The host–guest chemistry of metal–organic frameworks (MOFs) has enabled the derivation of numerous new functionalities. However, intrinsically chiral MOFs (CMOFs) with helical channels have not been ...used to realize crystalline circularly polarized luminescence (CPL) materials. Herein, enantiomeric pairs of MOF crystals are reported, where achiral fluorophores adhere to the inner surface of helical channels via biology‐like H‐bonds and hence inherit the helicity of the host MOFs, eventually amplifying the luminescence dissymmetry factor (glum) of the host l/d‐CMOF (±1.50 × 10−3) to a maximum of ±0.0115 for the composite l/d‐CMOF⊃fluorophores. l/d‐CMOF⊃fluorophores in pairs generate bright color‐tunable CPL and almost ideal white CPL (0.33, 0.32) with a record‐high photoluminescence quantum yield of ≈30%, which are further assembled into a white circularly polarized light‐emitting diode. The present strategy opens a new avenue for propagating the chirality of MOFs to realize universal chiroptical materials.
Achiral‐aggregation‐caused quenching fluorophores are helically arranged in the chiral channels of enantiomeric metal–organic frameworks (MOFs) for color‐tunable and bright white circularly polarized luminescence (photoluminescence quantum yield (PLQY), ≈33%). The experimental results indicate that the helical arrangement is superior to the ET process in the amplification of the luminescence dissymmetry factor. Also, the MOF‐based composites are assembled into a bright white circularly polarized light‐emitting diode (PLQY, ≈30%).
With the increasing number of urban vehicles, as well as the current situation of non-intelligent traffic control systems, spatiotemporal non-uniform traffic resource occupation, and limited traffic ...planning and design, existing urban traffic planning methods cannot effectively solve problems such as frequent traffic congestion and uncontrollable commuting time for residents. In order to solve the above problems, this paper first constructs a multi-queue, multi-server queuing model based on the server vacation and a multi-hop cascaded queuing model from the perspective of local intersections and global commuting paths. We analyze the theoretical changes in passage delay costs at local intersections and on global commuting paths as a function of traffic flow and the random duration of traffic signals. On this basis, this article proposes a collaborative intelligent traffic planning algorithm based on artificial intelligence, which utilizes traffic sensors to dynamically perceive traffic congestion status and collaboratively plans the optimal duration of traffic signals and the optimal driving path of vehicles from both local and global perspectives, thereby maximizing the on-time arrival ratio of vehicles while ensuring the required commuting delay. The simulation results show that the proposed method can increase the on-time arrival ratio of vehicles by at least 20% compared to contrast methods while meeting the requirements relating to commuting delays. This verifies that our method can provide support for the improvement in efficiency in future Internet of vehicles.
In this work, the consensus problem of multi‐agent systems is addressed whose agent dynamics are described by the switched linear system, and the interaction topology is a directed graph. Two cases ...are considered: For completely controllable agent dynamics, a novel construct method of control law and switching signal are proposed to derive sufficient conditions to solve the finite‐time consensus problem. When the controllability of the agent system is incomplete, it is proven that the uncontrollable sub‐mode of agent dynamics is consistently asymptotically stabilizable is a key condition to achieve consistency for multi‐agent systems. Finally, numerical examples are provided to demonstrate the effectiveness of the theoretical results obtained in this paper.
We proposed a new method to design control input and switching signals. And proved that, multi‐agent systems can achieve consensus if the uncontrollable sub‐mode is consistently stabilizable and all nonzero eigenvalues of the Laplace matrix of the communication topology are equal. And a completely controllable multi‐agent system can achieve finite‐time consensus, and the time is less than n(n+1)/2τ(N−1)$n(n+1)/2 \tau (N-1)$.
We numerically solve the (2+1)-dimensional effective kinetic theory of weak coupling QCD under longitudinal expansion, relevant for early stages of heavy-ion collisions. We find agreement with ...viscous hydrodynamics and classical Yang-Mills simulations in the regimes where they are applicable. By choosing initial conditions that are motivated by a color-glass-condensate framework, we find that for Q_{s}=2 GeV and α_{s}=0.3 the system is approximately described by viscous hydrodynamics well before τ≲1.0 fm/c.
•A new model based on LSTM is developed for predicting water table depth.•Only a very simple data pre-processing method is required in our proposed model.•The dropout strategy is adopted to prevent ...over-fitting significantly.•Our model shows superiority over the classic FFNN and the Double-LSTM models.
Predicting water table depth over the long-term in agricultural areas presents great challenges because these areas have complex and heterogeneous hydrogeological characteristics, boundary conditions, and human activities; also, nonlinear interactions occur among these factors. Therefore, a new time series model based on Long Short-Term Memory (LSTM), was developed in this study as an alternative to computationally expensive physical models. The proposed model is composed of an LSTM layer with another fully connected layer on top of it, with a dropout method applied in the first LSTM layer. In this study, the proposed model was applied and evaluated in five sub-areas of Hetao Irrigation District in arid northwestern China using data of 14 years (2000–2013). The proposed model uses monthly water diversion, evaporation, precipitation, temperature, and time as input data to predict water table depth. A simple but effective standardization method was employed to pre-process data to ensure data on the same scale. 14 years of data are separated into two sets: training set (2000–2011) and validation set (2012–2013) in the experiment. As expected, the proposed model achieves higher R2 scores (0.789–0.952) in water table depth prediction, when compared with the results of traditional feed-forward neural network (FFNN), which only reaches relatively low R2 scores (0.004–0.495), proving that the proposed model can preserve and learn previous information well. Furthermore, the validity of the dropout method and the proposed model’s architecture are discussed. Through experimentation, the results show that the dropout method can prevent overfitting significantly. In addition, comparisons between the R2 scores of the proposed model and Double-LSTM model (R2 scores range from 0.170 to 0.864), further prove that the proposed model’s architecture is reasonable and can contribute to a strong learning ability on time series data. Thus, one can conclude that the proposed model can serve as an alternative approach predicting water table depth, especially in areas where hydrogeological data are difficult to obtain.
