Marker Tracking Research Articles

Superimposed anatomical structures in Augmented Reality

The paper considers an approach to visualization of anatomical structures using augmented reality, which allows for more accurate planning of operations and reduces the degree of surgical intervention. To achieve this goal, a technology was developed using a frame with a volumetric optical marker, which allows you to correlate a virtual 3D model with the patient. As a result, it was possible to achieve an accurate positioning of the 3D model and obtain a reliable visualization of the location of internal anatomical structures. At the same time, the parallel application of spatial mapping technology allows you to fix the 3D model at a certain point in space and, in case of loss of marker tracking, save the correct location of the 3D model, taking into account that the patient is in a stationary state. This approach can be effectively applied in surgery, if it is possible to fix the skeleton relative to any bone structure. Options for surgical intervention can be different, starting with the installation of prostheses, ending with the removal of cancerous tumors. The article discusses a project to develop a technology for using augmented reality in planning and conducting maxillofacial surgery. The capabilities of the technology, as well as the prospects for its use, are highlighted.

Associations among Household Animal Ownership, Infrastructure, and Hygiene Characteristics with Source Attribution of Household Fecal Contamination in Peri-Urban Communities of Iquitos, Peru.

.Using previously validated microbial source tracking markers, we detected and quantified fecal contamination from avian species and avian exposure, dogs, and humans on household cooking tables and floors. The association among contamination, infrastructure, and socioeconomic covariates was assessed using simple and multiple ordinal logistic regressions. The presence of Campylobacter spp. in surface samples was linked to avian markers. Using molecular methods, animal feces were detected in 75.0% and human feces in 20.2% of 104 households. Floors were more contaminated than tables as detected by the avian marker Av4143, dog marker Bactcan, and human marker Bachum. Wood tables were consistently more contaminated than non-wood surfaces, specifically with the mitochondrial avian markers ND5 and CytB, fecal marker Av4143, and canine marker Bactcan. Final multivariable models with socioeconomic and infrastructure characteristics included as covariates indicate that detection of avian feces and avian exposure was associated with the presence of chickens, maternal age, and length of tenancy, whereas detection of human markers was associated with unimproved water source. Detection of Campylobacter in surface samples was associated with the avian fecal marker Av4143. We highlight the critical need to detect and measure the burden of animal fecal waste when evaluating household water, hygiene, and sanitation interventions, and the possibility of decreasing risk of exposure through the modification of surfaces to permit more effective household disinfection practices. Animals may be a more important source of household fecal contamination than humans in many low-resource settings, although interventions have historically focused almost exclusively on managing human waste.

Mobile application for quantification of the pivot shift examination: intraoperative usability and utility during real-world deployment

ObjectiveThe objective of the current study was to evaluate the utility and ease of use of a novel non-invasive tablet-based application for quantification of the pivot shift (QPS) in a multicentre setting.MethodsNine senior orthopaedic surgeons were recruited from academic medical centres and enrolled a total of 90 subjects. All surgeons received video and electronic training on how to perform QPS measurement using a novel tablet-based visual tracking system. Skin markers were used for visual tracking. Each orthopaedic surgeon performed a pivot shift test and obtained a QPS measurement for 10 subjects with known anterior cruciate ligament (ACL) injuries. Anterior translation of the lateral tibial compartment during the reduction event (in millimetre) was recorded. After all subjects were evaluated, the surgeons completed a survey about the ease of use, utility and willingness to use the mobile-based application in clinical practice. All automated visual tracking used to calculate anterior translation of the lateral tibial compartment was manually evaluated to ensure accurate tracking of skin markers. Statistical comparison was made between groups using Student’s t-test with significance defined as p<0.05.ResultsThe results showed that there is adequate tracking of skin markers to provide a QPS measurement across multiple academic medical centres and surgeons in only 70% of subjects. In 27 of 90 subjects, there were tracking errors which resulted in an invalid QPS measurement. Tracking errors were due to background noise, including objects in the room which were the same colour as the skin markers or use of skin preparation solution similar in colour to the skin markers. The QPS measurement was 3.2±1.8 mm, 2.4±1.3 mm in isolated ACL deficiency, and 3.2±2.0 mm with combined ACL and meniscus injury (not significant). There was significant variation among the QPS measurements of different surgeons (p=0.008).ConclusionThis study showed that mobile-based QPS measurement software can be used intraoperatively to allow surgeons greater objective feedback regarding the rotatory laxity of the knee prior to and following ACL reconstruction. Software upgrades with improved real-time feedback could help prevent errors in measurement and improve utility of QPS for assessment of injury severity in subjects.Level of evidenceLevel III.

