Positive exchange bias in ferromagnetic La0.67Sr0.33MnO3 / SrRuO3 bilayers

Epitaxial La0.67Sr0.33MnO3 (LSMO)/ SrRuO3 (SRO) ferromagnetic bilayers have been grown on (001) SrTiO3 (STO) substrates by pulsed laser deposition with atomic layer control. We observe a shift in the magnetic hysteresis loop of the LSMO layer in the same direction as the applied biasing field (positive exchange bias). The effect is not present above the Curie temperature of the SRO layer (), and its magnitude increases rapidly as the temperature is lowered below . The direction of the shift is consistent with an antiferromagnetic exchange coupling between the ferromagnetic LSMO layer and the ferromagnetic SRO layer. We propose that atomic layer charge transfer modifies the electronic state at the interface, resulting in the observed antiferromagnetic interfacial exchange coupling.Comment: accepted to Applied Physics Letter

Impact of hedging pressure on implied volatility in Financial Times and London Stock Exchange (FTSE) market

This paper examines the impact of net buying pressure and the event of 9/11 on the implied volatility of the U.K. FTSE 100 (Financial Times and the London Stock Exchange) index options. Our findings indicate that when effects such as financial leverage, information flow and mean reversion are held constant, the net buying pressure of the out-of-the-money put options plays a dominant role in determining the shape of the implied volatility function. Further, the event of 9/11 has a transitory influence on the implied volatility change. Our results also support the notion that hedging pressure can help explain the difference between implied volatility and realized volatility

FFT-LB modeling of thermal liquid-vapor systems

We further develop a thermal LB model for multiphase flows. In the improved model, we propose to use the FFT scheme to calculate both the convection term and external force term. The usage of FFT scheme is detailed and analyzed. By using the FFT algorithm spatiotemporal discretization errors are decreased dramatically and the conservation of total energy is much better preserved. A direct consequence of the improvement is that the unphysical spurious velocities at the interfacial regions can be damped to neglectable scale. Together with the better conservation of total energy, the more accurate flow velocities lead to the more accurate temperature field which determines the dynamical and final states of the system. With the new model, the phase diagram of the liquid-vapor system obtained from simulation is more consistent with that from theoretical calculation. Very sharp interfaces can be achieved. The accuracy of simulation results are also verified by the Laplace law. The FFT scheme can be easily applied to other models for multiphase flows.Comment: 34 pages, 21 figure

Analysis of energy saving potentials in intelligent manufacturing: A case study of bakery plants

To address the global challenge of the climate change, more strict legislations worldwide on carbon emission reductions have put energy intensive industries under immense pressure to improve the energy efficiency. Due to the lack of technical support and financial incentives, a range of technical and economic barriers still exist for small-medium enterprises (SMEs). This paper first introduces a point energy technology, which is developed for SMEs to improve the insight of the energy usage in the manufacturing processes and installed in a local bakery. Statistical analysis of electricity consumption data over a seven-day period is conducted, including the identification of operational modes for individual processing units using an enhanced clustering method and the voltage unbalance conditions associated with these identified modes. Two technical strategies, namely electrical load allotment and voltage unbalance minimisation, are then proposed, which could attain more than 800 kwh energy saving during this period and the current unbalance could be reduced to less than 10%. In addition, the genetic algorithm is deployed to solve the job shop scheduling problem based upon the commercial electrical tariffs, and this reduces the electricity bill by £80 per day in the case study. Implementation of the recommendations based on the above analysis therefore may potentially yield significant financial and environmental benefits

The Ensemble and Model Comparison Approaches for Big Data Analytics in Social Sciences

Big data analytics are prevalent in fields like business, engineering, public health, and the physical sciences, but social scientists are slower than their peers in other fields in adopting this new methodology. One major reason for this is that traditional statistical procedures are typically not suitable for the analysis of large and complex data sets. Although data mining techniques could alleviate this problem, it is often unclear to social science researchers which option is the most suitable one to a particular research problem. The main objective of this paper is to illustrate how the model comparison of two popular ensemble methods, namely, boosting and bagging, could yield an improved explanatory model. Accessed 993 times on https://pareonline.net from November 21, 2018 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Novel pH Responsive Amphiphilic Diblock Copolymers with Reversible Micellization Properties

Di-block copolymer of poly[methacrylic acid-block-2-(diethylamino)ethyl methacrylate] [P(MAA-b-DEA)] with narrow molecular weight distribution was synthesized using the atom transfer radical polymerization (ATRP) technique. The micellization behavior of the P(MAA-b-DEA) copolymer in aqueous solution at room temperature and different pH values were examined by potentiometric and conductivity titration, UV-Visible spectrophotometry, ¹H-NMR, static and dynamic laser light scattering. At low pH ( 9.5), core-shell like micelles consisting of hydrophobic DEA core and ionized MAA shell were re-established.Singapore-MIT Alliance (SMA

