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Background: An unmet need exists when clinically assessing retinal and layer-based features of retinal diseases. Therefore, quantification of retinal-layer-thicknesses/fluid volumes using deep-learning-augmented platforms to reproduce human-obtained clinical measurements is needed. Methods: In this analysis, 210 spectral-domain optical coherence tomography (SD-OCT) scans (30 without pathology, 60 dry age-related macular degeneration [AMD], 60 wet AMD, and 60 diabetic macular edema [total 23,625 B-scans]) were included. A fully automated segmentation platform segmented four retinal layers for compartmental assessment (internal limiting membrane, ellipsoid zone [EZ], retinal pigment epithelium [RPE], and Bruch's membrane). Two certified OCT readers independently completed manual segmentation and B-scan level validation of automated segmentation, with segmentation correction when needed (semi-automated). Certified reader metrics were compared to gold standard metrics using intraclass correlation coefficients (ICCs) to assess overall agreement. Across different diseases, several metrics generated from automated segmentations approached or matched human readers performance. Results: Absolute ICCs for retinal mean thickness measurements showed excellent agreement (range 0.980–0.999) across four cohorts. EZ-RPE thickness values and sub-RPE compartment ICCs demonstrated excellent agreement (ranges of 0.953–0.987 and 0.944–0.997, respectively) for full dataset, dry-AMD, and wet-AMD cohorts. Conclusions: Analyses demonstrated high reliability and consistency of segmentation of outer retinal compartmental features using a completely human/manual approach or a semi-automated approach to segmentation. These results support the critical role that measuring features, such as photoreceptor preservation through EZ integrity, in future clinical trials may optimize clinical care. [ABSTRACT FROM AUTHOR]

The Hindu Kush Himalaya (HKH) is one of the most flood-prone regions in the world, yet heavy cloud cover and limited in situ observations have hampered efforts to monitor the impact of heavy rainfall, flooding, and inundation during severe weather events. This paper introduces HydroSAR, a Sentinel-1 SAR-based hazard monitoring service which was co-developed with in-region partners to provide year-round, low-latency weather hazard information across the HKH. This paper describes the end user-focused concept and overall design of the HydroSAR service. It introduces the main processing algorithms behind HydroSAR's broad product portfolio, which includes qualitative visual layers as well as quantitative products measuring the surface water extent and water depth. We summarize the cloud-based implementation of the developed service, which provides the capability to scale automatically with the event size. A performance assessment of our quantitative algorithms is described, demonstrating the capabilities to map the flood extent and water depth with an accuracy of >90% and <1 m, respectively. An application of the HydroSAR service to the 2023 South Asia monsoon seasons showed that monsoon floods peaked near 6 August 2023 and covered 11.6% of Bangladesh in water. At the peak of the flood season, nearly 13.5% of Bangladesh's agriculture areas were affected. [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) levels vary across specific population groups, contributing to health inequalities. Little is known about how local authority leisure centers contribute to population PA and whether this differs by age, sex, or socioeconomic group. Methods: The authors calculated weekly leisure center–based moderate/vigorous PA for 20,904 registered adult users of local authority leisure facilities in Northumberland, United Kingdom, between July 2018 and June 2019, using administrative data. The authors categorized activity levels (<30, 30–149, and ≥150 min/wk) and used ordinal regression to examine predictors for activity category achieved. Results: Registered users were mainly female (58.7%), younger (23.9% of users aged 18–29 y vs 10.1% of those aged 70+ y), and from the 2 most affluent socioeconomic quintiles (53.7%). Median weekly moderate/vigorous leisure center–based activity was 55 minutes per week (interquartile range: 30–99). Being female (odds ratio: 2.09; 95% confidence interval, 1.95–2.35), older (odds ratio: 1.14; 95% confidence interval, 1.11–1.16), and using a large facility (odds ratio: 1.21; 95% confidence interval, 1.03–1.42) were positive predictors of leisure center–based PA. Conclusion: Older adults and females were more likely to be active and achieve the recommended PA levels through usage of the centers. Widespread use of this novel measure of leisure center–based activity would improve the understanding of how local authority leisure centers can address physical inactivity and its associated inequalities. [ABSTRACT FROM AUTHOR]

