Radical anions of electron-deficient systems are widely used, but are easily reoxidized upon exposure to air. Therefore, the stabilization of radical anions under ambient conditions is of great ...significance, but still remains a scientific challenge. Herein, perylenediimide is employed to prepare a crystalline metal-organic framework for stabilizing radical anions without extensive chemical modification. The porous, three-dimensional framework of perylenediimide can trap electron donors such as amine vapors and produce radical anions in-situ through photo-induced electron transfer. The radical anions are protected against quenching by shielding effect in air and remain unobstructed in air for at least a month. Because of the high yield and stability of the radical anions, which are the basis for near-infrared photothermal conversion, the framework shows high near-infrared photothermal conversion efficiency (η = 52.3%). The work provides an efficient and simple method towards ambient stable radical anions and affords a promising material for photothermal therapy.
The reliability of autonomous driving sensing systems impacts the overall safety of the driving system. However, perception system fault diagnosis is currently a weak area of research, with limited ...attention and solutions. In this paper, we present an information-fusion-based fault-diagnosis method for autonomous driving perception systems. To begin, we built an autonomous driving simulation scenario using PreScan software, which collects information from a single millimeter wave (MMW) radar and a single camera sensor. The photos are then identified and labeled via the convolutional neural network (CNN). Then, we fused the sensory inputs from a single MMW radar sensor and a single camera sensor in space and time and mapped the MMW radar points onto the camera image to obtain the region of interest (ROI). Lastly, we developed a method to use information from a single MMW radar to aid in diagnosing defects in a single camera sensor. As the simulation results show, for missing row/column pixel failure, the deviation typically falls between 34.11% and 99.84%, with a response time of 0.02 s to 1.6 s; for pixel shift faults, the deviation range is between 0.32% and 9.92%, with a response time of 0 s to 0.16 s; for target color loss, faults have a deviation range of 0.26% to 2.88% and a response time of 0 s to 0.05 s. These results prove the technology is effective in detecting sensor faults and issuing real-time fault alerts, providing a basis for designing and developing simpler and more user-friendly autonomous driving systems. Furthermore, this method illustrates the principles and methods of information fusion between camera and MMW radar sensors, establishing the foundation for creating more complicated autonomous driving systems.
With the rapid development of vehicular networks, vehicle-to-everything (V2X) communications have huge number of tasks to be calculated, which brings challenges to the scarce network resources. Cloud ...servers can alleviate the terrible situation regarding the lack of computing abilities of vehicular user equipment (VUE), but the limited resources, the dynamic environment of vehicles, and the long distances between the cloud servers and VUE induce some potential issues, such as extra communication delay and energy consumption. Fortunately, mobile edge computing (MEC), a promising computing paradigm, can ameliorate the above problems by enhancing the computing abilities of VUE through allocating the computational resources to VUE. In this paper, we propose a joint optimization algorithm based on a deep reinforcement learning algorithm named the double deep Q network (double DQN) to minimize the cost constituted of energy consumption, the latency of computation, and communication with the proper policy. The proposed algorithm is more suitable for dynamic scenarios and requires low-latency vehicular scenarios in the real world. Compared with other reinforcement learning algorithms, the algorithm we proposed algorithm improve the performance in terms of convergence, defined cost, and speed by around 30%, 15%, and 17%.
Abstract
The rapid-developing soft robots and wearable devices require flexible conductive materials to maintain electric functions over a large range of deformations. Considerable efforts are made ...to develop stretchable conductive materials; little attention is paid to the frequent failures of integrated circuits caused by the interface mismatch of soft substrates and rigid silicon-based microelectronics. Here, we present a stretchable solder with good weldability that can strongly bond with electronic components, benefiting from the hierarchical assemblies of liquid metal particles, small-molecule modulators, and non-covalently crosslinked polymer matrix. Our self-solder shows high conductivity (>2×10
5
S m
−1
), extreme stretchability (~1000%, and >600% with chip-integrated), and high toughness (~20 MJ m
−3
). Additionally, the dynamic interactions within our solder’s surface and interior enable a range of unique features, including ease of integration, component substitution, and circuit recyclability. With all these features, we demonstrated an application as thermoforming technology for three-dimensional (3D) conformable electronics, showing potential in reducing the complexity of microchip interfacing, as well as scalable fabrication of chip-integrated stretchable circuits and 3D electronics.
