Resilient Dynamic Channel Access via Robust Deep Reinforcement Learning
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A new satellite multi-access scheme for packet-switching computer communications combines a dynamic allocation technique with conventional time-division multiplexing to minimize delays and maximize traffic thruput. The scheme is designed to give the shortest delays to short-duration interactive or priority traffic, at the expense of longer delays for large data transfers. Simulation results show markedly improved delay-thruput characteristics over conventional time-division multiplexing for a wide range of traffic mixes, with especially significant performance gains as the traffic imbalance among the nodes increases.
In this paper, we apply the Non-Orthogonal Multiple Access (NOMA) technique to improve the massive channel access of a wireless IoT network where solar-powered Unmanned Aerial Vehicles (UAVs) relay data from IoT devices to remote servers. Specifically, IoT devices contend for accessing the shared wireless channel using an adaptive p-persistent slotted Aloha protocol; and the solar-powered UAVs adopt Successive Interference Cancellation (SIC) to decode multiple received data from IoT devices to improve access efficiency. To enable an energy-sustainable capacity-optimal network, we study the joint problem of dynamic multi-UAV altitude control and multi-cell wireless channel access management of IoT devices as a stochastic control problem with multiple energy constraints. We first formulate this problem as a Constrained Markov Decision Process (CMDP), and propose an online model-free Constrained Deep Reinforcement Learning (CDRL) algorithm based on Lagrangian primal-dual policy optimization to solve the CMDP. Extensive simulations demonstrate that our proposed algorithm learns a cooperative policy in which the altitude of UAVs and channel access probability of IoT devices are dynamically controlled to attain the maximal long-term network capacity while ensuring energy sustainability of UAVs, outperforming baseline schemes. The proposed CDRL agent can be trained on a small network, yet the learned policy can efficiently manage networks with a massive number of IoT devices and varying initial states, which can amortize the cost of training the CDRL agent.
Strong coupling between light and matter can produce hybrid eigenstates known as exciton-polaritons. Although polariton dynamics are important photophysical properties, the relaxation pathways of polaritons in different coupling regimes have seen limited attention. This paper reports the dynamics of hybridized states from 2D Ruddlesden-Popper perovskites coupled to plasmonic nanoparticle lattices. The open cavity architecture of Al lattices enables the coupling strength to be modulated by varying either the lead halide perovskite film thickness or the superstrate refractive index. Both experiments and finite-difference time-domain simulations of the optical dispersion diagrams showed avoided crossings that are a signature of strong coupling. Furthermore, our analytical model also elucidated the correlation between the exciton/plasmon mixing ratio and polariton coupling strength. Using fs-transient absorption spectroscopy, we found that both the upper and lower polaritons have shorter lifetimes than the excitons and that polaritons can show faster excited state dynamics when they have access to additional energy transfer channels.
Requiring catalysts to be both active yet stable over long periods of time under variable reaction conditions including high and low temperatures is a daunting challenge due to the almost mutual exclusivity of these constraints. Using CO oxidation as a probe reaction, in this work we demonstrate that thermally stable single atom copper catalysts prepared by high temperature synthesis (atom trapping) on ceria can achieve this feat by allowing modulation of the Cu charge state through facile charge transfer between active site and support. This provides the catalysts with an ability to activate either lattice or adatom oxygen atoms, accessing additional reaction channels depending on the reaction conditions. Such adaptability allows dynamic response of catalysts enabling them to remain active under variable reaction conditions. The inherent stability of the catalyst arises from the enhanced strength of the Cu-O interactions from high temperature synthesis that exist even when Cu oxidation state varies, which retards sintering and deactivation. As we show here, one can circumvent the dilemma of designing catalysts that are simultaneously active and stable by matching the redox properties of the active site and support and establishing an environmental adaptability around the active sites.