Hail and damaging winds are two threats associated with intense and severe thunderstorms that traverse the Midwest and Great Plains during the primary growing season. In certain severe thunderstorm events, large swaths of agricultural crops are impacted, allowing the damage to be viewed from multiple satellite remote sensing platforms. Previous studies have focused on analyzing individual hail and wind damage swaths (HWDSs) using satellite remote sensing, but these swaths have never been officially archived or documented. This lack of documentation has made it difficult to analyze the spatial extent and temporal frequency of HWDSs from year to year. This study utilizes daily true color imagery from MODIS aboard NASA's Terra and Aqua satellites and daily local storm reports from the Storm Prediction Center to build a database of HWDSs occurring in the months of May–August, for years 2000–20. This database identified 1646 HWDSs in 12 states throughout the Midwest and Great Plains, confirmed through a combination of archived severe weather warnings, radar information, and official storm reports. For each entry in the HWDS database, a geospatial outline is provided along with the most likely date of first visible damage from MODIS imagery as well as the physical characteristics and time of occurrence estimated from available warnings. This study also provides a summary of the radar characteristics for a portion of the database. This database will further the understanding of severe weather damage by hail and wind to agriculture to help understand the frequency of these events and assist in mapping the impacted areas. Significance Statement: Hail and wind damage swaths (HWDSs) frequently occur during the primary growing season throughout the Midwest and Great Plains but are not yet officially documented or tracked like other severe weather impacts (e.g., tornadoes and derechos). This study describes the creation of a 21-yr HWDS event database using archived daily storm reports and daily true color satellite imagery. Once the database was completed and underwent quality checks, the research team identified spatial and temporal trends from the confirmed swaths. [ABSTRACT FROM AUTHOR]

In this article, we introduce co-excavative letter writing as a method for developing racial literacy, deepening relationships, and challenging standard forms of knowledge production. Jordan and Karen, students in Yolanda's cotaught graduate seminar, developed an epistolary exchange as part of their "(un)final project." Collaborative epistles challenged the writers to explore their positionalities, allowing them to trace interrelated issues of power and identity in their past and present experiences. The co-excavative letter-writing process makes explicit the individual voices that combine to create coauthored academic articles, highlighting the process of collaboration in a way that traditional academic production obscures. [ABSTRACT FROM AUTHOR]

Some of the most intense thunderstorms on Earth occur in the Hindu Kush Himalaya (HKH) region of southern Asia—where many organizations lack the capacity needed to predict, observe, and/or effectively respond to the threats associated with high-impact convective weather. As a result, a disproportionately large number of casualties and damage often occur with premonsoon severe thunderstorms in this region. To address this problem, we combined ensemble numerical weather prediction (NWP), satellite-based precipitation products, and land-imagery techniques into a High-Impact Weather Assessment Toolkit (HIWAT) customized for HKH. In 2018 and 2019 demonstrations, a regional convection-allowing ensemble NWP system was configured to provide real-time probabilistic guidance of thunderstorm hazards over HKH, applying ensemble techniques developed for U.S.-focused experiments. Case studies of damaging wind, large hail, lightning, a rare Nepalese tornado, and landfalling tropical cyclone events show how HIWAT efficiently packages ensemble output into products that are readily interpreted by forecasters in HKH. Precipitation and total lightning flash verification reveal the highest skill occurred where deep convection was most frequently observed in Bangladesh and northeastern India, and verification scores exceeded global ensemble scores for heavy precipitation rates. These results demonstrate that plausible forecasts of thunderstorm hazards can be attained with relatively low computational resources, thereby facilitating advancements in extreme weather forecasting services in historically underserved regions such as HKH. In early 2022, a custom version of HIWAT was installed at the Bangladesh Meteorological Department using in-house computational resources, providing regional ensemble forecast guidance in real time. [ABSTRACT FROM AUTHOR]

There is currently a dearth of research on the creation and the implications of Black educational space, even with the increased awareness raised by the Black Lives Matter (BLM) movement to the individual and structural antiblackness inherent in the United States. This essay aims to share the BLM history that helped to motivate and inform two Black college educators' construction of Black educational space. The analysis reveals that a pro-Black political imagination is required to authentically and meaningfully engage in centering, supporting, and honoring Black people in classroom spaces and beyond. The article shares reflections from the two educators' about their experiences of constructing Black educational spaces. In doing so, this work attempts to motivate concrete pro-Black action by disrupting standardized academic practices in making commitments to ourselves, our students, and our communities. This work is significant insofar as it contributes to international debates about the purposes of education, and it reimagines how pedagogy can be operationalized to transform classrooms in global educational contexts into sites for Black Healing. [ABSTRACT FROM AUTHOR]

