus offers a refined approach to human action recognition, ensuring semantic integrity and detailed differentiation in video data analysis.

Differentially Private Guarantees for Analytics and Machine Learning on Graphs: A Survey of Results

We study the applications of differential privacy (DP) in the context of graph-structured data and discuss the formulations of DP applicable to the publication of graphs and their associated statistics as well as machine learning on graph-based data, including graph neural networks (GNNs). Interpreting DP guarantees in the context of graph-structured data can be challenging, as individual data points are interconnected (often non-linearly or sparsely). This connectivity complicates the computation of individual privacy loss in differentially private learning. The problem is exacerbated by an absence of a single, well-established formulation of DP in graph settings. This issue extends to the domain of GNNs, rendering private machine learning on graph-structured data a challenging task. A lack of prior systematisation work motivated us to study graph-based learning from a privacy perspective. In this work, we systematise different formulations of DP on graphs, discuss challenges and promising applications, including the GNN domain. We compare and separate works into graph analytics tasks and graph learning tasks with GNNs. We conclude our work with a discussion of open questions and potential directions for further research in this area.

Numerical Composition of Differential Privacy

We give a fast algorithm to optimally compose privacy guarantees of differentially private (DP) algorithms to arbitrary accuracy. Our method is based on the notion of \emph{privacy loss random variables} to quantify the privacy loss of DP algorithms.The running time and memory needed for our algorithm to approximate the privacy curve of a DP algorithm composed with itself $k$ times is $\tilde{O}(\sqrt{k})$. This improves over the best prior method by Koskela et al. (2021) which requires $\tilde{\Omega}(k^{1.5})$ running time. We demonstrate the utility of our algorithm by accurately computing the privacy loss of DP-SGD algorithm of Abadi et al. (2016) and showing that our algorithm speeds up the privacy computations by a few orders of magnitude compared to prior work, while maintaining similar accuracy.

Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism

Sparse histogram methods can be useful for returning differentially private counts of items in large or infinite histograms, large group-by queries, and more generally, releasing a set of statistics with sufficient item counts. We consider the Gaussian version of the sparse histogram mechanism and study the exact epsilon, delta differential privacy guarantees satisfied by this mechanism. We compare these exact epsilon, delta parameters to the simpler overestimates used in prior work to quantify the impact of their looser privacy bounds.

Line- and sex-dependent effects of juvenile stress on contextual fear- and anxiety-related behavior in high- and low-alcohol-preferring mouse lines

Juvenile stress (JS) is a known risk factor for the development of alcohol use disorder (AUD) and post-traumatic stress disorder (PTSD), both of which are frequently co-morbid. Data suggest there may be common, genetically-influenced biological responses to stress that contribute to the development of both AUD and PTSD. The present study investigated the impact of JS on contextual fear learning and extinction, as well as corticosterone (CORT) responses before and after JS, before and after contextual fear conditioning (CFC), and after fear extinction in male and female high-alcohol-preferring (HAP2) and low-alcohol-preferring (LAP2) mouse lines. We also measured unconditioned anxiety-related behavior in the light-dark-transition test before CFC. HAP2 and LAP2 mice did not differ in fear acquisition, but HAP2 mice showed faster fear extinction compared to LAP2 mice. No effects of JS were seen in HAP2 mice, whereas in LAP2 mice, JS reduced fear acquisition in males and facilitated fear extinction in females. Females showed greater fear-related behavior relative to males, regardless of subgroup. HAP2 males demonstrated more anxiolytic-like responses than LAP2 males and LAP2 females demonstrated more anxiolytic-like responses than LAP2 males in the light-dark transition test. HAP2 and LAP2 mice did not differ in CORT during the juvenile stage; however, adult LAP2 mice showed greater CORT levels than HAP2 mice at baseline and after CFC and extinction testing. These findings build upon prior work in these unique mouse lines that differ in genetic propensity toward alcohol preference and provide new information regarding contextual fear learning and extinction mechanisms theorized to contribute to co-morbid AUD and PTSD.

