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Potential limiting factor on engaged research: Academic evaluation systems
In-depth analysis of FeNi-based nanoparticles for the oxygen evolution reaction
Abstract This study investigates the effect of varying iron-to-nickel ratios on the catalytic performance of Fe-Ni oxide nanoparticles (NPs) for the oxygen evolution reaction (OER). Addressing the issue of high energy wastage due to large overpotentials in OER, we synthesized and characterized different NP catalysts with different Fe: Ni oxide ratios. Transmission Electron Microscopy (TEM), Energy Dispersive X-ray Spectroscopy (EDS), and X-ray Diffraction (XRD) were employed to determine the morphology, elemental and phase composition of the NPs. Furthermore, in-depth profiling with X-ray Photoelectron Spectroscopy (XPS) and Hard X-ray Photoelectron Spectroscopy (HAXPES) revealed that iron predominantly exists as oxide, while nickel exhibits both metallic and oxidic forms depending on the Fe content. XPS indicated an enrichment of iron at the NP surface, whereas HAXPES and EDS data agreed on the bulk stoichiometry. The assessment of the catalytic activity via cyclic voltammetry (CV) showed that the Fe: Ni ratio of 2:3 exhibited superior performance, characterized by lower overpotential and a smaller Tafel slope.
Effect of heating temperature on pore structure of briquette coal using SEM, NMR, N2/CH4 adsorption-desorption analyses
Analysis of midsole gait in running shoes with various 3d printed biomimetic structure
Comparison of machine learning models for rock UCS prediction using measurement while drilling data
Publisher Correction: Efficient and rapid identification of tropical maize inbred lines tolerant to waterlogging stress
Examining the effects of extremely low-frequency magnetic fields on cognitive functions and functional brain markers in aged mice
Genomic divergence across the tree of life
Nucleotide sequence data are being harnessed to identify species, even in cases in which organisms themselves are neither in hand nor witnessed. But how genome-wide sequence divergence maps to species status is far from clear. While gene sequence divergence is commonly used to delineate bacterial species, its correspondence to established species boundaries has yet to be explored across eukaryotic taxa. Because the processes underlying gene flow differ fundamentally between prokaryotes and eukaryotes, these domains are likely to differ in the relationship between reproductive isolation and genome-wide sequence divergence. In prokaryotes, homologous recombination, the basis of gene flow, depends directly on the degree of genomic sequence divergence, whereas in sexually reproducing eukaryotes, reproductive incompatibility can stem from changes in very few genes. Guided by measures of genome-wide sequence divergence in bacteria, we gauge how genomic criteria correspond to species boundaries in eukaryotes. In recognized species of eukaryotes, levels of gene sequence divergence within species are typically very small, averaging <1% across protein-coding regions in most animals, plants, and fungi. There are even instances in which divergence between sister species is the same or less than that among conspecifics. In contrast, bacterial species, defined as populations exchanging homologous genes, show levels of divergence both within and between species that are considerably higher. Although no single threshold delineates species, eukaryotic populations with >1% genome-wide sequence divergence are likely separate species, whereas prokaryotic populations with 1% divergence are still able to recombine and thus can be considered the same species.
Unlocking the therapeutic potential of unexplored phytocompounds as hepatoprotective agents through integration of network pharmacology and in-silico analysis
Enhancing fetal ultrasound image quality and anatomical plane recognition in low-resource settings using super-resolution models
The effects of photosynthetic rate on respiration in light, starch/sucrose partitioning, and other metabolic fluxes within photosynthesis
Characterization and machine learning analysis of hybrid alumina-copper oxide nanoparticles in therminol 55 for medium temperature heat transfer fluid
Abstract Efficient heat dissipation is crucial for various industrial and technological applications, ensuring system reliability and performance. Advanced thermal management systems rely on materials with superior thermal conductivity and stability for effective heat transfer. This study investigates the thermal conductivity, viscosity, and stability of hybrid Al2O3-CuO nanoparticles dispersed in Therminol 55, a medium-temperature heat transfer fluid. The nanofluid formulations were prepared with CuO-Al2O3 mass ratios of 10:90, 20:80, and 30:70 and tested at nanoparticle concentrations ranging from 0.1 wt% to 1.0 wt%. Experimental results indicate that the hybrid nanofluids exhibit enhanced thermal conductivity, with a maximum improvement of 32.82% at 1.0 wt% concentration, compared to the base fluid. However, viscosity increases with nanoparticle loading, requiring careful optimization for practical applications. To further analyze and predict thermal conductivity, a Type-2 Fuzzy Neural Network (T2FNN) was employed, demonstrating a correlation coefficient of 96.892%, ensuring high predictive accuracy. The integration of machine learning enables efficient modeling of complex thermal behavior, reducing experimental costs and facilitating optimization. These findings provide insights into the potential application of hybrid nanofluids in solar thermal systems, heat exchangers, and industrial cooling applications.
Correction for Qin et al., A signaling molecule from intratumor bacteria promotes trastuzumab resistance in breast cancer cells
Sex-specific attenuation of constant light-induced memory impairment and Clock gene expression in brain in hepatic Npas2 knockout mice
Abstract NPAS2 (Neuronal PAS Domain Protein 2) is a component of the core circadian clock and the coordinated activity between central brain and peripheral liver clock proteins postulated to be instrumental for linking behaviour and metabolism. We investigated a conditional liver-specific knockout mouse model (Npas2-/- or cKO) to explore its function in activity, circadian rhythms and cognition (novel object recognition-NOR). Circadian rhythms showed no genotype differences. Constant-light reduced NOR in floxxed controls but remarkably not in Npas2-/- mice, particularly females. Consistent with entrainment of systemic and central circadian biology, N pas2-/- mice showed altered expression of circadian gene Clock in frontal cortex. Sex differences independent of genotype were found in expression of circadian genes Clock, Bmal1 and Reverb-b in brain. Sex differences in Clock were absent in N pas2-/- mice. Females showed greater period length and phase response to constant light independently of genotype. The data suggest that a role for peripheral NPAS2 in constant light-induced memory impairment in females, and potential mediation by altered cortical circadian Clock gene expression, merit further investigation. These findings have implications for the interaction between peripheral and central circadian clocks, circadian sex differences and the deleterious effects of constant light on cognition.