Village Baseline Study – Site Analysis Report Ma village-Yen Binh district, Vietnam

Ma village, Vinh Kien commune, Yen Binh district, Yen Bai province has been selected to be one of Climate Smart Villages (CSVs) under the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) in Southeast Asia. The village baseline survey (VBS) of Ma village, was therefore conducted as part of the baseline effort. This VBS aimed to provide baseline information at the village level about some basic indicators of natural resource utilization, organizational landscapes, and information networks for weather and agricultural information, which can be compared across sites and monitored over time. The study was conducted using the method developed and provided by CCAFS. The study’s findings show that Ma Village is rich and diverse in natural resources. There are three main resources of vital importance for the local people livelihoods, namely farmland, forest and water resources. However, improper exploitation and management have caused negative impacts on these resources. As mentioned by farmers, in the past, farmland of the village used to be very fertile, but has now become severely degraded due to overexploitation and improper management. Regarding forest resources: before 1980s, natural forests existed in large areas and consisted of valuable timber and wild animals. Today, much of the forest area has been converted to production forests or to food crop production land. Water resources, including lakes, rivers and streams have been severely polluted with pollutants from processing cassava, wood and also from animal husbandry and crop production. Degradation of water, farmland and forest resources are causing increasing challenges to agricultural production and also to other human activities. Results of farmer group discussions also demonstrate that there are 34 organizations operating in the village. Most of them are governmental. Very few are private or non-governmental organizations. The number of organizations involving in food security accounts for nearly 50%, the figure for those involving food crisis is 41.6% and in natural resources management is 25%. Those organizations working in food security and food crisis focus mainly on providing support (financial, seed and agricultural inputs) to local farmers to implement some production activities. Insufficient attention and input spent for sustainable development by these 34 organizations, especially those working in the area of natural resources management, could be one of the main reasons for the degradation and erosion of natural resources. There was no activity supporting Ma Village to develop production systems which can respond well to climate change. The study findings however show that local people are very flexible and creative, especially in exploitation of information. Among media channels, television is the most popular. Nevertheless, organizations, in particular, extension networks, Farmers’ Union, local authorities, etc., also have an important role in information dissemination. Exploitation of information from the internet and mobile phones has also been given attention, but mostly by young people only

The Impact of Government Expenditure and Tertiary Education on High-Technology Exports: Evidence from Asia-Pacific and European Nations

This study extends the growing literature on the 4th and 9th Sustainable Development Goals by examining whether tertiary education moderates the relationship between government spending on education and high-technology exports. We employ Robust Least Squares Estimation to analyze an unbalanced panel of 24 Asia-Pacific countries and 37 European nations from 2007 to 2022. This method effectively handles outliers and heteroskedasticity in panel estimations. The empirical results indicate that both a higher ratio of tertiary education enrollment and government expenditure empower high-technology exports. Our findings support human capital, innovation, and endogenous growth theories, as well as prior literature. However, the study reveals significant regional disparities in the impact of education on high-technology exports. While higher tertiary enrollment boosts high-tech exports in Asia-Pacific countries, government spending has little impact. Conversely, in European countries, government spending positively influences high-tech exports, while tertiary enrollment shows no significant effect. This study contributes practical policy implications for sustainably improving high-technology exports in Asia-Pacific and European nations by fostering human capital development and efficient government spending on education

Optimizing Boiler Efficiency by Data Mining Teciques: A Case Study

In a fertilizer plant, the steam boiler is the most important component. In order to keep the plant operating in the effective mode, the boiler efficiency must be observed continuously by several operators. When the trend of the boiler efficiency is going down, they may adjust the controlling parameters of the boiler to increase its efficiency. Since manual operation usually leads to unex-pectedly mistakes and hurts the efficiency of the system, we build an information system that plays the role of the operators in observing the boiler and adjusting the controlling parameters to stabilize the boiler efficiency. In this paper, we first introduce the architecture of the information system. We then present how to apply K-means and Fuzzy C-means algorithms to derive a knowledge base from the historical operational data of the boiler. Next, recurrent fuzzy neural network is employed to build a boiler simulator for evaluating which tuple of input values is the best optimal and then automatically adjusting controlling inputs of the boiler by the optimal val-ues. In order to prove the effectiveness of our system, we deployed it at Phu My Fertilizer Plant equipped with MARCHI boiler having capacity of 76-84 ton/h. We found that our system have improved the boiler efficiency about 0.28-1.12% in average and brought benefit about 57.000 USD/year to the Phu My Fertilizer Plant

