There are several methods in the literature to find the fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems. However, in all these methods, it is assumed that the product of two trapezoidal (triangular) fuzzy numbers will also be a trapezoidal (triangular) fuzzy number. Fan et al. (“Generalized fuzzy linear programming for decision making under uncertainty: Feasibility of fuzzy solutions and solving approach”, Information Sciences, Vol. 241, pp. 12–27, 2013) proposed a method for finding the fuzzy optimal solution of FFLP problems without considering this assumption. In this paper, it is shown that the method proposed by Fan et al. (2013) suffer from errors and to overcome these errors, a new method (named as Mehar method) is proposed for solving FFLP problems by modifying the method proposed by Fan et al. (2013) . To illustrate the proposed method, some numerical problems are solved.

Global energy agencies and commissions report a sharp increase in energy demand based on commercial, industrial, and residential activities. At this point, we need energy-efficient and high-performance systems to maintain a sustainable environment. More than 30% of the generated electricity has been consumed by HVAC-R units, and heat exchangers are the main components affecting the overall performance. This study combines experimental measurements, numerical investigations, and ANN-aided optimization studies to determine the optimal operating conditions of an industrial shell and tube heat exchanger system. The cold/hot stream temperature level is varied between 10 ℃ and 50 ℃ during the experiments and numerical investigations. Furthermore, the flow rates are altered in a range of 50–500 L/h to investigate the thermal and hydraulic performance under laminar and turbulent regime conditions. The experimental and numerical results indicate that U-tube bundles dominantly affect the total pumping power; therefore, the energy consumption experienced at the cold side is about ten times greater the one at the hot side. Once the required data sets are gathered via the experiments and numerical investigations, ANN-aided stochastic optimization algorithms detected the C10H50 scenario as the optimal operating case when the cold and hot stream flow rates are at 100 L/h and 500 L/h, respectively.

Water splitting has gained significant attention as a means to produce clean and sustainable hydrogen fuel through the electrochemical or photoelectrochemical decomposition of water. Efficient and cost-effective water splitting requires the development of highly active and stable catalysts for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Carbon nanomaterials, including carbon nanotubes, graphene, and carbon nanofibers, etc., have emerged as promising candidates for catalyzing these reactions due to their unique properties, such as high surface area, excellent electrical conductivity, and chemical stability. This review article provides an overview of recent advancements in the utilization of carbon nanomaterials as catalysts or catalyst supports for the OER and HER in water splitting. It discusses various strategies employed to enhance the catalytic activity and stability of carbon nanomaterials, such as surface functionalization, hybridization with other active materials, and optimization of nanostructure and morphology. The influence of carbon nanomaterial properties, such as defect density, doping, and surface chemistry, on electrochemical performance is also explored. Furthermore, the article highlights the challenges and opportunities in the field, including scalability, long-term stability, and integration of carbon nanomaterials into practical water splitting devices. Overall, carbon nanomaterials show great potential for advancing the field of water splitting and enabling the realization of efficient and sustainable hydrogen production.

Definitive diagnosis of Craniosynostosis (CS) with computed tomography (CT) is readily available, however, exposure to ionizing radiation is often a hard stop for parents and practitioners. Lowering head CT radiation exposure helps mitigate risks and improves diagnostic utilization. The purpose of the study is to quantify radiation exposure from head CT in patients with CS using a ‘new’ (ultra-low dose) protocol; compare prior standard CT protocol; summarize published reports on cumulative radiation doses from pediatric head CT scans utilizing other low-dose protocols. A retrospective study was conducted on patients undergoing surgical correction of CS, aged less than 2 years, between August 2014 and February 2022. Cumulative effective dose (CED) in mSv was calculated, descriptive statistics were performed, and mean ± SD was reported. A literature search was conducted describing cumulative radiation exposure from head CT in pediatric patients and analyzed for ionizing radiation measurements. Forty-four patients met inclusion criteria: 17 females and 27 males. Patients who obtained head CT using the ‘New’ protocol resulted in lower CED exposure of 0.32 mSv ± 0.07 compared to the prior standard protocol at 5.25 mSv ± 2.79 (p < 0.0001). Five studies specifically investigated the reduction of ionizing radiation from CT scans in patients with CS via the utilization of low-dose CT protocols. These studies displayed overall CED values ranging from 0.015 mSv to 0.77 mSv. Our new CT protocol resulted in 94% reduction of ionizing radiation. Ultra-low dose CT protocols provide similar diagnostic data without loss of bone differentiation in CS and can be easily incorporated into the workflow of a children’s hospital.

Gold nanoparticles (AuNPs) have been known to possess exceptional electric, biochemical, and optical characteristics and are ‘the topic of discussion’ these days, especially relating to the field of biomedicine. Several plants, bacteria, and fungi have been utilized for the generation of AuNPs, besides other physical and chemical methods. While some studies have been reported with gold nanoparticles, less are aimed at fungi and its optimization factors. These parameters can allow us to design AuNPs of our choice depending on the use. The present review focuses on and inspects AuNPs with green synthesis through fungus optimization parameters followed by applications, aiming specifically at their antibacterial activity. Their antibacterial characteristics can open new doors for the pharmaceutical industry in the future.