30 research outputs found
The cones of Hilbert functions of squarefree modules
In this paper, we study different generalizations of the notion of
squarefreeness for ideals to the more general case of modules. We describe the
cones of Hilbert functions for squarefree modules in general and those
generated in degree zero. We give their extremal rays and defining
inequalities. For squarefree modules generated in degree zero, we compare the
defining inequalities of that cone with the classical Kruskal-Katona bound,
also asymptotically.Comment: 17 pages, 2 figures. This paper was produced during Pragmatic 201
A sharp bound for the resurgence of sums of ideals
We prove a sharp upper bound for the resurgence of sums of ideals involving
disjoint sets of variables, strengthening work of
Bisui--H\`a--Jayanthan--Thomas. Complete solutions are delivered for two
conjectures proposed by these authors. For given real numbers and , we
consider the set Res of possible values of the resurgence of where
and are ideals in disjoint sets of variables having resurgence and
, respectively. Some questions and partial results about Res are
discussed.Comment: 14 pages, 01 figur
ViCGCN: Graph Convolutional Network with Contextualized Language Models for Social Media Mining in Vietnamese
Social media processing is a fundamental task in natural language processing
with numerous applications. As Vietnamese social media and information science
have grown rapidly, the necessity of information-based mining on Vietnamese
social media has become crucial. However, state-of-the-art research faces
several significant drawbacks, including imbalanced data and noisy data on
social media platforms. Imbalanced and noisy are two essential issues that need
to be addressed in Vietnamese social media texts. Graph Convolutional Networks
can address the problems of imbalanced and noisy data in text classification on
social media by taking advantage of the graph structure of the data. This study
presents a novel approach based on contextualized language model (PhoBERT) and
graph-based method (Graph Convolutional Networks). In particular, the proposed
approach, ViCGCN, jointly trained the power of Contextualized embeddings with
the ability of Graph Convolutional Networks, GCN, to capture more syntactic and
semantic dependencies to address those drawbacks. Extensive experiments on
various Vietnamese benchmark datasets were conducted to verify our approach.
The observation shows that applying GCN to BERTology models as the final layer
significantly improves performance. Moreover, the experiments demonstrate that
ViCGCN outperforms 13 powerful baseline models, including BERTology models,
fusion BERTology and GCN models, other baselines, and SOTA on three benchmark
social media datasets. Our proposed ViCGCN approach demonstrates a significant
improvement of up to 6.21%, 4.61%, and 2.63% over the best Contextualized
Language Models, including multilingual and monolingual, on three benchmark
datasets, UIT-VSMEC, UIT-ViCTSD, and UIT-VSFC, respectively. Additionally, our
integrated model ViCGCN achieves the best performance compared to other
BERTology integrated with GCN models
HUE CITY HUONG RIVER FLOOD IN 1999
Joint Research on Environmental Science and Technology for the Eart
BISMUTH FILM ELECTRODE FOR STRIPPING VOLTAMMETRIC DETERMINATION OF BLOOD LEAD AND PRELIMINARY ASSESSMENT OF BLOOD LEAD LEVEL IN THE RESIDENTS AT CANH DUONG VILLAGE, THUA THIEN HUE PROVINCE
Joint Research on Environmental Science and Technology for the Eart
BISMUTH FILM ELECTRODE FOR MEASUREMENT OF TRACE LEAD BY ADSORPTIVE STRIPPING VOLTAMMETRY WITH CALCEIN BLUE
Joint Research on Environmental Science and Technology for the Eart
Seminormality and local cohomology of toric face rings
We characterize the toric face rings that are normal (respectively
seminormal). Extending results about local cohomology of Brun, Bruns, Ichim, Li
and R\"omer of seminormal monoid rings and Stanley toric face rings, we prove
the vanishing of certain graded parts of local cohomology of seminormal toric
face rings. The combinatorial formula we obtain generalizes Hochster's formula.
We also characterize all (necessarily seminormal) toric face rings that are
-pure or -split over a field of characteristic . An example is given
to show that -injectivity does not behave well with respect to face
projections of toric face rings. Finally, it is shown that weakly -regular
toric face rings are normal affine monoid rings.Comment: Final version. Replace the old proof of Lemma 4.6(ii) by an accurate
one. Some minor errors are corrected. This is part of the author's thesis. To
appear in Journal of Algebr
Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial
Background
Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population.
Methods
AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921.
Findings
Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months.
Interpretation
Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke