69,212 research outputs found
VIP: Incorporating Human Cognitive Biases in a Probabilistic Model of Retweeting
Information spread in social media depends on a number of factors, including
how the site displays information, how users navigate it to find items of
interest, users' tastes, and the `virality' of information, i.e., its
propensity to be adopted, or retweeted, upon exposure. Probabilistic models can
learn users' tastes from the history of their item adoptions and recommend new
items to users. However, current models ignore cognitive biases that are known
to affect behavior. Specifically, people pay more attention to items at the top
of a list than those in lower positions. As a consequence, items near the top
of a user's social media stream have higher visibility, and are more likely to
be seen and adopted, than those appearing below. Another bias is due to the
item's fitness: some items have a high propensity to spread upon exposure
regardless of the interests of adopting users. We propose a probabilistic model
that incorporates human cognitive biases and personal relevance in the
generative model of information spread. We use the model to predict how
messages containing URLs spread on Twitter. Our work shows that models of user
behavior that account for cognitive factors can better describe and predict
user behavior in social media.Comment: SBP 201
Sparse Coding Predicts Optic Flow Specificities of Zebrafish Pretectal Neurons
Zebrafish pretectal neurons exhibit specificities for large-field optic flow
patterns associated with rotatory or translatory body motion. We investigate
the hypothesis that these specificities reflect the input statistics of natural
optic flow. Realistic motion sequences were generated using computer graphics
simulating self-motion in an underwater scene. Local retinal motion was
estimated with a motion detector and encoded in four populations of
directionally tuned retinal ganglion cells, represented as two signed input
variables. This activity was then used as input into one of two learning
networks: a sparse coding network (competitive learning) and backpropagation
network (supervised learning). Both simulations develop specificities for optic
flow which are comparable to those found in a neurophysiological study (Kubo et
al. 2014), and relative frequencies of the various neuronal responses are best
modeled by the sparse coding approach. We conclude that the optic flow neurons
in the zebrafish pretectum do reflect the optic flow statistics. The predicted
vectorial receptive fields show typical optic flow fields but also "Gabor" and
dipole-shaped patterns that likely reflect difference fields needed for
reconstruction by linear superposition.Comment: Published Conference Paper from ICANN 2018, Rhode
Anaesthesia and subglottic airway obstruction
In this article, we describe the anaesthetic management and laser excision of a subglottic tumour that caused upper airway obstruction. Stridor was the presenting feature. A good history and careful assessment will reduce the likelihood of erroneous or delayed diagnosis and will improve patient outcome.This case report highlights the use of target-controlled infusions and jet ventilation (high-pressure source ventilation) in the surgical excision of a subglottic tumour.Keywords: shared airway; jet ventilation; TIVA/TCI; laser excision; monitorin
Synoptic environment of composite tropical cyclones in the south-west Indian ocean
The composite structure of the tropical cyclone (TC) environment in the South-West Indian Ocean is analysed using European Community medium-range weather data. Conditions suitable for the development of tropical cyclones are present between 5 and 15Ā°S and between 40 and 100Ā°E. Groups of westward-moving and polewardrecurving TCs are used to construct system-following composites from three days before maximum intensity toone day after. The synoptic fields surrounding the westward-moving composite TC remain steady, whereas the recurving composite environment supports rapid vortex growth. Interaction with a subtropical trough is prominentin the recurving TC. The results offer useful insights to weather interactions in the South-West Indian Ocean
CARDS: A Collaborative Community Model for Faculty Development or an Institutional Case Study of Writing Program Administration
The structure of writing programs evolves to account for the transformation of composition studies. Online and dual credit programs necessitate a need to adjust prior practices initially geared towards face-to-face pedagogy; however, several challenges surface in online and dual credit writing programs. The most prevalent is that these online courses are primarily staffed by non-tenured faculty, including adjuncts who do not have a physical presence on campus. The faculty dynamic presents many challenges when attempting to garner participation in collaborations. In recent years, the Writing Program Administrator (WPA) at a regional public university noticed a need to improve faculty morale, satisfaction, and participation, especially with the emergence of online programs. Through a national survey and selective interviews of current faculty at the university, we determined that the answer lies in the structure of the program. The Writing Program Administrator has several models to choose from, but we will argue that the collaborative community model is most conducive to addressing and enhancing faculty morale, satisfaction, and participation in first-year writing programs
Conditional Image-Text Embedding Networks
This paper presents an approach for grounding phrases in images which jointly
learns multiple text-conditioned embeddings in a single end-to-end model. In
order to differentiate text phrases into semantically distinct subspaces, we
propose a concept weight branch that automatically assigns phrases to
embeddings, whereas prior works predefine such assignments. Our proposed
solution simplifies the representation requirements for individual embeddings
and allows the underrepresented concepts to take advantage of the shared
representations before feeding them into concept-specific layers. Comprehensive
experiments verify the effectiveness of our approach across three phrase
grounding datasets, Flickr30K Entities, ReferIt Game, and Visual Genome, where
we obtain a (resp.) 4%, 3%, and 4% improvement in grounding performance over a
strong region-phrase embedding baseline.Comment: ECCV 2018 accepted pape
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High rate of extrapair paternity in a human population demonstrates diversity in human reproductive strategies.