Intelligent Test Paper Generation Based on Dynamic Programming Algorithm

This paper describes the problem of intelligent paper grouping and its mathematical model. By optimizing and improving the traditional dynamic programming algorithm, its space complexity is reduced from O(nb) to O(b). At the same time, the flexibility of dynamic programming algorithm is increased by using marker function and tracking algorithm, and the result composition is tracked to obtain the optimal solution. Finally, through several experiments, the improved dynamic programming algorithm is compared with the greedy algorithm and brute force algorithm, and it is found that the improved dynamic programming algorithm has a very good result and is with high efficiency when applied to the simple test paper. It is the most recommended algorithm among the two algorithms compared in this paper.

Full-scale deformation measurements of a wind turbine rotor in comparison with aeroelastic simulations

Abstract. The measurement of deformation and vibration of wind turbine rotor blades in field tests is a substantial part of the validation of aeroelastic codes. This becomes highly important for modern rotors as the rotor size increases, which comes along with structural changes, resulting in very high flexibility and coupling between different vibration modes. However, performing full-scale field measurements for rotor blade deformation is not trivial and requires high temporal and spatial resolution. A promising deformation measurement technique is based on an optical method called digital image correlation (DIC). Recently, DIC measurements on a Siemens Gamesa SWT-4.0-130 test turbine were performed on the tip of all blades in combination with marker tracking at the hub for the first time with synchronised measurement of the inflow conditions by a ground-based lidar. As the turbine was additionally equipped with strain gauges in the blade root of all blades, the DIC results can be directly compared to the actual prevailing loads to validate the measurement method. In the end, an example for a comparison of the measured deformations and torsion with aeroelastic simulations is shown in the time and frequency domain. All in all, DIC shows very good agreement with comparative measurements and simulations, which shows that it is a suitable method for measurement of deformation and torsion of multi-megawatt wind turbine rotor blades.

Human fecal contamination of the domestic environment and child enteric infection in urban Maputo, Mozambique

Background: Children living in settings with poor sanitation infrastructure are commonly infected by a range of enteric pathogens that can be transmitted through multiple pathways in the domestic environment. Host-associated microbial source tracking (MST) markers are increasingly used to identify fecal contamination, but the relationship between MST markers and infection risk remains poorly characterized.Methods: We assessed fecal contamination in samples of water, soil, and food preparation surfaces from household clusters (compounds) in low-income neighborhoods of urban Maputo, Mozambique through two cross-sectional surveys conducted approximately 12 months apart. Child stool was analyzed for 23 enteric pathogens from four classes: nine bacteria, three viruses, and three protozoan parasites by multiplex reverse-transcription polymerase chain reaction (RT-PCR) and eight soil transmitted helminths (STH) by Kato-Katz. Human fecal contamination was determined by real-time PCR (qPCR) targeting two human-associated MST markers, HF183/BacR287 and Mnif, and Escherichia coli was assessed by culture and qPCR to indicate non-specific fecal contamination. We estimated associations between fecal indicators in each sample type and infection by pathogen class and number of co-infections using multilevel logistic and negative binomial regression, respectively, with compound-varying intercepts.Results: Samples were collected from 193 children and 71 compounds, with 112 children contributing stool in both survey rounds. Prevalence of enteric infection was high, with 86-92% of children in each survey round shedding at least 1 pathogen, but most were asymptomatic with 8-12% reporting diarrhea in the preceding 7 days. Contamination of drinking water source demonstrated weak associations with bacterial (aOR: 2.2; 95% CI: 1.0-4.4) and viral (aOR: 1.9; 95% CI: 1.0-3.6) infections for increasing E. coli density, while detection of human-associated HF183 in latrine soil was weakly associated with reduced odds of protozoan infection (aOR: 0.7; 95% CI: 0.4-1.0).Conclusions: Measures of fecal contamination were largely unassociated with enteric infection prevalence or number of co-infections.

