Effects of tea cultivation on soil quality in the northern mountainous zone, Vietnam

The objectives of the study were to assess soil quality and its relationship to the sustainability of tea cultivation in the Northern Mountainous Zone, Vietnam. Overall soil quality declined with increasing age of the tea plantations as evidenced by decreases in soil OC, total N, K and S, available P and K, mean weight diameter of aggregates, total porosity, plant available water capacity (PAWC), and earthworm populations. As well, total P, bulk density and mechanical resistance increased with increasing cultivation intensity. Because these soil properties were sensitive to cultivation effects, they were considered to be good indicators of soil quality. Soil properties that were less sensitive to change, and limited as soil quality indicators included texture, clay mineralogy and sesquioxides, Cd concentration, and effective cation exchange capacity. Soil quality changes were greatest during the first 10 years of cultivation and were generally greatest in the surface 0-to 40-cm of soil. Soil and crop management factors (e.g., fertilization) were considered to be the most important factors affecting soil quality. Decreases in long-term crop yields were found to correspond with decreases in soil quality. In terms of crop productivity, the most important soil quality indicators (based on a multiple regression analysis) were OC, available P, total K and PAWC. Economic analysis of the yield and production cost data indicated that, under current conditions, tea cultivation in the Northern Mountainous Zone is sustainable for periods of about 40 years. Thus, measured values of soil quality indicators in the 40-yr tea soils were considered to represent the "critical levels" for economic sustainability of tea cultivation. In addition to quantitative assessments of soil quality, qualitative assessments involving farmer interviews were used to evaluate the overall efficiency of current management practices to sustain long-term tea production. The major socio-economic indicator of sustainability was farm prosperity, which reflected the willingness of farmers to adopt soil conservation technologies. Government policies related to land ownership and market access also were important factors influencing sustainability. Generally, farmer observations of the changes in soil quality were in good agreement with the quantitative assessments. Qualitative information obtained from on-farm surveys supplement the quantitative data obtained through soil analyses, and should be incorporated into future studies

DESIGN OF A HIGH-SENSITIVITY DEVICE FOR DETECTING WEAK MAGNETIC FIELDS

An anti-serial fluxgate sensor configuration is proposed in this report. The design comprises two identical bilayer-rod fluxgate sensors connected anti-serially in a straight line. Each bilayer-rod sensor is constructed of an excitation coil and a pick-up coil wrapped around a core. The core material consists of Metglas ribbon, an amorphous alloy with high permeability, negligible hysteresis, and a high saturated magnetic field. The core is cut into a bar shape and uses double layers to enhance modulated flux density. A high sensitivity of 10 mV/Oe (with excitation of 45 kHz and 250 mA) is obtained experimentally with low noise of 1´10-5 Oe/Ö Hz at 1 Hz. In measurements of weak magnetic fields, the azimuth response indicates its vector feature. The proposed design is suitable for electronic compass and displacement applications

A sharp bound for the resurgence of sums of ideals

We prove a sharp upper bound for the resurgence of sums of ideals involving disjoint sets of variables, strengthening work of Bisui--H\`a--Jayanthan--Thomas. Complete solutions are delivered for two conjectures proposed by these authors. For given real numbers $a$ and $b$, we consider the set Res$(a,b)$ of possible values of the resurgence of $I+J$ where $I$ and $J$ are ideals in disjoint sets of variables having resurgence $a$ and $b$, respectively. Some questions and partial results about Res$(a,b)$ are discussed.Comment: 14 pages, 01 figur

A fed-batch fermentation process for poly (3-hydroxybutyrate-co-3-hydroxyvalerate) production by Yangia sp. ND199 using molasses as substrate

A locally isolated halophilic bacterium, Yangia sp. ND199 was able to use molasses as substrate for copolymers poly(3-hydroxybutyrate-co-3-hydroxyvalerate) [P(3HB-co-3HV)] production. Cell dry weight (CDW) of 6.37 g/l, P(3HB-co-3HV) content of 43.1 wt% and P(3HB-co-3HV) concentration of 2.75 g/l were obtained by Yangia sp. after 60 h of cultivation in flask. In a batch cultivation mode in a fermentor, the CDW was increased to 9.1 g/l but P(3HB-co-3HV) content was decreased to 37 wt%. Fed-batch fermentation with two different nutrient feeding strategies was used. High CDW of 54.8 g/l was obtained after 54 h of cultivation but P(3HB-co-3HV) content was still low (39.8 wt%). Two-step fed-batch fermentation with two different nutrient feeding strategies was then designed. High CDW of 50 g/l and P(3HB-co-3HV) content of 52.9 wt% were obtained after 54 h of cultivation. The two-step fed-batch process designed here for the production of P(3HB-co-3HV) by Yangia sp. ND199 can be developed and used for further studies

