The Small Town Girl

https://digitalcommons.library.umaine.edu/mmb-vp/4305/thumbnail.jp

I\u27m A\u27 Looking For My Ten : I Don\u27t Want to See Caesar

https://digitalcommons.library.umaine.edu/mmb-vp/1575/thumbnail.jp

Arab Love Song : (Marie Cahill\u27s)

https://digitalcommons.library.umaine.edu/mmb-vp/1056/thumbnail.jp

Inside-out Infrared Marker Tracking via Head Mounted Displays for Smart Robot Programming

Intuitive robot programming through use of tracked smart input devices relies on fixed, external tracking systems, most often employing infra-red markers. Such an approach is frequently combined with projector-based augmented reality for better visualisation and interface. The combined system, although providing an intuitive programming platform with short cycle times even for inexperienced users, is immobile, expensive and requires extensive calibration. When faced with a changing environment and large number of robots it becomes sorely impractical. Here we present our work on infra-red marker tracking using the Microsoft HoloLens head-mounted display. The HoloLens can map the environment, register the robot on-line, and track smart devices equipped with infra-red markers in the robot coordinate system. We envision our work to provide the basis to transfer many of the paradigms developed over the years for systems requiring a projector and a tracked input device into a highly-portable system that does not require any calibration or special set-up. We test the quality of the marker-tracking in an industrial robot cell and compare our tracking with a ground truth obtained via an ART-3 tracking system.Comment: As accepted to the 5th International Workshop on Virtual, Augmented, and Mixed Reality for HR

Determination of clothing microclimate volume

Human heat transfer depends on the amount of ventilation between the skin and the clothing layers, which in turn depends on the microclimate volume (7). This volume is hard to quantify. The traditional method, developed by Crockford et al. (4) and further in Birnbaum and Crockford (1) and Sullivan et al. (10) utilises a vacuum oversuit to evacuate and measure the quantity of air trapped in the microenvironment. This method is cumbersome and an alternative may be found in a model approach or using 3D whole body scans. Lee and Hong (8) endeavoured to ascertain the relationship between the insulation value of the clothing ensemble and the air volume measured by using phase-shifting moiré topography. They determined the microclimate volume between a manikin and a T-shirt. This technique was time efficient and accurate, but it was not reported if this technique could be used on humans and how the results compared to the traditional technique of microclimate volume measurement. A third technique to estimate the microclimate volume assumes that the body is represented by a series of cylinders. The circumference of each segment is measured with and without clothing, allowing the volume of each to be calculated. The method was adopted from Lotens and Havenith (9) and is fast and simple. It is the purpose of this study to compare the reliability and reproducibility of the vacuum suit method, scanning method and cylinder model to determine microclimate volume

Endothermic salts integrated in impermeable suits do not reduce heat strain during exercise

Wearing impermeable garments during work inherently leads to heat strain, even in cold environments [1]. Phase change materials (mainly paraffin’s or salt [4]) may be used as a thermal buffer (e.g. [2]) to reduce initial heat stress. Salts can also be used to absorb sweat, which may enhance the cooling power from the skin. Recently, specific encapsulated salts utilising KSCN (potassium thiocyanate) have been developed that consume energy when the KSCN dissolves in water. The heat consumed when the KSCN (present inside 150 g of capsules containing 60% KSCN salt) dissolves in water is 22410 J (249 J/g * 60% * 150 g). When this solving takes place over a period of 30 minutes, the average power transfer is 12 W. One (1) g of KSCN-containing capsules absorbs close to 1 g of moisture. If we assume that 150 g sweat extra can be evaporated from the skin, this yields an extra cooling power of 182 W for 30 minutes. However this evaporated water from the skin is subsequently absorbed by the KSCN in the capsules. During this absorption from the gas phase, the condensation heat is released to the KSCN salt: about 182 W for 30 minutes. However, we hypothesise that this condensation heat will be partly transferred to the body and partly to the environment [3], providing a net benefit to the body. Thus, the total cooling effect due to the salt capsules is composed of two parts: • The cooling effect of about 12 W due to the heat consumption by the dissolving of the salts in water; • The cooling effect of maximal 182 W, which equals the difference between the evaporative heat and the condensation heat. The latter is generated in the salt capsules that transfer part of the heat to the environment. The overall cooling effect should therefore be in between 12 W and 194 W. The purpose of our study was to test the efficacy of a KSCN-based absorbing salt as a PCM for use within impermeable protective clothing. We tested the PCM during 20 min of moderate exercise in a hot (35°C, 40% relative humidity) environment, and hypothesized that thermal strain would be lower in the PCM compared to the non-PCM condition

Classification of Event-Related Potentials Associated with Response Errors in Actors and Observers Based on Autoregressive Modeling