Inter- and Intra-Fraction Movement of Prostate and Seminal Vesicles: Analysis from MR-Guided Hypo-Fractioned Radiotherapy

Modest to extreme hypo-fractionated radiotherapy has become standard of care for low to intermediate grade prostate cancer. With advances in soft-tissue image verification such as MR-guided has led to a reduction in PTV margins compared to conventional radiotherapy. Therefore, a detailed knowledge of prostate movement is required to ensure that PTV margins remain valid. Tracking of fiducial markers has been used previously to assess prostate motion during radiotherapy, but this cannot assess all regions of the prostate or a change in prostate shape. MR-guided radiotherapy gives a much higher degree of tracking accuracy and greater precision to identify intra- and inter-fraction prostate movement. This prospective study aims to determine inter- and intra-fraction movement of prostate and seminal vesicles (SV) and its impact on daily adaptation by evaluating changes in dominant intra-prostatic lesions (DIL) which occur during radiotherapy courses. Twenty patients with low to intermediate grade prostate cancer were treated with 36.25 Gy in 5 fractions using daily adapted, MR-guided radiotherapy. The prostate clinical target volume (CTV) and organs at risk (OARs) were re-contoured each fraction. The variation in prostate shape from the baseline planning MR scan was compared with each fraction to assess the inter-fraction movement. Tracking markers were set at the level of seminal vesicles root, apex of prostate and anterior and posterior aspects of the prostate to measure intra-fraction movement. Average treatment time for each adapted fraction was under 60 minutes. Initial results show a greater degree of movement and change of shape of SV compared to the apical region. The position of the prostate also altered considerably on the live cine-MRI compared to the pre-verification MRI image. Daily adaptation demonstrated significant geometrical alteration of SV position on an inter-fraction basis. A detailed model of inter- and intra-fraction prostate motion allows validation of the reduced PTV margins used in hypo-fractionated radiotherapy.

Real-time Linear Fiducial Marker Tracking in Respiratory-gated Radiotherapy With a Deep Neural Network

To achieve high treatment accuracy in respiratory-gated radiotherapy, it is important to obtain a mobile tumor position in 3D space. Instead of tracking a tumor, Mylonas et al. proposed the method of detecting linear fiducial markers in fluoroscopic images with convolutional neural network (CNN) models (Mylonas et al. Med Phys. 2019; 46 2286-97). However, it is difficult to prepare the many marker images required for training the model. Therefore, we propose a method to train a CNN model with 3D simulated training marker images. Furthermore, the proposed model tracks the markers in a pair of orthogonal fluoroscopic images. Owing to no need of taking fluoroscopic images of implanted markers, our method can build the model for the arbitrary-shaped marker more efficiently. To make training images, we cropped patch images, whose size was 31x31x2 pixels, from the position such that 3D points were projected onto the paired fluoroscopic images of non-implanted patients. These patch images were labeled “not-marker images”. The simulated “marker images” were generated by drawing the shape of the marker, which was virtually put at the 3D points with any posture, projected onto the patch images. We built a CNN model by training 1000 marker and not-marker images. The model consisted of four convolutional layers with two max-pooling layers and lastly a fully connected layer to output the marker likelihood. Each convolutional layer has a batch normalization layer and a rectified linear unit. For tracking the marker, the trained model calculated the likelihood of each 3D point by inputting the cropped image from where the 3D point was projected onto the fluoroscopic images and the marker position in 3D space was determined with the likelihood-weighted average of the positions. To reduce the number of calculated 3D points, we used a particle filter. The method was evaluated using three liver fluoroscopic image datasets with an implanted linear fiducial marker 0.5 mm in diameter by 3.0 mm in length. Each dataset consisted of at least one respiratory phase. The positional error of each marker was calculated between the tracked position and the ground truth position in 3D space. In addition, the calculation time was measured on a workstation (Intel Xeon® CPU @ 3.6 GHz). The mean positional error for three patients was measured to be 0.32 mm with a standard deviation of 0.17 mm. The worst positional error was 1.1 mm. For the first, second and third patient, the mean errors were 0.38, 0.26 and 0.32 mm with a standard deviation of 0.16, 0.13 and 0.16 mm, respectively. The calculation time was within 50.4 milliseconds per frame. We presented real-time linear fiducial marker tracking for respiratory-gated radiotherapy with a DNN framework. We performed experiments involving three live patients with our proposed method and obtained high accuracy and short computation time.

