Search results for: nitrogen content and stock

Authors: Qingqing Zhao, Junhong Bai

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To investigate the effects of salinity on dynamics of soil carbon and nitrogen contents and stocks, soil samples were collected at a depth of 30 cm at four sampling sites (Sites B, T, S and P) along a salinity gradient in a drained coastal wetland, the Yellow River Delta, China. The salinity of these four sites ranked in the order: B (8.68±4.25 ms/cm) > T (5.89±3.17 ms/cm) > S (3.19±1.01 ms/cm) > P (2.26±0.39 ms/cm). Soil total carbon (TC), soil organic carbon (SOC), soil microbial biomass carbon (MBC), soil total nitrogen (TC) and soil microbial biomass carbon (MBC) were measured. Based on these data, soil organic carbon density (SOCD), soil microbial biomass carbon density (MBCD), soil nitrogen density (TCD) and soil microbial biomass nitrogen density (MBND) were calculated at four sites. The results showed that the mean concentrations of TC, SOC, MBC, TN and MBN showed a general deceasing tendency with increasing salinities in the top 30 cm of soils. The values of SOCD, MBCD, TND and MBND exhibited similar tendency along the salinity gradient. As for profile distribution pattern, The C/N ratios ranged from 8.28 to 56. 51. Higher C/N ratios were found in samples with high salinity. Correlation analysis showed that the concentrations of TC, SOC and MBC at four sampling sites were significantly negatively correlated with salinity (P < 0.01 or P < 0.05), indicating that salinity could inhibit soil carbon accumulation. However, no significant relationship was observed between TN, MBN and salinity (P > 0.05).

Keywords: carbon content and stock, nitrogen content and stock, salinity, coastal wetland

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Authors: Alise Senberga, Laila Dubova, Liene Strauta, Ina Alsina, Ieva Erdberga

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Legume symbiotic relationship with nitrogen fixating bacteria Rhizobim leguminosarum is an important factor used to improve the productivity of legumes, due to the fact that rhizobia can supply plant with the necessary amount of nitrogen. R. leguminosarum strains have shown different activity in fixing nitrogen. Depending on the chosen R. leguminosarum strain, host plant biochemical content can be altered. In this study we focused particularly on the changes in protein content in beans (using two different varieties) and peas (five different varieties) due to the use of several different R. leguminosarum strains (four strains for both beans and peas). Overall, the protein content increase was observed after seed inoculation with R. leguminosarum. Strain and plant cultivar interaction specification was observed. The effect of R. leguminosarum inoculation on the content of protein was dependent on the R. leguminosarum strain used. Plant cultivar also appeared to have a decisive role in protein content formation with the help of R. leguminosaru.

Keywords: legumes, protein content, rhizobia strains, soil

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Authors: Saeed Ghali, Hoda El-Faramawy, Mamdouh Eissa, Michael Mishreky

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Scale-resistant austenitic stainless steel, X45CrNiW 18-9, has been developed, and modified steels produced through partial and total nickel replacement by nitrogen. These modified steels were produced in a 10 kg induction furnace under different nitrogen pressures and were cast into ingots. The produced modified stainless steels were forged, followed by air cooling. The phases of modified stainless steels have been investigated using the Schaeffler diagram, dilatometer, and microstructure observations. Both partial and total replacement of nickel using 0.33-0.50% nitrogen are effective in producing fully austenitic stainless steels. The nitrogen contents were determined and compared with those calculated using the Institute of Metal Science (IMS) equation. The results showed great deviations between the actual nitrogen contents and predicted values through IMS equation. So, an equation has been derived based on chemical composition, pressure, and temperature at 1600oC. [N%] = 0.0078 + 0.0406*X, where X is a function of chemical composition and nitrogen pressure. The derived equation has been used to calculate the nitrogen content of different steels using published data. The results reveal the difficulty of deriving a general equation for the prediction of nitrogen content covering different steel compositions. So, it is necessary to use a narrow composition range.

