CeO2 based catalysts for the treatment of propylene in motorcycle's exhaust gases

In this work, the catalytic activities of several single metallic oxides were studied for the treatment of propylene, a component in motorcycles' exhaust gases, under oxygen deficient conditions. Amongst them, CeO2 is one of the materials that exhibit the highest activity for the oxidation of C3H6. Therefore, several mixtures of CeO2 with other oxides (SnO2, ZrO2, Co3O4) were tested to investigate the changes in catalytic activity (both propylene conversion and CO2 selectivity). Ce0.9Zr0.1O2, Ce0.8Zr0.2O2 solid solutions and the mixtures of CeO2 and Co3O4 was shown to exhibit the highest propylene conversion and CO2 selectivity. They also exhibited good activities when tested under oxygen sufficient and excess conditions and with the presence of co-existing gases (CO, H2O)

EFFECT OF REDUCED CARBON SUPPLY ON ENHANCED BIOLOGICAL PHOSPHORUS REMOVAL AND DENITRIFICATION

Joint Research on Environmental Science and Technology for the Eart

Architecture Parallel for the Renewable Energy System

This chapter present one possible evolution is the parallel topology on the high-voltage bus for the renewable energy system. The system is not connected to a chain of photovoltaic (PV) modules and the different sources renewable. This evolution retains all the advantages of this system, while increasing the level of discretization of the Maximum Power Point Tracker (MPPT). So it is no longer a chain of PV modules that works at its MPPT but each PV module. In addition, this greater discretization allows a finer control and monitoring of operation and a faster detection of defects. The main interest of parallel step-up voltage systems, in this case, lies in the fact that the use of relatively high DC voltages is possible in these architectures distributed

DNA barcoding for identification of some fish species (Carangidae) in Vietnam coastal area

Carangidae family has got about 148 species belonging to 32 genera. In Vietnam, Carangidae is of high commercial value and playing an important role in the ecosystem. In the context Vietnam has received yellow card for seafood since Nov. 2017 by the EU, in which one of the main reasons was related to the restriction of traceability. In this study, DNA barcoding technique of mitochondrial cytochrome oxidase I (COI) gene was used to classify 56 specimens of Carangidae from three coastal areas (Northern, Central and Southern) in Vietnam to evaluate the effectiveness compared to the morphological classification method. Results showed that 21 species belonging to 16 genera were determined by the COI barcode while 18 species (16 genera) were determined when using morphological method. Seriola quinqueradiata and Trachinotus anak were newly recorded in Vietnam. From 56 sequences with 660 bp of mtDNA (COI), total 27 haplotypes were detected; haplotype diversity (h) and nucleotide diversity (π) were 0.903 ± 0.00060 and 0.14%, respectively. The DNA barcodes of COI gene of 21 species in Carangidae which were developed in this study could be used as a basis for comparison and traceability of their products. In addition, the results showed the high potentiality in using COI barcode to identify Carangidae fish in Vietnam

AN EVIDENCE FOR THE CONTRIBUTION OF ANAMMOX PROCESS IN NITROGEN REMOVAL FROM GROUNDWATER

Joint Research on Environmental Science and Technology for the Eart

Meat Quality of Lai Sind, Brahman × Lai Sind and Charolais × Lai Sind Cattle Raised in Dak Lak Province

Peer reviewe

CAMELLIA HOABINHENSIS (THEACEAE: SECT. CHRYSANTHA), A NEW YELLOW-FLOWERED SPECIES FROM NORTHERN VIETNAM

A new species, Camellia hoabinhensis (section Chrysantha, Theaceae), is described and illustrated based on specimens collected from a lowland forest on limestone hills in Hoa Binh Province, northern Vietnam. The species is characterized by its small habit to 4.5 m tall, large flowers 9.0–9.5 cm in diameter with 18–19 light yellow petals, and hairy filaments, ovaries, and styles. A comparison of the new species with similar species, C. euphlebia, C. impressinervis, C. phanii, and C. velutina, is provided. The IUCN conservation status of the proposed species is Data Deficient (DD)

Evaluation of Asaoka and Hyperbolic Methods for Settlement Prediction of Vacuum Preloading Combined with Prefabricated Vertical Drains in Soft Ground Treatment

This study evaluated the use of the Asaoka and hyperbolic methods to estimate the ultimate settlement of soft ground treated by vacuum preloading combined with prefabricated vertical drains. For this aim, a large-scale physical laboratory model was constructed. The model was a reinforced-tempered glass box containing a soil mass with dimensions of 2.0 × 1.0 × 1.2 m (length × width × depth). Physical models of this scale for the same purpose are rare in the literature. The soil was taken from a typical coastal region in Dinh Vu Hai Phong, Vietnam. The surface settlement near and between the two drains was measured right after the vacuum preloading started. Important properties of the soil were tested to evaluate the effectiveness of the treatment method. The measured settlement was used in the Asaoka and hyperbolic methods to predict the potential ultimate settlement. The results showed the superiority of the vacuum consolidation approach in improving fundamental engineering properties of soft soil. Furthermore, the ultimate settlement predicted by both methods showed a good agreement with the measured value, proving that the Asaoka and hyperbolic methods are suitable for the estimation of the ultimate settlement of soft soil treated with vacuum consolidation

Attention correlated appearance and motion feature followed temporal learning for activity recognition

Recent advances in deep neural networks have been successfully demonstrated with fairly good accuracy for multi-class activity identification. However, existing methods have limitations in achieving complex spatial-temporal dependencies. In this work, we design two stream fusion attention (2SFA) connected to a temporal bidirectional gated recurrent unit (GRU) one-layer model and classified by prediction voting classifier (PVC) to recognize the action in a video. Particularly in the proposed deep neural network (DNN), we present 2SFA for capturing appearance information from red green blue (RGB) and motion from optical flow, where both streams are correlated by proposed fusion attention (FA) as the input of a temporal network. On the other hand, the temporal network with a bi-directional temporal layer using a GRU single layer is preferred for temporal understanding because it yields practical merits against six topologies of temporal networks in the UCF101 dataset. Meanwhile, the new proposed classifier scheme called PVC employs multiple nearest class mean (NCM) and the SoftMax function to yield multiple features outputted from temporal networks, and then votes their properties for high-performance classifications. The experiments achieve the best average accuracy of 70.8% in HMDB51 and 91.9%, the second best in UCF101 in terms of 2DConvNet for action recognition