Methods to measure and track population perception and support within a manual wargame

The outcomes of military campaigns depend to a large extent on the support of local and other wider population groups, so it is important to understand their perceptions. Here we briefly describe the approach used to represent support for organizations and factions in a professional wargame designed to represent military campaigns. This specific approach was developed originally using a simple marker track system that used a basic quantified set of relationships between military campaign effects and changes to the track levels. This marker track system was developed for military campaign wargames in the UK as a means to portray support or dissent in population groups relevant to the operations, but there was originally no mechanism to drive changes other than by expert judgment. Our improved approach continues the use of marker tracks but attempts to develop a more defensible method based on Maslow’s hierarchy of needs for linking events to changes and levels on the tracks. We conducted experiments to quantify the relative importance of each element in Maslow’s hierarchy. We then continued by conducting a further experiment to identify the impact of a set of effects seen in a wargame against the Maslow elements. This has led to a set of quantified scores that may be used to drive the modifications to the marker tracks when wargame events occur. These scores are based on our initial experiments and may be updated for a specific application, perhaps for a specific setting or location in the world. The revised or enhanced approach aims to produce a transparent solution that can be understood by a military or security analyst, thus facilitating refinement, updating, and change.

Identification and cross-validation of genetic loci conferring resistance to Septoria nodorum blotch using a German multi-founder winter wheat population

Key messageWe identified allelic variation at two major loci, QSnb.nmbu-2A.1 and QSnb.nmbu-5A.1, showing consistent and additive effects on SNB field resistance. Validation of QSnb.nmbu-2A.1 across genetic backgrounds further highlights its usefulness for marker-assisted selection.Septoria nodorum blotch (SNB) is a disease of wheat (Triticum aestivum and T. durum) caused by the necrotrophic fungal pathogen Parastagonospora nodorum. SNB resistance is a typical quantitative trait, controlled by multiple quantitative trait loci (QTL) of minor effect. To achieve increased plant resistance, selection for resistance alleles and/or selection against susceptibility alleles must be undertaken. Here, we performed genetic analysis of SNB resistance using an eight-founder German Multiparent Advanced Generation Inter-Cross (MAGIC) population, termed BMWpop. Field trials and greenhouse testing were conducted over three seasons in Norway, with genetic analysis identifying ten SNB resistance QTL. Of these, two QTL were identified over two seasons: QSnb.nmbu-2A.1 on chromosome 2A and QSnb.nmbu-5A.1 on chromosome 5A. The chromosome 2A BMWpop QTL co-located with a robust SNB resistance QTL recently identified in an independent eight-founder MAGIC population constructed using varieties released in the United Kingdom (UK). The validation of this SNB resistance QTL in two independent multi-founder mapping populations, regardless of the differences in genetic background and agricultural environment, highlights the value of this locus in SNB resistance breeding. The second robust QTL identified in the BMWpop, QSnb.nmbu-5A.1, was not identified in the UK MAGIC population. Combining resistance alleles at both loci resulted in additive effects on SNB resistance. Therefore, using marker assisted selection to combine resistance alleles is a promising strategy for improving SNB resistance in wheat breeding. Indeed, the multi-locus haplotypes determined in this study provide markers for efficient tracking of these beneficial alleles in future wheat genetics and breeding activities.

