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Seagrasses play an important role in coastal ecosystems and serve as important marine carbon stores. Acoustic monitoring techniques exploit the sensitivity of underwater sound to bubbles, which are produced as a byproduct of photosynthesis and present within the seagrass tissue. To make accurate assessments of seagrass biomass and productivity, a model is needed to describe acoustic propagation through the seagrass meadow that includes the effects of gas contained within the seagrass leaves. For this purpose, a new seagrass leaf model is described for Thalassia testudinum that consists of a comparatively rigid epidermis that composes the outer shell of the leaf and comparatively compliant aerenchyma that surrounds the gas channels on the interior of the leaf. With the bulk modulus and density of the seagrass tissue determined by previous work, this study focused on characterizing the shear moduli of the epidermis and aerenchyma. These properties were determined through a combination of dynamic mechanical analysis and acoustic resonator measurements coupled with microscopic imagery and finite element modeling. The shear moduli varied as a function of length along the leaves with values of 100 and 1.8 MPa at the basal end and 900 and 3.7 MPa at the apical end for the epidermis and aerenchyma, respectively.

Infauna influence geoacoustic parameters in surficial marine sediments. To investigate these effects, an experiment was conducted in natural sand-silt sediment in the northern Gulf of Mexico. In situ acoustic measurements of sediment sound speed, attenuation, and shear speed were performed, and sediment cores were collected from the upper 20 cm of the seabed. Laboratory measurements of sound speed and attenuation in the cores were conducted, after which the core contents were analyzed for biological and physical properties. Since no model currently accounts for the effects of infauna, a deviation from model predictions is expected. To assess the extent of this, acoustic measurements were compared with the viscous grain shearing model from Buckingham [J. Acoust. Soc. Am. 122, 1486 (2007); J. Acoust. Soc. Am. 148, 962 (2020)], for which depth-dependent profiles of sediment porosity and mean grain size measured from the cores were used as input parameters. Comparison of acoustic results with distributions of infauna, worm tubes, and shell hash suggests biogenic impacts on acoustic variability and model accuracy are important in surficial marine sediments. The presence of infauna and worm tubes were correlated with higher variability in both sound speed and attenuation and greater deviation from the model near the sediment-water interface.

Purpose The Serious Illness Conversation (SIC) has emerged as a framework for conversations with patients with a serious illness diagnosis. This study reports on narratives generated from open-ended questions of a novel assessment tool, the SIC-Evaluation Exercise (SIC-Ex), to assess resident-led conversations with patients in oncology outpatient clinics.Methods We developed the SIC-Ex based on the Ariadne SIC framework. Seven resident trainees and ten preceptors were recruited from three cancer centres. Each trainee conducted a SIC with a patient, which was videotaped. The preceptors watched the videos and evaluated each trainee using the novel SIC-Ex and the reference Calgary-Cambridge Guide (CCG) at months 0 and 3. Two independent coders used template analysis to code the preceptors’ free-text narrative comments and identify themes/subthemes.Results Template analysis yielded 6 themes: behavioural attributes mapped to SIC, those mapped to CCG, those overlapping between SIC and CCG, trainees’ demeanors, rater mis-classification of comments, and comments on SIC-Ex. Narrative comments explored numerous verbal and non-verbal components essential to SIC. Some comments applied to both SIC and CCG (e.g. setting agenda, introduction, planning, exploring, non-verbal communication), whereas others mapped specific to one (e.g. SIC - identifying substitute decision maker, affirming commitment, introducing advance care planning, engaging family; CCG – using open ended questions, avoiding explanations, flow, time management).Conclusion Narrative comments generated by SIC-Ex provided a detailed and nuanced insight into trainee's competency in SIC, beyond numerical ratings and general communication skills assessed by CCG; they should continue to be a part of assessment.

