6,683 research outputs found
Two-gap superconducting properties of alkaline-earth intercalated (A = Ba or Sr)
Superconducting properties were studied on high quality superconductors
( = 39 K) and
( = 44 K) prepared by intercalating Ba/Sr atoms into tetragonal
-FeSe by liquid ammonia. The elongated c-axis and almost unchanged
a-axis of , comparing with -FeSe, suggested
an unchanged intra--layer structure and the enhancement
is due to a 3D to 2D-like Fermi surface transformation. The superconducting
coherent lengths (0), Ginzburg-Landau parameters and penetration
depths (0) obtained from the extrapolated lower and upper critical
fields (0) and (0) indicates that both compounds are typical
type-II superconductors. The temperature dependence of 1/(T) of
deduced from the low field magnetic susceptibility
shows a two-gap s-wave behaviour with superconducting gaps of =
6.47 meV and = 1.06 meV
Travelling wave solutions for Kolmogorov-type delayed lattice reaction–diffusion systems
[[abstract]]This work investigates the existence and non-existence of travelling wave solutions for Kolmogorov-type delayed lattice reaction–diffusion systems. Employing the cross iterative technique coupled with the explicit construction of upper and lower solutions in the theory of quasimonotone dynamical systems, we can find two threshold speeds c∗ and c∗ with c∗≥c∗>0. If the wave speed is greater than c∗, then we establish the existence of travelling wave solutions connecting two different equilibria. On the other hand, if the wave speed is smaller than c∗, we further prove the non-existence result of travelling wave solutions. Finally, several ecological examples including one-species, two-species and three-species models with various functional responses and time delays are presented to illustrate the analytical results.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]紙本[[countrycodes]]GB
Prioritizing disease candidate genes by a gene interconnectedness-based approach
<p>Abstract</p> <p>Background</p> <p>Genome-wide disease-gene finding approaches may sometimes provide us with a long list of candidate genes. Since using pure experimental approaches to verify all candidates could be expensive, a number of network-based methods have been developed to prioritize candidates. Such tools usually have a set of parameters pre-trained using available network data. This means that re-training network-based tools may be required when existing biological networks are updated or when networks from different sources are to be tried.</p> <p>Results</p> <p>We developed a parameter-free method, interconnectedness (ICN), to rank candidate genes by assessing the closeness of them to known disease genes in a network. ICN was tested using 1,993 known disease-gene associations and achieved a success rate of ~44% using a protein-protein interaction network under a test scenario of simulated linkage analysis. This performance is comparable with those of other well-known methods and ICN outperforms other methods when a candidate disease gene is not directly linked to known disease genes in a network. Interestingly, we show that a combined scoring strategy could enable ICN to achieve an even better performance (~50%) than other methods used alone.</p> <p>Conclusions</p> <p>ICN, a user-friendly method, can well complement other network-based methods in the context of prioritizing candidate disease genes.</p
Impacts of Light Rail Transit Tram on the Voltage and Unbalance of the Distribution System
This paper presents the three-phase voltage and unbalance analysis for the distribution system with the loading of a light rail transit (LRT) tram. To investigate the dynamic responses of the system voltage and current, this paper adopts the Alternative Transients Program (ATP) software to model and simulate a multigrounded four-wire distribution system with an LRT loading. Two different definitions about unbalance are used to evaluate the problem. In this paper, the traction supply substation (TSS) with a single-phase transformer configuration is designed first for providing the electric power to the trams of LRT. However, it may result in the significant neutral line current and unbalance phenomenon to deteriorate the power quality of the distribution system. A Le-Blanc connection transformer in the TSS is therefore proposed to solve the problems
TMPad: an integrated structural database for helix-packing folds in transmembrane proteins
