Increasing the Efficiency of Projection Models of Strip Lines

Journal of Communications Technology and Electronics - Abstract—The matrix coefficients of projection models of strip lines obtained using the Chebyshev basis are presented as a sum of...     

Phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters

Analog Integrated Circuits and Signal Processing - This paper presents the complete design of a phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters. The...     

Reusable and Efficient Polystyrene Immobilized Ionic Liquid Catalyst for Batch and Flow Methylation of Hydroquinone

Catalysis Letters - An environmentally benign process for synthesizing 4-methoxyphenol through methylation of hydroquinone using polystyrene immobilized Bronsted acidic ionic liquid is presented....     

Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

Effects of Cu on the corrosion behavior and microstructure of Mg–Zn–Ca bulk metallic glass

For the purpose of developing biodegradable magnesium alloys with suitable properties for biomedical applications, Mg–Zn–Ca–Cu metallic glasses were prepared by copper mold injection methods. In the present work, the effect of Cu doping on mechanical properties, corrosion behavior, and glass-forming ability of Mg₆₆Zn₃₀Ca₄ alloy was studied. The experimental findings demonstrated that the incorporation of Cu decreases the corrosion resistance of alloys, but increases the microhardness and degradation rate slightly. However, the addition of a trace amount of Cu can make the samples have antibacterial properties. Therefore, Mg–Zn–Ca–Cu has great advantages in clinical implantation and is the potential implant material.     

Stem Photosynthesis—A Key Element of Grass Pea (Lathyrus sativus L.) Acclimatisation to Salinity

Grass pea (Lathyrus sativus) is a leguminous plant of outstanding tolerance to abiotic stress. The aim of the presented study was to describe the mechanism of grass pea (Lathyrus sativus L.) photosynthetic apparatus acclimatisation strategies to salinity stress. The seedlings were cultivated in a hydroponic system in media containing various concentrations of NaCl (0, 50, and 100 mM), imitating none, moderate, and severe salinity, respectively, for three weeks. In order to characterise the function and structure of the photosynthetic apparatus, Chl a fluorescence, gas exchange measurements, proteome analysis, and Fourier-transform infrared spectroscopy (FT-IR) analysis were done inter alia. Significant differences in the response of the leaf and stem photosynthetic apparatus to severe salt stress were observed. Leaves became the place of harmful ion (Na⁺) accumulation, and the efficiency of their carboxylation decreased sharply. In turn, in stems, the reconstruction of the photosynthetic apparatus (antenna and photosystem complexes) activated alternative electron transport pathways, leading to effective ATP synthesis, which is required for the efficient translocation of Na⁺ to leaves. These changes enabled efficient stem carboxylation and made them the main source of assimilates. The observed changes indicate the high plasticity of grass pea photosynthetic apparatus, providing an effective mechanism of tolerance to salinity stress.     

Synergistic effect of bulk phase doping and layered-spinel structure formation on improving electrochemical performance of Li-Rich cathode material

In this study, La was doped into the lithium layer of Li-rich cathode material and formed a layered-spinel hetero-structure. The morphology, crystal structure, element valence and kinetics of lithium ion migration were studied by field emission scanning electron microscope (FESEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and electrochemical impedance spectroscopy (EIS). The La doped lithium-rich cathode material exhibited similar initial discharge capacity of 262.8 mAh g^?1 at 0.1 C compared with the undoped material, but the discharge capacity retention rate can be obviously improved to 90% after 50 cycles at 1.0 C. Besides that, much better rate capability and Li⁺ diffusion coefficient were observed. The results revealed that La doping not only stabilized the material structure and reduced the Li/Ni mixing degree, but also induced the generation of spinel phase to provide three-dimensional diffusion channels for lithium ion migration. Moreover, the porous structure of the doped samples also contributed to the remarkable excellent electrochemical performance. All of these factors combined to significantly improve the electrochemical performance of the material.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.