Graphene Effect on Efficiency of TiO2-based Dye Sensitized Solar Cells (DSSC)

Colloidal paste of TiO2 embedded with graphene (GS) was fabricated and used to spread TiO$_2$ film photo-electrode of DSSC solar cells. The dye N179 and Iodine-based electrolyte were used in the DSSC solar cells. Raman scattering, SEM images were used to identify the material phases and microstructure of the film photo-electrode. I/V characteristics of the DSSC cells were recorded at room temperature. Open-circuit voltage Voc, short-current $J_{sc}$ and efficiency η of the DSSC cells were estimated. It shows that graphene addition has affected on $V_{oc}$,$J_{sc}$ and $\eta$. The $V_{oc}$,$J_{sc}$ and $\eta$ abnormally depend on graphene content. The efficiency reached a maximal value with graphen concentration of 0.005 wt %, after that decreased. It is supposed to be related with an improving the charge transfer in the working photo-electrode of DSSC

Long short-term memory (LSTM) neural networks for short-term water level prediction in Mekong river estuaries

This study firstly adopts a state-of-the-art deep learning approach based on a Long Short-Term Memory (LSTM) neural network for predicting the hourly water level of Mekong estuaries in Vietnam. The LSTM models were developed from around 8,760 hourly data points within 2018 and were evaluated using the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error (MAE), and root mean square error (RMSE). The results showed that the NSE values for the training and testing steps were both above 0.98, which can be regarded as very good performance. Furthermore, the RMSE were between 0.09 and 0.11 m for the training and between 0.10 and 0.12 m for the testing, while MAE for the training ranged from 0.07 to 0.08 m and varied from 0.08 to 0.10 m for the testing. The LSTM networks appear to enable high precision and robustness in water level time series prediction. The outcomes of this research have crucial implications in river water level predictions, especially from the viewpoint of employing deep learning algorithms

Apramycin susceptibility of multidrug-resistant Gram-negative blood culture isolates in five countries in South-East Asia

Bloodstream infections (BSIs) are a leading cause of sepsis, a life-threatening condition that contributes significantly to the mortality of bacterial infections. Aminoglycoside antibiotics such as gentamicin or amikacin are essential medicines in the treatment of BSIs, but their clinical efficacy is increasingly compromised by antimicrobial resistance. The aminoglycoside apramycin has demonstrated preclinical efficacy against aminoglycoside- and multidrug-resistant (MDR) Gram-negative bacilli (GNB) and is currently in clinical development for the treatment of critical systemic infections. Here, we collected a panel of 470 MDR GNB isolates from health care facilities in Cambodia, Laos, Singapore, Thailand, and Vietnam for a multi-centre assessment of their antimicrobial susceptibility to apramycin in comparison to other aminoglycosides and colistin by broth microdilution assays. Apramycin and amikacin MICs ≤ 16 µg/mL were found for 462 (98.3%) and 408 (86.8%) GNB isolates, respectively. Susceptibility to gentamicin and tobramycin (MIC ≤ 4 µg/mL) was significantly lower at 122 (26.0%) and 101 (21.5%) susceptible isolates, respectively. Of note, all carbapenem- and third-generation cephalosporin (3GC) resistant Enterobacterales, all Acinetobacter baumannii, and all Pseudomonas aeruginosa isolates tested in this study appeared to be susceptible to apramycin. Of the 65 colistin-resistant isolates tested, only four (6.2%) had an apramycin MIC > 16 µg/mL. Apramycin demonstrated best-in-class activity against a panel of GNB isolates with resistances to other aminoglycosides, carbapenems, 3GC, and colistin, warranting continued consideration of apramycin as a drug candidate for the treatment of multidrug-resistant BSIs. Keywords: Bloodstream infection; Gram negative; aminoglycoside; antimicrobial resistance; apramycin; blood culture isolates

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

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

Common Adverse Events from Mixing COVID-19 Vaccine Booster in Hanoi, Vietnam

Background: Mixing vaccines was proposed as a solution to tackle supply chain interruptions during the crisis of the COVID-19 pandemic. This study aimed to investigate the safety of mixing COVID-19 vaccines for a booster dose in Hanoi, Vietnam. Method: A cross-sectional study was conducted via a telephone-based interview to identify the adverse events following COVID-19 vaccination among 719 participants in Hanoi, Vietnam. Results: In total, 45.76% of participants experienced at least one adverse event following two doses of the COVID-19 vaccine. Most of the adverse events were local effects with mild symptoms such as fever, headache, muscle pain, and/or pain at the site. In general, matching two doses in the same vaccines was not associated with the adverse events as compared to mixing vaccines (OR = 1.43, 96%CI: 0.93–2.2), except matching two doses of Pfizer (OR = 2.25, 95%CI: 1.33–3.82). Conclusion: The findings of this study suggest the overall safety of mixed vaccination. In light of the vaccine shortage, mixing vaccinations for COVID-19 prevention is a good solution. Further studies with larger cohorts and investigating immunity following mixing vaccines are needed to elucidate the mechanism

