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The article presents the critical design of the CubeSat for the FACSAT-2 (SAT-CHIRIBIQUETE) space mission for the georeferenced observation and analysis of the Colombian territory for environmental protection purposes. The satellite provides, through two payloads, data as electro-optical multispectral images (resolution between 4.75 m and 5 m) and, in parallel, data using a spectrometer in the short-wave infrared spectral range of 1000-1700 nm for monitoring greenhouse gases. Based on high-level technical requirements and the operational concept, the input identification and definition of the architecture of the space, ground, and launch segments were performed, defining a six-unit satellite, a ground segment with an S/X-band antenna in the city of Cali, and the use of an EXOpod with launcher-associated characteristics. The subsystems of the mechanical structure, electrical power system, data and command handling system, on-board communication system, and attitude control and determination system were defined and characterized in detail, in accordance with the ECSS standards of the European Space Agency. The initial design solution was customized based on spaces, operational and technical requirements, and the financial budget available for the space mission. It is noteworthy that the article contains exclusive contributions from Colombia, including the definition of the S/X-Band antenna, encryption software, and the design and implementation of the physical interface board to achieve electronic compatibility between the satellite bus and the Argus 2000 spectrometer. [ABSTRACT FROM AUTHOR]

Emergency managers have an increasing need for tools to enhance preparedness to extreme coastal storms and support disaster risk reduction measures. With the emergence of Early Warning Systems (EWSs) for coastal storm hazards, a fundamental challenge is the accurate prediction of sandy beach erosion at lead times of days to weeks corresponding to an approaching storm event. This work presents a data-driven modelling approach to predict storm-driven beach erosion (shoreline change) using a large dataset of 276 individual storm events at Narrabeen-Collaroy Beach, SE Australia. Correlation analysis between individual storm characteristics and shoreline response at three locations along the embayment with varying exposure to the prevailing waves indicates that cumulative storm wave energy is the dominant driver of storm erosion at this site. This is followed by the pre-storm beach width, storm wave direction and to a minimal extent, storm wave period and water levels. A multi-linear regression model of storm erosion is developed and found to accurately predict shoreline change due to individual storm events (RMSE = 3.7 m–6.4 m). This work highlights the value of high-frequency shoreline data for storm erosion forecasting and provides a framework for real-time forecasting applications. • Large dataset of shoreline change associated with 276 individual storm events at Narrabeen-Collaroy Beach (SE Australia) is used to develop a multi-linear regression model of storm erosion • Cumulative storm wave energy found to be the dominant driver of storm erosion, followed by the pre-storm beach width and storm wave direction • Water levels during storms only a minor contributor to storm erosion at this wave-dominated site • Data-driven erosion model can be used for real-time applications based on global wave forecast systems. [ABSTRACT FROM AUTHOR]

Nearshore sandbars characterize many sandy coasts, and unravelling their dynamics is crucial to understanding nearshore sediment pathways. Sandbar morphologies exhibit complex patterns that can be classified into distinct states. The tremendous progress in data-driven learning in image recognition has recently led to the first automated classification of single-barred beach states from Argus imagery using a Convolutional Neural Network (CNN). Herein, we extend this method for the classification of beach states in a double-barred system. We used transfer learning to fine-tune the pre-trained network of ResNet50. Our data consisted of labelled single-bar time-averaged images from the beaches of Narrabeen (Australia) and Duck (US), complemented by 9+ years of daily averaged low-tide images of the double-barred beach of the Gold Coast (Australia). We assessed seven different CNNs, of which each model was tested on the test data from the location where its training data came from, the self-tests, and on the test data of alternate, unseen locations, the transfer-tests. When the model trained on the single-barred data of both Duck and Narrabeen was tested on unseen data of the double-barred Gold Coast, we achieved relatively low performances as measured by F1 scores. In contrast, models trained with only the double-barred beach data showed comparable skill in the self-tests with that of the single-barred models. We incrementally added data with labels from the inner or outer bar of the Gold Coast to the training data from both single-barred beaches, and trained models with both single- and double-barred data. The tests with these models showed that which bar the labels used for training the model mattered. The training with the outer bar labels led to overall higher performances, except at the inner bar. Furthermore, only 10% of additional data with the outer bar labels was needed for reasonable transferability, compared to the 20% of additional data needed with the inner bar labels. Additionally, when trained with data from multiple locations, more data from a new location did not always positively affect the model's performance on other locations. However, the larger diversity of images coming from more locations allowed the transferability of the model to the locations from where new training data were added. [ABSTRACT FROM AUTHOR]

