Probing the messenger of supersymmetry breaking by the muon anomalous magnetic moment

Motivated by the recently measured muon's anomalous magnetic moment $a_{\mu}$, we examine the supersymmetry contribution to $a_{\mu}$ in various mediation models of supersymmetry breaking which lead to predictive flavor conserving soft parameters at high energy scale. The studied models include dilaton/modulus-mediated models in heterotic string/$M$ theory, gauge-mediated model, no-scale or gaugino-mediated model, and also the minimal and deflected anomaly-mediated models. For each model, the range of $a^{SUSY}_{\mu}$ allowed by other experimental constraints, e.g. b --> s\gamma and the collider bounds on superparticle masses, is obtained together with the corresponding parameter region of the model. Gauge-mediated models with low messenger scale can give any $a^{SUSY}_{\mu}$ within the $2\sigma$ bound. In many other models, b --> s\gamma favors $a^{SUSY}_{\mu}$ smaller than either the $-1\sigma$ value ($26\times 10^{-10}$) or the central value ($42\times 10^{-10}$).Comment: RevTeX, 29 pages, 14 eps figures, figure for deflected anomaly mediation is corrected, reference adde

Performance of Network-Based RTK GPS in Low-Latitude Region: A Case Study in Thailand

Thailand has established a Network-based Real Time Kinematic (NRTK) GPS system using the Virtual Reference Station (VRS) concept since 2008. Currently, the Thai NRTK consists of 11 reference stations located in the central part of Thailand with averaged reference station spacing at 60 km. A Previous test suggested some problems with the low rate of ambiguity-fixing and the large number of position jumps even when the ambiguity-fixed solutions could be obtained. In this paper, the position performance of NRTK is tested with a large number of GPS observations (31 consecutive days) and different reference receiver spacing, 10 - 20, 30 - 50, 50 - 60 and 60 - 80 km, with the use of all available Continuous GPS (CGPS) stations in the central part of Thailand. Test results indicate that the NRTK positioning performance is degraded when the reference station spacing is increased. It is also found that the ionospheric bias is the main error source that affects the performance of NRTK in Thailand. Even with the 10-20km reference station spacing, reliable ambiguity-fixed solutions could hardly be obtained during the period of high ionospheric variation. Thus, it is recommended that the reference station spacing should be kept less than 30 km. In order to achieve the relaible NRTK solutions especially in low-latitude region like in Thailand, the ionospheric bias should be properly handled

Performance Assessment of GPS-Sensed Precipitable Water Vapor using IGS Ultra-Rapid Orbits: A Preliminary Study in Thailand

Precipitable Water Vapor (PWV) is a significant variable used for climate change studies. Currently PWV can be derived from the Global Positioning System (GPS) observation in addition to the specific instruments such as Radiosondes (RS), Microwave Radiometers (MWR) and Meteorological Satellites. To accurately derive PWV from GPS data, long periods of observation time in conjunction with final orbit data have to be applied in the data processing steps. This final orbit data can be acquired from the International GNSS Service (IGS) with 13 days latency, which is not practical in climate change studies or meteorological forecasting. Alternatively, real-time ultra-rapid orbits are more suitable for this application but with lower orbit accuracy. It is therefore interesting to evaluate the impact of using different orbits in the estimation of PWV. In this study, data from permanent GPS base stations in Thailand were processed using Bernese 5.0 software to derive near real-time PWV values. Ultra-rapid orbit data have been introduced in the data processing step with different time windows and compared to that using final orbit data with the 24-hr time window. The results have shown that 1.0 mm and 2.9 mm biases can be achieved using 24-hr and 12-hr time windows, respectively. These results therefore address the potential use of ultra-rapid orbits for a near real-time estimation of PWV

The use of Facebook in a multi-course collaborative project within a cross-cultural context

Facebook is the most popular social network site worldwide with over one billion active users every month (Facebook, 2012) and most university students are already using it. Therefore, implementing it into the classroom provides a familiar environment for students. The benefits of Facebook use, such as interaction, communication, social relationship, and participation, have been found to affect student motivation in learning (Lam, 2012). However, the role of Facebook use in student attitude and intention toward the project has not been examined in a multi-course, multi-cultural context