Glacier ice loss impacts sound propagation within Arctic fjords. Regular calving events contribute to a collection of floating ice fragments, known as brash ice, at the ocean surface that obstruct the natural and anthropogenic acoustic signals, yet are difficult to characterize. Transmission loss measurements using a maximum length sequence ( m-sequence) signal were conducted in September 2017 near Hansbreen glacier in Hornsund Fjord, Svalbard with dense brash ice present at the water surface. An acoustic model of the brash ice surface was inferred through consideration of the experimental geometry, arrival amplitude, and travel time difference between the direct and surface reflected arrivals from the source to two receivers. The inferred surface was then incorporated into a forward simulation of the environment using sound speed profiles measured during the experiment. BELLHOP ([Porter and Bucker (1987). J. Acoust. Soc. Am. 82(4), 1349-1359],), a ray tracing code available in the Acoustics Toolbox (HLS Inc., San Diego, CA), was used to track the time difference of arrivals and amplitudes of the modeled direct and surface reflected rays. Comparisons between the measured and simulated results provide insight into the geometric shape and reflection characteristics of the brash ice surface within this and similar environments.

We demonstrate multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury. This point-of-care sensor includes a paper-based fluorescence vertical flow assay (fxVFA) processed by a low-cost mobile reader, which quantifies the target biomarkers through trained neural networks, all within 0.9 linearity and < 15 % coefficient of variation. The competitive performance of this multiplexed computational fxVFA along with its inexpensive paper-based design and handheld footprint make it a promising point-of-care sensor platform that could expand access to diagnostics in resource-limited settings., 17 Pages, 6 Figures

Changes in the Arctic environment with regard to declining sea ice are expected to alter the ambient sound field, affecting both the sound generating processes and the sound propagation. This paper presents acoustic recordings collected on the 150-m isobath on the Chukchi Shelf over a yearlong period spanning October 2016 to October 2017. The analysis uses sections of recordings approximately 12 min long collected six times daily. The measurements were collected on a vertical line array spanning the lower 110 m of the water column. The 25th percentile level is used to characterize the spectral shape of the background sound between 40 Hz and 4 kHz. The ambient sound data are analyzed using k-means clustering to quantify the occurrence of six spectral shapes over the yearlong experiment. Each cluster type is associated with a different sound generation process based on the correlations with environmental observations. The cluster observed most frequently was associated with wind-generated sound based on a correlation of sound level with wind speed as well as occurrence during the open water season. The cluster with the smallest number of observations was attributed to wind effects on frazil ice forming in open leads during the ice-covered season.

Over the past several decades the dramatic increase in the availability of computational resources, coupled with the maturation of machine learning, has profoundly impacted sensor technology. In this Perspective, we discuss computational sensing with a focus on intelligent sensor system design. By leveraging inverse design and machine learning techniques, data acquisition hardware can be fundamentally redesigned to ‘lock-in’ to the optimal sensing data with respect to a user-defined cost function or design constraint. We envision a new generation of computational sensing systems that reduce the data burden while also improving sensing capabilities, enabling low-cost and compact sensor implementations engineered through iterative analysis of data-driven sensing outcomes. We believe that the methodologies discussed in this Perspective will permeate the design phase of sensing hardware, and thereby will fundamentally change and challenge traditional, intuition-driven sensor and readout designs in favour of application-targeted and perhaps highly non-intuitive implementations. Such computational sensors enabled by machine learning can therefore foster new and widely distributed applications that will benefit from ‘big data’ analytics and the internet of things to create powerful sensing networks, impacting various fields, including for example, biomedical diagnostics, environmental sensing and global health, among others. Traditional sensing techniques apply computational analysis at the output of the sensor hardware to separate signal from noise. A new, more holistic and potentially more powerful approach proposed in this Perspective is designing intelligent sensor systems that ‘lock-in’ to optimal sensing of data, making use of machine leaning strategies.

Recent changes in ice cover and ocean stratification have been so large that acoustic measurements made during the Cold War no longer reflect current conditions.

