Goal-oriented Estimation of Multiple Markov Sources in Resource-constrained Systems

This paper investigates goal-oriented communication for remote estimation of multiple Markov sources in resource-constrained networks. An agent selects the update order of the sources and transmits the packet to a remote destination over an unreliable delay channel. The destination is tasked with source reconstruction for the purpose of actuation. We utilize the metric cost of actuation error (CAE) to capture the significance (semantics) of error at the point of actuation. We aim to find an optimal sampling policy that minimizes the time-averaged CAE subject to average resource constraints. We formulate this problem as an average-cost constrained Markov Decision Process (CMDP) and transform it into an unconstrained MDP by utilizing Lyapunov drift techniques. Then, we propose a low-complexity drift-plus-penalty(DPP) policy for systems with known source/channel statistics and a Lyapunov optimization-based deep reinforcement learning (LO-DRL) policy for unknown environments. Our policies achieve near-optimal performance in CAE minimization and significantly reduce the number of uninformative transmissions

A Computationally Efficient Bi-level Coordination Framework for CAVs at Unsignalized Intersections

In this paper, we investigate cooperative vehicle coordination for connected and automated vehicles (CAVs) at unsignalized intersections. To support high traffic throughput while reducing computational complexity, we present a novel collision region model and decompose the optimal coordination problem into two sub-problems: \textit{centralized} priority scheduling and \textit{distributed} trajectory planning. Then, we propose a bi-level coordination framework which includes: (i) a Monte Carlo Tree Search (MCTS)-based high-level priority scheduler aims to find high-quality passing orders to maximize traffic throughput, and (ii) a priority-based low-level trajectory planner that generates optimal collision-free control inputs. Simulation results demonstrate that our bi-level strategy achieves near-optimal coordination performance, comparable to state-of-the-art centralized strategies, and significantly outperform the traffic signal control systems in terms of traffic throughput. Moreover, our approach exhibits good scalability, with computational complexity scaling linearly with the number of vehicles. Video demonstrations can be found online at \url{https://youtu.be/WYAKFMNnQfs}

A Tightly Coupled Bi-Level Coordination Framework for CAVs at Road Intersections

Since the traffic administration at road intersections determines the capacity bottleneck of modern transportation systems, intelligent cooperative coordination for connected autonomous vehicles (CAVs) has shown to be an effective solution. In this paper, we try to formulate a Bi-Level CAV intersection coordination framework, where coordinators from High and Low levels are tightly coupled. In the High-Level coordinator where vehicles from multiple roads are involved, we take various metrics including throughput, safety, fairness and comfort into consideration. Motivated by the time consuming space-time resource allocation framework in [1], we try to give a low complexity solution by transforming the complicated original problem into a sequential linear programming one. Based on the "feasible tunnels" (FT) generated from the High-Level coordinator, we then propose a rapid gradient-based trajectory optimization strategy in the Low-Level planner, to effectively avoid collisions beyond High-level considerations, such as the pedestrian or bicycles. Simulation results and laboratory experiments show that our proposed method outperforms existing strategies. Moreover, the most impressive advantage is that the proposed strategy can plan vehicle trajectory in milliseconds, which is promising in realworld deployments. A detailed description include the coordination framework and experiment demo could be found at the supplement materials, or online at https://youtu.be/MuhjhKfNIOg

Design and implementation of experimental data access security policy for HEPS container computing platform

China’s High-Energy Photon Source (HEPS), the first national highenergy synchrotron radiation light source, is under design and construction. In the future, at the first stage of HEPS, it is predicted that 24PB raw experimental data will be produced per month from 14 beamlines. Faced with such a huge scale of scientific data and diverse data analysis environments in light source disciplines, the HEPS scientific computing platform was designed and implemented based on container mirroring and dynamic orchestration technology to provide HEPS users with a data analysis environment. In this article, a data security access strategy is designed and evaluated for a scientific computing platform to ensure the security and efficiency of data access for users in the entire process of data analysis. First, the general situation of HEPS is introduced. Second, the challenges faced by the HEPS scientific computing system. Third, the architecture and service process of the scientific computing platform are described from the perspective of IT, some key technical implementations will be introduced in detail. Finally, the application effect of data access security policies on computing platforms will be demonstrated

Better synoptic and subseasonal sea ice thickness predictions are urgently required: a lesson learned from the YOPP data validation

In the context of global warming, Arctic sea ice has declined substantially during the satellite era (Kwok 2018). The retreating and thinning of Arctic sea ice provide opportunities for human activities in the Arctic, such as tourism, fisheries, shipping, natural resource exploitation, and wildlife management; however, new risks emerge. To ensure the safety and emergency management of human activities in the Arctic, reliable Arctic sea ice prediction is essential

