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The ethanolic fermentation of liquid fractions (hydrolysates) issued from dilute acid pre-treatment of olive tree biomass by Pichia stipitis is reported for the first time. On the one side, P. stipitis has been reported as the most promising naturally occurring C5 fermenting microorganism; on the other side, olive tree biomass is a renewable, low cost, and lacking of alternatives agricultural residue especially abundant in Mediterranean countries. The study was performed in two steps. First, the fermentation performance of P. stipitis was evaluated on a fermentation medium also containing the main inhibitors found in these hydrolysates (acetic acid, formic acid, and furfural), as well as glucose and xylose as carbon sources. The effect of inhibitors, individually or in a mixture, on kinetic and yield parameters was calculated. In a second step, hydrolysates obtained from 1% (w/w) sulfuric acid pre-treatment of olive tree biomass at 190ºC for 10 min were used as a real fermentation medium with the same microorganism. Due to inhibition, effective fermentation required dilution of the hydrolysate and either overliming or activated charcoal treatment. Results show that ethanol yields obtained from hydrolysates, ranging from 0.35 to 0.42 g/g, are similar to those from synthetic medium, although the process proceeds at lower rates. Inhibiting compounds affect the fermentation performance in a synergistic way. Furfural is rapidly assimilated by the yeast; acetic acid and formic acid concentrations decrease slowly during the process. Activated charcoal or overliming detoxification improve the fermentability of diluted hydrolysates.

The ethanolic fermentation of liquid fractions (hydrolysates) issued from dilute acid pre-treatment of olive tree biomass by Pichia stipitis is reported for the first time. On the one side, P. stipitis has been reported as the most promising naturally occurring C5 fermenting microorganism; on the other side, olive tree biomass is a renewable, low cost, and lacking of alternatives agricultural residue especially abundant in Mediterranean countries. The study was performed in two steps. First, the fermentation performance of P. stipitis was evaluated on a fermentation medium also containing the main inhibitors found in these hydrolysates (acetic acid, formic acid, and furfural), as well as glucose and xylose as carbon sources. The effect of inhibitors, individually or in a mixture, on kinetic and yield parameters was calculated. In a second step, hydrolysates obtained from 1% (w/w) sulfuric acid pre-treatment of olive tree biomass at 190ºC for 10 min were used as a real fermentation medium with the same microorganism. Due to inhibition, effective fermentation required dilution of the hydrolysate and either overliming or activated charcoal treatment. Results show that ethanol yields obtained from hydrolysates, ranging from 0.35 to 0.42 g/g, are similar to those from synthetic medium, although the process proceeds at lower rates. Inhibiting compounds affect the fermentation performance in a synergistic way. Furfural is rapidly assimilated by the yeast; acetic acid and formic acid concentrations decrease slowly during the process. Activated charcoal or overliming detoxification improve the fermentability of diluted hydrolysates.

ABSTRACTPlant heme oxygenases (HOs) regulate biosynthesis of phytochrome which accounts for photo‐acceptance and ‐morphogenesis. Recent studies have demonstrated that plant HOs also regulate many other physiological processes including response to environmental stimuli. To elucidate the mechanism by which HOs regulate plant adaptation to heavy metal exposure, three novel HOs genes were isolated from rapeseed (Brassica napus) and their expression patterns were analysed. Alignment of deduced protein sequences revealed that the three BnHOs share high identity with their corresponding orthologos (AtHO1‐3) from Arabidopsis. To investigate whether the BnHO regulates plant tolerance to Hg toxicity, we constructed B. napus transgenic plants overexpressing BnHO‐1. Under Hg stress, the transgenic plants had 1.41–1.59 folds higher biomass than the untransformants. However, overexpression of BnHO‐1 resulted in less accumulation of Hg in some lines of transformants than in untransformants. The transgenic plants show lower abundance of reactive oxygen species and attenuated oxidative injury compared with the untransgenic plants. We cloned the promoter sequences of BnHO‐1 from B. napus. Analysis revealed that the 1119 bp fragment contains a conserved Cd responsive element (CdRE) and others responding to multiple environmental stimuli. Transient expression in tobacco leaves showed differential responses to heavy metals (Zn, Cu, Pb, Hg and Cd).

