Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Investigation of the effect of using data collection technology on students' attitudes to science instruction

The purpose of this project was to investigate the effect of using of data collection technology on student attitudes towards science instruction. The study was conducted over the course of two years at Madison High School in Adrian, Michigan, primarily in college preparatory physics classes, but also in one college preparatory chemistry class and one environmental science class. A preliminary study was conducted at a Lenawee County Intermediate Schools student summer environmental science day camp. The data collection technology used was a combination of Texas Instruments TI-84 Silver Plus graphing calculators and Vernier LabPro data collection sleds with various probeware attachments, including motion sensors, pH probes and accelerometers. Students were given written procedures for most laboratory activities and were provided with data tables and analysis questions to answer about the activities. The first year of the study included a pretest and posttest measuring student attitudes towards the class they were enrolled in. Pre-test and post-test data were analyzed to determine effect size, which was found to be very small (Coe, 2002). The second year of the study focused only on a physics class and used Keller’s ARCS model for measuring student motivation based on the four aspects of motivation: Attention, Relevance, Confidence and Satisfaction (Keller, 2010). According to this model, it was found that there were two distinct groups in the class, one of which was motivated to learn and the other that was not. The data suggest that the use of data collection technology in science classes should be started early in a student’s career, possibly in early middle school or late elementary. This would build familiarity with the equipment and allow for greater exploration by the student as they progress through high school and into upper level science courses.

EXPLORATION OF THE MTSAT2 SATELLITE CAPABILITIES FOR REAL TIME DETECTION AND CHARACTERIZATION OF VOLCANIC EMISSIONS

In this report, we attempt to define the capabilities of the infrared satellite remote sensor, Multifunctional Transport Satellite-2 (MTSAT-2) (i.e. a geosynchronous instrument), in characterizing volcanic eruptive behavior in the highly active region of Indonesia. Sulfur dioxide data from NASA's Ozone Monitoring Instrument (OMI) (i.e. a polar orbiting instrument) are presented here for validation of the processes interpreted using the thermal infrared datasets. Data provided from two case studies are analyzed specifically for eruptive products producing large thermal anomalies (i.e. lava flows, lava domes, etc.), volcanic ash and SO2 clouds; three distinctly characteristic and abundant volcanic emissions. Two primary methods used for detection of heat signatures are used and compared in this report including, single-channel thermal radiance (4-µm) and the normalized thermal index (NTI) algorithm. For automated purposes, fixed thresholds must be determined for these methods. A base minimum detection limit (MDL) for single-channel thermal radiance of 2.30E+05 Wm- 2sr-1m-1 and -0.925 for NTI generate false alarm rates of 35.78% and 34.16%, respectively. A spatial comparison method, developed here specifically for use in Indonesia and used as a second parameter for detection, is implemented to address the high false alarm rate. For the single-channel thermal radiance method, the utilization of the spatial comparison method eliminated 100% of the false alarms while maintaining every true anomaly. The NTI algorithm showed similar results with only 2 false alarms remaining. No definitive difference is observed between the two thermal detection methods for automated use; however, the single-channel thermal radiance method coupled with the SO2 mass abundance data can be used to interpret volcanic processes including the identification of lava dome activity at Sinabung as well as the mechanism for the dome emplacement (i.e. endogenous or exogenous). Only one technique, the brightness temperature difference (BTD) method, is used for the detection of ash. Trends of ash area, water/ice area, and their respective concentrations yield interpretations of increased ice formation, aggregation, and sedimentation processes that only a high-temporal resolution instrument like the MTSAT-2 can analyze. A conceptual model of a secondary zone of aggregation occurring in the migrating Kelut ash cloud, which decreases the distal fine-ash component and hazards to flight paths, is presented in this report. Unfortunately, SO2 data was unable to definitively reinforce the concept of a secondary zone of aggregation due to the lack of a sufficient temporal resolution. However, a detailed study of the Kelut SO2 cloud is used to determine that there was no climatic impacts generated from this eruption due to the atmospheric residence times and e-folding rate of ~14 days for the SO2. This report applies the complementary assets offered by utilizing a high-temporal and a high-spatial resolution satellite, and it demonstrates that these two instruments can provide unparalleled observations of dynamic volcanic processes.