In recognition of the fact that the COVID-19 pandemic pronounced racialized and ethnicized inequities, five educators and community activists from across the United States gathered to reflect on the ways Black and Brown communities have developed community cultural wealth in the time of COVID-19. The authors gathered on Zoom to share their personal, familial, and communal experiences with COVID-19. Moreover, they shared narratives of familial and communal beauty, resistance, and complexity that highlighted how Black and Brown communities collaborate in the face of — and respond to — adversity. The authors' collaboration unveils not only what communities have done to develop cultural wealth but also what individuals and communities have learned from the pandemic. [ABSTRACT FROM AUTHOR]

The catastrophic derecho that occurred on 10 August 2020 across the midwestern United States caused billions of dollars of damage to both urban and rural infrastructure as well as agricultural crops, most notably across the state of Iowa. This paper documents the complex evolution of the derecho through the use of low-Earth-orbit passive-microwave imager and GOES-16 satellite-derived products complemented by products derived from NEXRAD weather radar observations. Additional satellite sensors including optical imagers and synthetic aperture radar (SAR) were used to observe impacts to the power grid and agriculture in Iowa. SAR improved the identification and quantification of damaged corn and soybeans, as compared to true-color composites and normalized difference vegetation index (NDVI). A statistical approach to identify damaged corn and soybean crops from SAR was created with estimates of 1.97 million acres of damaged corn and 1.40 million acres of damaged soybeans in the state of Iowa. The damage estimates generated by this study were comparable to estimates produced by others after the derecho, including two commercial agricultural companies. [ABSTRACT FROM AUTHOR]

In this paper, we utilize poetic methods that seek to surface, but not overdetermine, the unanticipated relational excess produced through literacy practices. Karen, a queer white woman, and Jordan, a cis-gendered heterosexual Black man, wrote a series of letters to one another throughout the Spring 2020 semester. We turned to critical poetic inquiry to analyze the letters, interested in poetry's capacity to highlight literacy's critical power and its emergent potential. We found ourselves implicated in each other's lives in new ways; we found our relationship both strengthened and tested. Such relational indeterminacy creates methodological challenges in literacy research. We found critical poetic inquiry to be a uniquely useful method for expressing the ambiguity and incommensurability of literacy as 'affective encounters' (Lenters, 2016), particularly during the Covid-19 pandemic, as our interdependency and mutual obligation is highlighted. [ABSTRACT FROM AUTHOR]

Tumor spheroid models have proven useful in the study of cancer cell responses to chemotherapeutic compounds by more closely mimicking the 3-dimensional nature of tumors in situ. Their advantages are often offset, however, by protocols that are long, complicated, and expensive. Efforts continue for the development of high-throughput assays that combine the advantages of 3D models with the convenience and simplicity of traditional 2D monolayer methods. Herein, we describe the development of a breast cancer spheroid image cytometry assay using T47D cells in Aggrewell™400 spheroid plates. Using the Celigo® automated imaging system, we developed a method to image and individually track thousands of spheroids within the Aggrewell™400 microwell plate over time. We demonstrate the use of calcein AM and propidium iodide staining to study the effects of known anti-cancer drugs Doxorubicin, Everolimus, Gemcitabine, Metformin, Paclitaxel and Tamoxifen. We use the image cytometry results to quantify the fluorescence of calcein AM and PI as well as spheroid size in a dose dependent manner for each of the drugs. We observe a dose-dependent reduction in spheroid size and find that it correlates well with the viability obtained from the CellTiter96® endpoint assay. The image cytometry method we demonstrate is a convenient and high-throughput drug-response assay for breast cancer spheroids under 400 μm in diameter, and may lay a foundation for investigating other three-dimensional spheroids, organoids, and tissue samples. [ABSTRACT FROM AUTHOR]

This paper introduces a satellite-based cross-calibration (SCC) method for spectral reflectance estimation of unmanned aircraft system (UAS) multispectral imagery. The SCC method provides a low-cost and feasible solution to convert high-resolution UAS images in digital numbers (DN) to reflectance when satellite data is available. The proposed method is evaluated using a multispectral data set, including orthorectified KHawk UAS DN imagery and Landsat 8 Operational Land Imager Level-2 surface reflectance (SR) data over a forest/grassland area. The estimated UAS reflectance images are compared with the National Ecological Observatory Network's imaging spectrometer (NIS) SR data for validation. The UAS reflectance showed high similarities with the NIS data for the near-infrared and red bands with Pearson's r values being 97 and 95.74, and root-mean-square errors being 0.0239 and 0.0096 over a 32-subplot hayfield. [ABSTRACT FROM AUTHOR]