Considering the ever‐growing climatic degeneration, sustainable and renewable energy sources are needed to be effectively integrated into the grid through large‐scale electrochemical energy storage ...and conversion (EESC) technologies. With regard to their competent benefit in cost and sustainable supply of resource, room‐temperature sodium‐ion batteries (SIBs) have shown great promise in EESC, triumphing over other battery systems on the market. As one of the most fascinating cathode materials due to the simple synthesis process, large specific capacity, and high ionic conductivity, Na‐based layered transition metal oxide cathodes commonly suffer from the sluggish kinetics, multiphase evolution, poor air stability, and insufficient comprehensive performance, restricting their commercialization application. Here, this review summarizes the recent advances in layered oxide cathode materials for SIBs through different optimal structure modulation technologies, with an emphasis placed on strategies to boost Na+ kinetics and reduce the irreversible phase transition as well as enhance the store stability. Meanwhile, a thorough and in‐depth systematical investigation of the structure–function–property relationship is also discussed, and the challenges as well as opportunities for practical application electrode materials are sketched. The insights brought forward in this review can be considered as a guide for SIBs in next‐generation EESC.
The recent research progress of structure modulation technology on layered transition metal oxide cathodes for sodium‐ion batteries is summarized, concentrating especially on morphology design, coating technology, phase transition, ordering‐disordering, air stability, and composite structure to boost Na+ kinetics, suppress the irreversible phase transition, enhance the storage stability, improve the overall performance, and further realize sodium‐ion battery commercialization for market applications.
In the past few decades, coronaviruses have risen as a global threat to public health. Currently, the outbreak of coronavirus disease‐19 (COVID‐19) from Wuhan caused a worldwide panic. There are no ...specific antiviral therapies for COVID‐19. However, there are agents that were used during the severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) epidemics. We could learn from SARS and MERS. Lopinavir (LPV) is an effective agent that inhibits the protease activity of coronavirus. In this review, we discuss the literature on the efficacy of LPV in vitro and in vivo, especially in patients with SARS and MERS, so that we might clarify the potential for the use of LPV in patients with COVID‐19.
Highlights
LPV is an effective agent inhibiting coronavirus in vitro and animal studies.
The treatment of LPV improved outcomes of SARS and MERS patients.
LPV may be a potential treatment option for COVID‐19.
Sorafenib is an oral multikinase inhibitor that suppresses tumor cell proliferation and angiogenesis and promotes tumor cell apoptosis It was approved by the FDA for the treatment of advanced renal ...cell carcinoma in 2006, and as a unique target drug for advanced hepatocellular carcinoma （HCC） in 2007. Sorafenib can significantly extend the median survival time of patients but only by 3-5 months. Moreover, it is associated with serious adverse side effects, and drug resistance often develops. Therefore, it is of great importance to explore the mechanisms underlying sorafenib resistance and to develop individualized therapeutic strategies for coping with these problems. Recent studies to the primary resistance, mechanisms are underying the acquired resistance to sorafenib, such as crosstalk involving PI3K/Akt and JAK-STAT pathways, the activation of hypoxia-inducible pathways, and epithelial-mesenchymal transition. Here, we briefly describe the function of sorafenib, its clinical application, and the molecular mechanisms for drug resistance, especially for HCC patients.
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input image to output image, but ...also learn a loss function to train this mapping. This makes it possible to apply the same generic approach to problems that traditionally would require very different loss formulations. We demonstrate that this approach is effective at synthesizing photos from label maps, reconstructing objects from edge maps, and colorizing images, among other tasks. Moreover, since the release of the pi×2pi× software associated with this paper, hundreds of twitter users have posted their own artistic experiments using our system. As a community, we no longer hand-engineer our mapping functions, and this work suggests we can achieve reasonable results without handengineering our loss functions either.
It is still very urgent and challenging to simultaneously develop high‐rate and long‐cycle oxide cathodes for sodium‐ion batteries (SIBs) because of the sluggish kinetics and complex multiphase ...evolution during cycling. Here, the concept of accurately manipulating structural evolution and formulating high‐performance heterostructured biphasic layered oxide cathodes by local chemistry and orbital hybridization modulation is reported. The P2‐structure stoichiometric composition of the cathode material shows a layered P2‐ and O3‐type heterostructure that is explicitly evidenced by various macroscale and atomic‐scale techniques. Surprisingly, the heterostructured cathode displays excellent rate performance, remarkable cycling stability (capacity retention of 82.16% after 600 cycles at 2 C), and outstanding compatibility with hard carbon anode because of the integrated advantages of intergrowth structure and local environment regulation. Meanwhile, the formation process from precursors during calcination and the highly reversible dynamic structural evolution during the Na+ intercalation/deintercalation process are clearly articulated by a series of in situ characterization techniques. Also, the intrinsic structural properties and corresponding electrochemical behavior are further elucidated by the density of states and electron localization function of density functional theory calculations. Overall, this strategy, which finely tunes the local chemistry and orbitals hybridization for high‐performance SIBs, will open up a new field for other materials.
An abnormal heterostructured biphasic layered oxide cathode for sodium‐ion batteries (SIBs) is successfully constructed, and its dynamic formation process, intrinsic structural properties, and electrochemical behavior are elucidated by a series of in situ characterization techniques and density functional theory calculations. The concept of accurately manipulating structural evolution and formulating heterostructured cathode materials by local chemistry and orbital hybridization modulation is further demonstrated.
PDF
