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With the increasing integration of renewable energy sources, distributed shared energy storage (DSES) systems play a critical role in enhancing power system flexibility, operational resilience, and energy sustainability. However, conventional scheduling methods often suffer from excessive communication burdens, limited scalability, and poor real-time responsiveness, especially when handling fast-changing frequency regulation signals and fluctuating renewable energy outputs. To address these challenges, this paper proposes a consensus-driven distributed online convex optimization method that enables a decentralized scheduling of energy storage units by leveraging the consensus algorithm for local decision-making while maintaining global consistency. Additionally, an adaptive event-triggered mechanism is designed to dynamically adjust the communication frequency based on system state variations, reducing redundant information exchange and ensuring convergence and stability in a fully distributed environment. Simulation results on the IEEE 14-bus test system show that the strategy reduces the communication load by 33–60% and improves the convergence speed by over 40% compared to baseline methods. It also demonstrates a strong adaptability to storage unit disconnection and reconnection. By enabling a fast and efficient response to grid services such as frequency regulation and renewable energy balancing, the proposed approach contributes to the development of intelligent and sustainable power systems.

α 7 nicotinic acetylcholine receptors (nAChRs) are homopentameric ligand-gated ion channels with critical roles in the nervous system. Recent studies have resolved and functionally annotated closed, open, and desensitized states of these receptors, providing insight into ion permeation and lipid binding. However, the process by which α 7 nAChRs transition between states remains unclear. To understand gating and lipid modulation, we generated two ensembles of molecular dynamics simulations of apo α 7 nAChRs, with or without cholesterol. Using symmetry-adapted Markov state modeling, we developed a five-state gating model. Free energies recapitulated functional behavior, with the closed state dominating in absence of agonist. Open-to-nonconducting transition rates corresponded to experimental open durations. Cholesterol relatively stabilized the desensitized state, and reduced open-desensitized barriers. These results establish plausible asymmetric transition pathways between states, define lipid modulation effects on the α 7 nAChR conformational cycle, and provide an ensemble of structural models applicable to rational design of lipidic pharmaceuticals. The α 7 nicotinic acetylcholine receptor plays important roles in the human nervous system. Here, authors use molecular simulations to develop a gating model and reveal cholesterol effects, offering insights applicable to drug design.

γ-Aminobutyric acid type A (GABA A ) receptors mediate fast inhibitory signaling in the brain and are targets of numerous drugs and endogenous neurosteroids. A subset of neurosteroids are GABA A receptor positive allosteric modulators; one of these, allopregnanolone, is the only drug approved specifically for treating postpartum depression. There is a consensus emerging from structural, physiological and photolabeling studies as to where positive modulators bind, but how they potentiate GABA activation remains unclear. Other neurosteroids are negative modulators of GABA A receptors, but their binding sites remain debated. Here we present structures of a synaptic GABA A receptor bound to allopregnanolone and two inhibitory sulfated neurosteroids. Allopregnanolone binds at the receptor-bilayer interface, in the consensus potentiator site. In contrast, inhibitory neurosteroids bind in the pore. MD simulations and electrophysiology support a mechanism by which allopregnanolone potentiates channel activity and suggest the dominant mechanism for sulfated neurosteroid inhibition is through pore block. Legesse et al. present structural studies of a human GABAA receptor in complex with positive and negative modulator neurosteroids, uncovering mechanisms of potentiation and inhibition.

