Path rendering by counting pixel coverage

A frequent task in computer graphics is to render a closed path, e.g., a polygon or other shape. Such shapes are found in typography, vector graphics, design applications, etc. Current path-rendering techniques have certain drawbacks, e.g., paths cannot scale too far during animation, control points within the path must remain static, etc. The ability to render paths efficiently and with fewer constraints allows interfaces and applications with richer and more dynamic content. This disclosure describes techniques for efficient path rendering using a GPU. In particular, it introduces the concept of fractional coverage counting, which ameliorates aliasing at the edges of shapes. These techniques can reduce or eliminate reliance on hardware multisampling to achieve anti-aliasing, and open up the possibility of sophisticated graphics rendering on mobile devices or other platforms with resource constraints

NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to data centers with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, low-power AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Edge Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of TensorFlow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing

This work provides a solution to the challenge of small amounts of training data in Non-Destructive Ultrasonic Testing for composite components. It was demonstrated that direct simulation alone is ineffective at producing training data that was representative of the experimental domain due to poor noise reconstruction. Therefore, four unique synthetic data generation methods were proposed which use semi-analytical simulated data as a foundation. Each method was evaluated on its classification performance of real experimental images when trained on a Convolutional Neural Network which underwent hyperparameter optimization using a genetic algorithm. The first method introduced task specific modifications to CycleGAN, to learn the mapping from physics-based simulations of defect indications to experimental indications in resulting ultrasound images. The second method was based on combining real experimental defect free images with simulated defect responses. The final two methods fully simulated the noise responses at an image and signal level respectively. The purely simulated data produced a mean classification F1 score of 0.394. However, when trained on the new synthetic datasets, a significant improvement in classification performance on experimental data was realized, with mean classification F1 scores of 0.843, 0.688, 0.629, and 0.738 for the respective approaches.Comment: 16 Page

Machine-Learning Space Applications on SmallSat Platforms with TensorFlow

Due to their attractive benefits, which include affordability, comparatively low development costs, shorter development cycles, and availability of launch opportunities, SmallSats have secured a growing commercial and educational interest for space development. However, despite these advantages, SmallSats, and especially CubeSats, suffer from high failure rates and (with few exceptions to date) have had low impact in providing entirely novel, market-redefining capabilities. To enable these more complex science and defense opportunities in the future, small-spacecraft computing capabilities must be flexible, robust, and intelligent. To provide more intelligent computing, we propose employing machine intelligence on space development platforms, which can contribute to more efficient communications, improve spacecraft reliability, and assist in coordination and management of single or multiple spacecraft autonomously. Using TensorFlow, a popular, open-source, machine-learning framework developed by Google, modern SmallSat computers can run TensorFlow graphs (principal component of TensorFlow applications) with both TensorFlow and TensorFlow Lite. The research showcased in this paper provides a flight-demonstration example, using terrestrial-scene image products collected in flight by our STP-H5/CSP system, currently deployed on the International Space Station, of various Convolutional Neural Networks (CNNs) to identify and characterize newly captured images. This paper compares CNN architectures including MobileNetV1, MobileNetV2, Inception-ResNetV2, and NASNet Mobile

Establishing the extent of malaria transmission and challenges facing pre-elimination in the Republic of Djibouti.

