Evapotranspiration Modeling Using Different Tree Based Ensembled Machine Learning Algorithm

Water Resources Management - The present study investigates and evaluate the scope and potential of modern computing tools and techniques such as ensembled machine learning methods in estimating...     

A Contemporary Survey on IoT Based Smart Cities: Architecture,Applications, and Open Issues

Wireless Personal Communications - Internet of Things (IoT) is one of the emerging technologies, which is widely used across the globe. As the idea of a smart city was founded, IoT has been...     

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.     

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.     

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.     

The corrosion of mild and stainless steel in alkaline anaerobic conditions representing the Belgian “supercontainer” concept and the Swiss L/ILW repository

Deep geological repositories for radioactive waste contain metallic materials, either used to construct disposal canisters or as low-/intermediate-level waste (L/ILW). The safety relevance of corrosion is linked to canister lifetime in the former case and gas generation in the latter. More specifically, the Belgian “supercontainer” concept envisages mild steel for the used fuel disposal canister, and in the case of the Swiss L/ILW repository, mild steels are the largest metallic waste component due to the decommissioning of civilian power-generating facilities. For these circumstances, the corrosion environment is dominated by the chemistry of cement, which is used as buffer or backfill material. The corrosion behaviour of mild steel in anoxic environments was studied through the analysis of the hydrogen end-product. Hydrogen analysis was conducted by periodically purging the cell head-space and analysing the gas using a solid-state hydrogen sensor. While this method is limited to providing only uniform corrosion rates averaged over periods of time, ranging from weeks to months, it provides excellent resolution and sensitivity. The test cell environments were matched against the anticipated Belgian high-level waste and Swiss L/ILW repository environments, and also against experiments that have been conducted by other researchers for comparative purposes. Samples were exposed to synthetic cement pore waters, representing fresh and degraded cement. In young cement waters, the formation of initial corrosion products resulted in steel wire corrosion rates of the order of µm/year, which, at 80°C rapidly declined to ∼10 nm/year. In contrast, SA516 grade 70 steel plate corroded much more slowly under similar conditions. In aged cement waters, initial corrosion rates were higher but declined faster towards a longer-term rate of ∼10 nm/year. 316L stainless steel, embedded in cementitious material, corroded at a rate of <1 nm/year at 50°C.     

The Emerging Regulatory Role of Circular RNAs in Periodontal Tissues and Cells

Periodontitis is a chronic complex inflammatory disease associated with a destructive host immune response to microbial dysbiosis, leading to irreversible loss of tooth-supporting tissues. Regeneration of functional periodontal soft (periodontal ligament and gingiva) and hard tissue components (cementum and alveolar bone) to replace lost tissues is the ultimate goal of periodontal treatment, but clinically predictable treatments are lacking. Similarly, the identification of biomarkers that can be used to accurately diagnose periodontitis activity is lacking. A relatively novel category of molecules found in oral tissue, circular RNAs (circRNAs) are single-stranded endogenous, long, non-coding RNA molecules, with covalently circular-closed structures without a 5’ cap and a 3’ tail via non-classic backsplicing. Emerging research indicates that circRNAs are tissue and disease-specific expressed and have crucial regulatory functions in various diseases. CircRNAs can function as microRNA or RNA binding sites or can regulate mRNA. In this review, we explore the biogenesis and function of circRNAs in the context of the emerging role of circRNAs in periodontitis pathogenesis and the differentiation of periodontal cells. CircMAP3K11, circCDK8, circCDR1as, circ_0062491, and circ_0095812 are associated with pathological periodontitis tissues. Furthermore, circRNAs are expressed in periodontal cells in a cell-specific manner. They can function as microRNA sponges and can form circRNA–miRNA–mRNA networks during osteogenic differentiation for periodontal-tissue (or dental pulp)-derived progenitor cells.