Goal-Oriented Scheduling in Sensor Networks with Application Timing Awareness

Taking inspiration from linguistics, the communications theoretical community has recently shown a significant recent interest in pragmatic , or goal-oriented, communication. In this paper, we tackle the problem of pragmatic communication with multiple clients with different, and potentially conflicting, objectives. We capture the goal-oriented aspect through the metric of Value of Information (VoI), which considers the estimation of the remote process as well as the timing constraints. However, the most common definition of VoI is simply the Mean Square Error (MSE) of the whole system state, regardless of the relevance for a specific client. Our work aims to overcome this limitation by including different summary statistics, i.e., value functions of the state, for separate clients, and a diversified query process on the client side, expressed through the fact that different applications may request different functions of the process state at different times. A query-aware Deep Reinforcement Learning (DRL) solution based on statically defined VoI can outperform naive approaches by 15-20%

Electric vehicle battery charging controller

The present invention provides an electric vehicle charging controller. The charging controller comprises a first interface connectable to an electric vehicle charge source for receiving a charging current, a second interface connectable to an electric vehicle for providing the charging current to a battery management system in the electric vehicle to charge a battery therein, a first communication unit for receiving a charging message via a communication network, and a control unit for controlling a charging current provided from the charge source to the electric vehicle, the controlling at least in part being performed in response to a first information associated with a charging message received by the first communication unit</p

A high-affinity, bivalent PDZ domain inhibitor complexes PICK1 to alleviate neuropathic pain

Maladaptive plasticity involving increased expression of AMPA‐type glutamate receptors is involved in several pathologies, including neuropathic pain, but direct inhibition of AMPARs is associated with side effects. As an alternative, we developed a cell‐permeable, high‐affinity (~2 nM) peptide inhibitor, Tat‐P$_4$‐(C5)$_2$, of the PDZ domain protein PICK1 to interfere with increased AMPAR expression. The affinity is obtained partly from the Tat peptide and partly from the bivalency of the PDZ motif, engaging PDZ domains from two separate PICK1 dimers to form a tetrameric complex. Bivalent Tat‐P$_4$‐(C5)$_2$ disrupts PICK1 interaction with membrane proteins on supported cell membrane sheets and reduce the interaction of AMPARs with PICK1 and AMPA‐receptor surface expression in vivo. Moreover, Tat‐P$_4$‐(C5)$_2$ administration reduces spinal cord transmission and alleviates mechanical hyperalgesia in the spared nerve injury model of neuropathic pain. Taken together, our data reveal Tat‐P$_4$‐(C5)$_2$ as a novel promising lead for neuropathic pain treatment and expand the therapeutic potential of bivalent inhibitors to non‐tandem protein–protein interaction domains