The normalized difference vegetation index (NDVI) has been frequently used to map hail damage to vegetation, especially in agricultural areas, but observations can be blocked by cloud cover during the growing season. Here, the European Space Agency's Sentinel-1A/1B C-band synthetic aperture radar (SAR) imagery in co- and cross polarization is used to identify changes in backscatter of corn and soybeans damaged by hail during intense thunderstorm events in the early and late growing season. Following a June event, hail-damaged areas produced a lower mean backscatter when compared with surrounding, unaffected pixels [vertical–vertical (VV): −1.1 dB; vertical–horizontal (VH): −1.5 dB]. Later, another event in August produced an increase in co- and cross-polarized backscatter (VV: 0.7 dB; VH: 1.7 dB) that is hypothesized to result from the combined effects of crop growth, change in structure of damaged crops, and soil moisture conditions. Hail damage regions inferred from changes in backscatter were further assessed through coherence change detections to support changes in the structure of crops damaged within the hail swath. While studies using NDVI have routinely concluded a decrease in NDVI is associated with damage, the cause of change with respect to the damaged areas in SAR backscatter values is more complex. Influences of environmental variables, such as vegetation structure, vegetation maturity, and soil moisture conditions, need to be considered when interpreting SAR backscatter and will vary throughout the growing season. [ABSTRACT FROM AUTHOR]

Remote sensing analysis is routinely used to map flooding extent either retrospectively or in near-real time. For flood emergency response, remote-sensing-based flood mapping is highly valuable as it can offer continued observational information about the flood extent over large geographical domains. Information about the floodwater depth across the inundated domain is important for damage assessment, rescue, and prioritizing of relief resource allocation, but cannot be readily estimated from remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was developed to augment remote sensing analysis by calculating water depth based solely on an inundation map with an associated digital elevation model (DEM). The tool was shown to be accurate and was used in flood response activations by the Global Flood Partnership. Here we present a new version of the tool, FwDET v2.0, which enables water depth estimation for coastal flooding. FwDET v2.0 features a new flood boundary identification scheme which accounts for the lack of confinement of coastal flood domains at the shoreline. A new algorithm is used to calculate the local floodwater elevation for each cell, which improves the tool's runtime by a factor of 15 and alleviates inaccurate local boundary assignment across permanent water bodies. FwDET v2.0 is evaluated against physically based hydrodynamic simulations in both riverine and coastal case studies. The results show good correspondence, with an average difference of 0.18 and 0.31 m for the coastal (using a 1 m DEM) and riverine (using a 10 m DEM) case studies, respectively. A FwDET v2.0 application of using remote-sensing-derived flood maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater. Limitations include challenges in obtaining high-resolution DEMs and increases in uncertainty when applied for highly fragmented flood inundation domains. [ABSTRACT FROM AUTHOR]

A real-time understanding of the distribution and duration of power outages after a major disaster is a precursor to minimizing their harmful consequences. Here, we develop an approach for using daily satellite nighttime lights data to create spatially disaggregated power outage estimates, tracking electricity restoration efforts after disasters strike. In contrast to existing utility data, these estimates are independent, open, and publicly-available, consistently measured across regions that may be serviced by several different power companies, and inclusive of distributed power supply (off-grid systems). We apply the methodology in Puerto Rico following Hurricane Maria, which caused the longest blackout in US history. Within all of the island’s settlements, we track outages and recovery times, and link these measures to census-based demographic characteristics of residents. Our results show an 80% decrease in lights, in total, immediately after Hurricane Maria. During the recovery, a disproportionate share of long-duration power failures (> 120 days) occurred in rural municipalities (41% of rural municipalities vs. 29% of urban municipalities), and in the northern and eastern districts. Unexpectedly, we also identify large disparities in electricity recovery between neighborhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, the most vulnerable to increased mortality and morbidity risks from power losses, shouldered the longest outages because they lived in less dense, detached housing where electricity restoration lagged. The approach developed in this study demonstrates the potential of satellite-based estimates of power recovery to improve the real-time monitoring of disaster impacts, globally, at a spatial resolution that is actionable for the disaster response community. [ABSTRACT FROM AUTHOR]

