1,039 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
Hidden Trends in 90 Years of Harvard Business Review
In this paper, we demonstrate and discuss results of our mining the abstracts
of the publications in Harvard Business Review between 1922 and 2012.
Techniques for computing n-grams, collocations, basic sentiment analysis, and
named-entity recognition were employed to uncover trends hidden in the
abstracts. We present findings about international relationships, sentiment in
HBR's abstracts, important international companies, influential technological
inventions, renown researchers in management theories, US presidents via
chronological analyses.Comment: 6 pages, 14 figures, Proceedings of 2012 International Conference on
Technologies and Applications of Artificial Intelligenc
BANet: Blur-aware Attention Networks for Dynamic Scene Deblurring
Image motion blur usually results from moving objects or camera shakes. Such
blur is generally directional and non-uniform. Previous research efforts
attempt to solve non-uniform blur by using self-recurrent multi-scale or
multi-patch architectures accompanying with self-attention. However, using
self-recurrent frameworks typically leads to a longer inference time, while
inter-pixel or inter-channel self-attention may cause excessive memory usage.
This paper proposes blur-aware attention networks (BANet) that accomplish
accurate and efficient deblurring via a single forward pass. Our BANet utilizes
region-based self-attention with multi-kernel strip pooling to disentangle blur
patterns of different degrees and with cascaded parallel dilated convolution to
aggregate multi-scale content features. Extensive experimental results on the
GoPro and HIDE benchmarks demonstrate that the proposed BANet performs
favorably against the state-of-the-art in blurred image restoration and can
provide deblurred results in real-time
A study of readers’ motivations and behavior with motivational books in Taiwan
This poster reports on the preliminary findings from a survey on Taiwan readers’ reading motivations and behavior with motivational books. The sample is composed of 435 avid adult readers. The poster will focus on the reading motivation for four major subgenres under motivational books as well as the age-related differences in information sharing and medium/access methods for motivational reading
Deep Learning for Spin-Orbit Torque Characterizations with a Projected Vector Field Magnet
Spin-orbit torque characterizations on magnetic heterostructures with
perpendicular anisotropy are demonstrated on a projected vector field magnet
via hysteresis loop shift measurement and harmonic Hall measurement with planar
Hall correction. Accurate magnetic field calibration of the vector magnet is
realized with the help of deep learning models, which are able to capture the
nonlinear behavior between the generated magnetic field and the currents
applied to the magnet. The trained models can successfully predict the applied
current combinations under the circumstances of magnetic field scans, angle
scans, and hysteresis loop shift measurements. The validity of the models is
further verified, complemented by the comparison of the spin-orbit torque
characterization results obtained from the deep-learning-trained vector magnet
system with those obtained from a conventional setup comprised of two separated
electromagnets. The damping-like spin-orbit torque (DL-SOT) efficiencies
(||) extracted from the vector magnet and the traditional measurement
configuration are consistent, where || 0.22 for amorphous W
and || 0.02 for -W. Our work provides an advanced
method to meticulously control a vector magnet and to conveniently perform
various spin-orbit torque characterizations
Bian Zheng Lun Zhi
Background. Limited scientific evidence supports the positive effects of traditional Chinese medicine (TCM) for treating dysmenorrhea. Thus, an observation period of 3 months could verify the ancient indication that TCM treatments effectively alleviate menstrual cramps in women with primary dysmenorrhea or endometriosis. Methods. A prospective, nonrandomized study (primary dysmenorrhea and endometriosis groups) was conducted in women with dysmenorrhea for more than three consecutive menstrual cycles. All patients received TCM prescriptions based on bian zheng lun zhi theory 14 days before menstruation for a period of 12 weeks. Pain intensity was evaluated using a 10-cm visual analogue scale and two validated questionnaires (the Menstrual Distress Questionnaire and the World Health Organization Quality of Life questionnaire). Results. Of the initial 70 intent-to-treat participants, the women with dysmenorrhea reported significant alleviation of cramps during menstruation after the 12-week TCM treatment. Mixed model analysis revealed that TCM prescriptions were more effective in alleviating fatigue, hot flashes, dizziness, painful breasts, excitement, and irritability in the primary dysmenorrhea group (N=36) than in the endometriosis group (N=34). Conclusion. TCM prescriptions based on syndrome differentiation theory might be a potentially viable choice for treating painful menstruation and premenstrual symptoms after ruling out endometriosis
The potential impact of primary headache disorders on stroke risk
Distribution of PHDs. (DOC 55 kb
Inhibition of gap junctional Intercellular communication in WB-F344 rat liver epithelial cells by triphenyltin chloride through MAPK and PI3-kinase pathways
<p>Abstract</p> <p>Background</p> <p>Organotin compounds (OTCs) have been widely used as stabilizers in the production of plastic, agricultural pesticides, antifoulant plaints and wood preservation. The toxicity of triphenyltin (TPT) compounds was known for their embryotoxic, neurotoxic, genotoxic and immunotoxic effects in mammals. The carcinogenicity of TPT was not well understood and few studies had discussed the effects of OTCs on gap junctional intercellular communication (GJIC) of cells.</p> <p>Method</p> <p>In the present study, the effects of triphenyltin chloride (TPTC) on GJIC in WB-F344 rat liver epithelial cells were evaluated, using the scrape-loading dye transfer technique.</p> <p>Results</p> <p>TPTC inhibited GJIC after a 30-min exposure in a concentration- and time-dependent manner. Pre-incubation of cells with the protein kinase C (PKC) inhibitor did not modify the response, but the specific MEK 1 inhibitor PD98059 and PI3K inhibitor LY294002 decreased substantially the inhibition of GJIC by TPTC. After WB-F344 cells were exposed to TPTC, phosphorylation of Cx43 increased as seen in Western blot analysis.</p> <p>Conclusions</p> <p>These results show that TPTC inhibits GJIC in WB-F344 rat liver epithelial cells by altering the Cx43 protein expression through both MAPK and PI3-kinase pathways.</p
Chinese Herbal Medicine Therapy and the Risk of Mortality for Chronic Hepatitis B Patients with Concurrent Liver Cirrhosis: a Nationwide Population-Based Cohort Study
Chronic hepatitis B (CHB) is increasingly recognized as a public health problem in Taiwan. After affected patients are diagnosed with contaminant liver cirrhosis (LC), adverse clinical outcomes, especially death, are common. This study aimed to investigate the effect of Chinese herbal medicine (CHM), an essential branch of Traditional Chinese medicine (TCM), on the mortality risk among CHB patients with contaminant LC. This longitudinal cohort study used the Taiwanese National Health Insurance Research Database to identify 1522 patients 20–70 years of age with newly diagnosed CHB with LC during 1998–2007. Among them, 508 (33.37%) had received CHM products after the onset of CHB (CHM users), and the remaining 1014 patients (66.63%) were designated as a control group (non-CHM users). All enrollees were followed until the end of 2012 to determine deaths during the study period. We applied the Cox proportional hazards regression model to compute the hazard ratio for the association of CHM use and the subsequent risk of death. During the follow-up period, 156 CHM users and 493 non-CHM users died. After controlling for potential confounders, CHM users were found to have a significantly reduced risk of death compared with non-CHM users by 56%, and the effect was predominantly observed among those treated with CHM for \u3e 180 days. CHM therapy lowered the risk of death among CHB patients with contaminant LC, which supported CHM might provide further treatment options for those with chronic liver diseases
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