Keywords: solubility, nitrogen, stainless steel, Schaeffler

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Authors: Mohamed M. Alsull

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In the present study, two microalgae species “Nannochloropsis sp. and Tetraselmis sp.” isolated from Penang National Park coastal waters, Malaysia; were cultivated under combined various laboratory conditions “salinity, light, nitrogen limitation and starvation”. Growth rate, dry weight, chlorophyll a content, total lipid and protein contents, were estimated at mid exponential growth phase. Both Nannochloropsis sp. and Tetraselmis sp. showed remarkable decrease in growth rate, chlorophyll a content and protein content companied with increase in lipid content under nitrogen limitation and starvation conditions. Maintaining Nannochloropsis sp. under salinity 15‰ caused only significant decrease in total protein content; while Tetraselmis sp. grown at the same salinity caused decrease in the growth rate, chlorophyll a, dry weight and total protein content only when nitrogen was available.

Keywords: biochemical composition, light, microalgae, nitrogen limitation, salinity

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Authors: F. Z. Aliyat, B. Ben Messaoud, L. Nassiri, E. Bouiamrine, J. Ibijbijen

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The present study aims to assess the biological nitrogen fixation in the soybean tested in different Moroccan soils combined with the rhizobial inoculation. These effects were evaluated by the plant growth mainly by the aerial biomass production, total nitrogen content and the proportion of the nitrogen fixed. This assessment clearly shows that the inoculation with bacteria increases the growth of soybean. Five different soils and a control (peat) were used. The rhizobial inoculation was performed by applying the peat that contained a mixture of 2 strains Sinorhizobium fredii HH103 and Bradyrhizobium. The biomass, the total nitrogen content and the proportion of nitrogen fixed were evaluated under different treatments. The essay was realized at the greenhouse the Faculty of Sciences, Moulay Ismail University. The soybean has shown a great response for the parameters assessed. Moreover, the best response was reported by the inoculated plants compared to non- inoculated and to the absolute control. Finally, good production and the best biological nitrogen fixation present an important ecological technology to improve the sustainable production of soybean and to ensure the increase of the fertility of soils.

Keywords: biological nitrogen fixation, inoculation, rhizobium, soybean

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Authors: M. Alsull

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In this study, Tetraselmis sp. and Chlorella sp. isolated from Penang National Park coastal waters, Malaysia, and cultivated under combined various laboratory conditions (temperature, light and nitrogen limitation and starvation). Growth rate, dry weight, chlorophyll a content, total lipids content and total carbohydrates content were estimated at mid-exponential growth phase. Tetraselmis sp. and Chlorella sp. showed remarkably decrease in growth rate, chlorophyll a content and dry weight when maintained under nitrogen limitation and starvation conditions, as well as when grown under 12:12 h light, dark regime conditions. Chlorella sp. showed ability to counter the fluctuation in temperature with no significant effects on the measured parameters; in contrast, Tetraselmis sp. showed a decrease in growth rate, chlorophyll a content and dry weight when grown under 15±1˚C temperature. Cultures maintained under nitrogen full concentration, and 24 h light regime showed decrease in total lipids content, compared with 12:12 h light, dark cycle regime, in the two tested species.

Keywords: microalgae, biochemical composition, temperature, light, nitrogen limitation

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Authors: Mostafa Heidari

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Nitrogen fertilization has played a significant role in increasing crop yield, and solving problems of hunger and malnutrition worldwide. However, excessive of heavy metals such as arsenic can interfere on growth and reduced grain yield. In order to investigate the effects of different concentrations of arsenic and nitrogen fertilizer on photosynthetic pigments and antioxidant enzyme activities in safflower (cv. Goldasht), a factorial plot experiment as randomized complete block design with three replication was conducted in university of Zabol. Arsenic treatment included: A1= control or 0, A2=30, A3=60 and A4=90 mg. kg-1 soil from the Na2HASO4 source and three nitrogen levels including W1=75, W2=150 and W3=225 kg.ha-1 from urea source. Results showed that, arsenic had a significant effect on the activity of antioxidant enzymes. By increasing arsenic levels from A1 to A4, the activity of ascorbate peroxidase (APX) and gayacol peroxidase (GPX) increased and catalase (CAT) was decreased. In this study, arsenic had no significant on chlorophyll a, b and cartoneid content. Nitrogen and interaction between arsenic and nitrogen treatment, except APX, had significant effect on CAT and GPX. The highest GPX activity was obtained at A4N3 treatment. Nitrogen increased the content of chlorophyll a, b and cartoneid.