Event-Related Potentials (ERPs) provide non-invasive measurements of the electrical activity on the scalp related to the processing of stimuli and preparation of responses by the brain. In this paper an ERP-signal classification method is proposed for discriminating between ERPs of correct and incorrect responses of actors and of observers seeing an actor making such responses. The classification method targeted signals containing error-related negativity (ERN) and error positivity (Pe) components, which are typically associated with error processing in the human brain. Feature extraction consisted of Multivariate Autoregressive modeling combined with the Simulated Annealing technique. The resulting information was subsequently classified by means of an Artificial Neural Network (ANN) using back-propagation algorithm under the “leave-one-out cross-validation” scenario and the Fuzzy C-Means (FCM) algorithm. The ANN consisted of a multi-layer perceptron (MLP). The approach yielded classification rates of up to 85%, both for the actors’ correct and incorrect responses and the corresponding ERPs of the observers. The electrodes needed for such classifications were situated mainly at central and frontal areas. Results provide indications that the classification of the ERN is achievable. Furthermore, the availability of the Pe signals, in addition to the ERN, improves the classification, and this is more pronounced for observers’ signals. The proposed ERP-signal classification method provides a promising tool to study error detection and observational-learning mechanisms in performance monitoring and joint-action research, in both healthy and patient populations

A critical comparison of technologies for a plant genome sequencing project

BACKGROUND: A high-quality genome sequence of any model organism is an essential starting point for genetic and other studies. Older clone-based methods are slow and expensive, whereas faster, cheaper short-read-only assemblies can be incomplete and highly fragmented, which minimizes their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and associated new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, on larger (e.g., human) genomes. However, plant genomes can be much more repetitive and larger than the human genome, and plant biochemistry often makes obtaining high-quality DNA that is free from contaminants difficult. Reflecting their challenging nature, we observe that plant genome assembly statistics are typically poorer than for vertebrates. RESULTS: Here, we compare Illumina short read, Pacific Biosciences long read, 10x Genomics linked reads, Dovetail Hi-C, and BioNano Genomics optical maps, singly and combined, in producing high-quality long-range genome assemblies of the potato species Solanum verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA compute requirements and sequencing costs. CONCLUSIONS: The field of genome sequencing and assembly is reaching maturity, and the differences we observe between assemblies are surprisingly small. We expect that our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.</p

Nationwide Study to Predict Colonic Ischemia after Abdominal Aortic Aneurysm Repair in The Netherlands

BACKGROUND: Colonic ischemia remains a severe complication after abdominal aortic aneurysm (AAA) repair and is associated with a high mortality. With open repair being one of the main risk factors of colonic ischemia, deciding between endovascular or open aneurysm repair should be based on tailor-made medicine. This study aims to identify high-risk patients of colonic ischemia, a risk that can be taken into account while deciding on AAA treatment strategy.METHODS: A nationwide population-based cohort study of 9,433 patients who underwent an AAA operation between 2014 and 2016 was conducted. Potential risk factors were determined by reviewing prior studies and univariate analysis. With logistic regression analysis, independent predictors of intestinal ischemia were established. These variables were used to form a prediction model.RESULTS: Intestinal ischemia occurred in 267 patients (2.8%). Occurrence of intestinal ischemia was seen significantly more in open repair versus endovascular aneurysm repair (7.6% vs. 0.9%; P &lt; 0.001). This difference remained significant after stratification by urgency of the procedure, in both intact open (4.2% vs. 0.4%; P &lt; 0.001) and ruptured open repair (15.0% vs. 6.2%); P &lt; 0.001). Rupture of the AAA was the most important predictor of developing intestinal ischemia (odds ratio [OR], 5.9, 95% confidence interval [CI] 4.4-8.0), followed by having a suprarenal AAA (OR 3.4; CI 1.1-10.6). Associated procedural factors were open repair (OR 2.8; 95% CI 1.9-4.2), blood loss &gt;1L (OR 3.6; 95% CI 1.7-7.5), and prolonged operating time (OR 2.0; 95% CI 1.4-2.8). Patient characteristics included having peripheral arterial disease (OR 2.4; 95% CI 1.3-4.4), female gender (OR 1.7; 95% CI 1.2-2.4), renal insufficiency (OR 1.7; 1.3-2.2), and pulmonary history (OR 1.6; 95% CI 1.2-2.2). Age &lt;68 years proved to be a protective factor (OR 0.5; 95% CI 0.4-0.8). Associated mortality was higher in patients with intestinal ischemia versus patients without (50.6% vs. 5.1%, P &lt; 0.001). Each predictor was given a score between 1 and 4. Patients with a score of ≥10 proved to be at high risk. A prediction model with an excellent AUC = 0.873 (95% CI 0.855-0.892) could be formed.CONCLUSIONS: One of the main risk factors is open repair. Several other risk factors can contribute to developing colonic ischemia after AAA repair. The proposed prediction model can be used to identify patients at high risk for developing colonic ischemia. With the current trend in AAA repair leaning toward open repair for better long-term results, our prediction model allows a better informed decision can be made in AAA treatment strategy.</p