α-Helical transmembrane (TM) proteins play an important role in many critical and diverse biological processes, and specific associations between TM helices are important determinants for membrane protein folding, dynamics and function. In order to gain insights into the above phenomena, it is necessary to investigate different types of helix-packing modes and interactions. However, such information is difficult to obtain because of the experimental impediment and a lack of a well-annotated source of helix-packing folds in TM proteins. We have developed the TMPad (TransMembrane Protein Helix-Packing Database) which addresses the above issues by integrating experimentally observed helix–helix interactions and related structural information of membrane proteins. Specifically, the TMPad offers pre-calculated geometric descriptors at the helix-packing interface including residue backbone/side-chain contacts, interhelical distances and crossing angles, helical translational shifts and rotational angles. The TMPad also includes the corresponding sequence, topology, lipid accessibility, ligand-binding information and supports structural classification, schematic diagrams and visualization of the above structural features of TM helix-packing. Through detailed annotations and visualizations of helix-packing, this online resource can serve as an information gateway for deciphering the relationship between helix–helix interactions and higher levels of organization in TM protein structure and function. The website of the TMPad is freely accessible to the public at http://bio-cluster.iis.sinica.edu.tw/TMPad
An Algorithm for Preferential Selection of Spectroscopic Targets in LEGUE
We describe a general target selection algorithm that is applicable to any
survey in which the number of available candidates is much larger than the
number of objects to be observed. This routine aims to achieve a balance
between a smoothly-varying, well-understood selection function and the desire
to preferentially select certain types of targets. Some target-selection
examples are shown that illustrate different possibilities of emphasis
functions. Although it is generally applicable, the algorithm was developed
specifically for the LAMOST Experiment for Galactic Understanding and
Exploration (LEGUE) survey that will be carried out using the Chinese Guo Shou
Jing Telescope. In particular, this algorithm was designed for the portion of
LEGUE targeting the Galactic halo, in which we attempt to balance a variety of
science goals that require stars at fainter magnitudes than can be completely
sampled by LAMOST. This algorithm has been implemented for the halo portion of
the LAMOST pilot survey, which began in October 2011.Comment: 17 pages, 7 figures, accepted for publication in RA
BIOADI: a machine learning approach to identifying abbreviations and definitions in biological literature
BACKGROUND: To automatically process large quantities of biological literature for knowledge discovery and information curation, text mining tools are becoming essential. Abbreviation recognition is related to NER and can be considered as a pair recognition task of a terminology and its corresponding abbreviation from free text. The successful identification of abbreviation and its corresponding definition is not only a prerequisite to index terms of text databases to produce articles of related interests, but also a building block to improve existing gene mention tagging and gene normalization tools. RESULTS: Our approach to abbreviation recognition (AR) is based on machine-learning, which exploits a novel set of rich features to learn rules from training data. Tested on the AB3P corpus, our system demonstrated a F-score of 89.90% with 95.86% precision at 84.64% recall, higher than the result achieved by the existing best AR performance system. We also annotated a new corpus of 1200 PubMed abstracts which was derived from BioCreative II gene normalization corpus. On our annotated corpus, our system achieved a F-score of 86.20% with 93.52% precision at 79.95% recall, which also outperforms all tested systems. CONCLUSION: By applying our system to extract all short form-long form pairs from all available PubMed abstracts, we have constructed BIOADI. Mining BIOADI reveals many interesting trends of bio-medical research. Besides, we also provide an off-line AR software in the download section on http://bioagent.iis.sinica.edu.tw/BIOADI/
Team Quotients, Resilience, and Performance of Software Development Projects
Past studies have examined actions and strategies that software project teams can take to reduce the negative impact of uncertainties, such as changing requirements. Software development project teams often have to be flexible to follow the pre-defined plans and strive to meet project goals. Sometimes uncertainty may go extreme to temporarily slow projects down and set project teams into reduced productivity. Project teams should be resilient to recover from the reduce productivity condition and move forward toward predefined goals. This study focuses on understanding the importance of team resilience for software project teams and exploring the antecedents of team resilience. Specifically, we investigate the impacts of intelligence and emotional quotient on team resilience capability, the extent to which project team can recover from the impediment and move forward. This is a research-in-progress work. A future empirical test plan has been discussed at the end
Predicting RNA-binding sites of proteins using support vector machines and evolutionary information
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