Search

During the COVID-19 pandemic, there has been an increasing rollout of non-contact fever screening solutions to assist in curbing the spread of disease. This study begins by describing how screening for disease has historically been performed. It proposes four measurement characteristics of an ideal screening solution: non-contact, effective, rapid and low-cost measurements. Next, it reviews the existing literature on fever-screening using non-contact infrared thermometer (NCIT) devices as well as infrared thermography (IRT) devices, as these are two technologies which have experienced increasing use. For this review, 185 research papers were identified, 21 research studies were included after inclusion and exclusion criteria were applied. A total of 35 experiments were identified for analysis and their results tabulated. Of these studies, 66% are IRT and 34% are NCIT, with a median sample size of 430 subjects. 26 experiments involve febrile participants, with a median febrile percentage of 11.22 % of population. The reported sensitivity of febrile detection using NCIT varies from 3.7% to 97% and when using IRT it varies from 15% to 100%. Both indoor and outdoor studies are investigated, as well as those conducted in acute and non-acute settings. The results of this review show a clear lack of consensus on the effectiveness of these systems. Overall, these results indicate that sensitivity and specificity are reduced when using IRT and NCIT technologies compared to other thermometers used in medical practice. Their use should be carefully assessed based on the risks present in each particular measurement scenario. CCBY

Piezoelectric nanogenerator (PENG) is a leading-edge mechanical energy harvesting device used in portable power supply and self-powered sensor systems. Advanced 3D printers have been recently used to create 3D printed (3DP) PENGs. This has facilitated the rapid fabrication of PENGs and their integration into wearable electronics, biomedical systems, and internet of things devices. However, researchers face several critical challenges in developing robust 3DP-PENGs that can produce adequate electrical energy for self-powered systems. Therefore, this review on 3DP-PENGs is conducted to highlight their recent developments and challenges. This paper presents the latest 3D-printed piezoelectric nanogenerators in terms of their materials selection and functionalization, design and architecture formation, and applications including pressure sensors, flow sensors, microphones, and implants. Finally, crucial challenges and optimization strategies that considerably impact the output performance of 3DP-PENGs, along with a roadmap for their future enhancement are given. It is envisioned that this work will help reduce the gap between 3D printing and PENG technologies and accelerate the research and development of 3DP-PENGs. Graphical Abstract: [Figure not available: see fulltext.].

Deep brain stimulation (DBS) is an invasive neuromodulatory technique used for the treatment of individuals with neurological disorders. Open-loop DBS delivers fixed stimulation pulses while closed-loop DBS senses the state of disorder and delivers stimulation pulses optimized for the sensed state adaptively. This review focuses on current miniature closed-loop DBS devices. The latest progress in stimulation techniques and electrode configurations are discussed. We cover common circuit configurations used for stimulation and outline the latest methods for delivering rectangular and non-rectangular stimulation waveforms. Recent advances in feedback control for closing the loop in DBS are highlighted, as are cutting edge developments in artificial intelligence (AI) methods that analyse the sensed data to determine the state of disorder. Finally, we critically discuss present issues and future directions of miniaturized closed-loop DBS.

Fast-scan cyclic voltammetry (FSCV) is an electrochemical sensing method used for measuring the concentration of neurotransmitters within the brain. FSCV is typically conducted using benchtop equipment, providing accurate and high temporal resolution measurements. However, the large size and high cost of benchtop FSCV systems pose significant limitations in widespread preclinical use of FSCV. Recent technological improvements have facilitated the miniaturization of FSCV equipment, creating systems that can be mounted on the subject as they are small and lightweight. One key remaining bottleneck in the emerging miniaturized FSCV systems is that their data typically needs to be transmitted to an external computer for analysis. This paper presents a review on the current miniature FSCV devices. It discusses the latest improvements in voltage scan waveforms that help increase the sensitivity of measuring specific analytes, for use in miniaturized FSCV. It also tabulates analytes that have been detected using FSCV. It also details current issues with FSCV and the latest achievements in post-processing of FSCV data to better identify target analytes. Furthermore, the emerging miniature FSCV devices that have integrated on-board data processing capabilities to mitigate external data processing are discussed. These advances can accelerate neurochemistry research, reducing time spent analysing data on external computers, and allowing for investigation into questions on neurotransmitter dynamics in target brain regions.