Archiving Montana’s Geologic Data

Since the 19th century, enormous amounts of time and money were invested in the exploration and development of Montana’s natural resources. These investments generated tremendous volumes of geologic, geophysical, and environmental data. Over the years, many of these data have been stored, forgotten, lost, or destroyed. In this lecture, Peggy discusses the steps the Bureau is taking to rescue and make the data available to the public.

Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics

We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

Visual exploration in Parkinson's disease and Parkinson's disease dementia

Parkinson's disease, typically thought of as a movement disorder, is increasingly recognized as causing cognitive impairment and dementia. Eye movement abnormalities are also described, including impairment of rapid eye movements (saccades) and the fixations interspersed between them. Such movements are under the influence of cortical and subcortical networks commonly targeted by the neurodegeneration seen in Parkinson's disease and, as such, may provide a marker for cognitive decline. This study examined the error rates and visual exploration strategies of subjects with Parkinson's disease, with and without cognitive impairment, whilst performing a battery of visuo-cognitive tasks. Error rates were significantly higher in those Parkinson's disease groups with either mild cognitive impairment (P = 0.001) or dementia (P < 0.001), than in cognitively normal subjects with Parkinson's disease. When compared with cognitively normal subjects with Parkinson's disease, exploration strategy, as measured by a number of eye tracking variables, was least efficient in the dementia group but was also affected in those subjects with Parkinson's disease with mild cognitive impairment. When compared with control subjects and cognitively normal subjects with Parkinson's disease, saccade amplitudes were significantly reduced in the groups with mild cognitive impairment or dementia. Fixation duration was longer in all Parkinson's disease groups compared with healthy control subjects but was longest for cognitively impaired Parkinson's disease groups. The strongest predictor of average fixation duration was disease severity. Analysing only data from the most complex task, with the highest error rates, both cognitive impairment and disease severity contributed to a predictive model for fixation duration [F(2,76) = 12.52, P ≤ 0.001], but medication dose did not (r = 0.18, n = 78, P = 0.098, not significant). This study highlights the potential use of exploration strategy measures as a marker of cognitive decline in Parkinson's disease and reveals the efficiency by which fixations and saccades are deployed in the build-up to a cognitive response, rather than merely focusing on the outcome itself. The prolongation of fixation duration, present to a small but significant degree even in cognitively normal subjects with Parkinson's disease, suggests a disease-specific impact on the networks directing visual exploration, although the study also highlights the multi-factorial nature of changes in exploration and the significant impact of cognitive decline on efficiency of visual search.

PDB-Explorer: a web-based interactive map of the protein data bank in shape space

Background The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. Methods A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. Results The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. Conclusion A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.​cheminfo.​org/​pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.

The English of The Sleeping Lady: An exploration of the historical and current influences on the English of Kosrae

Kosrae, or ‘The Island of The Sleeping Lady’ as it is known to locals, is the most remote island of the Federated States of Micronesia (FSM), located in the western Pacific. FSM is an independent sovereign nation consisting of four state in total: Pohnpei, Chuuk, Yap and Kosrae. First claimed by the Spanish, who were forced to cede FSM to Germany in 1899. In 1914, the Japanese took military possession of the region resulting in considerable economic, social and political change for the islands’ inhabitants. By 1947 after WWII, the islands formed part of the Trust Territory of the Pacific Islands commissioned by the UN and administered by the US. The FSM became an independent nation in 1986 while still retaining affiliation with the US under a ‘Compact of Free Association’ encouraging the officiating of English as a language of FSM, alongside local languages. Here I examine the presence and uses of English in Kosrae with reference to these socio-historical influences. First, I discuss the extralinguistic factors which have shaped the English that is currently found on Kosrae. Secondly, I assess the use of English in this community in light of Schneider’s (2007) ‘Dynamic Model’. Finally, an overview of the salient linguistic characteristics of Kosraean English, based on data collected in informal conversations on the island, will be presented. The overall objective is to present a socio-historical, political and linguistic description of a hitherto unexamined English emerging in a postcolonial environment. Schneider, E. (2007). Postcolonial Englishes. Cambridge: Cambridge University Press. Research Interests: Global Englishes