Fungicide application timing for management of Ascochyta blight in chickpea

Non-Peer ReviewedAscochyta blight of chickpea [Ascochyta rabiei] is an extremely destructive disease capable of causing high yield and quality losses. The disease is widespread in chickpea growing areas of the prairies, and the pathogen can survive in crop debris for several years. Although partially resistant cultivars are available, the disease can still be devastating if weather conditions are favourable, making fungicides an important disease management tool. Trials investigating the effectiveness of different fungicide application timings and sequences were conducted on the desi cv. Myles and the kabuli cv. CDC Yuma at Saskatoon in 2003. The products used included Bravo 500, Headline, and Lance. The first application was made prior to flowering, when disease pressure was still extremely low. Additional applications were made at early flower, mid-flower, late flower or podding, with a maximum of three applications per treatment. In both cultivars, treatments without a pre-flower application of fungicide had higher disease severity and lower yields than treatments with a pre-flower application. Treatments without a pre-flower application that were sprayed three times were still inferior to treatments with a pre-flower application that were only sprayed twice. These results emphasize the need for early and frequent scouting for disease symptoms in chickpea to allow for early fungicide application if it is appropriate

OPAAS: a web server for optimal, permuted, and other alternative alignments of protein structures

The large number of experimentally determined protein 3D structures is a rich resource for studying protein function and evolution, and protein structure comparison (PSC) is a key method for such studies. When comparing two protein structures, almost all currently available PSC servers report a single and sequential (i.e. topological) alignment, whereas the existence of good alternative alignments, including those involving permutations (i.e. non-sequential or non-topological alignments), is well known. We have recently developed a novel PSC method that can detect alternative alignments of statistical significance (alignment similarity P-value <10(−5)), including structural permutations at all levels of complexity. OPAAS, the server of this PSC method freely accessible at our website (), provides an easy-to-read hierarchical layout of output to display detailed information on all of the significant alternative alignments detected. Because these alternative alignments can offer a more complete picture on the structural, evolutionary and functional relationship between two proteins, OPAAS can be used in structural bioinformatics research to gain additional insight that is not readily provided by existing PSC servers

Comparison of ground and aerial application of fungicide for control of Ascochyta blight in chickpeas

Non-Peer ReviewedAscochyta rabiei control from aerial and ground application was assessed near Saskatoon in 2003 and 2004. Each year, a site of about 12 ha was seeded to kabuli (cv. CDC Xena) chickpeas. At the first sign of disease, applications of fungicide were commenced and maintained at approximately 10-day intervals. In 2003, four applications (two with Headline (pyraclostrobin), two with Lance (boscalid)) were conducted. In 2004, the last Lance application was not done. Aerial application was made using a Cessna AgTruck applying 37 L/ha using CP nozzles emitting a spray with a VMD of approximately 271 μm. Ground applications were conducted using a Melroe SpraCoupe applying 100 L/ha using XR8003 nozzles with a VMD of approximately 246 μm. Disease ratings were done throughout the season, and seed yields were taken at crop maturity. Disease incidence progressed to 80 to 90% in the untreated plots, and fungicide application reduced disease incidence (to 20 to 30%) and increased seed yield in both years. Disease incidence and seed yield were not affected by application method in either season

In situ tropical peatland ire emission factors and their variability, as determined by field measurements in peninsula Malaysia

Fires in tropical peatlands account for >25% of estimated total greenhouse gas emissions from deforestation and degradation. Despite significant global and regional impacts, our understanding of specific gaseous fire emission factors (EFs) from tropical peat burning is limited to a handful of studies. Furthermore, there is substantial variability in EFs between sampled fires and/or studies. For example, methane EFs vary by 91% between studies. Here we present new fire EFs for the tropical peatland ecosystem; the first EFs measured for Malaysian peatlands, and only the second comprehensive study of EFs in this crucial environment. During August 2015 (under El Niño conditions) and July 2016, we embarked on field campaigns to measure gaseous emissions at multiple peatland fires burning on deforested land in Southeast Pahang (2015) and oil palm plantations in North Selangor (2016), Peninsula Malaysia. Gaseous emissions were measured using open-path Fourier transform infrared spectroscopy. The IR spectra were used to retrieve mole fractions of 12 different gases present within the smoke (including carbon dioxide and methane), and these measurements used to calculate EFs. Peat samples were taken at each burn site for physicochemical analysis and to explore possible relationships between specific physicochemical properties and fire EFs. Here we present the first evidence to indicate that substrate bulk density affects methane fire EFs reported here. This novel explanation of interplume, within-biome variability, should be considered by those undertaking greenhouse gas accounting and haze forecasting in this region and is of importance to peatland management, particularly with respect to artificial compaction