Towards a more robust approach for the restoration of mangroves in Vietnam

Key message Globally, mangrove forests are under threat from a range of causes. They also represent a large potential form of climate mitigation and adaptation via reforestation, and this investment may contribute to restoration efforts and reverse mangrove decline. There has been significant (c. 200,000 ha) mangrove reforestation and restoration activity in Vietnam, and these projects provide indicators of the causes of project failure or success, and what is required for more complex restoration of ecosystem services. Failure in mangrove programs can be attributed to lack of understanding of the reasons for the loss of mangroves, poor site and species selection, and lack of incentives to engage local residents in the long-term management of restored areas. Overcoming these impediments and adopting monitoring and reporting procedures that consider both areal success and ecosystem function will provide a more robust approach for future mangrove restoration projects. Context Over the last three decades there has been considerable (c. 200,000 ha) state and non-government investment in mangrove programs in Vietnam. The main objectives have been coastal protection and stabilization and the production of forest products, with fisheries, climate mitigation, and adaptation and ecosystem restoration as minor objectives. These have had reportedly varied success in terms of long-term survival rates. Much focus has been on the use of mono-species rather than restoring functioning mangrove ecosystems. Aims This paper provides an overview of the status of mangroves in Vietnam and considers the effectiveness of mangrove restoration efforts based on an analysis of these reports. We develop and recommend approaches to make future mangrove restoration programs more effective. Result First, we provide an overview of mangrove distribution and mangrove deforestation in Vietnam. Second, we analyse major mangrove projects by investigating their objectives and exploring reasons for their success or failure. Third, we suggest approaches for successful mangrove restoration activities in the context of current international agreements on climate change. Failure in some mangrove restoration programs in Vietnam can be attributed to lack of understanding of the reasons for the loss of mangroves and of site hydrology, poor site and species selection, lack of long-term monitoring and management, and lack of incentives to engage local communities in the long-term management of restored areas. Removal of these impediments will increase restoration success. Conclusion The widespread and varied mangrove reforestation and restoration activities in Vietnam allow the analysis of different approaches and identification of the key factors leading to restoration success. These include care with species selection, having clear protocols for monitoring and reporting and implementing a co-management approach that provides incentives for local communities to benefit from the management of restored mangroves

Real Time Burning Image Classification Using Support Vector Machine

Burning image classification is critical and attempted problems in medical image processing. This paper has proposed the real time image classification for burning image to automatically identify the degrees of burns in three levels: II, III, and IV. The proposed model uses the multi-colour channels extraction and binary based on adaptive threshold. The proposed model uses One-class Support Vector Machine instead of traditional Support Vector Machine (SVM) because of unbalanced degrees of burns images database. The classifying precision 77.78% shows the feasibility of our proposed model

Gas thermodynamic conditions of cold air entrainment by natural smoke exhaust system in case of compartment fire

Conditions of occurrence of abnormal operation of natural smoke exhaust system are analyzed when cold air is entrained into smoke exhaust windows preventing extraction of smoked heated gas layer beneath a ceiling (also known as plugholing). Analytical equation is derived for prediction of critical average volumetric temperature of gas layer beneath a ceiling when plugholing starts with consideration for the height of smoke exhaust window. This equation was compared with published experimental data and with numerical experiments using 3D field model of fire gas thermodynamics. It was found that the height of smoke exhaust window exerts significant influence on occurrence of plugholing and on maximum bulk flow rate of combustion products extracted from compartment via the window. © 2020, Institute of Advanced Scientific Research, Inc.. All rights reserved

RainPredRNN: A New Approach for Precipitation Nowcasting with Weather Radar Echo Images Based on Deep Learning

Precipitation nowcasting is one of the main tasks of weather forecasting that aims to predict rainfall events accurately, even in low-rainfall regions. It has been observed that few studies have been devoted to predicting future radar echo images in a reasonable time using the deep learning approach. In this paper, we propose a novel approach, RainPredRNN, which is the combination of the UNet segmentation model and the PredRNN_v2 deep learning model for precipitation nowcasting with weather radar echo images. By leveraging the abilities of the contracting-expansive path of the UNet model, the number of calculated operations of the RainPredRNN model is significantly reduced. This result consequently offers the benefit of reducing the processing time of the overall model while maintaining reasonable errors in the predicted images. In order to validate the proposed model, we performed experiments on real reflectivity fields collected from the Phadin weather radar station, located at Dien Bien province in Vietnam. Some credible quality metrics, such as the mean absolute error (MAE), the structural similarity index measure (SSIM), and the critical success index (CSI), were used for analyzing the performance of the model. It has been certified that the proposed model has produced improved performance, about 0.43, 0.95, and 0.94 of MAE, SSIM, and CSI, respectively, with only 30% of training time compared to the other methods. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

The paternal and maternal genetic history of Vietnamese populations

Vietnam exhibits great cultural and linguistic diversity, yet the genetic history of Vietnamese populations remains poorly understood. Previous studies focused mostly on the majority Kinh group, and thus the genetic diversity of the many other groups has not yet been investigated. Here we analyze complete mtDNA genome sequences and ~2.3 Mb sequences of the male-specific portion of the Y chromosome from the Kinh and 16 minority populations, encompassing all five language families present in Vietnam. We find highly variable levels of diversity within and between groups that do not correlate with either geography or language family. In particular, the Mang and Sila have undergone recent, independent bottlenecks, while the majority group, Kinh, exhibits low levels of differentiation with other groups. The two Austronesian-speaking groups, Giarai and Ede, show a potential impact of matrilocality on their patterns of variation. Overall, we find that isolation, coupled with limited contact involving some groups, has been the major factor influencing the genetic structure of Vietnamese populations, and that there is substantial genetic diversity that is not represented by the Kinh.Language Use in Past and Presen

Cockayne syndrome without UV-sensitivity in Vietnamese siblings with novel <em>ERCC8</em> variants.

Cockayne syndrome (CS) is a rare progeroid disorder characterized by growth failure, microcephaly, photosensitivity, and premature aging, mainly arising from biallelic ERCC8 (CS-A) or ERCC6 (CS-B) variants. In this study we describe siblings suffering from classical Cockayne syndrome but without photosensitivity, which delayed a clinical diagnosis for 16 years. By whole-exome sequencing we identified the two novel compound heterozygous ERCC8 variants c.370_371del (p.L124Efs*15) and c.484G&gt;C (p.G162R). The causality of the ERCC8 variants, of which one results in a frameshift and the other affects the WD3 domain, was tested and confirmed by a rescue experiment investigating DNA repair in H2O2 treated patient fibroblasts. Structural modeling of the p.G162R variant indicates effects on protein-protein interaction. This case shows the importance to test for ERCC6 and ERCC8 variants even if patients do not present with a complete CS phenotype