611 research outputs found
Interference-Aware Deployment for Maximizing User Satisfaction in Multi-UAV Wireless Networks
In this letter, we study the deployment of Unmanned Aerial Vehicle mounted
Base Stations (UAV-BSs) in multi-UAV cellular networks. We model the multi-UAV
deployment problem as a user satisfaction maximization problem, that is,
maximizing the proportion of served ground users (GUs) that meet a given
minimum data rate requirement. We propose an interference-aware deployment
(IAD) algorithm for serving arbitrarily distributed outdoor GUs. The proposed
algorithm can alleviate the problem of overlapping coverage between adjacent
UAV-BSs to minimize inter-cell interference. Therefore, reducing co-channel
interference between UAV-BSs will improve user satisfaction and ensure that
most GUs can achieve the minimum data rate requirement. Simulation results show
that our proposed IAD outperforms comparative methods by more than 10% in user
satisfaction in high-density environments.Comment: 5 pages, 3 figures, to appear in IEEE Wireless Communications Letter
Planar Compact Tablet Monopole Antenna for LTE/WWAN System
Abstract -This work describes a compact tablet monopole antenna with eight-band LTE/WWAN operation by introducing a G-shaped driven monopole strip. The obtained impedance bandwidths across dual operating bands approach 264 / 1046 MHz at the LTE and WWAN bands, respectively. Given that the overall antenna size is only 35 × 10 × 0.8 mm 3 , the proposed planar monopole antenna provides more than 40% reduction in antenna size over that of the conventional ones. Additionally, the measured peak gains and antenna efficiencies are approximately 3.6 / 5.2 dBi and 67 / 70 % for the LTE/WWAN bands, respectively. Index Terms -Monopole antenna, long-term evolution (LTE), wireless wide area network (WWAN)
Polymicrobial bloodstream infection involving Aeromonas species: Analysis of 62 cases
AbstractObjectiveTo better understand Aeromonas-involved polymicrobial bacteremia (AIPMB).Materials and MethodsWe conducted a retrospective analysis of patients with AIPMB admitted to three large referral hospitals in Taiwan between 2001 and 2008.ResultsOf a total of 62 patients with AIPMB, 22 had healthcare-associated infection and 40 had community-acquired infection. Enterobacteriaceae was the most common concurrent pathogen (82%). The leading underlying diseases/conditions in the affected patients were solid cancers (45%), recent gastric acid suppressant therapy (39%) and liver cirrhosis (26%). More than 95% of the Aeromonas isolates were susceptible to an aminoglycoside, a third- or fourth-generation cephalosporin, imipenem or ciprofloxacin. Antibiotic susceptibilities did not significantly differ between Aeromonas isolates in patients with healthcare-associated AIPMBs and those in patients with community-acquired AIPMBs. Coinfection with Enterobacteriaceae occurred more commonly in community-acquired AIPMB (93% vs. 64%; p=0.012).ConclusionsAIPMB occurred commonly in patients with liver cirrhosis, solid cancers or recent gastric acid suppressant therapy. Enterobacteriaceae were the most common concurrent pathogens. Similar antibiotic profiles were found in Aeromonas isolates of healthcare-associated and community-acquired AIPMBs
A pre-S gene chip to detect pre-S deletions in hepatitis B virus large surface antigen as a predictive marker for hepatoma risk in chronic hepatitis B virus carriers
<p>Abstract</p> <p>Background</p> <p>Chronic hepatitis B virus (HBV) infection is an important cause of hepatocellular carcinoma (HCC) worldwide. The pre-S<sub>1 </sub>and -S<sub>2 </sub>mutant large HBV surface antigen (LHBS), in which the pre-S<sub>1 </sub>and -S<sub>2 </sub>regions of the LHBS gene are partially deleted, are highly associated with HBV-related HCC.</p> <p>Methods</p> <p>The pre-S region of the LHBS gene in two hundred and one HBV-positive serum samples was PCR-amplified and sequenced. A pre-S oligonucleotide gene chip was developed to efficiently detect pre-S deletions in chronic HBV carriers. Twenty serum samples from chronic HBV carriers were analyzed using the chip.</p> <p>Results</p> <p>The pre-S deletion rates were relatively low (7%) in the sera of patients with acute HBV infection. They gradually increased in periods of persistent HBV infection: pre-S mutation rates were 37% in chronic HBV carriers, and as high as 60% in HCC patients. The Pre-S Gene Chip offers a highly sensitive and specific method for pre-S deletion detection and is less expensive and more efficient (turnaround time 3 days) than DNA sequencing analysis.</p> <p>Conclusion</p> <p>The pre-S<sub>1/2 </sub>mutants may emerge during the long-term persistence of the HBV genome in carriers and facilitate HCC development. Combined detection of pre-S mutations, other markers of HBV replication, and viral titers, offers a reliable predictive method for HCC risks in chronic HBV carriers.</p
NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition
BACKGROUND: Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. RESULTS: To develop our ML-based Bio-NER system, we employ conditional random fields, which have performed effectively in several well-known tasks, as our underlying ML model. Adding selected conjunction features, applying numerical normalization, and employing pattern-based post-processing improve the F-scores by 1.67%, 1.04%, and 0.57%, respectively. The combined increase of 3.28% yields a total score of 72.98%, which is better than the baseline system that only uses singleton features. CONCLUSION: We demonstrate the benefits of using the sequential forward search algorithm to select effective conjunction feature groups. In addition, we show that numerical normalization can effectively reduce the number of redundant and unseen features. Furthermore, the Smith-Waterman local alignment algorithm can help ML-based Bio-NER deal with difficult cases that need longer context windows
