Occurrence and Characteristics of Microplastics in Wild and Farmed Shrimps Collected from Cau Hai Lagoon, Central Vietnam.

This study investigated the occurrence of microplastics (MPs) in the gastrointestinal tracts (GT) and tissues of four common shrimps (including two wild-caught shrimps and two farmed shrimps) collected from a high-diversity lagoon in central Vietnam. The numbers of MP items in greasy-back shrimp (Metapenaeus ensis), green tiger shrimp (Penaeus semisulcatus), white-leg shrimp (Litopenaeus vannamei), and giant tiger shrimp (Penaeus monodon), determined per weight and individual, were 0.7 ± 0.3, 0.6 ± 0.2, 1.1 ± 0.4, and 0.5 ± 0.3 (items/g-ww), and 2.5 ± 0.5, 2.3 ± 0.7, 8.6 ± 3.5, 7.7 ± 3.5 (items/individual), respectively. The concentration of microplastics in the GT samples was significantly higher than that in the tissue samples (p < 0.05). The number of microplastics in the farmed shrimp (white-leg shrimp and black tiger shrimp) was statistically significantly higher than the number of microplastics in the wild-caught shrimp (greasy-back and green tiger shrimps) (p <0.05). Fibers and fragments were the dominant shapes of the MPs, followed by pellets, and these accounted for 42-69%, 22-57%, and 0-27% of the total microplastics, respectively. The chemical compositions determined using FTIR confirmed six polymers, in which rayon was the most abundant polymer, accounting for 61.9% of the MPs found, followed by polyamide (10.5%), PET (6.7%), polyethylene (5.7%), polyacrylic (5.8%), and polystyrene (3.8%). As the first investigation on the MPs in shrimps from Cau Hai Lagoon, central Vietnam, this study provides useful information on the occurrences and characteristics of the microplastics in the gastrointestinal tracts and tissues of four shrimp species that live in different living conditions.

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. OBJECTIVE: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. METHODS: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). RESULTS AND DISCUSSION: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. CONCLUSION: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.

Large scale screening for haemoglobin disorders in southern Vietnam: implications for avoidance and management.

In order to obtain an approximate assessment of the public health burden that will be posed by the inherited disorders of haemoglobin in southern Vietnam, several thousand individuals were screened for these conditions. A smaller sample was screened for glucose-6-phosphate dehydrogenase (G6PD) deficiency. The important haemoglobin disorders identified were beta thalassaemia, haemoglobin E and a variety of different forms of alpha thalassaemia. There were sufficient G6PD-deficient individuals to materially affect malaria control programme design. The most remarkable finding was wide variation in the gene frequencies of these conditions among the ethnic groups sampled. The approximate number of babies expected to be born with clinically significant haemoglobin disorders in Vietnam was estimated from the gene-frequency data. This study emphasizes the importance of wide-scale population screening, including ethnic subgroups, to establish the requirements for inherited haemoglobin disorder programmes in resource-limited settings.

Validation of gamma scanning method for optimizing NaI(Tl) detector model in Monte Carlo simulation.

The aim of this study is the validation of gamma scanning method for optimizing NaI(Tl) detector model in Monte Carlo simulation. The experimental procedure involved: scanning on front and lateral surfaces of the detector with collimated low-energy photon beam; calibrating the efficiency with energies between 31-1408 keV for point sources at distances of 0 cm and 30 cm from source to the detector. The Monte Carlo code used for the simulations was MCNP6. The diameter and the length of crystal were determined according to the measured results of gamma scanning with a collimated 241Am radioactive source. The distance from window to crystal was estimated using transmission measurement recorded on a second detector. The density of reflector was adjusted to obtain the match between measured and simulated values of efficiency ratio of 81 and 31 keV from a 133Ba radioactive source. The optimized model was applied in Monte Carlo simulations to determine the efficiency and energy spectrum response function of NaI(Tl) detector for point source measurements in two configurations. Good agreement was obtained between measured and simulated results.

Synthetic protein-conductive membrane nanopores built with DNA.

Nanopores are key in portable sequencing and research given their ability to transport elongated DNA or small bioactive molecules through narrow transmembrane channels. Transport of folded proteins could lead to similar scientific and technological benefits. Yet this has not been realised due to the shortage of wide and structurally defined natural pores. Here we report that a synthetic nanopore designed via DNA nanotechnology can accommodate folded proteins. Transport of fluorescent proteins through single pores is kinetically analysed using massively parallel optical readout with transparent silicon-on-insulator cavity chips vs. electrical recordings to reveal an at least 20-fold higher speed for the electrically driven movement. Pores nevertheless allow a high diffusive flux of more than 66 molecules per second that can also be directed beyond equillibria. The pores may be exploited to sense diagnostically relevant proteins with portable analysis technology, to create molecular gates for drug delivery, or to build synthetic cells.

Investigation of cosmic-ray induced background of Germanium gamma spectrometer using GEANT4 simulation.

In this article, a GEANT4 Monte Carlo simulation toolkit was used to study the response of the cosmic-ray induced background on a High-Purity Germanium (HPGe) gamma spectrometer in the wide energy range, up to 100MeV. The natural radiation background measurements of the spectrometer were carried out in the energy region from 0.04 to 50MeV. The simulated cosmic-ray induced background of the Ge detector was evaluated in comparison with the measured data. The contribution of various cosmic-ray components including muons, neutrons, protons, electrons, positrons and photons was investigated. We also analyzed secondary particle showers induced by the muonic component.

Intercomparison NaI(Tl) and HPGe spectrometry to studies of natural radioactivity on geological samples.

In this study, in situ gamma spectra using NaI(Tl) detector have been compared with the laboratory measurements by using HPGe detector on geological samples. The results for measuring naturally occurring terrestrial gamma radiation of 40K and the decay series of 232Th and, 238U respectively of both detectors show a maximum deviation about 5%. The mass activities series from both detectors were checked for coherence using proficiency test procedure from the International Atomic Energy Agency. The reliability and precision pass for final scores for all the analytical determinations of are received "acceptable" for all radionuclides.