16 research outputs found

    MoMA: Momentum Contrastive Learning with Multi-head Attention-based Knowledge Distillation for Histopathology Image Analysis

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    There is no doubt that advanced artificial intelligence models and high quality data are the keys to success in developing computational pathology tools. Although the overall volume of pathology data keeps increasing, a lack of quality data is a common issue when it comes to a specific task due to several reasons including privacy and ethical issues with patient data. In this work, we propose to exploit knowledge distillation, i.e., utilize the existing model to learn a new, target model, to overcome such issues in computational pathology. Specifically, we employ a student-teacher framework to learn a target model from a pre-trained, teacher model without direct access to source data and distill relevant knowledge via momentum contrastive learning with multi-head attention mechanism, which provides consistent and context-aware feature representations. This enables the target model to assimilate informative representations of the teacher model while seamlessly adapting to the unique nuances of the target data. The proposed method is rigorously evaluated across different scenarios where the teacher model was trained on the same, relevant, and irrelevant classification tasks with the target model. Experimental results demonstrate the accuracy and robustness of our approach in transferring knowledge to different domains and tasks, outperforming other related methods. Moreover, the results provide a guideline on the learning strategy for different types of tasks and scenarios in computational pathology. Code is available at: \url{https://github.com/trinhvg/MoMA}.Comment: Preprin

    LIGNANS FROM LEAVES OF AMESIODENDRON CHINENSE AND THEIR CYTOTOXIC ACTIVITY

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    ABSTRACTFrom leaves of Amesiodendron chinense (Mer.) Hu four lignans (+)-aptosimon (1), (+)-isolariciresinol (2), (-)-cleomiscosin A (3), and (-)-cleomiscosin C (3) were isolated. Their structures were determined by spectroscopic analysis including MS, 1D and 2D NMR as well as by comparison with reported data in literature. All compounds were evaluated for cytotoxic activities against five human cancer cell lines, KB, SK-LU-1, MCF-7, HepG-2, and SW-480. They showed weak cytotoxic activity on five tested human cancer cell lines with IC50 values ranging from 32.61 to 95.18 µg/ml

    The 80-year development of Vietnam mathematical research: Preliminary insights from the SciMath database on mathematicians, their works and their networks

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    Starting with the first international publication of Le Van Thiem (Lê Văn Thiêm) in 1947, modern mathematics in Vietnam is a longstanding research field. However, what is known about its development usually comes from discrete essays such as anecdotes or interviews of renowned mathematicians. We introduce SciMath—a database on publications of Vietnamese mathematicians. To ensure this database covers as many publications as possible, data entries are manually collected from scientists’ publication records, journals’ websites, universities, and research institutions. Collected data went through various verification steps to ensure data quality and minimize errors. At the time of this report, the database covered 8372 publications, profiles of 1566 Vietnamese, and 1492 foreign authors since 1947. We found a growing capability in mathematics research in Vietnam in various aspects: scientific output, publications on influential journals, or collaboration. The database and preliminary results were presented to the Scientific Council of Vietnam Institute for Advanced Study in Mathematics (VIASM) on November 13th, 2020

    Partial food systems baseline assessment at the Vietnam benchmark sites

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    Using data collected from a cross-sectional study in Moc Chau, Dong Anh and Cau Giay districts in Vietnam, this report aims to elucidate specific components of local Vietnamese food systems along a rural to urban transect focusing specifically on (i) diets, (ii) nutrition status (anthropometry), (iii) consumer behavior, (iv) food environment, and (v) food flows

    Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

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    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

    CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

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    Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery

    A refined convergence analysis of Popov's algorithm for pseudo-monotone variational inequalities

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    In this work, we present a refined convergence analysis of the Popov's projection algorithm for solving pseudo-monotone variational inequalities in Hilbert spaces. Our analysis results in a larger range of stepsize, which is achieved by using a new Lyapunov function. Furthermore, when the operator is strongly pseudo-monotone and Lipschitz continuous, we establish the linear convergence of the sequence generated by the Popov's algorithm. As a by-product of our analysis, we extend the range of stepsize in the projected reflected gradient algorithm for solving unconstrained pseudo-monotone variational inequalities.</p

    Reading habits, socioeconomic conditions, occupational aspiration and academic achievement in Vietnamese junior high school students

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    Reading practices play an important role in the learning process of students. Especially in a fast-changing world where knowledge about nature and society is in a constant state of flux, book reading helps students foster skills such as thinking, valuing, adaptability and creativity for sustainable development. This research study used a dataset of 1676 observations of junior high school students from Northern Vietnam to explore students' academic achievement and its association with their reading passion, family socio economic condition, parental education and occupational aspiration. The empirical results show that higher grades in STEM-related subjects are predicted by reading interest (βReadbook = 0.425, p < 0.0001), with students who love reading books achieve higher score than those who take no interest in books. Remarkably, the education level of the mother strongly enhances academic performance, with β = 0.721 (p < 0.0001) in cases of mother having a university diploma or higher. Students coming from wealthy families are more likely to buy books whereas borrowing from the library is the main source of books for students who grow up in not-rich families. However, even among wealthy families, investment into buying books still rely more on personal interest, despite the aforementioned educational benefits of book reading, as evidenced by an over 7 percentage point disparity between the likelihood of purchasing books among wealthy-family students who took an interest in reading (45%) versus students of the same background who did not like to read (38.7%). The results present implications for education policy making with a vision towards United Nations' Sustainable Development Goal 4: Quality Education.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

    Optimization of the calcination and two-step sintering temperatures of (K0.48Na0.48Li0.04)(Nb0.95Sb0.05)O3 ceramics

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    Lead-free (K _0.48 Na _0.48 Li _0.04 )(Nb _0.95 Sb _0.05 )O _3 (KNLNS) ceramics have been successfully optimized for the calcination and two-step sintering temperatures. The experimental results reveal that the KNLNS powder calcined at 850 or 900 °C presented a pure perovskite phase with an orthorhombic phase. The particle size was in the range of 0.1–0.4 μ m. The two-step sintering temperature (range: 950 to 1100 °C) significantly affects the structure, microstructure, and electrical properties of KNLNS ceramics. The presence of a pure perovskite phase with good crystallization is observed in all samples. The microstructure was researched by varying the two-step sintering temperature to obtain a dense microstructure and a clear grain boundary in order to optimize their piezoelectric properties. The best electrical properties of KNLNS ceramics were recorded at the optimized temperature of 1050 °C (density ( ρ ): 4,35 g cm ^−3 ; electromechanical coupling factor ( k _p ): 0.33, k _t : 0.35; dielectric constant ( ε _r ): 849; dielectric loss (tan δ ): 0.073; maximum dielectric constant ( ε _max at T _C ): 6659; piezoelectric constant ( d _33 ): 195 pC N ^−1 ; remanent polarization ( P _r ): 16.1 μ C cm ^−2 ; energy storage density ( W _rec ): 0.36 J cm ^−3 ; energy storage efficiency ( η ): 48.1%; t _2 = 4 h), proving the efficacy of the two-step sintering technique
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