Fast-scan cyclic voltammetry (FSCV) is an electrochemical technique for measuring rapid changes in the extracellular concentration of neurotransmitters within the brain. Due to its fast scan rate and large output-data size, the current analysis of the FSCV data is often conducted on a computer external to the FSCV device. Moreover, the analysis is semi-automated and requires a good understanding of the characteristics of the underlying chemistry to interpret, making it unsuitable for real-time implementation on low-resource FSCV devices. This paper presents a hardware-software co-design approach for the analysis of FSCV data. Firstly, a deep neural network (DNN) is developed to predict the concentration of a dopamine solution and identify the data recording electrode. Secondly, the DNN is pruned to decrease its computation complexity, and a custom overlay is developed to implement the pruned DNN on a low-resource FPGA-based platform. The pruned DNN attains a recognition accuracy of 97.2% with a compression ratio of 3.18. When the DNN overlay is implemented on a PYNQ-Z2 platform, it achieves the execution time of 13 ms and power consumption of 1.479 W on the entire PYNQ-Z2 board. This study demonstrates the possibility of operating the DNN for FSCV data analysis on portable FPGA-based platforms.

As an essential prerequisite task in image-based plant phenotyping, leaf segmentation has garnered increasing attention in recent years. While self-supervised learning is emerging as an effective alternative to various computer vision tasks, its adaptation for image-based plant phenotyping remains rather unexplored. In this work, we present a self-supervised leaf segmentation framework consisting of a self-supervised semantic segmentation model, a color-based leaf segmentation algorithm, and a self-supervised color correction model. The self-supervised semantic segmentation model groups the semantically similar pixels by iteratively referring to the self-contained information, allowing the pixels of the same semantic object to be jointly considered by the color-based leaf segmentation algorithm for identifying the leaf regions. Additionally, we propose to use a self-supervised color correction model for images taken under complex illumination conditions. Experimental results on datasets of different plant species demonstrate the potential of the proposed self-supervised framework in achieving effective and generalizable leaf segmentation.

Contribution: This paper demonstrated on a large scale that explicit articulation of creativity-related learning goals on engineering syllabi is quite limited, and primarily limited to the first year of study. Engineering educators may need to do more to ensure creativity is explicitly addressed as an expected learning outcome within engineering syllabi. Background: Prior studies have shown inclusion of creativity within engineering syllabi and course activities are generally limited. Students may perceive educators do not value creativity, and their studies have limited influence on their creative skills. Studies conflict on whether creativity skills increase over completing an engineering degree. Creativity has been demonstrated to be an important skill for engineering professionals, but one not necessarily appropriately addressed in engineering programs. Few studies have attempted to quantify coverage of creativity material on a nation-wide scale, as opposed to in a single or select few institutions. Research Questions: 1) To what extent do engineering educators explicitly articulate creativity and innovation-related learning goals and material on their course syllabi? and 2) To what extent do engineering educators explicitly articulate exposure to, or instruction in the use of, creativity heuristics within their course syllabi? Methodology: The online publicly accessible course outlines of 1109 compulsory courses from 42 degree programs accredited by two national engineering accreditation bodies were qualitatively analyzed in a two-stage approach using document analysis. Findings: Approximately 2% of compulsory electrical engineering course outlines explicitly articulate creativity-related material; only one course articulated engaging students in using creativity heuristics.

In 2006, the state of New York imposed mandated additional prison time for any crime committed with a firearm and increased the mandated minimum jail time for anyone carrying a firearm illegally. Using several different estimation strategies, we find that robberies immediately declined compared with other U.S. states once these enhancements were enacted. Other crimes, which are less likely to be committed with a firearm, were unaffected. The most plausible explanation is that criminals were deterred from committing robberies using a firearm because of the cost associated with additional prison time.

Insertion of a microelectrode into the brain to record/stimulate neurons damages neural tissue and blood vessels and initiates the brain’s wound healing response. Due to the large difference between the stiffness of neural tissue and microelectrode, brain micromotion also leads to neural tissue damage and associated local immune response. Over time, following implantation, the brain’s response to the tissue damage can result in microelectrode failure. Reducing the microelectrode’s cross-sectional dimensions to single-digit microns or using soft materials with elastic modulus close to that of the neural tissue are effective methods to alleviate the neural tissue damage and enhance microelectrode longevity. However, the increase in electrical impedance of the microelectrode caused by reducing the microelectrode contact site’s dimensions can decrease the signal-to-noise ratio. Most importantly, the reduced dimensions also lead to a reduction in the critical buckling force, which increases the microelectrode’s propensity to buckling during insertion. After discussing brain micromotion, the main source of neural tissue damage, surface modification of the microelectrode contact site is reviewed as a key method for addressing the increase in electrical impedance issue. The review then focuses on recent approaches to aiding insertion of flexible microelectrodes into the brain, including bending stiffness modification, effective length reduction, and application of a magnetic field to pull the electrode. An understanding of the advantages and drawbacks of the developed strategies offers a guide for dealing with the buckling phenomenon during implantation.

Background NCIT are non-invasive devices for fever screening in children. However, evidence of their accuracy for fever screening in adults is lacking. This study aimed to compare the accuracy of non-contact infrared thermometers (NCIT) with temporal artery thermometers (TAT) in an adult hospital. Methods A prospective observational study was conducted on a convenience sample of non-infectious inpatients in 2 Australian hospitals. NCIT and TAT devices were used to collect body temperature recordings. Participant characteristics included age, gender, skin color, highest temperature, and antipyretic medications recorded in last 24-hour. Results In 265 patients, a mean difference of ± 0.26°C was recorded between the NCIT (36.64°C) and the reference TAT (36.90°C) temperature devices. Bland-Altman analysis showed that NCIT and TAT temperatures were closely aligned at temperatures 37.5°C. NCIT had low sensitivity (16.13%) at temperatures ≥37.5°C. An AUROC score of 0.67 (SD 0.05) demonstrated poor accuracy of the NCIT device at temperatures ≥37.5°C. Conclusion This is the first study to compare accuracy of NCIT thermometers to TAT in adult patients. Although mass fever screening is currently underway using NCIT, these results indicate that the NCIT may not be the most accurate device for fever mass screening during a pandemic.

Background Bloodstream infections (BSI) are associated with significant mortality in hematologic cancer patients with febrile neutropenia. Poor clinical outcomes are associated with presence of multidrug resistant (MDR) organisms and polymicrobial infections. We sought to determine antimicrobial resistance and outcomes of polymicrobial bloodstream infections in hematologic cancer patients with febrile neutropenic episodes (FNEs) at the Uganda Cancer Institute. Methods Blood drawn from participants during an FNE (fever ≥ 37.5°C and neutrophil count ≤ 1000 cells/µL) was cultured in the BACTEC 9120 blood culture system. Bacteria from positive cultures were identified biochemically. Antimicrobial susceptibility testing was performed with the disc diffusion method. Participants were followed for 30 days from first FNE onset for death from any cause. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (95%). Results Six hundred and twenty-nine participants were followed for FNE. Two hundred and twenty-eight FNEs in 159 participants were observed. Of 181 FNEs with blood cultures completed, 65 (36%) had pathogenic organism isolated. A total of 74 Gram negative and 18 Gram positive bacteria were isolated. Forty-eight (74%) FNEs had monomicrobial (MBSI) and 17 (26%) had polymicrobial (PBSI) bloodstream infections. Gram negative - Gram negative (10 out of 17, 59%) was the most frequent PBSI combination (Fig 1). Up to 75% (12 out of 16) of Gram-negative PBSI were MDR. The most common organism isolated was E. coli (38% of isolates). Participants with PBSI had higher early mortality rates at 7 days compared to MBSI and negative cultures (44%, 22%, and 16% for PBSI, MBSI, and negative respectively; HR (95% CI): 3.63 (1.49, 8.86) for PBSI v. negative/MBSI cultures). Similarly, PBSI was associated with higher mortality within 30 days of FNE onset (63%, 52%, and 38% for PBSI, MBSI, and negative respectively; HR (95% CI): 2.17 (1.09, 4.32) for PBSI v. negative/MBSI) (Fig 2). Figure 1. Bar graph showing combinations for polymicrobial bloodstream infections (PBSI). GNGN: Gram-negative – Gram-negative; GNGP: Gram-negative – Gram-positive; GNO: Gram-negative – Other (fungi); GPGP: Gram-positive – Gram-positive Figure 2. Kaplan-Meier failure curves of participants with negative cultures, monomicrobial infections and polymicrobial infections Conclusion PBSI episodes were more likely to be multidrug resistant and are associated with higher mortality. Empirical therapy for patients with PBSI should consider multidrug resistant Gram-negative bacteria Disclosures All Authors: No reported disclosures

