Alternating Cationic-Hydrophobic Peptide/Peptoid Hybrids: Influence of Hydrophobicity on Antibacterial Activity and Cell Selectivity

The influence of hydrophobicity on antibacterial activity versus the effect on the viability of mammalian cells for peptide/peptoid hybrids was examined for oligomers based on the cationic Lys-like peptoid residue combined with each of 28 hydrophobic amino acids in an alternating sequence. Their relative hydrophobicity was correlated to activity against both Gram-negative and Gram-positive species, human red blood cells, and HepG2 cells. This identified hydrophobic side chains that confer potent antibacterial activity (e. g., MICs of 2–8 μg/mL against E. coli) and low toxicity toward mammalian cells (<10 % hemolysis at 400 μg/mL and IC₅₀>800 μg/mL for HepG2 viability). Most peptidomimetics retained activity against drug-resistant strains. These findings corroborate the hypothesis that for related peptidomimetics two hydrophobicity thresholds may be identified: i) it should exceed a certain level in order to confer antibacterial activity, and ii) there is an upper limit, beyond which cell selectivity is lost. It is envisioned that once identified for a given subclass of peptide-like antibacterials such thresholds can guide further optimisation.     

The relationship between highly-cited papers and the frequency of citations to other papers within-issue among three top information science journals

Scientometrics - This study investigates a potential relationship between highly-cited scholarly papers and the number of citations received by other papers with which they share a journal issue....     

Distributed ledger technology in supply chains: a transaction cost perspective

With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.     

Combination of Reaction and Separation in Heterogeneous Catalytic Hydrogenation of Ethylformate

Continuous hydrogenation reaction of ethyl benzoylformate was studied over a (–)‐cinchonidine (CD)‐modified Pt/Al₂O₃ catalyst. The catalyst showed a good stability, and high enantioselectivity was achieved in the fixed‐bed reactor. Chromatographic separation of (R)‐ and (S)‐ethyl mandelate originating from a post‐continuous hydrogenation reaction of ethyl benzoylformate over the (–)‐CD‐modified Pt/Al₂O₃ catalyst was investigated in the same reaction mixture. A commercial column filled with a chiral selector resin was chosen as a perspective preparative‐scale adsorbent. Since adsorption equilibrium isotherms were linear within the entire investigated range of concentrations, they were determined by pulse experiments for the isomers present in a post‐reaction mixture. Breakthrough curves were measured and described successfully by the dispersive plug‐flow model with linear driving force approximation.     

La0.6Sr0.4Co0.2Fe0.8O3-δ nanofiber cathode for intermediate-temperature solid oxide fuel cells by water-based sol-gel electrospinning: Synthesis and electrochemical behaviour

Water-based sol-gel electrospinning is employed to manufacture perovskite oxide La_0.6Sr_0.4Co_0.2Fe_0.8O_3-δ (LSCF) nanofiber cathodes for intermediate-temperature solid oxide fuel cells. LSCF fibrous scaffolds are synthesized through electrospinning of a sol-gel solution employing water as the only solvent. Morphological characterizations demonstrate that the LSCF fibers have highly crystalline structure with uniform elemental distribution. After heat treatment, the average fiber diameter is 250 nm and the porosity of the nanofiber tissue is 37.5 %. The heat treated LSCF nanofibers are applied directly onto a Ce_0.9Gd_0.1O_1.95 (CGO) electrolyte disk to form a symmetrical cell. Electrochemical characterization is carried out through electrochemical impedance spectroscopy (EIS) in the temperature range 550?°C–950?°C, and reproducibility of the electrochemical performance for a series of cells is demonstrated. At 650?°C, the average measured polarization resistance R_p is 1.0 Ω cm². Measured performance decay is 1 % during the first 33?h of operation at 750?°C, followed by an additional 0.7 % over the subsequent 70?h.     

Towards impedance-based temperature estimation for Li-ion battery packs

In order to meet the required power and energy demand of battery-powered applications, battery packs are constructed from a multitude of battery cells. For safety and control purposes, an accurate estimate of the temperature of each battery cell is of vital importance. Using electrochemical impedance spectroscopy (EIS), the battery temperature can be inferred from the impedance. However, performing EIS measurements simultaneously at the same frequency on each cell in a battery pack introduces crosstalk interference in surrounding cells, which may cause EIS measurements in battery packs to be inaccurate. Also, currents flowing through the pack interfere with impedance measurements on the cell level. In this paper, we propose, analyse, and validate a method for estimating the battery temperature in a battery pack in the presence of these disturbances. First, we extend an existing and effective estimation framework for impedance-based temperature estimation towards estimating the temperature of each cell in a pack in the presence of crosstalk and (dis)charge currents. Second, the proposed method is analysed and validated on a two-cell battery pack, which is the first step towards development of this method for a full-size battery pack. Monte Carlo simulations are used to find suitable measurement settings that yield small estimation errors and it is demonstrated experimentally that, over a range of temperatures, the method yields an accuracy of ±1°C in terms of bias, in the presence of both disturbances.