BACKGROUND: Countries aiming for malaria elimination require a detailed understanding of the current intensity of malaria transmission within their national borders. National household sample surveys are now being used to define infection prevalence but these are less efficient in areas of exceptionally low endemicity. Here we present the results of a national malaria indicator survey in the Republic of Djibouti, the first in sub-Saharan Africa to combine parasitological and serological markers of malaria, to evaluate the extent of transmission in the country and explore the potential for elimination. METHODS: A national cross-sectional household survey was undertaken from December 2008 to January 2009. A finger prick blood sample was taken from randomly selected participants of all ages to examine for parasitaemia using rapid diagnostic tests (RDTs) and confirmed using Polymerase Chain Reaction (PCR). Blood spots were also collected on filter paper and subsequently used to evaluate the presence of serological markers (combined AMA-1 and MSP-119) of Plasmodium falciparum exposure. Multivariate regression analysis was used to determine the risk factors for P. falciparum infection and/or exposure. The Getis-Ord G-statistic was used to assess spatial heterogeneity of combined infections and serological markers. RESULTS: A total of 7151 individuals were tested using RDTs of which only 42 (0.5%) were positive for P. falciparum infections and confirmed by PCR. Filter paper blood spots were collected for 5605 individuals. Of these 4769 showed concordant optical density results and were retained in subsequent analysis. Overall P. falciparum sero-prevalence was 9.9% (517/4769) for all ages; 6.9% (46/649) in children under the age of five years; and 14.2% (76/510) in the oldest age group (≥50 years). The combined infection and/or antibody prevalence was 10.5% (550/4769) and varied from 8.1% to 14.1% but overall regional differences were not statistically significant (χ2=33.98, p=0.3144). Increasing age (p<0.001) and decreasing household wealth status (p<0.001) were significantly associated with increasing combined P. falciparum infection and/or antibody prevalence. Significant P. falciparum hot spots were observed in Dikhil region. CONCLUSION: Malaria transmission in the Republic of Djibouti is very low across all regions with evidence of micro-epidemiological heterogeneity and limited recent transmission. It would seem that the Republic of Djibouti has a biologically feasible set of pre-conditions for elimination, however, the operational feasibility and the potential risks to elimination posed by P. vivax and human population movement across the sub-region remain to be properly established

Long-term functional recovery after facial nerve transection and repair in the rat

BACKGROUND: The rodent model is commonly used to study facial nerve injury. Because of the exceptional regenerative capacity of the rodent facial nerve, it is essential to consider the timing when studying facial nerve regeneration and functional recovery. Short-term functional recovery data following transection and repair of the facial nerve has been documented by our laboratory. However, because of the limitations of the head fixation device, there is a lack of long-term data following facial nerve injury. The objective of this study was to elucidate the long-term time course and functional deficit following facial nerve transection and repair in a rodent model. METHODS: Adult rats were divided into group 1 (controls) and group 2 (experimental). Group 1 animals underwent head fixation, followed by a facial nerve injury, and functional testing was performed from day 7 to day 70. Group 2 animals underwent facial nerve injury, followed by delayed head fixation, and then underwent functional testing from months 6 to 8. RESULTS: There was no statistical difference between the average whisking amplitudes in group 1 and group 2 animals. CONCLUSION: Functional whisking recovery 6 months after facial nerve injury is comparable to recovery within 1 to 4 months of transection and repair, thus the ideal window for evaluating facial nerve recovery falls within the 4 months after injury

Motor unit discharge variability is increased in mild-to-moderate Parkinson\u27s disease

Individuals with Parkinson\u27s disease (PD) demonstrate deficits in muscle activation such as decreased amplitude and inappropriate bursting. There is evidence that some of these disturbances are more pronounced in extensor vs. flexor muscles. Surface EMG has been used widely to quantify muscle activation deficits in PD, but analysis of discharge of the underlying motor units may provide greater insight and be more sensitive to changes early in the disease. Of the few studies that have examined motor unit discharge in PD, the majority were conducted in the first dorsal interosseous, and no studies have measured motor units from extensor and flexor muscles within the same cohort. The objective of this study was to characterize the firing behavior of single motor units in the elbow flexor and extensor muscles during isometric contractions in people with mild-to-moderate PD. Ten individuals with PD (off-medication) and nine healthy controls were tested. Motor unit spike times were recorded via intramuscular EMG from the biceps and triceps brachii muscles during 30-s isometric contractions at 10% maximum voluntary elbow flexion and elbow extension torque, respectively. We selected variables of mean motor unit discharge rate, discharge variability, and torque variability to evaluate motor abnormalities in the PD group. The effects of group, muscle, and group-by-muscle on each variable were determined using separate linear mixed models. Discharge rate and torque variability were not different between groups, but discharge variability was significantly higher in the PD group for both muscles combined