CoastalImageLib is a Python library that produces common coastal image products intended for quantitative analysis of coastal environments. This library contains functions to georectify and merge multiple oblique camera views, produce statistical image products for a given set of images, and create subsampled pixel instruments for use in bathymetric inversion, surface current estimation, run-up calculations, and other quantitative analyses. This package intends to be an open-source broadly generalizable front end to future coastal imaging applications, ultimately expanding user accessibility to optical remote sensing of coastal environments. This package was developed and tested on data collected from the Argus Tower, a 43 m tall observation structure in Duck, North Carolina at the US Army Engineer Research and Development Center’s Field Research Facility that holds six stationary cameras which collect twice-hourly coastal image products. Thus, CoastalImageLib also contains functions designed to interface with the file storage and collection system implemented at the Argus Tower.

Breaking waves constitute one of the main environmental stressors on coastal structures as well as a leading hazard to navigation in nearshore regions. In this paper, we use camera-based methods to measure wave breaking over two jetty systems in the Pacific Northwest; the North jetty of the Columbia River, Washington state, and the two jetties of Coos Bay, Oregon, as well as over three nearby nearshore dredge disposal areas. Data were collected using the "brightest" images and Argus camera technology over a span of 847 days for the Columbia River and 202 days for Coos Bay. Wave breaking over the Columbia north jetty reached 100% for wave heights greater than 3 m and for tides above mid-tide level and was concentrated on the seaward half of the jetty. For Coos Bay, the south jetty saw substantially more breaking than the north one with the worst overtopping occurring mid-jetty and seeming to be associated with sediment transport through the jetty and into the inlet, as well as possibly the navigation channel. Wave breaking at the Coos Bay inlet mouth was enhanced during ebb flow conditions. Argus imagery analysis showed no evidence of enhanced breaking over any of the three dredge material placement sites. [ABSTRACT FROM AUTHOR]

AHR reactors are known for the production of radiopharmaceuticals. The ARGUS reactor is one of the most famous of these reactors, which has been designed originally for radioisotopes production. The ARGUS reactor produces a suitable neutron flux that can be used for other applications such as neutron radiography (NR). Here, a NR system is designed step by step using the Monte Carlo method. The length of the collimator, divergence angle, diameter of the aperture, and thermal column dimension are designed. The designed aperture and thermal column are selected from boron carbide and heavy water, respectively. The depth of the thermal column is changed until the ratio of thermal neutrons to total neutrons (TNC) reached above 90%. The hole inside the thermal column is designed and internal lining is done. The inner lining is made of cadmium and had a thickness of 1 mm, and the space between the inner and outer lining is filled with lead. To reduce the gamma dose to acceptable values, the position of the collimator is changed instead of using a gamma filter. By changing the depth of the hole and creating the convergence angle to the hole, the flux of thermal neutrons will be 1.8E+6 n.cm−2s−1 that satisfy the IAEA suggested values for NR. Then, the uniformity of the radiation field of the neutron flux output from the collimator is obtained. At the end, images of SI and BPI standards are recorded. The good quality and contrast of these images showed the acceptable design of the NR system for the ARGUS reactor. • The ARGUS reactor is considered as a neutron source to design an appropriate neutron beamline for NR application. • Thermal neutron flux, thermal neutron content and N/G satisfy the IAEA suggested values for NR. • The uniformity of the radiation field of this collimator has been evaluated. • Due to the unique design, there is no need to use a gamma filter. • According to ASTM-E545 standard, this NR beamline achieves category (I) of image quality. [ABSTRACT FROM AUTHOR]

