Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

A low-cost intelligent gas sensing device for military applications

The field of electronic noses and gas sensing has been developing rapidly since the introduction of the silicon based sensors. There are numerous systems that can detect and indicate the level of a specific gas. We introduce here a system that is low power, small and cheap enough to be used in mobile robotic platforms while still being accurate and reliable enough for confident use. The design is based around a small circuit board mounted in a plastic case with holes to allow the sensors to protrude through the top and allow the natural flow of gas evenly across them. The main control board consists of a microcontroller PCB with surface mount components for low cost and power consumption. The firmware of the device is based on an algorithm that uses an Artificial Neural Network (ANN) which receives input from an array of gas sensors. The various sensors feeding the ANN allow the microcontroller to determine the gas type and quantity. The Testing of the device involves the training of the ANN with a number of different target gases to determine the weightings for the ANN. Accuracy and reliability of the ANN is validated through testing in a specific gas filled environment.

Application of an adaptive neural network with symbolic rule extraction to fault detection and diagnosis in a power generation plant

Artificial neural networks have a good potential to be employed for fault diagnosis and condition monitoring problems in complex processes. In this paper, the applicability of the fuzzy ARTMAP (FAM) neural network as an intelligent learning system for fault detection and diagnosis in a power generation plant is described. The process under scrutiny is the circulating water (CW) system, with specific attention to the conditions of heat transfer and tube blockage in the CW system. A series of experiments has been conducted systematically to investigate the effectiveness of FAM in fault detection and diagnosis tasks. In addition, a set of domain rules has been extracted from the trained FAM network so that its predictions can be explained and justified. The outcomes demonstrate the benefits of employing FAM as an intelligent fault detection and diagnosis tool with an explanatory capability for monitoring and diagnosing complex processes in power generation plants.

Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of amaryllidaceae

Background During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown.
Results We produced a phylogenetic hypothesis for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae) based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated with phylogeny and found evidence for a significant phylogenetic signal in these traits, although the effect is not strong.
Conclusions Several genera are non-monophyletic emphasizing the importance of using phylogeny for interpretation of character distribution. Alkaloid diversity and in vitro inhibition of acetylcholinesterase (AChE) and binding to the serotonin reuptake transporter (SERT) are significantly correlated with phylogeny. This has implications for the use of phylogenies to interpret chemical evolution and biosynthetic pathways, to select candidate taxa for lead discovery, and to make recommendations for policies regarding traditional use and conservation priorities.

Characteristics and applications of energy storage system to power network - A review

Maintaining reliability and stability of a power systems in transmission and distribution level becomes a big challenge in present scenario. Grid operators are always responsible to maintain equilibrium between available power generation and demand of end users. Maintaining grid balance is a bigger issue, in case of any unexpected generation shortage or grid disturbance or integration of any renewable energy sources like wind and solar power in the energy mix. In order to compensate such imbalance and to facilitate more renewable energy sources with the grid, energy storage system (ESS) started to be playing an important role with the advancement of the state of the art technology. ESS can also help to get reduction in greenhouse gas (GHG) emission by means of integrating more renewable energy sources to the grid. There are various types of Energy Storage (ES) technologies which are being used in power systems network from large scale (above 50MW) to small scale (up to 100KW). Based on the characteristics, each storage technology has their own merits and demerits. This paper carried out extensive review study and verifies merits and demerits of each storage technology and identifies the suitable technology for the future. This paper also has conducted feasibility study with the aid of E-SelectTM tool for various ES technologies in applications point of view at different grid locations. This review study helps to evaluate feasible ES technology for a particular electrical application and also helps to develop smart hybrid storage system for grid applications in efficient way.

The potential for indirect effects between co-flowering plants via shared pollinators depends on resource abundance, accessibility and relatedness

Co-flowering plant species commonly share flower visitors, and thus have the potential to influence each other's pollination. In this study we analysed 750 quantitative plant-pollinator networks from 28 studies representing diverse biomes worldwide. We show that the potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible. The potential indirect influence was also stronger between phylogenetically closer plant species and was independent of plant geographic origin (native vs. non-native). The positive effect of nectar sugar content and phylogenetic proximity was much more accentuated for bees than for other groups. Consequently, the impact of these factors depends on the pollination mode of plants, e.g. bee or fly pollinated. Our findings may help predict which plant species have the greatest importance in the functioning of plant-pollination networks.

Energy expenditure in relation to flight speed: what is the power of mass loss rate estimates?