International audience; Difficulties quantifying in situ prey patch quality have limited our understanding of how marine predators respond to variation within and between patches, and throughout their foraging range. In the present study, animal-borne video, GPS, accelerometer and dive behaviour data loggers were used to investigate the fine-scale foraging behaviour of Macaroni penguins (Eudyptes chrysolophus) in response to prey type, patch density and temporal variation in diving behaviour. Individuals mainly dived during the day and utilised two strategies, targeting different prey types. Subantarctic krill (Euphausia vallentini) were consumed during deep dives, while small soft-bodied fish were captured on shallow dives or during the ascent phase of deep dives. Despite breeding in large colonies individuals seemed to be solitary foragers and did not engage with conspecifics in coordinated behaviour as seen in other group foraging penguin species. This potentially reflects the high abundance and low manoeuvrability of krill. Video data were used to validate prey capture signals in accelerometer data and a Support Vector Machine learning algorithm was developed to identify prey captures that occurred throughout the entire foraging trip. Prey capture rates indicated that Macaroni penguins continued to forage beyond the optimal give up time. However, bout-scale analysis revealed individuals terminated diving behaviour for reasons other than patch quality. These findings indicate that individuals make complex foraging decisions in relation to their proximate environment over multiple spatio-temporal scales.

(Abridged) Using the Zwicky Transient Facility alert stream, we are conducting a large campaign to spectroscopically classify all transients occurring in galaxies in the Census of the Local Universe (CLU) catalog. The aim of the experiment is to construct a spectroscopically complete, volume-limited sample of transients coincident within 100" of CLU galaxies out to 200 Mpc, and to a depth of 20 mag. We describe the survey design and spectroscopic completeness from the first 16 months of operations. We present results from a systematic search for Calcium rich gap transients in the sample of 22 low luminosity (peak absolute magnitude $M > -17$), hydrogen poor events found in the experiment (out of 754 spectroscopically classified SNe). We report the detection of eight Calcium rich gap transients, and constrain their volumetric rate to be at least $\approx 15\pm5$% of the SN Ia rate. Combining this sample with ten events from the literature, we find a likely continuum of spectroscopic properties ranging from events with SN Ia-like features (Ca-Ia objects) to SN Ib/c-like features (Ca-Ib/c objects) at peak light. Within the Ca-Ib/c events, we find two populations of events distinguished by their red ($g - r \approx 1.5$ mag) or green ($g - r \approx 0.5$ mag) spectral colors at $r$-band peak, wherein redder events show strong line blanketing signatures, slower light curves, weaker He lines and lower [Ca II]/[O I] in the nebular phase. Together, we find that the spectroscopic continuum, volumetric rates and striking old environments are consistent with the explosive burning of He shells on low mass white dwarfs. We posit that Ca-Ia and red Ca-Ib/c objects are consistent with the double detonation of He shells with high He burning efficiency, while green Ca-Ib/c objects could arise from less efficient He burning scenarios such as detonations in low density He shells or He shell deflagrations., 30 figures, 6 tables. Submitted to ApJ

The COVID-19 pandemic has led to the rapid adoption and rollout of thermal camera-based Infrared Thermography (IRT) systems for fever detection. These systems use facial infrared emissions to detect individuals exhibiting an elevated core-body temperature, which is present in many symptomatic presentations of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Despite the rollout of these systems, there is little independent research supporting their efficacy. The primary objective of this study was to assess the precision and accuracy of IRT screening solutions in a real-world scenario. The method used was a single-centre, observational study investigating the agreement of three IRT systems compared to digital oral thermometer measurements of body temperature. Over 5 days, 107 measurements were taken from individuals wearing facial masks. During each entry, two measurements of the subject’s body temperature were made from each system to allow for the evaluation of the measurement precision, followed by an oral thermometer measurement. Each participant also answered a short demographic survey. This study found that the precision of the IRT systems was wider than 0.3 °C claimed accuracy of two of the systems. This study also found that the IRT measurements were only weakly correlated to those of the oral temperature. Additionally, it was found that demographic characteristics (age, gender, and mask-type) impacted the measurement error. This study indicates that using IRT systems in front-line scenarios poses a potential risk, where a lack of measurement accuracy could possibly allow febrile individuals to pass through undetected. Further research is required into methods which could increase accuracy and improve the techniques viability.

Marine predators adapt their hunting techniques to locate and capture prey in response to their surrounding environment. However, little is known about how certain strategies influence foraging success and efficiency. Due to the miniaturisation of animal tracking technologies, a single individual can be equipped with multiple data loggers to obtain multi-scale tracking information. With the addition of animal-borne video data loggers, it is possible to provide context-specific information for movement data obtained over the video recording periods. Through a combination of video data loggers, accelerometers, GPS and depth recorders, this study investigated the influence of habitat, sex and the presence of other predators on the foraging success and efficiency of the endangered African penguin,Spheniscus demersus, from two colonies in Algoa Bay, South Africa. Due to limitations in the battery life of video data loggers, a machine learning model was developed to detect prey captures across full foraging trips. The model was validated using prey capture signals detected in concurrently recording accelerometers and animal-borne cameras and was then applied to detect prey captures throughout the full foraging trip of each individual. Using GPS and bathymetry information to inform the position of dives, individuals were observed to perform both pelagic and benthic diving behaviour. Females were generally more successful on pelagic dives than males, suggesting a trade-off between manoeuvrability and physiological diving capacity. By contrast, males were more successful in benthic dives, at least for Bird Island (BI) birds, possibly due to their larger size compared to females, allowing them to exploit habitat deeper and for longer durations. Both males at BI and both sexes at St Croix (SC) exhibited similar benthic success rates. This may be due to the comparatively shallower seafloor around SC, which could increase the likelihood of females capturing prey on benthic dives. Observation of camera data indicated individuals regularly foraged with a range of other predators including penguins and other seabirds, predatory fish (sharks and tuna) and whales. The presence of other seabirds increased individual foraging success, while predatory fish reduced it, indicating competitive exclusion by larger heterospecifics. This study highlights novel benthic foraging strategies in African penguins and suggests that individuals could buffer the effects of changes to prey availability in response to climate change. Furthermore, although group foraging was prevalent in the present study, its influence on foraging success depends largely on the type of heterospecifics present.

Among the available energy harvesters, triboelectric nanogenerators (TENGs) are the most popular technologies for scavenging mechanical energy from ambient sources and converting them into electrical energy. Out of four working modes of a TENG, contact-separation (CS) mode is mostly used in practical applications. A typical CS mode TENG consists of the following components: two dielectric layers for friction, two electrodes for current conduction and a connected load. There are several factors which can affect the output performance of a TENG. Among different factors, dielectric layer's thickness and its relative constant can significantly influence the electrical output of a TENG. In addition, surface structure of the dielectric layers in a TENG has also a great impact on its electrical output. Therefore, this study considers these three aspects and vary them to observe the changes in electric potential distribution between two dielectric layers. A comparative study has been conducted for analysing four intrinsic electrical output of the TENG, including the open-circuit voltage, short-circuit charge, capacitance, and energy. In case of investigating dielectric thickness, thin dielectric film based TENG shows greater voltage, charge and energy compared to the thick one. During investigation of relative dielectric constant, the best electrical output is obtained from higher dielectric constant-based electronegative film in TENG. Regarding surface structures, patterned film based TENG exhibits enhanced output compared to non-patterned one. This study considers COMSOL Multiphysics software for all modeling and simulations of the TENG. With the help of this software the design, material selection and stationary study of the TENG has been performed. Overall, this work can be an ideal reference to the researchers which can help them to design a high performance based TENG.

Electroactive polymers (EAPs) have attracted much attention in a variety of areas such as robotics, sensors, and biomedical devices. However, the practical applications of these actuators are still challenging mainly because of their incomplete reversibility and high applied voltage. This paper presents a method for the fabrication of a conductive chitosan composite actuator with high flexural modulus. An essential component of the actuator is tubular carbonized-cellulose, synthesized in an orderly crystalline structure. The prepared actuator reveals high elasticity and flexural modulus with minimum plastic deformation. A reversible electro-thermal motion was observed upon the application of a direct current (DC) of 5 V to the composite ribbon.