Fatty acid (FA) transfer proteins extract FA from membranes and sequester them to facilitate their movement through the cytosol. Detailed structural information is available for these soluble protein–FA complexes, but the structure of the protein conformation responsible for FA exchange at the membrane is unknown. Staphylococcus aureus FakB1 is a prototypical bacterial FA transfer protein that binds palmitate within a narrow, buried tunnel. Here, we define the conformational change from a “closed” FakB1 state to an “open” state that associates with the membrane and provides a path for entry and egress of the FA. Using NMR spectroscopy, we identified a conformationally flexible dynamic region in FakB1, and X-ray crystallography of FakB1 mutants captured the conformation of the open state. In addition, molecular dynamics simulations show that the new amphipathic α-helix formed in the open state inserts below the phosphate plane of the bilayer to create a diffusion channel for the hydrophobic FA tail to access the hydrocarbon core and place the carboxyl group at the phosphate layer. The membrane binding and catalytic properties of site-directed mutants were consistent with the proposed membrane docked structure predicted by our molecular dynamics simulations. Finally, the structure of the bilayer-associated conformation of FakB1 has local similarities with mammalian FA binding proteins and provides a conceptual framework for how these proteins interact with the membrane to create a diffusion channel from the FA location in the bilayer to the protein interior.
Controlling nonequilibrium dynamics in quantum materials requires ultrafast probes with spectral selectivity. We report femtosecond reflectivity measurements on the cuprate superconductor Bi 2 Sr 2 CaCu 2 O 8+𝛿 using free-electron laser extreme-ultraviolet (23.5–177 eV) and near-infrared (1.5 eV) pump pulses. EUV pulses access deep electronic states, while NIR light excites valence-band transitions. Despite these distinct channels, both schemes produce nearly identical dynamics: above 𝑇 𝑐 , excitations relax through fast (100–300 fs) and slower (1–5 ps) channels; below 𝑇 𝑐 , a delayed component signals quasiparticle recombination and condensate recovery. We find that when electronic excitations are involved, the ultrafast response is governed mainly by absorbed energy rather than by the microscopic nature of the excitation. In contrast, bosonic driving in the THz or midinfrared produces qualitatively different dynamics. By demonstrating that EUV excitation of a correlated superconductor yields macroscopic dynamics converging with those from optical pumping, this work defines a new experimental paradigm: FEL pulses at core-level energies provide a powerful means to probe and control nonequilibrium electronic states in quantum materials on their intrinsic femtosecond timescales. This establishes FEL-based EUV pumping as a new capability for ultrafast materials science, opening routes toward soft x-ray and attosecond studies of correlated dynamics.
Local Area Networks are in common use for data communications and have enjoyed great success. Recently, there is a growing interest in using a single network to support many applications in addition to traditional data traffic. These additional applications introduce new requirements in terms of volume of traffic and real-time delivery of data which are not met by existing networks. To satisfy these requirements, a high-bandwidth tranmission medium, such as fiber optics, and a distributed channel access scheme for the efficient sharing of the bandwidth among the various applications are needed. As far as the throughput-delay requirements of the various application are concerned, a network structure along with a distributed channel access are proposed which incorporate appropriate scheduling policies for the transmission of outstanding messages on the network. A dynamic scheduling policy was devised which outperforms all existing policies in terms of minimizing the expected cost per message. A broadcast mechanism was devised for the efficient dissemination of all relevant information. Fiber optic technology is considered for the high-bandwidth transmisison medium.
Recently, a new framework for studying generic 2 → 3 hard exclusive reactions, referred to as single-diffractive hard exclusive processes, has been introduced to provide a cleaner separation of the underlying physical mechanisms. In this work, we expand this formalism to the case of exclusive real-photon electroproduction off a nucleon, 𝑒(ℓ) +𝑁(𝑝) →𝑒(ℓ′) +𝑁(𝑝′) + 𝛾(𝑞′), which represents the classical channel for accessing generalized parton distributions (GPDs) in nucleons and nuclei. This extension enables a more systematic and physically transparent formulation of the reaction dynamics, paving the way for improved extractions of GPDs from experimental data as compared to existing approaches.