ABSTRACTPlant heme oxygenases (HOs) regulate biosynthesis of phytochrome which accounts for photo‐acceptance and ‐morphogenesis. Recent studies have demonstrated that plant HOs also regulate many other physiological processes including response to environmental stimuli. To elucidate the mechanism by which HOs regulate plant adaptation to heavy metal exposure, three novel HOs genes were isolated from rapeseed (Brassica napus) and their expression patterns were analysed. Alignment of deduced protein sequences revealed that the three BnHOs share high identity with their corresponding orthologos (AtHO1‐3) from Arabidopsis. To investigate whether the BnHO regulates plant tolerance to Hg toxicity, we constructed B. napus transgenic plants overexpressing BnHO‐1. Under Hg stress, the transgenic plants had 1.41–1.59 folds higher biomass than the untransformants. However, overexpression of BnHO‐1 resulted in less accumulation of Hg in some lines of transformants than in untransformants. The transgenic plants show lower abundance of reactive oxygen species and attenuated oxidative injury compared with the untransgenic plants. We cloned the promoter sequences of BnHO‐1 from B. napus. Analysis revealed that the 1119 bp fragment contains a conserved Cd responsive element (CdRE) and others responding to multiple environmental stimuli. Transient expression in tobacco leaves showed differential responses to heavy metals (Zn, Cu, Pb, Hg and Cd).

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.

This article examines land-use, market and welfare implications of lignocellulosic bioethanol production in Hawaii to satisfy 10% and 20% of the State's gasoline demand in line with the State's ethanol blending mandate and Alternative Fuels Standard (AFS). A static computable general equilibrium (CGE) model is used to evaluate four alternative support mechanisms for bioethanol. Namely: (i) a federal blending tax credit, (ii) a long-term purchase contract, (iii) a state production subsidy financed by a lump-sum tax and (iv) a state production subsidy financed by an ad valorem gasoline tax. We find that because Hawaii-produced bioethanol is relatively costly, all scenarios are welfare reducing for Hawaii residents: estimated between -0.14% and -0.32%. Unsurprisingly, Hawaii.s economy and its residents fair best under the federal blending tax credit scenario, with a positive impact to gross state product of $49 million. Otherwise, impacts to gross state product are negative (up to -$63 million). We additionally find that Hawaii-based bioethanol is not likely to offer substantial greenhouse gas emissions savings in comparison to imported biofuel, and as such the policy cost per tonne of emissions displaced ranges between $130 to $2,100/tonne of CO2e. The policies serve to increase the value of agricultural lands, where we estimate that the value of pasture land could increase as much as 150% in the 20% AFS scenario.

This article examines land-use, market and welfare implications of lignocellulosic bioethanol production in Hawaii to satisfy 10% and 20% of the State's gasoline demand in line with the State's ethanol blending mandate and Alternative Fuels Standard (AFS). A static computable general equilibrium (CGE) model is used to evaluate four alternative support mechanisms for bioethanol. Namely: (i) a federal blending tax credit, (ii) a long-term purchase contract, (iii) a state production subsidy financed by a lump-sum tax and (iv) a state production subsidy financed by an ad valorem gasoline tax. We find that because Hawaii-produced bioethanol is relatively costly, all scenarios are welfare reducing for Hawaii residents: estimated between -0.14% and -0.32%. Unsurprisingly, Hawaii.s economy and its residents fair best under the federal blending tax credit scenario, with a positive impact to gross state product of $49 million. Otherwise, impacts to gross state product are negative (up to -$63 million). We additionally find that Hawaii-based bioethanol is not likely to offer substantial greenhouse gas emissions savings in comparison to imported biofuel, and as such the policy cost per tonne of emissions displaced ranges between $130 to $2,100/tonne of CO2e. The policies serve to increase the value of agricultural lands, where we estimate that the value of pasture land could increase as much as 150% in the 20% AFS scenario.