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

Characterization of OSIRIS NAC filters for the interpretation of multispectral data of comet 67P/Churyumov-Gerasimenko

Context. We interpret multicolor data from OSIRIS NAC for the remote-sensing exploration of comet 67P/Churyumov-Gerasimenko. Aims. We determine the most meaningful definition of color maps for the characterization of surface variegation with filters available on OSIRIS NAC. Methods. We analyzed laboratory spectra of selected minerals and olivine-pyroxene mixtures seen through OSIRIS NAC filters, with spectral methods existing in the literature: reflectance ratios, minimum band wavelength, spectral slopes, band tilt, band curvature, and visible tilt. Results. We emphasize the importance of reflectance ratios and particularly the relation of visible tilt vs. band tilt. This technique provides a reliable diagnostic of the presence of silicates. Color maps constructed by red-green-blue colors defined with the green, orange, red, IR, and Fe2O3 filters let us define regions that may significantly differ in composition.

Cognitive-Behavioural Analysis System of Psychotherapy (CBASP), a drug, or their combination: differential therapeutics for persistent depressive disorder: a study protocol of an individual participant data network meta-analysis.

INTRODUCTION Despite important advances in psychological and pharmacological treatments of persistent depressive disorders in the past decades, their responses remain typically slow and poor, and differential responses among different modalities of treatments or their combinations are not well understood. Cognitive-Behavioural Analysis System of Psychotherapy (CBASP) is the only psychotherapy that has been specifically designed for chronic depression and has been examined in an increasing number of trials against medications, alone or in combination. When several treatment alternatives are available for a certain condition, network meta-analysis (NMA) provides a powerful tool to examine their relative efficacy by combining all direct and indirect comparisons. Individual participant data (IPD) meta-analysis enables exploration of impacts of individual characteristics that lead to a differentiated approach matching treatments to specific subgroups of patients. METHODS AND ANALYSIS We will search for all randomised controlled trials that compared CBASP, pharmacotherapy or their combination, in the treatment of patients with persistent depressive disorder, in Cochrane CENTRAL, PUBMED, SCOPUS and PsycINFO, supplemented by personal contacts. Individual participant data will be sought from the principal investigators of all the identified trials. Our primary outcomes are depression severity as measured on a continuous observer-rated scale for depression, and dropouts for any reason as a proxy measure of overall treatment acceptability. We will conduct a one-step IPD-NMA to compare CBASP, medications and their combinations, and also carry out a meta-regression to identify their prognostic factors and effect moderators. The model will be fitted in OpenBUGS, using vague priors for all location parameters. For the heterogeneity we will use a half-normal prior on the SD. ETHICS AND DISSEMINATION This study requires no ethical approval. We will publish the findings in a peer-reviewed journal. The study results will contribute to more finely differentiated therapeutics for patients suffering from this chronically disabling disorder. TRIAL REGISTRATION NUMBER CRD42016035886.

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Exploration of genetic susceptibility to pancreatic cancer: A GWAS approach