Synthesis and characterization of the photoswitchable poly(methyl methacrylate- random-methacrylate spirooxazine)

Abstract The photoswitchable poly(methyl methacrylate-random-methacrylate spirooxazine) was synthesized via atom transfer radical polymerization with the feed mole ratio of MMA/MSp comonomer of about 5.5/1. Well-defined poly(methyl methacrylate- random-methacrylate spirooxazine) have been obtained with the average molecular weight (Mn) of 6500 g/mol and polydispersity of 1.21. The structure and properties of the resulting copolymers were characterized by proton nuclear magnetic resonance (1H NMR), gel permeation chromatography, Fourier Transform infrared, UV-visible spectroscopy, and differential scanning calorimetry. Moreover, the copolymer exhibited the erasable and rewritable photoimaging on the solid state film which could to be as potential candidate for optical data storage materials

Evaluation of the safety and immune stimulatory effects of multi-strain Lab Mix product on laboratory animals

Background &amp; aims: Probiotics are alive and beneficial bacteria used as food complements with sufficient amounts to improve and balance the intestinal flora in the human gastrointestinal tract and inhibit harmful microorganisms. In this study, we conducted experiments to evaluate he safety and the effect of one of our probiotics on selected biochemical parameters in animal models. Methods: LabMix is a probiotic product containing three bacterial strains, including Lactobacillus acidophilus LA 304.17, Lactobacillus casei LC 304.08, and Bifidobacterium bifidum BF 304.98, with a density of 9 × 109 CFU/g and being mixed with suitable excipients. In this study, we conducted experiments to evaluate LabMix's acute ttoxicity in mice as well as subchronic toxicity in rats. Results: The LD50 dose in mice of this product could not be determined since no death or disorder was recorded. In rats receiving LabMix with doses of 2.52 × 109 CFU/kg and 12.6 × 109 CFU/kg continuously for 28 days, this product caused no significant changes in the amount of red and white blood cells and platelets. Similarly, no significant changes were recorded in serum concentrations of hemoglobin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), glucose, protein, cholesterol, bilirubin, and creatinine. Besides, LabMix products also did not cause any changes in the histology of the liver, kidney, and spleen in rats. Moreover, LabMix was well tolerated without affecting the normal growth and feeding of rats. Furthermore, LabMix also decreased serum cytokines and increased serum and gut mucosal IgA antibodies. Conclusions: LabMix product is possibly considered safe for human., and this sproduct reduced the release of pro-inflammatory cytokines (IL-6 and TNF-α), but increased IgA levels. However, it is necessary to further evaluate the product's effectiveness in the preclinical phase as well as in further phases before mass production and commercialization

Spatial prediction of landslides along National Highway-6, Hoa Binh province, Vietnam using novel hybrid models

Landslides are considered to be a significant risk to life and property all over the world in general and in Vietnam in particular. Spatial prediction of landslides is required to reduce the landslides risk and to plan the development of hilly areas. In this regard, the accurate landslide susceptibility maps are very useful tool for decision-makers to identify areas where new landslides are likely to occur for planning timely adequate remedial measures. For the development of landslide susceptibility maps, seven hybrid models were developed namely AdaBoost-LMT (ABLMT), bagging-LMT (BLMT), cascade generalization-LMT (CGLMT), dagging-LMT (DLMT), MultiBoostAB-LMT (MBLMT), rotation forest-LMT (RFLMT) and random sub-space-LMT (RSSLMT) with logistic model trees (LMTs) as a base classifier. The model’s performance and validation were assessed through various statistical indices, such as sensitivity (SST), specificity (SPF), accuracy (ACC), area under ROC curve (AUC), RMSE and k index. The results show that all these models are performing well for the prediction of landslide susceptibility in the study area, but the performance of the RSSLMT model is the best (AUC: 0.816). In this study, open-source data has been used for the development of landslide susceptibility maps Along National Highway-6, passing through Hoa Binh province, Vietnam. These approaches can be applied also in other hilly regions of the world which are susceptible to landslides for better landslides prevention and management