Beef-derived mesoporous carbon as highly efficient support for PtRuIr electrocatalysts and their high activity for CO and methanol oxidation

In this work, a low-cost and nitrogen-containing carbon with mesoporous pores and high surface area was synthesized by carbonizing a natural biomass precursor, i.e. beef. It is found that the prepared material has excellent textural properties such as high specific surface areas and large pore diameters. TEM images showed that the PtRuIr nanoparticles were well dispersed on the surface of carbonized beef (C-Beef). PtRuIr/C-Beef was highly active for methanol electro-oxidation. PtRuIr/C-Beef showed superior catalytic activity to PtRuIr/C, i.e. lower onset potential and higher oxidation current density. Cyclic voltammograms of CO electro-oxidation showed that PtRuIr/C-Beef catalyst was kinetically more active for CO electro-oxidation than PtRuIr deposited on conventional carbon support. The highly porous structure and low cost of carbonized beef can be widely used as support for highly dispersed metal nanoparticles to increase their electrochemical performance as electrocatalysts

Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration

Degenerate neural circuits perform the same function despite being structurally different. However, it is unclear whether neural circuits with interacting neuromodulator sources can themselves degenerate while maintaining the same neuromodulatory function. Here, we address this by computationally modeling the neural circuits of neuromodulators serotonin and dopamine, local glutamatergic and GABAergic interneurons, and their possible interactions, under reward/punishment-based conditioning tasks. The neural modeling is constrained by relevant experimental studies of the VTA or DRN system using, e.g., electrophysiology, optogenetics, and voltammetry. We first show that a single parsimonious, sparsely connected neural circuit model can recapitulate several separate experimental findings that indicated diverse, heterogeneous, distributed, and mixed DRNVTA neuronal signaling in reward and punishment tasks. The inability of this model to recapitulate all observed neuronal signaling suggests potentially multiple circuits acting in parallel. Then using computational simulations and dynamical systems analysis, we demonstrate that several different stable circuit architectures can produce the same observed network activity profile, hence demonstrating degeneracy. Due to the extensive D2-mediated connections in the investigated circuits, we simulate the D2 receptor agonist by increasing the connection strengths emanating from the VTA DA neurons. We found that the simulated D2 agonist can distinguish among sub-groups of the degenerate neural circuits based on substantial deviations in specific neural populations’ activities in reward and punishment conditions. This forms a testable model prediction using pharmacological means. Overall, this theoretical work suggests the plausibility of degeneracy within neuromodulator circuitry and has important implications for the stable and robust maintenance of neuromodulatory functions

Application of stratified emulsion splitting technology in highly hard nuclear cataract surgery

AIM:To explore safety and effectiveness of stratified emulsion splitting technology in highly hard nuclear cataract ultrasonic emulsification. METHODS: Totally 43 cases(47 eyes)of highly hard nuclear cataract was performed cataract extraction combined IOL implantation with stratified emulsion splitting cataract ultrasonic emulsification technology. RESULTS:Postoperative visual acuity 1 day, 1 week and 1 month best-corrected visual acuity ≥0.5 was accounted for 70.21%, 87.23% and 89.36%. Intraoperative capsule rupture was found in 2 eyes. Corneal mild edema was found in 7 eyes(14.89%)after the first l day post-operation. CONCLUSION:Stratified emulsion splitting technique has a practical application with little tissue damage, low capsular rupture rate and few complications for highly hard nuclear cataract patients and can bring a desirable outcome

Neural dynamics implement a flexible decision bound with a fixed firing rate for choice: a model-based hypothesis

Decisions are faster and less accurate when conditions favour speed, and are slower and more accurate when they favour accuracy. This speed-accuracy trade-off (SAT) can be explained by the principles of bounded integration, where noisy evidence is integrated until it reaches a bound. Higher bounds reduce the impact of noise by increasing integration times, supporting higher accuracy (vice versa for speed). These computations are hypothesized to be implemented by feedback inhibition between neural populations selective for the decision alternatives, each of which corresponds to an attractor in the space of network states. Since decision-correlated neural activity typically reaches a fixed rate at the time of commitment to a choice, it has been hypothesized that the neural implementation of the bound is fixed, and that the SAT is supported by a common input to the populations integrating evidence. According to this hypothesis, a stronger common input reduces the difference between a baseline firing rate and a threshold rate for enacting a choice. In simulations of a two-choice decision task, we use a reduced version of a biophysically-based network model (Wong & Wang, 2006) to show that a common input can control the SAT, but that changes to the threshold-baseline difference are epiphenomenal. Rather, the SAT is controlled by changes to network dynamics. A stronger common input decreases the model’s effective time constant of integration and changes the shape of the attractor landscape, so the initial state is in a more error-prone position. Thus, a stronger common input reduces decision time and lowers accuracy. The change in dynamics also renders firing rates higher under speed conditions at the time that an ideal observer can make a decision from network activity. The difference between this rate and the baseline rate is actually greater under speed conditions than accuracy conditions, suggesting that the bound is not implemented by firing rates per se

Selenium-functionalized carbon as a support for platinum nanoparticles with improved electrochemical properties for the oxygen reduction reaction and CO tolerance

Using selenium-functionalized carbon as supports, platinum nanoparticles were uniformly dispersed on the carbon surface, and showed improved electrochemical properties for the oxygen reduction reaction. At the same time the CO tolerance is improved. The method provides a new route for functionalization of the carbon surface on which to disperse noble metal nanoparticles for use as electrocatalysts in the oxygen reduction reaction.Web of Scienc