Organic - Inorganic Hybrid Luminescent Composite for Solid-state Lighting

White light emitting diodes (WLEDs) made by coating organic and inorganic hybrid composites on blue LED chips. Y3Al5O12:Ce (YAG:Ce) nano inorganic powder prepared by low-temperature Sol-Gel method exhibited broad green emission with the peak at 521 nm. Poly[2-methoxy-5-(2'-ethyl-hexyloxy)-1,4-phenylene vinylene] (MEH-PPV) polymer has high luminescence efficiency and red emission peak at 590 nm. The white light was obtained by mixing blue light from emission of the blue LED chip - Indium Gallium Nitride (InGaN) and green-red light from the fluorescence of nano- YAG:Ce and MEH-PPV polymer hybrid composite. The hybrid nanocomposite-based WLEDs exhibited broad band emission spectra from blue light to red wavelengths and provided the white light with a CIE-1931 coordinate of x = 0.2986, y = 0.2620 and a colour rendering index Ra = 84.36. The results suggest a potential application of nanocomposite based WLEDs in efficient solid-state lighting

Spondylolysis-induced Multilevel Lumbar Spondylolisthesis; Challenges in Lumbar Spine Surgery

Lumbar spondylolysis and multilevel lumbar spondylolysis account for 4.4-5.8% and 0.3% of the general population, and multilevel lumbar spondylolysis resulting in spondylolisthesis is even rarer. Herein, we report two cases of three-level lumbar spondylolisthesis because of spondylolysis: A 49-year-old woman was admitted to the hospital for dull lower back pain over the past 8 months, with exacerbating symptoms when standing and walking. Spasticity at lumbar region and radiculopathy at S1 nerve root was found on examination and a 63-year-old man was admitted to the hospital because of numbness and perianal sensory disturbances with difficulty urinating 2 weeks ago, the symptoms gradually increased to the time of examination. Both patients were diagnosed with multilevel lumbar spondylolisthesis because of spondylolysis and were indicated for posterior lumbar interbody fusion (PLIF). After surgery, both patients recovered well without any significant complications. The improved treatment results suggest the application of PLIF technique to treat spondylolysis-induced multilevel lumbar spondylolisthesis

CSA: Thực hành nông nghiệp thông minh với khí hậu ở Việt Nam

During the last five years, Vietnam has been one of the countries most affected by climate change. Severe typhoons, flooding, cold spells, salinity intrusion, and drought have affected agriculture production across the country, from upland to lowland regions. Fortunately for Vietnam, continuous work in developing climate-smart agriculture has been occurring in research organizations and among innovative farmers and entrepreneurs. Application of various CSA practices and technologies to adapt to the impact of climate change in agriculture production have been expanding. However, there is a need to accelerate the scaling process of these practices and technologies in order to ensure growth of agriculture production and food security, increase income of farmers, make farming climate resilient, and contribute to global climate change mitigation. This book aims to provide basic information to researchers, managers, and technicians and extentionists at different levels on what CSA practices and technologies can be up scaled in different locations in Vietnam

Taxonomic assignment for large-scale metagenomic data on high-perfomance systems

Metagenomics is a powerful approach to study environment samples which do not require the isolation and cultivation of individual organisms. One of the essential tasks in a metagenomic project is to identify the origin of reads, referred to as taxonomic assignment. Due to the fact that each metagenomic project has to analyze large-scale datasets, the metatenomic assignment is very much computation intensive. This study proposes a parallel algorithm for the taxonomic assignment problem, called SeMetaPL, which aims to deal with the computational challenge. The proposed algorithm is evaluated with both simulated and real datasets on a high performance computing system. Experimental results demonstrate that the algorithm is able to achieve good performance and utilize resources of the system efficiently. The software implementing the algorithm and all test datasets can be downloaded at http://it.hcmute.edu.vn/bioinfo/metapro/SeMetaPL.html

The transfer and decay of maternal antibody against Shigella sonnei in a longitudinal cohort of Vietnamese infants.

