. In vitro propagation of the new orchid Dendrobium trankimianum T. Yukawa

Dendrobium trankimianum T. Yukawa is a beautiful, endemic orchid of Vietnam, a new species with a first - published description in 2004. It is very rare and expected to be added to the IUCN Red List status - CR. In vitro studies of orchid D. trankimianum T. Yukawa were conducted in order to conserve and increase the genetic pool of this precious wild orchid species. The results showed that full-strength MS medium supplemented with 2.0 mg/L BA and 0.5 mg/L NAA (10.24 PLBs/explant; 90.11% explants formed PLBs) or full-strength MS medium supplemented with 1.5 mg/L TDZ and 0.5 mg/L NAA (14.11 PLBs/explant; 92.06% explants formed PLBs) were the most suitable for protocorm formation. For subculture, suitable growth of shoots were obtained on full-strength MS medium supplemented 1.5 mg/L BA (22.35 shoots/explant; shoots length of 1.96 cm) and full-strength MS medium supplemented with 60 g ripe banana per liter (25.11 shoots/explant; shoots length of 2.12 cm). The shoots in vitro were transferred to half-strength MS supplemented with different concentrations of IAA, IBA and NAA to investigate root formation. The best rooting occurred at 0,5 mg/L NAA (7.91 roots/shoot; root length of 4.01 cm; 98.51% root formation). The plantlets with uniform growth were planted on different substrate: Eco clean soil, Coconut fiber, Fern fiber, 50% Rice husk in combination with 50% Eco clean soil for research the most suitable substrate. After 60 days of transplantion and acclimatization, the result showed that Fern fiber was suitable substrate for plantlet growth in a nursery garden (8.0 roots/ explant; root length of 5.5 cm; survival rate of 93.29%)

UTJECAJ UVJETA POSTUPKA DOBIVANJA MLJEVENE TROSKE TALJENJEM UGLJENA U VISOKOJ PEĆI UZ UPORABU GEOPOLIMERA

In this study, the material characterization of Vietnamese ground coal slag and ground granulated blast furnace slag (GGBFS), such as particle size distribution, chemical composition, bulk density and particle density are shown. The geopolymer specimens were prepared by mixing an 80 m/m% mass of solid materials (ground coal slag and GGBFS in a different ratio) with 20 m/m % of a 10M NaOH alkaline activator. A systematic experimental series was carried out in order to optimize the preparation process. In that series, the heat curing temperature was 60°C for 6 hours, and then selected specimens were heat treated at a high temperature (1000 °C) for 1 hour. After 7 days of ageing, the physical properties of the geopolymer (compressive strength, specimen density) were measured. Also, after 180 days of ageing, the pH values of water in the geopolymer leaching preparation were determined. The results show that the geopolymer can be used for refractory applications due to its good heat resistance properties. However, geopolymers that were heated at 1000 °C had lower compressive strength, specimen density and pH values of water containing the geopolymer than those that were cured at 60 °C.U ovome istraživanju donose se obilježja vijetnamskih granulata ugljene troske i troske željezne rude na osnovi njihove veličine, kemijskoga sastava i gustoće. Uzorci geopolimera pripremljeni su miješanjem 80 % m/m (mase otopljenoga / masa otopine) ugljene i željezne troske (u različitim omjerima) s 20 % m/m 10M NaOH kao alkalnoga aktivatora. Sustavnim serijama eksperimenata optimiziran je postupak pripreme, pri čemu je temperatura iznosila 60 °C tijekom 6 sati, nakon čega su odabrani uzorci zagrijavani 1 sat na 1000 °C. Nakon sljedećih 7 dana izmjerena su fizička svojstva geopolimera (tlačna čvrstoća, gustoća). Zatim je poslije 180 dana određena pH-vrijednost vode korištene u postupku ispiranja geopolimera. Rezultati su pokazali kako geopolimeri mogu biti korišteni za namjene u vatrostalnim uvjetima zahvaljujući toplinskim svojstvima. Također, geopolimeri koji su zagrijavani na 1000 °C imaju niže vrijednosti tlačne čvrstoće, gustoće i pH-vrijednosti vode u njima od onih koji su grijani na 60 °C

Design and fabrication of effective gradient temperature sensor array based on bilayer SnO2/Pt for gas classification

