Switching to Perennial Energy Crops under Uncertainty and Costly Reversibility

We study a farmer’s decision to convert traditional crop land into growing dedicated energy crops, taking in account sunk conversion costs, uncertainties in traditional and energy crop returns, and learning. The optimal decision rules differ significantly from the expected net present value rule, which ignores learning, and from real option models that allow only one way conversions into energy crops. These models also predict drastically different patterns of land conversions into and out of energy crops over time. Using corn-soybean rotations and switchgrass as examples, we show that the model predictions are sensitive to assumptions about stochastic processes of the returns. Government policies might have unintended consequences: subsidizing conversion costs into switchgrass reduces proportions of land in switchgrass in the long run.real options, irreversibility, sunk costs, land conversion, biofuel, cellulosic biomass, dynamic modeling, stochastic process, biofuel policy, Land Economics/Use, Resource /Energy Economics and Policy, Risk and Uncertainty, Q42, Q24,

Alternative Land Use Policies: Real Options with Costly Reversibility

This paper adopts a real options framework to evaluate the cost-effectiveness of four types of subsidies that aim to encourage a socially desirable land use under return uncertainties and costly reversibility of land use change. We first present a land conversion model to show how the subsidies that are expected net present value (ENPV) equivalent can change a representative farmer’s optimal land conversion rules differently for converting land into an alternative use as well as converting out of it. This is because these subsidies affect the land conversion costs, land return level and uncertainty differently. Then in the context of encouraging energy crop production, we compare the probabilities of inducing the representative farmer to convert land from a current crop to an energy crop across four subsidies for the same, fixed 30-year expected government budget. Results of Monte Carlo simulations show that the insurance subsidy results in the highest probability of land being converted to the energy crop, followed by the constant subsidy. Although the cost-sharing subsidy and the variable subsidy encourage land conversion to the energy crop, they also reduce the incentive to retain land in it. Over time, these two subsidies have little effect on the probability of land converting into energy crops compared to the no-subsidy baseline. Combining the establishment cost-sharing subsidy with other annual subsidies has no added effect over single subsidies in inducing land conversion to the energy crop.Monte Carlo simulations, real options, agricultural subsidies, cost-effectiveness, two-way land conversion, Agricultural and Food Policy, Resource /Energy Economics and Policy, Q24, Q48,

Measuring the phonon-assisted spectral function by using a non-quilibrium three-terminal single-molecular device

The electron transport through a three-terminal single-molecular transistor (SMT) is theoretically studied. We find that the differential conductance of the third and weakly coupled terminal versus its voltage matches well with the spectral function versus the energy when certain conditions are met. Particularly, this excellent matching is maintained even for complicated structure of the phonon-assisted side peaks. Thus, this device offers an experimental approach to explore the shape of the phonon-assisted spectral function in detail. In addition we discuss the conditions of a perfect matching. The results show that at low temperatures the matching survives regardless of the bias and the energy levels of the SMT. However, at high temperatures, the matching is destroyed.Comment: 9 pages, 5 figure

Studies directed towards the stereoselective total synthesis of miyakolide

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 1999.Includes bibliographical references (leaves 154-157).by Jinhua Song.Ph.D

Poly[(acetato-κ2 O,O′)aqua­(μ4-1H-benzimidazole-5,6-dicarboxyl­ato-κ6 N 3:O 5,O 5′:O 5,O 6:O 6′)cerium(III)]

In the title compound, [Ce(C9H4N2O4)(C2H3O2)(H2O)]n, the CeIII ion is coordinated by five O atoms and one N atom from four 1H-benzimidazole-5,6-dicarboxyl­ato (L) ligands and by two O atoms from an acetate ligand and one aqua ligand, forming a slightly distorted tricapped trigonal–prismatic geometry. The L ligands are bridging, forming a layered polymer parallel to (010). In the crystal, O—H⋯O and N—H⋯O hydrogen bonds connect the polymer layers into a three-dimensional network

Dummy Molecularly Imprinted Polymers-Capped CdTe Quantum Dots for the Fluorescent Sensing of 2,4,6-Trinitrotoluene

