A point-feature label placement algorithm based on spatial data mining

The point-feature label placement (PFLP) refers to the process of positioning labels near point features on a map while adhering to specific rules and guidelines, finally obtaining clear, aesthetically pleasing, and conflict-free maps. While various approaches have been suggested for automated point feature placement on maps, few studies have fully considered the spatial distribution characteristics and label correlations of point datasets, resulting in poor label quality in the process of solving the label placement of dense and complex point datasets. In this paper, we propose a point-feature label placement algorithm based on spatial data mining that analyzes the local spatial distribution characteristics and label correlations of point features. The algorithm quantifies the interference among point features by designing a label frequent pattern framework (LFPF) and constructs an ascending label ordering method based on the pattern to reduce interference. Besides, three classical metaheuristic algorithms (simulated annealing algorithm, genetic algorithm, and ant colony algorithm) are applied to the PFLP in combination with the framework to verify the validity of this framework. Additionally, a bit-based grid spatial index is proposed to reduce cache memory and consumption time in conflict detection. The performance of the experiments is tested with 4000, 10000, and 20000 points of POI data obtained randomly under various label densities. The results of these experiments showed that: (1) the proposed method outperformed both the original algorithm and recent literature, with label quality improvements ranging from 3 to 6.7 and from 0.1 to 2.6, respectively. (2) The label efficiency was improved by 58.2% compared with the traditional grid index

Spatial-temporal diffusion model of aggregated infectious diseases based on population life characteristics: a case study of COVID-19

Outbreaks of infectious diseases pose significant threats to human life, and countries around the world need to implement more precise prevention and control measures to contain the spread of viruses. In this study, we propose a spatial-temporal diffusion model of infectious diseases under a discrete grid, based on the time series prediction of infectious diseases, to model the diffusion process of viruses in population. This model uses the estimated outbreak origin as the center of transmission, employing a tree-like structure of daily human travel to generalize the process of viral spread within the population. By incorporating diverse data, it simulates the congregation of people, thus quantifying the flow weights between grids for population movement. The model is validated with some Chinese cities with COVID-19 outbreaks, and the results show that the outbreak point estimation method could better estimate the virus transmission center of the epidemic. The estimated location of the outbreak point in Xi'an was only 0.965 km different from the actual one, and the results were more satisfactory. The spatiotemporal diffusion model for infectious diseases simulates daily newly infected areas, which effectively cover the actual patient infection zones on the same day. During the mid-stage of viral transmission, the coverage rate can increase to over 90%, compared to related research, this method has improved simulation accuracy by approximately 18%. This study can provide technical support for epidemic prevention and control, and assist decision-makers in developing more scientific and efficient epidemic prevention and control policies

Overview of the Research Progress in the Earth Tessellation Grid

By analyzing the related literatures on the earth tessellation grid (ETG) in recent 10 years, the research achievements in this field are systematic reviewed in four aspects, i.e. the earth subdivision modeling (include quadrangle subdivision, equal-area subdivision and 3D subdivision), encoding computation (include hierarchical encoding computation, filling curve encoding computation and integer coordinate encoding computation), grid quality assessment (include evaluation criteria, evaluation factors, and propagation trend in diffferent levels) and typical applications (include government agency applications,business software applications and industry applications). The structural characteristics, applicable models and their shortcomings in the different grid models are given in details. Finally, some advanced academic problems in the ETG are given based on the completeness of basic theory, the efficiency of grid computing, and the reliability of grid quality

The application of freestanding titanate nanofiber paper for scattering layers in dye-sensitized solar cells

International Cooperation MOST-JST [2010DFA61410]; National Basic Research Program of China (973 Program) [2007CB607504]A titanate nanofiber paper with robust and good flexible property was successfully prepared by alkali hydrothermal synthesis with simple paper-making method. These nanofibers were about 80 nm in diameter and had a typical length in the range of tens of micrometers. Despite the transformation from titanate to TiO(2)-B phase was initially started, such nanofiber paper still kept its original shape and good flexibility after calcinations at 450 degrees C for 30 min. A solar cell with titanate nanofiber paper as scattering layer yielded an overall conversion efficiency of 4.90% under an incident solar energy of 100 mW/cm(2), about 27.5% higher than that without nanofiber paper. (C) 2011 Elsevier B.V. All rights reserved

Multilayer amnion-PCL nanofibrous membrane loaded with celecoxib exerts a therapeutic effect against tendon adhesion by improving the inflammatory microenvironment

Tendon adhesion is a common complication after tendon surgery. The inflammatory phase of tendon healing is characterized by the release of a large number of inflammatory factors, whose mediated excessive inflammatory response is an important cause of tendon adhesion formation. Nonsteroidal anti-inflammatory drugs(NSAIDs) were used to prevent tendon adhesions by reducing the inflammatory response. However, recent studies have shown that the NSAIDs partially impairs tendon healing. Therefore, optimizing the anti-adhesive membrane loaded with NSAIDs to mitigate the effects on tendon healing requires further in-depth study. Amniotic membranes(AM) are natural polymeric semi-permeable membranes from living organisms that are rich in matrix, growth factors, and other active ingredients. In this study, we used electrostatic spinning technology to construct multifunctional nanofiber membranes of the PCL membrane loaded with celecoxib and AM. In vitro cellular assays revealed that celecoxib-loaded PCL membranes significantly inhibited the adhesion and proliferation of fibroblasts with increasing concentrations of celecoxib. In a rabbit tendon repair model, biomechanical tests further confirmed that the PCL membrane loaded with celecoxib had better anti-adhesion effects. Further experimental studies revealed that the PCL/AM membrane improved the inflammatory microenvironment by downregulating the expression of pro-inflammatory factors such as COX-2, IL-1β, and TNF-α proteins; and inhibiting the synthesis of COL I and COL Ⅲ. The PCL/AM membrane can continuously release celecoxib to reduce the inflammatory response and deliver growth factors to the damaged area to build a suitable microenvironment for tendon repair, which provides a new direction to improve the repair efficiency of tendon

