Studies on Abscisic Acid

Methyl α-ionylideneacetates were oxidized with selenium dioxide to a mixture of methyl 3′-keto-β-ionylideneacetates and a small amount of methyl 4′-keto-α-ionylidene-acetates followed by treatment with active manganese dioxide. By a similar oxidation methyl 3′-keto-β-ionylideneacetates were prepared from methyl β-ionylidene acetates. Methyl 4′-keto-α-ionylideneacetates were obtained by oxidation of methyl α-ionylideneacetates with tert-butyl chromate. Dehydrobromination of methyl bromoionylideneacetate, obtained by bromination of methyl 2-trans-α-ionylideneacetate with N-bromosuccinimide, gave a mixture of methyl 2-trans-dehydro-β-ionylideneacetate and methyl 2-cis-dehydro-β-ionylideneacetate. The growth inhibitory activities of these sesquiterpene carboxylic acids and keto esters on rice seedlings were tested.     

Application of Artificial Bee Colony Algorithm to Maximum Likelihood DOA Estimation

Maximum Likelihood (ML) method has an excellent performance for Direction-Of-Arrival (DOA) estimation, but a multidimensional nonlinear solution search is required which complicates the computation and prevents the method from practical use. To reduce the high computational burden of ML method and make it more suitable to engineering applications, we apply the Artificial Bee Colony (ABC) algorithm to maximize the likelihood function for DOA estimation. As a recently proposed bio-inspired computing algorithm, ABC algorithm is originally used to optimize multivariable functions by imitating the behavior of bee colony finding excellent nectar sources in the nature environment. It offers an excellent alternative to the conventional methods in ML-DOA estimation. The performance of ABC-based ML and other popular meta-heuristic-based ML methods for DOA estimation are compared for various scenarios of convergence, Signal-to-Noise Ratio (SNR), and number of iterations. The computation loads of ABC-based ML and the conventional ML methods for DOA estimation are also investigated. Simulation results demonstrate that the proposed ABC based method is more efficient in computation and statistical performance than other ML-based DOA estimation methods.     

Inverse Optical Cavity Design for Ultrabroadband Light Absorption Beyond the Conventional Limit in Low‐Bandgap Nonfullerene Acceptor–Based Solar Cells

In the subwavelength regime, several nanophotonic configurations have been proposed to overcome the conventional light trapping or light absorption enhancement limit in solar cells also known as the Yablonovitch limit. It has been recently suggested that establishing such limit should rely on computational inverse electromagnetic design instead of the traditional approach combining intuition and a priori known physical effect. In the present work, by applying an inverse full wave vector electromagnetic computational approach, a 1D nanostructured optical cavity with a new resonance configuration is designed that provides an ultrabroadband (≈450 nm) light absorption enhancement when applied to a 107 nm thick active layer organic solar cell based on a low‐bandgap (1.32 eV) nonfullerene acceptor. It is demonstrated computationally and experimentally that the absorption enhancement provided by such a cavity surpasses the conventional limit resulting from an ergodic optical geometry by a 7% average over a 450 nm band and by more than 20% in the NIR. In such a cavity configuration the solar cells exhibit a maximum power conversion efficiency above 14%, corresponding to the highest ever measured for devices based on the specific nonfullerene acceptor used.     

Uniform High Ionic Conducting Lithium Sulfide Protection Layer for Stable Lithium Metal Anode

Artificial solid‐electrolyte interphase (SEI) is one of the key approaches in addressing the low reversibility and dendritic growth problems of lithium metal anode, yet its current effect is still insufficient due to insufficient stability. Here, a new principle of “simultaneous high ionic conductivity and homogeneity” is proposed for stabilizing SEI and lithium metal anodes. Fabricated by a facile, environmentally friendly, and low‐cost lithium solid‐sulfur vapor reaction at elevated temperature, a designed lithium sulfide protective layer successfully maintains its protection function during cycling, which is confirmed by both simulations and experiments. Stable dendrite‐free cycling of lithium metal anode is realized even at a high areal capacity of 5 mAh cm^?2, and prototype Li–Li₄Ti₅O₁₂ cell with limited lithium also achieves 900 stable cycles. These findings give new insight into the ideal SEI composition and structure and provide new design strategies for stable lithium metal batteries.     

Artificial cationic peptides that increase nuclease resistance of siRNA without disturbing RNAi activity

Properties of cationic peptides bearing amino or guanidino groups with various side chain lengths that bind to double stranded RNAs (dsRNAs) were investigated. Peptides with shorter side chain lengths effectively bound to dsRNAs (12mers) increasing their thermal stability. NMR measurements suggested that the cationic peptide binds to the inner side of the major groove of dsRNA. These peptides also increased the thermal stability of siRNA and effectively protected from RNase A digestion. On the other hand, both peptides containing amino groups and guanidine groups did not disturb RNAi activity.     

Effect of the rearing system on financial returns from Murciano-Granadina breed goats

In dairy goats, the kid rearing system can have critical importance in financial returns. Commonly used criteria for the choice of rearing system are not always clear due to the high number of factors involved. The aim of this study was to quantify all those factors to facilitate decision making. So, the effect of two different kid rearing systems, mixed rearing system (MRS) and artificial rearing system (ARS), on milk yield, milk composition and somatic cell count (SCC), milk yield loss at weaning for MRS, kid growth and costs of the different traits on the financial returns in Murciano-Granadina breed goats was studied. Twenty-four goats per group were used. In the MRS, goats reared only one kid, which had free access to goat milk 24 h a day and were weaned at week 6 of lactation, whereas kids in the ARS were separated from their mothers at kidding, colostrum and artificially reared. In both systems, dams were machine-milked once a day throughout lactation and the records took place weekly. Potential milk yield was estimated according to the oxytocin method up to week 12 of lactation, and was similar for both rearing systems, although a 12.3% drop in potential milk yield at weaning was observed for MRS. During the first 6 weeks of lactation, marketable milk was lower for dams in MRS compared to those in ARS (72.1 v. 113.0 l), but similar for the rest of the experiment (101.5 v. 99.4 l, respectively). Marketable milk composition and SCC throughout the 12 weeks of lactation were unaffected by the rearing system. Artificial rearing system entailed an increment in production cost of 22.2€ per kid compared to the rearing by MRS. A similar economic return per goat and kid was obtained from ARS and MRS in this experiment, although, due to one herd’s prolificacy of 1.8, the actual results would be 16.2€ per goat in favour of MRS. The real interest of this experiment may be the possibility of extrapolation to different flocks with diverse levels of milk production, prolificacy and prices and costs for incomes and outputs, to estimate the production system that increases returns. In conclusion, the results showed an increase in the cost of €22.2 per kid bred in the ARS, compared to the MRS, and a final return of 16.2€ per goat in favour of the mixed system.