Solid-state photochromic materials are very attractive due to their promising future in advanced functional materials with reversible and tunable optical properties. However, the development of ...photochromic material in the solid state, especially in the crystalline state, is still a great challenge due to dense molecular packing. In this study, a solid-state optical switch based on the methanol-esterified spiropyran derivative
S1
is constructed, which exhibits reversible photochromic properties in the solid-state product without further recrystallization. Moreover, the cultured single crystal (
S1-C
) can unexpectedly undergo photochromism at room temperature, which is a very rare example in a neutral spiropyran crystal. The crystallographic analysis reveals that weak van der Waals forces dominate in the crystal of
S1-C
, resulting in a relatively loose packing mode and photochromic properties. Mechanical force can destroy the restricted environment of the crystalline state and allow the
S1
compound to achieve more efficient photochromism. Our study opens up an avenue for relating the molecular structure/packing mode to photochromic properties. Consequently, by utilizing the reversible and efficient photochromic properties, we successfully demonstrate the application of
S1
as optical printing materials.
Solid-state photochromic materials are very attractive due to their promising future in advanced functional materials with reversible and tunable optical properties.
Phototheranostics provide a safe, effective, and noninvasive way for the diagnosis and treatment of contemporary diseases, and organic dyes play a vital role. For example, chemical modification ...endowed dyes with powerful reactive oxygen species or heat generation ability, favoring for photodynamic therapy and photoacoustic (PA) imaging guided photothermal therapy (PTT) of serious diseases. Therefore, photophysical properties manipulation of dyes has become the focus in current dye chemistry research. The development of aggregate science has made great effort to solve this problem. In recent years, a large number of studies have focused on molecular aggregation behavior and its effect on photophysical performance. The most famous example is the discovery of aggregation‐induced emission (AIE) phenomenon. Based on AIE theory, more theories for revealing the relationship between molecular aggregation behavior and photophysical properties were proposed and elucidated. The photophysical property changes caused by dye aggregation have become a unique discipline, guiding the development of molecular science and material science. With the help of molecular self‐assembly, controllable aggregation of dyes can be realized, and stable nano‐theranostic reagents can be obtained. Furthermore, constructing dye assemblies with various photophysical properties will greatly reduce the cost of theranostic reagents, thus, expanding biomedical applications of organic dyes. Therefore, this review focuses on the photophysical characteristic changes caused by dye aggregation and their biological applications including, fluorescence/phosphorescence/PA imaging as well as photodynamic and PTT. This review will provide guidance for the design of organic dyes, the development of controllable aggregation methods, and the construction of multifunctional phototheranostic reagents.
Dye assembly provides a facile and effective way to control the aggregation with desired properties. The photophysical characteristics of dye such as fluorescence/phosphorescence emission, photodynamic, and photothermal abilities are closely related to the aggregation state. Thus, the mechanisms of aggregation‐induced photophysical changes and biomedical applications including bioimaging, photodynamic therapy, and photothermal therapy of organic dye assemblies are summarized.
Review of global sanitation development Zhou, Xiaoqin; Li, Zifu; Zheng, Tianlong ...