The relationship between mass loss rate and chemical power in flying birds is analysed with regard to water and heat balance. Two models are presented: the first model is applicable to situations where heat loads are moderate. i.e. when heat balance can be achieved by regulating non-evaporative heat loss, and evaporative water loss is minimised. The second model is applicable when heat loads are high, non-evaporative heat loss is maximised. and heat balance has to be achieved by regulating evaporative heat loss. The rates of mass loss of two Thrush Nightingales Luscinia luscinia and one Teal Anas crecca were measured at various flight speeds in a wind tunnel. Estimates of metabolic water production indicate that the Thrush Nightingales did not dehydrate during experimental flights. Probably, the Thrush Nightingales maintained heat balance without actively increasing evaporative cooling. The Teal, however, most likely had to resort to evaporative cooling, although it may not have dehydrated. Chemical power was estimated from our mass loss rate data using the minimum evaporation model for the Thrush Nightingales and the evaporative heat regulation model for the Teal. For both Thrush Nightingales and the Teal, the chemical power calculated from our mass loss rate data showed a greater change with speed (more 'U-shaped' curve) than the theoretically predicted chemical power curves based on aerodynamic theory. The minimum power speeds calculated from our data differed little from theoretical predictions but maximum range speeds were drastically different. Mass loss rate could potentially be used to estimate chemical power in flying birds under laboratory conditions where temperature and humidity are controlled. However, the assumptions made in the models and the model predictions need further testing.

Metabolite profiling reveals distinct changes in carbon and nitrogen metabolism in phosphate-deficient barley plants (Hordeum vulgare L.)

Plants modify metabolic processes for adaptation to low phosphate (P) conditions. Whilst transcriptomic analyses show that P deficiency changes hundreds of genes related to various metabolic processes, there is limited information available for global metabolite changes of P-deficient plants, especially for cereals. As changes in metabolites are the ultimate ‘readout’ of changes in gene expression, we profiled polar metabolites from both shoots and roots of P-deficient barley (Hordeum vulgare) using gas chromatography–mass spectrometry (GC-MS). The results showed that mildly P-deficient plants accumulated di- and trisaccharides (sucrose, maltose, raffinose and 6-kestose), especially in shoots. Severe P deficiency increased the levels of metabolites related to ammonium metabolism in addition to di- and trisaccharides, but reduced the levels of phosphorylated intermediates (glucose-6-P, fructose-6-P, inositol-1-P and glycerol-3-P) and organic acids (α-ketoglutarate, succinate, fumarate and malate). The results revealed that P-deficient plants modify carbohydrate metabolism initially to reduce P consumption, and salvage P from small P-containing metabolites when P deficiency is severe, which consequently reduced levels of organic acids in the tricarboxylic acid (TCA) cycle. The extent of the effect of severe P deficiency on ammonium metabolism was also revealed by liquid chromatography–mass spectrometry (LC-MS) quantitative analysis of free amino acids. A sharp increase in the concentrations of glutamine and asparagine was observed in both shoots and roots of severely P-deficient plants. Based on these data, a strategy for improving the ability of cereals to adapt to low P environments is proposed that involves alteration in partitioning of carbohydrates into organic acids and amino acids to enable more efficient utilization of carbon in P-deficient plants.

Metabolic power method underestimates energy expenditure in field sport movements using a GPS tracking system

The purpose of this study was to assess the validity of a GPS tracking system to estimate energy expenditure (EE) during exercise and field sport locomotor movements. Twenty-seven participants each completed one 90 minute exercise session on an outdoor synthetic futsal pitch. During the exercise session participants wore a 5 Hz GPS unit interpolated to 15 Hz (SPI HPU, GPSports Pty Ltd, Australia) and a portable gas analyser (Metamax® 3B, Cortex Pty Ltd, Germany) which acted as the criterion measure of EE. The exercise session was comprised of alternating five minute exercise bouts of randomised walking, jogging, running or a field sport circuit (x3) followed by 10 minutes of recovery. One-way ANOVA showed significant (p<0.01) and very large underestimations between GPS metabolic power derived EE and VO2 derived EE for all field sport circuits (% difference ≈ -44%). No differences in EE were observed for the jog (7.8%) and run (4.8%) while very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90 minute session was significantly lower (p<0.01) than the VO2 EE, resulting in a moderate underestimation overall (-19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however is able to provide a reasonably accurate estimation of EE during continuous jogging and running.