Remote sensing analysis is routinely used to map flooding extent either retrospectively or in near-real-time. For flood emergency response, remote sensing-based flood mapping is highly valuable as it can offer continued observational information about the flood extent over large geographical domains. Information about the floodwater depth across the inundated domain is important for damage assessment, rescue, and to prioritize relief resource allocation, but cannot be readily estimated from remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was developed to augment remote sensing analysis by calculating water depth based solely on an inundation map with an associated Digital Elevation Model (DEM). The tool was shown to be accurate and was used in flood response activations by the Global Flood Partnership. Here we present a new version of the tool, FwDET v2.0, which enables water depth estimation for coastal flooding. FwDET v2.0 features a new flood boundary identification scheme which accounts for the lack of confinement of coastal flood domains at the shoreline. A new algorithm is used to calculate the local floodwater elevation for each cell, which improves the tool's runtime by a factor 15 and alleviates inaccurate local boundary assignment across permanent water bodies. FwDET v2.0 is evaluated against physically-based hydrodynamic simulations in both riverine and coastal case studies. The results show good correspondence, with an average difference of 0.18 m and 0.31 m for the coastal (using a 1-m DEM) and riverine (using a 10-m DEM) case studies respectively. A FwDET v2.0 application of using remote sensing derived flood maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater. Limitations include challenges in obtaining high-resolution DEMs and increases in uncertainty when applied for highly fragmented flood inundation domains. [ABSTRACT FROM AUTHOR]

During the growing season in the central United States, severe thunderstorms frequently occur and produce large hail that damages the underlying vegetation, often in agricultural areas. Satellite remote sensing provides a tool for identifying these damaged areas. Previous studies have used changes in the normalized difference vegetation index (NDVI) to identify and examine these areas of damage, but have done so in a manual, time-consuming manner. This study examines an automated approach to detecting areas of hail damage in satellite imagery. Two techniques are evaluated: (i) use of an NDVI change threshold and (ii) detection of anomalies that occur in both daily NDVI and land surface temperature imagery. The two techniques are scored against one another using three different case studies. Two of the case studies occurred late in the growing season in August, and the third occurred in the growing season in early June. The NDVI threshold performed well in the two August case studies with a final probability of detection (POD) ranging from 0.497 to 0.647, whereas the anomaly detection for these two case studies had a lower POD of 0.317 to 0.587. The early June case study highlighted the limitations of using an NDVI threshold and the strengths of using anomaly detection. The POD for the NDVI threshold technique was 0.07-0.08 with a false alarm ratio (FAR) of 0.661-0.758, whereas the anomaly detection had a POD of 0.399-0.418 and a FAR of 0.540-0.681 for this third case study. [ABSTRACT FROM AUTHOR]

The 27 April 2011 severe weather outbreak included 62 tornadoes across northern and central Alabama, leading to one of the largest post-event survey operations in history. The enormity of the task faced by National Weather Service surveyors required extensive planning in an attempt to ensure that every tornado was documented. Moderate- and high-resolution satellite imagery can support the assessment process. Normalized difference vegetation index (NDVI) imagery from the Moderate Resolution Imaging Spectro-radiometer, Enhanced Thematic Mapper Plus, and Advanced Spaceborne Thermal Emission and Reflection Radiometer was used to assess satellite-based capabilities to detect tornado damage tracks, expanding upon previous studies of tornado-track detection. Of the tornadoes that were officially documented and surveyed in Alabama, 22 (32.4%) were identified at least in part by a simple visual inspection of single-day NDVI imagery. Detection of satellite-based damage tracks improved for tornadoes with estimated maximum damage of ≥EF-2, with portions of 21 (65.6%) paths identified. Lengths of satellite-detected tornado tracks compared favorably (R² = 0.88-0.93) to official survey measurements, but maximum estimated widths compared less favorably (R² = 0.39-0.52). Longer-term NDVI change and image-enhancement techniques, such as principal component analysis, can improve visual inspection. Overall, this study demonstrates that near real-time access to moderate- and high-resolution imagery may support survey activities, particularly in well-vegetated regions where spectral bands and high spatial resolution allow for detection of vegetation damage resulting from severe weather. [ABSTRACT FROM AUTHOR]