Keywords: arsenic, physiological parameters, oxidative enzymes, nitrogen

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Authors: Tabassum Riaz

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This study provides a complete examination of the stock prices behavior in the Karachi stock exchange. It examines that whether Karachi stock exchange can be described as mean reversion or not. For this purpose daily, weekly and monthly index data from Karachi stock exchange ranging from period July 1, 1997 to July 2, 2011 was taken. After employing the Multiple variance ratio and unit root tests it is concluded that stock market follow mean reversion behavior and hence have reverting trend which opens the door for the active invest management. Thus technical analysis may be help to identify the potential areas for value creation.

Keywords: mean reversion, random walk, technical analysis, Karachi stock exchange

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Authors: Chih-Hsiang Chang, Chia-Ching Tsai

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The aim of this study is to examine the stock price effect of the enterprises being classified as socially responsible. We explore the stock price response to the announcement that an enterprise is selected for the Taiwan Corporate Sustainability Awards. Empirical results indicate that the announcements of the Taiwan Corporate Sustainability Awards provide useful informational content to stock market. We find the evidence of insignificantly positive short-term and significantly positive long-term price reaction to the enterprises being classified as socially responsible. This study concludes that investors in the Taiwan stock market tend to view an enterprise being selected for the Taiwan Corporate Sustainability Awards as one with superior quality and long-term price potential.

Keywords: corporate social responsibility, stock price effect, Taiwan stock market, investments

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Authors: Bita Bayatsarmadi, Shi-Zhang Qiao

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The development of ordered mesoporous carbon materials with controllable structures and improved physicochemical properties by doping heteroatoms such as nitrogen into the carbon framework has attracted a lot of attention, especially in relation to energy storage and conversion. Herein, a series of Nitrogen-doped mesoporous carbon spheres (NMC) was synthesized via a facile dual soft-templating procedure by tuning the nitrogen content and carbonization temperature. Various physical and (electro) chemical properties of the NMCs have been comprehensively investigated to pave the way for feasible design of nitrogen-containing porous carbon materials. The optimized sample showed a favorable electrocatalytic activity as evidenced by high kinetic current and positive onset potential for oxygen reduction reaction (ORR) due to its large surface area, high pore volume, good conductivity and high nitrogen content, which make it as a highly efficient ORR metal-free catalyst in alkaline solutions.

Keywords: porous carbon, N-doping, oxygen reduction reaction, soft-template

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Authors: Wenjing Ding, Weiwei Shan, Zijuan, Wang, Chao He

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Liquid spray heat exchanger is the critical equipment of temperature regulating system by gaseous nitrogen which realizes the environment temperature in the range of -180 ℃~+180 ℃. Liquid nitrogen is atomized into smaller liquid drops through liquid nitrogen sprayer and then contacts with gaseous nitrogen to be cooled. By adjusting the pressure of liquid nitrogen and gaseous nitrogen, the flowrate of liquid nitrogen is changed to realize the required outlet temperature of heat exchanger. The temperature accuracy of shrouds is ±1 ℃. Liquid nitrogen spray heat exchanger is simulated by CATIA, and the numerical simulation is performed by FLUENT. The comparison between the tests and numerical simulation is conducted. Moreover, the results help to improve the design of liquid nitrogen spray heat exchanger.

Keywords: liquid nitrogen spray, temperature regulating system, heat exchanger, numerical simulation

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Authors: Abdelrahman Zkria, Tsuyoshi Yoshitake

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Diamond is one of the most interesting semiconducting carbon materials owing to its unique physical and chemical properties, yet its application in electronic devices is limited due to the difficulty of realizing n-type conduction by nitrogen doping. In contrast Ultrananocrystalline diamond with diamond grains of about 3–5 nm in diameter have attracted much attention for device-oriented applications because they may enable the realization of n-type doping with nitrogen. In this study, nitrogen-doped Ultra-Nanocrystalline diamond films were prepared by coaxial arc plasma deposition (CAPD) method, the nitrogen content was estimated by X-ray photoemission spectroscopy (XPS). The electrical conductivity increased with increasing nitrogen contents. Heterojunction diodes with p-type Si were fabricated and evaluated based on current–voltage (I–V) and capacitance–voltage (C–V) characteristics measured in dark at room temperature.

