Linkage and association analyses of microsatellites and single-nucleotide polymorphisms in nuclear families

Several simulation studies have suggested that a high-density single-nucleotide polymorphisms (SNPs) marker set may be as useful as a traditional microsatellites (MS) marker set in performing whole-genome linkage analysis. However, very few studies have directly tested the SNPs-based genome-wide scan. In the present study, we compared the linkage results from the SNPs-based scan with a map density of 3-cM spacing with those from the MS scan using a 10-cM marker set among 300 nuclear families each from the Aipotu (AI), Danacaa (DA), and Karangar (KA) populations from the simulated Genetic Analysis Workshop 14 Problem 2 data. We found that information contents obtained from the SNPs scan were somewhat lower than those from the MS scan. However, the linkage results obtained from the two scans showed a high degree of similarity. Both scans identified a similar number of chromosomal regions attaining nominal significance (p < 0.05). Specifically, both scans detected confirmed evidence for linkage (NPL ≥ 4.07, p = 2 × 10(-5)) to chromosome 1 in the AI families, chromosomes 1 and 3 in the DA families, and chromosomes 3, 5, and 9 in the KA families. An additional confirmed linkage to chromosome 5 in the AI families was detected only by the MS scan. We also observed slightly wider 1-LOD intervals for more of the SNP peaks than for the MS peaks, which is likely due to lower information contents for the SNPs. Subsequent fine-mapping association analysis further identified 2 to 3 markers significantly associated with disease status in each population; B03T3056, B03T3058, and B05T4139 in the AI population, B03T3056 and B03T3058 in the KA population, and B03T3056, B03T3057, and B03T3058 in the DA population. Among the four markers, three were chosen based on results obtained from the two scans, but one was solely from the SNP scan. In summary, our finding suggests that the SNP-based genome scan has the potential to be as powerful as the traditional MS-based scan and offers good identification of peak location for further fine-mapped association analysis

Anomalous gauge couplings of the Higgs boson at the CERN LHC: Semileptonic mode in WW scatterings

We make a full tree level study of the signatures of anomalous gauge couplings of the Higgs boson at the CERN LHC via the semileptonic decay mode in WW scatterings. Both signals and backgrounds are studied at the hadron level for the Higgs mass in the range 115 GeV to 200 GeV. We carefully impose suitable kinematical cuts for suppressing the backgrounds. To the same sensitivity as in the pure leptonic mode, our result shows that the semileptonic mode can reduce the required integrated luminosity by a factor of 3. If the anomalous couplings in nature are actually larger than the sensitivity bounds shown in the text, the experiment can start the test for an integrated luminosity of 50 inverse fb.Comment: PACS numbers updated. Version published in Phys.Rev.D79,055010(2009

Average AoI Minimization for Energy Harvesting Relay-aided Status Update Network Using Deep Reinforcement Learning

A dual-hop status update system aided by energy harvesting (EH) relays with finite data and energy buffers is studied in this work. To achieve timely status updates, the best relays should be selected to minimize the average age of information (AoI), which is a recently proposed metric to evaluate information freshness. The average AoI minimization can be formulated as a Markov decision process (MDP), but the state space for capturing channel and buffer evolution grows exponentially with the number of relays, leading to high solution complexity. We propose a relay selection (RS) scheme based on deep reinforcement learning (DRL) according to the instantaneous channel packet freshness and buffer information of each relay. Simulation results show a significant improvement of the proposed DRL-based RS scheme over state-of-art approaches.Comment: This article has been accepted for publication in IEEE Wireless Communications Letters. Citation information: DOI 10.1109/LWC.2023.327886

Dynamic Magneto-Conductance Fluctuations and Oscillations in Mesoscopic Wires and Rings

Using a finite-frequency recursive Green's function technique, we calculate the dynamic magneto-conductance fluctuations and oscillations in disordered mesoscopic normal metal systems, incorporating inter-particle Coulomb interactions within a self-consistent potential method. In a disordered metal wire, we observe ergodic behavior in the dynamic conductance fluctuations. At low $\omega$, the real part of the conductance fluctuations is essentially given by the dc universal conductance fluctuations while the imaginary part increases linearly from zero, but for $\omega$ greater than the Thouless energy and temperature, the fluctuations decrease as $\omega^{-1/2}$. Similar frequency-dependent behavior is found for the Aharonov-Bohm oscillations in a metal ring. However, the Al'tshuler-Aronov-Spivak oscillations, which predominate at high temperatures or in rings with many channels, are strongly suppressed at high frequencies, leading to interesting crossover effects in the $\omega$-dependence of the magneto-conductance oscillations.Comment: 4 pages, REVTeX 3.0, 5 figures(ps file available upon request), #phd0

Understanding the e+e−→D(∗)+D(∗)−e^+e^-\to D^{(*)+}D^{(*)-} processes observed by Belle

We calculate the production cross sections for $D^{*+}D^{*-}$, $D^+D^{*-}$ and $D^+D^-$ in $e^+e^-$ annihilation through one virtual photon in the framework of perturbative QCD with constituent quarks. The calculated cross sections for $D^{*+}D^{*-}$ and $D^+D^{*-}$ production are roughly in agreement with the recent Belle data. The helicity decomposition for $D^{*}$ meson production is also calculated. The fraction of the $D^{*\pm}_LD^{*\mp}_T$ final state in $e^+e^-\to D^{*+}D^{*-}$ process is found to be 65%. The fraction of $DD^*_T$ production is 100% and $DD^*_L$ is forbidden in $e^+e^-$ annihilation through one virtual photon. We further consider $e^+e^-$ annihilation through two virtual photons, and then find the fraction of $DD^{*}_T$ in $e^+e^-\to DD^{*}$ process to be about 91%.Comment: 8 pages, 2 figure

Boosting alternating decision trees modeling of disease trait information

We applied the alternating decision trees (ADTrees) method to the last 3 replicates from the Aipotu, Danacca, Karangar, and NYC populations in the Problem 2 simulated Genetic Analysis Workshop dataset. Using information from the 12 binary phenotypes and sex as input and Kofendrerd Personality Disorder disease status as the outcome of ADTrees-based classifiers, we obtained a new quantitative trait based on average prediction scores, which was then used for genome-wide quantitative trait linkage (QTL) analysis. ADTrees are machine learning methods that combine boosting and decision trees algorithms to generate smaller and easier-to-interpret classification rules. In this application, we compared four modeling strategies from the combinations of two boosting iterations (log or exponential loss functions) coupled with two choices of tree generation types (a full alternating decision tree or a classic boosting decision tree). These four different strategies were applied to the founders in each population to construct four classifiers, which were then applied to each study participant. To compute average prediction score for each subject with a specific trait profile, such a process was repeated with 10 runs of 10-fold cross validation, and standardized prediction scores obtained from the 10 runs were averaged and used in subsequent expectation-maximization Haseman-Elston QTL analyses (implemented in GENEHUNTER) with the approximate 900 SNPs in Hardy-Weinberg equilibrium provided for each population. Our QTL analyses on the basis of four models (a full alternating decision tree and a classic boosting decision tree paired with either log or exponential loss function) detected evidence for linkage (Z ≥ 1.96, p < 0.01) on chromosomes 1, 3, 5, and 9. Moreover, using average iteration and abundance scores for the 12 phenotypes and sex as their relevancy measurements, we found all relevant phenotypes for all four populations except phenotype b for the Karangar population, with suggested subgroup structure consistent with latent traits used in the model. In conclusion, our findings suggest that the ADTrees method may offer a more accurate representation of the disease status that allows for better detection of linkage evidence