Here, in this study, we investigate the structure-dependent modulation characteristics of all-solid-state three-terminal electrochemical random-access memory (ECRAM) based on an anatase Li x TiO 2 channel. By directly comparing “asymmetric” and “symmetric” ECRAM device architectures, we reveal significant insight into the impact of a non-zero gate-drain open-circuit voltage and its influence on voltage vs. current-controlled gating. We also explore the impact of potentiation/depression write parameters on the symmetry, linearity, and dynamic range of the device response. Together, initial results from optimizing structure and programming approaches yielded unprecedented G max /G min ratios of >1,000 for ECRAM and hundreds of tunable memory states with excellent linearity and symmetry. Simulations based on these ECRAM devices further illustrate the promise of this analog memory technology, achieving near 2% classification error in the MNIST digit recognition benchmark for a range of training parameters compared to a theoretical best of 1.66% and outperforming other device models extracted from the literature.
Two independent structures of the proton-pumping, respiratory cytochrome bo3 ubiquinol oxidase (cyt bo 3 ) have been determined by cryogenic electron microscopy (cryo-EM) in styrene–maleic acid (SMA) copolymer nanodiscs and in membrane scaffold protein (MSP) nanodiscs to 2.55- and 2.19-Å resolution, respectively. The structures include the metal redox centers (heme b, heme o 3 , and Cu B ), the redox-active cross-linked histidine–tyrosine cofactor, and the internal water molecules in the proton-conducting D channel. Each structure also contains one equivalent of ubiquinone-8 (UQ8) in the substrate binding site as well as several phospholipid molecules. The isoprene side chain of UQ8 is clamped within a hydrophobic groove in subunit I by transmembrane helix TM0, which is only present in quinol oxidases and not in the closely related cytochrome c oxidases. Both structures show carbonyl O1 of the UQ8 headgroup hydrogen bonded to D75I and R71 I . In both structures, residue H98 I occupies two conformations. In conformation 1, H98 I forms a hydrogen bond with carbonyl O4 of the UQ8 headgroup, but in conformation 2, the imidazole side chain of H98 I has flipped to form a hydrogen bond with E14 I at the N-terminal end of TM0. We propose that H98 I dynamics facilitate proton transfer from ubiquinol to the periplasmic aqueous phase during oxidation of the substrate. Computational studies show that TM0 creates a channel, allowing access of water to the ubiquinol headgroup and to H98 I .
Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.
We examine changes in the picosecond structural dynamics with irreversible photobleaching of red fluorescent proteins (RFP) mCherry, mOrange2 and TagRFP-T. Measurements of the protein dynamical transition using terahertz time-domain spectroscopy show in all cases an increase in the turn-on temperature in the bleached state. The result is surprising given that there is little change in the protein surface, and thus, the solvent dynamics held responsible for the transition should not change. A spectral analysis of the measurements guided by quasiharmonic calculations of the protein absorbance reveals that indeed the solvent dynamical turn-on temperature is independent of the thermal stability/photostate however the protein dynamical turn-on temperature shifts to higher temperatures. This is the first demonstration of switching the protein dynamical turn-on temperature with protein functional state. The observed shift in protein dynamical turn-on temperature relative to the solvent indicates an increase in the required mobile waters necessary for the protein picosecond motions, that is, these motions are more collective. Melting-point measurements reveal that the photobleached state is more thermally stable, and structural analysis of related RFP’s shows that there is an increase in internal water channels as well as a more uniform atomic root mean squared displacement. These observations are consistent with previous suggestions that water channels form with extended light excitation providing O2 access to the chromophore and subsequent fluorescence loss. We report that these same channels increase internal coupling enhancing thermal stability and collectivity of the picosecond protein motions. The terahertz spectroscopic characterization of the protein and solvent dynamical onsets can be applied generally to measure changes in collectivity of protein motions.