Nearshore sandbars characterize many sandy coasts, and unravelling their dynamics is crucial to understanding nearshore sediment pathways. Sandbar morphologies exhibit complex patterns that can be classified into distinct states. The tremendous progress in data-driven learning in image recognition has recently led to the first automated classification of single-barred beach states from Argus imagery using a Convolutional Neural Network (CNN). Herein, we extend this method for the classification of beach states in a double-barred system. We used transfer learning to fine-tune the pre-trained network of ResNet50. Our data consisted of labelled single-bar time-averaged images from the beaches of Narrabeen (Australia) and Duck (US), complemented by 9+ years of daily averaged low-tide images of the double-barred beach of the Gold Coast (Australia). We assessed seven different CNNs, of which each model was tested on the test data from the location where its training data came from, the self-tests, and on the test data of alternate, unseen locations, the transfer-tests. When the model trained on the single-barred data of both Duck and Narrabeen was tested on unseen data of the double-barred Gold Coast, we achieved relatively low performances as measured by F1 scores. In contrast, models trained with only the double-barred beach data showed comparable skill in the self-tests with that of the single-barred models. We incrementally added data with labels from the inner or outer bar of the Gold Coast to the training data from both single-barred beaches, and trained models with both single- and double-barred data. The tests with these models showed that which bar the labels used for training the model mattered. The training with the outer bar labels led to overall higher performances, except at the inner bar. Furthermore, only 10% of additional data with the outer bar labels was needed for reasonable transferability, compared to the 20% of additional data needed with the inner bar labels. Additionally, when trained with data from multiple locations, more data from a new location did not always positively affect the model’s performance on other locations. However, the larger diversity of images coming from more locations allowed the transferability of the model to the locations from where new training data were added.

Breaking waves constitute one of the main environmental stressors on coastal structures as well as a leading hazard to navigation in nearshore regions. In this paper, we use camera-based methods to measure wave breaking over two jetty systems in the Pacific Northwest; the North jetty of the Columbia River, Washington state, and the two jetties of Coos Bay, Oregon, as well as over three nearby nearshore dredge disposal areas. Data were collected using the “brightest” images and Argus camera technology over a span of 847 days for the Columbia River and 202 days for Coos Bay. Wave breaking over the Columbia north jetty reached 100% for wave heights greater than 3 m and for tides above mid-tide level and was concentrated on the seaward half of the jetty. For Coos Bay, the south jetty saw substantially more breaking than the north one with the worst overtopping occurring mid-jetty and seeming to be associated with sediment transport through the jetty and into the inlet, as well as possibly the navigation channel. Wave breaking at the Coos Bay inlet mouth was enhanced during ebb flow conditions. Argus imagery analysis showed no evidence of enhanced breaking over any of the three dredge material placement sites.

Sleep is a conserved and essential behavior, but its mechanistic and functional underpinnings remain poorly defined. Through unbiased genetic screening in Drosophila, we discovered a novel short-sleep mutant we named argus. Positional cloning and subsequent complementation, CRISPR/Cas9 knock-out, and RNAi studies identified Argus as a transmembrane protein that acts in adult peptidergic neurons to regulate sleep. argus mutants accumulate undigested Atg8a(+) autophagosomes, and genetic manipulations impeding autophagosome formation suppress argus sleep phenotypes, indicating that autophagosome accumulation drives argus short-sleep. Conversely, a blue cheese neurodegenerative mutant that impairs autophagosome formation was identified independently as a gain-of-sleep mutant, and targeted RNAi screens identified additional genes involved in autophagosome formation whose knockdown increases sleep. Finally, autophagosomes normally accumulate during the daytime and nighttime sleep deprivation extends this accumulation into the following morning, while daytime gaboxadol feeding promotes sleep and reduces autophagosome accumulation at nightfall. In sum, our results paradoxically demonstrate that wakefulness increases and sleep decreases autophagosome levels under unperturbed conditions, yet strong and sustained upregulation of autophagosomes decreases sleep, whereas strong and sustained downregulation of autophagosomes increases sleep. The complex relationship between sleep and autophagy suggested by our findings may have implications for pathological states including chronic sleep disorders and neurodegeneration, as well as for integration of sleep need with other homeostats, such as under conditions of starvation.