Environment international,
November 2018, 2018-11-00, 20181101, 2018-11-01, Letnik:
120
Journal Article
Recenzirano
Odprti dostop
The implementation of the United Nations (UN) Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs) has resulted in an increased focus on developing innovative, sustainable ...sanitation techniques to address the demand for adequate and equitable sanitation in low-income areas. We examined the background, current situation, challenges, and perspectives of global sanitation. We used bibliometric analysis and word cluster analysis to evaluate sanitation research from 1992 to 2016 based on the Science Citation Index EXPANDED (SCI-EXPANDED) and Social Sciences Citation Index (SSCI) databases. Our results show that sanitation is a comprehensive field connected with multiple categories, and the increasing number of publications reflects a strong interest in this research area. Most of the research took place in developed countries, especially the USA, although sanitation problems are more serious in developing countries. Innovations in sanitation techniques may keep susceptible populations from contracting diseases caused by various kinds of contaminants and microorganisms. Hence, the hygienization of human excreta, resource recovery, and removal of micro-pollutants from excreta can serve as effective sustainable solutions. Commercialized technologies, like composting, anaerobic digestion, and storage, are reliable but still face challenges in addressing the links between the political, social, institutional, cultural, and educational aspects of sanitation. Innovative technologies, such as Microbial Fuel Cells (MFCs), Microbial Electrolysis Cells (MECs), and struvite precipitation, are at the TRL (Technology readiness levels) 8 level, meaning that they qualify as “actual systems completed and qualified through test and demonstration.” Solutions that take into consideration economic feasibility and all the different aspects of sanitation are required. There is an urgent demand for holistic solutions considering government support, social acceptability, as well as technological reliability that can be effectively adapted to local conditions.
Display omitted
•Data for sanitation research from year of 1900 to 2016 have been collected and analyzed.•Hotspots for sanitation research have been discussed for future work based on the keywords data.•The constraints for global sanitation have been identified.•Promising technologies have been evaluated and proposed.
Wireless traffic prediction is vital for intelligent cellular network operations, such as load-aware resource management and predictive control. Traditional centralized training addresses this but ...poses issues like excessive data transmission, disregarding delays, and user privacy. Traditional federated learning methods can meet the requirement of jointly training models while protecting the privacy of all parties' data. However, challenges arise when the local data features among participating parties exhibit inconsistency, making the training process difficult to sustain. Our study introduces an innovative framework for wireless traffic prediction based on split learning (SL) and vertical federated learning. Multiple edge clients collaboratively train high-quality prediction models by utilizing diverse traffic data while maintaining the confidentiality of raw data locally. Each participant individually trains dimension-specific prediction models with their respective data, and the outcomes are aggregated through collaboration. A partially global model is formed and shared among clients to address statistical heterogeneity in distributed machine learning. Extensive experiments on real-world datasets demonstrate our method's superiority over current approaches, showcasing its potential for network traffic prediction and accurate forecasting.
Non-holonomic wheeled robots (NWR) comprise a type of robotic system; they use wheels for movement and offer several advantages over other types. They are efficient, highly, and maneuverable, making ...them ideal for factory automation, logistics, transportation, and healthcare. The control of this type of robot is complicated, due to the complexity of modeling, asymmetrical non-holonomic constraints, and unknown perturbations in various applications. Therefore, in this study, a novel type-3 (T3) fuzzy logic system (FLS)-based controller is developed for NWRs. T3-FLSs are employed for modeling, and the modeling errors are considered in stability analysis based on the symmetric Lyapunov function. An observer is designed to detect the error, and its effect is eliminated by a developed terminal sliding mode controller (SMC). The designed technique is used to control a case-study NWR, and the results demonstrate the good accuracy of the developed scheme under non-holonomic constraints, unknown dynamics, and nonlinear disturbances.
The corrosion behavior of a medium-Mn steel in a simulated marine splash zone was studied by a dry–wet cyclic corrosion experiment and electrochemical experiment. The corrosion products were ...characterized by corrosion rate calculation, composition detection, morphology observation, element distribution detection, valence analysis, polarization curve, and electrochemical impedance test. The results show that the corrosion products of the sample mainly include γ-FeOOH, FexOy, MnxOy, and a small amount of (Fe,Mn)xOy, and the valence state of iron compounds and manganese compounds in different corrosion stages changed obviously. In the initial corrosion products, Mn is enriched significantly and facilitates the electrochemical reaction of corrosion process. The content of Ni in the inner rust layer is high. The semi-quantitative analysis of the corrosion product elements shows that the atomic concentrations of Cr and Mo increase significantly in later corrosion products, indicating that the dense isolation layer formed by alloy element compounds in the corroded layer is the main factor to improve the protection ability of the rust layer at the end corrosion stage of the sample. With the corrosion durations, the corrosion current density of the sample with the corrosion product film first increases and then decreases, and the corrosion potential first moves negative and then shifts in a positive direction subsequently, indicating that the protective effect of the corrosion product film is gradually significant.
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