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Solid-state stimuli-responsive materials are attracting increasing attention due to their broad prospects in the field of functional materials, but there are still some challenges. We design and synthesize two efficient solid-state stimuli-responsive materials SP-TPEm (m = 4, 6) based on TPE covalent connection with N-position of spiropyran through different lengths of alkyl spacers. Both of them show aggregation-induced emission behaviors. Efficient solid-state photoswitching between SP-TPEm and their photoisomer MC-TPEm is achieved. Both of the two films show great stimulus-responsive properties, and the characteristic emission peak is at around 460 nm for TPE and 601 nm for MC isomer. Therefore, SP-TPE4 is applied as an anticounterfeiting ink due to its great solid-state photochromic characteristics. In addition, the solid-state films of SP-TPEm are acidochromic responsive. Moreover, the surface wettability of the SP-TPEm films can be adjusted by UV light. Hence, we provide a new strategy for building solid-state multifunctional materials.

Recovering high quality surfaces from noisy point clouds, known as point cloud denoising, is a fundamental yet challenging problem in geometry processing. Most of the existing methods either directly denoise the noisy input or filter raw normals followed by updating point positions. Motivated by the essential interplay between point cloud denoising and normal filtering, we revisit point cloud denoising from a multitask perspective, and propose an end-to-end network, named PCDNF, to denoise point clouds via joint normal filtering. In particular, we introduce an auxiliary normal filtering task to help the overall network remove noise more effectively while preserving geometric features more accurately. In addition to the overall architecture, our network has two novel modules. On one hand, to improve noise removal performance, we design a shape-aware selector to construct the latent tangent space representation of the specific point by comprehensively considering the learned point and normal features and geometry priors. On the other hand, point features are more suitable for describing geometric details, and normal features are more conducive for representing geometric structures (e.g., sharp edges and corners). Combining point and normal features allows us to overcome their weaknesses. Thus, we design a feature refinement module to fuse point and normal features for better recovering geometric information. Extensive evaluations, comparisons, and ablation studies demonstrate that the proposed method outperforms state-of-the-arts for both point cloud denoising and normal filtering.

Additional file 1: Fig. S1. Flow chart of the inclusion and exclusion of study population. Table S1. Pearson correlation coefficient of air pollutants and meteorological variables. Fig. S2. Odds ratios (95% confidence intervals) of acute glaucoma attack per IQR increase in ambient air pollution exposure in two-pollutant model.

Additional file 2: Supplementary Table 2. Missing rate of gender and distribution comparison of age and payer type between missing group and non-missing group.

Additional file 3: Supplementary Table 3. Comparison of demographic characteristics between outpatient and ED visits.

Additional file 1: Supplementary Table 1. The detailed ICD codes for diseases.

Energy storage system (ESS) is an indispensible component for microgrid construction, so exploring its various functions is beneficial to improve the utilization in microgrid. From this point of view, the feasibility using voltage source converter (VSC) based ESS to compensate the harmonic current is discussed at first in this paper. And then based on instantaneous power theory, the harmonic current detection method of ip-iq and the determination of active and reactive currents output by VSC-based ESS are studied respectively. Further, the multi-objective control approach makes VSC-based ESS implement real time harmonic current suppression and improve the dynamic characteristics of both voltage and frequency in microgrid is presented based on grey model GM(1,1) and prediction model of output current of VSC. In the proposed control strategy, the different control time scale of the harmonic current suppression and the comprehensive compensation of both active and reactive powers are taken account into, the effectiveness of the multi-objective control is validated by simulation.

In order to avoid leakage problem caused by liquid electrolyte, a new ionogel electrolyte was developed by in situ immobilizing organosilicon-functionalized ionic liquid within a nanoporous silica matrix. The ionic liquid evenly coats on the surface of porous silica and fills in the silica framework pores with no strong chemical interaction. The ionogel electrolyte has the dual advantages of a silica solid support and a wide electrochemical stability window of ionic liquid (4.87 V vs. Li+/Li). The half-cells assembled with this electrolyte and LiFePO4 electrode have excellent performance at room temperature and 60 °C. The Li/SiO2-IGE/LiFePO4 cell displays a discharge capacity of 129.1 mAh·g−1 after 200 charge/discharge cycles at room temperature.

Dendritic growth of Li metal and its related safety issue in a liquid electrolyte greatly hinder the development of Li metal batteries. Herein, inspired by the Tai Chi philosophy of keeping rigid and flexible balance, we demonstrate a new rigid-flexible hybrid ionogel electrolyte composed of TiO2 rigid framework, PVDF-HFP flexible framework and LiTFSI-Py13TFSI ionic liquid for greatly boosting the performance of Li battery. The as-made hybrid ionogel electrolyte not only has excellent electrochemical properties, such as ionic conductivity up to 7.4 × 10−3 S/cm at 25 °C and anodic stability up to 5.5 V versus Li/Li+, but also has a high mechanical strength to withstand extrusion. These important features make it be able to realize the stable stripping/plating of Li anodes. The hybrid ionogel electrolyte enables the assembled LiFePO4/Li batteries to be successfully cycled at wide C rate (0.1–2.0 C) and exhibit no significant capacity degradation for up to 500 days (about 600 cycles) at a 0.1 C rate. The design from Tai Chi philosophy to protect Li metal opens new opportunities to realize high energy-density Li metal batteries.