Rutherford backscattering spectrometry (RBS) in channeling regimes (RBS/C), as an ion beam analysis method performed on a Tandetron 6MV accelerator, generally gives precise information about the structure of crystalline samples by combining RBS signals in the random and aligned configurations. This paper presents details about the design and implementation of tailored RBS/C measurements (coarse and fine) and data evaluation application developed in MATLAB for in situ accelerator control system ARGUS, delivered by High Voltage Engineering Europa BV (HVEE). Additionally, we examined two different ways of stepping during the measurement to reduce the possible inaccuracies related with goniometer's backslash affecting the evaluation of spectra. Verification experiment was carried out using a 2-MeV 4He+-beam directed on a Si (100) substrate. The channeling effect is seen as channeling dips of a lower signal in an otherwise rather homogeneous plane. Implemented application significantly facilitates the RBS/C measurement and analysis of the experiments, and also extends the ion beam analysis portfolio of Advanced Technologies Research Institute. Finally, software is ready-to-use for any Tandetron based ion beam facility with the ARGUS software for accelerator control. [ABSTRACT FROM AUTHOR]

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The Coastal Imaging Research Network (CIRN) is an international group of researchers who exploit signatures of phenomena in imagery of coastal, estuarine, and riverine environments. CIRN participants develop and implement new coastal imaging methodologies. The research objective of the group is to use imagery to gain a better fundamental understanding of the processes shaping those environments. Coastal imaging data may also be used to derive inputs for model boundary and initial conditions through assimilation, to validate models, and to make management decisions. CIRN was officially formed in 2016 to provide an integrative, multi-institutional group to collaborate on remotely sensed data techniques. As of 2021, the network is a collaboration between researchers from approximately 16 countries and includes investigators from universities, government laboratories and agencies, non-profits, and private companies. CIRN has a strong emphasis on education, exemplified by hosting annual “boot camps” to teach photogrammetry fundamentals and toolboxes from the CIRN code repository, as well as hosting an annual meeting for its members to present coastal imaging research. In this review article, we provide context for the development of CIRN as well as describe the goals and accomplishments of the CIRN community. We highlight components of CIRN’s resources for researchers worldwide including an open-source GitHub repository and coding boot camps. Finally, we provide CIRN’s perspective on the future of coastal imaging.

Corneal opacity is a leading cause of reversible blindness worldwide. An electronic corneal prosthesis, or intraocular projector, could potentially restore high-quality vision without need for corneal clarity. Four intraocular projection systems were constructed from commercially available electronic components and encased in biocompatible plastic housing. They were tested for optical properties, biocompatibility, heat dissipation, waterproofing, and accelerated wear. A surgical implantation technique was developed. Intraocular projectors were produced of a size that can fit within the eye. Their optics produce better than 20/200 equivalent visual acuity. MTT assay demonstrated no cytotoxicity of devices in vitro. Temperature testing demonstrated less than 2°C increase in temperature after 1 h. Three devices lasted over 12 weeks under accelerated wear conditions. Implantation surgery was demonstrated via corneal trephination insertion in a cadaver eye. This is the first study to demonstrate and characterize fully functional intraocular projection systems. This technology has the potential to be an important new tool in the treatment of intractable corneal blindness. [ABSTRACT FROM AUTHOR]