A Machine Learning-based Approach to Vietnamese Handwritten Medical Record Recognition

Handwritten text recognition has been an active research topic within computer vision division. Existing deep-learning solutions are practical; however, recognizing Vietnamese handwriting has shown to be a challenge with the presence of extra six distinctive tonal symbols and extra vowels. Vietnam is a developing country with a population of approximately 100 million, but has only focused on digitalization transforms in recent years, and so Vietnam has a significant number of physical documents, that need to be digitized. This digitalization transform is urgent when considering the public health sector, in which medical records are mostly still in hand-written form and still are growing rapidly in number. Digitization would not only help current public health management but also allow preparation and management in future public health emergencies. Enabling the digitalization of old physical records will allow efficient and precise care, especially in emergency units. We proposed a solution to Vietnamese text recognition that is combined into an end-to-end document-digitalization system. We do so by performing segmentation to word-level and then leveraging an artificial neural network consisting of both convolutional neural network (CNN) and a long short-term memory recurrent neural network (LSTM) to propagate the sequence information. From the experiment with the records written by 12 doctors, we have obtained encouraging results of 6.47% and 19.14% of CER and WER respectively

A study of 3D modelling the vibrations induced from grab shock at the Metro Line 3 project in Hanoi

The density of high-rise building is increasing over recent years in urban city. Construction activities, particularly piling processes, D-wall excavation, are paid attention due to ground borne vibrations. The impact of vibrations induced from construction activates on existing buildings is discussed in the past and so on. However, there is rarely study their vibrations in Vietname specially in construction activities such as grab shocking. Continuing the analytical and experimental studies of the grab shocking in the Metro Line 3 project in Hanoi, 3D modelling of vibrations induced from the grab shocking on the existing building is carried out by Plaxis software. The hardening soil model is used and the acceleration of the grabin the bentonite slurry is considered in the model. The comparison between the analytical solution and the 3D simulation is highlighted in the paper to show the accuracy and robustness of the 3D modeling. This study is applied to investigate the vibrations on existing building in the Metro Line 3 project and to control the grab drop length as well as the distance of existing building to the vibration source

Apply deep learning to improve the question analysis model in the Vietnamese question answering system

Question answering (QA) system nowadays is quite popular for automated answering purposes, the meaning analysis of the question plays an important role, directly affecting the accuracy of the system. In this article, we propose an improvement for question-answering models by adding more specific question analysis steps, including contextual characteristic analysis, pos-tag analysis, and question-type analysis built on deep learning network architecture. Weights of extracted words through question analysis steps are combined with the best matching 25 (BM25) algorithm to find the best relevant paragraph of text and incorporated into the QA model to find the best and least noisy answer. The dataset for the question analysis step consists of 19,339 labeled questions covering a variety of topics. Results of the question analysis model are combined to train the question-answering model on the data set related to the learning regulations of Industrial University of Ho Chi Minh City. It includes 17,405 pairs of questions and answers for the training set and 1,600 pairs for the test set, where the robustly optimized BERT pre-training approach (RoBERTa) model has an F1-score accuracy of 74%. The model has improved significantly. For long and complex questions, the mode has extracted weights and correctly provided answers based on the question’s contents

Extracting Fetal Electrocardiogram from Being Pregnancy Based on Nonlinear Projection

Fetal heart rate extraction from the abdominal ECG is of great importance due to the information that carries in assessing appropriately the fetus well-being during pregnancy. In this paper, we describe a method to suppress the maternal signal and noise contamination to discover the fetal signal in a single-lead fetal ECG recordings. We use a locally linear phase space projection technique which has been used for noise reduction in deterministically chaotic signals. Henceforth, this method is capable of extracting fetal signal even when noise and fetal component are of comparable amplitude. The result is much better if the noise is much smaller (P wave and T wave can be discovered)

The application of split step fourier migration to interpreting GPR data in Vietnam

Migration methods play an essential role in processing ground penetrating radar data. For estimating electromagnetic propagation velocity distribution, the finite - difference migration is used because of its reliable performance with high noise conditions. To optimize this migration algorithm, we propose using energy diagram as a criterion of looking for the correct velocity. If the velocity varies laterally and vertically, split step Fourier migration is used for creating a true image of subsurface structures. We applied these steps to real data in Vietnam. The results verified on field data show that migrated images with calculated velocity from energy diagram have the best quality