Precipitation of harmful substances in the faucets has always been the focus of attention, this experiment selected the four metal elements of Pb/Cu/Ni/Mo as the research object, and studied the precipitation in the faucets which were extracted at the ambient temperature of 20°C, 40°C and 60°C. The results showed that the Pb and Mo precipitation in the faucets increased with the temperature rise, while the Cu and Ni in most samples were the least precipitated at 60°C. Detection found that the metals precipitation among different batches and different samples in the same batch varied widely, mainly affected by the processing technology and the material of faucets.

Trusses are load-carrying light-weight structures consisting of bars connected at joints ubiquitously applied in a variety of engineering scenarios. Designing optimal trusses that satisfy functional specifications with a minimal amount of material has interested both theoreticians and practitioners for more than a century. In this paper, we introduce two main ideas to improve upon the state of the art. First, we formulate an alternating linear programming problem for geometry optimization. Second, we introduce two sets of complementary topological operations, including a novel subdivision scheme for global topology refinement inspired by Michell's famed theoretical study. Based on these two ideas, we build an efficient computational framework for the design of lightweight trusses. \AD{We illustrate our framework with a variety of functional specifications and extensions. We show that our method achieves trusses with smaller volumes and is over two orders of magnitude faster compared with recent state-of-the-art approaches., Comment: 15 pages,34 figures

Over the last few years, traffic data has been exploding and the transportation discipline has entered the era of big data. It brings out new opportunities for doing data-driven analysis, but it also challenges traditional analytic methods. This paper proposes a new Divide and Combine based approach to do K means clustering on activity-travel behavior time series using features that are derived using tools in Time Series Analysis and Topological Data Analysis. Clustering data from five waves of the National Household Travel Survey ranging from 1990 to 2017 suggests that activity-travel patterns of individuals over the last three decades can be grouped into three clusters. Results also provide evidence in support of recent claims about differences in activity-travel patterns of different survey cohorts. The proposed method is generally applicable and is not limited only to activity-travel behavior analysis in transportation studies. Driving behavior, travel mode choice, household vehicle ownership, when being characterized as categorical time series, can all be analyzed using the proposed method.

The study of topology is strictly speaking, a topic in pure mathematics. However in only a few years, Topological Data Analysis (TDA), which refers to methods of utilizing topological features in data (such as connected components, tunnels, voids, etc.) has gained considerable momentum. More recently, TDA is being used to understand time series. This article provides a review of TDA for time series, with examples using R functions. Features derived from TDA are useful in classification and clustering of time series and in detecting breaks in patterns.

The Nd–Fe–B magnets are pre-sintered and then processed with hot-pressing, and the resulting magnets are called the hot-pressed pretreated (HPP) magnets. The coercivity of the HPP magnets increases as the annealed temperature increases. When the annealing temperature is 900 °C, the coercivity of the magnet is only 17.6 kOe (1 Oe = 79.5775 A⋅m–1), but when the annealing temperature rises up to 1060 °C, the coercivity of the magnet reaches 23.53 kOe, which is remarkably increased by 33.7%. The microstructure analysis indicates that the grain surface of the HPP magnet becomes smoother as the annealed temperature increases. The microstructure factor α is changed according to the intrinsic coercivity model formula. The α of the magnet at 900 °C is only 0.578, but it is 0.825 at 1060 °C. Microstructural optimization is due mainly to the increase of coercivity of the HPP magnet.

Fastest-path queries between two points in a very large road map is an increasingly important primitive in modern transportation and navigation systems, thus very efficient computation of these paths is critical for system performance and throughput. We present a method to compute an effective heuristic for the fastest path travel time between two points on a road map, which can be used to significantly accelerate the classical A* algorithm when computing fastest paths. Our method is based on two hierarchical sets of separators of the map represented by two binary trees. A preprocessing step computes a short vector of values per road junction based on the separator trees, which is then stored with the map and used to efficiently compute the heuristic at the online query stage. We demonstrate experimentally that this method scales well to any map size, providing a better quality heuristic, thus more efficient A* search, for fastest path queries between points at all distances - especially small and medium range - relative to other known heuristics.

