Investigating the elements influencing the psychological issues of reform school students

Reformatory students are those whose deviant behaviors and habits prevent them from receiving education under normal educational conditions. These students frequently lead a careless, undisciplined lifestyle, being unwilling to work and learn eager to play and demanding. Therefore, when they are admitted to reformatories with severe study and lifestyle requirements, they have great psychological difficulty adjusting to their new environment. Students’ psychological issues in adapting to reformatory learning and living regimes are difficult and psychological deficits make it challenging for students to adapt to reformatory learning and living conditions. In Vietnam, 665 students from reformatory schools were polled to determine the causes of psychological issues. According to the findings, a variety of elements contribute to students’ psychological difficulties. Individual student conditions such as health, awareness, attitudes and actions as well as inappropriate habits, living without goals or aspirations, etc. are on the subjective side of the equation. On the objective side are the students’ conditions, family, education and psychological obstacles brought on by less-than-ideal circumstances which will make it more difficult for community students to adapt. Both the new school and society must pay more attention to reformatory students in order to establish the conditions necessary for successful integration into the new school and ultimate readmission into society for these students

Physico-chemical properties of fourteen popular cocoa bean varieties in Dongnai-highland Vietnam

Cocoa (Theobroma cacao L.) is a major, crucial economic, global crop and has been maintained several nutritional benefits. The exporting volume of Vietnamese cocoa bean is increasing in the world cocoa trade. The beans of fourteen popular cocoa varieties that are commonly cultivated in Trang Bom (Dong Nai, Vietnam) were characterized for their physico-chemical qualifications on the background of post-fermented cocoa beans and dehydration in the region of Trang Bom-Dong Nai. The physical properties were determined based on mass ratio and bean’s dimension (lengh, width and thickness) as well as chemical (proximate) composition (total crude protein, ash, moisture, and lipid). These values were analysed using AOAC methods. The largest-size beans were found for the TD8 variety (1.5 g of mass, 25.02 mm of length, 14.28 mm of width and 7.96 mm of thickness). The moisture content of the cocoa beans was in the range between 5.64 and 6.99 (% wb) and the ash content in the range between 3.67% and 2.47% (wb). Noticeably, the fat content ratio (the most important value of cocoa bean) found in 8 varieties (TD1, TD2, TD5, TD9, TD11, TD12, TD13, TD14) was over 50%, thus these varieties are worthy chemical component especially for exported cocoa bean and industrized cultivation (extending the cultivation producing area)

Design and simulation of automotive radar for autonomous vehicles

Modern automobile technology is pushing towards maximizing road safety, connected vehicles, autonomous vehicles, etc. Automotive RADAR is core sensor technology used for ADAS (Advanced Driver Assistance Technology), ACC (Adaptive Cruise Control), AEB (Automatic Emergency Braking System), traffic assistance, parking aid, and obstacle/pedestrian detection. Despite being inexpensive, RADAR technology provides robust results in harsh conditions such as harsh weather, extreme temperature, darkness, etc. However, the performance of these systems depends on the position of the RADAR and its characteristics like frequency, beamwidth, and bandwidths. Moreover, the characterization of varied materials like layers of paint, polish, primer, or layer of rainwater needs to be analyzed. This performance can be predicted through real-time simulation using advanced FEM software like Altair FEKO&WinProp. These simulations can provide valuable insight into the performance of the system, allowing engineers to optimize the system for specific use cases. For example, simulation can be used to determine the optimal parameters of the RADAR system for a given application. This information can then be used to design and build a physical model or prototype that is optimized for the desired performance. These simulations play a prominent role in determining appropriate data collection and sensor fusion, which reduces the cost and time required for the development of a physical model or prototype. The continued growth and demand for advanced safety features in vehicles further highlight the importance of RADAR technology in modern automobile technology. By accurately characterizing the environment and simulating the system's behavior in real time, engineers can optimize RADAR systems for specific use cases, contributing to safer and more efficient driving experience

Multifunctional nanocarriers of Fe3O4@PLA-PEG/curcumin for MRI, magnetic hyperthermia and drug delivery

Background: Despite medicinal advances, cancer is still a big problem requiring better diagnostic and treatment tools. Magnetic nanoparticle (MNP)-based nanosystems for multiple-purpose applications were developed for these unmet needs. Methods: This study fabricated novel trifunctional MNPs of Fe3O4@PLA-PEG for drug release, MRI and magnetic fluid hyperthermia. Result: The MNPs provided a significant loading of curcumin (∼11%) with controllable release ability, a high specific absorption rate of 82.2 W/g and significantly increased transverse relaxivity (r2 = 364.75 mM-1 s-1). The in vivo study confirmed that the MNPs enhanced MRI contrast in tumor observation and low-field magnetic fluid hyperthermia could effectively reduce the tumor size in mice bearing sarcoma 180. Conclusion: The nanocarrier has potential for drug release, cancer treatment monitoring and therapy.The authors are grateful for the financial support by AOARD under award FA2386-17-1-4042. The Spanish government is acknowledged for the “Nanotechnology in translational hyperthermia (HIPERNANO)” research network (RED2018102626-T) and for funding under the project number MAT2017-83631-C3. NTK Thanh thanks EPSRC (EP/M015157/1). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed

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

The epidemiology and aetiology of diarrhoeal disease in infancy in southern Vietnam: a birth cohort study.

OBJECTIVES: Previous studies indicate a high burden of diarrhoeal disease in Vietnamese children, however longitudinal community-based data on burden and aetiology are limited. The findings from a large, prospective cohort study of diarrhoeal disease in infants in southern Vietnam are presented herein. METHODS: Infants were enrolled at birth in urban Ho Chi Minh City and a semi-rural district in southern Vietnam, and followed for 12 months (n=6706). Diarrhoeal illness episodes were identified through clinic-based passive surveillance, hospital admissions, and self-reports. RESULTS: The minimum incidence of diarrhoeal illness in the first year of life was 271/1000 infant-years of observation for the whole cohort. Rotavirus was the most commonly detected pathogen (50% of positive samples), followed by norovirus (24%), Campylobacter (20%), Salmonella (18%), and Shigella (16%). Repeat infections were identified in 9% of infants infected with rotavirus, norovirus, Shigella, or Campylobacter, and 13% of those with Salmonella infections. CONCLUSIONS: The minimum incidence of diarrhoeal disease in infants in both urban and semi-rural settings in southern Vietnam was quantified prospectively. A large proportion of laboratory-diagnosed disease was caused by rotavirus and norovirus. These data highlight the unmet need for a rotavirus vaccine in Vietnam and provide evidence of the previously unrecognized burden of norovirus in infants