Green Synthesis of Silver Nanoparticles from Salvia aethiopis L. and Their Antioxidant Activity

Journal of Inorganic and Organometallic Polymers and Materials - Salvia species have been used extensively in medicinal and food industries for years due to their significant secondary metabolites...     

Circadian Rhythms in Legumes: What Do We Know and What Else Should We Explore?

The natural timing devices of organisms, commonly known as biological clocks, are composed of specific complex folding molecules that interact to regulate the circadian rhythms. Circadian rhythms, the changes or processes that follow a 24-h light–dark cycle, while endogenously programmed, are also influenced by environmental factors, especially in sessile organisms such as plants, which can impact ecosystems and crop productivity. Current knowledge of plant clocks emanates primarily from research on Arabidopsis, which identified the main components of the circadian gene regulation network. Nonetheless, there remain critical knowledge gaps related to the molecular components of circadian rhythms in important crop groups, including the nitrogen-fixing legumes. Additionally, little is known about the synergies and trade-offs between environmental factors and circadian rhythm regulation, especially how these interactions fine-tune the physiological adaptations of the current and future crops in a rapidly changing world. This review highlights what is known so far about the circadian rhythms in legumes, which include major as well as potential future pulse crops that are packed with nutrients, particularly protein. Based on existing literature, this review also identifies the knowledge gaps that should be addressed to build a sustainable food future with the reputed “poor man’s meat”.     

PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features

Nitrotyrosine, which is generated by numerous reactive nitrogen species, is a type of protein post-translational modification. Identification of site-specific nitration modification on tyrosine is a prerequisite to understanding the molecular function of nitrated proteins. Thanks to the progress of machine learning, computational prediction can play a vital role before the biological experimentation. Herein, we developed a computational predictor PredNTS by integrating multiple sequence features including K-mer, composition of k-spaced amino acid pairs (CKSAAP), AAindex, and binary encoding schemes. The important features were selected by the recursive feature elimination approach using a random forest classifier. Finally, we linearly combined the successive random forest (RF) probability scores generated by the different, single encoding-employing RF models. The resultant PredNTS predictor achieved an area under a curve (AUC) of 0.910 using five-fold cross validation. It outperformed the existing predictors on a comprehensive and independent dataset. Furthermore, we investigated several machine learning algorithms to demonstrate the superiority of the employed RF algorithm. The PredNTS is a useful computational resource for the prediction of nitrotyrosine sites. The web-application with the curated datasets of the PredNTS is publicly available.     

An investigation of free vibrations of a strain gradient Timoshenko beams with the method of initial values

Investigated herein is the free vibrations of beams based on the strain gradient Timoshenko beam theory with the method of initial values. For the vibration of strain-gradient Timoshenko beam (SGTB), the sixth-order ordinary differential equation and three boundary conditions at each end have been obtained by using the Hamilton principle. The effect of the characteristic length on the frequencies of free vibrations is shown. The frequencies of the SGTB are compared to the frequencies of the strain gradient Euler beam (SGEB), classical Timoshenko beam (CTB) and classical Euler beam (CEB). It has been observed that the high-frequency values of conventional and strain-gradient beams are very different. This result can be used to determine the value of the material characteristic length for a nanobeam for which lengthscale effects are believed to be dominant.

     

Electrodeposition of metallic molybdenum and its alloys – a review

Aqueous electrodeposition may represent a more economical and reliable technique to fabricate Mo coatings than the alternatives (electrodeposition from fused-salt baths and other available methods). However, studies on the aqueous electrodeposition of pure metallic Mo are rather limited due to its oxophilic nature, catalytic behaviour for the hydrogen evolution reaction and high tendency for polymerisation, especially in acidic media. To date, researchers have tended to focus on the aqueous electrodeposition of Mo alloys. These alloys usually contain <51% Mo. The factors that influence the quality of Mo deposits and the difficulties in the electrodeposition process are reviewed here. This review not only presents a survey of existing literature on the electrodeposition of metallic Mo coatings but also provides a basis for any future exploration.     

Single-row mapping and transformation of connected graphs

In a dimensional problem, the transformation of a graph into its linear network can be viewed as a transition involving demand and supply. A connected graph represents the demand flows between the components in the graph while the network supporting it is the resource or capacity links for supporting the demand volumes. The transformation involves a mapping from the graph to its network to satisfy certain performance metrics. In this work, we propose a model for transforming a connected graph to its linear network model in the form of a single-row routing network. The main objective is to provide an optimum routing network that minimizes the congestion. In this technique, the given graph is first partitioned into several disjoint cliques using the Hopfield neural network using our model called AdCliq. From the cliques, a set of intervals derived from the zones are obtained through the matching nodes in the single-row axis. The intervals are then mapped into a network of non-crossing nets using our previously developed tool called ESSR. The network is optimal in terms of minimum street congestion and number of doglegs, and this provides a reasonably good step towards the overall solution to the demand-supply problem.     

Chemical constituents of some basidiomycetes

The sterol, fatty acid and free amino acid (FAA) contents of some Basidiomycetes were determined. The overall sterol distribution was similar to that of other mushrooms, with ergosterol as the predominant sterol accompanied by the other closely related sterols. The mushrooms examined also contained high levels of fatty acids of which linoleic is the most prominent. Glutamic acid, valine and proline were the dominant FAA.