Electrochemical transistors (ECTs) are switches that are controlled by ionic gating, and find emerging applications in electronic devices and chemical sensors. In this paper, we fabricate microscale ...tungsten oxide (WO
x
) ECTs and study their subthreshold characteristics. We optimize the film deposition process to produce WO
x
films with various oxygen concentrations, and investigate their physical and chemical properties. We employ transparent amorphous WO
3
films as the channel material for ECTs, and experimentally investigate their subthreshold behaviors by injecting different metal ions in electrolytes. In addition, we explore the dynamic response of the WO
3
ECT. Gated by cation intercalation, we find that these WO
3
ECTs can obtain a subthreshold slope as low as 60 mV/dec at room temperature, approaching the same thermodynamic limit as field-effect transistors. The material and device strategies provide a route to realizing future computing and sensing devices.
Recently, Internet of Vehicles (IoV) has become one of the most active research fields in both academic and industry, which exploits resources of vehicles and Road Side Units (RSUs) to execute ...various vehicular applications. Due to the increasing number of vehicles and the asymmetrical distribution of traffic flows, it is essential for the network operator to design intelligent offloading strategies to improve network performance and provide high-quality services for users. However, the lack of global information and the time-variety of IoVs make it challenging to perform effective offloading and caching decisions under long-term energy constraints of RSUs. Since Artificial Intelligence (AI) and machine learning can greatly enhance the intelligence and the performance of IoVs, we push AI inspired computing, caching and communication resources to the proximity of smart vehicles, which jointly enable RSU peer offloading, vehicle-to-RSU offloading and content caching in the IoV framework. A Mix Integer Non-Linear Programming (MINLP) problem is formulated to minimize total network delay, consisting of communication delay, computation delay, network congestion delay and content downloading delay of all users. Then, we develop an online multi-decision making scheme (named OMEN) by leveraging Lyapunov optimization method to solve the formulated problem, and prove that OMEN achieves near-optimal performance. Leveraging strong cognition of AI, we put forward an imitation learning enabled branch-and-bound solution in edge intelligent IoVs to speed up the problem solving process with few training samples. Experimental results based on real-world traffic data demonstrate that our proposed method outperforms other methods from various aspects.
Based on the point-coupling density functional, the time-odd deformed relativistic Hartree-Bogoliubov theory in continuum (TODRHBc) is developed. The effects of nuclear magnetism on halo phenomenon ...are explored by taking the experimentally suggested deformed halo nucleus 31Ne as an example. For 31Ne, nuclear magnetism contributes 0.09 MeV to total binding energy, and the breaking of Kramers degeneracy results in a 0 – 0.2 MeV splitting in the canonical single particle spectra. The blocked neutron level has a dominant component of the p wave and is marginally bound. However, if we ignore nuclear magnetism, the level becomes unbound. This shows a subtle mechanism that nuclear magnetism changes the single particle energies, causing a nucleus to become bound. Based on the TODRHBc results, a prolate one-neutron halo is formed around the near-spherical core in 31Ne. The nucleon current is mostly contributed by the halo rather than the core, except near the center of the nucleus. A layered feature in the neutron current distribution is observed and studied in detail.
Recent developments of edge computing and content caching in wireless networks enable the Intelligent Transportation System (ITS) to provide high-quality services for vehicles. However, a variety of ...vehicular applications and time-varying network status make it challenging for ITS to allocate resources efficiently. Artificial intelligence algorithms, owning the cognitive capability for diverse and time-varying features of Internet of Connected Vehicles (IoCVs), enable an intent-based networking for ITS to tackle the above-mentioned challenges. In this paper, we develop an intent-based traffic control system by investigating Deep Reinforcement Learning (DRL) for 5G-envisioned IoCVs, which can dynamically orchestrate edge computing and content caching to improve the profits of Mobile Network Operator (MNO). By jointly analyzing MNO's revenue and users' quality of experience, we define a profit function to calculate the MNO's profits. After that, we formulate a joint optimization problem to maximize MNO's profits, and develop an intelligent traffic control scheme by investigating DRL, which can improve system profits of the MNO and allocate network resources effectively. Experimental results based on real traffic data demonstrate our designed system is efficient and well-performed.
To explore the failure mechanism of roadway in layered soft rocks, a physical model with the physically finite elemental slab assemblage (PFESA) method was established. Infrared thermography and a ...video camera were employed to capture thermal responses and deformation. The model results showed that layered soft roadway suffered from large deformation. A three-dimensional distinct element code (3DEC) model with tetrahedral blocks was built to capture the characteristics of roadway deformation, stress, and cracks. The results showed two failure patterns, layer bending fracture and layer slipping after excavation. The layer bending fracture occurred at positions where the normal direction of layers pointed to the inside of the roadway and the layer slipping occurred in the ribs. Six schemes were proposed to investigate the effects of layered soft rocks. The results showed that the deformation of ribs was obviously larger than that of the roof and floor when the roadway passed through three types of strata. When the roadway was completely in a coal seam, the change of deformation in ribs was not obvious, while the deformation in the roof and floor increased obviously. These results can provide guidance for excavation and support design of roadways in layered soft rocks.