Keywords: heterojunction diodes, hopping conduction mechanism, nitrogen-doping, ultra-nanocrystalline diamond

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Authors: Pragnyashree Mishra, Shradhanjali Mohapatra

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The present investigation is carried out to know the effect of foliar feeding of nitrogen and gibberellic acid on vegetative growth, flowering behaviour and yield of calendula variety ‘Golden Emporer’. The experiment was laid out in RBD in rabi season of 2013-14. There are 16 treatments are taken at different level such as nitrogen (at 0%,1%,2%,3%) and GA3 (at 50 ppm,100ppm,150 ppm). Among them maximum height at bud initiation stage was obtained at 3% nitrogen (27.00 cm) and at 150 ppm GA3 (26.5 cm), fist flowering was obtained at 3% nitrogen(60.00 days) and at 150 ppm GA3 (63.75 days), maximum flower stalk length was obtained at 3% nitrogen(3.50 cm) and at 150 ppm GA3 (5.42 cm),maximum duration of flowering was obtained at 3% nitrogen(46.00 days) and at 150 ppm GA3 (46.50days), maximum number of flower was obtained at 3% nitrogen (89.00per plant) and at 150 ppm GA3 (83.50 per plant), maximum flower weight was obtained at 3% nitrogen(1.25 gm per flower) and at 150 ppm GA3 (1.50 gm per flower), maximum yield was was obtained at 3% nitrogen (110.00 gm per plant) and at 150 ppm GA3 (105.00gm per plant) and minimum of all character was obtained when 0% nitrogen0 ppm GA3. All interaction between nitrogen and GA3 was found in significant except the yield .

Keywords: calendula, golden emporer, GA3, nitrogen and gibberellic acid

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Authors: Gultekin Gurcay

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In this paper, effects and responses of stock were analyzed. This analysis was done periodically. The dimensions of the financial crisis impact on the stock market were investigated by GARCH model. In this context, S&P 500 stock market is modeled with DAX, NIKKEI and BIST100. In this way, The effects of the changing in S&P 500 stock market were examined on European and Asian stock markets. Conditional variance coefficient will be calculated through garch model. The scope of the crisis period, the conditional covariance coefficient will be analyzed comparatively.

Keywords: conditional variance coefficient, financial crisis, garch model, stock market

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Alicja Sułek, Grażyna Cacak-Pietrzak, Marta Wyzińska, Anna Nieróbca

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In 2013/2014 and 2014/2015, a field experiment was conducted in two locations: Osiny and Wielichowo (Poland). The two-factor experiment was based on the method of randomized subblocks, in three replications. The first factor (A) was dose of nitrogen fertilization (two levels). The second factor (B) was nine winter wheat cultivars. It was found that winter wheat cultivars exhibited different reactions to higher nitrogen fertilization depending on the years and localities. Only KWS Dacanto cultivar under all growing conditions showed a significant increase in grain yield after the application of a higher level of nitrogen fertilization. The increase in nitrogen fertilization influenced the increase in gluten proteins content in wheat grain, but these changes were statistically significant only in the first year of the study. The quality of gluten does not depend on nitrogen fertilization. The quality of wheat grain depends on cultivars.

Keywords: fertilization, grain quality, winter wheat, yield

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Authors: Jakub Elbl, Lukáš Plošek, Antonín Kintl, Jaroslav Hynšt, Soňa Javoreková, Jaroslav Záhora, Libor Kalhotka, Olga Urbánková, Ivana Charousová