Background/Objectives: The serious illness conversation (SIC) is an evidence-based framework for conversations with patients about a serious illness diagnosis. The objective of our study was to develop and validate a novel tool, the SIC-evaluation exercise (SIC-Ex), to facilitate assessment of resident-led conversations with oncology patients. Design: We developed the SIC-Ex based on SIC and on the Royal College of Canada Medical Oncology milestones. Seven resident trainees and 10 evaluators were recruited. Each trainee conducted an SIC with a patient, which was videotaped. The evaluators watched the videos and evaluated each trainee by using the novel SIC-Ex and the reference Calgary-Cambridge guide (CCG) at months zero and three. We used Kane's validity framework to assess validity. Results: Intra-class correlation using average SIC-Ex scores showed a moderate level of inter-evaluator agreement (range 0.523–0.822). Most evaluators rated a particular resident similar to the group average, except for one to two evaluator outliers in each domain. Test–retest reliability showed a moderate level of consistency among SIC-Ex scores at months zero and three. Global rating at zero and three months showed fair to good/very good inter-evaluator correlation. Pearson correlation coefficients comparing total SIC-Ex and CCG scores were high for most evaluators. Self-scores by trainees did not correlate well with scores by evaluators. Conclusions: SIC-Ex is the first assessment tool that provides evidence for incorporating the SIG guide framework for evaluation of resident competence. SIC-Ex is conceptually related to, but more specific than, CCG in evaluating serious illness conversation skills.

The activities of infaunal organisms, including feeding, locomotion, and home building, alter sediment physical properties including grain size and sorting, porosity, bulk density, permeability, packing, tortuosity, and consolidation behavior. These activities are also known to affect the acoustic properties of marine sediments, although previous studies have demonstrated complicated relationships between infaunal activities and geoacoustic properties. To avoid difficulties associated with real animals, whose exact locations and activities are unknown, this work uses artificial burrows and simulates infaunal activities such as irrigation, compaction, and tube building in controlled laboratory experiments. The results show statistically significant changes in sound speed and attenuation over a frequency range of 100–400 kHz, corresponding to wavelengths on the order of the burrow diameter. The greatest effects were observed for tubes constructed of hard shells which increased the attenuation by ∼30 dB m−1 across the measurement band. These results highlight the importance of biogenic hard structures such as tubes on sound attenuation and suggest that organisms that create hard structures may be good targets for acoustic mapping of infaunal abundance and distribution.

This paper presents measurements of sediment sound-speed profiles measured in situ using the acoustic coring system (ACS). The reported measurements were obtained from seven gravity cores collected in the New England Mud Patch. The ACS uses two sets of transducers mounted below the penetrating tip of a sediment corer to make in situ measurements of geoacoustic properties as the corer penetrates the seabed. The in situ sound-speed profiles are interpreted in the context of stratigraphic layering measured by a seismic survey, and the measured sound-speed profiles are consistent with the geophysical description. The in situ sound-speed profiles measured by the ACS were compared to conventional measurements of sound speed on the recovered cores using the multisensor core logger (MSCL). The MSCL data displayed both random and systematic errors that were attributed to disturbance from the coring process and/or the handling of the sediments after collection. Finally, using porosity and grain size distributions measured from discrete samples of the cored sediments, the in situ sound-speed measurements were compared to empirical regressions based on independent data sets.

Acoustic propagation measurements were collected in a seagrass meadow in a shallow lagoon for periods of over 65 h in winter and 93 h in summer. A bottom-deployed sound source transmitted chirps (0.1–100 kHz) every 10 min that were received on a four-receiver horizontal hydrophone array. Oceanographic probes measured various environmental parameters. Daytime broadband acoustic attenuation was 2.4 dB greater in summer than winter, and the median received acoustic energy levels were 8.4 dB lower in summer compared to winter. These differences were attributed in part to seasonal changes in photosynthesis bubble production and above-ground seagrass biomass.

Background Brain arteriovenous malformations (AVMs) consist of abnormal connections between arteries and veins via an interposing nidus. While hemorrhage is the most common presentation, unruptured AVMs can present with headaches, seizures, neurological deficits, or be found incidentally. It remains unclear as to what AVM characteristics contribute to pain generation amongst unruptured AVM patients with headaches. Methods To assess this relationship, the current study evaluates angiographic and clinical features amongst patients with unruptured brain AVMs presenting with headache. Loyola University Medical Center medical records were queried for diagnostic codes corresponding to AVMs. In patients with unruptured AVMs, we analyzed the correlation between the presenting symptom of headache and various demographic and angiographic features. Results Of the 144 AVMs treated at our institution between 1980 and 2017, 76 were unruptured and had sufficient clinical data available. Twenty-three presented with headaches, while 53 patients had other presenting symptoms. Patients presenting with headache were less likely to have venous stenosis compared to those with a non-headache presentation (13 % vs. 36 %, p = 0.044). Conclusions Our study suggests that the absence of venous stenosis may contribute to headache symptomatology. This serves as a basis for further study of correlations between AVM angioarchitecture and symptomatology to direct headache management in AVM patients.