Molecularly imprinted polymers (MIPs) with trinitrophenol (TNP) as a dummy template molecule capped with CdTe quantum dots (QDs) were prepared using 3-aminopropyltriethoxy silane (APTES) as the functional monomer and tetraethoxysilane (TEOS) as the cross linker through a seedgrowth method via a sol gel process (i.e., DMIP@QDs) for the sensing of 2,4,6-trinitrotoluene (TNT) on the basis of electron-transfer-induced fluorescence quenching. With the presence and increase of TNT in sample solutions, a Meisenheimer complex was formed between TNT and the primary amino groups on the surface of the QDs. The energy of the QDs was transferred to the complex, resulting in the quenching of the QDs and thus decreasing the fluorescence intensity, which allowed the TNT to be sensed optically. DMIP@QDs generated a significantly reduced fluorescent intensity within less than 10 min upon binding TNT. The fluorescence-quenching fractions of the sensor presented a satisfactory linearity with TNT concentrations in the range of 0.8-30 mu M, and its limit of detection could reach 0.28 mu M. The sensor exhibited distinguished selectivity and a high binding affinity to TNT over its possibly competing molecules of 2,4-dinitrophenol (DNP), 4-nitrophenol (4-NP), phenol, and dinitrotoluene (DNT) because there are more nitro groups in TNT and therefore a stronger electron-withdrawing ability and because it has a high similarity in shape and volume to TNP. The sensor was successfully applied to determine the amount of TNT in soil samples, and the average recoveries of TNT at three spiking levels ranged from 90.3 to 97.8% with relative standard deviations below 5.12%. The results provided an effective way to develop sensors for the rapid recognition and determination of hazardous materials from complex matrices.Molecularly imprinted polymers (MIPs) with trinitrophenol (TNP) as a dummy template molecule capped with CdTe quantum dots (QDs) were prepared using 3-aminopropyltriethoxy silane (APTES) as the functional monomer and tetraethoxysilane (TEOS) as the cross linker through a seedgrowth method via a sol gel process (i.e., DMIP@QDs) for the sensing of 2,4,6-trinitrotoluene (TNT) on the basis of electron-transfer-induced fluorescence quenching. With the presence and increase of TNT in sample solutions, a Meisenheimer complex was formed between TNT and the primary amino groups on the surface of the QDs. The energy of the QDs was transferred to the complex, resulting in the quenching of the QDs and thus decreasing the fluorescence intensity, which allowed the TNT to be sensed optically. DMIP@QDs generated a significantly reduced fluorescent intensity within less than 10 min upon binding TNT. The fluorescence-quenching fractions of the sensor presented a satisfactory linearity with TNT concentrations in the range of 0.8-30 mu M, and its limit of detection could reach 0.28 mu M. The sensor exhibited distinguished selectivity and a high binding affinity to TNT over its possibly competing molecules of 2,4-dinitrophenol (DNP), 4-nitrophenol (4-NP), phenol, and dinitrotoluene (DNT) because there are more nitro groups in TNT and therefore a stronger electron-withdrawing ability and because it has a high similarity in shape and volume to TNP. The sensor was successfully applied to determine the amount of TNT in soil samples, and the average recoveries of TNT at three spiking levels ranged from 90.3 to 97.8% with relative standard deviations below 5.12%. The results provided an effective way to develop sensors for the rapid recognition and determination of hazardous materials from complex matrices

Radiometric dating of late Quaternary loess in the northern piedmont of South Tianshan Mountains: Implications for reliable dating

Reliable chronologies are prerequisites when interpreting proxy records in terrestrial archives of Quaternary climate and environmental change. Optically stimulated luminescence (OSL) dating and accelerator mass spectrometry radiocarbon dating (AMS C-14) are commonly used to date late Quaternary loess deposits in the Chinese Loess Plateau, but the range and reliability of the two methods in Central Asia are still debated. In this study, we investigate both fine-grained quartz OSL and AMS C-14 dating of a late Quaternary loess section located at the northern piedmont of the South Tianshan Mountains in Central Asia and discuss the reliability of the two radiometric dating methods. The results show that the OSL and AMS C-14 ages are generally consistent with the stratigraphic sequence when the ages are younger than 25cal ka BP, which means that both can be used to establish a reliable chronology in the Ili Basin. But beyond this age, the OSL dating method seems to be a more reliable approach. The results also supported previous dates based on medium-grained quartz OSL dating of the Ili loess in the southern piedmont of the North Tianshan Mountains. Radiocarbon ages older than 25cal ka BP should be treated with caution, and attention must be paid to the influence of pedoturbation on OSL signals in the Central Asian loess. Multiple dating approaches for mutual authentication and exploring new dating materials are suggested in further loess chronological research. These findings will be helpful in establishing a reliable timescale and in reconstructing high-resolution environmental change in Central Asia

Robust K-Median and K-Means Clustering Algorithms for Incomplete Data

Incomplete data with missing feature values are prevalent in clustering problems. Traditional clustering methods first estimate the missing values by imputation and then apply the classical clustering algorithms for complete data, such as K-median and K-means. However, in practice, it is often hard to obtain accurate estimation of the missing values, which deteriorates the performance of clustering. To enhance the robustness of clustering algorithms, this paper represents the missing values by interval data and introduces the concept of robust cluster objective function. A minimax robust optimization (RO) formulation is presented to provide clustering results, which are insensitive to estimation errors. To solve the proposed RO problem, we propose robust K-median and K-means clustering algorithms with low time and space complexity. Comparisons and analysis of experimental results on both artificially generated and real-world incomplete data sets validate the robustness and effectiveness of the proposed algorithms