The H-poor nature of incompletely melted planetesimals: The view from acapulcoites and lodranites

The abundance of H in planetary building blocks is of fundamental importance for constraining the evolution of the terrestrial planets. It is commonly assumed that chondrites are the principal sources of Earth’s H; however, recent studies have suggested that primitive achondrites and achondrites may retain a small complement of H. There are few constraints on the H budgets of primitive achondrites, which represent the transition from unmelted to melted planetesimals, but prior work suggests that bulk parent body H contents are several orders of magnitude lower than typical chondritic values. Therefore, to provide further constraints on H retention during the transition from unmelted to melted planetesimals, we have measured the H contents of olivine, orthopyroxene, clinopyroxene, and plagioclase from a suite of acapulcoite-lodranite clan meteorites. Acapulcoite-lodranite clan meteorites represent the “prototypical” primitive achondrite parent body and have bulk major element compositions more akin to the Earth than previously studied primitive achondrites (e.g., the ureilites). We find that the H2O contents of olivine (∼5–12 µg/g H2O), orthopyroxene (∼3–10 µg/g H2O), and clinopyroxene (∼5–8 µg/g H2O) are broadly similar, while plagioclase (∼2.5–5 µg/g H2O) tends to be offset to lower values. Using a simple, single-stage batch-melting model, we calculate a preferred maximum acapulcoite-lodranite parent body H2O content of 38 µg/g, which is similar to other estimates for primitive achondritic and achondritic parent bodies. Furthermore, assuming chondrite-like precursor materials, our data are consistent with efficient loss of H prior to or during the onset of melting of early-formed planetesimals. This requires that Earth’s H-budget was dominated by building blocks that underwent minimal thermal processing.

KPM: A Flexible and Data-driven K-process Model for Nucleosynthesis

The element abundance pattern found in Milky Way disk stars is close to two-dimensional, dominated by production from one prompt process and one delayed process. This simplicity is remarkable, since the elements are produced by a multitude of nucleosynthesis mechanisms operating in stars with a wide range of progenitor masses. We fit the abundances of 14 elements for 48,659 red-giant stars from APOGEE Data Release 17 using a flexible, data-driven K-process model—dubbed KPM. In our fiducial model, with K = 2, each abundance in each star is described as the sum of a prompt and a delayed process contribution. We find that KPM with K = 2 is able to explain the abundances well, recover the observed abundance bimodality, and detect the bimodality over a greater range in metallicity than has previously been possible. We compare to prior work by Weinberg et al., finding that KPM produces similar results, but that KPM better predicts stellar abundances, especially for the elements C+N and Mn and for stars at supersolar metallicities. The model fixes the relative contribution of the prompt and delayed processes to two elements to break degeneracies and improve interpretability; we find that some of the nucleosynthetic implications are dependent upon these detailed choices. We find that moving to four processes adds flexibility and improves the model’s ability to predict the stellar abundances, but does not qualitatively change the story. The results of KPM will help us to interpret and constrain the formation of the Galaxy disk, the relationship between abundances and ages, and the physics of nucleosynthesis.

A comprehensive review of noise pollution monitoring studies at bus transit terminals

Abstract This article systematically reviews research on noise pollution monitoring conducted over the past 23 years at various bus transit terminals located worldwide. About 18 articles were identified using PRISMA method and were evaluated to provide summary of prior research work to examine accuracy, authenticity, and reliability of noise monitoring results with respect to chosen methodology and extent of noise pollution at bus transit terminals. It examines important indicators of noise pollution and the analysis parameters such as noise sampling, noise descriptors, processing of acquired data, noise mapping, etc., and compares it with the regulations and standard guidelines notably ISO 1996-2:2017 and American National Standards Institute/ASA S12.18-1994 (R2009) and their prior versions aiming to identify research gaps. The studies have primarily focused on noise monitoring, revealing widespread excessive noise pollution exceeding permissible levels at bus terminals globally. This article underscores significant research deficiencies in noise pollution monitoring at bus terminals, emphasizing the challenge of conducting quantitative meta-analyses and statistical comparisons due to variations in parameters and qualities. Noise pollution standards are breached in all terminals covered in the identified literature; hence, noise mitigation measures must be implemented at these bus terminals. The study suggests that noise monitoring must be carefully devised with respect to individual site operations and noise sources and in compliance with standard guidelines to improve the accuracy of the results. There is a need for uniform guidelines that can be followed globally for environmental noise monitoring as there are only a few countries that have guidelines for noise monitoring. The outcomes of this research will be helpful in guiding noise monitoring, mapping, and mitigation strategies as well as designing transit terminals to improve overall acoustical ambiance for more passenger footfall for sustainable transportation.

Year-round Observations of Adult Culex Mosquitoes in Storm Sewer Pipes in the Northwestern Chicago Suburbs.

Over the course of three years, 200 ft to 0.75 mi (60 m to 1.2 km) sections of 3 larger (>6 ft [1.8 m] diam) belowground storm sewer conveyance pipes in the northwestern Chicago suburbs were inspected for the presence of adult mosquitoes. Culex mosquitoes were by far the most common (555 of 556 [99.8%] total mosquitoes) collected within pipes during all four meteorological seasons (i.e. during months of October, January, May, August). These observations support prior work elsewhere, suggesting storm sewer pipes are consistent sites of refuge for adult Culex mosquitoes.