Lyme disease (also known as Lyme borreliosis) is the most common vector-borne disease in the United States with an estimated 476,000 cases per year. While historically, the long-term impact of Lyme disease on patients has been controversial, mounting evidence supports the idea that a substantial number of patients experience persistent symptoms following treatment. The research community has largely lacked the necessary funding to properly advance the scientific and clinical understanding of the disease, or to develop and evaluate innovative approaches for prevention, diagnosis, and treatment. Given the many outstanding questions raised into the diagnosis, clinical presentation and treatment of Lyme disease, and the underlying molecular mechanisms that trigger persistent disease, there is an urgent need for more support. This review article summarizes progress over the past 5 years in our understanding of Lyme and tick-borne diseases in the United States and highlights remaining challenges.

This research examined self- and partner-enhancement biases in the everyday communication of commitment. A total of 189 romantic heterosexual couples completed a survey measuring self- and partner-...

This work examines three-dimensional (3D) propagation caused by interaction with the sea ice canopy using an approximate normal mode/parabolic equation hybrid model. The effects of horizontal refraction are assessed through comparison of two-dimensional (2D) and 3D solutions for the modal amplitudes and depth-averaged transmission loss. The following 3D effects are described: diffraction of sound into shadow zones behind ice keels, horizontal defocusing of sound behind ice keels, and horizontal focusing of sound that has propagated between ice keels. A statistical analysis shows that the 3D solution is characterized by 20% greater variance in the depth-averaged transmission loss than the 2D solution.

Scale-model tank experiments offer a controlled environment in which to make underwater acoustic propagation measurements that can provide high-quality data for comparison with numerical models. This paper presents results from a scale model experiment for a translationally invariant wedge with a 10° slope fabricated from closed-cell polyurethane foam to investigate three-dimensional (3-D) propagation effects. A computer controlled positioning system accurately located a receiving hydrophone in 3-D space to create a dense field of synthetic vertical line arrays, which are subsequently used to mode filter the measured pressure field. The resulting mode amplitudes show the modal propagation zone, the modal shadow zone, and the classical intra-mode interference pattern resulting from rays launched up and along the slope. The observed features of the measured data are compared to three different propagation models: an exact, closed-form solution for a point source in wedge with pressure release boundaries, a 3-D ray trace model, and an adiabatic model. Examination of the mode amplitudes produced by the models reveals how the effects of vertical mode coupling can be observed in the measured data.

Two scale-model acoustic propagation experiments were conducted in a laboratory tank to investigate three-dimensional (3D) propagation effects induced by range-dependent bathymetry. The model bathymetry, patterned after measured bathymetric data, represents a portion of the Hudson Canyon at 1:7500 scale. The bottom condition in the scale model is nearly pressure release, and as a result, the bottom reflection and backscattering are stronger than that of the real ocean environment. Measurements are presented for propagation paths oriented along and across the axis of the canyon. The measured data are interpreted using both 3D adiabatic-mode and 3D ray models. For propagation along the canyon axis, horizontal focusing is observed, and the out-of-plane arrivals are identified using the vertical mode/horizontal ray analogy to determine which wall or walls of the canyon refracted the sound. For the across-canyon propagation, out-of-plane arrivals are observed for both forward scattered and backward scattered sound. Using the 3D ray model, an investigation of the horizontal and vertical launch angles is used to identify features on the canyon walls responsible for the measured out-of-plane propagation. For both the along- and across-canyon experiments, the 3D ray model produced a solution that was more accurate and less computationally intensive.