Given a finitely-connected bounded planar domain $\Omega$, it is possible to define a {\it divergence distance} $D(x,y)$ from $x\in\Omega$ to $y\in\Omega$, which takes into account the complex geometry of the domain. This distance function is based on the concept of $f$-divergence, a distance measure traditionally used to measure the difference between two probability distributions. The relevant probability distributions in our case are the Poisson kernels of the domain at $x$ and at $y$. We prove that for the $\chi^2$-divergence distance, the gradient by $x$ of $D$ is opposite in direction to the gradient by $x$ of $G(x,y)$, the Green's function with pole $y$. Since $G$ is harmonic, this implies that $D$, like $G$, has a single extremum in $\Omega$, namely at $y$ where $D$ vanishes. Thus $D$ can be used to trace a gradient-descent path within~$\Omega$ from $x$ to $y$ by following $\nabla_x D(x,y)$, which has significant computational advantages over tracing the gradient of $G$. This result can be used for robotic path-planning in complex geometric environments., Comment: 7 pages

In the age of real-time online traffic information and GPS-enabled devices, fastest-path computations between two points in a road network modeled as a directed graph, where each directed edge is weighted by a "travel time" value, are becoming a standard feature of many navigation-related applications. To support this, very efficient computation of these paths in very large road networks is critical. Fastest paths may be computed as minimal-cost paths in a weighted directed graph, but traditional minimal-cost path algorithms based on variants of the classic Dijkstra algorithm do not scale well, as in the worst case they may traverse the entire graph. A common improvement, which can dramatically reduce the number of traversed graph vertices, is the A* algorithm, which requires a good heuristic lower bound on the minimal cost. We introduce a simple, but very effective, heuristic function based on a small number of values assigned to each graph vertex. The values are based on graph separators and computed efficiently in a preprocessing stage. We present experimental results demonstrating that our heuristic provides estimates of the minimal cost which are superior to those of other heuristics. Our experiments show that when used in the A* algorithm, this heuristic can reduce the number of vertices traversed by an order of magnitude compared to other heuristics.

Path planning is an important problem in robotics. One way to plan a path between two points $x,y$ within a (not necessarily simply-connected) planar domain $\Omega$, is to define a non-negative distance function $d(x,y)$ on $\Omega\times\Omega$ such that following the (descending) gradient of this distance function traces such a path. This presents two equally important challenges: A mathematical challenge -- to define $d$ such that $d(x,y)$ has a single minimum for any fixed $y$ (and this is when $x=y$), since a local minimum is in effect a "dead end", A computational challenge -- to define $d$ such that it may be computed efficiently. In this paper, given a description of $\Omega$, we show how to assign coordinates to each point of $\Omega$ and define a family of distance functions between points using these coordinates, such that both the mathematical and the computational challenges are met. This is done using the concepts of \emph{harmonic measure} and \emph{$f$-divergences}. In practice, path planning is done on a discrete network defined on a finite set of \emph{sites} sampled from $\Omega$, so any method that works well on the continuous domain must be adapted so that it still works well on the discrete domain. Given a set of sites sampled from $\Omega$, we show how to define a network connecting these sites such that a \emph{greedy routing} algorithm (which is the discrete equivalent of continuous gradient descent) based on the distance function mentioned above is guaranteed to generate a path in the network between any two such sites. In many cases, this network is close to a (desirable) planar graph, especially if the set of sites is dense.

Aprotic Li-CO2 batteries are a new class of green energy storage and conversion system, which can utilize the CO2 from the atmosphere in an environmentally friendly way. However, the biggest problem of the existing Li-CO2 batteries is that they suffer from high polarization and poor cycling performance, mainly caused by the insulating and insoluble discharge product, Li2 CO3 . Herein, this study reports the synthesis of wrinkled, ultrathin Ir nanosheets fully anchored on the surface of N-doped carbon nanofibers (Ir NSs-CNFs) as an efficient cathode for improving the performance of lithium-CO2 batteries. The battery can be steadily discharged and charged at least for 400 cycles with a cut-off capacity of 1000 mAh g-1 at 500 mA g-1 . Meanwhile, the cathode can effectively reduce the charge overpotential by showing a charge termination voltage below 3.8 V at 100 mA g-1 , which is the smallest charge overpotential reported to date. The ex situ analysis of the intermediate products reveals that during the discharge process, Ir NSs-CNFs can greatly stabilize amorphous granular intermediate (probably Li2 C2 O4 ) and delay its further transformation into thin plate-like Li2 CO3 , whereas during the charge process, it can make Li2 CO3 be easily and completely decomposed, which is the key in greatly improving its performance for lithium-CO2 batteries.

Cyclin-dependent kinases (CDKs) 7 and 9 are deregulated in various types of human cancer and are thus viewed as therapeutic targets. Accordingly, small-molecule inhibitors of both CDKs are highly sought-after. Capitalising on our previous discovery of CDKI-73, a potent CDK9 inhibitor, medicinal chemistry optimisation was pursued. A number of N-pyridinylpyrimidin-2-amines were rationally designed, chemically synthesised and biologically assessed. Among them, N-(6-(4-cyclopentylpiperazin-1-yl)pyridin-3-yl)-4-(imidazo[1,2-a]pyrimidin-3-yl)pyrimidin-2-amine was found to be one of the most potent inhibitors of CDKs 7 and 9 as well as the most effective anti-proliferative agent towards multiple human cancer cell lines. The cellular mode of action of this compound was investigated in MV4-11 acute myeloid leukaemia cells, revealing that the compound dampened the kinase activity of cellular CDKs 7 and 9, arrested the cell cycle at sub-G1 phase and induced apoptosis. Refereed/Peer-reviewed