A principled experimental design approach to Big Data analysis

Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

COL1A1 C-propeptide cleavage site mutation causes high bone mass, bone fragility and jaw lesions: A new cause of gnathodiaphyseal dysplasia?

Gnathodiaphyseal dysplasia (GDD) is a rare autosomal dominant condition characterized by bone fragility, irregular bone mineral density (BMD) and fibro-osseous lesions in the skull and jaw. Mutations in Anoctamin-5 (ANO5) have been identified in some cases. We aimed to identify the causative mutation in a family with features of GDD but no mutation in ANO5, using whole exome capture and massive parallel sequencing (WES). WES of two affected individuals (a mother and son) and the mother's unaffected parents identified a mutation in the C-propeptide cleavage site of COL1A1. Similar mutations have been reported in individuals with osteogenesis imperfecta (OI) and paradoxically increased BMD. C-propeptide cleavage site mutations in COL1A1 may not only cause 'high bone mass OI', but also the clinical features of GDD, specifically irregular sclerotic BMD and fibro-osseous lesions in the skull and jaw. GDD patients negative for ANO5 mutations should be assessed for mutations in type I collagen C-propeptide cleavage sites.

FlexAnalytics: A flexible data analytics framework for big data applications with I/O performance improvement

Increasingly larger scale applications are generating an unprecedented amount of data. However, the increasing gap between computation and I/O capacity on High End Computing machines makes a severe bottleneck for data analysis. Instead of moving data from its source to the output storage, in-situ analytics processes output data while simulations are running. However, in-situ data analysis incurs much more computing resource contentions with simulations. Such contentions severely damage the performance of simulation on HPE. Since different data processing strategies have different impact on performance and cost, there is a consequent need for flexibility in the location of data analytics. In this paper, we explore and analyze several potential data-analytics placement strategies along the I/O path. To find out the best strategy to reduce data movement in given situation, we propose a flexible data analytics (FlexAnalytics) framework in this paper. Based on this framework, a FlexAnalytics prototype system is developed for analytics placement. FlexAnalytics system enhances the scalability and flexibility of current I/O stack on HEC platforms and is useful for data pre-processing, runtime data analysis and visualization, as well as for large-scale data transfer. Two use cases – scientific data compression and remote visualization – have been applied in the study to verify the performance of FlexAnalytics. Experimental results demonstrate that FlexAnalytics framework increases data transition bandwidth and improves the application end-to-end transfer performance.

TMIO-pyrimid hybrids are profluorescent, site-directed spin labels for nucleic acids

We report the synthesis of a new class of molecules which are hybrids of long-lived tetramethylisoindolinoxyl (TMIO) radicals and the pyrido[1,2-a]benzimidazole (PyrImid) scaffold. These compounds represent a new lead for noncovalently binding nucleic acid probes, as they interact with nucleic acids with previously unreported C (DNA) and C/U (RNA) complementarity, which can be detected by electron paramagnetic resonance (EPR) techniques. They also have promising properties for fluorimetric analysis, as their fluorescent spin-quenched derivatives exhibit a significant Stokes shift

A CCG virtual system for big data application communication costs analysis

Network topology and routing are two important factors in determining the communication costs of big data applications at large scale. As for a given Cluster, Cloud, or Grid system, the network topology is fixed and static or dynamic routing protocols are preinstalled to direct the network traffic. Users cannot change them once the system is deployed. Hence, it is hard for application developers to identify the optimal network topology and routing algorithm for their applications with distinct communication patterns. In this study, we design a CCG virtual system (CCGVS), which first uses container-based virtualization to allow users to create a farm of lightweight virtual machines on a single host. Then, it uses software-defined networking (SDN) technique to control the network traffic among these virtual machines. Users can change the network topology and control the network traffic programmingly, thereby enabling application developers to evaluate their applications on the same system with different network topologies and routing algorithms. The preliminary experimental results through both synthetic big data programs and NPB benchmarks have shown that CCGVS can represent application performance variations caused by network topology and routing algorithm.

