5,287 research outputs found
Dense molecular clumps in the envelope of the yellow hypergiant IRC+10420
The circumstellar envelope of the hypergiant star IRC+10420 has been traced
as far out in SiO J=2-1 as in CO J = 1-0 and CO J = 2-1, in dramatic contrast
with the centrally condensed (thermal) SiO- but extended CO-emitting envelopes
of giant and supergiant stars. Here, we present an observation of the
circumstellar envelope in SiO J=1-0 that, when combined with the previous
observation in {\sioii}, provide more stringent constraints on the density of
the SiO-emitting gas than hitherto possible. The emission in SiO peaks at a
radius of 2\arcsec\ whereas that in SiO J=2-1 emission peaks at a smaller
radius of 1\arcsec, giving rise to their ring-like appearances. The ratio
in brightness temperature between SiO J=1-0 and SiO J=2-1 decreases from a
value well above unity at the innermost measurable radius to about unity at
radius of 2\arcsec, beyond which this ratio remains approximately
constant. Dividing the envelope into three zones as in models for the CO J =
1-0 and CO J = 2-1 emission, we show that the density of the SiO-emitting gas
is comparable with that of the CO-emitting gas in the inner zone, but at least
an order of magnitude higher by comparison in both the middle and outer zones.
The SiO-emitting gas therefore originates from dense clumps, likely associated
with the dust clumps seen in scattered optical light, surrounded by more
diffuse CO-emitting interclump gas. We suggest that SiO molecules are released
from dust grains due to shock interactions between the dense SiO-emitting
clumps and the diffuse CO-emitting interclump gas.Comment: Accepted for publication in Ap
Determinants of dividend policy in Malaysian banking sector
The purpose of this study is to examine the factors that influence dividend policy in the Malaysian banking sector. For this purpose, a sample of 19 commercial banks in Malaysia were selected including eight domestic banks and eleven foreign banks. Ordinary Least Squares (OLS) Regression was used to examine the impact of leverage, profitability, liquidity, past dividend, size of firm, sales growth, corporate tax, and business risk on dividend policy in the banking sector over a period of five years from 2007 to 2011. The empirical results of this study show that profitability, liquidity, past dividend, size of firm, and sales growth have a positive relationship with dividend payout. Meanwhile, leverage, corporate tax and
business risk have a negative relationship with dividend payout. The results of the analysis indicated that profitability, past dividend, size of firm and corporate tax were the major factors that affected dividend payment decision. Furthermore, we found that domestic banks had higher dividend payout than foreign bank
Disseminated eruptive giant mollusca contagiosa in an adult psoriasis patient during efalizumab therapy
Molluscum contagiosum is a common viral skin infection in children with atopic diathesis and not rare in HIV patients. We report a 45-year-old psoriasis patient who developed eruptive mollusca contagiosa during an antipsoriatic treatment with efalizumab. Copyright (C) 2008 S. Karger AG, Basel
So near and yet so far: Harmonic radar reveals reduced homing ability of nosema infected honeybees
Pathogens may gain a fitness advantage through manipulation of the behaviour of their hosts. Likewise, host behavioural changes can be a defence mechanism, counteracting the impact of pathogens on host fitness. We apply harmonic radar technology to characterize the impact of an emerging pathogen - Nosema ceranae (Microsporidia) - on honeybee (Apis mellifera) flight and orientation performance in the field. Honeybees are the most important commercial pollinators. Emerging diseases have been proposed to play a prominent role in colony decline, partly through sub-lethal behavioural manipulation of their hosts. We found that homing success was significantly reduced in diseased (65.8%) versus healthy foragers (92.5%). Although lost bees had significantly reduced continuous flight times and prolonged resting times, other flight characteristics and navigational abilities showed no significant difference between infected and non-infected bees. Our results suggest that infected bees express normal flight characteristics but are constrained in their homing ability, potentially compromising the colony by reducing its resource inputs, but also counteracting the intra-colony spread of infection. We provide the first high-resolution analysis of sub-lethal effects of an emerging disease on insect flight behaviour. The potential causes and the implications for both host and parasite are discussed
So near and yet so far: Harmonic radar reveals reduced homing ability of nosema infected honeybees