Test methods for investigation of reusable launch vehicle materials under severe environment

Ceramic matrix composite (CMC) integrated with various advanced properties is a promising material in many space projects. In those applications, CMC will be subjected to various extreme environments with temperature range of − 170 to 2000 ∘C as well as space particles. A series of methods have been developed to simulate different stage of severe environment, i.e., launching stage, staying stage and re-entry stage. C/SiC related materials have been investigated by these simulation methods. A lot of useful information obtained by the series of simulation methods have been remarkably enhanced our understanding on the behavior of CMC used for RLV hot structures

The influence of nitric acid on electron transport and recombination for non-sintering Tio(2) photoanodes

National High Technology Research and Development Program of China (863 Program) [2011AA050522]; Qinghai Science & Technology Department [2010-N-S03]; Ministry of Science & Technology (MOST) of China [2010DFB23160]Nitric acid was added to binder-free TiO2 paste for the preparation of plastic TiO2 dye-sensitized photoanode at low temperature on conductive indium-tin oxide (ITO)-coated polyethylene naphthalate (PEN) substrate. The influence of nitric acid on the electron transport within the cells was scrutinized. It was found that the electron transport was accelerated by means of increasing nitric acid contents. Rheological behavior testing revealed that the increasing concentration of nitric acid leaded to a decrease of viscosity of the paste and then increased the coordination number within the photoanode, which represent the possible electron transfer pathways in the photoanode. This was confirmed by scanning electronic microscopy (SEM) results. Electrochemical impedance spectroscopy (EIS) results showed that the charge transport resistance in the TiO2 film (R-t) decreased gradually when the nitric acid content increased from 0 to 0.1 M, which was attributed to the increasing coordination number of TiO2 particles in the nanoporous film. Meanwhile, the increasing NO3- will prohibit the electron recombination between TiO2 and electrolyte proved by EIS measurements. However, excessive nitric acid also leaded to a corrosion of the ITO substrate and impaired the photovoltaic performance of the flexible devices. Hence, the devices prepared with nitric acid content of 0.025 M achieved the highest overall energy conversion efficiency of 5.30%. (C) 2012 Elsevier Ltd. All rights reserved

The influence of nitric acid on electron transport and recombination for non-sintering Tio2 photoanodes

Nitric acid was added to binder-free TiO2 paste for the preparation of plastic TiO2 dye-sensitized photoanode at low temperature on conductive indium-tin oxide (ITO)-coated polyethylene naphthalate (PEN) substrate. The influence of nitric acid on the electron transport within the cells was scrutinized. It was found that the electron transport was accelerated by means of increasing nitric acid contents. Rheological behavior testing revealed that the increasing concentration of nitric acid leaded to a decrease of viscosity of the paste and then increased the coordination number within the photoanode, which represent the possible electron transfer pathways in the photoanode. This was confirmed by scanning electronic microscopy (SEM) results. Electrochemical impedance spectroscopy (EIS) results showed that the charge transport resistance in the TiO2 film (Rt) decreased gradually when the nitric acid content increased from 0 to 0.1 M, which was attributed to the increasing coordination number of TiO2 particles in the nanoporous film. Meanwhile, the increasing NO3 - will prohibit the electron recombination between TiO2 and electrolyte proved by EIS measurements. However, excessive nitric acid also leaded to a corrosion of the ITO substrate and impaired the photovoltaic performance of the flexible devices. Hence, the devices prepared with nitric acid content of 0.025 M achieved the highest overall energy conversion efficiency of 5.30%. 漏 2012 Elsevier Ltd. All rights reserved

An adaptive decision‐making approach for transmission expansion planning considering risk assessment of renewable energy extreme scenarios

Abstract The extreme power output scenarios of renewable energy sources (RES) proposed new challenges to the safe and stable operation of the power system. Transmission expansion planning (TEP) with large‐scale RES grid integration needs considering the risk of extreme scenarios. In this paper, an adaptive decision‐making approach for the TEP problem based on planning‐risk assessment‐replanning iterative process is proposed. The method obtains massive temporal and spatial correlated wind‐photovoltaic (PV) power output scenarios by generalizing the historical data to describe the uncertainties. A data‐driven load loss risk assessment model (RAM) based on the power system's actual operating state is built, referring to the degree of extreme scenario risks on the balance of supply and demand, and the probability of extreme scenario occurrence. The planning decision is progressively revised according to the risk assessment result. The Garver's 6‐bus system and the IEEE RTS 24‐bus system are adopted as simulation cases. The results show that the optimal expansion plans achieve a balance between the economy and robustness, which verifies the effectiveness of the proposed method