Metal-Specific Reactivity in Single-Atom Catalysts: CO Oxidation on 4d and 5d Transition Metals Atomically Dispersed on MgO

Understanding and tuning the catalytic properties of metals atomically dispersed on oxides are major stepping-stones toward a rational development of single-atom catalysts (SACs). Beyond individual showcase studies, the design and synthesis of structurally regular series of SACs opens the door to systematic experimental investigations of performance as a function of metal identity. Herein, a series of single-atom catalysts based on various 4d (Ru, Rh, Pd) and 5d (Ir, Pt) transition metals has been synthesized on a common MgO carrier. Complementary experimental (X-ray absorption spectroscopy) and theoretical (Density Functional Theory) studies reveal that, regardless of the metal identity, metal cations occupy preferably octahedral coordination MgO lattice positions under step-edges, hence highly confined by the oxide support. Upon exposure to O2-lean CO oxidation conditions, FTIR spectroscopy indicates the partial deconfinement of the monatomic metal centers driven by CO at precatalysis temperatures, followed by the development of surface carbonate species under steady-state conditions. These findings are supported by DFT calculations, which show the driving force and final structure for the surface metal protrusion to be metal-dependent, but point to an equivalent octahedral-coordinated M4+ carbonate species as the resting state in all cases. Experimentally, apparent reaction activation energies in the range of 96 ± 19 kJ/mol are determined, with Pt leading to the lowest energy barrier. The results indicate that, for monatomic sites in SACs, differences in CO oxidation reactivity enforceable via metal selection are of lower magnitude than those evidenced previously through the mechanistic involvement of adjacent redox centers on the oxide carrier, suggesting that tuning of the oxide surface chemistry is as relevant as the selection of the supported metal

Do mutual funds have consistency in their performance?

Using a comprehensive data set of 714 Chinese mutual funds from 2004 to 2015, the study investigates these funds’ performance persistence by using the Capital Asset Pricing model, the Fama-French three-factor model and the Carhart Four-factor model. For persistence analysis, we categorize mutual funds into eight octiles based on their one year lagged performance and then observe their performance for the subsequent 12 months. We also apply Cross-Product Ratio technique to assess the performance persistence in these Chinese funds. The study finds no significant evidence of persis- tence in the performance of the mutual funds. Winner (loser) funds do not continue to be winner (loser) funds in the subsequent time period. These findings suggest that future performance of funds cannot be predicted based on their past performance.info:eu-repo/semantics/publishedVersio

Coherent optical wavelength conversion via cavity-optomechanics

We theoretically propose and experimentally demonstrate coherent wavelength conversion of optical photons using photon-phonon translation in a cavity-optomechanical system. For an engineered silicon optomechanical crystal nanocavity supporting a 4 GHz localized phonon mode, optical signals in a 1.5 MHz bandwidth are coherently converted over a 11.2 THz frequency span between one cavity mode at wavelength 1460 nm and a second cavity mode at 1545 nm with a 93% internal (2% external) peak efficiency. The thermal and quantum limiting noise involved in the conversion process is also analyzed, and in terms of an equivalent photon number signal level are found to correspond to an internal noise level of only 6 and 4x10-3 quanta, respectively.Comment: 11 pages, 7 figures, appendi

Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches

Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats

This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets

Interactions among mitochondrial proteins altered in glioblastoma

Mitochondrial dysfunction is putatively central to glioblastoma (GBM) pathophysiology but there has been no systematic analysis in GBM of the proteins which are integral to mitochondrial function. Alterations in proteins in mitochondrial enriched fractions from patients with GBM were defined with label-free liquid chromatography mass spectrometry. 256 mitochondrially-associated proteins were identified in mitochondrial enriched fractions and 117 of these mitochondrial proteins were markedly (fold-change ≥2) and significantly altered in GBM (p ≤ 0.05). Proteins associated with oxidative damage (including catalase, superoxide dismutase 2, peroxiredoxin 1 and peroxiredoxin 4) were increased in GBM. Protein–protein interaction analysis highlighted a reduction in multiple proteins coupled to energy metabolism (in particular respiratory chain proteins, including 23 complex-I proteins). Qualitative ultrastructural analysis in GBM with electron microscopy showed a notably higher prevalence of mitochondria with cristolysis in GBM. This study highlights the complex mitochondrial proteomic adjustments which occur in GBM pathophysiology

IFNβ Protects Neurons from Damage in a Murine Model of HIV-1 Associated Brain Injury.