Implementing a context-based environmental science unit in the middle years: Teaching and learning at the creek

Engaging middle-school students in science continues to be a challenge in Australian schools. One initiative that has been tried in the senior years but is a more recent development in the middle years is the context-based approach. In this ethnographic study, we researched the teaching and learning transactions that occurred in one 9th grade science class studying a context-based Environmental Science unit that included visits to the local creek for 11 weeks. Data were derived from field notes, audio and video recorded conversations, interviews, student journals and classroom documents with a particular focus on two selected groups of students. This paper presents two assertions that highlight pedagogical approaches that contributed to learning. Firstly, spontaneous teaching episodes created opportunities for in-the-moment questioning by the teacher that led to students’ awareness of environmental issues and the scientific method; secondly, group work using flip cameras afforded opportunities for students to connect the science concepts with the context. Furthermore, students reported positively about the unit and expressed their appreciation for the opportunity to visit the creek frequently. This findings from this study should encourage teachers to take students into the real-world field for valuable teaching and learning experiences that are not available in the formal classroom.

Probabilistic assessment of herbicide runoff from Japanese rice paddies: The effects of local meteorological conditions and site-specific water management

Uncertainty assessments of herbicide losses from rice paddies in Japan associated with local meteorological conditions and water management practices were performed using a pesticide fate and transport model, PCPF-1, under the Monte Carlo (MC) simulation scheme. First, MC simulations were conducted for five different cities with a prescribed water management scenario and a 10-year meteorological dataset of each city. The effectiveness of water management was observed regarding the reduction of pesticide runoff. However, a greater potential of pesticide runoff remained in Western Japan. Secondly, an extended analysis was attempted to evaluate the effects of local water management and meteorological conditions between the Chikugo River basin and the Sakura River basin using uncertainty inputs processed from observed water management data. The results showed that because of more severe rainfall events, significant pesticide runoff occurred in the Chikugo River basin even when appropriate irrigation practices were implemented. © Pesticide Science Society of Japan.

Site and gender specificity of inheritance of bone mineral density

Differences in genetic control of BMD by skeletal sites and genders were examined by complex segregation analysis in 816 members of 147 families with probands with extreme low BMD. Spine BMD correlated more strongly in male-male comparisons and hip BMD in female-female comparisons, consistent with gender- and site-specificity of BMD heritability. Introduction: Evidence from studies in animals and humans suggests that the genetic control of bone mineral density (BMD) may differ at different skeletal sites and between genders. This question has important implications for the design and interpretation of genetic studies of osteoporosis. Methods: We examined the genetic profile of 147 families with 816 individuals recruited through probands with extreme low BMD (T-score < −2.5, Z-score < −2.0). Complex segregation analysis was performed using the Pedigree Analysis Package. BMD was measured by DXA at both lumbar spine (L1-L4) and femoral neck. Results: Complex segregation analysis excluded purely monogenic and environmental models of segregation of lumbar spine and femoral neck BMD in these families. Pure polygenic models were excluded at the lumbar spine when menopausal status was considered as a covariate, but not at the femoral neck. Mendelian models with a residual polygenic component were not excluded. These models were consistent with the presence of a rare Mendelian genotype of prevalence 3–19 %, causing high BMD at the hip and spine in these families, with additional polygenic effects. Total heritability range at the lumbar spine was 61–67 % and at the femoral neck was 44–67 %. Significant differences in correlation of femoral neck and lumbar spine BMD were observed between male and female relative pairs, with male-male comparisons exhibiting stronger lumbar spine BMD correlation than femoral neck, and female-female comparisons having greater femoral neck BMD correlation than lumbar spine. These findings remained true for parent-offspring correlations when menopausal status was taken into account. The recurrence risk ratio for siblings of probands of a Z-score < −2.0 was 5.4 at the lumbar spine and 5.9 at the femoral neck. Conclusions: These findings support gender- and site-specificity of the inheritance of BMD. These results should be considered in the design and interpretation of genetic studies of osteoporosis.

The case for “n«all”: Why the Big Data revolution will probably happen differently in the mining sector

Big Data and predictive analytics have received significant attention from the media and academic literature throughout the past few years, and it is likely that these emerging technologies will materially impact the mining sector. This short communication argues, however, that these technological forces will probably unfold differently in the mining industry than they have in many other sectors because of significant differences in the marginal cost of data capture and storage. To this end, we offer a brief overview of what Big Data and predictive analytics are, and explain how they are bringing about changes in a broad range of sectors. We discuss the “N=all” approach to data collection being promoted by many consultants and technology vendors in the marketplace but, by considering the economic and technical realities of data acquisition and storage, we then explain why a “n « all” data collection strategy probably makes more sense for the mining sector. Finally, towards shaping the industry’s policies with regards to technology-related investments in this area, we conclude by putting forward a conceptual model for leveraging Big Data tools and analytical techniques that is a more appropriate fit for the mining sector.

