Uso de variables de mercado en la predicción de dificultades financieras para las empresas que cotizan en Vietnam

This paper aims to investigate the classification power of market variables as predictors in the financial distress prediction model for listed companies in a frontier market as Vietnam securities market. Data is collected from 70 financially distressed companies that suffer a loss in 3 consecutive years and 156 non-financially distressed companies in Vietnam from 2010 to 2017. Four different models have been constructed using Logit regression and SVM analysis technique to make a prediction in 1 to 3-year ahead. The analysis results show that combining accounting ratios with market variables such as price volatility and P/E can improve the classification ability of the ex-ante model. In addition, contrary to the results of related previous researches in emerging markets, in this study, Logit models outperform SVM models. Therefore, for future research, models that apply other machine learning classifiers such as Decision Tree (DT) or Neural Network (NN) should be investigated.Este artículo tiene como objetivo investigar el poder de clasificación de las variables del mercado como factores predictivos en el modelo de predicción de dificultades financieras para las empresas que cotizan en bolsa en un mercado fronterizo como el mercado de valores de Vietnam. Los datos se recopilan de 70 compañías con dificultades financieras que sufrieron una pérdida en 3 años consecutivos y 156 empresas sin dificultades financieras en Vietnam desde 2010 a 2017. Se han construido cuatro modelos diferentes utilizando regresión Logit y la técnica de análisis de SVM para hacer una predicción en 1 a 3 años por delante. Los resultados del análisis muestran que la combinación de ratios contables con variables de mercado como la volatilidad de los precios y el P / E puede mejorar la capacidad de clasificación del modelo ex ante. Además, a diferencia de los resultados de investigaciones anteriores relacionadas en mercados emergentes, en este estudio, los modelos Logit superan a los modelos SVM. Por lo tanto, para futuras investigaciones, se deben investigar los modelos que aplican otros clasificadores de aprendizaje automático, como el Árbol de decisiones (DT) o la Red neuronal (NN)

Catalytic Reactions for Upgrading Bio-oils and Petroleum Fuels

The increasing consumption and phase-out of conventional fuels has derived the tremendous interest of our society in making uses of renewable energy resources such as biomass. In response to this interest, bio-oil produced from biomass feed stocks has been gradually making its contribution as a part of normal fuels. However, since the bio-oil is not stable due to its high oxygen content, upgrading is necessary to improve its performance. In parallel to the need for sustainable fuel sources, a huge desire in creating more environmentally friendly fuels is generated. For instance, lowering emission for conventional diesel and gasoline fuels has been considered one of the actions to reduce the negative impacts of fuel combustion on human health. From point of view of upgrading petroleum fuels, this could partially mean reduction in aromatic content in both diesel and gasoline. In the scope of this dissertation, the author will present two catalytic strategies to improve the performances of bio-oils and conventional diesel and gasoline fuels. Since the high oxygen content of bio-oils has limited its storage ability and lower its heating content, in some cases, removing oxygen or deoxygenating bio-oil molecules has been proposed as a recommended catalytic reaction. In the first part of the dissertation, the author will focus on the deoxygenation reaction of methyl esters and triglycerides, which can be derived from biomass feed stocks and contain the ester functional group (-COO-) relevant to bio-oil molecules. Hydrocarbons are the desired products from the deoxygenation reactions. The first step in optimizing the yield and selectivity of the hydrocarbons is to establish the reaction mechanisms with all possible reaction pathways leading to formation of hydrocarbons. In addition, the effects of various parameters on the deoxygenation reactions have been examined. The important parameters include pressure, temperature, hydrogen partial pressure, and reactor configuration. Certainly, one cannot exclude the important role of catalysts. The catalysts implemented in these reactions were supported noble-metal-based catalysts such as Pt and Pd. The variation of these parameters will be used in the reactions of several representative molecules such as methyl hexanoate, methyl octanoate, methyl dodecanone, and triacetin. A number of interesting findings on reaction mechanism, catalyst deactivation, and the role of active sites have been drawn from these studies. The second part of this work has touched on the upgrading reactions of aromatics in petroleum fuel. Hydrogenation of the aromatic rings followed by selective ring opening of the corresponding naphthenic compounds has been proposed as one of the strategies to improve the cetane number and other fuel properties. In this work, the ring opening reactions of various naphthenic compounds on different modified Iridium catalysts have been studied. The supported Iridium catalysts are not only active for ring opening reaction but also selective for certain positions of C-C cleavage when supports and additive modifications are applied. Although the two parts of this dissertation deal with different feed molecules, they all bring the common understandings on how to modify the reaction variables to optimize the selective production of hydrocarbon fuels