A technique is presented to produce real-time, daily vegetation composites at 0.01 ° resolution ( ~ 1 km) over the Conterminous United States (CONUS) for use in the NASA Land Information System (LIS) and weather prediction models. Green vegetation fraction (GVF) is derived from direct-broadcast swaths of normalized difference vegetation index from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the NASA Earth Observing System satellites. The real-time data and increased resolution compared to the 0.144 ° ( ~ 16 km) resolution monthly GVF climatology in community models result in an improved representation of vegetation in high-resolution models, especially in complex terrain. The MODIS GVF fields show seasonal variations that are similar to the community model climatology, and respond realistically to temperature and precipitation anomalies. The wet spring and summer 2010 over the U.S. Plains led to higher regional GVF than in the climatology. The GVF substantially decreased over the U.S. Southern Plains from 2010 to 2011, consistent with the transition to extreme drought in summer 2011. LIS simulations depict substantial sensitivity to the MODIS GVF, with regional changes in heat fluxes around 100 Wm-2 over the northern U.S. in June 2010. CONUS LIS simulations during the 2010 warm season indicate that the larger MODIS GVF in the western U.S. led to higher latent heat fluxes and initially lower sensible heat fluxes, with a net drying effect on the soil. With time, the drier soil eventually lead to higher mean sensible heat fluxes such that the total surface energy output increased by late summer 2010 over the western U.S. A sensitivity simulation of a severe weather event using real-time MODIS GVF data results in systematic changes to low-level temperature, moisture, and instability fields, and improves the evolution of simulated precipitation. [ABSTRACT FROM PUBLISHER]

Euler discovered the pentagonal number theorem in 1740 but was not able to prove it until 1750. He sent the proof to Goldbach and published it in a paper that finally appeared in 1760. Moreover, Euler formulated another proof of the pentagonal number theorem in his notebooks around 1750. Euler did not publish this proof or communicate it to his correspondents, probably because of the difficulty of clearly presenting it with the notation at the time. In this paper we show that the method of Euler's unpublished proof can be used to give a new proof of the celebrated Rogers-Fine identity. [ABSTRACT FROM AUTHOR]

In this article, we give a summary of Leonhard Euler’s work on the pentagonal number theorem. First we discuss related work of earlier authors and Euler himself. We then review Euler’s correspondence, papers and notebook entries about the pentagonal number theorem and its applications to divisor sums and integer partitions. In particular, we work out the details of an unpublished proof of the pentagonal number theorem from Euler’s notebooks. As we follow Euler’s discovery and proofs of the pentagonal number theorem, we pay attention to Euler’s ideas about when we can consider a mathematical statement to be true. Finally, we discuss related results in the theory of analytic functions. [ABSTRACT FROM AUTHOR]

This essay examines three reality TV shows: MTV's The Real World: Denver, CBS's Survivor: Cook Islands, and the FX network's miniseries Black.White. The essay uses Grindstaff's conceptual framework of news media and television talk shows as a mechanism to examine the way race is constructed on reality TV. It argues that the shows promote a politics of difference,emphasize conflict and division by positioning race as a point of contention among the cast members and dramatize scenarios that reinforce cultural codes and stereotypes. Three points of reference will guide this analysis: First, Jhally and Lewis write that we should more closely examine the ways that media texts purposely, critically and unapologetically confront race in the US. Second, Brummett proposes that media texts are sites of struggle over meaning and that we engage in an unconscious yet powerful struggle over how to interpret them. Third, recent theoretical discourses on race and representation in media call for continued critique of how media marginalize the lived experiences of African Americans, perpetuate crippling representations of marginalized groups, and often render them invisible. [ABSTRACT FROM AUTHOR]

The article focuses on African American activist and comedian Dave Chappelle, whose satirical television program "Chappele's Show," (Comedy Central Network) presents a comedic discourse on issues such as racial inequality, prejudice, and intolerance in the U.S. Mentioned is New York University professor Diana Taylor's notion of "scenarios of discovery" to analyze the comedic performance on "Chappele's Show." Also discussed is the concept known as "comiculture."