NuTrea: Neural Tree Search for Context-guided Multi-hop KGQA

Multi-hop Knowledge Graph Question Answering (KGQA) is a task that involves retrieving nodes from a knowledge graph (KG) to answer natural language questions. Recent GNN-based approaches formulate this task as a KG path searching problem, where messages are sequentially propagated from the seed node towards the answer nodes. However, these messages are past-oriented, and they do not consider the full KG context. To make matters worse, KG nodes often represent proper noun entities and are sometimes encrypted, being uninformative in selecting between paths. To address these problems, we propose Neural Tree Search (NuTrea), a tree search-based GNN model that incorporates the broader KG context. Our model adopts a message-passing scheme that probes the unreached subtree regions to boost the past-oriented embeddings. In addition, we introduce the Relation Frequency-Inverse Entity Frequency (RF-IEF) node embedding that considers the global KG context to better characterize ambiguous KG nodes. The general effectiveness of our approach is demonstrated through experiments on three major multi-hop KGQA benchmark datasets, and our extensive analyses further validate its expressiveness and robustness. Overall, NuTrea provides a powerful means to query the KG with complex natural language questions. Code is available at https://github.com/mlvlab/NuTrea.Comment: Neural Information Processing Systems (NeurIPS) 202

Decadal changes in the leading patterns of sea level pressure in the Arctic and their impacts on the sea ice variability in boreal summer

Besides its negative trend, the interannual and the interdecadal changes in the Arctic sea ice have also been pronounced in recent decades. The three leading modes in the sea level pressure (SLP) variability in the Arctic (70???90??????N) ??? the Arctic Oscillation (AO), the Arctic Dipole (AD), and the third mode (A3) ??? are analyzed to understand the linkage between sea ice variability and large-scale atmospheric circulation in boreal summer (June???August). This study also compares the decadal changes of the modes between the early (1982???1997) and the recent (1998???2017) periods and their influences on the Arctic sea ice extent (SIE). Only the AD mode shows a significant correlation increase with SIE in summer (JJA) from ???0.05 in the early period to 0.57 in the recent period. The AO and the A3 modes show a less significant relationship with SIE for the two periods. The AD is characterized by a dipole pattern of SLP, which modulates the strength of meridional surface winds and the Transpolar Drift Stream (TDS). The major circulation change in the late 1990s is that the direction of the wind has been changed more meridionally over the exit region of the Fram Strait, which causes sea ice drift and discharge through that region. In addition, the response of surface albedo and the net surface heat flux becomes larger and much clearer, suggesting a positive sea-ice???albedo feedback in the sea ice variability associated with the AD. The analysis also reveals that the zonal shift of the centers of SLP anomalies and associated circulation change affects a significant reduction in sea ice concentration over the Pacific sector of the Arctic Ocean. This study further suggests that the Pacific Decadal Oscillation (PDO) phase change could influence the spatial pattern change in the AD

CSGM Designer: a platform for designing cross-species intron-spanning genic markers linked with genome information of legumes.

BackgroundGenetic markers are tools that can facilitate molecular breeding, even in species lacking genomic resources. An important class of genetic markers is those based on orthologous genes, because they can guide hypotheses about conserved gene function, a situation that is well documented for a number of agronomic traits. For under-studied species a key bottleneck in gene-based marker development is the need to develop molecular tools (e.g., oligonucleotide primers) that reliably access genes with orthology to the genomes of well-characterized reference species.ResultsHere we report an efficient platform for the design of cross-species gene-derived markers in legumes. The automated platform, named CSGM Designer (URL: http://tgil.donga.ac.kr/CSGMdesigner), facilitates rapid and systematic design of cross-species genic markers. The underlying database is composed of genome data from five legume species whose genomes are substantially characterized. Use of CSGM is enhanced by graphical displays of query results, which we describe as "circular viewer" and "search-within-results" functions. CSGM provides a virtual PCR representation (eHT-PCR) that predicts the specificity of each primer pair simultaneously in multiple genomes. CSGM Designer output was experimentally validated for the amplification of orthologous genes using 16 genotypes representing 12 crop and model legume species, distributed among the galegoid and phaseoloid clades. Successful cross-species amplification was obtained for 85.3% of PCR primer combinations.ConclusionCSGM Designer spans the divide between well-characterized crop and model legume species and their less well-characterized relatives. The outcome is PCR primers that target highly conserved genes for polymorphism discovery, enabling functional inferences and ultimately facilitating trait-associated molecular breeding