Allergic asthma exhaled breath metabolome: a challenge for comprehensive two-dimensional gas chromatography

Allergic asthma represents an important public health issue, most common in the paediatric population, characterized by airway inflammation that may lead to changes in volatiles secreted via the lungs. Thus, exhaled breath has potential to be a matrix with relevant metabolomic information to characterize this disease. Progress in biochemistry, health sciences and related areas depends on instrumental advances, and a high throughput and sensitive equipment such as comprehensive two-dimensional gas chromatography–time of flight mass spectrometry (GC × GC–ToFMS) was considered. GC × GC–ToFMS application in the analysis of the exhaled breath of 32 children with allergic asthma, from which 10 had also allergic rhinitis, and 27 control children allowed the identification of several hundreds of compounds belonging to different chemical families. Multivariate analysis, using Partial Least Squares-Discriminant Analysis in tandem with Monte Carlo Cross Validation was performed to assess the predictive power and to help the interpretation of recovered compounds possibly linked to oxidative stress, inflammation processes or other cellular processes that may characterize asthma. The results suggest that the model is robust, considering the high classification rate, sensitivity, and specificity. A pattern of six compounds belonging to the alkanes characterized the asthmatic population: nonane, 2,2,4,6,6-pentamethylheptane, decane, 3,6-dimethyldecane, dodecane, and tetradecane. To explore future clinical applications, and considering the future role of molecular-based methodologies, a compound set was established to rapid access of information from exhaled breath, reducing the time of data processing, and thus, becoming more expedite method for the clinical purposes.

Physiological dose response of coffee (Coffea arabica L.) plants to glyphosate depends on growth stage

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effect of nitrogen supply on growth and photosynthesis of sunflower plants grown in the greenhouse

The effects of nitrogen availability on growth and photosynthesis were followed in plants of sunflower (Helianthus annuus L., var. CATISSOL-01) grown in the greenhouse under natural photoperiod. The sunflower plants were grown in vermiculite under two contrasting nitrogen supply, with nitrogen supplied as ammonium nitrate. Higher nitrogen concentration resulted in higher shoot dry matter production per plant and the effect was apparent from 29 days after sowing (DAS). The difference in dry matter production was mainly attributed to the effect of nitrogen on leaf production and on individual leaf dry matter. The specific leaf weight (SLW) was not affected by the nitrogen supply. The photosynthetic CO2 assimilation (A) of the target leaves was remarkably improved by high nitrogen nutrition. However, irrespective of nitrogen supply, the decline in photosynthetic CO2 assimilation occurred before the end of leaf growth. Although nitrogen did not change significantly stomatal conductance (gs), high-N grown plants had lower intercellular CO2 concentration (C-i) when compared with low-N grown plants. Transpiration rate (E) was increased in high-N grown plants only at the beginning of leaf growth. However, this not resulted in lower intrinsic water use efficiency (WUE). (C) 2004 Elsevier B.V.. All rights reserved.

Thermoeconomic analysis method for optimization of combined heat and power systems - part II

In this paper, a thermoeconomic functional analysis method based on the Second Law of Thermodynamics and applied to analyze four cogeneration systems is presented. The objective of the developed technique is to minimize the operating costs of the cogeneration plant, namely exergetic production cost (EPC), assuming fixed rates of electricity production and process steam in exergy base. In this study a comparison is made between the same four configurations of part I. The cogeneration system consisting of a gas turbine with a heat recovery steam generator, without supplementary firing, has the lowest EPC. (C) 2004 Published by Elsevier Ltd.

Line-pack management for producing electric power on peak periods

The distribution of natural gas is carried out by means of long ducts and intermediate compression stations to compensate the pressure drops due to friction. The natural gas compressors are usually driven by an electric motor or a gas turbine system, offering possibilities for energy management, one of these consisting in generating energy for use in-plant or to commercialize as independent power producer. It can be done by matching the natural gas demand, at the minimum pressure allowed in the reception point, and the storage capacity of the feed duct with the maximum compressor capacity, for storing the natural gas at the maximum permitted pressure. This allows the gas turbine to drive an electric generator during the time in which the decreasing pressure in duct is above the minimum acceptable by the sink unit. In this paper, a line-pack management analysis is done for an existing compression station considering its actual demand curve for determining the economic feasibility of maintaining the gas turbine system driver generating electricity in a peak and off-peak tariff structure. The potential of cost reduction from the point of view of energy resources (natural gas and electric costs) is also analyzed. (C) 2010 Elsevier Ltd. All rights reserved.

Variable-Structure Control Design of Switched Systems With an Application to a DC-DC Power Converter

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)