GABA A receptors (GABA A Rs) are the primary inhibitory neurotransmitter receptors throughout the central nervous system. Genetic mutations causing their dysfunction are related to a broad spectrum of human disorders such as epilepsy, neurodevelopment and intellectual disability, autism spectrum disorder, schizophrenia, and depression. GABA A Rs are also important drug targets for anxiolytics, anticonvulsants, antidepressants, and anesthetics. Despite significant progress in understanding their three-dimensional structure, a critical gap remains in determining the molecular basis for channel gating. We recently identified mutations in the M2-M3 linkers that suggest linker flexibility has asymmetric subunit-specific correlations with channel opening. Here we use non-canonical amino acids (ncAAs) to investigate the role of main-chain H-hydrogen bonds (H-bonds) that may stabilize the M2-M3 linkers. We show that a single main-chain H-bond within the β2 subunit M2-M3 linker inhibits pore opening and is required to keep the unliganded channel closed. Furthermore, breaking this H-bond accounts for approximately one third of the energy used to open the channel during activation by GABA. In contrast, the analogous H-bond in the α1 subunit has no effect on gating. Our molecular simulations support the idea that channel opening involves the state-dependent breakage/disruption of a specific main-chain H-bond within the β2 subunit M2-M3 linker. The authors identify a single main-chain hydrogen bond required to keep GABA A receptors closed in the absence of neurotransmitter. Electrophysiology and molecular dynamics simulations suggest disruption of this bond is a key component of channel opening during inhibitory synaptic signaling in the brain.

This paper presents a planning and real-time pricing approach for EV charging stations (CSs). The approach takes the form of a bi-level model to fully consider the interest of both the government and EV charging station operators in the planning process. From the perspective of maximizing social welfare, the government acts as the decision-maker of the upper level that optimizes the charging price matrix, and uses it as a transfer variable to indirectly influence the decisions of the lower level operators. Then each operator at the lower level determines their scale according to the goal of maximizing their own revenue, and feeds the scale matrix back to the upper level. A Logit model is applied to predict the drivers' preference when selecting a CS. Furthermore, an improved particle swarm optimization (PSO) with the utilization of a penalty function is introduced to solve the nonlinear nonconvex bi-level model. The paper applies the proposed Bi-level planning model to a singlecenter small/medium-sized city with three scenarios to evaluate its performance, including the equipment utilization rate, payback period, traffic attraction ability, etc. The result verifies that the model performs very well in typical CS distribution scenarios with a reasonable station payback period (average 6.5 years), and relatively high equipment utilization rate, 44.32%.

Locating and planning charging stations for Low-Emission Vehicles (LEVs) such as Battery Electric Vehicle (BEV), Hydrogen Fuel-Cell Vehicle (HFCV), and Natural Gas Vehicle (NGV) are becoming increasingly important for LEV users, government, and the automobile industry. Conventional planning approach of charging station usually plans single functional charging station that can only serve one kind of LEVs, and other factors such as fuel type, driving range, initial fuel tank level, and refueling time of the LEV are less considered in the planning stage. In this article, we propose a bi-level planning model to locate and size Multi-Functional Charging Station (MFCS) which can recharge BEV, HFCV, and NGV at the same time in a medium-sized city with different functional areas (e.g., residential area, industrial area, CBD area). We also established a method for generating a daily route considering vehicle attributes and user habits, and we loaded these traveling data into the upper model to select a set of optimal combinations of refueling station locations with a relatively high success ratio. In the lower model, we introduced the mathematical relationship between number of chargers and average user waiting time, and set the total social cost factor, including investment cost and waiting time cost, to evaluate each optimal combination, and then identified the optimum locational result and defined the size of each station. In the case study, we verify the proposed model in several scenarios and conclude that multifunctional refueling station performs better in terms of investment cost and users’ satisfaction level.

