90 research outputs found

    New BSFQ circuit designs with wide margins

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    Recently we have proposed novel Boolean Single-Flux-quantum (BSFQ) circuits, which Just like CMOS circuits support Boolean primitives directly, and do not require local synchronization for each operation cell. However, previous BSFQ AND, OR, and XOR cells suffered from problems with narrow margin, where their critical margins hardly exceeded +/- 10% due to low flux gain. Furthermore, while being suitable for combinational circuits, previous BSFQ NOT cells had initialization problems in sequential circuits. In this paper, new versions of these circuits with simulated margins beyond +/- 30% are proposed. Moreover, a Muller C-element, an error canceller, a destructive read-out (DRO), and a demultiplexer are also newly created. The operation time, parameter margins, and circuit size of these BSFQ cells are comparable to those of the conventional RSFQ cells

    Development and Validation of an Attitudinal-Profiling Tool for Patients With Asthma

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    Evaluation of methods and marker systems in genomic selection of oil palm (Elaeis guineensis Jacq.)

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    Background Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits. Results The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods. Conclusion Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation

    Genomic selection in commercial perennial crops: applicability and improvement in oil palm (Elaeis guineensis Jacq.)

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    Genomic selection (GS) uses genome-wide markers to select individuals with the desired overall combination of breeding traits. A total of 1,218 individuals from a commercial population of Ulu Remis x AVROS (UR x AVROS) were genotyped using the OP200K array. The traits of interest included: shellto- fruit ratio (S/F, %), mesocarp-to-fruit ratio (M/F, %), kernel-to-fruit ratio (K/F, %), fruit per bunch (F/B, %), oil per bunch (O/B, %) and oil per palm (O/P, kg/palm/year). Genomic heritabilities of these traits were estimated to be in the range of 0.40 to 0.80. GS methods assessed were RR-BLUP, Bayes A (BA), Cπ (BC), Lasso (BL) and Ridge Regression (BRR). All methods resulted in almost equal prediction accuracy. The accuracy achieved ranged from 0.40 to 0.70, correlating with the heritability of traits. By selecting the most important markers, RR-BLUP B has the potential to outperform other methods. The marker density for certain traits can be further reduced based on the linkage disequilibrium (LD). Together with in silico breeding, GS is now being used in oil palm breeding programs to hasten parental palm selection

    T Cell-Intrinsic and -Extrinsic Contributions of the IFNAR/STAT1-Axis to Thymocyte Survival

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    STAT1 is an essential part of interferon signaling, and STAT1-deficiency results in heightened susceptibility to infections or autoimmunity in both mice and humans. Here we report that mice lacking the IFNα/β-receptor (IFNAR1) or STAT1 display impaired deletion of autoreactive CD4+CD8+-T-cells. Strikingly, co-existence of WT T cells restored thymic elimination of self-reactive STAT1-deficient CD4+CD8+-T cells. Analysis of STAT1-deficient thymocytes further revealed reduced Bim expression, which was restored in the presence of WT T cells. These results indicate that type I interferons and STAT1 play an important role in the survival of MHC class I-restricted T cells in a T cell intrinsic and non-cell intrinsic manner that involves regulation of Bim expression through feedback provided by mature STAT1-competent T cells

    Biomechanical analysis of the lumbar spine on facet joint force and intradiscal pressure - a finite element study

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    <p>Abstract</p> <p>Background</p> <p>Finite element analysis results will show significant differences if the model used is performed under various material properties, geometries, loading modes or other conditions. This study adopted an FE model, taking into account the possible asymmetry inherently existing in the spine with respect to the sagittal plane, with a more geometrically realistic outline to analyze and compare the biomechanical behaviour of the lumbar spine with regard to the facet force and intradiscal pressure, which are associated with low back pain symptoms and other spinal disorders. Dealing carefully with the contact surfaces of the facet joints at various levels of the lumbar spine can potentially help us further ascertain physiological behaviour concerning the frictional effects of facet joints under separate loadings or the responses to the compressive loads in the discs.</p> <p>Methods</p> <p>A lumbar spine model was constructed from processes including smoothing the bony outline of each scan image, stacking the boundary lines into a smooth surface model, and subsequent further processing in order to conform with the purpose of effective finite element analysis performance. For simplicity, most spinal components were modelled as isotropic and linear materials with the exception of spinal ligaments (bilinear). The contact behaviour of the facet joints and changes of the intradiscal pressure with different postures were analyzed.</p> <p>Results</p> <p>The results revealed that asymmetric responses of the facet joint forces exist in various postures and that such effect is amplified with larger loadings. In axial rotation, the facet joint forces were relatively larger in the contralateral facet joints than in the ipsilateral ones at the same level. Although the effect of the preloads on facet joint forces was not apparent, intradiscal pressure did increase with preload, and its magnitude increased more markedly in flexion than in extension and axial rotation.</p> <p>Conclusions</p> <p>Disc pressures showed a significant increase with preload and changed more noticeably in flexion than in extension or in axial rotation. Compared with the applied preloads, the postures played a more important role, especially in axial rotation; the facet joint forces were increased in the contralateral facet joints as compared to the ipsilateral ones at the same level of the lumbar spine.</p

    A Survey of Bayesian Statistical Approaches for Big Data

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    The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A natural question is how these approaches differ from those that were available prior to the advent of Big Data. We present a review of published studies that present Bayesian statistical approaches specifically for Big Data and discuss the reported and perceived benefits of these approaches. We conclude by addressing the question of whether focusing only on improving computational algorithms and infrastructure will be enough to face the challenges of Big Data
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