Use of mental simulations to change theory of planned behaviour variables

Objectives. The predictive validity of the theory of planned behaviour iswell established, but much less is known about: (a) whether there are causal relationships between key components of the model and (b) how to go about changing the theory of planned behaviour variables. This study tested the ability of outcome and process simulations to change variables specified in the theory of planned behaviour in relation to blood donation. Design. Participants (N ¼ 146) were randomized to one of four conditions: outcome simulation only, process simulation only, process-plus-outcome simulation and a distractor control condition. The dependent variables were state anxiety, and intention attitude, subjective norm and perceived control from the theory of planned behaviour. Methods. Participants were asked to empty their mind and visualize themselves: (a) after donating blood (outcome manipulation), (b) preparing to donate blood (process manipulation), (c) both preparing to donate blood and after having donated blood (process-plus-outcome manipulation) or (d) both preparing to get a high mark and after having got a high mark on their course (control condition). Following mental rehearsal, participants completed the dependent variables. Results. There were no main effects of outcome simulation, but process simulation successfully increased intention, subjective norm and perceived control. There was also a significant outcome simulation x process simulation interaction for attitude. The effect of the process manipulation on intention was mediated by subjective norm and perceived control. Conclusions. The findings show promise for the use of mental simulations in changing cognitions and further research is required to extend the present findings to other health behaviours.</p

Collective skyrmion motion under the influence of an additional interfacial spin-transfer torque

Here we study the effect of an additional interfacial spin-transfer torque, as well as the well-established spin-orbit torque, on skyrmion collections - group of skyrmions dense enough that they are not isolated from one another - in ultrathin heavy metal / ferromagnetic multilayers, by comparing modelling with experimental results. Using a skyrmion collection with a range of skyrmion diameters, we study the dependence of the skyrmion Hall angle on diameter and velocity. As for an isolated skyrmion, a nearly-independent skyrmion Hall angle on skyrmion diameter for all skyrmion collection densities is reproduced by the model which includes interfacial spin-transfer torque. On the other hand, the skyrmion Hall angle change with velocity is significantly more abrupt compared to the isolated skyrmion case. This suggests that the effect of disorder on the collective skyrmion behavior is reduced compared to the isolated case. Our results further show the significance of the interfacial spin-transfer torque in ultrathin magnetic multilayers. Due to the good agreement with experiments, we conclude that the interfacial spin-transfer torque should be included in micromagnetic simulations for reproduction of experimental results.Comment: 18 pages, 4 figure

Програма, методичні вказівки та контрольні завдання з дисципліни "Сучасні технології вина і коньяку"

Дисципліна "Сучасні технології вина і коньяку" входить до складу рекомендованого переліку навчальних дисциплін нормативної частини освітньо-професійної програми підготовки магістрів спеціальності 181 "Харчові технології", спеціалізації "Технології продуктів бродіння і виноробства". Предметом вивчення навчальної дисципліни "Сучасні технології вина і коньяку" є технологія виноградних та плодово-ягідних вин, коньяків, бренді та інших міцних напоїв, схеми технохімічного і мікробіологічного контролю, методики визначення якісних показників сировини, основних і допоміжних матеріалів, напівпродуктів, готової продукції, вторинних продуктів виноробства й оцінювання їх відповідності вимогам чинної нормативної документації, методики розрахунку продуктів, основних і допоміжних матеріалів, втрат і відходів виробництва. Метою викладання начальної дисципліни "Сучасні технології вина і коньяку" є формування у студентів системи навичок для здійснення ефективної професіональної діяльності на підприємствах виноробної галузі та у наукових закладах в умовах ринкової економіки, технічного переоснащення й удосконалення підприємств, застосування сучасних інноваційних технологій на основі творчого об’єднання і впровадження у виробництво отриманих знань з фундаментальних, загальноінженерних, економічних та спеціальних дисциплін, забезпечення випуску високоякісної продукції з гарантованим ступенем безпеки для людини і навколишнього середовища, оптимальними питомими витратами людської праці, матеріальних та енергетичних ресурсів