Periplasmic biomineralization for semi-artificial photosynthesis

Semiconductor-based biointerfaces are typically established either on the surface of the plasma membrane or within the cytoplasm. In Gram-negative bacteria, the periplasmic space, characterized by its confinement and the presence of numerous enzymes and peptidoglycans, offers additional opportunities for biomineralization, allowing for nongenetic modulation interfaces. We demonstrate semiconductor nanocluster precipitation containing single- and multiple-metal elements within the periplasm, as observed through various electron- and x-ray-based imaging techniques. The periplasmic semiconductors are metastable and display defect-dominant fluorescent properties. Unexpectedly, the defect-rich (i.e., the low-grade) semiconductor nanoclusters produced in situ can still increase adenosine triphosphate levels and malate production when coupled with photosensitization. We expand the sustainability levels of the biohybrid system to include reducing heavy metals at the primary level, building living bioreactors at the secondary level, and creating semi-artificial photosynthesis at the tertiary level. The biomineralization-enabled periplasmic biohybrids have the potential to serve as defect-tolerant platforms for diverse sustainable applications

Detection of concealed and buried chemicals by using multifrequency excitations

This is the published version. Copyright © 2010 American Institute of PhysicsIn this paper, we present a new type of concealed and buried chemical detection system by stimulating and enhancing spectroscopic signatures with multifrequency excitations, which includes a low frequency gradient dcelectric field, a high frequency microwave field, and higher frequency infrared (IR) radiations. Each excitation frequency plays a unique role. The microwave, which can penetrate into the underground and/or pass through the dielectric covers with low attenuation, could effectively transform its energy into the concealed and buried chemicals and increases its evaporation rate from the sample source. Subsequently, a gradient dcelectric field, generated by a Van De Graaff generator, not only serves as a vapor accelerator for efficiently expediting the transportation process of the vapor release from the concealed and buried chemicals but also acts as a vapor concentrator for increasing the chemical concentrations in the detection area, which enables the trace level chemical detection. Finally, the stimulated and enhanced vapors on the surface are detected by the IR spectroscopic fingerprints. Our theoretical and experimental results demonstrate that more than sixfold increase in detection signal can be achieved by using this proposed technology. The proposed technology can also be used for standoff detection of concealed and buried chemicals by adding the remote IR and/or thermal spectroscopic and imaging detection systems

Optimizing fluconazole-embedded transfersomal gel for enhanced antifungal activity and compatibility studies

Fungal infections are of major concern all over the globe, and fluconazole is the most prevalently used drug to treat it. The goal of this research work was to formulate a fluconazole-embedded transfersomal gel for the treatment of fungal infections. A compatibility study between fluconazole and soya lecithin was performed by differential scanning calorimetry (DSC). Transfersomes were formulated by a thin-film hydration technique using soya lecithin and Span 80. A central composite design was adopted to prepare different formulations. Soya lecithin and Span 80 were chosen as independent variables, and the effect of these variables was studied on in vitro drug diffusion. Formulations were evaluated for entrapment efficiency and in vitro drug diffusion. The results of in vitro drug diffusion were analyzed using the analysis of variance (ANOVA) test. Optimized formulation was prepared based on the overlay plot and evaluated by scanning electron microscopy, DSC, vesicle size, polydispersity index (PDI), zeta potential, and in vitro drug diffusion studies. An optimized formulation was loaded into xanthan gum gel base and evaluated for pH, viscosity, in vitro and ex vivo drug diffusion, and antifungal activity. DSC studies revealed compatibility between fluconazole and soya lecithin. Entrapment efficiency and in vitro drug diffusion of various formulations ranged between 89.92% ± 0.20% to 97.28% ± 0.42% and 64% ± 1.56% to 85% ± 2.05%, respectively. A positive correlation was observed between in vitro drug diffusion and Span 80; conversely, a negative correlation was noted with soya lecithin. Entrapment efficiency, particle size, zeta potential, PDI, and drug diffusion of optimized formulation were 95.0% ± 2.2%, 397 ± 2 nm, −38 ± 5 mV, 0.43%, and 81 % ± 2%, respectively. SEM images showed well-distributed spherical-shaped transfersomes. In vitro, ex vivo drug diffusion and antifungal studies were conclusive of better diffusion and enhanced antifungal potential fluconazole in transfersomal formulation

Use of nanomaterials in the pretreatment of water samples for environmental analysis

The challenge of providing clean drinking water is of enormous relevance in today’s human civilization, being essential for human consumption, but also for agriculture, livestock and several industrial applications. In addition to remediation strategies, the accurate monitoring of pollutants in water sup-plies, which most of the times are present at low concentrations, is a critical challenge. The usual low concentration of target analytes, the presence of in-terferents and the incompatibility of the sample matrix with instrumental techniques and detectors are the main reasons that renders sample preparation a relevant part of environmental monitoring strategies. The discovery and ap-plication of new nanomaterials allowed improvements on the pretreatment of water samples, with benefits in terms of speed, reliability and sensitivity in analysis. In this chapter, the use of nanomaterials in solid-phase extraction (SPE) protocols for water samples pretreatment for environmental monitoring is addressed. The most used nanomaterials, including metallic nanoparticles, metal organic frameworks, molecularly imprinted polymers, carbon-based nanomaterials, silica-based nanoparticles and nanocomposites are described, and their applications and advantages overviewed. Main gaps are identified and new directions on the field are suggested.publishe