One of the bottlenecks in widespread adoption of biosensors is the large and sophisticated bioanalytical system that is required to perform signal transduction and analysis. A miniaturized bioanalytical system facilitates biosensing techniques that are portable, easy to handle and inexpensive for fast and reliable measurements of biochemical species. Thus, downscaling the bioanalytical system has become a highly active research area, significantly assisted by recent advances in the microelectronics technology. In this work, a miniaturized system is designed and implemented for amperometric detection, and subsequently tested with a glucose biosensor based on the one-step approach utilizing water soluble poly(o-aminophenol). Several experiments are conducted to assess the viability of this system including calibration, interference and application tests. The results are compared with the previously published work performed using the same biosensor tested with a commercial potentiostat in order to verify the applicability of the designed system.

3D printing technology is driving innovation in a wide variety of disciplines, and is beginning to make inroads into the fields of medicine and biology. In particular, 3D printing is being increasingly utilized for the design and fabrication of three-dimensional cell culture scaffolds. This technology allows for scaffolds to be produced rapidly while maintaining a great deal of control over the matrix architecture. This paper presents an effective technique for rapidly designing and fabricating scaffolds from silicone rubber and polycaprolactone (PCL), appropriate for primary human cardiomyocyte cell cultures. Additionally, a stimulation device is developed and presented which can provide 6 channels of wirelessly controlled electrical stimulation to the cell culture scaffolds. The design, fabrication, benchtop evaluation, and biological evaluation of the scaffolds and stimulation device for primary human cardiomyocyte cell culture are presented. The results clearly indicate the effectiveness of both the scaffold fabrication technique and the operation of the stimulation device. The silicone rubber scaffold showed significantly lower cell attachment as compared to the PCL scaffold, validating the suitability of PCL as a material to be employed in the synthesis of bioscaffolds, employed in the management of several medical pathologies such as tissue regeneration and wound healing. Additionally, the biocompatible PCL scaffold stimulated with electrical impulse (5 V, 2 ms pulses, 1 Hz) exhibited higher cell attachment and differentiated actin cytoskeletal structures as compared to the unstimulated scaffold, indicating the potential of this technique in tissue engineering applications.

To support U.S. Department of Homeland Security efforts to prioritize capability investments, this report examines trends in small unmanned aerial system development, the features that are likely to aid nefarious users, and how such actors could use an sUAS (or multiple systems) to conduct various types of operations—from surveilling U.S. government facilities to dispersing a chemical agent at a large public event.

The ability to monitor neurochemical dynamics in target brain regions with a high degree of temporal resolution has assisted researchers in investigating the pathogenesis, and pathophysiology of a variety of neurological and psychiatric disorders. Current systems for neurochemical monitoring are bulky or expensive, limiting widespread exploration of this research field and preventing large-scale parallel experimentation. In this paper, we present a new miniaturized research platform, the TinyFSCV system, which can be used to monitor dynamic changes in neurochemicals through Fast-Scan Cyclic Voltammetry (FSCV). This system contains a precision voltage output circuit that can accurately output potentials between −0.55 to 2 V and scan a connected electrochemical cell at up to 400 V/s, the required speed to sense most neurochemicals with FSCV. In addition, the device includes precision current measurement circuity with a measurement range of −115 to $115~\mu \text{A}$ capable of taking measurements at up to 56 KS/s. Four experiments are conducted to demonstrate the capability of the system. These consisted of: static bench tests, static ferrocene tests, and static and dynamic dopamine tests. These experiments demonstrate the ability of the miniaturized platform to accurately sense and measure neurochemicals. Ultimately, the TinyFSCV system is a platform that can enable large-scale, low-cost parallel experimentation to take place in the field of neurochemical monitoring. In addition, this device will increase the accessibility of neurochemical sensing, providing advanced tools and techniques to more researchers, and facilitating widespread exploration of the field of neurodynamics.

We use the universe of birth records in the United States from 2013 to 2018 to examine the effect of e-cigarette tax rates on pre-pregnancy smoking and prenatal smoking. We study these questions using two-way fixed effects models and pregnancy fixed effects models. We show that e-cigarette taxes increase pre-pregnancy smoking, increase prenatal smoking, and lower smoking cessation during pregnancy. These findings imply that e-cigarettes and traditional cigarettes are substitutes among pregnant women. We also find evidence that e-cigarette taxes reduce pre-pregnancy and third trimester e-cigarette use.