Selection and identification of thermophilic yeast strains in leachate from the organic waste heap in Phu Luong district, Thai Nguyen province, Vietnam

The study was carried out to isolate and select useful thermophilic yeast strains in the process of organic domestic waste treatment in Phu Luong - Thai Nguyen. Research results from 23 samples of rust have isolated 10 strains of yeast on YPG medium at 40 oC. Among them, 6 strains of yeast were selected with the ability to grow and develop in a wide temperature range from 20-45 oC. The results of identification combined with morphological, physiological, and biochemical characteristics of yeast strains showed that, out of 6 selected strains, there were 3 strains belonging to the genus Saccharomyces (Saccharomyces sp. TNY13.01, Saccharomyces sp. TNY22.01), Saccharomyces cerevisiae TNY13.09), 2 strains of the genus Candida (Candida sp. TNY23.01, Candida tropicalis TNY23.126) and 1 strain of the genus Papiliotrema (Papiliotrema laurentii TNY23.127). Among them, the identified strain Saccharomyces cerevisiae TNY13.09 has the ability to grow at 45, tolerates a wide pH range of 4.0– 8.5, has a positive catalase reaction, is capable of using a variety of carbon sources, and belongs to class I biosafety group. On that basis, Saccharomyces cerevisiae TNY13.09 has the potential to be further researched and applied as additional microbial inoculants to the organic waste heap

STUDY THE ANTICANCER MECHANISM OF THE PROMISSING COMPOUND 2B2D BY USING MICROARRAY TECHNIQUE

Being a modern technique with the ability of studying, discovering, probing and analyzing the  expression  of  thousands  genes,  even  the  whole  genome  in  the  only  one  experiment, microarray  proved  to  be  a  powerful  tool  for  cancer  research  especially  at  molecular  level. Employing  the  potential  anticancer  compound  1-(5,7-dimetoxy-2,2-dimetyl-2H-cromen-8-yl)-but-2-en-1-on  (2B2D  in  short) and LU-1,  the human  lung cancer cells as  research objects, we successfully  hybridized  the  cy3/5  incorporated  cDNA  with  Phalanx  HOV5  microarray.  The results  showed  742  genes  that  got  effected with  equal  or  over  two  folds  change  under  2B2D treatment.  Among  -  those,  386  genes  were  up-regulated  while  the  other  356  were  down-regulated. The Nuclear  factor  (erythroid-derived  2,  regulatory  factor X  domain  containing  1, fibroblast  growth  factor  receptor  3  (achondroplasia,  thanatophoric  dwarfism)  and  E2F transcription factor 8 genes were the most stimulated by our compound. The genes that named as Solute carrier  family 7  (cationic amino acid  transporter,  system) member 11,  kelch-like 24 and Hypothetical LOC344887 were the most down in action

Physical Model Test for Soft Soil With or Without Prefabricated Vertical Drain with Loading

The paper builds a physical model of testing in the laboratory with the parametric tempered glass box 0.5  0.5 1.2 m (length  width  depth) containing saturated clay to study the settlement and consolidation when loading increased gradually over time. The research covers herein to present the monitoring of settlement and pore water pressure, settlement calculation, numerical simulation using PLAXIS software V8.2 based on the results of soil physical and mechanical tests before and after loading in case of having or not prefabricated vertical drain (PVD). In case of no PVD, the calculation and numerical simulation using the soil parameters before loading have the differential settlement from the monitoring data, approximately 3.86 mm (10.45%), 0.41 mm (1.11%) respectively. Meanwhile, the deviation in the case using data after loading is about 2.29 mm (6.20%), 0.21 mm (0.56%) respectively. In case of PVD, the calculation and numerical simulation with the testing result of before loading deviation from the settlement monitoring by subsidence meter is 2.91 mm (7.88%), 44.42 mm (120.28%), calculation and simulation with the testing result of after loading deviation is 0.80 mm (2.17%), 1.26 mm (3.41%). In the case of having PVD, the difference in calculation, subsidence observation, and numerical simulation between the mechanical properties before and after loading is significant, when using the mechanical data after loading then the results are quite close to the subsidence of observation and simulation rather than before loading.