Pancreatic cancer is the 4th most common cause for cancer death in the United States, accompanied by less than 5% five-year survival rate based on current treatments, particularly because it is usually detected at a late stage. Identifying a high-risk population to launch an effective preventive strategy and intervention to control this highly lethal disease is desperately needed. The genetic etiology of pancreatic cancer has not been well profiled. We hypothesized that unidentified genetic variants by previous genome-wide association study (GWAS) for pancreatic cancer, due to stringent statistical threshold or missing interaction analysis, may be unveiled using alternative approaches. To achieve this aim, we explored genetic susceptibility to pancreatic cancer in terms of marginal associations of pathway and genes, as well as their interactions with risk factors. We conducted pathway- and gene-based analysis using GWAS data from 3141 pancreatic cancer patients and 3367 controls with European ancestry. Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Using the logistic kernel machine (LKM) test, we analyzed 17906 genes defined by University of California Santa Cruz (UCSC) database. Using the likelihood ratio test (LRT) in a logistic regression model, we analyzed 177 pathways and 17906 genes for interactions with risk factors in 2028 pancreatic cancer patients and 2109 controls with European ancestry. After adjusting for multiple comparisons, six pathways were marginally associated with risk of pancreatic cancer ( P < 0.00025): Fc epsilon RI signaling, maturity onset diabetes of the young, neuroactive ligand-receptor interaction, long-term depression (Ps < 0.0002), and the olfactory transduction and vascular smooth muscle contraction pathways (P = 0.0002; Nine genes were marginally associated with pancreatic cancer risk (P < 2.62 × 10−5), including five reported genes (ABO, HNF1A, CLPTM1L, SHH and MYC), as well as four novel genes (OR13C4, OR 13C3, KCNA6 and HNF4 G); three pathways significantly interacted with risk factors on modifying the risk of pancreatic cancer (P < 2.82 × 10−4): chemokine signaling pathway with obesity ( P < 1.43 × 10−4), calcium signaling pathway (P < 2.27 × 10−4) and MAPK signaling pathway with diabetes (P < 2.77 × 10−4). However, none of the 17906 genes tested for interactions survived the multiple comparisons corrections. In summary, our current GWAS study unveiled unidentified genetic susceptibility to pancreatic cancer using alternative methods. These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer, once confirmed, will shed promising light on the prevention and treatment of this disease. ^

Geological and geochemical characteristics of the Tersang gold deposit, Malaysia: implications for genesis and gold exploration

The Central gold belt of peninsular Malaysia comprises a number of gold deposits located in the east of the N-S striking Bentong-Raub Suture Zone. The Tersang gold deposit is one of the gold deposits in the gold belt and hosted in sandstone, rhyolite and breccia units. The deposit has an inferred resource of 528,000 ounces of gold. The geochronology of the Tersang deposit has been newly constrained by LA ICP-MS U-Pb zircon dating. The maximum depositional age of the host sedimentary rocks ranges from Early Carboniferous to Early Permian (261.5 ± 4.9 Ma to 333.5 ± 2.5 Ma) for the host sandstone and Late Triassic for the rhyolite intrusion (218.8 ± 1.7 Ma). Textural characteristics of pyrite have revealed five types including (1) Euhedral to subhedral pyrite with internal fracturing and porous cores located in the sandstone layers (pyrite 1); (2) Anhedral pyrite overgrowths on pyrite 1 and disseminated in stage 1 vein (pyrite 2); (3) Fracture-filled or vein pyrite located in stages 1 and 2 vein (pyrite 3); (4) Euhedral pyrite with internal fractures also located in stage 2 vein (pyrite 4); and (5) Subhedral clean pyrite located in the rhyolite intrusion (pyrite 5). Based on pyrite mapping and spot analyses, two main stages of gold enrichment are documented from the Tersang gold deposit. Gold in sandstone-hosted pyrite 1 (mean 4.3 ppm) shows best correlation with Bi and Pb (as evidenced on pyrite maps). In addition, gold in pyrite 3 (mean 8 ppm) located in stage 2 vein shows a good correlation with As, Ag, Sb, Cu, Tl, and Pb. In terms of gold exploration, we suggest that elements such as As, Ag, Sb, Cu, Tl, Bi, and Pb associated with Au may serve as vectoring tools in gold exploration. Our new geological, structural, geochemical and isotopic data together with mineral paragenesis, pyrite chemistry and ore fluid characteristics indicate that the Tersang gold deposit is comparable to a sediment-hosted gold deposit. Our new genetic model suggests deposition of the Permo-Carboniferous sediments followed by intrusion of rhyolitic magma in the Late Triassic. At a later stage, gold mineralisation overprinted the rhyolite intrusion and the sandstone.