Vietnam National University, Ho Chi Minh City

About: Vietnam National University, Ho Chi Minh City is a education organization based out in Ho Chi Minh City, Vietnam. It is known for research contribution in the topics: Computer science & Population. The organization has 6023 authors who have published 6278 publications receiving 60419 citations.

TRY plant trait database : Enhanced coverage and open access

Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

The vulnerability of Indo-Pacific mangrove forests to sea-level rise

Abstract: Sea-level rise can threaten the long-term sustainability of coastal communities and valuable ecosystems such as coral reefs, salt marshes and mangroves. Mangrove forests have the capacity to keep pace with sea-level rise and to avoid inundation through vertical accretion of sediments, which allows them to maintain wetland soil elevations suitable for plant growth. The Indo-Pacific region holds most of the world's mangrove forests, but sediment delivery in this region is declining, owing to anthropogenic activities such as damming of rivers. This decline is of particular concern because the Indo-Pacific region is expected to have variable, but high, rates of future sea-level rise. Here we analyse recent trends in mangrove surface elevation changes across the Indo-Pacific region using data from a network of surface elevation table instruments. We find that sediment availability can enable mangrove forests to maintain rates of soil-surface elevation gain that match or exceed that of sea-level rise, but for 69 per cent of our study sites the current rate of sea-level rise exceeded the soil surface elevation gain. We also present a model based on our field data, which suggests that mangrove forests at sites with low tidal range and low sediment supply could be submerged as early as 2070.

Synthesis and optical properties of copper nanoparticles prepared by a chemical reduction method

Abstract: Copper nanoparticles, due to their interesting properties, low cost preparation and many potential applications in catalysis, cooling fluid or conductive inks, have attracted a lot of interest in recent years. In this study, copper nanoparticles were synthesized through the chemical reduction of copper sulfate with sodium borohydride in water without inert gas protection. In our synthesis route, ascorbic acid (natural vitamin C) was employed as a protective agent to prevent the nascent Cu nanoparticles from oxidation during the synthesis process and in storage. Polyethylene glycol (PEG) was added and worked both as a size controller and as a capping agent. Cu nanoparticles were characterized by Fourier transform infrared (FT-IR) spectroscopy to investigate the coordination between Cu nanoparticles and PEG. Transmission electron microscopy (TEM) and UV–vis spectrometry contributed to the analysis of size and optical properties of the nanoparticles, respectively. The average crystal sizes of the particles at room temperature were less than 10 nm. It was observed that the surface plasmon resonance phenomenon can be controlled during synthesis by varying the reaction time, pH, and relative ratio of copper sulfate to the surfactant. The surface plasmon resonance peak shifts from 561 to 572 nm, while the apparent color changes from red to black, which is partly related to the change in particle size. Upon oxidation, the color of the solution changes from red to violet and ultimately a blue solution appears.

Addressing cold-start problem in recommendation systems

Abstract: Recommender systems for automatically suggested items of interest to users have become increasingly essential in fields where mass personalization is highly valued. The popular core techniques of such systems are collaborative filtering, content-based filtering and combinations of these. In this paper, we discuss hybrid approaches, using collaborative and also content data to address cold-start - that is, giving recommendations to novel users who have no preference on any items, or recommending items that no user of the community has seen yet. While there have been lots of studies on solving the item-side problems, solution for user-side problems has not been seen public. So we develop a hybrid model based on the analysis of two probabilistic aspect models using pure collaborative filtering to combine with users' information. The experiments with MovieLen data indicate substantial and consistent improvements of this model in overcoming the cold-start user-side problem.