Seabed variability introduced by physical or biogenic processes contributes to multi-scale horizontal and vertical variability in seabed acoustic and geotechnical properties. An experiment was conducted near the mouth of Mobile Bay to investigate such spatial variability over a mud-sand gradient. A normal-incidence bottom loss survey was conducted on a 750 × 1500 m2 grid with 50-m track-line spacing, in which a broadband acoustic source transmitted frequency-modulated chirps (1–100 kHz) every second, resulting in dense sampling of the seabed reflection coefficient over a wide frequency band. Diver cores were collected in the survey area for direct analysis of near-surface seabed properties. Cores were acoustically logged to obtain vertical profiles of sound speed and attenuation (10–1000 kHz) and then analyzed for physical properties (porosity, grain size, carbon content), infauna community composition, and sediment strength properties. Additionally, in situ portable free fall penetrometer measurements were conducted within the survey area to characterize geotechnical properties within the upper 50 cm of the sediment. Spatial distributions of properties estimated from bottom loss measurements (e.g. porosity and sound speed) will be compared with vertical profiles from the cores and from the penetrometer to examine potential connections between seabed acoustic, geotechnical, and biological parameters. [Sponsored by ONR.]

We report a deep-learning based compact spectrometer. Using a spectral encoder chip composed of unique plasmonic tiles (containing periodic nanohole-arrays), diffraction patterns created by the transmitted light through these tiles are captured by a CMOS sensor-array, without the use of any lenses or other components between the plasmonic encoder and the CMOS-chip. A neural network rapidly reconstructs the input light spectrum from the recorded lensless image data, which was blindly tested on randomly-generated new spectra to demonstrate the success of this computational on-chip spectrometer, which will find applications in various fields that demand low-cost and compact spectrum analyzers.

Conventional spectrometers are limited by trade-offs set by size, cost, signal-to-noise ratio (SNR), and spectral resolution. Here, we demonstrate a deep learning-based spectral reconstruction framework, using a compact and low-cost on-chip sensing scheme that is not constrained by the design trade-offs inherent to grating-based spectroscopy. The system employs a plasmonic spectral encoder chip containing 252 different tiles of nanohole arrays fabricated using a scalable and low-cost imprint lithography method, where each tile has a unique geometry and, thus, a unique optical transmission spectrum. The illumination spectrum of interest directly impinges upon the plasmonic encoder, and a CMOS image sensor captures the transmitted light, without any lenses, gratings, or other optical components in between, making the entire hardware highly compact, light-weight and field-portable. A trained neural network then reconstructs the unknown spectrum using the transmitted intensity information from the spectral encoder in a feed-forward and non-iterative manner. Benefiting from the parallelization of neural networks, the average inference time per spectrum is ~28 microseconds, which is orders of magnitude faster compared to other computational spectroscopy approaches. When blindly tested on unseen new spectra (N = 14,648) with varying complexity, our deep-learning based system identified 96.86% of the spectral peaks with an average peak localization error, bandwidth error, and height error of 0.19 nm, 0.18 nm, and 7.60%, respectively. This system is also highly tolerant to fabrication defects that may arise during the imprint lithography process, which further makes it ideal for applications that demand cost-effective, field-portable and sensitive high-resolution spectroscopy tools., Comment: 18 pages, 6 figures

We demonstrate a deep learning-based spectroscopy framework using a low-cost on-chip plasmonic encoder. When blindly tested on N=14,648 random spectra our system shows competitive performance, where the reconstruction of an unknown spectrum on average takes ~28µs.

We report the quantification of lysozyme in tear fluid using contact lenses and a mobile-phone well-plate reader. We observed significantly lower lysozyme levels in human participants with dry eye disease compared to healthy controls.

