Explore the vast range of titles available.

In this study, a magnetic photocatalyst, Fe 3 O 4 –SiO 2 –EN (FSE) doped with Zn–Al–LDH nanocomposites (FSEZAL), was successfully synthesized via the sol–gel method. The catalyst was then applied for the removal of penicillin G (PNG) under solar, visible, and UV irradiation. The optimal conditions for achieving 100% PNG removal were determined to be an initial PNG concentration of 25 mg/L, a solution pH of 3–5, an FSEZAL dose of 0.4 g/L, and a reaction time of 60 min. The study also examined the degradation mechanism and oxidation pathway. The experimental observations highlighted that the catalyst had high reusability, with only a slight decrease in PNG degradation ratios after five consecutive cycles (from 100 to 94.3%). Under UV and visible radiation, PNG (25 mg/L) was completely degraded, while sunlight exposure achieved 90.1% removal and required 100 min for full degradation. At the beginning of the process, the BOD 5 /COD (five-day biochemical oxygen demand to total organic carbon) and BOD₅/TOC (total organic carbon) ratios were 0.22 and 0.73, respectively, indicating non-biodegradable wastewater. By the end of the process, these ratios increased to 0.73 and 1.37, reflecting complete mineralization of the wastewater. Toxicity assays performed with Daphnia magna confirmed complete detoxification of the PNG solution, in contrast to the adsorption process, which lowered toxicity by only 30%. According to scavenger tests, the degradation of the studied pollutant involved hydroxyl radical ( · OH), superoxide radical ( · O 2 − ), electron (e − ), and hole (h + ), among which · OH was the most influential. In conclusion, it can be stated that the evaluated process has the potential to effectively eliminate a range of antibiotics from water-based solutions.

High-speed trains are very sensitive due to their very high speed of movement, so the slightest defect or fault is not acceptable. This sensitivity necessitates the development of advanced and robust control strategies capable of handling dynamic uncertainties, nonlinearities, and external disturbances commonly present in high-speed rail systems. To achieve this, the control system must be very precise and eliminate the smallest errors. In this paper, a very precise nonlinear controller is designed by combining the TSK type-2 fuzzy system with the sliding mode control (SMC) method. The integration leverages the robustness of sliding mode control and the superior uncertainty modeling capability of TSK Type-2 fuzzy logic, aiming to overcome the limitations of conventional SMC and Type-1 fuzzy approaches. The TSK Type-2 fuzzy system can estimate sliding surfaces well and the control system will be very fast and accurate. In the simulation section, an attempt has been made to apply the parameters of a real train in order to evaluate it more accurately with the proposed control system. The results show the high efficiency of the proposed control system so that the RMSE of the control system reaches less than 1%. Compared to other existing control methods, the proposed controller demonstrates significant improvements in tracking accuracy, vibration reduction, and control effort minimization. Theoretical analysis based on Lyapunov stability further confirms the stability and reliability of the closed-loop system.

This work investigates the utilization of ensemble machine learning methods in forecasting the distribution of chemical concentrations in membrane separation system for removal of an impurity from water. Mass transfer was evaluated using CFD and machine learning performed numerical simulations. A membrane contactor was employed for the separation and mass transfer analysis for the removal of organic molecules from water. The process is simulated via computational fluid dynamics and machine learning. Utilizing a dataset of over 25,000 data points with r(m) and z(m) as inputs, four tree-based learning algorithms were employed: Decision Tree (DT), Extremely Randomized Trees (ET), Random Forest (RF), and Histogram-based Gradient Boosting Regression (HBGB). Hyper-parameter optimization was conducted using Successive Halving, a method aimed at efficiently allocating computational resources to optimize model performance. The ET model emerged as the top performer, with R² of 0.99674. The ET model exhibited a RMSE of 37.0212 mol/m³ and a MAE of 19.6784 mol/m³. The results emphasize the capability of ensemble machine learning techniques to accurately estimate solute concentration profiles in membrane engineering applications.

Palladium nanoparticles were supported on L-H-functionalized KIT-6 (KIT-6@L-H-Pd) and evaluated using various characterization techniques such as TGA, FT-IR, SEM, XRD, EDS, and BET. KIT-6@L-H-Pd showed excellent catalytic performance as a recyclable nanocatalyst for the oxidation of sulfides to sulfoxides and the amination of aryl halides. This approach offers multiple benefits, including the use of readily available and cost-effective materials, a straightforward procedure, short reaction durations, high yields, and a catalyst that is easy to separate and reuse. Additionally, the catalyst can be recovered and reused multiple times without significant palladium loss or alteration in its activity.

Psoriasis is a long-lasting inflammatory skin condition that impacts millions globally. The occurrence of this disorder differs significantly across various areas, resulting from a complex interplay of genetic and environmental influences. In psoriasis, the pathogenesis represents a complex interaction of innate and adaptive immunity that plays a significant role in the disease manifestation process. Many genetic factors predispose to psoriasis, which is considered a polygenic disease. Several genes concerning pathways like NF-κB and PI3K/Akt that modulate the amplification of inflammatory response and keratinocyte dysregulation have been elaborated in the light of their differential expression, susceptibility loci, and polymorphisms. Such genetic insights could open a whole new avenue for precision medicine in which biomarkers and gene-targeting therapies are promising options for personalized treatment. This review emphasizes the need for complex investigations into psoriasis, from molecular mechanisms to clinical manifestations, to bridge the gap between basic research and therapeutic development by furthering the understanding of psoriasis and paving the way for innovative treatments addressing skin lesions and systemic effects.