Infection with human immunodeficiency virus-1 (HIV-1) causes brain injury. Type I interferons (IFNα/β) are critical mediators of any anti-viral immune response and IFNβ has been implicated in the temporary control of lentiviral infection in the brain. Here we show that transgenic mice expressing HIV-1 envelope glycoprotein 120 in their central nervous system (HIVgp120tg) mount a transient IFNβ response and provide evidence that IFNβ confers neuronal protection against HIVgp120 toxicity. In cerebrocortical cell cultures, neuroprotection by IFNβ against gp120 toxicity is dependent on IFNα receptor 1 (IFNAR1) and the β-chemokine CCL4, as IFNAR1 deficiency and neutralizing antibodies against CCL4, respectively, abolish the neuroprotective effects. We find in vivo that IFNβ mRNA is significantly increased in HIVgp120tg brains at 1.5, but not 3 or 6 months of age. However, a four-week intranasal IFNβ treatment of HIVgp120tg mice starting at 3.5 months of age increases expression of CCL4 and concomitantly protects neuronal dendrites and pre-synaptic terminals in cortex and hippocampus from gp120-induced damage. Moreover, in vivo and in vitro data suggests astrocytes are a major source of IFNβ-induced CCL4. Altogether, our results suggest exogenous IFNβ as a neuroprotective factor that has potential to ameliorate in vivo HIVgp120-induced brain injury

Where It’s at Really Matters: In Situ In Vivo Vascular Endothelial Growth Factor Spatially Correlates with Electron Paramagnetic Resonance pO2 Images in Tumors of Living Mice

Purpose: Tumor microenvironments show remarkable tumor pO_{2} heterogeneity, as seen in prior EPR pO_{2} images (EPROI). pO_{2} correlation with hypoxia response proteins is frustrated by large rapid pO2 changes with position. Procedures: To overcome this limitation, biopsies stereotactically located in the EPROI were used to explore the relationship between vascular endothelial growth factor A (VEGF) concentrations in living mouse tumors and the local EPROI pO_{2}. Results: Quantitative ELISA VEGF concentrations correlated (p = 0.0068 to 0.019) with mean pO_{2}, median pO_{2}, and the fraction of voxels in the biopsy volume with pO_{2} less than 3, 6, and 10 Torr. Conclusions: This validates EPROI hypoxic fractions at the molecular level and provides a new paradigm for the assessment of the relationship, in vivo, between hypoxia and hypoxia response proteins. When translated to human subjects, this will enhance understanding of human tumor pathophysiology and cancer response to therapy

An integration of enhanced social force and crowd control models for high-density crowd simulation

Social force model is one of the well-known approaches that can successfully simulate pedestrians’ movements realistically. However, it is not suitable to simulate high-density crowd movement realistically due to the model having only three basic crowd characteristics which are goal, attraction, and repulsion. Therefore, it does not satisfy the high-density crowd condition which is complex yet unique, due to its capacity, density, and various demographic backgrounds of the agents. Thus, this research proposes a model that improves the social force model by introducing four new characteristics which are gender, walking speed, intention outlook, and grouping to make simulations more realistic. Besides, the high-density crowd introduces irregular behaviours in the crowd flow, which is stopping motion within the crowd. To handle these scenarios, another model has been proposed that controls each agent with two different states: walking and stopping. Furthermore, the stopping behaviour was categorized into a slow stop and sudden stop. Both of these proposed models were integrated to form a high-density crowd simulation framework. The framework has been validated by using the comparison method and fundamental diagram method. Based on the simulation of 45,000 agents, it shows that the proposed framework has a more accurate average walking speed (0.36 m/s) compared to the conventional social force model (0.61 m/s). Both of these results are compared to the real-world data which is 0.3267 m/s. The findings of this research will contribute to the simulation activities of pedestrians in a highly dense population