It is anticipated that the penetration of “Green-Energy” vehicles, including Electric Vehicle (EV), Fuel Cell Vehicle (FCV), and Natural Gas Vehicle (NGV) will keep increasing in next decades. The demand of refueling stations will correspondingly increase for refueling these “Green-Energy” vehicles. While such kinds of “Green-Energy” vehicles can provide both social and economic benefits, effective management of refueling various kinds of these vehicles is necessary to maintain vehicle users’ comfortabilities and refueling station’s return on investment. To tackle these problems, this paper proposes a novel energy management approach for hybrid refueling stations with EV chargers, Hydrogen pumps and gas pumps. Firstly, the detailed models of EV chargers, Hydrogen pumps with electrolyte and hydrogen tank, the gas pumps with gas tank, renewable resources, and battery energy storage systems are established. The forecasting methodologies for renewable energy, electricity price and the traffic flow are also presented to support the hybrid refueling station modeling and operation. Then, a management approach is adopted to manage the refueling various kinds of vehicles with considerations of the refueling station profitability. Finally, the proposed management approach is verified under four different kinds of tariffs- Economy-7, Economy-10, Flat-rate, and Real-Time Pricing (RTP), finding that the proposed management approach has the best performance under RTP tariff. The economic assessment of the Energy Storage System (ESS) is also performed. It is found that the ESS can make the saving up to $127 per day. Different sizes of gas storage tank are compared in the final section as well. The result shows that increasing the size of the tank does not bring attractive extra benefits with the consideration of the investment on enlarging the tank size.

The tunability of spectral lineshapes, ranging from Lorentzian to Fano profiles, is essential for advancing nanoscale photonic technologies. Conventional far-field techniques are insufficient for studying nanoscale phenomena, particularly within the terahertz (THz) range. In this work, we use a U-shaped resonant ring on a waveguide substrate to achieve precise modulation of Lorentzian, Fano, and antiresonance profiles. THz scattering scanning near-field optical microscopy (s-SNOM) reveals the underlying physical mechanism of these transitions, driven by time-domain phase shifts between the background excitation from the waveguide and the resonance of the U-shaped ring. Our approach reveals a pronounced asymmetry in the near-field response, which remains undetectable in far-field systems. The ability to control spectral lineshapes at the nanoscale presents promising applications in characterizing composite nanoresonators and developing nanoscale phase sensors.

Ligand-gated ion channels are critical mediators of electrochemical signal transduction across evolution. Biophysical and pharmacological characterization of these receptor proteins relies on high-quality structures in multiple, subtly distinct functional states. However, structural data in this family remain limited, particularly for resting and intermediate states on the activation pathway. Here, we report cryo-electron microscopy (cryo-EM) structures of the proton-activated Gloeobacter violaceus ligand-gated ion channel (GLIC) under three pH conditions. Decreased pH was associated with improved resolution and side chain rearrangements at the subunit/domain interface, particularly involving functionally important residues in the β1–β2 and M2–M3 loops. Molecular dynamics simulations substantiated flexibility in the closed-channel extracellular domains relative to the transmembrane ones and supported electrostatic remodeling around E35 and E243 in proton-induced gating. Exploration of secondary cryo-EM classes further indicated a low-pH population with an expanded pore. These results allow us to define distinct protonation and activation steps in pH-stimulated conformational cycling in GLIC, including interfacial rearrangements largely conserved in the pentameric channel family.

Most general anaesthetics and classical benzodiazepine drugs act through positive modulation of γ-aminobutyric acid type A (GABA A ) receptors to dampen neuronal activity in the brain 1 – 5 . However, direct structural information on the mechanisms of general anaesthetics at their physiological receptor sites is lacking. Here we present cryo-electron microscopy structures of GABA A receptors bound to intravenous anaesthetics, benzodiazepines and inhibitory modulators. These structures were solved in a lipidic environment and are complemented by electrophysiology and molecular dynamics simulations. Structures of GABA A receptors in complex with the anaesthetics phenobarbital, etomidate and propofol reveal both distinct and common transmembrane binding sites, which are shared in part by the benzodiazepine drug diazepam. Structures in which GABA A receptors are bound by benzodiazepine-site ligands identify an additional membrane binding site for diazepam and suggest an allosteric mechanism for anaesthetic reversal by flumazenil. This study provides a foundation for understanding how pharmacologically diverse and clinically essential drugs act through overlapping and distinct mechanisms to potentiate inhibitory signalling in the brain. Cryo-electron microscopy structures of GABA A receptors bound to intravenous anaesthetics and benzodiazepines reveal both common and distinct transmembrane binding sites, and show that the mechanisms of action of anaesthetics partially overlap with those of benzodiazepines.