Proper adjustments of metabolic thermogenesis play an important role in thermoregulation in endotherm to cope with cold and/or warm ambient temperatures, however its roles in energy balance and fat ...accumulation remain uncertain. Our study aimed to investigate the effect of previous cold exposure (10 and 0 °C) on the energy budgets and fat accumulation in the striped hamsters (Cricetulus barabensis) in response to warm acclimation. The body mass, energy intake, resting metabolic rate (RMR) and nonshivering thermogenesis (NST), serum thyroid hormone levels (THs: T3 and T4), and the activity of brown adipose tissue (BAT), indicated by cytochrome c oxidase (COX) activity and uncoupling protein 1 (ucp
) expression, were measured following exposure to the cold (10 °C and 0 °C) and transition to the warm temperature (30 °C).
The hamsters at 10 °C and 0 °C showed significant increases in energy intake, RMR and NST, and a considerable reduction in body fat than their counterparts kept at 21 °C. After being transferred from cold to warm temperature, the hamsters consumed less food, and decreased RMR and NST, but they significantly increased body fat content. Interestingly, the hamsters that were previously exposed to the colder temperature showed significantly more fat accumulation after transition to the warm. Serum T3 levels, BAT COX activity and ucp
mRNA expression were significantly increased following cold exposure, and were considerably decreased after transition to the warm. Furthermore, body fat content was negatively correlated with serum T3 levels, BAT COX activity and UCP
expression.
The data suggest that the positive energy balance resulting from the decreased RMR and NST in BAT under the transition from the cold to the warm plays important roles in inducing fat accumulation. The extent of fat accumulation in the warm appears to reflect the temperature of the previous cold acclimation.
Efficient layout of large-scale graphs remains a challenging problem: the force-directed and dimensionality reduction-based methods suffer from high overhead for graph distance and gradient ...computation. In this paper, we present a new graph layout algorithm, called DRGraph, that enhances the nonlinear dimensionality reduction process with three schemes: approximating graph distances by means of a sparse distance matrix, estimating the gradient by using the negative sampling technique, and accelerating the optimization process through a multi-level layout scheme. DRGraph achieves a linear complexity for the computation and memory consumption, and scales up to large-scale graphs with millions of nodes. Experimental results and comparisons with state-of-the-art graph layout methods demonstrate that DRGraph can generate visually comparable layouts with a faster running time and a lower memory requirement.
Based on the analysis of the principle and structure of a convolutional neural network (CNN) model used for in-depth learning, an intelligent discriminant diagnosis method for porcelain fuselage ...insulators in transmission lines is proposed. Firstly, the infrared image of a porcelain insulator is extracted, and then Lenet is used to optimize the network structure. Finally, the model of fixed parameters is formed by training. The model has high classification and judgment robustness and offers accuracy under different conditions such as: temperature, humidity, position of deterioration on the insulator, and thermal load, which allows weight-sharing in the CNN model under different environmental conditions. Based on the experimental data from an infrared heating experiment using a porcelain deteriorated insulator, this work uses the back-propagation gradient descent method to train the model, to form an intelligent detection model for deteriorated insulators. This method has the advantages of high accuracy and robustness, and represents a new method for intelligent detection of deteriorated insulators.
Advanced optical fibers and photonic structures play important roles in neuroscience research, along with recent progresses of genetically encoded optical actuators and indicators. Most techniques ...for optical neural implants rely on fused silica or long‐lasting polymeric fiber structures. In this paper, implantable and biodegradable optical fibers based on poly(l‐lactic acid) (PLLA) are presented. PLLA fibers with dimensions similar to standard silica fibers are constructed using a simple thermal drawing process at around 220 °C. The formed PLLA fibers exhibit high mechanical flexibility and optical transparency, and their structural evolution and optical property changes are systematically studied during in vitro degradation. In addition, their biocompatibility with brain tissues is evaluated in living mice, and full in vivo degradation is demonstrated. Finally, PLLA fibers are implemented as a tool for intracranial light delivery and detection, realizing deep brain fluorescence sensing and optogenetic interrogation in vivo. The presented materials and device platform offer paths to fully biocompatible and bioresorbable photonic systems for biomedical uses.
Implantable and biodegradable poly(l‐lactic acid) fibers are constructed using a simple thermal drawing process at around 220 °C. Their structural evolution and optical property changes are systematically studied during in vitro degradation. The fibers are implemented for deep brain fluorescence sensing and optogenetic interrogation in vivo.
Constructing SiO
x
-based composite materials with fast reaction kinetics and high stability is crucial but challenging for high-performance lithium-ion batteries. Herein, we developed the N-doped Ti
...3
C
2
T
x
MXene ultrathin sheet (NTS)-coupled SiO
x
nanoparticles using a melamine-assisted ball milling and annealing procedure. The principle of melamine in exfoliating MXene was demonstrated by contrast experiments and theoretical calculations. The strong interfacial interactions between SiO
x
and the NTS (Si−O−Ti bond) can effectively enhance the electron transfer and ensure electrode stability. Moreover, the NTS with rich surface groups endowed the composite with a pseudocapacitive behavior, beneficial for fast lithium storage. As a result, the composite delivered a long lifespan (∼700 mA h g
−1
over 800 cycles at 1.0 A g
−1
) and a superior rate performance (596.4 mA h g
−1
at 5 A g
−1
). More importantly, the composite in half and full cells exhibited high areal capacity and good cycling stability at high mass loadings, revealing a promising application prospect.
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