Concept: Personal computer
Principal component (PC) maps, which plot the values of a given PC estimated on the basis of allele frequency variation at the geographic sampling locations of a set of populations, are often used to investigate the properties of past range expansions. Some studies have argued that in a range expansion, the axis of greatest variation (i.e., the first PC) is parallel to the axis of expansion. In contrast, others have identified a pattern in which the axis of greatest variation is perpendicular to the axis of expansion. Here, we seek to understand this difference in outcomes by investigating the effect of the geographic sampling scheme on the direction of the axis of greatest variation under a two-dimensional range expansion model. From datasets simulated using each of two different schemes for the geographic sampling of populations under the model, we create PC maps for the first PC. We find that depending on the geographic sampling scheme, the axis of greatest variation can be either parallel or perpendicular to the axis of expansion. We provide an explanation for this result in terms of intra- and inter-population coalescence times.
This software package provides an R-based framework to make use of multi-core computers when running analyses in the population genetics program STRUCTURE. It is especially addressed to those users of STRUCTURE dealing with numerous and repeated data analyses, and who could take advantage of an efficient script to automatically distribute STRUCTURE jobs among multiple processors. It also consists of additional functions to divide analyses among combinations of populations within a single data set without the need to manually produce multiple projects, as it is currently the case in STRUCTURE. The package consists of two main functions: MPI_structure() and parallel_structure() as well as an example data file. We compared the performance in computing time for this example data on two computer architectures and showed that the use of the present functions can result in several-fold improvements in terms of computation time. ParallelStructure is freely available at https://r-forge.r-project.org/projects/parallstructure/.
The introduction of affordable, consumer-oriented 3-D printers is a milestone in the current “maker movement,” which has been heralded as the next industrial revolution. Combined with free and open sharing of detailed design blueprints and accessible development tools, rapid prototypes of complex products can now be assembled in one’s own garage-a game-changer reminiscent of the early days of personal computing. At the same time, 3-D printing has also allowed the scientific and engineering community to build the “little things” that help a lab get up and running much faster and easier than ever before.
SpeedSeq is an open-source genome analysis platform that accomplishes alignment, variant detection and functional annotation of a 50× human genome in 13 h on a low-cost server and alleviates a bioinformatics bottleneck that typically demands weeks of computation with extensive hands-on expert involvement. SpeedSeq offers performance competitive with or superior to current methods for detecting germline and somatic single-nucleotide variants, structural variants, insertions and deletions, and it includes novel functionality for streamlined interpretation.
SUMMARY: Computational workloads for genome-wide association studies (GWAS) are growing in scale and complexity outpacing the capabilities of single-threaded software designed for personal computers. The BlueSNP R package implements GWAS statistical tests in the R programming language and executes the calculations across computer clusters configured with Apache Hadoop, a de facto standard framework for distributed data processing using the MapReduce formalism. BlueSNP makes computationally intensive analyses, such as estimating empirical p-values via data permutation, and searching for expression quantitative trait loci over thousands of genes, feasible for large genotype-phenotype datasets.Availability and implementation: http://github.com/ibm-bioinformatics/bluesnp CONTACT: firstname.lastname@example.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
A virtual pet in the form of a mid-sized dog was developed based on the framework of social cognitive theory and tested as a vehicle for promoting fruit and vegetable (F&V) consumption in children. Three groups of children (N = 68) between the ages of 7 and 13 years were studied: baseline (no treatment), computer only, and virtual dog. Children in the virtual dog condition interacted with the virtual dog for 3 days, setting F&V consumption goals and receiving evaluation and reinforcement based on whether they met their self-set goals. Children vicariously experienced future health outcomes of F&V consumption by seeing, hearing, and feeling their virtual dog’s physical and mental health improve or deteriorate based on their F&V consumption in the physical world. Children in the computer only condition interacted with a computer system that presented equivalent features, but without the virtual dog. Children in the baseline condition did not receive any experimental treatment. Results indicated that children in the virtual dog condition chose to be served significantly more F&V than those in the computer only or baseline conditions did. However, children in the virtual dog condition were unable to consume significantly more F&V than those in the computer only condition, although children in those two conditions consumed more F&V than the baseline condition. Food preferences did not differ significantly across the three conditions before and after the experimental treatments. Theoretical and practical potentials of using a virtual pet to promote F&V consumption systematically in children are discussed.
