Skynet’s New Observing Mode: The Campaign Manager

Built in 2004, the Skynet robotic telescope network originally consisted of six 0.4 m telescopes located at the Cerro-Tololo Inter-American Observatory in the Chilean Andes. The network was designed to carry out simultaneous multi-wavelength observations of gamma-ray bursts (GRBs) when they are only tens of seconds old. To date, the network has been expanded to ≈20 telescopes, including a 20 m radio telescope, that span four continents and five countries. The Campaign Manager (CM) is a new observing mode that has been developed for Skynet. Available to all Skynet observers, the CM semi-autonomously and indefinitely scales and schedules exposures on the observer’s behalf while allowing for modification to scaling parameters in real time. The CM is useful for follow up to various transient phenomena including gravitational-wave events, GRB localizations, young supernovae, and eventually, sufficiently bright Argus Optical Array and Large Synoptic Survey Telescope events.

Enhanced Conformational Sampling of Nanobody CDR H3 Loop by Generalized Replica-Exchange with Solute Tempering

The variable domains of heavy-chain antibodies, known as nanobodies, are potential substitutes for IgG antibodies. They have similar affinities to antigens as antibodies, but are more heat resistant. Their small size allows us to exploit computational approaches for structural modeling or design. Here, we investigate the applicability of an enhanced sampling method, a generalized replica-exchange with solute tempering (gREST) for sampling CDR-H3 loop structures of nanobodies. In the conventional replica-exchange methods, temperatures of only a whole system or scaling parameters of a solute molecule are selected for temperature or parameter exchange. In gREST, we can flexibly select a part of a solute molecule and a part of the potential energy terms as a parameter exchange region. We selected the CDR-H3 loop and investigated which potential energy term should be selected for the efficient sampling of the loop structures. We found that the gREST with dihedral terms can explore a global conformational space, but the relaxation to the global equilibrium is slow. On the other hand, gREST with all the potential energy terms can sample the equilibrium distribution, but the structural exploration is slower than with dihedral terms. The lessons learned from this study can be applied to future studies of loop modeling.

Global Illumination on a Mobile Phone: Scalable Real-time Global Illumination using Sparse Radiance Probes

<p>Real-time global illumination that scales from low to high-end hardware is important for interactive applications so they can reach wider audiences. To do this, the real-time lighting algorithm used needs to have varying performance characteristics. Sparse Radiance Probes (SRP) is a recent real-time global illumination algorithm that runs in under 5 ms per frame on a high-end Nvidia Titan X GPU. Its low per-frame timings suggest it could scale to low-end devices, but no prior work provides complete implementation details and evaluates its performance across devices with varying performance characteristics to prove this. Therefore, this thesis aims to fill this gap and determine if SRP is scalable across low to high-end devices. SRP is implemented with adjustable scaling parameters, and its performance is compared across three test devices. A low-end iPhone 7, a mid-range AMD Radeon 560 graphics card, and a high-end AMD RX Vega 56 graphics card. The implementation in this thesis ran above 60 FPS for simple scenes on the iPhone 7, and with a reasonable reduction in quality, it ran just above 30 FPS on more complex scenes like Crytek Sponza. These results show that SRP can scale to low-end devices. While the implementation in this thesis runs in real time, there are implementation optimisations that would make SRP run even faster across all the test devices without reducing quality.</p>

Diversity Scaling Analysis of Chinese Gut Microbiomes Across Ethnicities and Lifestyles

Diversity scaling (changes) of human gut microbiome is important because it measures the inter-individual heterogeneity of diversity and other important parameters of population-level diversity. Understanding the heterogeneity of microbial diversity can be used as a reference for the personalized medicine of microbiome-associated diseases. Similar to diversity per se, diversity scaling may also be influenced by host factors, especially lifestyles and ethnicities. Nevertheless, this important topic regarding Chinese populations has not been addressed, to our best knowledge. Here, we fill the gap by applying a recent extension to the classic species–area relationship (SAR), i.e., diversity–area relationship (DAR), to reanalyze a large dataset of Chinese gut microbiomes covering the seven biggest Chinese ethnic groups (covering &gt; 95% Chinese) living rural and urban lifestyles. Four DAR profiles were constructed to investigate the diversity scaling, diversity overlap, potential maximal diversity, and the ratio of local to global diversity of Chinese gut microbiomes. We discovered the following: (i) The diversity scaling parameters (z) at various taxon levels are little affected by either ethnicity or lifestyles, as exhibited by less than 0.5% differences in pairwise comparisons. (ii) The maximal accrual diversity (potential diversity) exhibited difference in only about 5% of pairwise comparisons, and all of the differences occurred in ethnicity comparisons (i.e., lifestyles had no effects). (iii) Ethnicity seems to have stronger effects than lifestyles across all taxon levels, and this may reflect the reality that China has been experiencing rapid urbanization in the last few decades, while the ethnic-related genetic background may change relatively little during the same period.