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This work presents the first results from the long-term laboratory experiment dealing with impact of drought on soil properties. Three groups of the treatment (A, B and C) with different regime of irrigation were prepared. The soil water content was maintained at 70 % of soil water holding capacity in group A, at 40 % in group B. In group C, soil water regime was maintained in the range of wilting point. Each group of the experiment was divided into three variants (A1 = B1, C1; A2 = B2, C2 etc.) with three repetitions: Variants A1 (B1, C1) were controls without addition of another fertilizer. Variants A2 (B2, C2) were fertilized with mineral nitrogen fertilizer DAM 390 (0.140 Mg of N per ha) and variants A3 (B3, C3) contained 45 g of Cp per a pot. The significant differences (ANOVA, P<0.05) in the leaching of mineral nitrogen and values of saturated hydraulic conductivity (Ksat) were found. The highest values of Ksat were found in variants (within each group) with addition of compost (A3, B3, C3). Conversely, the lowest values of Ksat were found in variants with addition of mineral nitrogen. Low values of Ksat indicate an increased level of hydrophobicity in individual groups of the experiment. Moreover, all variants with compost addition showed lower amount of mineral nitrogen leaching and high level of microbial activity than variants without. This decrease of mineral nitrogen leaching was about 200 % in comparison with the control variant and about 300 % with variant, where mineral nitrogen was added. Based on these results, we can conclude that changes of soil water content directly have impact on microbial activity, soil hydrophobicity and loss of mineral nitrogen from the soil.

Keywords: drought, microbial activity, mineral nitrogen, soil hydrophobicity

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Authors: Yogita Mishra, Arijit Roy, Dhruval Bhavsar

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The study estimates the nitrogen concentration in selected vegetation community’s i.e. chir pine (pinusroxburghii) by using hyperspectral satellite data and also identified the appropriate spectral bands and nitrogen indices. The Short Wave InfraRed reflectance spectrum at 1790 nm and 1680 nm shows the maximum possible absorption by nitrogen in selected species. Among the nitrogen indices, log normalized nitrogen index performed positively and negatively too. The strong positive correlation is taken out from 1510 nm and 760 nm for the pinusroxburghii for leaf nitrogen concentration and leaf nitrogen mass while using NDNI. The regression value of R² developed by using linear equation achieved maximum at 0.7525 for the analysis of satellite image data and R² is maximum at 0.547 for ground truth data for pinusroxburghii respectively.

Keywords: hyperspectral, NDNI, nitrogen concentration, regression value

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Authors: Sakura Yoshii, Masakazu Abe, Akihiro Iijima

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Nitrogen saturation has become one of the serious issues in the field of forest environment. The watershed protection forests located in the downwind hinterland of Tokyo Metropolitan Area are believed to be facing nitrogen saturation. In this study, we carefully focus on the balance of nitrogen between load and runoff. Annual nitrogen load via atmospheric deposition was estimated to 461.1 t-N/year in the upper reaches of the Kanna River. Annual nitrogen runoff to the forested headwater stream of the Kanna River was determined to 184.9 t-N/year, corresponding to 40.1% of the total nitrogen load. Clear seasonal change in NO3-N concentration was still observed. Therefore, watershed protection forest of the Kanna River is most likely to be in Stage-1 on the status of nitrogen saturation.

Keywords: atmospheric deposition, nitrogen accumulation, denitrification, forest ecosystems

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Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

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Authors: Tijjani Bashir Musa

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The recent global crisis which suddenly results to Nigerian stock market crash revealed some peculiarities of Nigerian firms. Some firms in Nigeria are performing but their stock prices are not increasing while some firms are at the brink of collapse but their stock prices are increasing. Thus, this study examines the relationship between firm performance and stock price in Nigeria. The study covered the period of 2005 to 2009. This period is the period of stock boom and also marked the period of stock market crash as a result of global financial meltdown. The study is a panel study. A total of 140 firms were sampled from 216 firms listed on the Nigerian Stock Exchange (NSE). Data were collected from secondary source. These data were divided into four strata comprising the most performing stock, the least performing stock, most performing firms and the least performing firms. Each stratum contains 35 firms with characteristic of most performing stock, most performing firms, least performing stock and least performing firms. Multiple linear regression models were used to analyse the data while statistical/econometrics package of Stata 11.0 version was used to run the data. The study found that, relationship exists between selected firm performance parameters (operating efficiency, firm profit, earning per share and working capital) and stock price. As such firm performance gave sufficient information or has predictive power on stock prices movements in Nigeria for all the years under study.. The study recommends among others that Managers of firms in Nigeria should formulate policies and exert effort geared towards improving firm performance that will enhance stock prices movements.