Over the last decade, there has been a promising increase in market trends toward plant proteins. This trend is expected to persist in coming years due to more sustainability, lower environmental footprints, and health benefits associated with plant proteins along with the recent surge in veganism. To meet market demand, plant-based proteins must compete with or outperform conventional animal proteins in terms of quality and functionality. However, plant proteins possess lower digestibility/solubility, lower water/oil holding capacity, and unfavorable emulsifying/foaming properties, which limit their bioavailability and functionality. The presence of anti-nutrients and non-digestible polysaccharides also results in lower quality, making it necessary to modify these properties through chemical, physical, and enzymatic methods. Food industries prefer physical and biological approaches over chemical approaches due to clean label demand and toxicity issues encountered while applying chemical methods. In this article, we investigate research progress in plant protein modification area using physical approaches comprising ultrasonication, pulse electric field, microwaves, extrusion, gamma irradiation, high-pressure processing, radiofrequency, and cold plasma. This review also highlights associated functionality challenges and summarizes recent studies in an attempt to improve plant protein functionality for obtaining multifunctional proteins. Graphical Abstract

Three-dimensional food printing is an inchoate industry with enormous potential for raising customized food. It offers many advantages as it allows the formulation of complex geometries and permits personalized nutrition to meet special dietary needs without much altering the taste preferences and widens the use of available food sources. A keen surge in this technology has opened the doors to better value addition by supplementing existing processes with 3D food printing and utilizing non-traditional food source for 3D ink formulations. A good understanding of the different properties of ingredients for formulation of 3D ink is necessary to better understand the behavior and properties of the ink system directly affecting the quality of the final printed product. The research and development in the field of ink formulation utilizing non-traditional food ingredients (plant and algae based) is of paramount relevance. In the present article, we review the recent advancements in plant- and algae-based functional ingredients (non-traditional food sources), either added in small amounts or utilized as base material for application in 3D ink formulations. This review spotlights the new ingredients, their physiological function, and impact upon addition on rheological, structural, and printing characteristics of the product. 3D food printing with its application to deliver customized food and personalized nutrition has proven outstanding. Highlighting the advancements in the area of edible ink ingredients and summarizing the existing studies will build the foundation for future studies.

Pregnancy induces significant physiological and hormonal changes that can affect oral health. These changes can worsen existing oral conditions or lead to the development of new conditions such as pregnancy gingivitis, periodontal diseases, and dental caries. This review explores the various factors responsible for these conditions, such as changes in immunological response, oral environment, increased levels of steroid hormones, and nutritional deficits. Periodontal diseases that are left untreated during pregnancy are also seen to be associated with adverse maternal and fetal outcomes. On the other hand, dental caries is further exacerbated due to salivary changes in the oral cavity of pregnant women. Hence, a comprehensive management of oral health during pregnancy should focus on prevention, patient education, and safe management of existing conditions. Dental treatment should be provided following the recommended guidelines for the different stages of pregnancy, with the second trimester being the safest for most procedures. A strong collaboration between dental professionals and prenatal care providers is essential for ensuring optimal maternal and fetal health. However, the presence of socioeconomic challenges, such as a lack of awareness and restricted access to dental treatment, underscores the need for developing targeted interventions and innovative solutions for delivering oral health education and preventive care to pregnant women.

Metamaterials are periodic structures made by repeating a unit cell. Such a structure shows frequency-specific wave attenuation behaviour. In this work, a 2D metamaterial foundation is proposed for the seismic protection of buildings. The paramount challenge is to offer low frequency attenuation (~ 2–8 Hz), which is the dominant excitation during an earthquake. Based on the parametric study performed, a new type of metamaterial structure was proposed. It was found that the foundation consisting of repeating circular scatterers made of steel and plumbum embedded in rubber matrix can provide low and wide frequency wave attenuation from 2.6 to 7.8 Hz. The computational model of the structure was subjected to transient excitation against three pre-recorded earthquake excitations. The result showed that the novel foundation can resist the propagation of the seismic wave to the structure. Further, the response of a 2D building frame with metamaterial foundation was compared to a concrete foundation exposed to different earthquake excitations. The results are very promising as the frame vibration on the metamaterial foundation was significantly less than the same frame on the concrete foundation. The presented work opens the path to new research and development of seismic metamaterial foundation for earthquake attenuation.

Rheumatoid arthritis (RA) is a persistent autoimmune disorder that is characterized by joint inflammation, discomfort, and impairment. Despite the existence of several therapeutic approaches, their effectiveness is often restricted and may be linked to unfavorable side effects. Consequently, there has been growing interest in investigating naturally derived compounds as plausible therapeutic agents for RA disease. The objective of this review is to summarize the existing preclinical and clinical evidence regarding the efficacy of naturally extracted compounds and plant extracts in the treatment of RA, focusing on their anti-inflammatory, anti-oxidative, and immunomodulatory properties. Some of the problems with using natural chemicals are the uneven quality of commercially available preparations and the poor bioavailability of these compounds. Future investigations should focus on improving the formulations, conducting thorough clinical trials, and exploring different techniques to fully utilize the intrinsic potential of naturally derived chemicals in treating RA.