On-board processing for future satellite communications systems: Satellite-Routed FDMA

A frequency division multiple access (FDMA) 30/20 GHz satellite communications architecture without on-board baseband processing is investigated. Conceptual system designs are suggested for domestic traffic models totaling 4 Gb/s of customer premises service (CPS) traffic and 6 Gb/s of trunking traffic. Emphasis is given to the CPS portion of the system which includes thousands of earth terminals with digital traffic ranging from a single 64 kb/s voice channel to hundreds of channels of voice, data, and video with an aggregate data rate of 33 Mb/s. A unique regional design concept that effectively smooths the non-uniform traffic distribution and greatly simplifies the satellite design is employed. The satellite antenna system forms thirty-two 0.33 deg beam on both the uplinks and the downlinks in one design. In another design matched to a traffic model with more dispersed users, there are twenty-four 0.33 deg beams and twenty-one 0.7 deg beams. Detailed system design techniques show that a single satellite producing approximately 5 kW of dc power is capable of handling at least 75% of the postulated traffic. A detailed cost model of the ground segment and estimated system costs based on current information from manufacturers are presented

Percolation model for nodal domains of chaotic wave functions

Nodal domains are regions where a function has definite sign. In recent paper [nlin.CD/0109029] it is conjectured that the distribution of nodal domains for quantum eigenfunctions of chaotic systems is universal. We propose a percolation-like model for description of these nodal domains which permits to calculate all interesting quantities analytically, agrees well with numerical simulations, and due to the relation to percolation theory opens the way of deeper understanding of the structure of chaotic wave functions.Comment: 4 pages, 6 figures, Late

Theory of spin and charge fluctuations in the Hubbard model

A self-consistent theory of both spin and charge fluctuations in the Hubbard model is presented. It is in quantitative agreement with Monte Carlo data at least up to intermediate coupling $(U\sim 8t)$. It includes both short-wavelength quantum renormalization effects, and long-wavelength thermal fluctuations which can destroy long-range order in two dimensions. This last effect leads to a small energy scale, as often observed in high temperature superconductors. The theory is conserving, satisfies the Pauli principle and includes three-particle correlations necessary to account for the incipient Mott transition.Comment: J1K 2R1 10 pages, Revtex 3.0, 4 uuencoded postscript figures, report# CRPS-93-4

Trapped 6^{6}Li : A high T_c superfluid ?

We consider the effect of the indirect interaction due to the exchange of density fluctuations on the critical temperature of superfluid $^{6}$Li . We obtain the strong coupling equation giving this critical temperature. This equation is solved approximately by retaining the same set of diagrams as in the paramagnon model. We show that, near the instability threshold, the attractive interaction due to density fluctuations gives rise to a strong increase in the critical temperature, providing a clear signature of the existence of fluctuation induced interactions.Comment: 4 pages, revtex, 1 figur

Fusing data mining, machine learning and traditional statistics to detect biomarkers associated with depression

BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. METHODS: The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. RESULTS: After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). CONCLUSION: The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin

Complementary medicine, exercise, meditation, diet, and lifestyle modification for anxiety disorders : a review of current evidence

Use of complementary medicines and therapies (CAM) and modification of lifestyle factors such as physical activity and exercise, and diet are being increasingly considered as potential therapeutic options for anxiety disorders. The objective of this metareview was to examine evidence across a broad range of CAM and lifestyle interventions in the treatment of anxiety disorders. In early 2012 we conducted a literature search of PubMed, Scopus, CINAHL, Web of Science, PsycInfo, and the Cochrane Library, for key studies, systematic reviews, and metaanalyses in the area. Our review found that in respect to treatment of generalized anxiety or specific anxiety disorders, CAM evidence revealed support for the herbal medicine Kava. One isolated study shows benefit for naturopathic medicine, whereas acupuncture, yoga, and Tai chi have tentative supportive evidence, which is hampered by overall poor methodology. The breadth of evidence does not support homeopathy for treating anxiety. Strong support exists for lifestyle modifications including adoption of moderate exercise and mindfulness meditation, whereas dietary improvement, avoidance of caffeine, alcohol, and nicotine offer encouraging preliminary data. In conclusion, certain lifestyle modifications and some CAMs may provide a beneficial role in the management of anxiety disorders

Coulomb suppression of NMR coherence peak in fullerene superconductors

The suppressed NMR coherence peak in the fullerene superconductors is explained in terms of the dampings in the superconducting state induced by the Coulomb interaction between conduction electrons. The Coulomb interaction, modelled in terms of the onsite Hubbard repulsion, is incorporated into the Eliashberg theory of superconductivity with its frequency dependence considered self-consistently at all temperatures. The vertex correction is also included via the method of Nambu. The frequency dependent Coulomb interaction induces the substantial dampings in the superconducting state and, consequently, suppresses the anticipated NMR coherence peak of fullerene superconductors as found experimentally.Comment: 4 pages, Revtex, and 2 figures. Revised and final version to appear in Phys. Rev. Lett. (1998