Keywords: firm, Nigeria, performance, stock price

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Authors: Eti Mizrahi, Gizem İntepe

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The geographical location of Turkey that stretches from Asia to Europe and Russia to Africa makes it an important logistics hub in the region. Although logistics is a developing sector in Turkey, the stock market representation is still low with only two companies listed in Turkey’s stock exchange since 2010. In this paper, we use the daily values of these two listed stocks as a benchmark for the logistics sector. After modeling logistics stock prices, an empirical examination is conducted between the existing logistics indices and these stock prices. The paper investigates whether the measures of logistics stocks are correlated with newly available logistics indices. It also shows the reflection of the economic activity in the logistics sector on the stock exchange market. The results presented in this paper are the first analysis of the behavior of logistics indices and logistics stock prices for Turkey.

Keywords: forecasting, logistic stock exchange, modeling, Africa

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Authors: Lukáš Plošek, Jaroslav Hynšt, Jaroslav Záhora, Jakub Elbl, Antonín Kintl, Ivana Charousová, Silvia Kovácsová

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Compost can influence soil fertility and plant health. At the same time compost can play an important role in the nitrogen cycle and it can influence leaching of mineral nitrogen from soil to underground water. This paper deals with the influence of compost addition and mineral nitrogen fertilizer on leaching of mineral nitrogen, nitrogen availability in microbial biomass and plant biomass production in the lysimetric experiment. Twenty-one lysimeters were filed with topsoil and subsoil collected in the area of protection zone of underground source of drinking water - Březová nad Svitavou. The highest leaching of mineral nitrogen was detected in the variant fertilized only mineral nitrogen fertilizer (624.58 mg m-2), the lowest leaching was recorded in the variant with high addition of compost (315.51 mg m-2). On the other hand, losses of mineral nitrogen are not in connection with the losses of available form of nitrogen in microbial biomass. Because loss of mineral nitrogen was detected in variant with the least change in the availability of N in microbial biomass. The leaching of mineral nitrogen, yields as well as the results concerning nitrogen availability from the first year of long term experiment suggest that compost can positive influence the leaching of nitrogen into underground water.

Keywords: nitrogen, compost, biomass production, lysimeter

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Authors: Vikas Baliram Kalyankar

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Study of ecology is important as it plays role in development of environment engineering. With the advent of technologies the study of ecosystem structure and changes in it are remaining unnoticed. The ecological succession is the sequential replacement of plant species following changes in the environment. The present study depicts the primary ecological succession in an area leveled up to the height of five feet with no signs of plant life on it. The five quadrates of 1 meter square size were observed during the study period of six months. Rain water being the only source of water in the area increased its ecological importance. The primary successor was non- leguminous plant Balonites roxburgii during the peak drought periods in the region of the summer 2013-14. The increased nitrogen content of soil after the plant implied its role in atmospheric nitrogen fixation.

Keywords: succession, Balonites roxburgii, non-leguminous plant, ecology

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Authors: Mohammed S. Aly, Abou-Zeid N. El-Shahat, Nabila Y. Naguib, Huussie A. Said-Al Ahl, Atef M. Zakaria, Mohamed A. Abou Dahab

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This study was conducted during two successive seasons of 2000/2001 and 2001/2002 to evaluate the response of Anethum graveolens L. plants to nitrogen fertilizer with or without bio-fertilizer on fruits yield, total flavonoids and carbohydrates content, essential oil yield and constituents. Results cleared that the treatment of 60 Kg N/feddan without and with bio-fertilizer gave the highest umbels number per plant through the two seasons and these increments were significant in comparison with control plants. Meanwhile, fruits weight (g/plant) showed significant increase with the treatments of nitrogen fertilizers alone and combined with bio-fertilizers compared with control plants in the first and second season. Maximum increments were resulted with the previous treatment (60 Kg N/fed). Fruits yield (Kg/fed) revealed the same trend of fruits weight (g/plant). Total flavonoids contents were significantly increased with all of used treatments. Maximum increase was noticed with bio-fertilizers combined with 60 Kg N/fed during two seasons. Total carbohydrate contents showed significant increase with applied nitrogen fertilizers treatments as alone, meanwhile total carbohydrate contents were increased non-significantly with the other used treatments during the two seasons in comparison with control plants content. The treatment of bio-fertilizer and in most of nitrogen fertilizer levels significantly increased essential oil percentage, content and yield. The treatment of 60 Kg N/fed with or without bio-fertilizer gave the best values. All identified compounds were observed in the essential oil of all treatments. The major compounds were limonene, carvone and dillapiole. The most effective fertilization on limonene content was 40 Kg N/fed and/or bio-fertilizers. Meanwhile 20 Kg N/fed with or without bio-fertilizers increased carvone, but most of fertilization treatments except those of bio-fertlizers and 40 Kg N/fed increased dillapiole content.