Pathogens may gain a fitness advantage through manipulation of the behaviour of their hosts. Likewise, host behavioural changes can be a defence mechanism, counteracting the impact of pathogens on host fitness. We apply harmonic radar technology to characterize the impact of an emerging pathogen - Nosema ceranae (Microsporidia) - on honeybee (Apis mellifera) flight and orientation performance in the field. Honeybees are the most important commercial pollinators. Emerging diseases have been proposed to play a prominent role in colony decline, partly through sub-lethal behavioural manipulation of their hosts. We found that homing success was significantly reduced in diseased (65.8%) versus healthy foragers (92.5%). Although lost bees had significantly reduced continuous flight times and prolonged resting times, other flight characteristics and navigational abilities showed no significant difference between infected and non-infected bees. Our results suggest that infected bees express normal flight characteristics but are constrained in their homing ability, potentially compromising the colony by reducing its resource inputs, but also counteracting the intra-colony spread of infection. We provide the first high-resolution analysis of sub-lethal effects of an emerging disease on insect flight behaviour. The potential causes and the implications for both host and parasite are discussed
SBTRec- A Transformer Framework for Personalized Tour Recommendation Problem with Sentiment Analysis
When traveling to an unfamiliar city for holidays, tourists often rely on
guidebooks, travel websites, or recommendation systems to plan their daily
itineraries and explore popular points of interest (POIs). However, these
approaches may lack optimization in terms of time feasibility, localities, and
user preferences. In this paper, we propose the SBTRec algorithm: a BERT-based
Trajectory Recommendation with sentiment analysis, for recommending
personalized sequences of POIs as itineraries. The key contributions of this
work include analyzing users' check-ins and uploaded photos to understand the
relationship between POI visits and distance. We introduce SBTRec, which
encompasses sentiment analysis to improve recommendation accuracy by
understanding users' preferences and satisfaction levels from reviews and
comments about different POIs. Our proposed algorithms are evaluated against
other sequence prediction methods using datasets from 8 cities. The results
demonstrate that SBTRec achieves an average F1 score of 61.45%, outperforming
baseline algorithms.
The paper further discusses the flexibility of the SBTRec algorithm, its
ability to adapt to different scenarios and cities without modification, and
its potential for extension by incorporating additional information for more
reliable predictions. Overall, SBTRec provides personalized and relevant POI
recommendations, enhancing tourists' overall trip experiences. Future work
includes fine-tuning personalized embeddings for users, with evaluation of
users' comments on POIs,~to further enhance prediction accuracy
BTRec: BERT-Based Trajectory Recommendation for Personalized Tours
An essential task for tourists having a pleasant holiday is to have a
well-planned itinerary with relevant recommendations, especially when visiting
unfamiliar cities. Many tour recommendation tools only take into account a
limited number of factors, such as popular Points of Interest (POIs) and
routing constraints. Consequently, the solutions they provide may not always
align with the individual users of the system. We propose an iterative
algorithm in this paper, namely: BTREC (BERT-based Trajectory Recommendation),
that extends from the POIBERT embedding algorithm to recommend personalized
itineraries on POIs using the BERT framework. Our BTREC algorithm incorporates
users' demographic information alongside past POI visits into a modified BERT
language model to recommend a personalized POI itinerary prediction given a
pair of source and destination POIs. Our recommendation system can create a
travel itinerary that maximizes POIs visited, while also taking into account
user preferences for categories of POIs and time availability. Our
recommendation algorithm is largely inspired by the problem of sentence
completion in natural language processing (NLP). Using a dataset of eight
cities of different sizes, our experimental results demonstrate that our
proposed algorithm is stable and outperforms many other sequence prediction
algorithms, measured by recall, precision, and F1-scores.Comment: RecSys 2023, Workshop on Recommenders in Touris
AD-Link: An adaptive approach for user identity linkage
National Research Foundation (NRF) Singapore under its International Research Centres in Singapore Funding Initiativ
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