Tachistoscopes allow brief visual stimulation delivery, which is crucial for experiments in which subliminal presentation is required. Up to now, tachistoscopes have had shortcomings with respect to timing accuracy, reliability, and flexibility of use. Here, we present a new and inexpensive two-channel tachistoscope that allows for exposure durations in the submillisecond range with an extremely high timing accuracy. The tachistoscope consists of two standard liquid-crystal display (LCD) monitors of the light-emitting diode (LED) backlight type, a semipermeable mirror, a mounting rack, and an experimental personal computer (PC). The monitors have been modified to provide external access to the LED backlights, which are controlled by the PC via the standard parallel port. Photodiode measurements confirmed reliable operation of the tachistoscope and revealed switching times of 3 μs. Our method may also be of great advantage in single-monitor setups, in which it allows for manipulating the stimulus timing with submillisecond precision in many experimental situations. Where this is not applicable, the monitor can be operated in standard mode by disabling the external backlight control instantaneously.
As electronic learning (e-learning) becomes increasingly popular in education worldwide, learning technology (LT) has been applied in various learning environments and activities to promote meaningful, efficient, and effective learning. LT has also been adopted by researchers and teacher-practitioners in the field of special education, but as yet little review-based research has been published. This review research thus carefully examined the trends of LT implementations in special education, providing a comprehensive analysis of 26 studies published in indexed journals in the past five years (2008-2012). Two research questions were addressed: (a) What are the major research aims, methodologies, and outcomes in these studies of implementing LT in the field of special education? and (b) What types of LT are mainly used with special education students, and for what kinds of students? Major findings include that examining the learning effectiveness of LT using was the most common research purpose (75%); researchers primarily relied on experimental studies (46%, 12 studies), followed by interviews and questionnaires (19%, 5 studies). Moreover, the most common use of LT was computer-assisted technology (such as web-based mentoring, educational computer games, laptop computers) in special education; studies investigating the use of LT with mentally disabled students were more than those with physically disabled ones. It is expected that the findings of this work and their implications will serve as valuable references with regard to the use of LT with special education students.
This paper presents a low-cost microcontroller-based data acquisition device. The key component of the presented solution is a configurable microcontroller-based device with an integrated USB transceiver and a 12-bit analogue-to-digital converter (ADC). The presented embedded DAQ device contains a preloaded program (firmware) that enables easy acquisition and generation of analogue and digital signals and data transfer between the device and the application running on a PC via USB bus. This device has been developed as a USB human interface device (HID). This USB class is natively supported by most of the operating systems and therefore any installation of additional USB drivers is unnecessary. The input/output peripheral of the presented device is not static but rather flexible, and could be easily configured to customised needs without changing the firmware. When using the developed configuration utility, a majority of chip pins can be configured as analogue input, digital input/output, PWM output or one of the SPI lines. In addition, LabVIEW drivers have been developed for this device. When using the developed drivers, data acquisition and signal processing algorithms as well as graphical user interface (GUI), can easily be developed using a well-known, industry proven, block oriented LabVIEW programming environment.
Computer screen videos (CSVs) and users' facial expressions videos (FEVs) are recommended to evaluate systems performance. However, software combining both methods is often non-accessible in clinical research fields. The Observer-XT software is commonly used for clinical research to assess human behaviours. Thus, this study reports on the combination of CSVs and FEVs, to evaluate a graphical user interface (GUI). Eight physiotherapists entered clinical information in the GUI while CSVs and FEVs were collected. The frequency and duration of a list of behaviours found in FEVs were analysed using the Observer-XT-10.5. Simultaneously, the frequency and duration of usability problems of CSVs were manually registered. CSVs and FEVs timelines were also matched to verify combinations. The analysis of FEVs revealed that the category most frequently observed in users behaviour was the eye contact with the screen (ECS, 32±9) whilst verbal communication achieved the highest duration (14.8±6.9min). Regarding the CSVs, 64 problems, related with the interface (73%) and the user (27%), were found. In total, 135 usability problems were identified by combining both methods. The majority were reported through verbal communication (45.8%) and ECS (40.8%). “False alarms” and “misses” did not cause quantifiable reactions and the facial expressions problems were mainly related with the lack of familiarity (55.4%) felt by users when interacting with the interface. These findings encourage the use of Observer-XT-10.5 to conduct small usability sessions, as it identifies emergent groups of problems by combining methods. However, to validate final versions of systems further validation should be conducted using specialized software.