This slide presentation reviews the issues around Adaptive Quality of Service (QoS) in wireless networks for lunar communications, and how a dynamic 802.11e standard meets the requirements for all aspects of communications for lunar surface missions. This paper focuses on the use of Enhanced Distributed Channel Access (EDCA). It includes a description of an adaptive QoS Algorithm, a review of the set up of the simulation of the 802.11e standard, and the results of the simulation are included.
Superior properties in organic mixed ionic-electronic conductors (OMIECs) over inorganic counterparts have inspired intense interest in biosensing, soft-robotics, neuromorphic computing, and smart medicine. However, slow ion transport relative to charge transport in these materials is a limiting factor. Here, it is demonstrated that hydrophilic molecules local to an interfacial OMIEC nanochannel can accelerate ion transport with ion mobilities surpassing electrophoretic transport by more than an order of magnitude. Furthermore, ion access to this interfacial channel can be gated through local surface energy. This mechanism is applied in a novel sensing device, which electronically detects and characterizes chemical reaction dynamics local to the buried channel. The ability to enhance ion transport at the nanoscale in OMIECs as well as govern ion transport through local chemical signaling enables new functionalities for printable, stretchable, and biocompatible mixed conduction devices.
This paper considers the dynamic spectrum access and power control problem in a single-hop point-to-point Air-Air Communication Network (AACN). Due to spectrum scarcity, we assume the number of Aircraft-to-Aircraft (A2A) communication links is greater than that of the available channels, such that some communication links need to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the Weighted Sum Spectral Efficiency (WSSE). A distributed and dynamic deep Q learning-based algorithm is proposed to find the optimal solution. Specifically, we design two different policies that are trained by conducting a trial-and-error scheme. Each communication link can achieve the optimal policy by exploiting the local information from its neighbors, and this distributive approach make it scalable to large networks. Finally, our experimental results demonstrate the effectiveness of the proposed solution in various AACN scenarios.
This paper considers the dynamic spectrum access and power control problem in a single-hop point-to-point Air-Air Communication Network (AACN). Due to spectrum scarcity, we assume the number of Aircraft-to-Aircraft (A2A) communication links is greater than that of the available channels, such that some communication links need to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the Weighted Sum Spectral Efficiency (WSSE). A distributed and dynamic deep Q learning-based algorithm is proposed to find the optimal solution. Specifically, we design two different policies that are trained by conducting a trial-and-error scheme. Each communication link can achieve the optimal policy by exploiting the local information from its neighbors, and this distributive approach make it scalable to large networks. Finally, our experimental results demonstrate the effectiveness of the proposed solution in various AACN scenarios.
A 3-D weather radar visualization software program was developed and implemented as part of an experimental Launch Pad 39 Hail Monitor System. 3DRadPlot, a radar plotting program, is one of several software modules that form building blocks of the hail data processing and analysis system (the complete software processing system under development). The spatial and temporal mapping algorithms were originally developed through research at the University of Central Florida, funded by NASA s Tropical Rainfall Measurement Mission (TRMM), where the goal was to merge National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD) volume reflectivity data with drop size distribution data acquired from a cluster of raindrop disdrometers. In this current work, we adapted these algorithms to process data from a cluster of hail disdrometers positioned around Launch Pads 39A or 39B, along with the corresponding NWS radar data. Radar data from all NWS NEXRAD sites is archived at the National Climatic Data Center (NCDC). That data can be readily accessed at . 3DRadPlot plots Level III reflectivity data at four scan elevations (this software is available at Open Channel Software, ). By using spatial and temporal interpolation/extrapolation based on hydrometeor fall dynamics, we can merge the hail disdrometer array data coupled with local Weather Surveillance Radar-1988, Doppler (WSR-88D) radial velocity and reflectivity data into a 4-D (3-D space and time) picture of hail size distributions. Hail flux maps can then be generated and used for damage prediction and assessment over specific surfaces corresponding to structures within the disdrometer array volume. Immediately following a hail storm, specific damage areas and degree of damage can be identified for inspection crews.