Implementation of escape room system based on augmented reality involving deep convolutional neural network

Escape room is a live-action adventure game, where the players search clues, solve puzzles and achieve the assigned tasks. This paper proposed a novel escape room system combining augmented reality and deep learning technology. The system adopts a client–server architecture and can be divided into the server module, the smart glasses module and the player–hardware interaction module. The player–hardware interaction module consists of subsystems each of which includes a Raspberry Pi 3. HoloLens is used as the smart glasses in the experiment of the paper. The server communicates with all the Raspberry Pis and HoloLens through TCP/IP protocol and manages all the devices to achieve the game flow by following the process timeline. The smart glasses module provides two display modes, i.e., the AR 3D models display and the 2D text clues display. In the first mode, the SDK Vuforia is used for detection and tracking of markers. In the second mode, the scene images captured by HoloLens camera are sent to the pre-trained image classifier based on deep convolutional neural network. Considering both the image category and the game status value, the server decides the text clue image to be displayed on HoloLens. The accuracy of the image classification model reaches 94.9%, which can be correctly classified for a certain rotation angle and partial occlusion. The integration of AR, deep learning, electronics and escape room games opens up exciting new directions for the development of escape room. Finally, a built mini-escape room is analyzed to prove that the proposed system can support more complicated narratives showing the potential of achieving immersion.

Relationships among microbial indicators of fecal pollution, microbial source tracking markers, and pathogens in Costa Rican coastal waters

Tropical coastal waters are understudied, despite their ecological and economic importance. They also reflect projected climate change scenarios for other climate zones, e.g., increased rainfall and water temperatures. We conducted an exploratory microbial water quality study at a tropical beach influenced by sewage-contaminated rivers, and tested the hypothesis that fecal microorganisms (fecal coliforms, enterococci, Clostridium perfringens, somatic and male-specific coliphages, pepper mild mottle virus (PMMoV), Bacteroides HF183, norovirus genogroup I (NoVGI), Salmonella, Cryptosporidium and Giardia) would vary by season and tidal stage. Most microorganisms’ concentrations were greater in the rainy season; however, NoVGI was only detected in the dry season and Cryptosporidium was the only pathogen most frequently detected in rainy season. Fecal indicator bacteria (FIB) levels exceeded recreational water quality criteria standards in >85% of river samples and in <50% of ocean samples, regardless of the FIB or regulatory criterion. Chronic sewage contamination was demonstrated by detection of HF183 and PMMoV in 100% of river samples, and in >89% of ocean samples. Giardia, Cryptosporidium, Salmonella, and NoVGI were frequently detected in rivers (39%, 39%, 26%, and 39% of samples, respectively), but infrequently in ocean water, particularly during the dry season. Multivariate analysis showed that C. perfringens, somatic coliphage, male-specific coliphage, and PMMoV were the subset of indicators that maximized the correlation with pathogens in the rivers. In the ocean, the best subset of indicators was enterococci, male-specific coliphage, and PMMoV. We also executed redudancy analyses on environmental parameters and microorganim concentrations, and found that rainfall best predicted microbial concentrations. The seasonal interplay of rainfall and pathogen prevalence undoubtedly influences beach users’ health risks. Relationships are likely to be complex, with some risk factors increasing and others decreasing each season. Future use of multivariate approaches to better understand linkages among environmental conditions, microbial predictors (fecal indicators and MST markers), and pathogens will improve prediction of high-risk scenarios at recreational beaches.

