RNA sequencing (RNA-seq) is the conventional genome-scale approach used to capture the expression levels of all detectable genes in a biological sample. This is now regularly used for population-based studies designed to identify genetic determinants of various diseases. Naturally, the accuracy of these tests should be verified and improved if possible. In this study, we aimed to detect and correct for expression level-dependent errors which are not corrected by conventional normalization techniques. We examined several RNA-seq datasets from the Cancer Genome Atlas (TCGA), Stand Up 2 Cancer (SU2C), and GTEx databases with various types of preprocessing. By applying local averaging, we found expression-level dependent biases that differ from sample to sample in all datasets studied. Using simulations, we show that these biases corrupt gene-gene correlation estimations and t tests between subpopulations. To mitigate these biases, we introduce two different nonlinear transforms based on statistical considerations that correct these observed biases. We demonstrate that these transforms effectively remove the observed per-sample biases, reduce sample-to-sample variance, and improve the characteristics of gene-gene correlation distributions. Using a novel simulation methodology that creates controlled differences between subpopulations, we show that these transforms reduce variability and increase sensitivity of two population tests. The improvements in sensitivity and specificity were of the order of 3-5% in most instances after the data was corrected for bias. Altogether, these results improve our capacity to understand gene-gene relationships, and may lead to novel ways to utilize the information derived from clinical tests.

BACKGROUND: Proliferation and expansion of security risks necessitates new measures to ensure authenticity and validation of GMOs. Watermarking and other cryptographic methods are available which conceal and recover the original signature, but in the process reveal the authentication information. In many scenarios watermarking and standard cryptographic methods are necessary but not sufficient and new, more advanced, cryptographic protocols are necessary. RESULTS: Herein, we present a new crypto protocol, that is applicable in broader settings, and embeds the authentication string indistinguishably from a random element in the signature space and the string is verified or denied without disclosing the actual signature. Results show that in a nucleotide string of 1000, the algorithm gives a correlation of 0.98 or higher between the distribution of the codon and that of E. coli, making the signature virtually invisible. CONCLUSIONS: This algorithm may be used to securely authenticate and validate GMOs without disclosing the actual signature. While this protocol uses watermarking, its novelty is in use of more complex cryptographic techniques based on zero knowledge proofs to encode information.

A new design method for optimizing Gough-Stewart platform geometries is proposed in this paper. The prior studies are extended through optimizing both the kinematics and dynamics. Firstly, a new class of weighted orthogonal Gough-Stewart platforms (w-OGSPs) is proposed. Then the concept of simultaneously diagonal OGSPs (sd-OGSPs) is defined. The sd-OGSPs allow the Cartesian second order impedance to be specified, thus obtaining desired local system poles. Design algorithms and simulation results are given

For any manipulator, fault tolerance is a desirable property. This paper shows that for any serial or parallel manipulator functioning about a single point in its workspace, the mean square of the relative manipulabilities over all possible failures, with a given number of links failing at a time, is always constant irrespective of the geometry of the manipulator. In this paper optimal fault tolerant manipulability is defined for parallel manipulators. This concept is applied to orthogonal Gough-Stewart platforms (OGSPs) to identify a class of symmetric OGSPs having optimal fault tolerant manipulability. As an example, an 8-strut OGSP having this property is described

This paper develops new, analytical methods to find a large class of orthogonal Gough-Stewart platforms (OGSPs) having desired properties at their home position. In contrast, prior methods have been computationally intensive, relying on numerical search techniques. By exploiting symmetry, 27 equations are reduced to only two. The new techniques are directly applicable to clean-sheet design of micro-manipulators, vibration isolators, and Cartesian stiffness matrices. In addition, straightforward methods for retro-fitting existing OGSPs are illustrated. Because the new theory greatly simplifies OGSP formulas about a single point, it is expected that these results will also prove to be very useful when numerically designing gross motion platforms

Parallel mechanisms frequently possess an unstable type of singularity that has no counterpart in serial mechanisms. When the mechanism is at or near this type of singularity, it loses the ability to counteract external forces in certain directions. The determination of unstable singular configurations in parallel robots is challenging, and in the past, has been tackled by exhaustive numerical searches of the mechanism workspace using an accurate analytical model of the mechanism kinematics. This paper considers the singularity-determination problem from a geometric perspective for n-legged spatial parallel mechanisms. By using the constraints on the passive joint velocities, a necessary condition for an unstable singularity is derived.

