An experimental comparison of several approaches to the linear least squares problem

Algorithms and original data matrix approaches compared for linear least squares proble

Mission design for a ballistic slow flyby Comet Encke 1980

Preliminary mission analyses for a proposed 1980 slow flyby (7-9 km/s) of comet Encke are presented. Among the topics covered are science objectives, Encke's physical activity and ephemeris accuracy, trajectory and launch-window analysis, terminal guidance, and spacecraft concepts. The nominal mission plan calls for a near-perihelion intercept with two spacecraft launched on a single launch vehicle. Both spacecraft will arrive at the same time, one passing within 500 km from Encke's nucleus on its sunward side, the other cutting through the tail region. By applying a small propulsive correction about three weeks after the encounter, it is possible to retarget both spacecraft for a second Encke intercept in 1984. The potential science return from the ballistic slow flyby is compared with other proposed mission modes for the 1980 Encke flyby mission, including the widely advocated slow flyby using solar-electric propulsion. It is shown that the ballistic slow flyby is superior in every respect

An addressable quantum dot qubit with fault-tolerant control fidelity

Exciting progress towards spin-based quantum computing has recently been made with qubits realized using nitrogen-vacancy (N-V) centers in diamond and phosphorus atoms in silicon, including the demonstration of long coherence times made possible by the presence of spin-free isotopes of carbon and silicon. However, despite promising single-atom nanotechnologies, there remain substantial challenges in coupling such qubits and addressing them individually. Conversely, lithographically defined quantum dots have an exchange coupling that can be precisely engineered, but strong coupling to noise has severely limited their dephasing times and control fidelities. Here we combine the best aspects of both spin qubit schemes and demonstrate a gate-addressable quantum dot qubit in isotopically engineered silicon with a control fidelity of 99.6%, obtained via Clifford based randomized benchmarking and consistent with that required for fault-tolerant quantum computing. This qubit has orders of magnitude improved coherence times compared with other quantum dot qubits, with T_2* = 120 mus and T_2 = 28 ms. By gate-voltage tuning of the electron g*-factor, we can Stark shift the electron spin resonance (ESR) frequency by more than 3000 times the 2.4 kHz ESR linewidth, providing a direct path to large-scale arrays of addressable high-fidelity qubits that are compatible with existing manufacturing technologies

MicroRNA-Integrated and Network-Embedded Gene Selection with Diffusion Distance

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways

Multi-wave coherent control of a solid-state single emitter

The authors acknowledge support by the European Research Council Starting Grant 'PICSEN' contract no. 306387.Coherent control of individual two-level systems (TLSs) is at the basis of any implementation of quantum information. An impressive level of control is now achieved using nuclear, vacancies and charge spins. Manipulation of bright exciton transitions in semiconductor quantum dots (QDs) is less advanced, principally due to the sub-nanosecond dephasing. Conversely, owing to their robust coupling to light, one can apply tools of nonlinear spectroscopy to achieve all-optical command. Here, we report on the coherent manipulation of an exciton via multi-wave mixing. Specifically, we employ three resonant pulses driving a single InAs QD. The first two induce a four-wave mixing (FWM) transient, which is projected onto a six-wave mixing (SWM) depending on the delay and area of the third pulse, in agreement with analytical predictions. Such a switch enables to demonstrate the generation of SWM on a single emitter and to engineer the spectro-temporal shape of the coherent response originating from a TLS. These results pave the way toward multi-pulse manipulations of solid state qubits via implementing the NMR-like control schemes in the optical domain.PostprintPeer reviewe

The cystic fibrosis transmembrane recruiter the alter ego of CFTR as a multi-kinase anchor

This review focuses on a newly discovered interaction between protein kinases involved in cellular energetics, a process that may be disturbed in cystic fibrosis for unknown reasons. I propose a new model where kinase-mediated cellular transmission of energy provides mechanistic insight to a latent role of the cystic fibrosis transmembrane conductance regulator (CFTR). I suggest that CFTR acts as a multi-kinase recruiter to the apical epithelial membrane. My group finds that, in the cytosol, two protein kinases involved in cell energy homeostasis, nucleoside diphosphate kinase (NDPK) and AMP-activated kinase (AMPK), bind one another. Preliminary data suggest that both can also bind CFTR (function unclear). The disrupted role of this CFTR-kinase complex as ‘membrane transmitter to the cell’ is proposed as an alternative paradigm to the conventional ion transport mediated and CFTR/chloride-centric view of cystic fibrosis pathogenesis. Chloride remains important, but instead, chloride-induced control of the phosphohistidine content of one kinase component (NDPK, via a multi-kinase complex that also includes a third kinase, CK2; formerly casein kinase 2). I suggest that this complex provides the necessary near-equilibrium conditions needed for efficient transmission of phosphate energy to proteins controlling cellular energetics. Crucially, a new role for CFTR as a kinase controller is proposed with ionic concentration acting as a signal. The model posits a regulatory control relay for energy sensing involving a cascade of protein kinases bound to CFTR

Working conditions, self-perceived stress, anxiety, depression and quality of life: A structural equation modelling approach

<p>Abstract</p> <p>Background</p> <p>The relationships between working conditions [job demand, job control and social support]; stress, anxiety, and depression; and perceived quality of life factors [physical health, psychological wellbeing, social relationships and environmental conditions] were assessed using a sample of 698 male automotive assembly workers in Malaysia.</p> <p>Methods</p> <p>The validated Malay version of the Job Content Questionnaire (JCQ), Depression Anxiety Stress Scales (DASS) and the World Health Organization Quality of Life-Brief (WHOQOL-BREF) were used. A structural equation modelling (SEM) analysis was applied to test the structural relationships of the model using AMOS version 6.0, with the maximum likelihood ratio as the method of estimation.</p> <p>Results</p> <p>The results of the SEM supported the hypothesized structural model (<it>χ</it>²= 22.801, <it>df </it>= 19, <it>p </it>= 0.246). The final model shows that social support (JCQ) was directly related to all 4 factors of the WHOQOL-BREF and inversely related to depression and stress (DASS). Job demand (JCQ) was directly related to stress (DASS) and inversely related to the environmental conditions (WHOQOL-BREF). Job control (JCQ) was directly related to social relationships (WHOQOL-BREF). Stress (DASS) was directly related to anxiety and depression (DASS) and inversely related to physical health, environment conditions and social relationships (WHOQOL-BREF). Anxiety (DASS) was directly related to depression (DASS) and inversely related to physical health (WHOQOL-BREF). Depression (DASS) was inversely related to the psychological wellbeing (WHOQOL-BREF). Finally, stress, anxiety and depression (DASS) mediate the relationships between job demand and social support (JCQ) to the 4 factors of WHOQOL-BREF.</p> <p>Conclusion</p> <p>These findings suggest that higher social support increases the self-reported quality of life of these workers. Higher job control increases the social relationships, whilst higher job demand increases the self-perceived stress and decreases the self-perceived quality of life related to environmental factors. The mediating role of depression, anxiety and stress on the relationship between working conditions and perceived quality of life in automotive workers should be taken into account in managing stress amongst these workers.</p