Among nonhuman species, social monogamy is rarely accompanied by complete fidelity. Evolutionary theory predicts that the rate of extrapair paternity (EPP) should vary according to socioecological conditions. In humans, however, geneticists contend that EPP is negligible and relatively invariable. This conclusion is based on a limited set of studies, almost all of which describe European-descent groups. Using a novel, double-blind method designed in collaboration with a community of Himba pastoralists, we find that the rate of EPP in this population is 48%, with 70% of couples having at least one EPP child. Both men and women were very accurate at detecting cases of EPP. These data suggest that the range of variation in EPP across human populations is substantially greater than previously thought. We further show that a high rate of EPP can be accompanied by high paternity confidence, which highlights the importance of disaggregating EPP from the notion of "cuckoldry.
Fatty-acid uptake in prostate cancer cells using dynamic microfluidic raman technology
It is known that intake of dietary fatty acid (FA) is strongly correlated with prostate cancer progression but is highly dependent on the type of FAs. High levels of palmitic acid (PA) or arachidonic acid (AA) can stimulate the progression of cancer. In this study, a unique experimental set-up consisting of a Raman microscope, coupled with a commercial shear-flow microfluidic system is used to monitor fatty acid uptake by prostate cancer (PC-3) cells in real-time at the single cell level. Uptake of deuterated PA, deuterated AA, and the omega-3 fatty acids docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) were monitored using this new system, while complementary flow cytometry experiments using Nile red staining, were also conducted for the validation of the cellular lipid uptake. Using this novel experimental system, we show that DHA and EPA have inhibitory effects on the uptake of PA and AA by PC-3 cells
Determining the date of diagnosis ā is it a simple matter? The impact of different approaches to dating diagnosis on estimates of delayed care for ovarian cancer in UK primary care
Background Studies of cancer incidence and early management will increasingly draw on routine electronic patient records. However, data may be incomplete or inaccurate. We developed a generalisable strategy for investigating presenting symptoms and delays in diagnosis using ovarian cancer as an example. Methods The General Practice Research Database was used to investigate the time between first report of symptom and diagnosis of 344 women diagnosed with ovarian cancer between 01/06/2002 and 31/05/2008. Effects of possible inaccuracies in dating of diagnosis on the frequencies and timing of the most commonly reported symptoms were investigated using four increasingly inclusive definitions of first diagnosis/suspicion: 1. "Definite diagnosis" 2. "Ambiguous diagnosis" 3. "First treatment or complication suggesting pre-existing diagnosis", 4 "First relevant test or referral". Results The most commonly coded symptoms before a definite diagnosis of ovarian cancer, were abdominal pain (41%), urogenital problems(25%), abdominal distension (24%), constipation/change in bowel habits (23%) with 70% of cases reporting at least one of these. The median time between first reporting each of these symptoms and diagnosis was 13, 21, 9.5 and 8.5 weeks respectively. 19% had a code for definitions 2 or 3 prior to definite diagnosis and 73% a code for 4. However, the proportion with symptoms and the delays were similar for all four definitions except 4, where the median delay was 8, 8, 3, 10 and 0 weeks respectively. Conclusion Symptoms recorded in the General Practice Research Database are similar to those reported in the literature, although their frequency is lower than in studies based on self-report. Generalisable strategies for exploring the impact of recording practice on date of diagnosis in electronic patient records are recommended, and studies which date diagnoses in GP records need to present sensitivity analyses based on investigation, referral and diagnosis data. Free text information may be essential in obtaining accurate estimates of incidence, and for accurate dating of diagnoses
Compositional nonblocking verification with always enabled events and selfloop-only events
This paper proposes to improve compositional nonblocking verification through the use of always enabled and selfloop-only events. Compositional verification involves abstraction to simplify parts of a system during verification. Normally, this abstraction is based on the set of events not used in the remainder of the system, i.e., in the part of the system not being simplified. Here, it is proposed to exploit more knowledge about the system and abstract events even though they are used in the remainder of the system. Abstraction rules from previous work are generalised, and experimental results demonstrate the applicability of the resulting algorithm to verify several industrial-scale discrete event system models, while achieving better state-space reduction than before
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