A model-based circular binary segmentation algorithm for the analysis of array CGH data
<p>Abstract</p> <p>Background</p> <p>Circular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-<it>t </it>test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent implementation utilizing a hybrid method and early stopping rules (hybrid CBS) to improve the performance in speed was subsequently proposed. However, a time analysis revealed that a major portion of computation time of the hybrid CBS was still spent on permutation. In addition, what the hybrid method provides is an approximation of the significance upper bound or lower bound, not an approximation of the significance of change-points itself.</p> <p>Results</p> <p>We developed a novel model-based algorithm, extreme-value based CBS (eCBS), which limits permutations and provides robust results without loss of accuracy. Thousands of aCGH data under null hypothesis were simulated in advance based on a variety of non-normal assumptions, and the corresponding maximal-<it>t </it>distribution was modeled by the Generalized Extreme Value (GEV) distribution. The modeling results, which associate characteristics of aCGH data to the GEV parameters, constitute lookup tables (eXtreme model). Using the eXtreme model, the significance of change-points could be evaluated in a constant time complexity through a table lookup process.</p> <p>Conclusions</p> <p>A novel algorithm, eCBS, was developed in this study. The current implementation of eCBS consistently outperforms the hybrid CBS 4× to 20× in computation time without loss of accuracy. Source codes, supplementary materials, supplementary figures, and supplementary tables can be found at <url>http://ntumaps.cgm.ntu.edu.tw/eCBSsupplementary</url>.</p
RssAB Signaling Coordinates Early Development of Surface Multicellularity in Serratia marcescens
Bacteria can coordinate several multicellular behaviors in response to environmental changes. Among these, swarming and biofilm formation have attracted significant attention for their correlation with bacterial pathogenicity. However, little is known about when and where the signaling occurs to trigger either swarming or biofilm formation. We have previously identified an RssAB two-component system involved in the regulation of swarming motility and biofilm formation in Serratia marcescens. Here we monitored the RssAB signaling status within single cells by tracing the location of the translational fusion protein EGFP-RssB following development of swarming or biofilm formation. RssAB signaling is specifically activated before surface migration in swarming development and during the early stage of biofilm formation. The activation results in the release of RssB from its cognate inner membrane sensor kinase, RssA, to the cytoplasm where the downstream gene promoters are located. Such dynamic localization of RssB requires phosphorylation of this regulator. By revealing the temporal activation of RssAB signaling following development of surface multicellular behavior, our findings contribute to an improved understanding of how bacteria coordinate their lifestyle on a surface
Clonal spread of multidrug-resistant Acinetobacter baumannii in eastern Taiwan
Background and PurposeThis study was conducted to investigate the molecular epidemiology and antimicrobial susceptibility of multidrug-resistant (MDR) Acinetobacter baumannii to three types of antibiotics.MethodsOne hundred and thirty-four specimens of MDR A baumannii were collected from three branches (Taipei, Dalin, and Hualien branches) of Buddhist Tzu Chi Hospital, which are located in northern, southern, and eastern Taiwan, during 2007. Genotyping was performed by pulsed-field gel electrophoresis. Antibiotic susceptibilities to colistin, rifampicin, and tigecycline were determined. The synergistic effects of rifampin and colistin were also evaluated.ResultsAntibiotic susceptibility testing showed that 10.4%, 47.8% and 45.5% of the MDR A baumannii isolates are resistant to colistin, rifampicin, and tigecycline, respectively. A majority of the rifampicin-resistant isolates (62.7%) were found in the Haulien branch, whereas 62.2% of tigecycline-resistant isolates were found in the Taipei branch. The combination of colistin and rifampicin had a synergistic effect on all of the isolates. Genotyping by pulsed-field gel electrophoresis identified 17, 23, and 11 pulsotypes in the Taipei, Dalin, and Haulien branches, respectively. Furthermore, 74.5% of isolates in the Haulien branch were identified as one of three pulsotypes. Among 37 rifampicin-resistant and 22 tigecycline-resistant MDR A baumannii isolates found in the Haulien branch, 51.3% (19/37) and 50% (11/22) of the isolates belonged to the same clone, respectively.ConclusionThis study confirms the high prevalence of resistance to rifampicin and tigecycline in MDR A baumannii in the three hospitals that were studied, and the high proportion of identical strains that exist in eastern Taiwan
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