This manuscript describes and tests a set of improvements to the cBathy algorithm, published in 2013 by Holman et al. [hereafter HPH13], for the estimation of bathymetry based on optical observations of propagating nearshore waves. Three versions are considered, the original HPH13 algorithm (now labeled V1.0), an intermediate version that has seen moderate use but limited testing (V1.2), and a substantially updated version (V2.0). Important improvements from V1.0 include a new deep-water weighting scheme, removal of a spurious variable in the nonlinear fitting, an adaptive scheme for determining the optimum tile size based on the approximate wavelength, and a much-improved search seed algorithm. While V1.2 was tested and results listed, the primary interest is in comparing V1.0, the original code, with the new version V2.0. The three versions were tested against an updated dataset of 39 ground-truth surveys collected from 2015 to 2019 at the Field Research Facility in Duck, NC. In all, 624 cBathy collections were processed spanning a four-day period up to and including each survey date. Both the unfiltered phase 2 and the Kalman-filtered phase 3 bathymetry estimates were tested. For the Kalman-filtered estimates, only the estimate from mid-afternoon on the survey date was used for statistical measures. Of those 39 Kalman products, the bias, rms error, and 95% exceedance for V1.0 were 0.15, 0.47, and 0.96 m, respectively, while for V2.0, they were 0.08, 0.38, and 0.78 m. The mean observed coverage, the percentage of successful estimate locations in the map, were 99.1% for V1.0 and 99.9% for V2.0. Phase 2 (unfiltered) bathymetry estimates were also compared to ground truth for the 624 available data runs. The mean bias, rms error, and 95% exceedance statistics for V1.0 were 0.19, 0.64, and 1.27 m, respectively, and for V2.0 were 0.16, 0.56, and 1.19 m, an improvement in all cases. The coverage also increased from 78.8% for V1.0 to 84.7% for V2.0, about a 27% reduction in the number of failed estimates. The largest errors were associated with both large waves and poor imaging conditions such as fog, rain, or darkness that greatly reduced the percentage of successful coverage. As a practical mitigation of large errors, data runs for which the significant wave height was greater than 1.2 m or the coverage was less than 50% were omitted from the analysis, reducing the number of runs from 624 to 563. For this reduced dataset, the bias, rms error, and 95% exceedance errors for V1.0 were 0.15, 0.58, and 1.16 m and for V2.0 were 0.09, 0.41, and 0.85 m, respectively. Successful coverage for V1.0 was 82.8%, while for V2.0, it was 90.0%, a roughly 42% reduction in the number of failed estimates. Performance for V2.0 individual (non-filtered) estimates is slightly better than the Kalman results in the original HPH13 paper, and it is recommended that version 2.0 becomes the new standard algorithm.

An imagery-based monitoring system was developed for nearshore topography. The system was based on the wave breaking density observed using a land-based camera and calculated the bathymetry using a depth-controlled breaking wave model. The system was applied to the Fukude-Asaba Coast, Shizuoka Prefecture, where rapid topography change was expected around the outlet of pipeline-based sand bypassing. The validity of the system was verified through comparisons with bathymetry survey data. It is observed that the system can successfully capture the nearshore bathymetry change owing to a typhoon. It is also suggested that the accuracy is sensitive to the incident wave properties and therefore can be improved by introducing selective averaging in which only appropriate imageries were used for the depth estimation depending on the target depth zones. [ABSTRACT FROM AUTHOR]

Purpose of Review: With increasing rates of radical prostatectomy, post prostatectomy incontinence represents a growing challenge for urologists. The artificial urinary sphincter is a highly effective treatment but is invasive, expensive and associated with mechanical failure. Over the past two decades, a plethora of minimally invasive sling devices to treat post prostatectomy incontinence have become available. This review aims to describe the various male slings available and the evidence supporting their use. Recent Findings: Various sling devices are available, each with limited generally low quality evidence reporting their efficacy and safety. Few comparative studies are available. Summary: Evolving mid-term data suggest that male slings are an effective alternative to artificial urinary sphincter for well-selected patients. Further study is needed to provide higher quality particularly comparative evidence to support the continued use of male sling devices. [ABSTRACT FROM AUTHOR]

Abstract: Simulations of nearshore waves using the Steady-State Spectral Wave (STWAVE) Model with temporally-varying bathymetric boundary conditions were undertaken for a period of 11 months at the U.S. Army Corps of Engineers Field Research Facility in Duck, NC. Five sets of bathymetry were tested, two of which were derived from survey data (one evolving with each monthly bathymetric survey, one static) and three were derived from the depth inversion algorithm, cBathy, using Argus optical imagery data updated every half hour. The standard cBathy half-hourly Kalman filtered product was used along with two modified versions that filter depth estimates during large waves prior to being assimilated by the Kalman filter using an offshore wave height threshold or an optically derived wave breaking threshold to reduce bottom boundary condition errors. Bathymetry derived from the modified Kalman filter methods were first validated using continuous in-situ sonic altimeter data, and were found to improve RMSEs relative to the original cBathy bathymetry from an average of about 0.09 m and about 0.15 m offshore and onshore of the sandbar, respectively. Wave model results over the five bathymetric boundary conditions show that the thresholded cBathy bathymetry performs similarly (and slightly better in places) to simulations using an evolving bathymetry as new measurements are available. The wave height predictions using the static bathymetry were approximately equivalent in performance (if not, slightly better in places) to that of the original cBathy, while the evolving surveyed bathymetry had similar performance to the thresholded cBathy method. Highlights • A video-based depth inversion algorithm, cBathy, was evaluated as a temporally varying bottom boundary condition for nearshore wave modeling. • To improve the quality of remotely sensed bottom boundary estimates, bathymetry was only updated when there was minimal wave breaking in the surfzone. • Nearshore wave height predictions over remotely sensed and surveyed bathymetry had similar skill when compared to field observations over 11 months. • During storm events, wave heights were better predicted when the cBathy bottom boundary condition was held static verses updating every half hour. • The modified cBathy boundary condition reduced over-estimations of wave height predictions compared to the original cBathy boundary condition. [ABSTRACT FROM AUTHOR]