Thermo-fluid simulation using particle method based on hand-pouring motion in casting process

Casting simulators are widely used to evaluate casting designs. However, most simulators using conventional methods such as FDM or FEM entail difficulty in evaluating casting designs sufficiently based on ladle motions or an operator’s pouring motion because they do not readily accommodate dynamically changing wall boundaries and do not easily accommodate the ladle motion as input. For this study, the authors extended the thermo-fluid simulation based on particle method, an earlier proposed method, so that the measured ladle motion can be input. The authors measured an operator’s ladle motion using marker tracking technique for AR and executed thermo-fluid simulations using the proposed simulation method. Comparisons of the experiments and the simulation results clarified that the proposed method can accurately predict flow behaviors of the molten metal resulting from the ladle motion. Comparisons of the proposed simulation and the simulation with a conventional simulation using the inflow condition of the constant flow rate clarified the importance of executing the simulation based on the ladle motion for high-accuracy prediction of molten metal behavior.

Effect of Fiber Orientation on Nonlinear Damping and Internal Microdeformation in Short-Fiber-Reinforced Natural Rubber

Nonlinear damping with respect to vibration amplitude is particularly important in mechanical dynamics. The addition of short fibers to damping materials is considered to result in strong nonlinear damping due to interfacial peeling at the edges of the fibers. However, little has been reported on the occurrence of nonlinear damping in short-fiber reinforced rubber due to compounding difficulties. In this study, we investigated the relationship between the damping characteristics and deformation behavior of microdeformed short-fiber reinforced rubber by X-ray computed tomography (CT). We prepared a damping material with a natural rubber (NR) matrix and micrometer-sized polyethylene terephthalate (PET) fiber filler. The loss factor was identified by dynamic mechanical analysis, and three-dimensional strain maps were obtained using marker tracking in the CT data. The addition of 5 wt% PET fibers to NR resulted in an increase in the loss factor. Experimentally, we found that the nonlinear damping of the composite rubber is affected by the peeling of the filler/matrix interface and the strain inside the material.

Correction to: PDCAT: a framework for fast, robust, and occlusion resilient fiducial marker tracking

In the original publication of the article, the family name of the 1st author has been changed to Araar.

Infrared marker tracking with the HoloLens for neurosurgical interventions

Abstract Patient tracking is an essential part in a surgical augmented reality system for correct hologram to patient registration. Augmented reality can support a surgeon with visual assistance to navigate more precisely during neurosurgical interventions. In this work, a system for patient tracking based on infrared markers is proposed. These markers are widely used in medical applications and meet the special medical requirements such as sterilizability. A tracking accuracy of 0.76 mm is achieved when using the near field reflectivity and depth sensor of the HoloLens. On the HoloLens a performance of 55–60 fps is reached, which grants a sufficiently stable placement of the holograms in the operating room.

Klasifikasi Motif Citra Kain Sutera Bugis Mengunakan Metode Markerless Marker

Silk is one of the national cultural heritage with various motifs and patterns. This research aims to detect and classify the image of the silk cloth based on motive. This research uses Augemented Reality technology with Markerless Marker Tracking method. To display a 3D object, the proposed method uses a special pattern as a marker to recognize the fabric type. As a research sample, the authors used 10 types of bugis silk motifs. From the test results found that markers can detect fabric motifs in bright rooms and undetectable markers in dim rooms. The best distance in detecting markers is 10 cm – 50 cm. Meanwhile at a distance of 110 cm, the marker cannot be detected.

Improved Position Accuracy of Foot-Mounted Inertial Sensor by Discrete Corrections from Vision-Based Fiducial Marker Tracking.