Introduction Placement of an external ventricular drain (EVD) is a common procedure routinely completed at bedside by neurosurgical residents. A standardized protocol for placement and maintenance of an EVD is potentially useful. Methods This single-institution retrospective review analyzed all patients who underwent placement of an EVD over a 5-year span using a standardized protocol. RESULTS A total of 428 EVDs in 381 patients were placed as per this protocol. Overall compliance with the practice protocol was 98.7%. Overall, our infection rate was 1.86% (8 external ventricular drain–related infection [ERIs] over 428 EVDs). There was no difference in age for the ERI cases (median 55, range (50.5–60.5), compared with the non-ERI cases (median of 53, range [38–65]) (P = 0.512). Indications for placement of EVD were hemorrhage (51.9%, n = 198), tumor (16.2%, n = 62), trauma (12.8%, n = 49), hydrocephalus (11.5%, n = 44), cerebellar stroke (2.8%, n = 11), infection (3.1%, n = 12), unknown (1.3%, n = 5). Most EVDs (77.6%, n = 296) were placed bedside by second-year residents (median PGY level 2, interquartile range 1–2.75). Computed tomography confirmed placement in the ipsilateral frontal horn in 72% (n = 277) of EVDs. EVD-related complications were noted in 8.3% of EVDs (n = 32, with 8 infections and 24 tract hemorrhages). The median EVD duration was 10 days; duration of EVD had no statistically significant impact on the risk of an ERI (P = 1). Only replacement of an EVD was associated with an increased risk of infection. Conclusions Adherence to a standard EVD placement protocol is useful in maintaining a low risk of ERI regardless of the duration of catheter utilization. Replacement of the catheter through the same access hole as the original catheter is associated with an increased risk of ERI.

We present a deep learning-based framework to perform single image super-resolution of SEM images. We experimentally demonstrated that this network can enhance the resolution of SEM images by two-fold, allowing for a reduction of the scanning time and electron dosage by four-fold without any significant loss of image quality. Using blindly tested regions of a gold-on-carbon resolution test target, we quantitatively and qualitatively confirmed the image enhancement achieved by the trained network. We believe that this technique has the potential to improve the SEM imaging process, particularly in cases where imaging throughput and minimizing beam damage are of utmost importance.

We report a point-of-care (POC) assay and neural network-based diagnostic algorithm for Lyme Disease (LD). A paper-based test in a vertical flow format detects 16 different IgM and IgG LD-specific antibodies in serum using a mobile phone reader and automated image processing to quantify its colorimetric signals. The multiplexed information is then input into a trained neural-network which infers a positive or negative result for LD. The assay and diagnostic decision algorithm were validated through fully-blinded testing of human serum samples yielding an area-under-the-curve (AUC), sensitivity, and specificity of 0.950, 90.5%, and 87.0% respectively, outperforming previous Lyme POC tests.

Seagrasses provide a multitude of ecosystem services and serve as important organic carbon stores. However, seagrass habitats are declining worldwide, threatened by global climate change and regional shifts in water quality. Acoustical methods have been applied to assess changes in oxygen production of seagrass meadows since sound propagation is sensitive to the presence of bubbles, which exist both within the plant tissue and freely floating the water as byproducts of photosynthesis. This work applies acoustic remote sensing techniques to characterize two different regions of a seagrass meadow: a densely vegetated meadow of Thalassia testudinum and a sandy region sparsely populated by isolated stands of T. testudinum. A Bayesian approach is applied to estimate the posterior probability distributions of the unknown model parameters. The sensitivity of sound to the void fraction of gas present in the seagrass meadow was established by the narrow marginal probability distributions that provided distinct estimates of the void fraction between the two sites. The absolute values of the estimated void fractions are biased by limitations in the forward model, which does not capture the full complexity of the seagrass environment. Nevertheless, the results demonstrate the potential use of acoustical methods to remotely sense seagrass health and density.

We report a method for sensing analytes in tear-fluid using commercial contact lenses (CLs) as sample collectors for subsequent analysis with a cost-effective and field-portable reader. In this study we quantify lysozyme, the most prevalent protein in tear fluid, non-specifically bound to CLs worn by human participants. Our mobile reader uses time-lapse imaging to capture an increasing fluorescent signal in a standard well-plate, the rate-of-change of which is used to indirectly infer lysozyme concentration through the use of a standard curve. We empirically determined the best-suited CL material for our sampling procedure and assay, and subsequently monitored the lysozyme levels of nine healthy human participants over a two-week period. Of these participants who were regular CL wearers (6 out of 9), we observed an increase in lysozyme levels from 6.89 ± 2.02 μg mL-1 to 10.72 ± 3.22 μg mL-1 (mean ± SD) when inducing an instance of digital eye-strain by asking them to play a game on their mobile-phones during the CL wear-duration. We also observed a lower mean lysozyme concentration (2.43 ± 1.66 μg mL-1) in a patient cohort with dry eye disease (DED) as compared to the average monitoring level of healthy (no DED) human participants (6.89 ± 2.02 μg mL-1). Taken together, this study demonstrates tear-fluid analysis with simple and non-invasive sampling steps along with a rapid, easy-to-use, and cost-effective measurement system, ultimately indicating physiological differences in human participants. We believe this method could be used in future tear-fluid studies, even supporting multiplexed detection of a panel of tear biomarkers toward improved diagnostics and prognostics as well as personalized mobile-health applications.

We demonstrate a contact-lens (CL) based mobile sensing system which can be used to measure protein levels in human tear. By using a cost-effective mobile-phone-based well-plate reader and a fluorescent assay, we quantify lysozyme nonspecifically bound to CLs. We monitored the lysozyme levels of 9 healthy volunteers to establish individual baselines, and then compared these measurements to participants who had been diagnosed with Dry Eye Disease (N=6), observing a statistically significant difference in their means. Due to its non-invasive and simple operation, this method could be used for tear-based sensing and health monitoring applications in point-of-care settings and at home.

Seagrasses provide a multitude of ecosystem services: they alter water flow, cycle nutrients, stabilize sediments, support the food web structure, and provide a critical habitat for many animals. H...

The article of record may be found at https://doi.org/10.1121/10.0001970 The Pacific Arctic Region has experienced decadal changes in atmospheric conditions, seasonal sea-ice coverage, and thermohaline structure that have consequences for underwater sound propagation. To better understand Arctic acoustics, a set of experiments known as the deep-water Canada Basin acoustic propagation experiment and the shallow-water Canada Basin acoustic propagation experiment was conducted in the Canada Basin and on the Chukchi Shelf from summer 2016 to summer 2017. During the experiments, low-frequency signals from five tomo- graphic sources located in the deep basin were recorded by an array of hydrophones located on the shelf. Over the course of the yearlong experiment, the surface conditions transitioned from completely open water to fully ice- covered. The propagation conditions in the deep basin were dominated by a subsurface duct; however, over the slope and shelf, the duct was seen to significantly weaken during the winter and spring. The combination of these surface and subsurface conditions led to changes in the received level of the sources that exceeded 60 dB and showed a dis- tinct spacio-temporal dependence, which was correlated with the locations of the sources in the basin. This paper seeks to quantify the observed variability in the received signals through propagation modeling using spatially sparse environmental measurements. This work was supported by the Office of Naval Research Ocean Acoustics Program (ONR OA322) under Grant Nos. N00014-15-1-2144, N00014-15-1-2119, N00014-15-1-2017, N00014-15-1-2068, N00014-15-1-2110, N00014-19-1-2721, N00014-15-1-2898, N00014-15-1-2806, and N00014-18-1- 2140. The basin moored environmental data were supported by the ONR Arctic and Global Prediction Program (ONR AG322) under Grant No. N00014-15-1-2782. Mooring and hydrographic data were collected and made available by the Beaufort Gyre Exploration Program based at the Woods Hole Oceanographic Institution (http://www.whoi.edu/beaufortgyre) in collaboration with researchers from Fisheries and Oceans Canada at the Institute of Ocean Sciences. This work was supported by the Office of Naval Research Ocean Acoustics Program (ONR OA322) under Grant Nos. N00014-15-1-2144, N00014-15-1-2119, N00014-15-1-2017, N00014-15-1-2068, N00014-15-1-2110, N00014-19-1-2721, N00014-15-1-2898, N00014-15-1-2806, and N00014-18-1- 2140. The basin moored environmental data were supported by the ONR Arctic and Global Prediction Program (ONR AG322) under Grant No. N00014-15-1-2782. Mooring and hydrographic data were collected and made available by the Beaufort Gyre Exploration Program based at the Woods Hole Oceanographic Institution (http://www.whoi.edu/beaufortgyre) in collaboration with researchers from Fisheries and Oceans Canada at the Institute of Ocean Sciences.

We demonstrate computational sensing with a multiplexed paper-based point-of-care assay for high sensitivity C-Reactive protein testing (hsCRP). Using blindly-tested human serum samples, we achieved an R2 value of 0.95 and an average coefficient-of-variation of 11.2%.