Complex two-dimensional nearshore current patterns are generated by feedbacks between sub-aqueous morphology and momentum imparted on the water column by breaking waves, winds, and tides. These non-stationary features, such as rip currents and circulation cells, respond to changing environmental conditions and underlying morphology. However, using fixed instruments to observe nearshore currents is limiting due to the high costs and logistics necessary to achieve adequate spatial sampling resolution. A new technique for processing surf-zone imagery, WAMFlow, quantifies fluid velocities to reveal complex, multi-scale (10 s–1000 s meters) nearshore surface circulation patterns. We apply the concept of a wave-averaged movie (WAM) to measure surf-zone circulation patterns on spatial scales of kilometers in the alongshore and 100 s of meters in the cross-shore. The approach uses a rolling average of 2 Hz optical imagery, removing the dominant optical clutter of incident waves, to leave the residual foam or water turbidity features carried by the flow. These residual features are tracked as quasi-passive tracers in space and time using optical flow, which solves for u and v as a function of image intensity gradients in x, y, and t. Surf zone drifters were deployed over multiple days with varying nearshore circulations to validate the optically derived flow patterns. Root mean square error are reduced to 0.1 m per second after filtering based on image attributes. The optically derived patterns captured longshore currents, rip currents, and gyres within the surf zone. Quantifying nearshore circulation patterns using low-cost image platforms and open-source computer vision algorithms presents the potential to further our understanding of fundamental surf zone dynamics.

Clinical research is making toiling efforts for promotion and wellbeing of the health status of the people. There is a rapid increase in number and severity of diseases like cancer, hepatitis, HIV etc, resulting in high morbidity and mortality. Clinical research involves drug discovery and development whereas clinical trials are performed to establish safety and efficacy of drugs. Drug discovery is a long process starting with the target identification, validation and lead optimization. This is followed by the preclinical trials, intensive clinical trials and eventually post marketing vigilance for drug safety. Softwares and the bioinformatics tools play a great role not only in the drug discovery but also in drug development. It involves the use of informatics in the development of new knowledge pertaining to health and disease, data management during clinical trials and to use clinical data for secondary research. In addition, new technology likes molecular docking, molecular dynamics simulation, proteomics and quantitative structure activity relationship in clinical research results in faster and easier drug discovery process. During the preclinical trials, the software is used for randomization to remove bias and to plan study design. In clinical trials software like electronic data capture, Remote data capture and electronic case report form (eCRF) is used to store the data. eClinical, Oracle clinical are software used for clinical data management and for statistical analysis of the data. After the drug is marketed the safety of a drug could be monitored by drug safety software like Oracle Argus or ARISg. Therefore, softwares are used from the very early stages of drug designing, to drug development, clinical trials and during pharmacovigilance. This review describes different aspects related to application of computers and bioinformatics in drug designing, discovery and development, formulation designing and clinical research.