BACKGROUND: Shigella sonnei is an emergent and major diarrheal pathogen for which there is currently no vaccine. We aimed to quantify duration of maternal antibody against S. sonnei and investigate transplacental IgG transfer in a birth cohort in southern Vietnam. METHODS AND RESULTS: Over 500-paired maternal/infant plasma samples were evaluated for presence of anti-S. sonnei-O IgG and IgM. Longitudinal plasma samples allowed for the estimation of the median half-life of maternal anti-S. sonnei-O IgG, which was 43 days (95% confidence interval: 41-45 days). Additionally, half of infants lacked a detectable titer by 19 weeks of age. Lower cord titers were associated with greater increases in S. sonnei IgG over the first year of life, and the incidence of S. sonnei seroconversion was estimated to be 4/100 infant years. Maternal IgG titer, the ratio of antibody transfer, the season of birth and gestational age were significantly associated with cord titer. CONCLUSIONS: Maternal anti-S. sonnei-O IgG is efficiently transferred across the placenta and anti-S. sonnei-O maternal IgG declines rapidly after birth and is undetectable after 5 months in the majority of children. Preterm neonates and children born to mothers with low IgG titers have lower cord titers and therefore may be at greater risk of seroconversion in infancy

The Impact of Teaching Strategies in Blended Learning on Students’ Self-Directed Learning Capability at Hanoi University of Science and Technology

Blended learning (BL) is considered a highly effective educational approach in the 21st century. It not only fosters creative thinking but also promotes problem-solving, critical thinking, effective communication, and technology application among learners. This study investigates the impact of teaching strategies within a BL environment on the self-directed learning (SDL) competence of students at Hanoi University of Science and Technology (HUST). Using quantitative methods, the study analyzes data from 485 students engaging in a combination of face-to-face and online learning. Seven commonly used and valued teaching strategies in BL were examined. The study evaluates students’ SDL levels using the Self-Rating Scale of Self-Directed Learning (SRSSDL), which comprises five factors. The research participants were divided into seven specialized groups based on their characteristics and academic majors. The results indicate that students’ SDL competence is generally high. The students in the Electrical and Electronics Engineering group exhibited the highest SDL capability, while those in the Mechanical Engineering group require further improvement. The teaching strategies that have the most positive impact on SDL are Active Learning, Problem-Based Learning, and Personalized Learning. The findings of this study provide valuable insights into the effectiveness of various teaching strategies utilised in BL, which can serve as a foundation for optimizing teaching strategies to further promote learner self-direction competence

Hemorrhagic Meningioma With Symptom of Convulsion: A Rare Presentation of Parietal Meningioma

Meningioma is the most common, extra-axial, non-glial intracranial tumor with an incidence of 2.3-5.5/100 000, accounting for 20%-30% of all primary brain tumor diagnoses in adults. Meningiomas associated with intratumoral hemorrhage are very rare occurring in 0.5%-2.4%. of individuals. Herein, we report a rare case of hemorrhagic meningioma with the symptom of convulsion. The case was a 68-year-old woman admitted to the hospital with severe headache and convulsions. Computed tomography revealed an increase in heterogeneous lesion measuring 4 × 3 × 2.5 cm at the right parietal lobe. Brain magnetic resonance imaging (MRI) showed a grossly stable homogeneously enhancing extra-axial mass measuring 43 × 33 × 28 mm, small calcified peripheral, intratumoral hemorrhage. Histopathology showed a multi-celled meningioma with bleeding areas (WHO grade I)