Site-controlled growth of Ge nanostructures on Si(100) via pulsed laser deposition nanostenciling

The authors combine nanostenciling and pulsed laser deposition to patterngermanium(Ge)nanostructures into desired architectures. They have analyzed the evolution of the Ge morphology with coverage. Following the formation of a wetting layer within each area defined by the stencil’s apertures, Gegrowth becomes three dimensional and the size and number of Ge nanocrystals evolve with coverage. Micro-Raman spectroscopy shows that the deposits are crystalline and epitaxial. This approach is promising for the parallel patterning of semiconductor nanostructures for optoelectronic applications.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Plantar pressure distribution character in young female with mild hallux valgus wearing high-heeled shoes

Young females with mild hallux valgus (HV) have been identified as having an increased risk of first ray deformation. Little is known, however, about the biomechanical changes that might contribute to this increased risk. The purpose of this study was to compare kinetics changes during walking for mild HV subjects with high-heel-height shoes. Twelve female subjects (six with mild HV and six controls) participated in this study with heel height varying from 0 cm (barefoot) to 4.5 cm. Compared to healthy controls, patients had significantly higher peak pressure on the big toe area during barefoot walking. When the heel height increased, loading was transferred to medial side of the forefoot, and the big toe area suffered more impact compared to barefoot in mild HV. This study also demonstrated that the center of pressure (COP) inclines to medial side alteration after high-heeled shoes wearing. These findings indicate that mild HV people should be discouraged from wearing high-heeled shoes.

Arterial luminal curvature and fibrous-cap thickness affect critical stress conditions within atherosclerotic plaque: An in vivo MRI-based 2D finite-element study

High mechanical stress in atherosclerotic plaques at vulnerable sites, called critical stress, contributes to plaque rupture. The site of minimum fibrous cap (FC) thickness (FCMIN) and plaque shoulder are well-documented vulnerable sites. The inherent weakness of the FC material at the thinnest point increases the stress, making it vulnerable, and it is the big curvature of the lumen contour over FC which may result in increased plaque stress. We aimed to assess critical stresses at FCMIN and the maximum lumen curvature over FC (LCMAX) and quantify the difference to see which vulnerable site had the highest critical stress and was, therefore, at highest risk of rupture. One hundred patients underwent high resolution carotid magnetic resonance (MR) imaging. We used 352 MR slices with delineated atherosclerotic components for the simulation study. Stresses at all the integral nodes along the lumen surface were calculated using the finite-element method. FCMIN and LCMAX were identified, and critical stresses at these sites were assessed and compared. Critical stress at FC MIN was significantly lower than that at LCMAX (median: 121.55 kPa; inter quartile range (IQR) = [60.70-180.32] kPa vs. 150.80 kPa; IQR = [91.39-235.75] kPa, p < 0.0001). If critical stress at FCMIN was only used, then the stress condition of 238 of 352 MR slices would be underestimated, while if the critical stress at LCMAX only was used, then 112 out of 352 would be underestimated. Stress analysis at FCMIN and LCMAX should be used for a refined mechanical risk assessment of atherosclerotic plaques, since material failure at either site may result in rupture.

Has the Three-Gorges Dam made the Poyang Lake wetlands wetter and drier?

The Three-Georges Dam holds many records in the history of engineering. While the dam has produced benefits in terms of flood control, hydropower generation and increased navigation capacity of the Yangtze River, serious questions have been raised concerning its impact on both upstream and downstream ecosystems. It has been suggested that the dam operation intensifies the extremes of wet and dry conditions in the downstream Poyang Lake, and affects adversely important local wetlands. A floodgate has been proposed to maintain the lake water level by controlling the flow between the Poyang Lake and Yangtze River. Using extensive hydrological data and generalized linear statistical models, we demonstrated that the dam operation induces major changes in the downstream river discharge near the dam, including an average "water loss". The analysis also revealed considerable effects on the Poyang Lake water level, particularly a reduced level over the dry period from late summer to autumn. However, the dam impact needs to be further assessed based on long-term monitoring of the lake ecosystem, covering a wide range of parameters related to hydrological and hydraulic characteristics of the lake, water quality, geomorphological characteristics, aquatic biota and their habitat, wetland vegetation and associated fauna.