Nearshore morphology is a key driver in wave breaking and the resulting nearshore circulation, recreational safety, and nutrient dispersion. Morphology persists within the nearshore in specific shapes that can be classified into equilibrium states. Equilibrium states convey qualitative information about bathymetry and relevant physical processes. While nearshore bathymetry is a challenge to collect, much information about the underlying bathymetry can be gained from remote sensing of the surfzone. This study presents a new method to automatically classify beach state from Argus daytimexposure imagery using a machine learning technique called convolutional neural networks (CNNs). The CNN processed imagery from two locations: Narrabeen, New South Wales, Australia and Duck, North Carolina, USA. Three different CNN models are examined, one trained at Narrabeen, one at Duck, and one trained at both locations. Each model was tested at the location where it was trained in a self-test, and the single-beach models were tested at the location where it was not trained in a transfer-test. For the self-tests, skill (as measured by the F-score) was comparable to expert agreement (CNN F-values at Duck = 0.80 and Narrabeen = 0.59). For the transfer-tests, the CNN model skill was reduced by 24–48%, suggesting the algorithm requires additional local data to improve transferability performance. Transferability tests showed that comparable F-scores (within 10%) to the self-trained cases can be achieved at both locations when at least 25% of the training data is from each site. This suggests that if applied to additional locations, a CNN model trained at one location may be skillful at new sites with limited new imagery data needed. Finally, a CNN visualization technique (Guided-Grad-CAM) confirmed that the CNN determined classifications using image regions (e.g., incised rip channels, terraces) that were consistent with beach state labelling rules.

This contribution describes 10 years of observed sandbar and shoreline cross-shore position variability at a meso-tidal, high energy, multiple sandbar beach. To examine relationships between the temporal variability in shoreline/sandbar position with offshore wave forcing, a simple equilibrium model is applied to these data. The analysis presented in this paper shows that the equilibrium model is skilled at predicting the alongshore-averaged, time-varying position of the shoreline (R = 0.82) and the outer sandbar position (R = 0.75), suggesting that these end members of the nearshore sediment system are most strongly influenced by offshore wave forcing in a predictable, equilibrium-forced manner. The middle and inner bars are hypothesized to act as sediment transport pathways between the shoreline and the outer bar. Prediction of these more transient features by an equilibrium model was less skilful. Model coefficients reveal that these two end members (outer bar and shoreline) in the sediment system act in opposite directions to changes in the annual offshore wave forcing. During high wave events, sediment is removed from the shoreline and deposited in the nearshore sediment system with simultaneous landward retreat of the shoreline and offshore migration of the outer sandbar. While both end member features have cycles at annual and inter-annual scales, their respective equilibrium response factor differs by almost a factor of 10, with the shoreline responding around an inter-annual mean (ϕ = 1000 days) and the outer bar responding around a seasonal mean (ϕ = 170 days). The model accurately predicts shoreline response to both mild (e.g. 2004/05, 2008/09) and extreme (e.g. 2005/06, 2009/10) winter storms, as well as their summer recovery. The more mobile and dynamic outer sandbar is well-modelled during typical winters. Summer onshore sandbar migration of the outer bar in 2005 and 2006 is under-predicted as the system transitioned between a triple (winter) and double (summer) sandbar system. The changing of the number of bars present in the system is something that this simple model cannot predict. Analysis of the data suggests that this multi-bar system adjusts its cross-shore seasonal movement when there is a significant change in the sediment supply to the system (e.g., nourishment projects, severe storms). [ABSTRACT FROM AUTHOR]

We explore the potential for using a small unmanned aerial vehicle (UAV) quadcopter to collect long-dwell imagery of the nearshore from which important measurements can be made at low cost and with flexibility. This paper extends the existing topographic imaging approaches that rely on having plentiful ground control spread across the image, to the nearshore case where the bulk of the image is water with no control point and vehicle metadata must be used. The UAV autopilot was found to be capable of excellent station-keeping with the positional errors of 0.20 and 0.53 m (horizontal and vertical) and the viewing angle errors of 0.25° (tilt and roll) and 0.38° (azimuth). The ground position of imaged objects could be found with 0.21-m accuracy. Metadata returned by the UAV on camera position was accurate at 5 m, and the camera roll could be assumed to be 0°, reducing the ground control requirements to two, or even one location. Even under this extreme simplification, ground position errors averaged only 10 m but were worse for cases when only control points near to the UAV were used. A model for the visual contrast of waves when viewed from different angles found that large tilts are important but, in contrast to theory, that there was little dependence on the viewing azimuthal angle. Derived Argus products agreed well with the same products collected using a traditional fixed Argus station. UAVs appear to be a very promising alternate to fixed camera systems if limited duration sampling is adequate. [ABSTRACT FROM PUBLISHER]

