Ballistic Thermal Transistor of Dielectric Four-terminal Nanostructures

We report a theoretical model for a thermal transistor in dielectric four-terminal nanostructures based on mesoscopic ballistic phonon transport, in which a steady thermal flow condition of system is obtained to set up the temperature field effect of gate. In the environment, thermal flow shows the transisting behaviors at low temperatures: saturation, asymmetry, and rectification. The phenomena can be explained reasonably by the nonlinear variation of the temperature dependence of propagating phonon modes in terminals. The results suggest the possibility of the novel nano-thermal transistor fabrication

Kinetics and mechanism of oxidation of n-butylamine and 1,3-propanediamine by potassium ferrate

The kinetics of oxidation of n-butylamine and 1,3-propanediamine by home-made potassium ferrate(VI) at different conditions has been studied spectrophotometrically in the temperature range of 283.2-298.2 K. The results show first order dependence on potassium ferrate (VI) and on each reductant. The observed rate constant (kobs) decreases with the increase of [OH-], and the reaction rate has a negative fraction order with respect to [OH-]. A plausible mechanism is proposed and the rate equations derived from the mechanism was shown to fit all the experimental results. The rate constants of the rate-determining step and the thermodynamic activation parameters are calculated

MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals

Brain signals are important quantitative data for understanding physiological activities and diseases of human brain. Most existing studies pay attention to supervised learning methods, which, however, require high-cost clinical labels. In addition, the huge difference in the clinical patterns of brain signals measured by invasive (e.g., SEEG) and non-invasive (e.g., EEG) methods leads to the lack of a unified method. To handle the above issues, we propose to study the self-supervised learning (SSL) framework for brain signals that can be applied to pre-train either SEEG or EEG data. Intuitively, brain signals, generated by the firing of neurons, are transmitted among different connecting structures in human brain. Inspired by this, we propose MBrain to learn implicit spatial and temporal correlations between different channels (i.e., contacts of the electrode, corresponding to different brain areas) as the cornerstone for uniformly modeling different types of brain signals. Specifically, we represent the spatial correlation by a graph structure, which is built with proposed multi-channel CPC. We theoretically prove that optimizing the goal of multi-channel CPC can lead to a better predictive representation and apply the instantaneou-time-shift prediction task based on it. Then we capture the temporal correlation by designing the delayed-time-shift prediction task. Finally, replace-discriminative-learning task is proposed to preserve the characteristics of each channel. Extensive experiments of seizure detection on both EEG and SEEG large-scale real-world datasets demonstrate that our model outperforms several state-of-the-art time series SSL and unsupervised models, and has the ability to be deployed to clinical practice

Cell-type specific potent Wnt signaling blockade by bispecific antibody.

Cell signaling pathways are often shared between normal and diseased cells. How to achieve cell type-specific, potent inhibition of signaling pathways is a major challenge with implications for therapeutic development. Using the Wnt/β-catenin signaling pathway as a model system, we report here a novel and generally applicable method to achieve cell type-selective signaling blockade. We constructed a bispecific antibody targeting the Wnt co-receptor LRP6 (the effector antigen) and a cell type-associated antigen (the guide antigen) that provides the targeting specificity. We found that the bispecific antibody inhibits Wnt-induced reporter activities with over one hundred-fold enhancement in potency, and in a cell type-selective manner. Potency enhancement is dependent on the expression level of the guide antigen on the target cell surface and the apparent affinity of the anti-guide antibody. Both internalizing and non-internalizing guide antigens can be used, with internalizing bispecific antibody being able to block signaling by all ligands binding to the target receptor due to its removal from the cell surface. It is thus feasible to develop bispecific-based therapeutic strategies that potently and selectively inhibit signaling pathways in a cell type-selective manner, creating opportunity for therapeutic targeting