Global Illumination on a Mobile Phone: Scalable Real-time Global Illumination using Sparse Radiance Probes

<p>Real-time global illumination that scales from low to high-end hardware is important for interactive applications so they can reach wider audiences. To do this, the real-time lighting algorithm used needs to have varying performance characteristics. Sparse Radiance Probes (SRP) is a recent real-time global illumination algorithm that runs in under 5 ms per frame on a high-end Nvidia Titan X GPU. Its low per-frame timings suggest it could scale to low-end devices, but no prior work provides complete implementation details and evaluates its performance across devices with varying performance characteristics to prove this. Therefore, this thesis aims to fill this gap and determine if SRP is scalable across low to high-end devices. SRP is implemented with adjustable scaling parameters, and its performance is compared across three test devices. A low-end iPhone 7, a mid-range AMD Radeon 560 graphics card, and a high-end AMD RX Vega 56 graphics card. The implementation in this thesis ran above 60 FPS for simple scenes on the iPhone 7, and with a reasonable reduction in quality, it ran just above 30 FPS on more complex scenes like Crytek Sponza. These results show that SRP can scale to low-end devices. While the implementation in this thesis runs in real time, there are implementation optimisations that would make SRP run even faster across all the test devices without reducing quality.</p>

A Novel Variable Extensometer Method for Measuring Ductility Scaling Parameters from Single Specimens

Macro-scale ductility is not an intrinsic material property but is dependent on the overall geometry of the specimen. To account for variety in specimen geometries, multiple ductility scaling laws have been developed which scale ductility between different specimen sizes. Traditionally, these ductility laws rely on testing multiple different specimens of varying sizes to obtain material parameters, often done by varying gauge lengths. With the use of Digital Image Correlation (DIC), this work presents a technique where multiple different gauge lengths are extracted from a single specimen to obtain ductility scaling parameters from a single experiment. This technique provides orders of magnitude more data from each specimen than previous techniques. This variable extensometer method is then validated by testing multiple different geometries and select scaling laws are then compared.

Experience of OpenStack Test Deployment and Comparison of Virtual and Real Cluster Environments

Introduction. A brief overview of the properties and architecture of one of the components of the National Cloud of Open Science prototype – the cloud platform OpenStack is given. The list of software and hardware components of the OpenStack test cloud environment and the sequence of actions required for the deployment of both OpenStack itself and the Slurm virtual cluster environment for portable, scalable, reproducible scientific biomedical computing are presented. The purpose of the paper is a description of the experience of test deployment of OpenStack to create a scalable computing environment for reproducible scientific computing using modern technological solutions, which can be applied to both cloud (OpenStack, AWS, Google) and cluster platforms (Slurm). Results. The structure of the created test containerized (using Singularity technology) biomedical application, which contains modern software and libraries and can be used in conventional and cloud virtual cluster environments is briefly described. The results of a comparative test of this application in the virtual cluster environment Slurm under the control of OpenStack and in the node of cluster SKIT-4.5 in the V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine are given. Information on solving the problem of finding the optimal in terms of saving resources scaling parameters for the developed application in two comparable cluster environments is given. Some features of the use of these cluster environments are clarified, in particular, a comparison of the dependence of the application speed on the number of parallel processes for two cluster environments is presented. Empirical data are presented in graphical form, which illustrate the nature of the load on the OpenStack server and the use of RAM on the number of parallel processes. Possibilities of portability between the specified cluster environments, scaling of calculations and maintenance of reproducibility of calculations for the offered test application are demonstrated. The advantages of using OpenStack technology for scientific biomedical calculations are pointed out. Conclusions. The described example of test deployment and use of OpenStack gives an idea of the requirements for the necessary technical base to ensure the reproducibility of scientific biomedical calculations in cloud and cluster environments. Keywords: cloud technologies, reproducible calculations, cluster platform.