This paper develops new, analytical methods to find a large class of Orthogonal Gough-Stewart Platforms (OGSPs) having desired manipulabilities at a single point. In contrast, prior methods have been computationally intensive, relying on numerical search techniques. The new techniques are directly applicable to clean sheet design of micro-manipulators, vibration isolators, and Cartesian stiffness matrices. In addition, straightforward methods for retro-fitting existing OGSPs are illustrated. The approach relies on symmetrically repeating a strut at least three times.

Parallel mechanisms frequently possess an unstable type of singularity that has no counterpart in serial mechanisms. When the mechanism is at or near this type of singularity, it loses the ability to counteract external forces in certain directions. The determination of unstable singular configurations in parallel robots is challenging, and in the past has been tackled by exhaustive numerical searches of the mechanism workspace using an accurate analytical model of the mechanism kinematics. This paper considers the singularity determination problem from a geometric perspective for n-legged spatial parallel mechanisms. By using the constraints on the passive joint velocities, a necessary condition for unstable singularity is derived that identifies the reason for such singularities.

Parallel mechanisms frequently possess an unstable type of singularity that has no counterpart in serial mechanisms. When the mechanism is at or near this type of singularity, it loses the ability to counteract external forces in certain directions. The determination of unstable singular configurations in parallel robots is challenging, and in the past has been tackled by exhaustive numerical searches of the mechanism workspace using an accurate analytical model of the mechanism kinematics. This paper considers the singularity determination problem from a geometric perspective for n-legged spatial parallel mechanisms. By using the constraints on the passive joint velocities, a necessary condition for unstable singularity is derived that identifies the reason for such singularities.

This paper develops methods for generating classes of orthogonal Gough-Stewart platforms (OGSPs). First, a new, two-parameter class of six-strut OGSPs which leads to isotropic manipulators are found. Next, this class is extended to include redundant Gough-Stewart platforms (GSPs). For an even number of struts, the same algorithm used to generate the six-strut case can be employed. For an odd number of struts, similar essential concepts are used to derive seven-strut and nine-strut OGSPs. Maximization of fault tolerance is implemented for a nine-strut isotropic OGSP. By exploiting invariant properties of the inverse Jacobian, new methods for favorably altering the center of gravity, strut attachment surface, and strut spatial distribution are developed.

Optimal geometric design is of key importance to the performance of a manipulator. First, this paper extends the work in Y. Yi, et al., (2004) to generate a class of isotropic Gough-Stewart platforms (GSPs) with an odd number of struts. Then, it develops methods for finding a highly fault tolerant GSP from that class. Two optimization criteria are considered, isotropy and fault tolerance. To meet the mission critical needs imposed by laser weapons applications, nine-strut isotropic GSPs that retain kinematic stability despite the loss of any three struts are found. First, we develop methods for generating a five parameter class of isotropic nine-strut GSPs. Next, new measures of fault tolerance are introduced and used to optimize the free parameter space. The optimized design is much more fault tolerant than the GSP currently baselined for the airborne laser.

This paper develops methods for generating classes of orthogonal Gough-Stewart platforms (OGSPs). First, a new, two-parameter class of six-strut OGSPs is found. For an even number of struts, the same essential concepts used to generate the six-strut case can be employed to generate OGSPs with eight struts, ten struts, etc. Next, by exploiting invariant properties of the inverse Jacobian, new methods for favorably altering the center of gravity, strut attachment surface, and strut spatial distribution are developed. As an illustrative example, these methods are applied to the design of the attachment of vibration isolation and precision pointing system for the space based laser.

Development of methods to design optimal Gough-Stewart platform geometries capable of meeting desired specifications is of high interest. Computationally intensive methods have been used to treat this problem in various settings. This paper uses analytic methods to characterize all orthogonal Gough-Stewart platforms (OGSPs) and to study their properties over a small workspace. This characterization is used to design optimal OGSPs for precision applications that achieve a desired hyperellipsoid of velocities. Some examples demonstrating the versatility of this theory are discussed.

This research investigates the capability of a multiprocessor system in guaranteeing the execution of critical tasks and determines the cause of deadline failures. By implementing a real-time application using an INMOS transputer and Occam language, we were able to distribute required tasks among the processors and determine their CPUs usage. We evaluated the performance of the system in terms of the number of guaranteed critical and non-critical tasks, arrival rates, and conflicting deadlines.