Summary The hippocampal-entorhinal system is important for spatial and relational memory tasks. We formally link these domains, provide a mechanistic understanding of the hippocampal role in generalization, and offer unifying principles underlying many entorhinal and hippocampal cell types. We propose medial entorhinal cells form a basis describing structural knowledge, and hippocampal cells link this basis with sensory representations. Adopting these principles, we introduce the Tolman-Eichenbaum machine (TEM). After learning, TEM entorhinal cells display diverse properties resembling apparently bespoke spatial responses, such as grid, band, border, and object-vector cells. TEM hippocampal cells include place and landmark cells that remap between environments. Crucially, TEM also aligns with empirically recorded representations in complex non-spatial tasks. TEM also generates predictions that hippocampal remapping is not random as previously believed; rather, structural knowledge is preserved across environments. We confirm this structural transfer over remapping in simultaneously recorded place and grid cells.

Acidic dissolution of transition metals from Pt based alloy catalysts for oxygen reduction reaction (ORR) is an unavoidable process during fuel cell operation. In this work we studied the effect of acid treatment of graphene-supported Pt 1 Ni x (x ) 0, 0.25, 0.5, 1, and 2) alloys on the kinetics of the ORR in both alkaline and acidic solutions together with the generation of OH radicals in alkaline solutions. The alloy nanoparticles were synthesized through coimpregnation and chemical reduction. The electronic and structural features of the alloy were characterized by X-ray photoelectron spectroscopy, X-ray diffraction, transmission electron microscopy, and high-resolution transmission electron microscopy. The ORR performances were studied using cyclic voltammetry and rotating ring disk electrode techniques in 0.05 M H 2 SO 4 and 0.1 M NaOH, respectively. The alloy catalysts were more active than pure Pt toward ORR, and after acid treatment the ORR activity of Pt-Ni alloy was enhanced in both acidic and alkaline media. The maximum activity of the Pt-based catalysts was found with ca. 50 atom % Ni content in the alloys (Pt 1 Ni 1 @graphene). OH radicals were generated through dissociation of hydroperoxide at the catalysts' surface and detected by fluorescence technique using terephthalic acid as capture reagent, which readily reacts with OH radical to produce highly fluorescent product, 2-hydroxyterephthalic acid. More OH radicals were found to be generated at Pt 1 Ni 1 @graphene catalyst. This work may be valuable in the design of electrocatalysts with higher ORR activity but lower efficiency of OH radical generation.

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Biological growth is driven by numerous functions, such as hormones and mineral nutrients, and is also involved in various ecological processes. Therefore, it is necessary to accurately capture the growth trajectory of various species in ecosystems. A new sigmoidal growth (NSG) model is presented here for describing the growth of animals and plants when the assumption is that the growth rate curve is asymmetric. The NSG model was compared with four classic sigmoidal growth models, including the logistic equation, Richards, Gompertz, and ontogenetic growth models. Results indicated that all models fit well with the empirical growth data of 12 species, except the ontogenetic growth model, which only captures the growth of animals. The estimated maximum asymptotic biomass wmax of plants from the ontogenetic growth model was not reliable. The experiment result shows that the NSG model can more precisely estimate the value and time of reaching maximum biomass when growth rate becomes close to zero near the end of growth. The NSG model contains three other parameters besides the value and time of reaching maximum biomass, and thereby, it can be difficult to assign initial values for parameterization using local optimization methods (e.g., using Gauss–Newton or Levenberg–Marquardt methods). We demonstrate the use of a differential evolution algorithm for resolving this issue efficiently. As such, the NSG model can be applied to describing the growth patterns of a variety of species and estimating the value and time of achieving maximum biomass simultaneously.

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Separation and purification of graphene oxide (GO) prepared from chemical oxidation of flake graphite and ultrasonication by capillary electrophoresis (CE) was demonstrated. CE showed the ability to provide high-resolution separations of GO fractionations with baseline separation. The GO fractionations after CE were collected for Raman spectroscopy, atomic force microscopy, and transmission electron microscopy characterizations. GO nanoparticles (unexfoliated GO) or stacked GO sheets migrated toward the anode, while the thin-layer GO sheets migrated toward the cathode. Therefore, CE has to be performed twice with a reversed electric field to achieve a full separation of GO. This separation method was suggested to be based on the surface charge of the GO sheets, and a separation model was proposed. This study might be valuable for fabrication of GO or graphene micro- or nanodevices with controlled thickness.

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