Data handling and tabulation are a time-consuming job when writing appendices for clinical study reports. The authors have developed an automated appendix generation system (ARGUS) conforming to the CDISC/SDTM standard using SAS (version 9.3) and R (version 3.3.1: for PK plot generation). It consists of the one main program and three subprograms. The program runs to convert a database file into an appendix document with about 100 tables and plots in MS Word format within one min after pressing the submit button under common desktop environments. We found that tasks of constructing appendices for a typical 2×2 crossover design study that have taken our team about 8 days were completed within 6 or 7 hours using the ARGUS system. [ABSTRACT FROM AUTHOR]

ABSTRACT The backshore zone is transitional environment strongly affected by ocean, air and sand movements. On dissipative beaches, the formation of ephemeral dunes over the backshore zone plays significant contribution in the beach morphodynamics and sediment budget. The aim of this work is to describe a novel method to identify ephemeral dunes in the backshore region and to discuss their morphodynamic behavior. The beach morphology is identified using Argus video imagery, which reveals the behavior of morphologies at Cassino Beach, Rio Grande do Sul, Brasil. Daily images from 2005 to 2007, topographic profiles, meteorological data, and sedimentological parameters were used to determine the frequency and pervasiveness of these features on the backshore. Results indicated that coastline orientation relative to the dominant NE and E winds and the dissipative morphological beach state favored aeolian sand transport towards the backshore. Prevailing NE winds increase sand transportation to the backshore, resulting in the formation of barchans, transverse, and barchanoid-linguiod dunes. Precipitation inhibits aeolian transport and ephemeral dune formation and maintains the existing morphologies during strong SE and SW winds, provided the storm surge is not too high.

Narrabeen-Collaroy Beach, located on the Northern Beaches of Sydney along the Pacific coast of southeast Australia, is one of the longest continuously monitored beaches in the world. This paper provides an overview of the evolution and international scientific impact of this long-term beach monitoring program, from its humble beginnings over 40 years ago using the rod and tape measure Emery field survey method; to today, where the application of remote sensing data collection including drones, satellites and crowd-sourced smartphone images, are now core aspects of this continuing and much expanded monitoring effort. Commenced in 1976, surveying at this beach for the first 30 years focused on in-situ methods, whereby the growing database of monthly beach profile surveys informed the coastal science community about fundamental processes such as beach state evolution and the role of cross-shore and alongshore sediment transport in embayment morphodynamics. In the mid-2000s, continuous (hourly) video-based monitoring was the first application of routine remote sensing at the site, providing much greater spatial and temporal resolution over the traditional monthly surveys. This implementation of video as the first of a now rapidly expanding range of remote sensing tools and techniques also facilitated much wider access by the international research community to the continuing data collection program at Narrabeen-Collaroy. In the past decade the video-based data streams have formed the basis of deeper understanding into storm to multi-year response of the shoreline to changing wave conditions and also contributed to progress in the understanding of estuary entrance dynamics. More recently, ‘opportunistic’ remote sensing platforms such as surf cameras and smartphones have also been used for image-based shoreline data collection. Commencing in 2011, a significant new focus for the Narrabeen-Collaroy monitoring program shifted to include airborne lidar (and later Unmanned Aerial Vehicles (UAVs)), in an enhanced effort to quantify the morphological impacts of individual storm events, understand key drivers of erosion, and the placing of these observations within their broader regional context. A fixed continuous scanning lidar installed in 2014 again improved the spatial and temporal resolution of the remote-sensed data collection, providing new insight into swash dynamics and the often-overlooked processes of post-storm beach recovery. The use of satellite data that is now readily available to all coastal researchers via Google Earth Engine continues to expand the routine data collection program and provide key insight into multi-decadal shoreline variability. As new and expanding remote sensing technologies continue to emerge, a key lesson from the long-term monitoring at Narrabeen-Collaroy is the importance of a regular re-evaluation of what data is most needed to progress the science.

This review focuses on a description of the Argus II retinal prosthesis system (Argus II; Second Sight Medical Products, Sylmar, CA) that was approved for humanitarian use by the FDA in 2013 in patients with retinitis pigmentosa with bare or no light perception vision. The article describes the components of Argus II, the studies on the implant, and future directions. [ABSTRACT FROM AUTHOR]