Keywords: carbohydrates, dill, essential oil, fertilizer, flavonoids

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Authors: Ying Guo, Miaochan Li, David Yang, Xiao-Yan Li

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This paper examines the relevance of accounting information to stock prices at different periods using manufacturing companies listed in China’s Growth Enterprise Market (GEM). We find that both the average stock price at fiscal year-end and the average stock price one month after fiscal year-end are more relevant to the accounting information than the closing stock price four months after fiscal year-end. This implies that Chinese stock markets react before the public disclosure of accounting information, which may be due to information leak before official announcements. Our findings confirm that accounting information is relevant to stock prices for Chinese listed manufacturing companies, which is a critical question to answer for investors who have interest in Chinese companies.

Keywords: accounting information, response time, value relevance, stock price

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: Helena Dvořáčková, Jakub Elbl, Irina Mikajlo, Antonín Kintl, Jaroslav Hynšt, Olga Urbánková, Jaroslav Záhora

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Application of biochar to arable soils represents a new approach to restore soil health and quality. Many studies reported the positive effect of biochar application on soil fertility and development of soil microbial community. Moreover biochar may affect the soil water retention, but this effect has not been sufficiently described yet. Therefore this study deals with the influence of biochar application on: microbial activities in soil, availability of mineral nitrogen in soil for microorganisms, mineral nitrogen retention and plant production. To demonstrate the effect of biochar addition on the above parameters, the pot experiment was realized. As a model crop, Lactuca sativa L. was used and cultivated from December 10th 2014 till March 22th 2015 in climate chamber in thoroughly homogenized arable soil with and without addition of biochar. Five variants of experiment (V1–V5) with different regime of irrigation were prepared. Variants V1–V2 were fertilized by mineral nitrogen, V3–V4 by biochar and V5 was a control. The significant differences were found only in plant production and mineral nitrogen retention. The highest content of mineral nitrogen in soil was detected in V1 and V2, about 250 % in comparison with the other variants. The positive effect of biochar application on soil fertility, mineral nitrogen availability was not found. On the other hand results of plant production indicate the possible positive effect of biochar application on soil water retention.

Keywords: arable soil, biochar, drought, mineral nitrogen

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Authors: Jyoti Singh, Swati Dubey, Mukta Singh, R. P. Singh

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The freshwater microalgae Chlorella sp. is alluring considerable interest as a source for biofuel production due to its fast growth rate and high lipid content. Under nitrogen limited conditions, they can accumulate significant amounts of lipids. Thus, it is important to gain insight into the molecular mechanism of their lipid metabolism. In this study under nitrogen limited conditions, regular pattern of growth characteristics lipid accumulation and gene expression analysis of key regulatory genes of lipid biosynthetic pathway were carried out in microalgae Chlorella sp 3. Our results indicated that under nitrogen limited conditions there is a significant increase in the lipid content and lipid productivity, achieving 44.21±2.64 % and 39.34±0.66 mg/l/d at the end of the cultivation, respectively. Time-course transcript patterns of lipid biosynthesis genes i.e. acetyl coA carboxylase (accD) and diacylglycerol acyltransferase (dgat) showed that during late log phase of microalgae Chlorella sp.3 both the genes were significantly up regulated as compared to early log phase. Moreover, the transcript level of the dgat gene is two-fold higher than the accD gene. The results suggested that both the genes responded sensitively to the nitrogen limited conditions during the late log stage, which proposed their close relevance to lipid biosynthesis. Further, this transcriptome data will be useful for engineering microalgae species by targeting these genes for genetic modification to improve microalgal biofuel quality and production.

Keywords: biofuel, gene, lipid, microalgae

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Authors: Carol Anne Hargreaves

Abstract:

A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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