Classification of different gases is important, and it is possible to use different gas sensors for this purpose. Electronic noses, for example, combine separated gas sensors into an array for detecting different gases. However, the use of separated sensors in an array suffers from being bulky, high-energy consumption and complex fabrication processes. Generally, gas sensing properties, including gas selectivity, of semiconductor gas sensors are strongly dependent on their working temperature. It is therefore feasible to use a single device composed of identical sensors arranged in a temperature gradient for classification of multiple gases. Herein, we introduce a design for simple fabrication of gas sensor array based on bilayer Pt/SnO2 for real-time monitoring and classification of multiple gases. The study includes design simulation of the sensor array to find an effective gradient temperature, fabrication of the sensors and test of their performance. The array, composed of five sensors, was fabricated on a glass substrate without the need of backside etching to reduce heat loss. A SnO2 thin film sensitized with Pt on top deposited by sputtering was used as sensing material. The sensor array was tested against different gases including ethanol, methanol, isopropanol, acetone, ammonia, and hydrogen. Radar plots and principal component analysis were used to visualize the distinction of the tested gases and to enable effective classification

Does sunlight drive seasonality of TB in Vietnam? A retrospective environmental ecological study of tuberculosis seasonality in Vietnam from 2010 to 2015.

BACKGROUND: Tuberculosis (TB) is a major global health burden, with an estimated quarter of the world's population being infected. The World Health Organization (WHO) launched the "End TB Strategy" in 2014 emphasising knowing the epidemic. WHO ranks Vietnam 12th in the world of high burden countries. TB spatial and temporal patterns have been observed globally with evidence of Vitamin D playing a role in seasonality. We explored the presence of temporal and spatial clustering of TB in Vietnam and their determinants to aid public health measures. METHODS: Data were collected by the National TB program of Vietnam from 2010 to 2015 and linked to the following datasets: socio-demographic characteristics; climatic variables; influenza-like-illness (ILI) incidence; geospatial data. The TB dataset was aggregated by province and quarter. Descriptive time series analyses using LOESS regression were completed per province to determine seasonality and trend. Harmonic regression was used to determine the amplitude of seasonality by province. A mixed-effect linear model was used with province and year as random effects and all other variables as fixed effects. RESULTS: There were 610,676 cases of TB notified between 2010 and 2015 in Vietnam. Heat maps of TB incidence per quarter per province showed substantial temporal and geospatial variation. Time series analysis demonstrated seasonality throughout the country, with peaks in spring/summer and troughs in autumn/winter. Incidence was consistently higher in the south, the three provinces with the highest incidence per 100,000 population were Tay Ninh, An Giang and Ho Chi Minh City. However, relative seasonal amplitude was more pronounced in the north. Mixed-effect linear model confirmed that TB incidence was associated with time and latitude. Of the demographic, socio-economic and health related variables, population density, percentage of those under 15 years of age, and HIV infection prevalence per province were associated with TB incidence. Of the climate variables, absolute humidity, average temperature and sunlight were associated with TB incidence. CONCLUSION: Preventative public health measures should be focused in the south of Viet Nam where incidence is highest. Vitamin D is unlikely to be a strong driver of seasonality but supplementation may play a role in a package of interventions

Countering Eavesdroppers with Meta-learning-based Cooperative Ambient Backscatter Communications

This article introduces a novel lightweight framework using ambient backscattering communications to counter eavesdroppers. In particular, our framework divides an original message into two parts: (i) the active-transmit message transmitted by the transmitter using conventional RF signals and (ii) the backscatter message transmitted by an ambient backscatter tag that backscatters upon the active signals emitted by the transmitter. Notably, the backscatter tag does not generate its own signal, making it difficult for an eavesdropper to detect the backscattered signals unless they have prior knowledge of the system. Here, we assume that without decoding/knowing the backscatter message, the eavesdropper is unable to decode the original message. Even in scenarios where the eavesdropper can capture both messages, reconstructing the original message is a complex task without understanding the intricacies of the message-splitting mechanism. A challenge in our proposed framework is to effectively decode the backscattered signals at the receiver, often accomplished using the maximum likelihood (MLK) approach. However, such a method may require a complex mathematical model together with perfect channel state information (CSI). To address this issue, we develop a novel deep meta-learning-based signal detector that can not only effectively decode the weak backscattered signals without requiring perfect CSI but also quickly adapt to a new wireless environment with very little knowledge. Simulation results show that our proposed learning approach, without requiring perfect CSI and complex mathematical model, can achieve a bit error ratio close to that of the MLK-based approach. They also clearly show the efficiency of the proposed approach in dealing with eavesdropping attacks and the lack of training data for deep learning models in practical scenarios