Background: More than 3 decades after Jones and Smith (1973) reported on the devastation caused by alcohol exposure on fetal development, the rates of heavy drinking during pregnancy remain relatively unchanged. Early identification of fetal alcohol exposure and maternal abstinence led to better infant outcomes. This study examined the utility of biometry for detecting alcohol-related fetal growth impairment. Methods: We obtained fetal ultrasound measures from routine ultrasound examinations for 167 pregnant hazardous drinkers who were enrolled in a brief alcohol intervention study. The fetal measures for women who quit after learning of their pregnancies were compared with measures for women who continued some drinking throughout the course of their pregnancies. Because intensity of alcohol consumption is associated with poorer fetal outcomes, separate analyses were conducted for the heavy (average of ≥5 drinks per drinking day) alcohol consumers. Fetal measures from the heavy-exposed fetuses were also compared with measures from a nondrinking group that was representative of normal, uncomplicated pregnancies from our clinics. Analyses of covariance were used to determine whether there were differences between groups after controlling for influences of gestational age and drug abuse. Results: Nearly half of the pregnant drinkers abstained after learning of their pregnancies. When women reportedly quit drinking early in their pregnancies, fetal growth measures were not significantly different from a non–alcohol-exposed group, regardless of prior drinking patterns. Any alcohol consumption postpregnancy recognition among the heavy drinkers resulted in reduced cerebellar growth as well as decreased cranial to body growth in comparison with women who either quit drinking or who were nondrinkers. Amphetamine abuse was predictive of larger cranial to body growth ratios. Conclusions: Alterations in fetal biometric measurements were observed among the heavy drinkers only when they continued drinking after becoming aware of their pregnancies. Although the reliance on self-reported drinking is a limitation in this study, these findings support the benefits of early abstinence and the potential for ultrasound examinations in the detection of fetal alcohol effects. [ABSTRACT FROM AUTHOR]

Rationale. The ethical debate concerning the use of animals in biomedical and pharmacological research continues to be replete with misunderstandings about whether animals have moral standing. Objectives. This article briefly reviews the central ethical positions and their relationship to the basic parameters of research regulation from an international perspective. The issues associated with the validation of animal models will then be discussed. Finally, suggestions for empirical ethics research will be presented. Methods. Recent literature reviews were accessed and analyzed. Results. This review summarizes the pertinent ethical and research literature. Conclusions. In summary, regardless of the ethical perspective one favors, there is strong agreement that animals matter morally and that at a minimum their welfare must be considered. This position is reflected in the structure of national regulatory schemes that emphasize the three Rs (replacement, reduction, refinement). Researchers should more actively participate in the discussion by becoming more knowledgeable about the details of the ethical issues. Research with animal models has been problematic in that it has often focused on attempting to produce global models of psychiatric disorders, which suffer from inherent validity problems. Researchers must also become more sophisticated about issues of model validation and the nature of the animals they use. [ABSTRACT FROM AUTHOR]

In response to Hurricane Florence of 2018, NASA JPL collected quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument, observing record-setting river stages across North and South Carolina. Fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging, stemming from the sensor's ability to penetrate cloud cover and dense vegetation. This study used random forest classification to generate maps of inundation from L-band UAVSAR imagery processed using the Freeman–Durden decomposition method. An average overall classification accuracy of 87% is achieved with this methodology, with areas of both under- and overprediction for the focus classes of open water and inundated forest. Fuzzy logic operations using hydrologic variables are used to reduce the number of small noise-like features and false detections in areas unlikely to retain water. Following postclassification refinement, estimated flood extents were combined to an event maximum for societal impact assessments. Results from the Hurricane Florence case study are discussed in addition to the limitations of available validation data for accuracy assessments. [ABSTRACT FROM AUTHOR]

The Greater Houston metropolitan area has experienced recurring flooding events in the past two decades related to tropical cyclones and heavy inland rainfall. With the projected recurrence of severe weather events, an approach that outlines the susceptibility of different localities within the study area to potential floods based on analyses of the impacts from earlier events would be beneficial. We applied a novel C-band Sentinel-1 Synthetic Aperture Radar (SAR)-based flood detection method to map floodwater distribution following three recent severe weather events with the goal of identifying areas that are prone to future flood hazards. Attempts were made to calibrate and validate the C-band-based results and analyses to compensate for possible sources of error. These included qualitative and quantitative assessments on L-band aerial SAR data, as well as aerial imagery acquired after one of the events. The findings included the following: (1) most urban centers of Harris county, with few exceptions, are not believed to be prone to flooding hazards in contrast to the densely populated areas on the outskirts of Harris county; (2) nearly 44% of the mapped flood-prone areas lie within a 1 km distance of major drainage networks; (3) areas experiencing high subsidence rates have persistently experienced flooding, possibly exacerbated by morphological changes to the land surface induced by subsidence. [ABSTRACT FROM AUTHOR]