In this paper, we present a novel pedestrian indoor positioning system that uses sensor fusion between a foot-mounted inertial measurement unit (IMU) and a vision-based fiducial marker tracking system. The goal is to provide an after-action review for first responders during training exercises. The main contribution of this work comes from the observation that different walking types (e.g., forward walking, sideways walking, backward walking) lead to different levels of position and heading error. Our approach takes this into account when accumulating the error, thereby leading to more-accurate estimations. Through experimentation, we show the variation in error accumulation and the improvement in accuracy alter when and how often to activate the camera tracking system, leading to better balance between accuracy and power consumption overall. The IMU and vision-based systems are loosely coupled using an extended Kalman filter (EKF) to ensure accurate and unobstructed positioning computation. The motion model of the EKF is derived from the foot-mounted IMU data and the measurement model from the vision system. Existing indoor positioning systems for training exercises require extensive active infrastructure installation, which is not viable for exercises taking place in a remote area. With the use of passive infrastructure (i.e., fiducial markers), the positioning system can accurately track user position over a longer duration of time and can be easily integrated into the environment. We evaluated our system on an indoor trajectory of 250 m. Results show that even with discrete corrections, near a meter level of accuracy can be achieved. Our proposed system attains the positioning accuracy of 0.55 m for a forward walk, 1.05 m for a backward walk, and 1.68 m for a sideways walk with a 90% confidence level.

Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI)

Hydro-meteorological conditions facilitate transport of fecal indicator bacteria (FIB) to the nearshore environment, affecting recreational water quality. North Beach (Racine, Wisconsin, United States), is an exemplar public beach site along Lake Michigan, where precipitation-mediated surface runoff, wave encroachment, stormwater and tributary outflow were demonstrated to contribute to beach advisories. Multiple restoration actions, including installation of a stormwater retention wetland, were successfully deployed to improve recreational water quality. Implementation of molecular methods (e.g. human microbial source tracking markers and Escherichia coli (E. coli) qPCR) assisted in identifying potential pollution sources and improving public health response time. However, periodic water quality failures still occur. As local beach managers reassess restoration measures in response to climatic changes, use of expanded microbial methods (including bacterial community profiling) may contribute to a better understanding of these dynamic environments. In this 2-year study (2015 and 2019), nearshore/offshore Lake Michigan, stormwater, and tributary samples were collected to determine if, 1) the constructed wetland (~50 m from the shoreline) continued to provide stormwater separation/retention and 2) mixing between onshore sources, Root River and Lake Michigan, was increasing due to rising precipitation/lake levels. Monthly rainfall totals were 1.5× higher in 2019 than 2015, coinciding with a 0.63 m lake-level rise. The prevalence of more intense, onshore winds also increased, facilitating interaction between potential reservoirs of FIB with nearshore water through wind driven waves and lake intrusion, e.g. beach sands and the adjacent Root River. While a strong relationship existed between wet weather wetland and North Beach nearshore E. coli concentrations (all sites), bacterial communities were strikingly different. Conversely, bacterial community overlap existed between the Root River mouth and nearshore/offshore sites. These results suggest the constructed wetland can accommodate the climate-related changes observed in this study. Future restoration activities could be directed towards upstream tributary sources in order to minimize microbial contaminants entering Lake Michigan.

Augmented Reality-assisted Pedicle Instrumentation: Versatility Across Major Instrumentation Sets.

Laboratory investigation with phantom spine models. The aim of this study was to demonstrate the ability of Augmented Reality system to track instruments from different companies without major modifications. Augmented Reality is an emergent technology with applications in industrial, military, gaming, and medical fields. AR applications in Spine surgery are actively being developed. Features of headpiece ergonomics, digital processing power, intuitive interface, and reliable accuracy are being optimized for successful adaptation of technology into the field. System versatility across various instrumentation sets is important for cost-effectiveness and efficiency in application. In this project, five phantom spine models were instrumented L1-S1 with pedicle screws from five major companies. AR assistance was used for all. Each screwdriver was equipped with a generic 3D printed navigation marker for tracking. Every instrumentation set was successfully paired with AR navigation imaging. Sixty pedicle screws were inserted with an average time of 1.6 min/screw. There was an evidence of learning curve with fastest time achieved of 1 min/screw. All five systems had equivocal radiographic outcomes. There were two breached screws (3%). Any currently available instrumentation set can readily pair for tracking with Augmented Reality system. Active tracking of the drivers allowed for improved accuracy making AR system very attractive as an adjunct to the current instrumentation techniques. 3.